Showing papers in "Bioinformatics and Biology Insights in 2021"

Structure and Function of Major SARS-CoV-2 and SARS-CoV Proteins.

Abstract: SARS-CoV-2 virus, the causative agent of COVID-19 pandemic, has a genomic organization consisting of 16 nonstructural proteins (nsps), 4 structural proteins, and 9 accessory proteins. Relative of SARS-CoV-2, SARS-CoV, has genomic organization, which is very similar. In this article, the function and structure of the proteins of SARS-CoV-2 and SARS-CoV are described in great detail. The nsps are expressed as a single or two polyproteins, which are then cleaved into individual proteins using two proteases of the virus, a chymotrypsin-like protease and a papain-like protease. The released proteins serve as centers of virus replication and transcription. Some of these nsps modulate the host's translation and immune systems, while others help the virus evade the host immune system. Some of the nsps help form replication-transcription complex at double-membrane vesicles. Others, including one RNA-dependent RNA polymerase and one exonuclease, help in the polymerization of newly synthesized RNA of the virus and help minimize the mutation rate by proofreading. After synthesis of the viral RNA, it gets capped. The capping consists of adding GMP and a methylation mark, called cap 0 and additionally adding a methyl group to the terminal ribose called cap1. Capping is accomplished with the help of a helicase, which also helps remove a phosphate, two methyltransferases, and a scaffolding factor. Among the structural proteins, S protein forms the receptor of the virus, which latches on the angiotensin-converting enzyme 2 receptor of the host and N protein binds and protects the genomic RNA of the virus. The accessory proteins found in these viruses are small proteins with immune modulatory roles. Besides functions of these proteins, solved X-ray and cryogenic electron microscopy structures related to the function of the proteins along with comparisons to other coronavirus homologs have been described in the article. Finally, the rate of mutation of SARS-CoV-2 residues of the proteome during the 2020 pandemic has been described. Some proteins are mutated more often than other proteins, but the significance of these mutation rates is not fully understood.

DEELIG: A Deep Learning Approach to Predict Protein-Ligand Binding Affinity

Abstract: Protein-ligand binding prediction has extensive biological significance. Binding affinity helps in understanding the degree of protein-ligand interactions and is a useful measure in drug design. Pr...

The Relevance of Bioinformatics Applications in the Discovery of Vaccine Candidates and Potential Drugs for COVID-19 Treatment

Abstract: The application of bioinformatics to vaccine research and drug discovery has never been so essential in the fight against infectious diseases. The greatest combat of the 21st century against a debilitating disease agent SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus discovered in Wuhan, China, December 2019, has piqued an unprecedented usage of bioinformatics tools in deciphering the molecular characterizations of infectious pathogens. With the viral genome data of SARS-COV-2 been made available barely weeks after the reported outbreak, bioinformatics platforms have become an all-time critical tool to gain time in the fight against the disease pandemic. Before the outbreak, different platforms have been developed to explore antigenic epitopes, predict peptide-protein docking and antibody structures, and simulate antigen-antibody reactions and lots more. However, the advent of the pandemic witnessed an upsurge in the application of these pipelines with the development of newer ones such as the Coronavirus Explorer in the development of efficacious vaccines, drug repurposing, and/or discovery. In this review, we have explored the various pipelines available for use, their relevance, and limitations in the timely development of useful therapeutic candidates from genomic data knowledge to clinical therapy.

Cloud computing enabled big multi-omics data analytics

Abstract: High-throughput experiments enable researchers to explore complex multifactorial diseases through large-scale analysis of omics data. Challenges for such high-dimensional data sets include storage, analyses, and sharing. Recent innovations in computational technologies and approaches, especially in cloud computing, offer a promising, low-cost, and highly flexible solution in the bioinformatics domain. Cloud computing is rapidly proving increasingly useful in molecular modeling, omics data analytics (eg, RNA sequencing, metabolomics, or proteomics data sets), and for the integration, analysis, and interpretation of phenotypic data. We review the adoption of advanced cloud-based and big data technologies for processing and analyzing omics data and provide insights into state-of-the-art cloud bioinformatics applications.

