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Bioinformatics and Biology Insights
Journal Prestige (SJR): 1.141  Citation Impact (citeScore): 2 Number of Followers: 13  Open Access journalISSN (Print) 1177-9322 Published by Sage Publications  [1176 journals]
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- MicroRNAs Regulate Tumorigenesis by Downregulating SOCS3 Expression: An In
silico Approach
Authors: Sura Al-Asadi, Hiba Mansour, Ahmed Jwaid Ataimish, Rusul Al-Kahachi, Jamila Rampurawala
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Tumor microenvironment is characterized by the occurrence of significant changes due to disrupted signaling pathways that affect a broad spectrum of cellular activities such as proliferation, differentiation, signaling, invasiveness, migration, and apoptosis. Similarly, a downregulated suppressor of cytokine signaling 3 (SOCS3) promotes increased JAK/STAT function due to aberrant cytokine signaling, which results in increased cell proliferation, differentiation, and migration. Multiple carcinomas including breast cancer, prostate cancer, hepatocellular carcinoma, pancreatic cancer, and colorectal cancer involve the disruption of SOCS3 expression due to microRNA overexpression. MicroRNAs are small, conserved, and non-coding RNA molecules that regulate gene expression through post-transcriptional inhibition and mRNA destabilization. The aim of this study was to identify putative microRNAs that interact with SOCS3 and downregulate its expression. In this study, miRWalk, TargetScan, and miRDB were used to identify microRNAs that interact with SOCS3, whereas RNA22 was utilized to identify the binding sites of 238 significant microRNAs. The tertiary structures of shortlisted microRNAs and SOCS3 regions were predicted through MC Sym and RNAComposer, respectively. For molecular docking, HDOCK was used, which predicted 80 microRNA-messengerRNA complexes and the interactions of the top 5 shortlisted complexes were assessed. The complexes were shortlisted on the basis of least binding affinity score and maximum confidence score. This study identifies the interactions of known (miR-203a-5p) and novel (miR-6756-5p, miR-6732-5p, miR-1203, miR-6887-5p) microRNAs with SOCS3 regions due to their maximum interactions. Identifying the interactions of these microRNAs with SOCS3 will significantly advance the understanding of oncomiRs (miRNAs that are associated with cancer development) in tumor development due to their influence on SOCS3 expression. These insights will assist in future studies to understand the significance of miRNA-SOCS3-associated tumor development and progression.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-09-09T10:23:55Z
DOI: 10.1177/11779322231193535
Issue No: Vol. 17 (2023)
- Genomic Characterization of Endosymbiotic Bacteria Associated With
Helicoverpa armigera in Iran Using Next-Generation Sequencing
Authors: Parinaz Sheibani, Manizheh Jamshidi, Reza Khakvar, Sevil Nematollahi
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Several species of the Helicoverpa genus have been recognized as major agricultural pests from different regions of the world, among which Helicoverpa armigera species has been reported as the most destructive and cosmopolitan species in most regions of the world, including Iran. This pest is a polyphagous species and can cause damage to more than 120 plant species. Studying the internal microbiome of pests is very important in identifying species’ weaknesses and natural enemies and potential biological control agents. For genomic characterization of the microbial community associated with H armigera, the whole genome of insect larvae collected from vegetable fields in the northwest of Iran was sequenced using next-generation sequencing Illumina platform. Finally, about 2 GB of raw data were obtained. Using the MetaPhlAn2 pipeline, it was predicted that 2 endosymbiont bacterial species including Buchnera aphidicola and Serratia symbiotica were associated with H armigera. Alignment of reference strains sequences related to both endosymbiotic bacteria with raw data and subsequently, assembly analyses resulted in 2 genomes with 657 623 bp length with GC content of 27.4% for B aphidicola and 1 595 135 bp length with GC content of 42.90% for S symbiotica. This research is the first report on the association of B aphidicola and S symbiotica as endosymbiotic bacteria with H armigera worldwide.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-08-24T06:18:37Z
DOI: 10.1177/11779322231195457
Issue No: Vol. 17 (2023)
- Structural-Based Virtual Screening of FDA-Approved Drugs Repository for
NSP16 Inhibitors, Essential for SARS-COV-2 Invasion Into Host Cells:
Elucidation From MM/PBSA Calculation
Authors: Subodh Kumar, Harvinder Singh, Manisha Prajapat, Phulen Sarma, Anusuya Bhattacharyya, Hardeep Kaur, Gurjeet Kaur, Nishant Shekhar, Karanveer Kaushal, Kalpna Kumari, Seema Bansal, Saniya Mahendiratta, Arushi Chauhan, Ashutosh Singh, Rahul Soloman Singh, Saurabh Sharma, Prasad Thota, Pramod Avti, Ajay Prakash, Anurag Kuhad, Bikash Medhi
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
NSP16 is one of the structural proteins of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) necessary for its entrance to the host cells. It exhibits 2’O-methyl-transferase (2’O-MTase) activity of NSP16 using methyl group from S-adenosyl methionine (SAM) by methylating the 5-end of virally encoded mRNAs and shields viral RNA, and also controls its replication as well as infection. In the present study, we used in silico approaches of drug repurposing to target and inhibit the SAM binding site in NSP16 using Food and Drug Administration (FDA)-approved small molecules set from Drug Bank database. Among the 2 456 FDA-approved molecules, framycetin, paromomycin, and amikacin were found to be significant binders against the SAM binding cryptic pocket of NSP16 with docking score of –13.708, –14.997 and –15.841 kcal/mol, respectively. Classical molecular dynamics (MD) simulation and molecular mechanics Poisson−Boltzmann surface area (MM/PBSA)-based binding free energy calculation depicted that all these three framycetin, paromomycin, and amikacin might be promising therapeutic leads towards SARS-CoV-2 infections via host immune escape inhibition pathway.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-07-31T11:07:15Z
DOI: 10.1177/11779322231171777
Issue No: Vol. 17 (2023)
- Antibacterial Activity of Economically Important Medicinal Plants in
Pakistan Against Different Bacterial Strains
Authors: Adil Ali, Muhammad Ali, Zonaira Nisar, Syed Muhammad Ali Shah, Imtiaz Mustafa, Jaweria Nisar, Rizwan Asif
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The emergence of medication resistance and unfavorable side effects from existing antibiotics has prompted the quest for novel antimicrobial agents over the last 2 decades. Plant extracts have been shown to have antibacterial effects in numerous studies. The objective of this study was the evaluation of the antibacterial effect of economically important medicinal plants found in Pakistan. Onosma bracteatum (flowers and leaves), Viola odorata (flowers and leaves), Cuscuta reflexa (whole plant), Swertia chirata (whole plant), and Fagonia arabica (whole plant) were used against Bacillus subtilis, Escherichia coli, and Pseudomonas aeruginosa. Water and ethanol extracts were obtained from different parts of the plants. To evaluate the antibacterial effect of these plants, qualitative assay agar well diffusion method was performed. The minimum inhibitory concentration (MIC) was determined by the broth micro dilution method. Results revealed that the highest inhibition zone (18 mm) was shown by ethanol extract of V odorata flower against P aeruginosa. Ethanol extract of C reflexa plants is best for all 3 tested microbes (P aeruginosa, B subtilis, and E coli). The results concluded that all these plants have abilities to fight against these tested bacteria. Ethanol extract of V odorata flower has the highest activity against P aeruginosa.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-07-31T08:36:42Z
DOI: 10.1177/11779322231189374
Issue No: Vol. 17 (2023)
- Insights into Omicron’s Low Fusogenicity through In Silico Molecular
Studies on Spike-Furin Interactions
Authors: Spencer Mark Mondol, Md Hasib, Md. Belayet Hasan Limon, A S M Rubayet Ul Alam
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant and its subvariants have a unique set of mutations. Two of those mutations (N679 K and P681 H) reside close to the S1 /S2 furin cleavage site (FCS; 685-686). When these mutations reside together, they exert less-efficient membrane fusion than wild type and most other variants of concern such as the Delta variant. Here, we in silico targeted these mutations to find out which of the amino acids and interactions change plays the key role in fusion. To comprehend the epistatic effect of N679 K and P681 H mutations on the spike protein, we in silico constructed three types of spike protein sequences by changing the respective amino acids on 679 and 681 positions (P681 H, N679 K, K679 N-H681 P variants). We then analyzed the binding affinity of furin and spike (Furin-Wild, Furin-Omicron, Furin-P681 H, Furin-N679 K, and Furin-K679 N/H681 P) complexes. Omicron and P681 H variants showed a similar higher binding energy trend compared to the wild type and N679 K. The variation in hydrogen, hydrophobic, and salt bridge bonds between spike protein and furin provided an explanation for the observed low fusogenicity of Omicron. The fate of the epistasis in furin binding and possible cleavage depends on the efficient interaction between FCS in spike and furin catalytic triad, and in addition, the loss of the hydrogen bond between Arg 681 (spike) and Asn 295 (furin) along with inhibitor-like ineffective higher affinity plays an important role in the enzymatic activity.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-07-28T11:22:50Z
DOI: 10.1177/11779322231189371
Issue No: Vol. 17 (2023)
- Identification and Interaction Analysis of Molecular Markers in Pancreatic
Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing
Data Analysis
Authors: Muttanagouda Giriyappagoudar, Basavaraj Vastrad, Rajeshwari Horakeri, Chanabasayya Vastrad
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Background:Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular mechanism of PDAC through integrated bioinformatics analysis.Methods:To identify the candidate genes in the carcinogenesis and progression of PDAC, next-generation sequencing (NGS) data set GSE133684 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and Gene Ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using Integrated Interactions Database (IID) interactome database and Cytoscape. Subsequently, miRNA-DEG regulatory network and TF-DEG regulatory network were constructed using miRNet database, NetworkAnalyst database, and Cytoscape software. The expression levels of hub genes were validated based on Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis.Results:A total of 463 DEGs were identified, consisting of 232 upregulated genes and 233 downregulated genes. The enriched GO terms and pathways of the DEGs include vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis, and adaptive immune system. Four hub genes (namely, cathepsin B [CCNB1], four-and-a-half LIM domains 2 (FHL2), major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) and tubulin beta 1 class VI (TUBB1)) were obtained via taking interaction of different analysis results.Conclusions:On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of PDAC and provide potential targets for further investigation.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-07-25T08:59:10Z
DOI: 10.1177/11779322231186719
Issue No: Vol. 17 (2023)
- SARS-CoV-2 Spike Protein Mutations in Different Variants: A Comparison
Between Vaccinated and Unvaccinated Population in Western Amazonia
