Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants.

The genome feature of SARS-CoV-2 leads the virus to mutate and creates new variants of concern. Tackling viral mutations is also an important challenge for the development of a new vaccine. Accordingly, in the present study, we undertook to identify B- and T-cell epitopes with immunogenic potential for eliciting responses to SARS-CoV-2, using computational approaches and its tailoring to coronavirus variants. A total of 47 novel epitopes were identified as immunogenic triggering immune responses and no toxic after investigation with in silico tools. Furthermore, we found these peptide vaccine candidates showed a significant binding affinity for MHC I and MHC II alleles in molecular docking investigations. We consider them to be promising targets for developing peptide-based vaccines against SARS-CoV-2. Subsequently, we designed two efficient multi-epitopes vaccines against the SARS-CoV-2, the first one based on potent MHC class I and class II T-cell epitopes of S (FPNITNLCPF-NYNYLYRLFR-MFVFLVLLPLVSSQC), M (MWLSYFIASF-GLMWLSYFIASFRLF), E (LTALRLCAY-LLFLAFVVFLLVTLA), and N (SPRWYFYYL-AQFAPSASAFFGMSR). The second candidate is the result of the tailoring of the first designed vaccine according to three classes of SARS-CoV-2 variants. Molecular docking showed that the protein-protein binding interactions between the vaccines construct and TLR2-TLR4 immune receptors are stable complexes. These findings confirmed that the final multi-epitope vaccine could be easily adapted to new viral variants. Our study offers a shortlist of promising epitopes that can accelerate the development of an effective and safe vaccine against the virus and its adaptation to new variants.Communicated by Ramaswamy H. Sarma.

Diversifying the chloroquinoline scaffold against SARS-CoV-2 main protease: Virtual screening approach using cross-docking, SiteMap analysis and molecular dynamics simulation

The absence of designated remedies for coronavirus disease 19 (Covid-19) and the lack of treatment protocols drove scientists to propose new small molecules and to attempt to repurpose existing drugs against various targets of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in order to bring forward efficient solutions. The main protease (Mpro) is one of the most promising drug targets due to its crucial role in fighting viral replic-ation. Several antiviral drugs have been used in an attempt to overcome the pandemic, such as hydroxychloroquine (HCQ). Despite its perceived positive outcomes in the beginning of the disease, HCQ was associated with several drawbacks, such as insolubility, toxicity, and cardiac adverse effects. There-fore, in the present study, a structure-based virtual screening approach was performed to identify structurally modified ligands of the chloroquinoline (CQ) scaffold with good solubility, absorption, and permeation aimed at eventually suggesting a more dependable alternative. PDB ID:7BRP Mpro was chosen as the most reliable receptor after cross-docking calculation using 30 crystal struc-tures. Then, a SiteMap analysis was performed and a total of 231,456 structur-ally modified compounds of the CQ scaffold were suggested. After Lipinski criteria filtration, 64,312 molecules were docked and their MM-GBSA free binding energy were calculated. Next, ADME descriptors were calculated, and 12 molecules with ADME properties better than that of HCQ were identified. The resulting molecules were subjected to molecular dynamics (MD) simul-ation for 100 ns. The results of the study indicate that 3 molecules (CQ_22;CQ_2 and CQ_5) show better interactions and stability with the Mpro receptor. Binding interaction analysis indicates that GLU143, THR26, and HIS41 amino acids are potential binding hot-spot residues for the remaining 3 ligands.

Effectiveness of estrogen and its derivatives over dexamethasone in the treatment of COVID-19.

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus and dexamethasone is a glucocorticoid widely used for its treatment. Dexamethasone is not used in non-severe cases due to its immunosuppressant action. So, considering this, Estrogen and Estetrol were tested for the treatment of COVID-19 as they all possess a common steroid ring and dislike dexamethasone, they are immunoenhancer. Virtual screening of test ligands was performed through molecular docking, MM-GBSA, simulations, in silico ADMET and drug-likeness prediction to identify their potential to inhibit the effects of SARS-CoV-2. Results showed that test ligands possess drug-like properties and they are safe as drug candidates. The protein-ligand interaction study revealed that they bind with the amino acid residues at the active site of the target proteins and the test ligands possess better binding potential than Dexamethasone. With protein Mpro, Estetrol and Estrogen showed docking score of -7.240 and -5.491 kcal/mol, and with protein ACE2, Estetrol and Estrogen showed docking score of -5.269 and -4.732 kcal/mol, respectively. Further, MD Simulation was carried out and most of the interactions of molecular docking are preserved during simulation. The prominent interactions that our test ligands showed during MD Simulation are similar to drugs that possess in vitro anticovid activity as shown in recent studies. Hence, our test ligands possessed potential for anticovid activity and they should be further tested through in vitro and in vivo studies for their activity against COVID-19.Communicated by Ramaswamy H. Sarma.

