scholarly journals Improved binding affinity of the Omicron's spike protein with hACE2 receptor is the key factor behind its increased virulence

2021 ◽  
Author(s):  
Rajender Kumar ◽  
Murugan Natarajan Arul ◽  
Vaibhav Srivastava
Keyword(s):  
Free Energy ◽  
Hydrogen Bonding ◽  
Binding Affinity ◽  
Electrostatic Interactions ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Spike Protein ◽  
Strong Interactions ◽  
Salt Bridges ◽  
New Variant

The new variant of SARS-CoV-2, Omicron, has been quickly spreading in many countries worldwide. Compared to the original virus, Omicron is characterized by several mutations in its genomic region, including spike protein's receptor-binding domain (RBD). We have computationally investigated the interaction between RBD of both wild-type and omicron variants with hACE2 receptor using molecular dynamics and MM-GBSA based binding free energy calculations. The mode of the interaction between Omicron's RBD to the human ACE2 (hACE2) receptor is similar to the original SARS-CoV-2 RBD except for a few key differences. The bind-ing free energy difference shows that the spike protein of Omicron has increased binding affinity for the hACE-2 receptor. The mutated residues in the RBD showed strong interactions with a few amino acid residues of the hACE2. More specifically, strong electrostatic interactions (salt bridges) and hydrogen bonding were observed between R493 and R498 residues of the Omicron RBD with D30/E35 and D38 residues of the hACE2, respectively. Other mutated amino acids in the Omicron RBD, e.g. S496 and H505, also exhibited hydrogen bonding with the hACE2 receptor. The pi-stacking interaction was also observed between tyrosine residues (RBD-Tyr501: hACE2-Tyr41) in the complex, which contributes majorly to binding free energies suggesting this as one of the key interactions stabilizing the complex formation. The structural insights of RBD:hACE2 complex, their binding mode information and residue wise contributions to binding free energy provide insight on the increased transmissibility of Omicron and pave the way to design and optimize novel antiviral agents.

Automated, Accurate, and Scalable Relative Protein-Ligand Binding Free Energy Calculations using Lambda Dynamics

2020 ◽  
Author(s):  
E. Prabhu Raman ◽  
Thomas J. Paul ◽  
Ryan L. Hayes ◽  
Charles L. Brooks III
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Binding Free Energy ◽  
Computational Cost ◽  
Combinatorial Libraries ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Efficient Estimation ◽  
Lead Compound

<p>Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization.</p>

scholarly journals Omicron SARS-CoV-2 Variant Spike Protein Shows an Increased Affinity to the Human ACE2 Receptor: An In Silico Analysis

Pathogens ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 45
Author(s):  
Joseph Thomas Ortega ◽  
Beata Jastrzebska ◽  
Hector Rafael Rangel
Keyword(s):  
Free Energy ◽  
Electrostatic Interactions ◽  
Structural Model ◽  
Binding Free Energy ◽  
In Silico Analysis ◽  
Spike Protein ◽  
Medical Community ◽  
Converting Enzyme ◽  
Angiotensin Converting Enzyme 2 ◽  
Silico Analysis

The rise of SARS-CoV-2 variants, with changes that could be related to an increased virus pathogenicity, have received the interest of the scientific and medical community. In this study, we evaluated the changes that occurred in the viral spike of the SARS-CoV-2 Omicron variant and whether these changes modulate the interactions with the angiotensin-converting enzyme 2 (ACE2) host receptor. The mutations associated with the Omicron variant were retrieved from the GISAID and covariants.org databases, and a structural model was built using the SWISS-Model server. The interaction between the spike and the human ACE2 was evaluated using two different docking software, Zdock and Haddock. We found that the binding free energy was lower for the Omicron variant as compared to the WT spike. In addition, the Omicron spike protein showed an increased number of electrostatic interactions with ACE2 than the WT spike, especially the interactions related to charged residues. This study contributes to a better understanding of the changes in the interaction between the Omicron spike and the human host ACE2 receptor.

scholarly journals SARS-CoV-2 Omicron Variant: ACE2 Binding, Cryo-EM Structure of Spike Protein-ACE2 Complex and Antibody Evasion

2021 ◽  
Author(s):  
Dhiraj Mannar ◽  
James W. Saville ◽  
Xing Zhu ◽  
Shanti S. Srivastava ◽  
Alison M. Berezuk ◽  
...  
Keyword(s):  
Structural Analysis ◽  
Hydrogen Bonds ◽  
Binding Affinity ◽  
Spike Protein ◽  
Strong Interactions ◽  
Binding Affinities ◽  
Salt Bridges ◽  
The World