Authors: Gabriella Sgorlon, Tárcio Peixoto Roca, Ana Maisa Passos-Silva, Márlon Grégori Flores Custódio, Jackson Alves da Silva Queiroz, André Luiz Ferreira da Silva, Karolaine Santos Teixeira, Flávia Serrano Batista, Juan Miguel Villalobos Salcedo, Rita de Cassia P. Rampazzo, Felipe Gomes Naveca, Deusilene Vieira
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The increased transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated variants of concern (VOCs) throughout the pandemic, responsible for waves of cases worldwide. To monitor mutations in the S gene of SARS-CoV-2 in different variants, we evaluated 1497 individuals with COVID-19 in western Amazonia in the period April 2021 to July 2022. The epidemiological and clinical data of the individuals were collected; subsequently, the samples were extracted using a commercial kit, the viral load was assessed, and viral genomes were sequenced. We analyzed the quality and mutations of the genomes and maximum likelihood phylogenetic inference. However, 3 main clusters were observed, referring to Gamma (52.91%), Delta (24.38%), and Omicron (20.38%) VOCs with wide distribution in all health regions of the Rondônia state. Regarding the vaccination profile, there was a higher percentage of unvaccinated and partially vaccinated individuals, with more representatives by the Gamma variant. A total of 1412 sequences were suitable for mutation analysis in the S gene region. The Omicron VOC showed 38 mutations, with the Delta and Gamma variants with 16 and 17, respectively. The VOC Omicron and Gamma shared 4 mutations E484K, H655Y, N501Y, and N679K with high frequency, and Delta and Omicron 2 mutations (T478K and T95I). Regarding the comparison between the frequency of mutations for each variant concerning the vaccination groups, there were no changes in mutations for each group. In conclusion, the study showed a temporal increase in mutations and subvariants for characterized strains. Furthermore, the vaccination profile did not impact significant changes in the mutational profile yet remains a determining factor for severe disease.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-07-15T05:04:54Z
DOI: 10.1177/11779322231186477
Issue No: Vol. 17 (2023)
- Molecular Biomarker Identification Using a Network-Based Bioinformatics
Approach That Links COVID-19 With Smoking
Authors: Md Anisur Rahman, Md Al Amin, Most Nilufa Yeasmin, Md Zahidul Islam
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The COVID-19 coronavirus, which primarily affects the lungs, is the source of the disease known as SARS-CoV-2. According to “Smoking and COVID-19: a scoping review,” about 32% of smokers had a severe case of COVID-19 pneumonia at their admission time and 15% of non-smokers had this case of COVID-19 pneumonia. We were able to determine which genes were expressed differently in each group by comparing the expression of gene transcriptomic datasets of COVID-19 patients, smokers, and healthy controls. In all, 37 dysregulated genes are common in COVID-19 patients and smokers, according to our analysis. We have applied all important methods namely protein-protein interaction, hub-protein interaction, drug-protein interaction, tf-gene interaction, and gene-MiRNA interaction of bioinformatics to analyze to understand deeply the connection between both smoking and COVID-19 severity. We have also analyzed Pathways and Gene Ontology where 5 significant signaling pathways were validated with previous literature. Also, we verified 7 hub-proteins, and finally, we validated a total of 7 drugs with the previous study.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-07-15T05:01:33Z
DOI: 10.1177/11779322231186481
Issue No: Vol. 17 (2023)
- In Silico Functional Characterization of a Hypothetical Protein From
Pasteurella Multocida Reveals a Novel S-Adenosylmethionine-Dependent
Methyltransferase Activity
Authors: Md. Habib Ullah Masum, Sultana Rajia, Uditi Paul Bristi, Mir Salma Akter, Mohammad Ruhul Amin, Tushar Ahmed Shishir, Jannatul Ferdous, Firoz Ahmed, Md. Mizanur Rahaman, Otun Saha
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Genomes may now be sequenced in a matter of weeks, leading to an influx of “hypothetical” proteins (HP) whose activities remain a mystery in GenBank. The information included inside these genes has quickly grown in prominence. Thus, we selected to look closely at the structure and function of an HP (AFF25514.1; 246 residues) from Pasteurella multocida (PM) subsp. multocida str. HN06. Possible insights into bacterial adaptation to new environments and metabolic changes might be gained by studying the functions of this protein. The PM HN06 2293 gene encodes an alkaline cytoplasmic protein with a molecular weight of 28352.60 Da, an isoelectric point (pI) of 9.18, and an overall average hydropathicity of around −0.565. One of its functional domains, tRNA (adenine (37)-N6)-methyltransferase TrmO, is a S-adenosylmethionine (SAM)-dependent methyltransferase (MTase), suggesting that it belongs to the Class VIII SAM-dependent MTase family. The tertiary structures represented by HHpred and I-TASSER models were found to be flawless. We predicted the model’s active site using the Computed Atlas of Surface Topography of Proteins (CASTp) and FTSite servers, and then displayed it in 3 dimensional (3D) using PyMOL and BIOVIA Discovery Studio. Based on molecular docking (MD) results, we know that HP interacts with SAM and S-adenosylhomocysteine (SAH), 2 crucial metabolites in the tRNA methylation process, with binding affinities of 7.4 and 7.5 kcal/mol, respectively. Molecular dynamic simulations (MDS) of the docked complex, which included only modest structural adjustments, corroborated the strong binding affinity of SAM and SAH to the HP. Evidence for HP’s possible role as an SAM-dependent MTase was therefore given by the findings of Multiple sequence alignment (MSA), MD, and molecular dynamic modeling. These in silico data suggest that the investigated HP might be used as a useful adjunct in the investigation of Pasteurella infections and the development of drugs to treat zoonotic pasteurellosis.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-07-03T08:10:12Z
DOI: 10.1177/11779322231184024
Issue No: Vol. 17 (2023)
- Metagenomics Reveals the Microbiome Multifunctionalities of Environmental
Importance From Termite Mound Soils
Authors: Ben Jesuorsemwen Enagbonma, Olubukola Oluranti Babalola
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The ecological deterioration caused by the continuous and excessive use of synthetic inputs in agriculture has prompted the search for environmentally favorable resources for crop production. Many have advocated for the use of soils from termite mounds to improve soil and plant health; therefore, the purpose of this study was to characterize the microbiome multifunctionalities that are important for plant health and growth in termite mound soil. The metagenomics of soil from termite mounds revealed taxonomic groups with functional potentials associated with promoting the growth and health of plants in nutrient-poor, virtually dry environments. Analysis of microorganisms revealed that Proteobacteria dominated the soil of termite colonies, while Actinobacteria ranked second. The predominance of Proteobacteria and Actinobacteria, the well-known antibiotic-producing populations, indicates that the termite mound soil microbiome possesses metabolic resistance to biotic stresses. Functions recognized for diverse proteins and genes unveiled that a multi-functional microbiome carry out numerous metabolic functions including virulence, disease, defense, aromatic compound and iron metabolism, secondary metabolite synthesis, and stress response. The abundance of genes in termite mound soils associated with these prominent functions could unquestionably validate the enhancement of plants in abiotic and biotically stressed environments. This study reveals opportunities to revisit the multifunctionalities of termite mound soils in order to establish a connection between taxonomic diversity, targeted functions, and genes that could improve plant yield and health in unfavorable soil conditions.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-30T05:41:11Z
DOI: 10.1177/11779322231184025
Issue No: Vol. 17 (2023)
- A Novel Inhibitor of DKK1/LRP6 Interactions Against the Alzheimer Disease:
An Insilco Approach
Authors: Manisha Prajapat, Harvinder Singh, Gajendra Chaudhary, Phulen Sarma, Gurjeet Kaur, Ajay Prakash Patel, Bikash Medhi
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The activation of the Wnt signaling pathway is implicated in a neuroprotective mechanism against the Alzheimer disease. When this pathway is blocked, it activates GSK3 beta, leading to tau hyperphosphorylation and the apoptosis of neurons. Dickkopf-related protein 1 (DKK1) is a protein that competes with the Wnt ligand for the low-density lipoprotein receptor–related protein 6 (LRP6) receptor’s binding, interrupting the Wnt-induced Fzd-Wnt-LRP6 complex. This counteracts Wnt’s neuroprotective effect and contributes to the progression of the Alzheimer disease. The aim of this study was to use in silico approach to develop new agents that can combat the Alzheimer disease by targeting the interaction between DKK1 and LRP6. To achieve this, we conducted a virtual screening (Vsw) of the Asinex-CNS database library (n = 54 513) compounds against a generated grid in LRP6 protein. From this screening, we selected 6 compounds based on their docking score and performed molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations on the selected ligands. Next, we evaluated the Absorption, Distribution, Metabolism, and Excretion (ADME) results of the 6 screened compounds using the Quick prop module of Schrödinger. We then employed several computational techniques, including PCA (Principal Component Analysis), DCCM (Dynamic Cross-Correlation Map), molecular dynamics simulation, and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA)–based negative binding free energy (BFE) calculation, to further analyze the compounds. Our extensive computational analysis resulted in the identification of 3 potential hits, LAS 29757582, LAS 29984441, and LAS 29757942. These compounds were found to block the interaction of DKK1 with LRP6 (A and B interface) protein, and their potential as therapeutic agents was supported by negative BFE calculation. Therefore, these compounds show potential as possible therapeutic agents for treating the Alzheimer disease through targeting the interaction between DKK1 and LRP6.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-28T10:14:55Z
DOI: 10.1177/11779322231183762
Issue No: Vol. 17 (2023)
- Targeted Gene Panel Sequencing Unveiled New Pathogenic Mutations in
Patients With Breast Cancer
Authors: Souad Kartti, El Mehdi Bouricha, Oumaima Zarrik, Youssef Aghlallou, Chaimaa Mounjid, Rachid ELJaoudi, Lahcen Belyamani, Azeddine Ibrahimi, Basma EL khannoussi
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The increasing commercialization of new gene panels based on next-generation sequencing for clinical research has significantly improved our understanding of breast cancer genetics and has led to the discovery of new mutation variants. The study included 16 unselected Moroccan breast cancer patients tested with multi-gene panel (HEVA screen panel) using Illumina Miseq, followed by Sanger sequencing to validate the most relevant mutation. Mutational analysis revealed the presence of 13 mutations (11 single-nucleotide polymorphisms [SNPs] and 2 indels), and 6 of 11 identified SNPs were predicted as pathogenic. One of the 6 pathogenic mutations was c.7874G>C, a heterozygous SNP in HD-OB domain of BRCA2 gene, which led to the arginine to threonine change at codon 2625 of the protein. This work describes the first case of a patient with breast cancer harboring this pathogenic variant and analyzes its functional impact using molecular docking and molecular dynamics simulation. Further experimental investigations are needed to validate its pathogenicity and to verify its association with breast cancer.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-24T11:52:55Z
