SARS-CoV-2 Omicron Spike shows strong binding affinity and favourable interaction landscape with the TLR4/MD2 compared to other variants.

Emergences of SARS-CoV-2 variants have made the pandemic more critical. Toll-like receptor 4 (TLR4) recognizes the molecular patterns of pathogens and activates the production of proinflammatory cytokines to restrain the infection. We have identified a molecular basis of interaction between the Spike and TLR4 of SARS-CoV-2 and its present and past VOCs (variant- of concern) through in silico analysis. The interaction of wild type Spike with TLR4 showed 15 number hydrogen bonds formation. Similarly, the Alpha variants' Spike with the TLR4 has illustrated that 14 hydrogen bonds participated in the interaction. However, the Delta Spike and TLR4 interaction interface showed that 17 hydrogen bonds were formed during the interaction. Furthermore, Omicron S-glycoprotein and TLR4 interaction interface was depicted (interaction score: -170.3), and 16 hydrogen bonds were found to have been formed in the interaction. Omicron S-glycoprotein shows stronger binding affinity with the TLR4 than wild type, Alpha, and Delta variants. Similarly, the Alpha Spike shows higher binding affinity with TLR4 than the wild type and Delta variant. Now, it is an open question of the molecular basis of the interaction of Spike and TLR4 and the activated downstream signaling events of TLR4 for SARS-CoV-2 and its variants.

B.1.1.7 (Alpha) variant is the most antigenic compared to Wuhan strain, B.1.351, B.1.1.28/triple mutant and B.1.429 variants.

The rapid spread of the SARS-CoV-2 virus and its variants has created a catastrophic impact worldwide. Several variants have emerged, including B.1.351 (Beta), B.1.1.28/triple mutant (P.1), B.1.1.7 (Alpha), and B.1.429 (Epsilon). We performed comparative and comprehensive antigenicity mapping of the total S-glycoprotein using the Wuhan strain and the other variants and identified 9-mer, 15-mer, and 20-mer CTL epitopes through in silico analysis. The study found that 9-mer CTL epitope regions in the B.1.1.7 variant had the highest antigenicity and an average of the three epitope types. Cluster analysis of the 9-mer CTL epitopes depicted one significant cluster at the 70% level with two nodes (KGFNCYFPL and EGFNCYFPL). The phage-displayed peptides showed mimic 9-mer CTL epitopes with three clusters. CD spectra analysis showed the same band pattern of S-glycoprotein of Wuhan strain and all variants other than B.1.429. The developed 3D model of the superantigen (SAg)-like regions found an interaction pattern with the human TCR, indicating that the SAg-like component might interact with the TCR beta chain. The present study identified another partial SAg-like region (ANQFNSAIGKI) from the S-glycoprotein. Future research should examine the molecular mechanism of antigen processing for CD8+ T cells, especially all the variants' antigens of S-glycoprotein.

Antiferromagnetically coupled double perovskite as an efficient and robust catalyst for visible light driven water splitting at neutral pH.

Green and sustainable energy production through renewable sources is an enormously exciting field of research. Herein, we report an A-site lanthanum doped oxygen excess ruthenate (predominantly Ru5+-ions) double perovskite system, CaLaScRuO6+δ (CLSR), as an excellent photocatalyst for water splitting. The well characterized polycrystalline compound shows canted antiferromagnetic (AFM) behavior due to the existence of disordered Ru-ions at the B-site. Based on density functional theory + U (Hubbard U) calculations, we have estimated various magnetic exchange interactions and found that the ground state is antiferromagnetic in nature which is in perfect agreement with our experimental results. Detailed analysis of the electronic structure further reveals that the present system belongs to the family of charge transfer semiconductors with an energy gap of ∼0.45 eV. Finally, the material is found to proficiently work for the oxygen evolution reaction (OER) via visible-light driven water splitting at neutral pH in an ecofriendly manner.

TN strain proteome mediated therapeutic target mapping and multi-epitopic peptide-based vaccine development for Mycobacterium leprae.