In Silico Integrative Approach Revealed Key MicroRNAs and Associated Target Genes in Cardiorenal Syndrome.

Abstract: Cardiorenal syndromes constellate primary dysfunction of either heart or kidney whereby one organ dysfunction leads to the dysfunction of another. The role of several microRNAs (miRNAs) has been implicated in number of diseases, including hypertension, heart failure, and kidney diseases. Wide range of miRNAs has been identified as ideal candidate biomarkers due to their stable expression. Current study was aimed to identify crucial miRNAs and their target genes associated with cardiorenal syndrome and to explore their interaction analysis. Three differentially expressed microRNAs (DEMs), namely, hsa-miR-4476, hsa-miR-345-3p, and hsa-miR-371a-5p, were obtained from GSE89699 and GSE87885 microRNA data sets, using R/GEO2R tools. Furthermore, literature mining resulted in the retrieval of 15 miRNAs from scientific research and review articles. The miRNAs-gene networks were constructed using miRNet (a Web platform of miRNA-centric network visual analytics). CytoHubba (Cytoscape plugin) was adopted to identify the modules and the top-ranked nodes in the network based on Degree centrality, Closeness centrality, Betweenness centrality, and Stress centrality. The overlapped miRNAs were further used in pathway enrichment analysis. We found that hsa-miR-21-5p was common in 8 pathways out of the top 10. Based on the degree, 5 miRNAs, namely, hsa-mir-122-5p, hsa-mir-222-3p, hsa-mir-21-5p, hsa-mir-146a-5p, and hsa-mir-29b-3p, are considered as key influencing nodes in a network. We suggest that the identified miRNAs and their target genes may have pathological relevance in cardiorenal syndrome (CRS) and may emerge as potential diagnostic biomarkers.

FastMLST: A Multi-core Tool for Multilocus Sequence Typing of Draft Genome Assemblies

Abstract: Multilocus Sequence Typing (MLST) is a precise microbial typing approach at the intra-species level for epidemiological and evolutionary purposes. It operates by assigning a sequence type (ST) identifier to each specimen, based on a combination of allelic sequences obtained for multiple housekeeping genes included in a defined scheme. The use of MLST has multiplied due to the availability of large numbers of genomic sequences and epidemiological data in public repositories. However, data processing speed has become problematic due to datasets’ massive size. Here, we present FastMLST, a tool that is designed to perform PubMLST searches using BLASTn and a divide-and-conquer approach. Compared to mlst, CGE/MLST, MLSTar, and PubMLST, FastMLST takes advantage of current multi-core computers to simultaneously type thousands of genome assemblies in minutes, reducing processing times by at least 16-fold and with more than 99.95% consistency. Availability and Implementation The source code, installation instructions and documentation are available at https://github.com/EnzoAndree/FastMLST

Prediction of anti-COVID 19 therapeutic power of medicinal Moroccan plants using molecular docking

Abstract: The emerging pathogen SARS-CoV2 causing coronavirus disease 2019 (COVID-19) is a global public health challenge. To the present day, COVID-19 had affected more than 40 million people worldwide. The exploration and the development of new bioactive compounds with cost-effective and specific anti-COVID 19 therapeutic power is the prime focus of the current medical research. Thus, the exploitation of the molecular docking technique has become essential in the discovery and development of new drugs, to better understand drug-target interactions in their original environment. This work consists of studying the binding affinity and the type of interactions, through molecular docking, between 54 compounds from Moroccan medicinal plants, dextran sulfate and heparin (compounds not derived from medicinal plants), and 3CLpro-SARS-CoV-2, ACE2, and the post fusion core of 2019-nCoV S2 subunit. The PDB files of the target proteins and prepared herbal compounds (ligands) were subjected for docking to AutoDock Vina using UCSF Chimera, which provides a list of potential complexes based on the criteria of form complementarity of the natural compound with their binding affinities. The results of molecular docking revealed that Taxol, Rutin, Genkwanine, and Luteolin-glucoside have a high affinity with ACE2 and 3CLpro. Therefore, these natural compounds can have 2 effects at once, inhibiting 3CLpro and preventing recognition between the virus and ACE2. These compounds may have a potential therapeutic effect against SARS-CoV2, and therefore natural anti-COVID-19 compounds.