DOI: 10.1177/11779322231182054
Issue No: Vol. 17 (2023)
- In Silico Investigation of a Chimeric IL24-LK6 Fusion Protein as a Potent
Candidate Against Breast Cancer
Authors: Hafiz Muhammad Rehman, Hafiz Muzzammel Rehman, Muhammad Naveed, Muhammad Tahir Khan, Muhammad Aqib Shabbir, Shakira Aslam, Hamid Bashir
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Targeted delivery of therapeutic anticancer chimeric molecules enhances the efficacy of drug by improving cellular uptake and circulation time. Engineering the molecules to facilitate the specific interaction between chimeric protein and its receptor is critical to elucidate biological mechanism as well as accuracy in modeling of complexes. A theoretically designed novel protein-protein interfaces can serve as a bottom-up method for comprehensive understanding of interacting protein residues. This study was aimed for in silico analyses of a chimeric fusion protein against breast cancer. The amino acid sequences of the interleukin 24 (IL-24) and LK-6 peptide were used to design the chimeric fusion protein via a rigid linker. The secondary and tertiary structures along with physicochemical properties by ProtParam and solubility were predicted using online software. The validation and quality of the fusion protein was confirmed by Rampage and ERRAT2. The newly designed fusion construct has a total length of 179 amino acids. The top-ranked structure from alpha fold2 showed 18.1 KD molecular weight by ProtParam, quality factor of 94.152 by ERRAT, and a valid structure by a Ramachandran plot with 88.5% residues in the favored region. Finally, the docking and simulation studies were performed using HADDOCK and Desmond module of Schrodinger. The quality, validity, interaction analysis, and stability of the fusion protein depict a functional molecule. The fusion gene IL24-LK6 after cloning and expression in a suitable prokaryotic cell might be a useful candidate for developing a novel anticancer therapy.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-23T12:43:11Z
DOI: 10.1177/11779322231182560
Issue No: Vol. 17 (2023)
- Investigation of
Methyl-5-(pentan-3-yloxy)-7-oxabicyclo[4.1.0]hept-3-ene-3-carboxyhydrazide
Derivatives as Potential Inhibitors of COVID-19 Main Protease: DFT and
Molecular Docking Study
Authors: Olawale Folorunso Akinyele, Emmanuel Gabriel Fakola, Omolara Olubunmi Adeboye, Sunday Chimela Chinuomah
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The search for effective therapeutics to combat COVID-19 has led to the exploration of the biological activity of numerous compounds. In this study, hydrazones derived from oseltamivir intermediate, methyl 5-(pentan-3-yloxy)-7-oxabicyclo[4.1.0]hept-3-ene-3-carboxylate have been investigated for their potential as drug candidates against the COVID-19 virus using computational methods, including density functional theory (DFT) studies, molecular docking, and absorption, distribution, metabolism, excretion and toxicity (ADMET) analysis. The DFT studies provide information on the electronic properties of the compounds while the molecular docking results using AutoDock reported the binding energies between the main protease of COVID-19 and the compounds. The DFT results revealed that the energy gap of the compounds ranged from 4.32 to 5.82 eV while compound HC had the highest energy gap (5.82 eV) and chemical potential (2.90 eV). The electrophilicity index values of the 11 compounds ranged from 2.49 to 3.86, thus they were classified as strong electrophiles. The molecular electrostatic potential (MESP) revealed electron-rich and electron-deficient regions of the compounds. The docking results reveal that all the compounds had better docking scores than remdesivir and chloroquine, frontline drugs employed in combating COVID-19, with HC having the best docking score of -6.5. The results were visualized using Discovery studio, which revealed hydrogen bonding, pi-alkyl interaction, alkyl interaction, salt bridge interaction, halogen interaction as being responsible for the docking scores. The drug-likeness results showed that the compounds qualify as oral drug candidates as none of them violated Vebers and Lipinski’s rule. Thus, they could serve as potential inhibitors of COVID-19.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-23T10:35:52Z
DOI: 10.1177/11779322231182050
Issue No: Vol. 17 (2023)
- Indigenous Oral and Gut Phages Defeat the Deadly NDM-1 Superbug
Authors: Pradeep Kumar Yadalam, Raghavendra Vamsi Anegundi, Ramya Ramadoss, M Saravanan, AshokKumar Veeramuthu, Artak Heboyan
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Aim:Antibiotics treat various diseases by targeting microorganisms by killing them or reducing their multiplication rate. New Delhi Metallo-beta-lactamase-1 (NDM-1) is produced by bacteria possessing the resistance gene blaNDM-1, the enzyme that makes bacteria resistant to beta-lactams. Bacteriophages, especially Lactococcus, have shown their ability to break down lactams. Hence, the current study computationally evaluated the binding potential of Lactococcus bacteriophages with NDM using Molecular docking and dynamics.Methods:Modelling of NDM I-TASSER for Main tail protein gp19 OS=Lactococcus phage LL-H or Lactobacillus delbrueckii subsp. lactis after downloading from UNIPROT ID- Q38344. Cluspro tool helps in Understanding cellular function and organization with protein-protein interactions. MD simulations(19) typically compute atom movements over time. Simulations were used to predict the ligand binding status in the physiological environment.Results:The best binding affinity score was found -1040.6 Kcal/mol compared to other docking scores. MD simulations show in RMSD values for target remains within 1.0 Angstrom, which is acceptable. The ligand-protein fit to receptor protein RMSD values of 2.752 fluctuates within 1.5 Angstrom after equilibration.Conclusions:Lactococcus bacteriophages showed a strong affinity to the NDM. Hence, this hypothesis, supported by evidence from a computational approach, will solve this life-threatening superbug problem.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-23T07:59:12Z
DOI: 10.1177/11779322231182767
Issue No: Vol. 17 (2023)
- Plastid DNA Barcoding and RtActin cDNA Fragment Isolation of Reutealis
Trisperma: A Promising Bioresource for Biodiesel Production
Authors: Nurul Jadid, Nur Laili Alfina Rosidah, Muhammad Rifqi Nur Ramadani, Indah Prasetyowati, Noor Nailis Sa’adah, Aulia Febrianti Widodo, Dwi Oktafitria
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Reutealis trisperma belonging to the family Euphorbiaceae is currently used for biodiesel production, and rapid development in plant-based biofuel production has led to its increasing demand. However, massive utilization of bio-industrial plants has led to conservation issues. Moreover, genetic information on R trisperma is still limited, which is crucial for developmental, physiological, and molecular studies. Studying gene expression is essential to explain plant physiological processes. Nonetheless, this technique requires sensitive and precise measurement of messenger RNA (mRNA). In addition, the presence of internal control genes is important to avoid bias. Therefore, collecting and preserving genetic data for R trisperma is indispensable. In this study, we aimed to evaluate the application of plastid loci, rbcL, and matK, to the DNA barcode of R trisperma for use in conservation programs. In addition, we isolated and cloned the RtActin (RtACT) gene fragment for use in gene expression studies. Sequence information was analyzed in silico by comparison with other Euphorbiaceae plants. For actin fragment isolation, reverse-transcription polymerase chain reaction was used. Molecular cloning of RtActin was performed using the pTA2 plasmid before sequencing. We successfully isolated and cloned 592 and 840 bp of RtrbcL and RtmatK fragment genes, respectively. The RtrbcL barcoding marker, rather than the RtmatK plastidial marker, provided discriminative molecular phylogenetic data for R Trisperma. We also isolated 986 bp of RtACT gene fragments. Our phylogenetic analysis demonstrated that R trisperma is closely related to the Vernicia fordii Actin gene (97% identity). Our results suggest that RtrbcL could be further developed and used as a barcoding marker for R trisperma. Moreover, the RtACT gene could be further investigated for use in gene expression studies of plant.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-21T06:01:40Z
DOI: 10.1177/11779322231182768
Issue No: Vol. 17 (2023)
- Retrospective Phylodynamic and Phylogeographic Analysis of the Human
Papillomavirus 16 E6 Gene in the Mediterranean Region
Authors: Oussama Souiai, Ameni Sallemi
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Human papillomavirus 16 (HPV16) is considered to be strongly correlated with the development of cervical cancer. Among the 8 HPV16 genes, the E6 constitutes a remarkable marker to follow the evolutionary history and spatial phylodynamics of HPV16 in the Mediterranean basin. Thus, this work aims to decipher the major evolutionary events and crosstalks in the Mediterranean basin with a focus on Tunisian strains regarding the E6 oncogene. In this study, we first extracted the available and annotated Mediterranean strains of HPV16 E6 gene sequences (n = 155) from the NCBI nucleotide database. These sequences were aligned, edited, and used for the downstream phylogenetic analyses. Finally, a Bayesian Markov Chain Monte Carlo approach was applied to reconstruct the evolutionary history of HPV16 migration. Our results showed that the HPV circulating in Tunisia derived from a Croatian ancestor around the year 1987. This starting point spreads to most European countries to reach northern Africa through the Moroccan gateway in 2004.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-08T11:57:25Z
DOI: 10.1177/11779322231178598
Issue No: Vol. 17 (2023)
- Association of Novel C319T Variant of PITX2 Gene 3’UTR Region With
Reproductive Performance in Awassi Sheep
Authors: Ahmed H Alkhammas, Tahreer M Al-Thuwaini, Mohammed Baqur S Al-Shuhaib, Neam M Khazaal
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Several genes influence sheep’s reproductive performance, among them the paired-like homeodomain transcription factor 2 (PITX2) gene. Thus, this study aimed to examine whether the variability within the PITX2 gene is associated with the reproductive performance of Awassi ewes. A total of 123 single-progeny ewes and 109 twin ewes were used to extract genomic DNA. An amplicon of 4 sequence fragments from exons 2, 4, 5 (upstream portion), and 5 (downstream portion) of the PITX2 gene was generated by polymerase chain reaction (PCR), 228, 304, 381, and 382 bp, respectively. Three genotypes of 382 bp amplicons were identified: CC, CT, and TT. Sequence analysis revealed a novel mutation in the CT genotype 319C > T. Statistical analysis revealed that single-nucleotide polymorphism (SNP) 319C > T was associated with reproductive performance. Single-nucleotide polymorphism 319C > T-carrying ewes had significantly (P ⩽ .01) lower litter sizes, twinning rates, lambing rates, and more days to lambing than those carrying CT and CC genotypes. Based on a logistic regression analysis, it was confirmed that the 319C > T SNP decreased litter size. Ewes with TT genotype produced fewer lambs than ewes with CT and CC genotypes. According to these results, the variant 319C> T SNP negatively affects the reproductive performance of Awassi sheep. Ewes carrying the 319C > T SNP have a lower litter size and are less prolific than those without the SNP.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-06T05:05:07Z
