Optimization of protein-protein docking for predicting Fc-protein interactions

Development of a Multiepitope Vaccine Against SARS-CoV-2: Immunoinformatics Study

Background

Since the first appearance of SARS-CoV-2 in China in December 2019, the world witnessed the emergence of the SARS-CoV-2 outbreak. Due to the high transmissibility rate of the virus, there is an urgent need to design and develop vaccines against SARS-CoV-2 to prevent more cases affected by the virus.

Objective

A computational approach is proposed for vaccine design against the SARS-CoV-2 spike (S) protein, as the key target for neutralizing antibodies, and envelope (E) protein, which contains a conserved sequence feature.

Methods

We used previously reported epitopes of S protein detected experimentally and further identified a collection of predicted B-cell and major histocompatibility (MHC) class II–restricted T-cell epitopes derived from E proteins with an identical match to SARS-CoV-2 E protein.

Results

The in silico design of our candidate vaccine against the S and E proteins of SARS-CoV-2 demonstrated a high affinity to MHC class II molecules and effective results in immune response simulations.

Conclusions

Based on the results of this study, the multiepitope vaccine designed against the S and E proteins of SARS-CoV-2 may be considered as a new, safe, and efficient approach to combatting the COVID-19 pandemic.

Comprehensive analysis of carbohydrate-protein recognition in the Protein Data Bank

Carbohydrate-protein interactions underpin wide-ranging aspects of biology. However, such interactions remain relatively unexplored in pharmaceutical and biotechnological applications, in part due to the challenges associated with their structural characterisation, both experimentally and computationally. Knowledge-based approaches have shown great success in the prediction of drug-protein and protein-protein interactions, although have not been comprehensively investigated for carbohydrate-protein interactions. In this work, carbohydrate-protein complexes from the Protein Data Bank were comprehensively obtained and analysed to identify patterns in how carbohydrate-protein interactions are mediated.

An in-silico approach to develop of a multi-epitope vaccine candidate against SARS-CoV-2 envelope (E) protein

Since the first appearance of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS- CoV-2) in China on December 2019, the world has now witnessed the emergence of the SARS- CoV-2 outbreak. Therefore, due to the high transmissibility rate of virus, there is an urgent need to design and develop vaccines against SARS-CoV-2 to prevent more cases affected by the virus. In this study, a computational approach is proposed for vaccine design against the envelope (E) protein of SARS-CoV-2, which contains a conserved sequence feature. First, we sought to gain potential B-cell and T-cell epitopes for vaccine designing against SARS-CoV-2. Second, we attempted to develop a multi-epitope vaccine. Immune targeting of such epitopes could theoretically provide defense against SARS-CoV-2. Finally, we evaluated the affinity of the vaccine to major histocompatibility complex (MHC) molecules to stimulate the immune system response to this vaccine. We also identified a collection of B-cell and T-cell epitopes derived from E proteins that correspond identically to SARS-CoV-2 E proteins. The in-silico design of our potential vaccine against E protein of SARS-CoV-2 demonstrated a high affinity to MHC molecules, and it can be a candidate to make a protection against this pandemic event.

Wnt Binding Affinity Prediction for Putative Frizzled-Type Cysteine-Rich Domains

Several proteins other than the frizzled receptors (Fzd) and the secreted Frizzled-related proteins (sFRP) contain Fzd-type cysteine-rich domains (CRD). We have termed these domains “putative Fzd-type CRDs”, as the relevance of Wnt signalling in the majority of these is unknown; the RORs, an exception to this, are well known for mediating non-canonical Wnt signalling. In this study, we have predicted the likely binding affinity of all Wnts for all putative Fzd-type CRDs. We applied both our previously determined Wnt‒Fzd CRD binding affinity prediction model, as well as a newly devised model wherein the lipid term was forced to contribute favourably to the predicted binding energy. The results obtained from our new model indicate that certain putative Fzd CRDs are much more likely to bind Wnts, in some cases exhibiting selectivity for specific Wnts. The results of this study inform the investigation of Wnt signalling modulation beyond Fzds and sFRPs.

Vaccine Target Discovery

With the rise in novel infectious agents and disease pandemics, a new era of vaccine discovery is necessary. To address this, the new field of immunomics is described, which is synergistically powered by integrating bioinformatics methodologies with technological advances in biology and high-throughput instrumentation. By incorporating biological data from immunology and molecular biology with current genomics and proteomics, immunomics is geared to deliver an insight into immune function, optimal stimulation of immune responses and precise mapping and rational selection of immune targets that cover antigenic diversity. These efforts are expected to contribute towards the development of new generation of vaccines, tailored to both the genetic make-up of the human population and of the pathogen. Vaccine technologies are also being explored for prevention or control of non-communicable diseases.

Structural insights into suppressor of cytokine signaling 1 protein- identification of new leads for type 2 diabetes mellitus

The study considers the Suppressor of cytokine signaling 1 (SOCS1) protein as a novel Type 2 diabetes mellitus (T2DM) drug target. T2DM in human beings is also triggered by the over expression of SOCS proteins. The SOCS1 acts as a ubiquitin ligase (E3), degrades Insulin Receptor Substrate 1 and 2 (IRS1 and IRS2) proteins, and causes insulin resistance. Therefore, the structure of the SOCS1 protein was evaluated using homology-modeling and molecular dynamics methods and validated using standard computational protocols. The Protein-Protein docking study of SOCS1 with its natural substrates, IRS1 and IRS2, and subsequent solvent accessible surface area analysis gave insight into the binding region of the SOCS1 protein. The in silico active site prediction tools highlight the residues Val155 to Ile211 in SOCS1 being implicated in the ubiquitin mediated protein degradation of the proteins IRS1 and IRS2. Virtual screening in the active site region, using large structural databases, results in selective lead structures with 3-Pyridinol, Xanthine, and Alanine moieties as Pharmacophore. The virtual screening study shows that the residues Glu149, Gly187, Arg188, Leu191, and Ser205 of the SOCS1 are important for binding. The docking study with current anti-diabetic therapeutics shows that the drugs Glibenclamide and Glyclopyramide have a partial affinity towards SOCS1. The predicted ADMET and IC₅₀ properties for the identified ligands are within the acceptable range with drug-like properties. The structural data of SOCS1, its active site, and the identified lead structures are expedient in the development of new T2DM therapeutics.

Computational Modelling of Protein Complex Structure and Assembly

Sequence and structure space are nowadays sufficiently large that we can use computational methods to model the structure of proteins based on sequence similarity alone. Not only useful as a standalone tool, homology modelling has also had a transformative effect on the ease with which we can solve crystal structures and electron density maps. Another technique-molecular dynamics-aims to model protein structures from first principles and, thanks to increases in computational power, is slowly becoming a viable tool for studying protein complexes. Finally, the prediction of protein assembly pathways from three-dimensional structures of complexes is also now becoming possible.