Cheminformatics-Based Discovery of Potential Chemical Probe Inhibitors of Omicron Spike Protein.

During the past two decades, the world has witnessed the emergence of various SARS-CoV-2 variants with distinct mutational profiles influencing the global health, economy, and clinical aspects of the COVID-19 pandemic. These variants or mutants have raised major concerns regarding the protection provided by neutralizing monoclonal antibodies and vaccination, rates of virus transmission, and/or the risk of reinfection. The newly emerged Omicron, a genetically distinct lineage of SARS-CoV-2, continues its spread in the face of rising vaccine-induced immunity while maintaining its replication fitness. Efforts have been made to improve the therapeutic interventions and the FDA has issued Emergency Use Authorization for a few monoclonal antibodies and drug treatments for COVID-19. However, the current situation of rapidly spreading Omicron and its lineages demands the need for effective therapeutic interventions to reduce the COVID-19 pandemic. Several experimental studies have indicated that the FDA-approved monoclonal antibodies are less effective than antiviral drugs against the Omicron variant. Thus, in this study, we aim to identify antiviral compounds against the Spike protein of Omicron, which binds to the human angiotensin-converting enzyme 2 (ACE2) receptor and facilitates virus invasion. Initially, docking-based virtual screening of the in-house database was performed to extract the potential hit compounds against the Spike protein. The obtained hits were optimized by DFT calculations to determine the electronic properties and molecular reactivity of the compounds. Further, MD simulation studies were carried out to evaluate the dynamics of protein-ligand interactions at an atomistic level in a time-dependent manner. Collectively, five compounds (AKS-01, AKS-02, AKS-03, AKS-04, and AKS-05) with diverse scaffolds were identified as potential hits against the Spike protein of Omicron. Our study paves the way for further in vitro and in vivo studies.

Immunoinformatic approach for the construction of multi-epitopes vaccine against omicron COVID-19 variant.

The newly discovered SARS-CoV-2 Omicron variant B.1.1.529 is a Variant of Concern (VOC) announced by the World Health Organization (WHO). It's becoming increasingly difficult to keep these variants from spreading over the planet. The fifth wave has begun in several countries because of Omicron variant, and it is posing a threat to human civilization. As a result, we need effective vaccination that can tackle Omicron SARS-CoV-2 variants that are bound to emerge. Therefore, the current study is an initiative to design a peptide-based chimeric vaccine that may potentially battle SARS-CoV-2 Omicron variant. As a result, the most relevant epitopes present in the mutagenic areas of Omicron spike protein were identified using a set of computational tools and immunoinformatic techniques to uncover common MHC-1, MHC-II, and B cell epitopes that may have the ability to influence the host immune mechanism. A final of three epitopes from CD8+ T-cell, CD4+ T-cell epitopes, and B-cell were shortlisted from spike protein, and that are highly antigenic, IFN-γ inducer, as well as overlapping for the construction of twelve vaccine models. As a result, the antigenic epitopes were coupled with a flexible and stable peptide linker, and the adjuvant was added at the N-terminal end to create a unique vaccine candidate. The structure of a 3D vaccine candidate was refined, and its quality was assessed by using web servers. However, the applied immunoinformatic study along with the molecular docking and simulation of 12 modeled vaccines constructs against six distinct HLAs, and TLRs (TLR2, and TLR4) complexes revealed that the V1 construct was non-allergenic, non-toxic, highly immunogenic, antigenic, and most stable. The vaccine candidate's stability was confirmed by molecular dynamics investigations. Finally, we studied the expression of the suggested vaccination using codon optimization and in-silico cloning. The current study proposed V1 Multi-Epitope Vaccine (MEV) as a significant vaccine candidate that may help the scientific community to treat SARS-CoV-2 infections.