DOI: 10.1177/11779322231179018
Issue No: Vol. 17 (2023)
- Comparative Molecular Analysis and Antigenicity Prediction of an Outer
Membrane Protein (ompC) of Non-typhoidal Salmonella Serovars Isolated from
Different Food Animals in Lagos, Nigeria
Authors: Morufat Yusuf, Abraham Ajayi, Utibeima Udo Essiet, Oyin Oduyebo, Adeyemi Isaac Adeleye, Stella Ifeanyi Smith
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Non-typhoidal Salmonella (NTS) infections occur globally with high morbidity and mortality. The public health challenge caused is exacerbated by increasing rate of antibiotic resistance and absence of NTS vaccine. In this study, we characterized the outer membrane protein C (OmpC) serovars isolated from different food animals and predicted antigenicity. ompC of 27 NTS serovars were amplified by polymerase chain reaction (PCR) and sequenced. Sequence data were analysed and B-cell epitope prediction was done by BepiPred tool. T-cell epitope prediction was done by determining peptide-binding affinities of major histocompatibility complex (MHC) classes I and II using NetMHC pan 2.8 and NetMHC-II pan 3.2, respectively. ompC sequence analysis revealed conserved region among ompCs of Salmonella Serovars. A total of 66.7% of ompCs were stable with instability index value
Citation: Bioinformatics and Biology Insights
PubDate: 2023-06-02T06:12:08Z
DOI: 10.1177/11779322231176131
Issue No: Vol. 17 (2023)
- A Missense p.Q>R234 Mutation in the Osteopontin Gene Is Associated With
the Prolificacy of Iraqi Awassi Ewes
Authors: Tahreer M Al-Thuwaini, Mohammed Baqur S Al-Shuhaib, Ahmed F Kadhem, Ahmed H Alkhammas
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
One of the most valuable traits in production and breeding is a sheep’s prolificacy which is influenced by several genes, one of which is the osteopontin (OPN) gene. Thus, this study aimed to determine the effect of genetic variation within the OPN gene on Awassi ewe prolificacy. Genomic DNA was extracted from 123 single-progeny ewes and 109 twin ewes. Polymerase chain reaction (PCR) was used to amplify 4 sequence fragments (289, 275, 338, and 372 bp), representing exons 4, 5, 6, and 7 of the OPN gene. A 372 bp amplicon was identified with 3 different genotypes: TT, TC, and CC. Sequence analysis revealed a novel mutation in TC genotypes p.Q>R234. Statistical analysis revealed that the single nucleotide polymorphism (SNP) p.Q>R234 was associated with prolificacy. Ewes carrying the p.Q>R234 SNP had significantly (P ⩽ .01) lower litter sizes, twinning rates, and lambing rates, and more days to lambing than those with the TC and TT genotypes. The p.Q>R234 SNP was confirmed to be responsible for lower litter size through logistic regression analysis. From these results, we can conclude that the missense variant p.Q>R234 adversely affects the traits of interest and shows that the p.Q>R234 SNP negatively influences the prolificacy of Awassi sheep. Based on this study, it is evident that ewes in this population carrying the p.Q>R234 SNP have a lower litter size and are less prolific.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-05-13T10:11:36Z
DOI: 10.1177/11779322231172848
Issue No: Vol. 17 (2023)
- Bioinformatics Analysis to Uncover the Potential Drug Targets Responsible
for Mycobacterium tuberculosis Peptidoglycan and Lysine Biosynthesis
Authors: Dian Ayu Eka Pitaloka, Afifah Izzati, Siti Rafa Amirah, Luqman Abdan Syakuran, Lalu Muhammad Irham, Athika Darumas Putri, Wirawan Adikusuma
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Drug-resistant tuberculosis (TB), which results mainly from the selection of naturally resistant strains of Mycobacterium tuberculosis (MTB) due to mismanaged treatment, poses a severe challenge to the global control of TB. Therefore, screening novel and unique drug targets against this pathogen is urgently needed. The metabolic pathways of Homo sapiens and MTB were compared using the Kyoto Encyclopedia of Genes and Genomes tool, and further, the proteins that are involved in the metabolic pathways of MTB were subtracted and proceeded to protein-protein interaction network analysis, subcellular localization, drug ability testing, and gene ontology. The study aims to identify enzymes for the unique pathways for further screening to determine the feasibility of the therapeutic targets. The qualitative characteristics of 28 proteins identified as drug target candidates were studied. The results showed that 12 were cytoplasmic, 2 were extracellular, 12 were transmembrane, and 3 were unknown. Furthermore, druggability analysis revealed 14 druggable proteins, of which 12 were novel and responsible for MTB peptidoglycan and lysine biosynthesis. The novel targets obtained in this study are used to develop antimicrobial treatments against pathogenic bacteria. Future studies should further shed light on the clinical implementation to identify antimicrobial therapies against MTB.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-05-10T09:31:34Z
DOI: 10.1177/11779322231171774
Issue No: Vol. 17 (2023)
- Online Omics Platform Expedites Industrial Application of Halomonas
bluephagenesis TD1.0
Authors: Helen Park, Matthew Faulkner, Helen S Toogood, Guo-Qiang Chen, Nigel Scrutton
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Multi-omic data mining has the potential to revolutionize synthetic biology especially in non-model organisms that have not been extensively studied. However, tangible engineering direction from computational analysis remains elusive due to the interpretability of large datasets and the difficulty in analysis for non-experts. New omics data are generated faster than our ability to use and analyse results effectively, resulting in strain development that proceeds through classic methods of trial-and-error without insight into complex cell dynamics. Here we introduce a user-friendly, interactive website hosting multi-omics data. Importantly, this new platform allows non-experts to explore questions in an industrially important chassis whose cellular dynamics are still largely unknown. The web platform contains a complete KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis derived from principal components analysis, an interactive bio-cluster heatmap analysis of genes, and the Halomonas TD1.0 genome-scale metabolic (GEM) model. As a case study of the effectiveness of this platform, we applied unsupervised machine learning to determine key differences between Halomonas bluephagenesis TD1.0 cultivated under varied conditions. Specifically, cell motility and flagella apparatus are identified to drive energy expenditure usage at different osmolarities, and predictions were verified experimentally using microscopy and fluorescence labelled flagella staining. As more omics projects are completed, this landing page will facilitate exploration and targeted engineering efforts of the robust, industrial chassis H bluephagenesis for researchers without extensive bioinformatics background.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-05-09T01:10:46Z
DOI: 10.1177/11779322231171779
Issue No: Vol. 17 (2023)
- Selective Non-toxics Inhibitors Targeting DHFR for Tuberculosis and Cancer
Therapy: Pharmacophore Generation and Molecular Dynamics Simulation
Authors: Ghyzlane EL Haddoumi, Mariam Mansouri, Houda Bendani, Mohammed Walid Chemao-Elfihri, Jouhaina Kourou, Hanane Abbou, Lahcen Belyamani, Ilham Kandoussi, Azeddine Ibrahimi
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Dihydrofolate reductase (DHFR) is a crucial enzyme that catalyzes the conversion of folic acid. Its reserved properties and significance in both human (h-DHFR) and mycobacterium (mt-DHFR) make it a challenging target for developing drugs against cancer and bacterial infections. Although methotrexate (MTX) is commonly used for cancer therapy and bacterial infections, it has a toxic profile. In this study, we aimed to identify selective and non-toxic inhibitors against h-DHFR and mt-DHFR using an in silico approach. From a data set of 8 412 inhibitors, 11 compounds passed the toxicity and drug-likeness tests, and their interaction with h-DHFR and mt-DHFR was studied by performing molecular docking. To evaluate the inhibitory activity of the compounds against mt-DHFR, five known reference ligands and the natural ligand (dihydrofolate) were used to generate a pharmacophoric map. Two potential selective inhibitors for mt-DHFR and h-DHFR were selected for further investigation using molecular dynamics for 100 ns. As a result, BDBM18226 was identified as the best compound selective for mt-DHFR, non-toxic, with five features listed in the map, with a binding energy of –9.6 kcal/mol. BDBM50145798 was identified as a non-toxic selective compound with a better affinity than MTX for h-DHFR. Molecular dynamics of the two best ligands suggest that they provide more stable, compact, and hydrogen bond interactions with the protein. Our findings could significantly expand the chemical space for new mt-DHFR inhibitors and provide a non-toxic alternative toward h-DHFR for the respective treatment of tuberculosis and cancer therapy.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-05-08T07:27:02Z
DOI: 10.1177/11779322231171778
Issue No: Vol. 17 (2023)
- A Novel c.100C > G Mutation in the FST Gene and Its Relation With the
Reproductive Traits of Awassi Ewes
Authors: Tahreer M Al-Thuwaini, Wefak J Albazi, Mohammed Baqur S Al-Shuhaib, Layth H Merzah, Rihab G Mohammed, Fadhil A Rhadi, Ali B Abd Al-Hadi, Ahmed H Alkhammas
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Reproductive traits are affected by many factors, including ovarian function, hormones, and genetics. Genetic polymorphisms of candidate genes are associated with reproductive traits. Several candidate genes are associated with economic traits, including the follistatin (FST) gene. Thus, this study aimed to evaluate whether the genetic variations in the FST gene are associated with the reproductive traits in Awassi ewes. The genomic DNA was extracted from 109 twin ewes and 123 single-progeny ewes. Therefore, 4 sequence fragments from the FST gene were amplified using polymerase chain reaction (PCR) (exon 2/240, exon 3/268, exon 4/254, and exon 5/266 bp, respectively). For a 254 bp amplicon, 3 genotypes were identified: CC, CG, and GG. Sequencing revealed a novel mutation in CG genotypes c.100C > G. The statistical analysis of c.100C > G showed an association with reproductive characteristics. Ewes carrying the c.100C > G had significantly (P ⩽ .01) lower litter sizes, twinning rates, lambing rates, and more days to lambing compared with CG and CC genotypes. Logistic regression analysis confirmed that the c.100C > G single-nucleotide polymorphism (SNP) is responsible for decreasing litter size. According to these results, the variant c.100C > G negatively affects the traits of interest and is associated with lower reproductive traits in Awassi sheep. As a result of this study, ewes carrying the c.100C > G SNP have lower litter size and are less prolific.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-05-02T06:00:13Z
DOI: 10.1177/11779322231170988
Issue No: Vol. 17 (2023)
- Potential Biomarkers for Parkinson Disease from Functional Enrichment and
Bioinformatic Analysis of Global Gene Expression Patterns of Blood and
Substantia Nigra Tissues
Authors: Ramu Elango, Babajan Banaganapalli, Abdulrahman Mujalli, Nuha AlRayes, Sarah Almaghrabi, Majid Almansouri, Ahmed Sahly, Gada Ali Jadkarim, Md Zubbair Malik, Hussam Ibrahim Kutbi, Noor Ahmad Shaik, Eman Alefishat
