scholarly journals Insights into the Binding and Covalent Inhibition Mechanism of PF-07321332 to SARS-CoV-2 Mpro

Author(s):  
Son Tung Ngo ◽  
Trung Hai Nguyen ◽  
Nguyen Thanh Tung ◽  
Binh Khanh Mai

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been causing the COVID-19 pandemic resulting in several million death were reported. Numerous investigations have been carried out to discover a compound that can inhibit the biological activity of SARS-CoV-2 main protease, which is an enzyme related to the viral replication. Among these, PF-07321332 is currently under clinical trial for COVID-19 therapy. Therefore, in this work, atomistic and electronic simulations were performed to unravel the binding and covalent inhibition mechanism of the compound to Mpro. Initially, 5 µs of steered-molecular dynamics simulations were carried out to evaluate the ligand-binding process to SARS-CoV-2 Mpro. Successfully generated bound state between two molecules showed the important role of the PF-07321332 pyrrolidinyl group and the residues Glu166 and Gln189 in the ligand-binding process. Moreover, from the MD-refined structure, quantum mechanics/molecular mechanics (QM/MM) calculations were carried out to unravel the reaction mechanism for the formation of thioimidate product from SARS-CoV-2 Mpro and PF07321332 inhibitor. We found that the catalytic triad Cys145–His41–Asp187 of SARS-CoV-2 Mpro plays important role in the activation of PF-07321332 covalent inhibitor, which renders the deprotonation of Cys145 and, thus, facilitates further reaction. Our results are definitely beneficial for better understanding on the inhibition mechanism and designing new effective inhibitors for SARS-CoV-2 Mpro.

2019 ◽  
Author(s):  
Shae-Lynn Lahey ◽  
Christopher Rowley

Drug molecules adopt a range of conformations both in solution and in their protein-bound state. The strain and reduced flexibility of bound drugs can partially counter the intermolecular interactions that drive protein–ligand binding. To make accurate computational predictions of drug binding affinities, computational chemists have attempted to develop efficient empirical models of these interactions, although these methods are not always reliable. Machine learning has allowed the development of highly-accurate neural-network potentials (NNPs), which are capable of predicting the stability of molecular conformations with accuracy comparable to state-of-the-art quantum chemical calculations but at a billionth of the computational cost. Here, we demonstrate that these methods can be used to represent the intramolecular forces of protein-bound drugs within molecular dynamics simulations. These simulations are shown to be capable of predicting the protein–ligand binding pose and conformational component of the absolute Gibbs energy of binding for a set of drug molecules. Notably, the conformational energy for anti-cancer drug erlotinib binding to its target was found to considerably overestimated by a molecular mechanical model, while the NNP predicts a more moderate value. Although the ANI-1ccX NNP was not trained to describe ionic molecules, reasonable binding poses are predicted for charged ligands, although this method is not suitable for modeling the ligands in solution.


2019 ◽  
Author(s):  
Shae-Lynn Lahey ◽  
Christopher Rowley

Drug molecules adopt a range of conformations both in solution and in their protein-bound state. The strain and reduced flexibility of bound drugs can partially counter the intermolecular interactions that drive protein–ligand binding. To make accurate computational predictions of drug binding affinities, computational chemists have attempted to develop efficient empirical models of these interactions, although these methods are not always reliable. Machine learning has allowed the development of highly-accurate neural-network potentials (NNPs), which are capable of predicting the stability of molecular conformations with accuracy comparable to state-of-the-art quantum chemical calculations but at a billionth of the computational cost. Here, we demonstrate that these methods can be used to represent the intramolecular forces of protein-bound drugs within molecular dynamics simulations. These simulations are shown to be capable of predicting the protein–ligand binding pose and conformational component of the absolute Gibbs energy of binding for a set of drug molecules. Notably, the conformational energy for anti-cancer drug erlotinib binding to its target was found to considerably overestimated by a molecular mechanical model, while the NNP predicts a more moderate value. Although the ANI-1ccX NNP was not trained to describe ionic molecules, reasonable binding poses are predicted for charged ligands, although this method is not suitable for modeling the ligands in solution.