Prognostic Value Estimation of BRIP1 in Breast Cancer by Exploiting Transcriptomics Data Through Bioinformatics Approaches.

Abstract: BRIP1 (Breast Cancer 1 Interacting Helicase 1) is a tumor suppressor gene that has vital function in preserving the genetic stability by repairing DNA damage though have significant associations with the onset of breast cancer (BC) if mutated or overexpressed. In this study, the prognostic value of BRIP1 gene was evaluated and validated through bioinformatics approaches utilizing transcriptomic (mRNA expression) data from several BC databases. To determine the prognostic value, the expression level of mRNA transcript was analyzed in context of comparison between breast tumor and normal tissues regarding clinical features, breast tumor subtypes, promoter methylation status, correlation level, mutation frequency, and survival of BC patients. BRIP1 expression was found to be significantly overexpressed in various BC molecular subtypes (e.g. PAM50, Sorlie's) and clinical status (estrogen and progesterone receptor) than associated normal tissues which correlated with prognosis. Also, in promoter methylation level, its expression was observed as upregulated-hypomethylated regarding various clinicopathological features. Multiple data mining exhibited positive correlation between BRIP1 and INTS2 (Integrator Complex Subunit 2) expressions in BC. Further, mutation analysis revealed that BRIP1 gene was altered by acquiring both somatic and germline mutations. In addition, a total of 42 mutations; 24 missense, 8 fusion, 7 truncating, and 3 inframe mutations in BC patients was detected in BRIP1 protein. Moreover, higher BRIP1 expression was found to be correlated with poor disease-specific, disease metastasis-free, relapse-free, and overall survivals of BC patients. Since, overexpression of BRIP1 was identified to be associated with different clinical features, breast tumor subtypes, promoter methylation status, and survival of BC patients that may provide a risk of ensuing malignant transformation. Thus, lower expression of BRIP1 might hinder BC prognosis. We consider that this analysis will present a proof for BRIP1 gene to be a noteworthy molecular biomarker for BC prognosis.

In Silico Exploration of Phytoconstituents From Phyllanthus emblica and Aegle marmelos as Potential Therapeutics Against SARS-CoV-2 RdRp.

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has increased the importance of computational tools to design a drug or vaccine in reduced time with minimum risk. Earlier stu...

Significance of African Diets in Biotherapeutic Modulation of the Gut Microbiome.

Abstract: Diet plays an essential role in human development and growth, contributing to health and well-being. The socio-economic values, cultural perspectives, and dietary formulation in sub-Saharan Africa can influence gut health and disease prevention. The vast microbial ecosystems in the human gut frequently interrelate to maintain a healthy, well-coordinated cellular and humoral immune signalling to prevent metabolic dysfunction, pathogen dominance, and induction of systemic diseases. The diverse indigenous diets could differentially act as biotherapeutics to modulate microbial abundance and population characteristics. Such modulation could prevent stunted growth, malnutrition, induction of bowel diseases, attenuated immune responses, and mortality, particularly among infants. Understanding the associations between specific indigenous African diets and the predictability of the dynamics of gut bacteria genera promises potential biotherapeutics towards improving the prevention, control, and treatment of microbiome-associated diseases such as cancer, inflammatory bowel disease, obesity, type 2 diabetes, and cardiovascular disease. The dietary influence of many African diets (especially grain-base such as millet, maize, brown rice, sorghum, soya, and tapioca) promotes gut lining integrity, immune tolerance towards the microbiota, and its associated immune and inflammatory responses. A fibre-rich diet is a promising biotherapeutic candidate that could effectively modulate inflammatory mediators' expression associated with immune cell migration, lymphoid tissue maturation, and signalling pathways. It could also modulate the stimulation of cytokines and chemokines involved in ensuring balance for long-term microbiome programming. The interplay between host and gut microbial digestion is complex; microbes using and competing for dietary and endogenous proteins are often attributable to variances in the comparative abundances of Enterobacteriaceae taxa. Many auto-inducers could initiate the process of quorum sensing and mammalian epinephrine host cell signalling system. It could also downregulate inflammatory signals with microbiota tumour taxa that could trigger colorectal cancer initiation, metabolic type 2 diabetes, and inflammatory bowel diseases. The exploitation of essential biotherapeutic molecules derived from fibre-rich indigenous diet promises food substances for the downregulation of inflammatory signalling that could be harmful to gut microbiota ecological balance and improved immune response modulation.