In-silico studies on wild orange (Citrus macroptera Mont.) compounds against COVID-19 pro-inflammation targets.

One-fifth of COVID-19 patients suffer a severe course of COVID-19 (SARS-CoV-2) infection; however, the specific causes remain unclear. Despite numerous papers that have been flooded in different scientific journals clear clinical picture of COVID-19 aftermath persists to remain fuzzy. The survivors of severe COVID-19infection having defeated the virus are just the starting of an uncharted recovery path. Currently, there is no drug available that is safe to consume to combat this pandemic. However, researchers still struggling to find specific therapeutic solutions. The present study employed an in silico approach to assessing the inhibitory potential of the phytochemicals obtained from GC-MS analysis of Citrus macroptera against inflammatory proteins like COX-2, NMDAR and VCAM-1 which remains in a hyperactive state even after a patient is fully cured of this deadly mRNA virus. An extensive molecular docking investigation of the phyto-compounds at the active binding pockets of the inflammatory proteins revealed the promising inhibitory potential of the phytochemicals. Reasonable physicochemical attributes of the compounds following Lipinski's rule of five, VEBER and PAINS analysis further established them as potential therapeutic candidates against aforesaid inflammatory proteins. MM-GBSA binding free energy estimation revealed that Limonene was the most promising candidate displaying the highest binding efficacy with the concerned VCAM-1 protein included in the present analysis. An interesting finding is the phytochemicals exhibited better binding energy scores with the concerned COX-2, VCAM-1 and NMDA receptor proteins than the conventional drugs that are specifically targeted against them. Our in silico results suggest that all the natural phyto-compounds derived from C. macroptera could be employed in Post covid inflammation complexities after appropriate pre-clinical and clinical trials for further scientific validation.Communicated by Ramaswamy H. Sarma.

Exploring potential SARS-CoV-2 Mpro non-covalent inhibitors through docking, pharmacophore profile matching, molecular dynamic simulation, and MM-GBSA.

CONTEXT: In the replication of SARS-CoV-2, the main protease (Mpro/3CLpro) is significant. It is conserved in a number of novel coronavirus variations, and no known human proteases share its cleavage sites. Therefore, 3CLpro is an ideal target. In the report, we screened five potential inhibitors (1543, 2308, 3717, 5606, and 9000) of SARS-CoV-2 Mpro through a workflow. The calculation of MM-GBSA binding free energy showed that three of the five potential inhibitors (1543, 2308, 5606) had similar inhibitor effects to X77 against Mpro of SARS-CoV-2. In conclusion, the manuscript lays the groundwork for the design of Mpro inhibitors. METHODS: In the virtual screening phase, we used structure-based virtual screening (Qvina2.1) and ligand-based virtual screening (AncPhore). In the molecular dynamic simulation part, we used the Amber14SB + GAFF force field to perform molecular dynamic simulation of the complex for 100 ns (Gromacs2021.5) and performed MM-GBSA binding free energy calculation according to the simulation trajectory.

Activity of Some Novel Chalcone Substituted 9-anilinoacridines against Coronavirus (COVID-19): A Computational Approach