Leprosy is a significant universal health problem that is remarkably still a concern in developing countries due to infection frequency. New therapeutic molecules and next-generation vaccines are urgently needed to accelerate the leprosy-free world. In this direction, the present study was performed using two routes: proteome-mediated therapeutic target identification and mapping as well as multi-epitopic peptide-based novel vaccine development using state of the art of computational biology for the TN strain of M. leprae. The TN strain was selected from 65 Mycobacterium strains, and TN strain proteome mediated 83 therapeutic protein targets were mapped and characterized according to subcellular localization. Also, drug molecules were mapped with respect to protein targets localization. The Druggability potential of proteins was also evaluated. For multi-epitope peptide-based vaccine development, the four common types of B and T cell epitopes were identified (SLFQSHNRK, VVGIGQHAA, MMHRSPRTR, LGVDQTQPV) and combined with the suitable peptide linker. The vaccine component had an acceptable protective antigenic score (0.9751). The molecular docking of vaccine components with TLR4/MD2 complex exhibited a low ACE value (-244.12) which signifies the proper binding between the two molecules. The estimated free Gibbs binding energy ensured accurate protein-protein interactions (-112.46 kcal/mol). The vaccine was evaluated through adaptive immunity stimulation as well as immune interactions. The molecular dynamic simulation was carried out by using CHARMM topology-based parameters to minimize the docked complex. Subsequently, the Normal Mode Analysis in the internal coordinates showed a low eigen-value (1.3982892e-05), which also signifies the stability of molecular docking. Finally, the vaccine components were adopted for reverse transcription and codon optimization in E. coli strain K12 for the pGEX-4T1 vector, which supports in silico cloning of the vaccine components against the pathogen. The study directs the experimental study for therapeutics molecules discovery and vaccine candidate development with higher reliability.

SARS-CoV-2 protein drug targets landscape: a potential pharmacological insight view for the new drug development.

Introduction: Protein drug targets play a significant choice in different stages of the drug discovery process. There is an urgent need to understand the drug discovery approaches and protein drug targets (PDT) of SARS-CoV-2, with structural insights for the development of SARS-CoV-2 drugs through targeted therapeutic approach.Areas covered: We have described the protein as a drug target class and also discussed various drug discovery approaches for SARS-CoV-2 involving the protein drug targets such as drug repurposing study, designing of viral entry inhibitors, viral replication inhibitors, and different enzymes of the virus. We have performed comprehensive literature search from the popular databases such as PubMed Google scholar, Web of Science, and Scopus. Finally, we have illustrated the structural landscape of different significant viral proteins (3 CLpro or Mpro, PLpro, RdRp, helicase, S protein) and host proteins as drug targets (cathepsin L, furin, TMPRSS2, ACE2).Expert opinion: The structural landscape of PDT with their binding pockets, and significant residues involved in binding has been discussed further to better understand the PDT and the structure-based drug discovery for SARS-CoV-2. This attempt will increase more therapeutic options, and combination therapies with a multi-target strategy.

Immunoinformatics approach to understand molecular interaction between multi-epitopic regions of SARS-CoV-2 spike-protein with TLR4/MD-2 complex.

BACKGROUND: The coronavirus (CoV) spike (S) protein is critical for receptor binding, membrane fusion and internalization of the virus into the human cells. We have tried to search the epitopic component of the S-protein that might be served as crucial targets for the vaccine development and also tried to understand the molecular mechanism of epitopes and TLR4/MD-2 complex for adaptive immunity. MATERIAL AND METHODS: Here we identified the antigenicity and the epitopic divergence of S-protein via immunoinformatics approach. The study was performed to identify the epitopes, composition of amino acids and its distribution in epitopic regions, composition of amino acid between the identified epitopes, secondary structure architecture of epitopes, physicochemical and biochemical parameters and molecular interaction between the identified epitope and TLR4/MD-2 complex. The SARS-CoV-2 can be possibly recognised by TLR4 of host immune cells that are responsible for the adaptive immune response. RESULTS: We identified four SARS-CoV-2 S-protein 9mer antigenic epitopes and observed that they bind with the TLR4/MD-2 complex by varied stable molecular bonding interactions. Molecular interaction between these characterized epitopes with TLR4/MD-2 complex might be indicated the binding affinity and downstream signalling of adaptive immune response. Different physicochemical and biochemical parameters such as O-glycosylation and N-glycosylation, Hydrophobicity, GRAVY were identified within epitopic regions of S-protein. These parameters help to understand the protein-protein interaction between epitopes and TLR4/MD-2 complex. The study also revealed different epitopic binding pockets of TLR4/MD-2 complex. CONCLUSIONS: The identified epitopes impart suitable prospects for the development of novel peptide-based epitopic vaccine for the control of COVID-19 infection.

Identification and Design of a Next-Generation Multi Epitopes Bases Peptide Vaccine Candidate Against Prostate Cancer: An In Silico Approach.

Prostate cancer (PCa) is the second most diagnosed cancer in men and ranked fifth in overall cancer diagnosis. During the past decades, it has arisen as a significant life-threatening disease in men at an older age. At the early onset of illness when it is in localized form, radiation and surgical treatments are applied against this disease. In case of adverse situations androgen deprivation therapy, chemotherapy, hormonal therapy, etc. are widely used as a therapeutic element. However, studies found the occurrences of several side effects after applying these therapies. In current work, several immunoinformatic techniques were applied to formulate a multi-epitopic vaccine from the overexpressed antigenic proteins of PCa. A total of 13 epitopes were identified from the five prostatic antigenic proteins (PSA, PSMA, PSCA, STEAP, and PAP), after validation with several in silico tools. These epitopes were fused to form a vaccine element by (GGGGS)3 peptide linker. Afterward, 5, 6-dimethylxanthenone-4-acetic acid (DMXAA) was used as an adjuvant to initiate and induce STING-mediated cytotoxic cascade. In addition, molecular docking was performed between the vaccine element and HLA class I antigen with the low ACE value of -251 kcal/mol which showed a significant binding. Molecular simulation using normal mode analysis (NMA) illustrated the docking complex as a stable one. Therefore, this observation strongly indicated that our multi epitopes bases peptide vaccine molecule will be an effective candidate for the treatment of the PCa.