Prediction of Human-Plasmodium vivax Protein Associations From Heterogeneous Network Structures Based on Machine-Learning Approach.

Abstract: Malaria caused by Plasmodium vivax can lead to severe morbidity and death. In addition, resistance has been reported to existing drugs in treating this malaria. Therefore, the identification of new...

In Silico Characterization of a Hypothetical Protein from Shigella dysenteriae ATCC 12039 Reveals a Pathogenesis-Related Protein of the Type-VI Secretion System:

Abstract: Shigellosis caused by Shigella dysenteriae is a major public health concern worldwide, particularly in developing countries. The bacterial genome is known, but there are many hypothetical proteins ...

Identification of Terpenoids From Abrus precatorius Against Parkinson's Disease Proteins Using In Silico Approach.

Abstract: Parkinson’s disease (PD) is the second major neuro-degenrative disorder that causes morbidity and mortality among older populations. Terpenoids were reported as potential neuro-protective agents. T...

Bioinformatics Analysis Unveils Certain Mutations Implicated in Spike Structure Damage and Ligand-Binding Site of Severe Acute Respiratory Syndrome Coronavirus 2

Abstract: There are certain mutations related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In addition to these known mutations, other new mutations have been found across regions in this study. Based on the results, in which 4,326 SARS-CoV-2 whole sequences were used, some mutations are found to be peculiar with certain regions, while some other mutations are found in all regions. In Asia, mutations (3 different mutations in QLA46612 isolated from South Korea) were found in the same sequence. Although huge number of mutations are detected (more than 70 in Asia) by regions, according to bioinformatics tools, some of them which are G75V (isolated from North America), T95I (isolated from South Korea), G143V (isolated from North America), M177I (isolated from Asia), L293M (isolated from Asia), P295H (isolated from Asia), T393P (isolated from Europe), P507S (isolated from Asia), and D614G (isolated from all regions) (These color used only make correct) predicted a damage to spike' protein structure. Furthermore, this study also aimed to reveal how binding sites of ligands change if the spike protein structure is damaged, and whether more than one mutation affects ligand binding. Mutations that were predicted to damage the structure did not affect the ligand-binding sites, whereas ligands' binding sites were affected in those with multiple mutations. It is thought that this study will give a different perspective to both the vaccine SARS-CoV studies and the change in the structure of the spike protein belonging to this virus against mutations.

Plasma Phospholipids: A Promising Simple Biochemical Parameter to Evaluate COVID-19 Infection Severity

Abstract: Background: Coronavirus-19 (COVID-19) pandemic is a worldwide public health problem that has been known in China since December 25, 2019. Phospholipids are structural components of the mammalian cytoskeleton and cell membranes. They suppress viral attachment to the plasma membrane and subsequent replication in lung cells. In the virus-infected lung, phospholipids are highly prone to oxidation by reactive oxygen species, leading to the production of oxidized phospholipids (OxPLs). Objective: This study was carried out to explain the correlation between the level of plasma phospholipids in patients with COVID-19 infection and the levels of cytokine storms to assess the severity of the disease. Methods: Plasma samples from 34 enrolled patients with mild, moderate, and severe COVID-19 infection were collected. Complete blood count (CBC), plasma levels of D-dimer, ferritin, C-reactive protein (CRP), cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), phospholipids, secretory phospholipase A2 (sPLA2)α2, and cytokine storms were estimated, and lung computed tomography (CT) imaging was detected. Results: The CBC picture showed the presence of leukopenia, lymphopenia, and eosinopenia in patients with COVID-19 infection. Furthermore, a significant increase was found in plasma levels of D-dimer, CRP, ferritin, tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, and IL-13 as well as sPLA2α2 activity compared to normal persons. However, plasma levels of phospholipids decreased in patients with moderate and severe COVID-19 infection, as well as significantly decreased in levels of triacylglycerols and HDL-C in plasma from patients with severe infection only, compared to normal persons. Furthermore, a lung CT scan showed the presence of inflammation in a patient with mild, moderate, and severe COVID-19 infection. Conclusions: This study shows that there is a correlation between plasma phospholipid depletion and elevated cytokine storm in patients with COVID-19 infection. Depletion of plasma phospholipid levels in patients with COVID-19 infection is due to oxidative stress, induction of cytokine storm, and systemic inflammatory response after endothelial cell damage promote coagulation. According to current knowledge, patients with COVID-19 infection may need to administer surfactant replacement therapy and sPLA2 inhibitors to treat respiratory distress syndrome, which helps them to maintain the interconnected surfactant structures. [ FROM AUTHOR] Copyright of Bioinformatics & Biology Insights is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A Computational-Based Drug Repurposing Method Targeting SARS-CoV-2 and its Neurological Manifestations Genes and Signaling Pathways