The newly reported Omicron variant is poised to replace Delta as the most rapidly spread SARS-CoV-2 variant across the world. Cryo-EM structural analysis of the Omicron variant spike protein in complex with human ACE2 reveals new salt bridges and hydrogen bonds formed by mutated residues R493, S496 and R498 in the RBD with ACE2. These interactions appear to compensate for other Omicron mutations such as K417N known to reduce ACE2 binding affinity, explaining our finding of similar biochemical ACE2 binding affinities for Delta and Omicron variants. Neutralization assays show that pseudoviruses displaying the Omicron spike protein exhibit increased antibody evasion, with greater evasion observed in sera obtained from unvaccinated convalescent patients as compared to doubly vaccinated individuals (8- vs 3-fold). The retention of strong interactions at the ACE2 interface and the increase in antibody evasion are molecular factors that likely contribute to the increased transmissibility of the Omicron variant.

scholarly journals An Effective MM/GBSA Protocol for Absolute Binding Free Energy Calculations: A Case Study on SARS-CoV-2 Spike Protein and the Human ACE2 Receptor

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2383
Author(s):  
Negin Forouzesh ◽  
Nikita Mishra
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Normal Mode Analysis ◽  
Free Energy Calculations ◽  
Spike Protein ◽  
Upper And Lower Bounds ◽  
Mode Analysis ◽  
Implicit Solvent ◽  
Energy Calculation ◽  
Generalized Born

The binding free energy calculation of protein–ligand complexes is necessary for research into virus–host interactions and the relevant applications in drug discovery. However, many current computational methods of such calculations are either inefficient or inaccurate in practice. Utilizing implicit solvent models in the molecular mechanics generalized Born surface area (MM/GBSA) framework allows for efficient calculations without significant loss of accuracy. Here, GBNSR6, a new flavor of the generalized Born model, is employed in the MM/GBSA framework for measuring the binding affinity between SARS-CoV-2 spike protein and the human ACE2 receptor. A computational protocol is developed based on the widely studied Ras–Raf complex, which has similar binding free energy to SARS-CoV-2/ACE2. Two options for representing the dielectric boundary of the complexes are evaluated: one based on the standard Bondi radii and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein–ligand binding. Predictions based on the two radii sets provide upper and lower bounds on the experimental references: −14.7(ΔGbindBondi)<−10.6(ΔGbindExp.)<−4.1(ΔGbindOPT1) kcal/mol. The consensus estimates of the two bounds show quantitative agreement with the experiment values. This work also presents a novel truncation method and computational strategies for efficient entropy calculations with normal mode analysis. Interestingly, it is observed that a significant decrease in the number of snapshots does not affect the accuracy of entropy calculation, while it does lower computation time appreciably. The proposed MM/GBSA protocol can be used to study the binding mechanism of new variants of SARS-CoV-2, as well as other relevant structures.

scholarly journals Molecular simulation of SARS-CoV-2 spike protein binding to pangolin ACE2 or human ACE2 natural variants reveals altered susceptibility to infection

2020 ◽  
Vol 101 (9) ◽  
pp. 921-924 ◽  
Author(s):  
Jingfang Wang ◽  
Xintian Xu ◽  
Xinbo Zhou ◽  
Ping Chen ◽  
Huiying Liang ◽  
...  
Keyword(s):  
Free Energy ◽  
Protein Binding ◽  
Binding Affinity ◽  
Binding Free Energy ◽  
Virus Transmission ◽  
Dynamics Simulation ◽  
Spike Protein ◽  
Susceptibility To Infection ◽  
Natural Variants ◽  
Complex Models

We constructed complex models of SARS-CoV-2 spike protein binding to pangolin or human ACE2, the receptor for virus transmission, and estimated the binding free energy changes using molecular dynamics simulation. SARS-CoV-2 can bind to both pangolin and human ACE2, but has a significantly lower binding affinity for pangolin ACE2 due to the increased binding free energy (9.5 kcal mol−1). Human ACE2 is among the most polymorphous genes, for which we identified 317 missense single-nucleotide variations (SNVs) from the dbSNP database. Three SNVs, E329G (rs143936283), M82I (rs267606406) and K26R (rs4646116), had a significant reduction in binding free energy, which indicated higher binding affinity than wild-type ACE2 and greater susceptibility to SARS-CoV-2 infection for people with them. Three other SNVs, D355N (rs961360700), E37K (rs146676783) and I21T (rs1244687367), had a significant increase in binding free energy, which indicated lower binding affinity and reduced susceptibility to SARS-CoV-2 infection.