Understanding the molecular interaction of human argonaute-2 and miR-20a complex: A molecular dynamics approach.

Argonaute-2 (AGO2), a member of the Argonaute family, is the only member possessing catalytic and RNA silencing activity. In here, a molecular dynamics (MDs) simulation was performed using the crystal structure of human AGO2 protein complex with miR-20a. miR-20a is involved with various kind of biological process like heart and lung development, oncogenic process, etc. In precise, MD simulation was carried out with AGO2 protein complex with wild type, two mutant sites and four mutant sites in guided microRNA (miRNA). It has been noted that root-mean-square deviation (RMSD) of atomic positions of nucleic acid for wild type and two mutant sites guided miRNA has the same pattern of fluctuations, which stabilizes around 0.27 nm after 2 ns. Cα atom of AGO2 protein in the complex shows that this complex with wild type and two mutant site mutation duplex has a stable RMSD value after 20 ns, ranging between 0.14 and 0.21 nm. From the root-mean-square fluctuation (RMSF), we observed an increased pattern of fluctuations for the atoms of four mutant complex of AGO2-miR-20a complex. This increased RMSF of non-mutated nucleic acids is contributed by U-A bond breaking at the site of the nucleotide of U2 of guided miRNA, as observed from the duplex structure taken at different time steps of the simulation. Superimposed structure of the miRNA-mRNA duplex for the three complexes depicts that the three miRNA-mRNA duplexes are stable during the simulation. Current work demonstrates the possible correlations between the conformational changes of this AGO2-miR-20a duplex structure and the interactions of different atoms.

Micro-Environmental Signature of The Interactions between Druggable Target Protein, Dipeptidyl Peptidase-IV, and Anti-Diabetic Drugs.

OBJECTIVE: Druggability of a target protein depends on the interacting micro-environment between the target protein and drugs. Therefore, a precise knowledge of the interacting micro-environment between the target protein and drugs is requisite for drug discovery process. To understand such micro-environment, we performed in silico interaction analysis between a human target protein, Dipeptidyl Peptidase-IV (DPP-4), and three anti-diabetic drugs (saxagliptin, linagliptin and vildagliptin). MATERIALS AND METHODS: During the theoretical and bioinformatics analysis of micro-environmental properties, we performed drug-likeness study, protein active site predictions, docking analysis and residual interactions with the protein-drug interface. Micro-environmental landscape properties were evaluated through various parameters such as binding energy, intermolecular energy, electrostatic energy, van der Waals'+H-bond+desolvo energy (EVHD) and ligand efficiency (LE) using different in silico methods. For this study, we have used several servers and software, such as Molsoft prediction server, CASTp server, AutoDock software and LIGPLOT server. RESULTS: Through micro-environmental study, highest log P value was observed for linagliptin (1.07). Lowest binding energy was also observed for linagliptin with DPP-4 in the binding plot. We also identified the number of H-bonds and residues involved in the hydrophobic interactions between the DPP-4 and the anti-diabetic drugs. During interaction, two H-bonds and nine residues, two H-bonds and eleven residues as well as four H-bonds and nine residues were found between the saxagliptin, linagliptin as well as vildagliptin cases and DPP-4, respectively. CONCLUSION: Our in silico data obtained for drug-target interactions and micro-environmental signature demonstrates linagliptin as the most stable interacting drug among the tested anti-diabetic medicines.

Structure of polymeric carbon dioxide CO2-V.

The structure of polymeric carbon dioxide (CO2-V) has been solved using synchrotron x-ray powder diffraction, and its evolution followed from 8 to 65 GPa. We compare the experimental results obtained for a 100% CO2 sample and a 1 mol % CO2/He sample. The latter allows us to produce the polymer in a pure form and study its compressibility under hydrostatic conditions. The high quality of the x-ray data enables us to solve the structure directly from experiments. The latter is isomorphic to the ß-cristobalite phase of SiO2 with the space group I42d. Carbon and oxygen atoms are arranged in CO4 tetrahedral units linked by oxygen atoms at the corners. The bulk modulus determined under hydrostatic conditions, B0=136(10) GPa, is much smaller than previously reported. The comparison of our experimental findings with theoretical calculations performed in the present and previous studies shows that density functional theory very well describes polymeric CO2.