Background: In the year earlier part of 2020, many scientists urged to discover novel drugs against for the treatments of COVID-19. Coronavirus Disease 2019 (COVID-19), a life-threatening viral disease, was discovered first in China and quickly spread throughout the world. Objective(s): In the present article, some novel chalcone substituted 9-anilinoacridines (1a-z) were developed by in silico studies for their COVID19 inhibitory activity. Molecular docking studies of the ligands 1a-z were performed against COVID19 (PDB id-5R82) targeting the coronavirus using Schrodinger suite 2019-4. Method(s): The molecular docking studies were performed by the Glide module and the binding energy of ligands was calculated using the PRIME MM-GB/SA module of Schrodinger suite 2019-4. Result(s): From the results, many compounds are significantly active against COVID19 with a Glide score of more than-5.6 when compared to the currently used drug for the treatment of COVID19, Hy-droxychloroquine (-5.47). The docking results of the compounds exhibited similar mode of interactions with COVID19 and the residues, THR25, THR26, LEU27, SER46, MET49, HIE41, GLN189, ARG188, ASP187, VAL186, HIE164, ASN142, and GLY143 play a crucial role in binding with ligands. MM-GBSA binding calculations of the most potent inhibitors are more stably favourable. Conclusion(s): From the results of in-silico studies, it provides strong evidence for the consideration of valuable ligands in chalcone substituted 9-anilinoacridines as potential COVID19 inhibitors and the compounds, 1x,a,r,s with significant Glide scores may produce significant COVID19 activity for further development, which may prove their therapeutic potential.Copyright © 2020 Bentham Science Publishers.

Imidazole-Based Alkaloids from Marine Sponges (Leucetta and Clathrina) as Potential Inhibitors Targeting SARS-CoV-2 Main Protease: An In Silico Approach

Imidazole-based compounds form a prominent class of heterocyclic compounds, displaying diverse applications, especially with regards to its biological and pharmacological activities. Molecular docking, simulations, and drug-likeness prediction were performed on 45 imidazole-based alkaloids from two species of marine sponges (Leucetta and Clathrina). The study seeks to identify possible inhibitors of the SARS-CoV-2 Main Protease in an effort to battle the prevailing pandemic which has been caused by the widespread infections of the SAR-CoV-2 virus in its varied mutated forms. Computational analysis with MOE 2015.10 program reveals that, among the imidazole-based alkaloids, Naamidines have a high affinity for the target protein (PDB ID:6W63), even interacting with the catalytic dyad, as compared to its non-covalent inhibitor X77. Among all the top-scoring ligands, Naamidine H produced the highest binding score of −8.87078 kcal/mol. MD simulation studies with NAMD confirms the stability of the interactions of Naamidines with the target protein. MM-GBSA calculations were performed on the top binding ligands which further confirms the binding affinity of the top-scoring ligands. Computational and pharmacological investigations in this study proposes Naamidines, as effective inhibitors of Mpro. Naamidine I, Naamidine E, and Pyronaamidine could be potential anti-viral candidates against SAR-CoV-2. © 2023 Taylor & Francis Group, LLC.

Finding a prospective dual-target drug for the treatment of coronavirus disease by theoretical study.

Spike protein of coronavirus is a key protein in binding and entrance of virus to the human cell via binding to the receptor-binding domain (RBD) domain of S1 subunit to peptidase domain region of ACE2 receptor. In this study, the possible effect of 24 antiviral drugs on the RBD domain of spike protein was investigated via docking and molecular dynamics simulation for finding a dual-target drug. At first, all drugs were docked to the RBD domain of spike protein, and then all complexes and free RBD domains were separately used for molecular dynamics simulation for 50 ns via amber18 software. The simulation results showed that 10 ligands from 28 ligands were separated from the RBD domain, and among 18 remained ligands, baloxavir marboxil, and danoprevir drugs, besides endonuclease activity and protease inhibitory, can bind to key residues of the RBD domain. Then these drugs have a dual target and should be more effective than current drugs, and experimental studies should be done on baloxavir marboxil and danoprevir as more potential drugs for coronavirus disease Communicated by Ramaswamy H. Sarma.

QSAR, molecular docking, molecular dynamics and MM-GBSA approach for identification of prospective benzotriazole-based SARS-CoV 3CL protease inhibitors.