Abstract: Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a global concern involves infections in multiple organs. Much of the research up to now has been descriptive on neurological manifestations followed by SARS-CoV-2 infection. Despite considerable efforts on effective SARS-CoV-2 vaccine, novel therapeutic options for COVID-19 comorbidities are warranted. One of the fast ways to introduce possible effective drugs for clinical trials is bioinformatics methods. We have conducted a comprehensive enrichment analysis of genes involved in SARS-CoV-2 and neurological disorders associated with COVID-19. For this purpose, gene sets were extracted from the GeneWeaver database. To find out some significant enriched findings for common genes between SARS-CoV-2 and its neurological disorders, several practical databases were used. Finally, to repurpose an efficient drug, DrugBank databases were used. Overall, we detected 139 common genes concerning SARS-CoV-2 and their neurological disorders. Interestingly, our study predicted around 6 existing drugs (ie, carvedilol, andrographolide, 2-methoxyestradiol, etanercept, polaprezinc, and arsenic trioxide) that can be used for repurposing. We found that polaprezinc (zinc l-carnosine) drug is not investigated in the context of COVID-19 till now and it could be used for the treatment of COVID-19 and its neurological manifestations. To summarize, enrichment and network data get us a coherent picture to predict drug repurposing to speed up clinical trials.

DGraph Clusters Flaviviruses and β-Coronaviruses According to Their Hosts, Disease Type, and Human Cell Receptors

Abstract: Motivation:There is a need for rapid and easy-to-use, alignment-free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to vi...

Inhibitory Potential of Phytochemicals on Interleukin-6-Mediated T-Cell Reduction in COVID-19 Patients: A Computational Approach.

Abstract: Background:A recent COVID-19 pandemic has resulted in a large death toll rate globally and even no cure or vaccine has been successfully employed to combat this disease. Patients have been reported...

Anticancer Potential of Moringa oleifera on BRCA-1 Gene: Systems Biology:

Abstract: Breast cancer has consistently been a global challenge that is prevalent among women. There is a continuous increase in the high number of women mortality rates because of breast cancer and affecti...

Performance of Regression Models as a Function of Experiment Noise.

Abstract: Background:A challenge in developing machine learning regression models is that it is difficult to know whether maximal performance has been reached on the test dataset, or whether further model im...

Metagenomics Approaches to Investigate the Gut Microbiome of COVID-19 Patients.

Abstract: Over the last decade, it has become increasingly apparent that the microbiome is a central component in human well-being and illness. However, to establish innovative therapeutic methods, it is crucial to learn more about the microbiota. Thereby, the area of metagenomics and associated bioinformatics methods and tools has become considerable in the study of the human microbiome biodiversity. The application of these metagenomics approaches to studying the gut microbiome in COVID-19 patients could be one of the promising areas of research in the fight against the SARS-CoV-2 infection and disparity. Therefore, understanding how the gut microbiome is affected by or could affect the SARS-CoV-2 is very important. Herein, we present an overview of approaches and methods used in the current published studies on COVID-19 patients and the gut microbiome. The accuracy of these researches depends on the appropriate choice and the optimal use of the metagenomics bioinformatics platforms and tools. Interestingly, most studies reported that COVID-19 patients' microbiota are enriched with opportunistic microorganisms. The choice and use of appropriate computational tools and techniques to accurately investigate the gut microbiota is therefore critical in determining the appropriate microbiome profile for diagnosis and the most reliable antiviral or preventive microbial composition.