scholarly journals Predicting the Potential Effect of E484K Mutation on the Binding of 28 Antibodies to the Spike Protein of SARS-CoV-2 by Molecular Dynamics Simulation and Free Energy Calculation

2021 ◽  
Author(s):  
Leyun Wu ◽  
Cheng Peng ◽  
Zhijian Xu ◽  
weiliang zhu
Keyword(s):  
Free Energy ◽  
Binding Affinity ◽  
Immune Escape ◽  
Binding Free Energy ◽  
Experimental Studies ◽  
Potential Effect ◽  
Dynamics Simulation ◽  
Spike Protein ◽  
Energy Calculation ◽  
Potential Impact

Vaccines and antibody therapeutic are needed to fight the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has spread since 2020. Experimental studies have shown that the E484K variant may escape the neutralization of antibodies. To explore the potential impact of E484K mutation on the antibody binding affinity, we calculated the binding free energy of 28 antibodies to the wild type and K484 mutant of the spike protein of SARS-CoV-2. We found that 71% of the antibodies show lower binding affinity to the E484K mutant, indicating the highly possible immune escape risk of the mutated virus. Further analysis revealed that the other mutations, e.g. F490 and V483, are also likely to cause immune escape.

scholarly journals SARS-CoV-2 host cell entry: an in silico investigation of potential inhibitory roles of terpenoids

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Gideon A. Gyebi ◽  
Oludare M. Ogunyemi ◽  
Ibrahim M. Ibrahim ◽  
Olalekan B. Ogunro ◽  
Adegbenro P. Adegunloye ◽  
...  
Keyword(s):  
Free Energy ◽  
In Silico ◽  
Md Simulation ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Cell Entry ◽  
Spike Protein ◽  
Energy Calculations ◽  
Wide Range ◽  
Binding Free Energy Calculations

Abstract Background Targeting viral cell entry proteins is an emerging therapeutic strategy for inhibiting the first stage of SARS-CoV-2 infection. In this study, 106 bioactive terpenoids from African medicinal plants were screened through molecular docking analysis against human angiotensin-converting enzyme 2 (hACE2), human transmembrane protease serine 2 (TMPRSS2), and the spike (S) proteins of SARS-CoV-2, SARS-CoV, and MERS-CoV. In silico absorption-distribution-metabolism-excretion-toxicity (ADMET) and drug-likeness prediction, molecular dynamics (MD) simulation, binding free energy calculations, and clustering analysis of MD simulation trajectories were performed on the top docked terpenoids to respective protein targets. Results The results revealed eight terpenoids with high binding tendencies to the catalytic residues of different targets. Two pentacyclic terpenoids (24-methylene cycloartenol and isoiguesteri) interacted with the hACE2 binding hotspots for the SARS-CoV-2 spike protein, while the abietane diterpenes were found accommodated within the S1-specificity pocket, interacting strongly with the active site residues TMPRSS2. 3-benzoylhosloppone and cucurbitacin interacted with the RBD and S2 subunit of SARS-CoV-2 spike protein respectively. These interactions were preserved in a simulated dynamic environment, thereby, demonstrating high structural stability. The MM-GBSA binding free energy calculations corroborated the docking interactions. The top docked terpenoids showed favorable drug-likeness and ADMET properties over a wide range of molecular descriptors. Conclusion The identified terpenoids from this study provides core structure that can be exploited for further lead optimization to design drugs against SARS-CoV-2 cell-mediated entry proteins. They are therefore recommended for further in vitro and in vivo studies towards developing entry inhibitors against the ongoing COVID-19 pandemic.

scholarly journals Predicting the Potential Effect of E484K Mutation on the Binding of 28 Antibodies to the Spike Protein of SARS-CoV-2 by Molecular Dynamics Simulation and Free Energy Calculation

2021 ◽  
Author(s):  
Leyun Wu ◽  
Cheng Peng ◽  
Zhijian Xu ◽  
weiliang zhu
Keyword(s):  
Free Energy ◽  
Binding Affinity ◽  
Immune Escape ◽  
Binding Free Energy ◽  
Experimental Studies ◽  
Potential Effect ◽  
Dynamics Simulation ◽  
Spike Protein ◽  
Energy Calculation ◽  
Potential Impact