The 3CL Protease of severe acute respiratory syndrome coronavirus (SARS-CoV), responsible for viral replication, has emerged as an essential target for designing anti-coronaviral inhibitors in drug discovery. In recent years, small molecule and peptidomimetic inhibitors have been used to target the inhibition of SARS-CoV 3CL Protease. In this study, we have developed 2D and 3D Quantitative structure activity relationship (QSAR) models on 3CL protease inhibitors with good predictive capability to propose inhibitors with improved affinities. Based on the 3 D contour maps, three new inhibitors were designed in silico, which were further subjected to molecular docking to explore their binding modes. The newly designed compounds showed improved interaction energies toward SARS-CoV-3CLPro due to additional interactions with the active site residues. The molecular docking studies of the most potent compounds revealed specific interactions with Glu 166 and Cys 145. Furthermore, absorption, distribution, metabolism, elimination (ADME) and drug-likeness evaluation revealed improved pharmacokinetic properties for these compounds. The molecular dynamics simulations confirmed the stability of the interactions identified by docking. The results presented would guide the development of new 3CL protease inhibitors with improved affinities in the future.Communicated by Ramaswamy H. Sarma.

Computational basis of SARS-CoV 2 main protease inhibition: an insight from molecular dynamics simulation based findings.

The coronavirus disease 2019 (COVID-19) pandemic is caused by newly discovered severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). One of the striking targets amongst all the proteins in coronavirus is the main protease (Mpro), as it plays vital biological roles in replication and maturation of the virus, and hence the potential target. The aim of this study is to repurpose the Food and Drug Administration (FDA) approved molecules via computer-aided drug designing against Mpro (PDB ID: 6Y2F) of SARS CoV-2 due to its high x-ray resolution of 1.95 Å as compared to other published Mprostructures. High Through Virtual Screening (HTVS) of 2456 FDA approved drugs using structure-based docking were analyzed. Molecular Dynamics simulations were performed to check the overall structural stability (RMSD), Cα fluctuations (RMSF) and protein-ligand interactions. Further, trajectory analysis was performed to assess the binding quality by exploiting the protein-residue motion cross correlation (DCCM) and binding free energy (MM/GBSA). Tenofovir, an antiretroviral for HIV-proteases and Terlipressin, a vasoconstrictor show stable RMSD, RMSF, better MM/GBSA with good cross correlation as compared to the Apo and O6K. Moreover, the results show concurrence with Nelfinavir, Lopinavir and Ritonavir which have shown significant inhibition in in vitro studies. Therefore, we conclude that Tenofovir and Terlipresssin might also show protease inhibition but are still open to clinical validation in case of SARS-CoV 2 treatment.Communicated by Ramaswamy H. Sarma.

Inhibitory activity of marine sponge metabolites on SARS-CoV-2 RNA dependent polymerase: virtual screening and molecular dynamics simulation.

Marine species are known as rich sources of metabolites involved mainly in the pharmaceutical industry. This study aimed to evaluate the effect of biologically active compounds in the marine sponge on the SARS-CoV-2 RNA-dependent-RNA polymerase protein (RdRp) using the in-silico method. A total of 51 marine compounds were checked for their possible interaction with SARS-CoV-2 RdRp using Maestro interface for molecular docking, molecular dynamic (MD) simulation, and MM/GBSA method to estimate compounds binding affinities. Among the 51 compounds screened in this study, two (mycalamide A, and nakinadine B) exhibited the lowest docking energy and best interaction. Among these compounds, mycalamide A was identified as a potent inhibitor of SARS-CoV-2 RdRp that showed the best and stable interaction during molecular dynamic simulation, with residues (Asp760 and Asp761) found in the catalytic domain of RdRp. The analysis through MM/GBSA for molecular dynamic simulation results revealed binding energy -59.7 ± 7.18 for Mycalamide A and -56 ± 10.55 for Nakinadine B. These results elucidate the possible use of mycalamide A for treating coronavirus disease.Communicated by Ramaswamy H. Sarma.

Multidimensional virtual screening approaches combined with drug repurposing to identify potential covalent inhibitors of SARS-CoV-2 3CL protease.

The outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused an unprecedented global pandemic, and new cases are still on the rise due to the absence of effective medicines. However, developing new drugs within a short time is extremely difficult. Repurposing the existing drugs provides a fast and effective strategy to identify promising inhibitors. Here we focus on the screening of drugs database for discovering potential covalent inhibitors that target 3-chymotrypsin-like protease (3CLpro), an essential enzyme mediating viral replication and transcription. Firstly, we constructed a receptor-ligand pharmacophore model and verified it through decoy set. The importance of pharmacophore features was evaluated by combining molecular dynamics simulation with interaction analyses. Then, covalent docking was used to perform further screening. According to docking score and Prime/Molecular Mechanics Generalized Born Surface Area (MM-GBSA) score, total ten compounds obtained good scores and successfully established covalent bonds with the catalytic Cys145 residue. They also formed favorable interactions with key residues in active sites and closely integrated with 3CLpro with binding modes similar to known 3CLpro inhibitor. Finally, the top four hits DB08732, DB04653, DB01871 and DB07299 were further subjected to 100 ns molecular dynamics (MD) simulation and MM-GBSA binding free energy calculations. The results suggest that the four candidates show good binding affinities for 3CLpro, which warrants further evaluation for their in-vitro/in-vivo activities. Overall, our research methods provide a valuable reference for discovering promising inhibitors against SARS-CoV-2 and help to fight against the epidemic.Communicated by Ramaswamy H. Sarma.

Graph Convolutional Capsule Regression (GCCR): A Model for Accelerated Filtering of Novel Potential Candidates for SARS-CoV-2 Based on Binding Affinity.

BACKGROUND: There has been a growing interest in discovering a viable drug for the new coronavirus (SARS-CoV-2) since the beginning of the pandemic. Protein-ligand interaction studies are a crucial step in the drug discovery process, as it helps us narrow the search space for potential ligands with high drug-likeness. Derivatives of popular drugs like Remdesivir generated through tools employing evolutionary algorithms are usually considered potential candidates. However, screening promising molecules from such a large search space is difficult. In a conventional screening process, for each ligand-target pair, there are time-consuming interaction studies that use docking simulations before downstream tasks like thermodynamic, kinetic, and electrostatic-potential evaluation. METHODS: In this work, 'Graph Convolutional Capsule Regression' (GCCR), a model which uses Capsule Neural Networks (CapsNet) and Graph Convolutional Networks (GCN) to predict the binding energy of a protein-ligand complex is being proposed. The model's predictions were further validated with kinetic and free energy studies like Molecular Dynamics (MD) for kinetic stability and MM/GBSA analysis for free energy calculations. RESULTS: The GCCR showed an RMSE value of 0.0978 for 81.3% of the concordance index. The RMSE of GCCR converged around the iteration of just 50 epochs scoring a lower RMSE than GCN and GAT. When training with Davis Dataset, GCCR gave an RMSE score of 0.3806 with a CI score of 87.5%. CONCLUSION: The proposed GCCR model shows great potential in improving the screening process based on binding affinity and outperforms baseline machine learning models like DeepDTA, KronRLS, SimBoost, and other Graph Neural Networks (GNN) based models like Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT).

Identification of RdRp inhibitors against SARS-CoV-2 through E-pharmacophore-based virtual screening, molecular docking and MD simulations approaches.

The outbreak of novel Coronavirus, an enduring pandemic declared by WHO, has consequences to an alarming ongoing public health menace which has already claimed several million human lives. In addition to numerous vaccinations and medications for mild to moderate COVID-19 infection, lack of promising medication or therapeutic pharmaceuticals remains a serious concern to counter the ongoing coronavirus infections and to hinder its dreadful spread. Global health emergencies have called for urgency for potential drug discovery and time is the biggest constraint apart from the financial and human resources required for the high throughput drug screening. However, computational screening or in-silico approaches appeared to be an effective and faster approach to discover potential molecules without sacrificing the model animals. Accumulated shreds of evidence on computational studies against viral diseases have revealed significance of in-silico drug discovery approaches especially in the time of urgency. The central role of RdRp in SARS-CoV-2 replication makes it promising drug target to curtain on going infection and its spread. The present study aimed to employ E-pharmacophore-based virtual screening to reveal potent inhibitors of RdRp as potential leads to block the viral replication. An energy-optimised pharmacophore model was generated to screen the Enamine REAL DataBase (RDB). Then, ADME/T profiles were determined to validate the pharmacokinetics and pharmacodynamics properties of the hit compounds. Moreover, High Throughput Virtual Screening (HTVS) and molecular docking (SP & XP) were employed to screen the top hits from pharmacophore-based virtual screening and ADME/T screen. The binding free energies of the top hits were calculated by conducting MM-GBSA analysis followed by MD simulations to determine the stability of molecular interactions between top hits and RdRp protein. These virtual investigations revealed six compounds having binding free energies of -57.498, -45.776, -46.248, -35.67, -25.15 and -24.90 kcal/mol respectively as calculated by the MM-GBSA method. The MD simulation studies confirmed the stability of protein ligand complexes, hence, indicating as potent RdRp inhibitors and are promising candidate drugs to be further validated and translated into clinics in future.