In Silico Analysis of Partial Fatty Acid Desaturase 2 cDNA From Reutealis trisperma (Blanco) Airy Shaw

Abstract: Reutealis trisperma oil is a new source for biodiesel production. The predominant fatty acids in this plant are stearic acid (9%), palmitic acid (10%), oleic acid (12%), linoleic acid (19%), and α-...

Comparison of Hyaluronic Acid Biosynthetic Genes From Different Strains of Pasteurella multocida.

Abstract: Pasteurella multocida produces a capsule composed of different polysaccharides according to the capsular serotype (A, B, D, E, and F). Hyaluronic acid (HA) is a component of certain capsular types ...

Expression, Interaction, and Role of Pseudogene Adh6-ps1 in Cancer Phenotypes.

Abstract: Pseudogenes have been classified as functionless and their annotation is an ongoing problem. The Adh6-ps1-a mouse pseudogene belonging to the alcohol dehydrogenase gene complex (Adh) was analyzed to review the conservation, homology, expression, and interactions and identify any role it plays in disease phenotypes using bioinformatics databases. Results showed that Adh6-ps1 have 2 transcripts (processed and unprocessed) which may have emerged from a transposition and duplication event, respectively, and that induced inversions (Uox gene, In(3)11Rk) involving gene complexes associated with Adh6-ps1 have been implicated in a diverse range of diseases. Adh6-ps1 is highly conserved in vertebrates particularly rodents and expressed in the liver. The top 5 MirRNA targets were Mir455, Mir511, Mir1903, Mir361, and Mir669o markers. While much is unknown about Mir1903 and Mir669o, the silencing of Mir455 and Mir511 is linked with hepatocellular carcinoma (HCC), and Mir361 is implicated in endometrial cancers. Given the identified MirRNA interactions with Adh6-ps1 and its expression in HCC and reproductive systems, it may well have a role in tumorigenesis and disease phenotypes. Nonetheless, further studies are required to establish these facts to add to the growing efforts to understand pseudogenes and their potential involvement in disease conditions.

Ligand Docking Methods to Recognize Allosteric Inhibitors for G-Protein-Coupled Receptors.

Abstract: G-protein-coupled receptors (GPCRs) are membrane proteins which play an important role in many cellular processes and are excellent drug targets. Despite the existence of several US Food and Drug A...

In Silico Identification and Functional Characterization of Conserved miRNAs in the Genome of Cryptosporidium parvum.

Abstract: Cryptosporidium parvum, a predominant causal agent of a fatal zoonotic protozoan diarrhoeal disease called cryptosporidiosis, bears a worldwide public health concern for childhood mortality and poses a key threat to the dairy and water industries. MicroRNAs (miRNAs), small but powerful posttranscriptional gene silencing RNA molecules, regulate a variety of molecular, biological, and cellular processes in animals and plants. As to the present date, there is a paucity of information regarding miRNAs of C. parvum; hence, this study was used to identify miRNAs in the organism using a comprehensible expressed sequence tag-based homology search approach consisting of a series of computational screening process from the identification of putative miRNA candidates to the functional annotation of the important gene targets in C. parvum. The results revealed a conserved miRNA that targeted 487 genes in the model organism (Drosophila melanogaster) and 85 genes in C. parvum, of which 11 genes had direct involvements in several crucial virulence factors such as environmental oocyst protection, excystation, locomotion, adhesion, invasion, stress protection, intracellular growth, and survival. Besides, 20 genes showed their association with various major pathways dedicated for the ribosomal biosynthesis, DNA repair, transportation, protein production, gene expression, cell cycle, cell proliferation, development, immune response, differentiation, and nutrient metabolism of the organism in the host. Thus, this study provides a strong evidence of great impact of identified miRNA on the biology, virulence, and pathogenesis of C. parvum. Furthermore, the study suggests that the detected miRNA could be a potential epigenomic tool for controlling the protozoon through silencing those virulent and pathway-related target genes.