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The Parkinson disease (PD) is the second most common neurodegenerative disorder affecting the central nervous system and motor functions. The biological complexity of PD is yet to reveal potential targets for intervention or to slow the disease severity. Therefore, this study aimed to compare the fidelity of blood to substantia nigra (SN) tissue gene expression from PD patients to provide a systematic approach to predict role of the key genes of PD pathobiology. Differentially expressed genes (DEGs) from multiple microarray data sets of PD blood and SN tissue from GEO database are identified. Using the theoretical network approach and variety of bioinformatic tools, we prioritized the key genes from DEGs. A total of 540 and 1024 DEGs were identified in blood and SN tissue samples, respectively. Functional pathways closely related to PD such as ERK1 and ERK2 cascades, mitogen-activated protein kinase (MAPK) signaling, Wnt, nuclear factor-κB (NF-κB), and PI3K-Akt signaling were observed by enrichment analysis. Expression patterns of 13 DEGs were similar in both blood and SN tissues. Comprehensive network topological analysis and gene regulatory networks identified additional 10 DEGs functionally connected with molecular mechanisms of PD through the mammalian target of rapamycin (mTOR), autophagy, and AMP-activated protein kinase (AMPK) signaling pathways. Potential drug molecules were identified by chemical-protein network and drug prediction analysis. These potential candidates can be further validated in vitro/in vivo to be used as biomarkers and/or novel drug targets for the PD pathology and/or to arrest or delay the neurodegeneration over the years, respectively.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-04-29T08:44:40Z
DOI: 10.1177/11779322231166214
Issue No: Vol. 17 (2023)
- Unraveling the Mechanism of Immunity and Inflammation Related to Molecular
Signatures Crosstalk Among Obesity, T2D, and AD: Insights From
Bioinformatics Approaches
Authors: Kumar Vishal, Piplu Bhuiyan, Junxia Qi, Yang Chen, Jubiao Zhang, Fen Yang, Juxue Li
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Individuals with type 2 diabetes (T2D) and obesity have a higher risk of developing Alzheimer disease (AD), and increasing evidence indicates a link between impaired immune signaling pathways and the development of AD. However, the shared cellular mechanisms and molecular signatures among these 3 diseases remain unknown. The purpose of this study was to uncover similar molecular markers and pathways involved in obesity, T2D, and AD using bioinformatics and a network biology approach. First, we investigated the 3 RNA sequencing (RNA-seq) gene expression data sets and determined 224 commonly shared differentially expressed genes (DEGs) from obesity, T2D, and AD diseases. Gene ontology and pathway enrichment analyses revealed that mutual DEGs were mainly enriched with immune and inflammatory signaling pathways. In addition, we constructed a protein-protein interactions network for finding hub genes, which have not previously been identified as playing a critical role in these 3 diseases. Furthermore, the transcriptional factors and protein kinases regulating commonly shared DEGs among obesity, T2D, and AD were also identified. Finally, we suggested potential drug candidates as possible therapeutic interventions for 3 diseases. The results of this bioinformatics analysis provided a new understanding of the potential links between obesity, T2D, and AD pathologies.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-04-25T11:42:28Z
DOI: 10.1177/11779322231167977
Issue No: Vol. 17 (2023)
- Bioinformatic Evaluation of Features on Cis-regulatory Elements at 6q25.1
Authors: N Sreekar, Smeeta Shrestha
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Eukaryotic non-coding regulatory features contribute significantly to cellular plasticity which on aberration leads to cellular malignancy. Enhancers are cis-regulatory elements that contribute to the development of resistance to endocrine therapy in estrogen receptor (ER)-positive breast cancer leading to poor clinical outcome. ER is vital for therapeutic targets in ER-positive breast cancer. Here, we review and report the different regulatory features present on ER with the objective to delineate potential mechanisms which may contribute to development of resistance. The UCSC Genome Browser, data mining, and bioinformatics tools were used to review enhancers, transcription factors (TFs), histone marks, long non-coding RNAs (lncRNAs), and variants residing in the non-coding region of the ER gene. We report 7 enhancers, 3 of which were rich in TF-binding sites and histone marks in a cell line-specific manner. Furthermore, some enhancers contain estrogen resistance variants and sites for lncRNA. Our review speculates putative models suggesting potential aberrations in gene regulation and expression if these regulatory landscapes and assemblies are altered. This review gives an interesting perspective in designing integrated in vitro studies including non-coding elements to study development of endocrine resistance in ER-positive breast cancer.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-04-25T11:40:48Z
DOI: 10.1177/11779322231167971
Issue No: Vol. 17 (2023)
- Potential Inhibitory Biomolecular Interactions of Natural Compounds With
Different Molecular Targets of Diabetes
Authors: Precious A Akinnusi, Samuel O Olubode, Adebowale A Alade, Aderemi A Ashimi, Olamide L Onawola, Abigail O Agbolade, Adaobi P Emeka, Sidiqat A Shodehinde, Olawole Y Adeniran
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Type II diabetes is an endemic disease and is responsible for approximately 90% to 95% of diabetes cases. The pathophysiological distortions are majorly β-cell dysfunction, insulin resistance, and long-term inflammation, which all progressively unsettle the control of blood glucose levels and trigger microvascular and macrovascular complications. The diverse pathological disruptions which patients with type II diabetes mellitus exhibit precipitate the opinion that different antidiabetic agents, administered in combination, might be required to curb this menace and maintain normal blood glucose. To this end, natural compounds were screened to identify small molecular weight compounds with inhibitory effects on protein tyrosine phosphatase 1B (PTP1B), dipeptidyl-peptidase-4 (DPP-4), and α-amylase. From the result, the top 5 anthocyanins with the highest binding affinity are reported herein. Further ADMET profiling showed moderate pharmacokinetic profiles for these compounds as well as insignificant toxicity. Cyanidin 3-(p-coumaroyl)-diglucoside-5-glucoside (−15.272 kcal/mol), cyanidin 3-O-(6ʺ-malonyl-3ʺ-glucosyl-glucoside) (−9.691 kcal/mol), and delphinidin 3,5-O-diglucoside (−12.36 kcal/mol) had the highest binding affinities to PTP1B, DPP-4, and α-amylase, respectively, and can be used in combination to control glucose fluctuations. However, validations must be carried out through further in vitro and in vivo tests.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-04-25T11:39:08Z
DOI: 10.1177/11779322231167970
Issue No: Vol. 17 (2023)
- Genomic Evidence of Multiple Introductions of SARS-CoV-2 in Mauritania
Authors: Abdelmalick Abdelmalick, Sofia Sehli, Abdellah Idrissi Azami, Nihal Habib, Najib Al Idrissi, Lahcen Belyamani, Ahmed Houmeida, Hassan Ghazal
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The rapid and global spread of the novel coronavirus severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has raised serious public health concerns, including in Mauritania. We sequenced and analyzed the entire genome of 13 SARS-CoV-2 virus strains isolated from polymerase chain reaction (PCR)-positive symptomatic patients sampled from March 3 to May 31, 2021 to better understand SARS-CoV-2 introduction, propagation, and evolution in Mauritania. A phylogenetic tree using available data from the EpiCoV GISAID database and a variant network with non-Mauritanian sequences were constructed. Variant analysis of the 13 Mauritanian SARS-CoV-2 genome sequences indicated an average mutational percentage of 0.39, which is similar to that in other countries. Phylogenetic analysis revealed multiple spatiotemporal introductions, mainly from Europe (France, Belgium) and Africa (Senegal, Côte d’Ivoire), which also provided evidence of early community transmission. A total of 2 unique mutations, namely, NSP6_Q208K and NSP15_S273T, were detected in the NSP6 and NSP15 genes, respectively, confirming the aforementioned introduction of SARS-CoV-2 in Mauritania. These findings highlight the relevance of continuous genomic monitoring strategies for understanding virus transmission dynamics and acquiring knowledge to address forthcoming sources of infection in Africa.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-04-25T11:35:48Z
DOI: 10.1177/11779322231167927
Issue No: Vol. 17 (2023)
- The Alteration of Akkermansiaceae/Lachnospiraceae Ratio Is a Microbial
Feature of Antibiotic-Induced Microbiota Remodeling
Authors: Pei-Chen Chen, Ming-Shian Lin, Tien-Ching Lin, Ting-Wei Kang, Jhen-Wei Ruan
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Antibiotic treatment has been shown to cause gut microbiota dysbiosis. However, lacking critical features defining gut microbiota dysbiosis makes it challenging to prevent. By co-occurrence network analysis, we found that despite short antibiotic courses eliminating certain microbial taxa, the Akkermansia genus played the role of a high-centrality hub to maintain microbiota homeostasis. When the antibiotic courses continued, the elimination of Akkermansia induced a significant microbiota remodeling of the gut microbiota networks. Based on this finding, we found that under long-term antibiotic stress, the gut microbiota was rearranged into a stable network with a significantly lower Akkermansiaceae/Lachnospiraceae (A/L) ratio and no microbial hub. By functional prediction analysis, we confirmed that the gut microbiota with a low A/L ratio also had enhanced mobile elements and biofilm-formation functions that may be associated with antibiotic resistance. This study identified A/L ratio as an indicator of antibiotic-induced dysbiosis. This work reveals that besides the abundance of specific probiotics, the hierarchical structure also critically impacts the microbiome function. Co-occurrence analysis may help better monitor the microbiome dynamics than only comparing the differentially abundant bacteria between samples.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-04-15T04:45:28Z
DOI: 10.1177/11779322231166229
Issue No: Vol. 17 (2023)
- COVID-19 Epidemic Forecast in Brazil
Authors: Oleg Gaidai, Yihan Xing
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
This study advocates a novel spatio-temporal method for accurate prediction of COVID-19 epidemic occurrence probability at any time in any Brazil state of interest, and raw clinical observational data have been used. This article describes a novel bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient time period, resulting in robust long-term forecast of the virus outbreak probability. COVID-19 daily numbers of recorded patients in all affected Brazil states were taken into account. This work aimed to benchmark novel state-of-the-art methods, making it possible to analyse dynamically observed patient numbers while taking into account relevant regional mapping. Advocated approach may help to monitor and predict possible future epidemic outbreaks within a large variety of multi-regional biological systems. Suggested methodology may be used in various modern public health applications, efficiently using their clinical survey data.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-04-11T12:31:08Z
DOI: 10.1177/11779322231161939
Issue No: Vol. 17 (2023)
- Comparative In Silico Analysis and Functional Characterization of
TANK-Binding Kinase 1–Binding Protein 1
Authors: Humaira Aziz Sawal, Shagufta Nighat, Tanzeela Safdar, Laiba Anees