Deciphering the Impact of Mutations on the Binding Efficacy of SARS-CoV-2 Omicron and Delta Variants With Human ACE2 Receptor

The pandemic of COVID-19, caused by SARS-CoV-2, has globally affected the human health and economy. Since the emergence of the novel coronavirus SARS-CoV-2, the life-threatening virus continues to mutate and evolve. Irrespective of acquired natural immunity and vaccine-induced immunity, the emerging multiple variants are growing exponentially, crossing the territorial barriers of the modern world. The rapid emergence of SARS-CoV-2 multiple variants challenges global researchers regarding the efficacy of available vaccines and variant transmissibility. SARS-CoV-2 surface-anchored S-protein recognizes and interacts with the host-cell ACE2, facilitating viral adherence and entrance into the cell. Understanding the interfacial interactions between the spike protein of SARS-CoV-2 variants and human ACE2 receptor is important for the design and development of antiviral therapeutics against SARS-CoV-2 emerging variants. Despite extensive research, the crucial determinants related to the molecular interactions between the spike protein of SARS-CoV-2 variants and host receptors are poorly understood. Thus, in this study, we explore the comparative interfacial binding pattern of SARS-CoV-2 spike RBD of wild type, Delta, and Omicron with the human ACE2 receptor to determine the crucial determinants at the atomistic level, using MD simulation and MM/GBSA energy calculations. Based on our findings, the substitution of Q493R, G496S, Q498R, and Y505H induced internal conformational changes in Omicron spike RBD, which leads to higher binding affinity than Delta spike RBD with the human ACE2 receptor, eventually contributing to higher transmission and infectivity. Taken together, these results could be used for the structure-based design of effective antiviral therapeutics against SARS-CoV-2 variants.

Probing CAS database as prospective antiviral agents against SARS-CoV-2 main protease.

The pandemic of COVID-19 has an unprecedented impact on global health and economy. The novel SARS-CoV-2 is recognized as the etiological agent of current outbreak. Because of its contagious human-to-human transmission, it is an utmost global health emergency at present. To mitigate this threat many scientists and researchers are racing to develop antiviral therapy against the virus. Unfortunately, to date no vaccine or antiviral therapeutic is approved thus there is an urgent need to discover antiviral agent to help the individual who are at high risk. Virus main protease or chymotrypsin-like protease plays a pivotal role in virus replication and transcription; thus, it is considered as an attractive drug target to combat the COVID-19. In this study, multistep structure based virtual screening of CAS antiviral database is performed for the identification of potent and effective small molecule inhibitors against chymotrypsin-like protease of SARS-CoV-2. Consensus scoring strategy combine with flexible docking is used to extract potential hits. As a result of extensive virtual screening, 4 hits were shortlisted for MD simulation to study their stability and dynamic behavior. Insight binding modes demonstrated that the selected hits stabilized inside the binding pocket of the target protein and exhibit complementarity with the active site residues. Our study provides compounds for further in vitro and in vivo studies against SARS-CoV-2.

Identification of chymotrypsin-like protease inhibitors of SARS-CoV-2 via integrated computational approach.

Recently, the world has witnessed outbreak of a novel Coronavirus (SARS-CoV-2), the virus which initially emerged in Wuhan, China has now made its way to a large part of the world, resulting in a public emergency of international concern. The functional importance of Chymotrypsin-like protease (3CLpro) in viral replication and maturation turns it into an attractive target for the development of effective antiviral drugs against SARS and other coronaviruses. At present, there is no standard drug regime nor any vaccine available against the infection. The rapid development and identification of efficient interventions against SARS-CoV-2 remains a major challenge. Based on the available knowledge of closely related coronavirus and their safety profiles, repurposing of existing antiviral drugs and screening of available databases is considered a near term strategic and economic way to contain the SARS-CoV-2 pandemic. Herein, we applied computational drug design methods to identify Chymotrypsin-like protease inhibitors from FDA approved antiviral drugs and our in-house database of natural and drug-like compounds of synthetic origin. As a result three FDA approved drugs (Remdesivir, Saquinavir and Darunavir) and two natural compounds (. flavone and coumarine derivatives) were identified as promising hits. Further, MD simulation and binding free energy calculations were performed to evaluate the dynamic behavior, stability of protein-ligand contact, and binding affinity of the hit compounds. Our results indicate that the identified compounds can inhibit the function of Chymotrypsin-like protease (3CLpro) of Coronavirus. Considering the severity of the spread of coronavirus, the current study is in-line with the concept of finding the new inhibitors against the vital pathway of the corona virus to expedite the process of drug discovery.Communicated by Ramaswamy H. Sarma.