2020 ◽  
Author(s):  
Ying Li Weng ◽  
Shiv Rakesh Naik ◽  
Nadia Dingelstad ◽  
Subha Kalyaanamoorthy ◽  
Aravindhan Ganesan

AbstractThe 2019 novel coronavirus pandemic caused by SARS-CoV-2 remains a serious health threat to humans and a number of countries are already in the middle of the second wave of infection. There is an urgent need to develop therapeutics against this deadly virus. Recent scientific evidences have suggested that the main protease (Mpro) enzyme in SARS-CoV-2 can be an ideal drug target due to its crucial role in the viral replication and transcription processes. Therefore, there are ongoing research efforts to identify drug candidates against SARS-CoV-2 Mpro that resulted in hundreds of X-ray crystal structures of ligand bound Mpro complexes in the protein data bank (PDB) that describe structural details of different chemotypes of fragments binding within different sites in Mpro. In this work, we perform rigorous molecular dynamics (MD) simulation of 62 reversible ligand-Mpro complexes in the PDB to gain mechanistic insights about their interactions at atomic level. Using a total of ~2.25 μs long MD trajectories, we identified and characterized different pockets and their conformational dynamics in the apo Mpro structure. Later, using the published PDB structures, we analyzed the dynamic interactions and binding affinity of small ligands within those pockets. Our results identified the key residues that stabilize the ligands in the catalytic sites and other pockets in Mpro. Our analyses unraveled the role of a lateral pocket in the catalytic site in Mpro that is critical for enhancing the ligand binding to the enzyme. We also highlighted the important contribution from HIS163 in this lateral pocket towards ligand binding and affinity against Mpro through computational mutation analyses. Further, we revealed the effects of explicit water molecules and Mpro dimerization in the ligand association with the target. Thus, comprehensive molecular level insights gained from this work can be useful to identify or design potent small molecule inhibitors against SARS-CoV-2 Mpro.


2015 ◽  
Vol 17 (48) ◽  
pp. 32257-32267 ◽  
Author(s):  
Yan Li ◽  
Xiang Li ◽  
Zigang Dong

The binding process of a drug-like small molecule through a conformational gate is illustrated by extensive molecular dynamics simulations.


2020 ◽  
Author(s):  
Jiming Chen ◽  
Alexandra White ◽  
David C. Nelson ◽  
Diwakar Shukla

Witchweed, or Striga hermonthica, is a parasitic weed that destroys billions of dollars worth of crops globally every year. Its germination is stimulated by strigolactones exuded by its host plants. Despite high sequence, structure, and ligand binding site conservation across different plant species, one strigolactone receptor in witchweed (Sh HTL7) uniquely exhibits a picomolar EC50 for downstream signaling. Previous biochemical and structural analyses have hypothesized that this unique ligand sensitivity can be attributed to a large binding pocket volume in Sh HTL7 resulting in enhanced ability to bind substrates. Additional structural details of the substrate binding process can help explain its role in modulating the ligand selectivity. Using long-timescale molecular dynamics simulations, we demonstrate that mutations at the entrance of the binding pocket facilitate a more direct ligand binding pathway to Sh HTL7, whereas hydrophobicity at the binding pocket entrance results in a stable “anchored” state. We also demonstrate that several residues on the D-loop of At D14 stabilize catalytically inactive conformations. Finally, we show that strigolactone selectivity is not modulated by binding pocket volume. Our results indicate that while ligand binding is not the sole modulator of strigolactone receptor selectivity, it is a significant contributing factor. These results can be used to inform the design of selective antagonists for strigolactone receptors in witchweed.


Author(s):  
Olivier Sheik Amamuddy ◽  
Gennady M Verkhivker ◽  
Ozlem Tastan Bishop

The new coronavirus (SARS-CoV-2) is a global threat to world health and its economy. Its main protease (Mpro), which functions as a dimer, cleaves viral precursor proteins in the process of viral maturation. It is a good candidate for drug development owing to its conservation and the absence of a human homolog. An improved understanding of the protein behaviour can accelerate the discovery of effective therapies in order to reduce mortality. 100 ns all-atom molecular dynamics simulations of 50 homology modelled mutant Mpro dimers were performed at pH 7 from filtered sequences obtained from the GISAID database. Protease dynamics were analysed using RMSD, RMSF, Rg, the averaged betweenness centrality and geometry calculations. Domains from each Mpro protomer were found to generally have independent motions, while the dimer-stabilising N-finger region was found to be flexible in most mutants. A mirrored interprotomer pocket was found to be correlated to the catalytic site using compaction dynamics, and can be a potential allosteric target. The high number of titratable amino acids of Mpro may indicate an important role of pH on enzyme dynamics, as previously reported for SARS-CoV. Independent coarse-grained Monte Carlo simulations suggest a link between rigidity/mutability and enzymatic function.