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Protein modelling plays a vital role in the drug discovery process. TANK-binding kinase 1–binding protein 1 is also called an adapter protein, which is encoded by gene TBK1 present in Homo sapiens. It is found in lungs, small intestine, leukocytes, heart, placenta, muscle, kidney, lower level of thymus, and brain. It has a number of protein-binding sites, to which TBK1 and IKBKE bind and perform different functions as immunomodulatory, antiproliferative, and antiviral innate immunity which release different types of interferons. Our study predicts the comparative model of 3-dimensional (3D) structure through different bioinformatics tools that will be helpful for further studies in future. The reactivity and stability of these proteins were evaluated physicochemically and through domain determination and prediction of secondary structure using bioinformatics methods such as ProtParam, Pfam, and SOPMA, respectively. Robetta, an ab initio approach, I-TASSER, and AlphaFold was used for 3D structure prediction, and the models were validated using the SAVESv6.0 (PROCHECK) server. Conclusively, the best 3D structure of TBK1-binding protein 1 was predicted using Robetta software. After unveiling the 3D structure of the novel protein, we concluded that this structure will help us to find out its role other than in antiviral innate immunity and by producing torsion in its 3D structure researchers will be able to detect either this protein is involved in any disease or not because according to previous studies it was not associated with any disease.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-04-03T04:58:32Z
DOI: 10.1177/11779322231164828
Issue No: Vol. 17 (2023)
- Identification of Conserved and Novel MicroRNAs with their Targets in
Garden Pea (Pisum Sativum L.) Leaves by High-Throughput Sequencing
Authors: Qurshid Hasan Khan
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
MicroRNAs (miRNAs) are single-stranded, endogenous, non-coding RNAs of 20–24 nucleotides that play a significant role in post-transcriptional gene regulation. Various conserved and novel miRNAs have been characterized, especially from the plant species whose genomes were well-characterized; however, information on miRNA in economically important plants such as pea (Pisum sativum L.) is limited. In this study, I have identified conserved and novel miRNA in garden pea plant leaves samples along with their targets by analyzing the next generation sequencing (NGS) data. The raw data obtained from NGS were processed and 1.38 million high-quality non-redundant reads were retained for analysis, this tremendous quantity of reads indicates a large and diverse small RNA population in pea leaves. After analyzing the deep sequencing data, 255 conserved and 11 novel miRNAs were identified in the garden pea leaves sample. Utilizing psRNATarget tool, the miRNA targets of conserved and novel miRNA were predicted. Further, the functional annotation of the miRNA targets were performed using blast2Go software and the target gene products were predicted. The miRNA target gene products along with GO_ID (Gene Ontology Identifier) were categorized into biological processes, cellular components, and molecular functions. The information obtained from this study will provide genomic resources that will help in understanding miRNA-mediated post-transcriptional gene regulation in garden peas.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-03-31T11:56:08Z
DOI: 10.1177/11779322231162777
Issue No: Vol. 17 (2023)
- Normalization of Large-Scale Transcriptome Data Using Heuristic Methods
Authors: Arthur Yosef, Eli Shnaider, Moti Schneider, Michael Gurevich
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
In this study, we introduce an artificial intelligent method for addressing the batch effect of a transcriptome data. The method has several clear advantages in comparison with the alternative methods presently in use. Batch effect refers to the discrepancy in gene expression data series, measured under different conditions. While the data from the same batch (measurements performed under the same conditions) are compatible, combining various batches into 1 data set is problematic because of incompatible measurements. Therefore, it is necessary to perform correction of the combined data (normalization), before performing biological analysis. There are numerous methods attempting to correct data set for batch effect. These methods rely on various assumptions regarding the distribution of the measurements. Forcing the data elements into pre-supposed distribution can severely distort biological signals, thus leading to incorrect results and conclusions. As the discrepancy between the assumptions regarding the data distribution and the actual distribution is wider, the biases introduced by such “correction methods” are greater. We introduce a heuristic method to reduce batch effect. The method does not rely on any assumptions regarding the distribution and the behavior of data elements. Hence, it does not introduce any new biases in the process of correcting the batch effect. It strictly maintains the integrity of measurements within the original batches.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-03-31T10:33:48Z
DOI: 10.1177/11779322231160397
Issue No: Vol. 17 (2023)
- Somatic Super-Enhancer Epigenetic Signature for Overall Survival
Prediction in Patients with Breast Invasive Carcinoma
Authors: Xu Yang, Wenzhong Zheng, Mengqiang Li, Shiqiang Zhang
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
To analyze genome-wide super-enhancers (SEs) methylation signature of breast invasive carcinoma (BRCA) and its clinical value. Differential methylation sites (DMS) between BRCA and adjacent tissues from The Cancer Genome Atlas (TCGA) database were identified by using ChAMP package in R software. Super-enhancers were identified sing ROSE software. Overlap analysis was used to assess the potential DMS in SEs region. Feature selection was performed by Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm based on TCGA training cohort. Prognosis model validation was performed in TCGA training cohort, TCGA validation cohort, and gene expression omnibus (GEO) test cohort. The gene ontology and KEGG analysis revealed that SEs target genes were significantly enriched in cell-migration-associated processes and pathways. A total of 83 654 DMS were identified between BRCA and adjacent tissues. Around 2397 DMS in SEs region were identified by overlap study and used to feature selection. By using Cox regression and LASSO algorithm, 42 features were selected to develop a clinical prediction model (CPM). Both training (TCGA) and validation cohorts (TCGA and GEO) show that the CPM has ideal discrimination and calibration. The CPM based on DMS at SE regions has ideal discrimination and calibration, which combined with tumor node metastasis (TNM) stage could improve prognostication, and thus contribute to individualized medicine.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-03-31T06:56:06Z
DOI: 10.1177/11779322231162767
Issue No: Vol. 17 (2023)
- miR-6087 Might Regulate Cell Cycle–Related mRNAs During
Cardiomyogenesis of hESCs
Authors: Hellen Cristine Machado, Saloe Bispo, Bruno Dallagiovanna
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
MicroRNAs (miRNAs) are small noncoding RNAs that act as negative regulators of gene expression at the post-transcriptional level, promoting mRNA degradation or translation repression. Despite the well-described presence of miRNAs in various human tissues, there is still a lack of information about the relationship between miRNAs and the translation regulation in human embryonic stem cells (hESCs) during cardiomyogenesis. Here, we investigate RNA-seq data from hESCs, focusing on distinct stages of cardiomyogenesis and searching for polysome-bound miRNAs that could be involved in translational regulation. We identify miR-6087 as a differentially expressed miRNA at latest steps of cardiomyocyte differentiation. We analyzed the coexpression pattern between the differentially expressed mRNAs and miR-6087, evaluating whether they are predicted targets of the miRNA. We arranged the genes into an interaction network and identified BLM, RFC4, RFC3, and CCNA2 as key genes of the network. A post hoc analysis of the key genes suggests that miR-6087 could act as a regulator of the cell cycle in hESC during cardiomyogenesis.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-03-31T06:52:06Z
DOI: 10.1177/11779322231161918
Issue No: Vol. 17 (2023)
- Pharmacophore-Aided Virtual Screening and Molecular Dynamics Simulation
Identifies TrkB Agonists for Treatment of CDKL5-Deficiency Disorders
Authors: Ibitayo Abigail Ademuwagun, Gbolahan Oladipupo Oduselu, Solomon Oladapo Rotimi, Ezekiel Adebiyi
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Therapeutic intervention in cyclin-dependent kinase-like 5 (CDKL5) deficiency disorders (CDDs) has remained a concern over the years. Recent advances into the mechanistic interplay of signalling pathways has revealed the role of deficient tropomyosin receptor kinase B (TrkB)/phospholipase C γ1 signalling cascade in CDD. Novel findings showed that in vivo administration of a TrkB agonist, 7,8-dihydroxyflavone (7,8-DHF), resulted in a remarkable reversal in the molecular pathologic mechanisms underlying CDD. Owing to this discovery, this study aimed to identify more potent TrkB agonists than 7,8-DHF that could serve as alternatives or combinatorial drugs towards effective management of CDD. Using pharmacophore modelling and multiple database screening, we identified 691 compounds with identical pharmacophore features with 7,8-DHF. Virtual screening of these ligands resulted in identification of at least 6 compounds with better binding affinities than 7,8-DHF. The in silico pharmacokinetic and ADMET studies of the compounds also indicated better drug-like qualities than those of 7,8-DHF. Postdocking analyses and molecular dynamics simulations of the best hits, 6-hydroxy-10-(2-oxo-1-azatricyclo[7.3.1.05,13]trideca-3,5(13),6,8-tetraen-3-yl)-8-oxa-13,14,16-triazatetracyclo[7.7.0.02,7.011,15]hexadeca-1,3,6,9,11,15-hexaen-5-one (PubChem: 91637738) and 6-hydroxy-10-(8-methyl-2-oxo-1H-quinolin-3-yl)-8-oxa-13,14,16-triazatetracyclo[7.7.0.02,7.011,15]hexadeca-1,3,6,9,11,15-hexaen-5-one (PubChem ID: 91641310), revealed unique ligand interactions, validating the docking findings. We hereby recommend experimental validation of the best hits in CDKL5 knock out models before consideration as drugs in CDD management.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-03-03T06:22:08Z
DOI: 10.1177/11779322231158254
Issue No: Vol. 17 (2023)
- S-Adenosyl-l-Homocysteine Exhibits Potential Antiviral Activity Against
Dengue Virus Serotype-3 (DENV-3) in Bangladesh: A Viroinformatics-Based
Approach
Authors: Dipok Kumer Shill, Shafina Jahan, Mohammad Mamun Alam, Md Belayet Hasan Limon, Muntasir Alam, Mohammed Ziaur Rahman, Mustafizur Rahman
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Dengue outbreak is one of the concerning issues in Bangladesh due to the annual outbreak with the alarming number of death and infection. However, there is no effective antiviral drug available to treat dengue-infected patients. This study evaluated and screened antiviral drug candidates against dengue virus serotype 3 (DENV-3) through viroinformatics-based analyses. Since 2017, DENV-3 has been the predominant serotype in Bangladesh. We selected 3 non-structural proteins of DENV-3, named NS3, NS4A, and NS5, as antiviral targets. Protein modeling and validation were performed with VERIFY-3D, Ramachandran plotting, MolProbity, and PROCHECK. We found 4 drug-like compounds from DRUGBANK that can interact with these non-structural proteins of DENV-3. Then, the ADMET profile of these compounds was determined by admetSAR2, and molecular docking was performed with AutoDock, SWISSDOCK, PatchDock, and FireDock. Furthermore, they were subjected to molecular dynamics (MD) simulation study using the DESMOND module of MAESTRO academic version 2021-4 (force field OPLS_2005) to determine their solution’s stability in a predefined body environment. Two drug-like compounds named Guanosine-5’-Triphosphate (DB04137) and S-adenosyl-l-homocysteine (DB01752) were found to have an effective binding with these 3 proteins (binding energy > 33.47 KJ/mole). We found NS5 protein was stable and equilibrated in a 100 ns simulation run along with a negligible (
