Epitope Based Peptide Prediction from Proteome of Enterotoxigenic E.coli

In Silico Investigation against Inhibitors of Alpha-Amylase Using Structure-based Screening, Molecular Docking, and Molecular Simulations Studies

Type-II diabetes mellitus is a chronic disorder that results from fluctuations in the glucose level leading to hyperglycemia with severe adverse effects increasing worldwide. Alpha-Amylase is the key enzyme involved in the mechanism of glucose formation therefore Alpha-Amylase inhibitors have become a therapeutic target in the development of new leads as they have the potential to suppress glucose levels. Existing drugs targeting Alpha-Amylase highlight major drawbacks in terms of poor absorption rate that causes several gastrointestinal issues. So, this research is aimed to develop novel inhibitors interacting with Alpha-Amylase's active site using structural-based screening, binding pattern analysis, and molecular dynamic simulation. Hence, to search for a potential lead, we analyzed a total of 133 valiolamine derivatives and 535 desoxynojirimycin derivatives that exhibited drug-like properties screened through Lipinski filters. Virtual screening followed by binding interaction analysis we identified ten compounds that exhibited better binding energy scores compared to the standard drugs voglibose and miglitol, used in our study. The docking analysis, ADMET and metabolic site prediction estimated the best top two compounds with good drug profiles. Further, top compounds VG9 and VG15 were promoted to simulation study using the Biovia Discovery study to access the stability at a time interval of 100 ns. MD simulation results revealed that our compound VG9 possesses better conformational stability in the complex to the active site residues of Alpha-Amylase target protein than standard drug voglibose. Thus, our investigation revealed that compound VG9 also exhibits the best pharmacokinetic as well as binding affinity results and could act as a potential lead compound targeting Alpha-Amylase for Type II diabetes.

An integrative docking and simulation-based approach towards the development of epitope-based vaccine against enterotoxigenic Escherichia coli

Enterotoxigenic E.coli is causing diarrheal illness in children as well as adults with the majority of the cases occurring in developing countries. To reduce the number of cases occurring worldwide, the development of an effectual vaccine against these bacteria can be the only prevention. This conjectural work was performed using modern bioinformatics tools for investigation of proteome of ETEC strain E24377A. Different computational vaccinology approaches were deployed to assess several parameters including antigenicity, allergenicity, stability, localization, molecular weight and toxicity of the predicted epitopes required for good vaccine candidate to elicit immune response against diarrhea. We estimated two known control antigens, epitope ¹⁴¹STLPETTVV¹⁴⁹ of Hepatitis B virus and epitope ²⁶⁵ILRGSVAHK²⁷³ of H1N1 Nucleoprotein in an attempt to corroborate our research work. Furthermore molecular docking was performed to evaluate the interaction between HLA allele and peptide, the peptide QYGGGNSAL and peptide LPYFELRWL were considered to be the most promiscuous T cell epitopes with the highest binding energy value of −2.09 kcal/mol and −1.84 kcal/mol, respectively. In addition, dynamic simulation revealed good stability of the vaccine construct as well as population coverage analysis exhibits the highest population coverage in the regions of East Asia, India, Northeast Asia, South Asia and North America. Therefore, these two epitopes can be further synthesized for wet lab analysis and could be considered as a promising vaccine against diarrhea.

Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2

With an increasing fatality rate, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has emerged as a promising threat to human health worldwide. Recently, the World Health Organization (WHO) has announced the infectious disease caused by SARS-CoV-2, which is known as coronavirus disease-2019 (COVID-2019), as a global pandemic. Additionally, the positive cases are still following an upward trend worldwide and as a corollary, there is a need for a potential vaccine to impede the progression of the disease. Lately, it has been documented that the nucleocapsid (N) protein of SARS-CoV-2 is responsible for viral replication and interferes with host immune responses. We comparatively analyzed the sequences of N protein of SARS-CoV-2 for the identification of core attributes and analyzed the ancestry through phylogenetic analysis. Subsequently, we predicted the most immunogenic epitope for the T-cell and B-cell. Importantly, our investigation mainly focused on major histocompatibility complex (MHC) class I potential peptides and NTASWFTAL interacted with most human leukocyte antigen (HLA) that are encoded by MHC class I molecules. Further, molecular docking analysis unveiled that NTASWFTAL possessed a greater affinity towards HLA and also available in a greater range of the population. Our study provides a consolidated base for vaccine design and we hope that this computational analysis will pave the way for designing novel vaccine candidates.