Quantifying Mutational Response to Track the Evolution of SARS-CoV-2 Spike Variants: Introducing a Statistical-Mechanics-Guided Machine Learning Method

The emergence of SARS-CoV-2 and its variants that critically affect global public health requires characterization of mutations and their evolutionary pattern from specific Variants of Interest (VOIs) to Variants of Concern (VOCs). Leveraging the concept of equilibrium statistical mechanics, we introduce a new responsive quantity defined as "Mutational Response Function (MRF)" aptly quantifying domain-wise average entropy-fluctuation in the spike glycoprotein sequence of SARS-CoV-2 based on its evolutionary database. As the evolution transits from a specific variant to VOC, we find that the evolutionary crossover is accompanied by a dramatic change in MRF, upholding the characteristic of a dynamic phase transition. With this entropic information, we have developed an ancestral-based machine learning method that helps predict future domain-specific mutations. The feedforward binary classification model pinpoints possible residues prone to future mutations that have implications for enhanced fusogenicity and pathogenicity of the virus. We believe such MRF analyses followed by a statistical mechanics augmented ML approach could help track different evolutionary stages of such species and identify a critical evolutionary transition that is alarming.

A Computational Study on the Interaction of NSP10 and NSP14: Unraveling the RNA Synthesis Proofreading Mechanism in SARS-CoV-2, SARS-CoV, and MERS-CoV

The interaction of exoribonuclease (ExoN) nonstructural protein (NSP14) with NSP10 co-factors is crucial for high-fidelity proofreading activity of coronavirus replication and transcription. Proofreading function is critical for maintaining the large genomes to ensure replication proficiency; therefore, while maintaining the viral replication fitness, quick resistance has been reported to the nucleotide analogue (NA) drugs. Therefore, targeting the NSP14 and NSP10 interacting interface with small molecules or peptides could be a better strategy to obstruct replication processes of coronaviruses (CoVs). A comparative study on the binding mechanism of NSP10 with the NSP14 ExoN domain of SARS-CoV-2, SARS-CoV, MERS-CoV, and four SARS-CoV-2 NSP14mutant complexes has been carried out. Protein-protein interaction (PPI) dynamics, per-residue binding free energy (BFE) analyses, and the identification of interface hotspot residues have been studied using molecular dynamics simulations and various computational tools. The BFE of the SARS-CoV NSP14-NSP10 complex was higher when compared to novel SARS-CoV-2 and MERS. However, SARS-CoV-2 NSP14mutant systems display a higher BFE as compared to the wild type (WT) but lower than SARS-CoV and MERS. Despite the high BFE, the SARS-CoV NSP14-NSP10 complex appears to be structurally more flexible in many regions especially the catalytic site, which is not seen in SARS-CoV-2 and its mutant or MERS complexes. The significantly high residue energy contribution of key interface residues and hotspots reveals that the high binding energy between NSP14 and NSP10 may enhance the functional activity of the proofreading complex, as the NSP10-NSP14 interaction is essential in maintaining the stability of the ExoN domain for the replicative fitness of CoVs. The factors discussed for SARS-CoV-2 complexes may be responsible for NSP14 ExoN having a high replication proficiency, significantly leading to the evolution of new variants of SARS-CoV-2. The NSP14 residues V66, T69, D126, and I201and eight residues of NSP10 (L16, F19, V21, V42, M44, H80, K93, and F96) are identified as common hotspots. Overall, the interface area, hotspot locations, bonded/nonbonded contacts, and energies between NSP14 and NSP10 may pave a way in designing potential inhibitors to disrupt NSP14-NSP10 interactions of CoVs especially SARS-CoV-2.

Spike Protein and the Various Cell-Surface Carbohydrates: An Interaction Study

The SARS-CoV-2 virus has been known to gain entry into the host cell through the spike protein that binds to the host ACE2 cell surface protein. However, the role of the putative sugar-binding sites in the spike protein has remained unclear. We provide a comprehensive in silico outlook into the infection initiation wherein the virus first recognizes the sialosides on the cell via its S1A domain of the spike protein as it surfs over the cell surface. This facilitates the subsequent interaction with the cellular glycosaminoglycans through the S1B domain of the spike protein as it binds to the ACE2 receptor. The unique coadaptation to recognize both the host protein and the cell-surface carbohydrate receptors provides an additional coupling mechanism for efficient viral attachment and infection.

Drug Repurposing to Identify Nilotinib as a Potential SARS-CoV-2 Main Protease Inhibitor: Insights from a Computational and In Vitro Study

COVID-19, an acute viral pneumonia, has emerged as a devastating pandemic. Drug repurposing allows researchers to find different indications of FDA-approved or investigational drugs. In this current study, a sequence of pharmacophore and molecular modeling-based screening against COVID-19 Mpro (PDB: 6LU7) suggested a subset of drugs, from the Drug Bank database, which may have antiviral activity. A total of 44 out of 8823 of the most promising virtual hits from the Drug Bank were subjected to molecular dynamics simulation experiments to explore the strength of their interactions with the SARS-CoV-2 Mpro active site. MD findings point toward three drugs (DB04020, DB12411, and DB11779) with very low relative free energies for SARS-CoV-2 Mpro with interactions at His41 and Met49. MD simulations identified an additional interaction with Glu166, which enhanced the binding affinity significantly. Therefore, Glu166 could be an interesting target for structure-based drug design. Quantitative structural-activity relationship analysis was performed on the 44 most promising hits from molecular docking-based virtual screening. Partial least square regression accurately predicted the values of independent drug candidates' binding energy with impressively high accuracy. Finally, the EC50 and CC50 of 10 drug candidates were measured against SARS-CoV-2 in cell culture. Nilotinib and bemcentinib had EC50 values of 2.6 and 1.1 μM, respectively. In summary, the results of our computer-aided drug design provide a roadmap for rational drug design of Mpro inhibitors and the discovery of certified medications as COVID-19 antiviral therapeutics.

A Multi-omics Longitudinal Study Reveals Alteration of the Leukocyte Activation Pathway in COVID-19 Patients

Severe coronavirus disease 2019 (COVID-19) infection may lead to lung injury, multi-organ failure, and eventually death. Cytokine storm due to excess cytokine production has been associated with fatality in severe infections. However, the specific molecular signatures associated with the elevated immune response are yet to be elucidated. We performed a mass-spectrometry-based proteomic and metabolomic analysis of COVID-19 plasma samples collected at two time points. Using Orbitrap Fusion LC-MS/MS-based label-free proteomic analysis, we identified around 10 significant proteins, 32 significant peptides, and 5 metabolites that were dysregulated at the severe time points. Few of these proteins identified by quantitative proteomics were validated using the multiple reaction monitoring (MRM) assay. Integrated pathway analysis using distinct proteomic and metabolomic signatures revealed alterations in complement and coagulation cascade, platelet aggregation, myeloid leukocyte activation pathway, and arginine metabolism. Further, we highlight the role of leukocyte activation and arginine metabolism in COVID-19 pathogenesis and targeting these pathways for COVID-19 therapeutics.

Brain Imaging in COVID-19

Considering the neurological and neuropsychiatric manifestations of coronavirus disease 2019 (COVID-19), its early diagnosis is crucial. This Viewpoint aims to highlight these manifestations through multimodal neuroimaging studies reflecting neurochemical and structural impairment.