Citation: Bioinformatics and Biology Insights
PubDate: 2023-02-28T07:06:29Z
DOI: 10.1177/11779322231158249
Issue No: Vol. 17 (2023)
- An Integrated Approach of Learning Genetic Networks From Genome-Wide Gene
Expression Data Using Gaussian Graphical Model and Monte Carlo Method
Authors: Haitao Zhao, Sujay Datta, Zhong-Hui Duan
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Global genetic networks provide additional information for the analysis of human diseases, beyond the traditional analysis that focuses on single genes or local networks. The Gaussian graphical model (GGM) is widely applied to learn genetic networks because it defines an undirected graph decoding the conditional dependence between genes. Many algorithms based on the GGM have been proposed for learning genetic network structures. Because the number of gene variables is typically far more than the number of samples collected, and a real genetic network is typically sparse, the graphical lasso implementation of GGM becomes a popular tool for inferring the conditional interdependence among genes. However, graphical lasso, although showing good performance in low dimensional data sets, is computationally expensive and inefficient or even unable to work directly on genome-wide gene expression data sets. In this study, the method of Monte Carlo Gaussian graphical model (MCGGM) was proposed to learn global genetic networks of genes. This method uses a Monte Carlo approach to sample subnetworks from genome-wide gene expression data and graphical lasso to learn the structures of the subnetworks. The learned subnetworks are then integrated to approximate a global genetic network. The proposed method was evaluated with a relatively small real data set of RNA-seq expression levels. The results indicate the proposed method shows a strong ability of decoding the interactions with high conditional dependences among genes. The method was then applied to genome-wide data sets of RNA-seq expression levels. The gene interactions with high interdependence from the estimated global networks show that most of the predicted gene-gene interactions have been reported in the literatures playing important roles in different human cancers. Also, the results validate the ability and reliability of the proposed method to identify high conditional dependences among genes in large-scale data sets.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-02-27T08:57:30Z
DOI: 10.1177/11779322231152972
Issue No: Vol. 17 (2023)
- LC-MS Analysis, Computational Investigation, and Antimalarial Studies of
Azadirachta indica Fruit
Authors: Kolade O Faloye, Stephen A Adesida, Samuel A Oguntimehin, Adetola H Adewole, Olajide B Omoyeni, Sunday J Fajobi, Jeremiah P Ugwo, Isaac D Asiyanbola, Victoria O Bamimore, Emmanuel G Fakola, Olayemi J Oladiran, Michael Spiteller
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Malaria is a deadly disease that continues to pose a threat to children and maternal well-being. This study was designed to identify the chemical constituents in the ethanolic fruit extract of Azadirachta indica, elucidate the pharmacological potentials of identified phytochemicals through the density functional theory method and carry out the antimalarial activity of extract using chemosuppression and curative models. The liquid chromatography-mass spectrometry (LC-MS) analysis of the ethanolic extract was carried out, followed by the density functional theory studies of the identified phytochemicals using B3LYP and 6-31G (d, p) basis set. The antimalarial assays were performed using the chemosuppression (4 days) and curative models. The LC-MS fingerprint of the extract led to the identification of desacetylnimbinolide, nimbidiol, O-methylazadironolide, nimbidic acid, and desfurano-6α-hydroxyazadiradione. Also, the frontier molecular orbital properties, molecular electrostatic potential, and dipole moment studies revealed the identified phytochemicals as possible antimalarial agents. The ethanolic extract of A indica fruit gave 83% suppression at 800 mg/kg, while 84% parasitaemia clearance was obtained in the curative study. The study provided information about the phytochemicals and background pharmacological evidences of the antimalarial ethnomedicinal claim of A indica fruit. Thus, isolation and structure elucidation of the identified phytochemicals from the active ethanolic extract and extensive antimalarial studies towards the discovery of new therapeutic agents is recommended for further studies.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-02-25T10:35:14Z
DOI: 10.1177/11779322231154966
Issue No: Vol. 17 (2023)
- New Insight Into Mechanisms of Hepatic Encephalopathy: An Integrative
Analysis Approach to Identify Molecular Markers and Therapeutic Targets
Authors: Ali Sepehrinezhad, Ali Shahbazi, Sajad Sahab Negah, Fin Stolze Larsen
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Hepatic encephalopathy (HE) is a set of complex neurological complications that arise from advanced liver disease. The precise molecular and cellular mechanism of HE is not fully understood. Differentially expressed genes (DEGs) from microarray technologies are powerful approaches to obtain new insight into the pathophysiology of HE. We analyzed microarray data sets of cirrhotic patients with HE from Gene Expression Omnibus to identify DEGs in postmortem cerebral tissues. Consequently, we uploaded significant DEGs into the STRING to specify protein-protein interactions. Cytoscape was used to reconstruct the genetic network and identify hub genes. Target genes were uploaded to different databases to perform comprehensive enrichment analysis and repurpose new therapeutic options for HE. A total of 457 DEGs were identified in 2 data sets totally from 12 cirrhotic patients with HE compared with 12 healthy subjects. We found that 274 genes were upregulated and 183 genes were downregulated. Network analyses on significant DEGs indicated 12 hub genes associated with HE. Enrichment analysis identified fatty acid beta-oxidation, cerebral organic acidurias, and regulation of actin cytoskeleton as main involved pathways associated with upregulated genes; serotonin receptor 2 and ELK-SRF/GATA4 signaling, GPCRs, class A rhodopsin-like, and p38 MAPK signaling pathway were related to downregulated genes. Finally, we predicted 39 probable effective drugs/agents for HE. This study not only confirms main important involved mechanisms of HE but also reveals some yet unknown activated molecular and cellular pathways in human HE. In addition, new targets were identified that could be of value in the future study of HE.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-02-18T07:03:06Z
DOI: 10.1177/11779322231155068
Issue No: Vol. 17 (2023)
- Molecular Cloning and AlphaFold Modeling of Thyrotropin (ag-TSH) From the
Amazonian Fish Pirarucu (Arapaima gigas)
Authors: Renan Passos Freire, Jorge Enrique Hernandez-Gonzalez, Eliana Rosa Lima, Miriam Fussae Suzuki, João Ezequiel de Oliveira, Lucas Simon Torai, Paolo Bartolini, Carlos Roberto Jorge Soares
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Arapaima gigas, known as Pirarucu in Brazil, is one of the largest freshwater fish in the world. Some individuals could reach 3 m in length and weight up to 200 kg. Due to extinction risks and its economic value, the species has been a focus for preservation and reproduction studies. Thyrotropin (TSH) is a glycoprotein hormone formed by 2 subunits α and β whose main activity is related to the synthesis of thyroid hormones (THs)—T3 and T4. In this work, we present a combination of bioinformatics tools to identify Arapaima gigas βTSH (ag-βTSH), modeling its molecular structure and express the recombinant heterodimer form in mammalian cells. Using the combination of computational biology, based on genome-related information, in silico molecular cloning and modeling led to confirm results of the ag-βTSH sequence by reverse transcriptase-polymerase chain reaction (RT-PCR) and transient expression in human embryonic kidney (HEK293F) cells. Molecular cloning of ag-βTSH retrieved 146 amino acids with a signal peptide of 21 amino acid residues and 6 disulfide bonds. The sequence has a similarity to 39 fish species, ranging between 43.1% and 81.6%, whose domains are extremely conserved, such as cystine knot motif and N-glycosylation site. The Arapaima gigas thyrotropin (ag-TSH) model, solved by AlphaFold, was used in molecular dynamics simulations with Scleropages formosus receptor, providing similar values of free energy ΔGbind and ΔGPMF in comparison with Homo sapiens model. The recombinant expression in HEK293F cells reached a yield of 25 mg/L, characterized via chromatographic and physical-chemical techniques. This work shows that other Arapaima gigas proteins could be studied in a similar way, using the combination of these techniques, recovering more information from its genome and improving the reproduction and preservation of this prehistoric fish.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-02-13T04:54:53Z
DOI: 10.1177/11779322231154148
Issue No: Vol. 17 (2023)
- Identification of Putative Drug Targets in Highly Resistant Gram-Negative
Bacteria; and Drug Discovery Against Glycyl-tRNA Synthetase as a New
Target
Authors: Sepideh Fereshteh, Narjes Noori Goodarzi, Hourieh Kalhor, Hamzeh Rahimi, Seyed Mahmoud Barzi, Farzad Badmasti
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Background:Gram-negative bacterial infections are on the rise due to the high prevalence of multidrug-resistant bacteria, and efforts must be made to identify novel drug targets and then new antibiotics.Methods:In the upstream part, we retrieved the genome sequences of 4 highly resistant Gram-negative bacteria (e.g., Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterobacter cloacae). The core proteins were assessed to find common, cytoplasmic, and essential proteins with no similarity to the human proteome. Novel drug targets were identified using DrugBank, and their sequence conservancy was evaluated. Protein Data Bank files and STRING interaction networks were assessed. Finally, the aminoacylation cavity of glycyl-tRNA synthetase (GlyQ) was virtually screened to identify novel inhibitors using AutoDock Vina and the StreptomeDB library. Ligands with high binding affinity were clustered, and then the pharmacokinetics properties of therapeutic agents were investigated.Results:A total of 6 common proteins (e.g., RP-L28, RP-L30, RP-S20, RP-S21, Rnt, and GlyQ) were selected as novel and widespread drug targets against highly resistant Gram-negative superbugs based on different criteria. In the downstream analysis, virtual screening revealed that Rimocidin, Flavofungin, Chaxamycin, 11,11′-O-dimethyl-14′-deethyl-14′-methylelaiophylin, and Platensimycin were promising hit compounds against GlyQ protein. Finally, 11,11′-O-dimethyl-14′-deethyl-14′-methylelaiophylin was identified as the best potential inhibitor of GlyQ protein. This compound showed high absorption capacity in the human intestine.Conclusion:The results of this study provide 6 common putative new drug targets against 4 highly resistant and Gram-negative bacteria. Moreover, we presented 5 different hit compounds against GlyQ protein as a novel therapeutic target. However, further in vitro and in vivo studies are needed to explore the bactericidal effects of proposed hit compounds against these superbugs.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-02-13T04:52:45Z
DOI: 10.1177/11779322231152980
Issue No: Vol. 17 (2023)
- A Literature Review: ECG-Based Models for Arrhythmia Diagnosis Using