Modeling and Molecular Dynamic Simulation of F(ab′)2 Fragment of Nimotuzumab for Lung Cancer Diagnostics:

Abstract: Lung cancer is one of the leading causes of cancer-related deaths in the world among both men and women. Several studies in the literature report that overexpression and mutation of the epidermal g...

Prediction of the Effects of Variants and Differential Expression of Key Host Genes ACE2 , TMPRSS2 , and FURIN in SARS-CoV-2 Pathogenesis: An In Silico Approach.

Abstract: A new strain of the beta coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is solely responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic. Although several studies suggest that the spike protein of this virus interacts with the cell surface receptor, angiotensin-converting enzyme 2 (ACE2), and is subsequently cleaved by TMPRSS2 and FURIN to enter into the host cell, conclusive insight about the interaction pattern of the variants of these proteins is still lacking. Thus, in this study, we analyzed the functional conjugation among the spike protein, ACE2, TMPRSS2, and FURIN in viral pathogenesis as well as the effects of the mutations of the proteins through the implementation of several bioinformatics approaches. Analysis of the intermolecular interactions revealed that T27A (ACE2), G476S (receptor-binding domain [RBD] of the spike protein), C297T (TMPRSS2), and P812S (cleavage site for TMPRSS2) coding variants may render resistance in viral infection, whereas Q493L (RBD), S477I (RBD), P681R (cleavage site for FURIN), and P683W (cleavage site for FURIN) may lead to increase viral infection. Genotype-specific expression analysis predicted several genetic variants of ACE2 (rs2158082, rs2106806, rs4830971, and rs4830972), TMPRSS2 (rs458213, rs468444, rs4290734, and rs6517666), and FURIN (rs78164913 and rs79742014) that significantly alter their normal expression which might affect the viral spread. Furthermore, we also found that ACE2, TMPRSS2, and FURIN proteins are functionally co-related with each other, and several genes are highly co-expressed with them, which might be involved in viral pathogenesis. This study will thus help in future genomics and proteomics studies of SARS-CoV-2 and will provide an opportunity to understand the underlying molecular mechanism during SARS-CoV-2 pathogenesis.

Molecular Modeling and Bioinformatics Analysis of Drug-Receptor Interactions in the System Formed by Glargine, Its Metabolite M1, the Insulin Receptor, and the IGF1 Receptor.

Abstract: Introduction Insulin and insulin-like growth factor type 1 (IGF1) regulate multiple physiological functions by acting on the insulin receptor (IR) and insulin-like growth factor type 1 receptor (IGF1R). The insulin analog glargine differs from insulin in three residues (GlyA21, ArgB31, ArgB32), and it is converted to metabolite M1 (lacks residues ArgB31 and ArgB32) by in vivo processing. It is known that activation of these receptors modulates pathways related to metabolism, cell division, and growth. Though, the structures and structural basis of the glargine interaction with these receptors are not known. Aim To generate predictive structural models, and to analyze the drug/receptor interactions in the system formed by glargine, its metabolite M1, IR, and IGF1R by using bioinformatics tools. Methods Ligand/receptor models were built by homology modeling using SWISSMODEL, and surface interactions were analyzed using Discovery Studio® Visualizer. Target and hetero target sequences and appropriate template structures were used for modeling. Results Our glargine/IR and metabolite M1/IR models showed an overall symmetric T-shaped conformation and full occupancy with four ligand molecules. The glargine/IR model revealed that the glargine residues ArgB31 and ArgB32 fit in a hydrophilic region formed by the α-chain C-terminal helix (αCT) and the cysteine-rich region (CR) domain of this receptor, close to the CR residues Arg270-Arg271-Gln272 and αCT residue Arg717. Regarding IGF1R, homologous ligand/receptor models were further built assuming that the receptor is in a symmetrical T-shaped conformation and is fully occupied with four ligand molecules, similar to what we described for IR. Our glargine/IGF1R model showed the interaction of the glargine residues ArgB31 and ArgB32 with Glu264 and Glu305 in the CR domain of IGF1R. Conclusion Using bioinformatics tools and predictive modeling, our study provides a better understanding of the glargine/receptor interactions.