Exploration of potent antiviral phytomedicines from Lauraceae family plants against SARS-CoV-2 RNA-dependent RNA polymerase.

RNA-dependent RNA polymerase, also known as RdRp, is a possible therapeutic target that could be used to suppress the proliferation of RNA viruses such as SARS-CoV-2. This protein has two major functional sites (a) catalytic and (b) substrate entry, which regulate the natural substrate entry and its corresponding interaction with the protein. In this study, a computational drug design pipeline was applied to investigate potential inhibitors against SARS-CoV-2 RdRp from Lauraceae plants, and five top hits were selected based on the docked score (< -7 kcal/mol). The docking study suggested that the Glochidioboside had a minimum binding score of -7.8 kcal/mol. This compound showed total five hydrogen bonds while two of them were with catalytic residues Asp618 and Asp760. However, another compound, Sitogluside showed a binding score of -7.3 kcal/mol with four hydrogen bonds targeting three functional residues (Arg555, Ser759, and Asp760). Later, 100 ns explicit solvent molecular dynamics (MD) simulation was performed to evaluate the stability of the protein-ligand docked system. These compounds translocated their positions from the catalytic site to the substrate entry site, as observed in the MD simulation trajectory. However, translocation did not affect the binding strength of these compounds, and they retained the strong binding affinity (ΔG < -11.5 kcal/mol), estimated using the MM/GBSA method. In general, the findings of this study indicated the potential therapeutic compounds that may be used targeting SARS-CoV-2 RdRp. However, these compounds still need to be validated by experimentation in order to determine their inhibitory function.Communicated by Ramaswamy H. Sarma.

Computational Design, Synthesis, and Biophysical Evaluation of ß-Amido Boronic Acids as SARS-CoV-2 Mpro Inhibitors.

The COVID-19 pandemic has given a strong impetus to the search for antivirals active on SARS-associated coronaviruses. Over these years, numerous vaccines have been developed and many of these are effective and clinically available. Similarly, small molecules and monoclonal antibodies have also been approved by the FDA and EMA for the treatment of SARS-CoV-2 infection in patients who could develop the severe form of COVID-19. Among the available therapeutic tools, the small molecule nirmatrelvir was approved in 2021. It is a drug capable of binding to the Mpro protease, an enzyme encoded by the viral genome and essential for viral intracellular replication. In this work, by virtual screening of a focused library of ß-amido boronic acids, we have designed and synthesized a focused library of compounds. All of them were biophysically tested by microscale thermophoresis, attaining encouraging results. Moreover, they also displayed Mpro protease inhibitory activity, as demonstrated by performing enzymatic assays. We are confident that this study will pave the way for the design of new drugs potentially useful for the treatment of SARS-CoV-2 viral infection.

High-Affinity Antibodies Designing of SARS-CoV-2 Based on Molecular Dynamics Simulations.

SARS-CoV-2 has led to a global pandemic of new crown pneumonia, which has had a tremendous impact on human society. Antibody drug therapy is one of the most effective way of combating SARS-CoV-2. In order to design potential antibody drugs with high affinity, we used antibody S309 from patients with SARS-CoV as the target antibody and RBD of S protein as the target antigen. Systems with RBD glycosylated and non-glycosylated were constructed to study the influence of glycosylation. From the results of molecular dynamics simulations, the steric effects of glycans on the surface of RBD plays a role of "wedge", which makes the L335-E340 region of RBD close to the CDR3 region of the heavy chain of antibody and increases the contact area between antigen and antibody. By mutating the key residues of antibody at the interaction interface, we found that the binding affinities of antibody mutants G103A, P28W and Y100W were all stronger than that of the wild-type, especially for the G103A mutant. G103A significantly reduces the distance between the binding region of L335-K356 in the antigen and P28-Y32 of heavy chain in the antibody through structural transition. Taken together, the antibody design method described in this work can provide theoretical guidance and a time-saving method for antibody drug design.

Potential Inhibitors of SARS-CoV-2 Main Protease (Mpro) Identified from the Library of FDA-Approved Drugs Using Molecular Docking Studies.