Artificial Intelligence Techniques
Authors: Abir Boulif, Bouchra Ananou, Mustapha Ouladsine, Stéphane Delliaux
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
In the health care and medical domain, it has been proven challenging to diagnose correctly many diseases with complicated and interferential symptoms, including arrhythmia. However, with the evolution of artificial intelligence (AI) techniques, the diagnosis and prognosis of arrhythmia became easier for the physicians and practitioners using only an electrocardiogram (ECG) examination. This review presents a synthesis of the studies conducted in the last 12 years to predict arrhythmia’s occurrence by classifying automatically different heartbeat rhythms. From a variety of research academic databases, 40 studies were selected to analyze, among which 29 of them applied deep learning methods (72.5%), 9 of them addressed the problem with machine learning methods (22.5%), and 2 of them combined both deep learning and machine learning to predict arrhythmia (5%). Indeed, the use of AI for arrhythmia diagnosis is emerging in literature, although there are some challenging issues, such as the explicability of the Deep Learning methods and the computational resources needed to achieve high performance. However, with the continuous development of cloud platforms and quantum calculation for AI, we can achieve a breakthrough in arrhythmia diagnosis.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-02-10T08:52:56Z
DOI: 10.1177/11779322221149600
Issue No: Vol. 17 (2023)
- In Silico Characterization of the Physicochemical and Biological
Properties of the Pink (Pleurotus djamor var. salmoneostramineus) Oyster
Mushroom Chromoprotein
Authors: Mónica A Valdez-Solana, Erica K Ventura-García, Iván A Corral-Guerrero, Atahualpa Guzmán de Casa, Claudia Avitia-Domínguez, Alfredo Téllez-Valencia, Erick Sierra-Campos
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Cap color is an important commercial trait for oyster mushrooms. Various pigment constituents determine a diverse color. However, the pigments of oyster mushrooms are still ambiguous. The pink oyster mushroom (Pleurotus salmoneostramineus or Pleurotus djamor) chromoprotein is one of the few proteins belonging to this fungus that has a record of its sequence of amino acid residues. However, even though there are studies about this chromoprotein isolation, purification, and crystallization, the current information focused on its 3-dimensional model and the cofactor and prosthetic group (3H-indol-3-one) binding sites is unreliable and fragmented. Therefore, in this study, using free online servers such as Prot pi, GalaxyWEB, MIB, and CB-Dock2, a structural analysis and the prediction of its physicochemical and biological properties were conducted, to understand the possible function of this chromoprotein. The obtained results showed that this molecule is a protein with a molecular weight of 23 712.5 Da, an isoelectric point of 7.505, with oligomerization capacity in a dimer and glycation in the Ser6 residue. In addition, the participation of the residues Leu5, Leu8, Lys211, Ala214, and Gln215 in the binding of the prosthetic group to the protein was highlighted; as well as Ser6 and Pro7 are important residues for the interaction of the Mg2+ ion and eumelanin. Likewise, morphological changes based on different culture conditions (light/dark) showed that this protein is constitutive expressed and independent of blue light. The findings in this study demonstrate that pink chromoprotein is a melanosomal protein, and it possibly has a critical role in melanogenesis and the melanin polymerization. However, more experimental studies are needed to predict a possible mechanism of action and type of enzymatic activity.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-02-09T04:53:01Z
DOI: 10.1177/11779322231154139
Issue No: Vol. 17 (2023)
- In silico Structure Prediction, Molecular Docking, and Dynamic Simulation
of Plasmodium falciparum AP2-I Transcription Factor
Authors: David O Oladejo, Gbolahan O duselu, Titilope M Dokunmu, Itunuoluwa Isewon, Jelili Oyelade, Esther Okafor, Emeka EJ Iweala, Ezekiel Adebiyi
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Plasmodium falciparum Apicomplexan Apetala 2 Invasion (PfAP2-I) transcription factor (TF) is a protein that regulates the expression of a subset of gene families involved in P. falciparum red blood cell (RBC) invasion. Inhibiting PfAP2-I TF with small molecules represents a potential new antimalarial therapeutic target to combat drug resistance, which this study aims to achieve. The 3D model structure of PfAP2-I was predicted ab initio using ROBETTA prediction tool and was validated using Save server 6.0 and MolProbity. Computed Atlas of Surface Topography of proteins (CASTp) 3.0 was used to predict the active sites of the PfAP2-I modeled structure. Pharmacophore modeling of the control ligand and PfAP2-I modeled structure was carried out using the Pharmit server to obtain several compounds used for molecular docking analysis. Molecular docking and postdocking studies were conducted using AutoDock vina and Discovery studio. The designed ligands’ toxicity predictions and in silico drug-likeness were performed using the SwissADME predictor and OSIRIS Property Explorer. The modeled protein structure from the ROBETTA showed a validation result of 96.827 for ERRAT, 90.2% of the amino acid residues in the most favored region for the Ramachandran plot, and MolProbity score of 1.30 in the 98th percentile. Five (5) best hit compounds from molecular docking analysis were selected based on their binding affinity (between −8.9 and −11.7 Kcal/mol) to the active site of PfAP2-I and were considered for postdocking studies. For the absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties, compound MCULE-7146940834 had the highest drug score (0.63) and drug-likeness (6.76). MCULE-7146940834 maintained a stable conformation within the flexible protein’s active site during simulation. The good, estimated binding energies, drug-likeness, drug score, and molecular dynamics simulation interaction observed for MCULE-7146940834 against PfAP2-I show that MCULE-7146940834 can be considered a lead candidate for PfAP2-I inhibition. Experimental validations should be carried out to ascertain the efficacy of these predicted best hit compounds.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-01-21T11:54:01Z
DOI: 10.1177/11779322221149616
Issue No: Vol. 17 (2023)
- Antioxidant and Anti-inflammatory Activity of Sea Cucumber (Holothuria
scabra) Active Compounds against KEAP1 and iNOS Protein
Authors: Teresa Liliana Wargasetia, Hana Ratnawati, Nashi Widodo, Muhammad Hermawan Widyananda
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Oxidative stress and inflammation have a role in the development of various diseases. Oxidative stress and inflammation are associated with many proteins, including Kelch ECH associating protein 1 (KEAP1) and inducible nitric oxide synthase (iNOS) proteins. The active compounds contained in Holothuria scabra have antioxidant and anti-inflammatory properties. This study aimed to evaluate the antioxidant and anti-inflammatory activity of sea cucumber’s active compounds by targeting KEAP1 and iNOS proteins. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) scavenging activity of H. scabra extract were measured spectrophotometrically. The 3-dimensional (3D) structures of sea cucumber’s active compounds and proteins were obtained from the PubChem and Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) databases. Molecular docking was performed using AutoDock Vina software. Molecular dynamics simulations were carried out using Yet Another Scientific Artificial Reality Application (YASARA) software with environmental parameters according to the cell’s physiological conditions. The membrane permeability test was performed using the PerMM web server. The methanol extract of H. scabra had a weak antioxidant activity against DPPH and strong activity against NO radical. Scabraside and holothurinoside G had the most negative binding affinity values when interacting with the active site of KEAP1 and iNOS proteins. Molecular dynamics simulations also showed that both compounds were stable when interacting with KEAP1 and iNOS. However, scabraside and holothurinoside G were difficult to penetrate the cell plasma membrane, which is seen from the high energy transfer value in the lipid acyl chain region of phospholipids. Scabraside and holothurinoside G are predicted to act as antioxidants and anti-inflammations, but in their implementation to in vitro and in vivo study, it is necessary to have liposomes or nanoparticles, or other delivery methods to help these 2 compounds enter the cell.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-01-17T05:23:58Z
DOI: 10.1177/11779322221149613
Issue No: Vol. 17 (2023)
- The Potential of Ameliorating COVID-19 and Sequelae From Andrographis
paniculata via Bioinformatics
Authors: Hien Thi Nguyen, Van Mai Do, Thanh Thuy Phan, Dung Tam Nguyen Huynh
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
The current coronavirus disease 2019 (COVID-19) outbreak is alarmingly escalating and raises challenges in finding efficient compounds for treatment. Repurposing phytochemicals in herbs is an ideal and economical approach for screening potential herbal components against COVID-19. Andrographis paniculata, also known as Chuan Xin Lian, has traditionally been used as an anti-inflammatory and antibacterial herb for centuries and has recently been classified as a promising herbal remedy for adjuvant therapy in treating respiratory diseases. This study aimed to screen Chuan Xin Lian’s bioactive components and elicit the potential pharmacological mechanisms and plausible pathways for treating COVID-19 using network pharmacology combined with molecular docking. The results found terpenoid (andrographolide) and flavonoid (luteolin, quercetin, kaempferol, and wogonin) derivatives had remarkable potential against COVID-19 and sequelae owing to their high degrees in the component-target-pathway network and strong binding capacities in docking scores. In addition, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the PI3K-AKT signaling pathway might be the most vital molecular pathway in the pathophysiology of COVID-19 and long-term sequelae whereby therapeutic strategies can intervene.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-01-12T09:15:25Z
DOI: 10.1177/11779322221149622
Issue No: Vol. 17 (2023)
- Pyridine Derivatives as Potential Inhibitors for Coronavirus SARS-CoV-2: A
Molecular Docking Study
Authors: Kamaraj Karthick, Kalaiyar Swarnalatha
Abstract: Bioinformatics and Biology Insights, Volume 17, Issue , January-December 2023.
Coronavirus SARS-CoV-2, a causative agent for the global epidemic disease COVID-19, which has a highest modality rate. Several initiatives have been undertaken to repurpose current antiviral medications and tested the classic pyridine derivatives (PyDev), which have showed substantial therapeutic potential against a variety of illnesses and also have several biological functions such as, antibacterial, antiviral, and anti-inflammatory. However, limited reports are available for the treatment of Coronavirus SARS-CoV-2 using PyDev. Hence, the possibilities of the best-described PyDev molecules of powerful Coronavirus SARS-CoV-2 inhibitors have been attempted in this investigation. This study primarily focused on blocking four key targets of Coronavirus SARS-CoV-2 proteins. Terpyridine has shown the greatest inhibitory potential (with a binding energy of −8.8 kcal/mol) against all four coronavirus targets. This study results would pave the potential lead medication for Coronavirus SARS-CoV-2 therapeutic strategies.
Citation: Bioinformatics and Biology Insights
PubDate: 2023-01-07T05:36:10Z
DOI: 10.1177/11779322221146651
Issue No: Vol. 17 (2023)