Vaccines and antibody therapeutic are needed to fight the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has spread since 2020. Experimental studies have shown that the E484K variant may escape the neutralization of antibodies. To explore the potential impact of E484K mutation on the antibody binding affinity, we calculated the binding free energy of 28 antibodies to the wild type and K484 mutant of the spike protein of SARS-CoV-2. We found that 71% of the antibodies show lower binding affinity to the E484K mutant, indicating the highly possible immune escape risk of the mutated virus. Further analysis revealed that the other mutations, e.g. F490 and V483, are also likely to cause immune escape.

scholarly journals Identification of Potential Binders of the SARS-Cov-2 Spike Protein via Molecular Docking, Dynamics Simulation and Binding Free Energy Calculation

2020 ◽  
Author(s):  
Dr. Chirag N. Patel ◽  
Dr. Prasanth Kumar S. ◽  
Dr. Himanshu A. Pandya ◽  
Dr. Rakesh M. Rawal
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Spike Protein ◽  
Energy Calculations ◽  
Dynamics Simulations

<p>The pandemic outbreak of COVID-19 virus (SARS-CoV-2) has become critical global health issue. The biophysical and structural evidence shows that SARS-CoV-2 spike protein possesses higher binding affinity towards angiotensin-converting enzyme 2 (ACE2) and hemagglutinin-acetylesterase (HE) glycoprotein receptor. Hence, it was selected as a target to generate the potential candidates for the inhibition of HE glycoprotein. The present study focuses on extensive computational approaches which contains molecular docking, ADMET prediction followed by molecular dynamics simulations and free energy calculations. Furthermore, virtual screening of NPACT compounds identified 3,4,5-Trihydroxy-1,8-bis[(2R,3R)-3,5,7-trihydroxy-3,4-dihydro-2H-chromen-2-yl]benzo[7]annulen-6-one, Silymarin, Withanolide D, Spirosolane and Oridonin were interact with high affinity. The ADMET prediction revealed pharmacokinetics and drug-likeness properties of top-ranked compounds. Molecular dynamics simulations and binding free energy calculations affirmed that these five NPACT compounds were robust HE inhibitor.</p>

scholarly journals Phytochemical Moieties From Indian Traditional Medicine for Targeting Dual Hotspots on SARS-CoV-2 Spike Protein: An Integrative in-silico Approach

2021 ◽  
Vol 8 ◽  
Author(s):  
V. Umashankar ◽  
Sanjay H. Deshpande ◽  
Harsha V. Hegde ◽  
Ishwar Singh ◽  
Debprasad Chattopadhyay
Keyword(s):  
Free Energy ◽  
Binding Energy ◽  
Traditional Medicine ◽  
Binding Affinity ◽  
In Silico ◽  
Binding Free Energy ◽  
Contemporary Literature ◽  
Dynamics Simulation ◽  
Spike Protein ◽  
Syzygium Aromaticum

SARS-CoV-2 infection across the world has led to immense turbulence in the treatment modality, thus demanding a swift drug discovery process. Spike protein of SARS-CoV-2 binds to ACE2 receptor of human to initiate host invasion. Plethora of studies demonstrate the inhibition of Spike-ACE2 interactions to impair infection. The ancient Indian traditional medicine has been of great interest of Virologists worldwide to decipher potential antivirals. Hence, in this study, phytochemicals (1,952 compounds) from eight potential medicinal plants used in Indian traditional medicine were meticulously collated, based on their usage in respiratory disorders, along with immunomodulatory and anti-viral potential from contemporary literature. Further, these compounds were virtually screened against Receptor Binding Domain (RBD) of Spike protein. The potential compounds from each plant were prioritized based on the binding affinity, key hotspot interactions at ACE2 binding region and glycosylation sites. Finally, the potential hits in complex with spike protein were subjected to Molecular Dynamics simulation (450 ns), to infer the stability of complex formation. Among the compounds screened, Tellimagrandin-II (binding energy of −8.2 kcal/mol and binding free energy of −32.08 kcal/mol) from Syzygium aromaticum L. and O-Demethyl-demethoxy-curcumin (binding energy of −8.0 kcal/mol and binding free energy of −12.48 kcal/mol) from Curcuma longa L. were found to be highly potential due to their higher binding affinity and significant binding free energy (MM-PBSA), along with favorable ADMET properties and stable intermolecular interactions with hotspots (including the ASN343 glycosylation site). The proposed hits are highly promising, as these are resultant of stringent in silico checkpoints, traditionally used, and are documented through contemporary literature. Hence, could serve as promising leads for subsequent experimental validations.

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