The Corona Virus Infectious Disease-2019 (COVID-19) outbreak originated at Wuhan, China, in December 2019. It has already spread rapidly and caused more than 6.5 million deaths worldwide. Its causal agent is a beta-coronavirus named SARS-CoV-2. Many efforts have already been made to develop new vaccines and drugs against these viruses, but over time, it has changed its molecular nature and evolved into more lethal variants, such as Delta and Omicron. These will lead us to target its more-conserved proteins. The sequences' BLAST and crystal structure of the main protease Mpro suggest a high sequence and structural conservation. Mpro is responsible for the proteolytic maturation of the polyprotein essential for the viral replication and transcription, which makes it an important drug target. Discovery of new drug molecules may take years before getting to the clinics. So, considering urgency, we performed molecular docking studies using FDA-approved drugs to identify molecules that could potentially bind to the substrate-binding site and inhibit SARS-CoV-2's main protease (Mpro). We used the Glide module in the Schrödinger software suite to perform molecular docking studies, followed by MM-GBSA-based energy calculations to score the hit molecules. Molecular docking and manual analysis suggest that several drugs may bind and potentially inhibit Mpro. We also performed molecular simulations studies for selected compounds to evaluate protein-drug interactions. Considering bioavailability, lesser toxicity, and route of administration, some of the top-ranked drugs, including lumefantrine (antimalarial), dipyridamole (coronary vasodilator), dihydroergotamine (used for treating migraine), hexoprenaline (anti asthmatic), riboflavin (vitamin B2), and pantethine (vitamin B5) may be taken forward for further in vitro and in vivo experiments to investigate their therapeutic potential.

Repulsive Scaling Replica Exchange Molecular Dynamics in Modeling Protein-Glycosaminoglycan Complexes.

Glycosaminoglycans are long linear periodic anionic polysaccharides consisting of disaccharide units exhibiting different sulfation patterns forming a highly heterogeneous group of molecules. Due to their flexibility, length, high charge, and periodicity, they are challenging for computational approaches. Despite their biological significance in terms of the important role in various diseases (e.g., Alzheimer, cancer, SARS-CoV-2) and proper cell functioning (e.g., proliferation, maturation), there is a lack of effective molecular docking tools designed specifically for glycosaminoglycans due to their challenging physical-chemical nature. In this chapter we present protocols for the Repulsive Scaling Replica Exchange Molecular Dynamics (RS-REMD) methods to dock glycosaminoglycans with both implicit and explicit solvent models implemented. This novel molecular dynamics-based replica exchange technique should help to elevate our current knowledge on the complexes and interactions between glycosaminoglycans and their protein receptors.

Structural plasticity of omicron BA.5 and BA.2.75 for enhanced ACE-dependent entry into cells.

The current study investigated the binding variations among the wilt type, Omicron sub-variants BA.2.75 and BA.5, using protein-protein docking, protein structural graphs (P SG), and molecular simulation methods. HADDOCK predicted docking scores and dissociation constant (KD) revealed tighter binding of these sub-variants in contrast to the WT. Further investigation revealed variations in the hub residues, protein sub-networks, and GlobalMetapath in these variants as compared to the WT. A very unusual dynamic for BA.2.75 and BA.5 was observed, and secondary structure transition can also be witnessed in the loops (44-505). The results show that the flexibility of these three loops is increased by the mutations as an allosteric effect and thus enhances the chances of bonding with the nearby residues to connect and form a stable connection. Furthermore, the additional hydrogen bonding contacts steer the robust binding of these variants in contrast to the wild type. The total binding free energy for the wild type was calculated to be -61.38 kcal/mol, while for BA.2.75 and BA.5 variants the T BE was calculated to be -70.42 kcal/mol and 69.78 kcal/mol, respectively. We observed that the binding of BA.2.75 is steered by the electrostatic interactions while the BA.5 additional contacts are due to the vdW (Van der Waal) energy. From these findings, it can be observed the Spike (S) protein is undergoing structural adjustments to bind efficiently to the hACE2 (human angiotensin-converting enzyme 2) receptor and, in turn, increase entry to the host cells. The current study will aid the development of structure-based drugs against these variants.Communicated by Ramaswamy H. Sarma.