2020 ◽  
Author(s):  
Shafi Ullah Khan ◽  
Thet.thet Htar

<p>At present, there are no proven agents for the treatment of 2019 coronavirus disease (COVID-19). The available evidence has not allowed guidelines to clearly recommend any drugs outside the context of clinical trials. One of the most important SARS-CoV-2 protein targets for therapeutics is the 3C-like protease (main protease, Mpro). Here in this study we utilize the recently published 6W63 crystal structure of Mpro complexed with a non-covalent inhibitor X77. Various docking methods FRED, HYBRID, CDOCKER and LEADFINDER tools were benchmark to optimally re-dock the co-crystal ligand within the active site of SARS-COV-2 Mpro. This study was restricted to molecular docking without validation by molecular dynamics simulations. CDOCKER was found to depict the exact binding of co-crystal ligand having lowest RMSD of less than 2 A. Interactions with the SARS-COV-2 Mpro may play a key role in fighting against viruses. Dexamethasone was found to bind with a high affinity to the same sites of the SARS-COV-2 Mpro than the Remdesivir. Dexamethasone was forming six hydrogen bonds compared to the three hydrogen bonds formed by Remdesivir within the active site of SARS-COV-2 Mpro. LEU141, GLY143, HIS163, GLU166, GLN192 were the key amino acid residue of SAR-COV-2 Mpro involved in stabilizing the complex between Dexamethasone and SARS-COV-2 Mpro. The results suggest the effectiveness of Dexamethasone as potent drugs against SARS-CoV-2 since it bind tightly to its Mpro. In addition, the results also suggest that dexamethasone as top antiviral treatments option than the Remdesivir with high potential to fight the SARS-CoV-2.</p>


2014 ◽  
Vol 144 (1) ◽  
pp. 41-54 ◽  
Author(s):  
João Pessoa ◽  
Fátima Fonseca ◽  
Simone Furini ◽  
João H. Morais-Cabral

Cyclic nucleotide–binding (CNB) domains regulate the activity of channels, kinases, exchange factors, and transcription factors. These proteins are highly variable in their ligand selectivity; some are highly selective for either cAMP or cGMP, whereas others are not. Several molecular determinants of ligand selectivity in CNB domains have been defined, but these do not provide a complete view of the selectivity mechanism. We performed a thorough analysis of the ligand-binding properties of mutants of the CNB domain from the MlotiK1 potassium channel. In particular, we defined which residues specifically favor cGMP or cAMP. Inversion of ligand selectivity, from favoring cAMP to favoring cGMP, was only achieved through a combination of three mutations in the ligand-binding pocket. We determined the x-ray structure of the triple mutant bound to cGMP and performed molecular dynamics simulations and a biochemical analysis of the effect of the mutations. We concluded that the increase in cGMP affinity and selectivity does not result simply from direct interactions between the nucleotide base and the amino acids introduced in the ligand-binding pocket residues. Rather, tighter cGMP binding over cAMP results from the polar chemical character of the mutations, from greater accessibility of water molecules to the ligand in the bound state, and from an increase in the structural flexibility of the mutated binding pocket.


2020 ◽  
Author(s):  
Gabriella J. Gerlach ◽  
Rachel Carrock ◽  
Robyn Stix ◽  
Elliott J. Stollar ◽  
K. Aurelia Ball

AbstractProtein-protein interactions are involved in a wide range of cellular processes. These interactions often involve intrinsically disordered proteins (IDPs) and protein binding domains. However, the details of IDP binding pathways are hard to characterize using experimental approaches, which can rarely capture intermediate states present at low populations. SH3 domains are common protein interaction domains that typically bind proline-rich disordered segments and are involved in cell signaling, regulation, and assembly. We hypothesized, given the flexibility of SH3 binding peptides, that their binding pathways include multiple steps important for function. Molecular dynamics simulations were used to characterize the steps of binding between the yeast Abp1p SH3 domain (AbpSH3) and a proline-rich IDP, ArkA. Before binding, the N-terminal segment 1 of ArkA is pre-structured and adopts a polyproline II helix, while segment 2 of ArkA (C-terminal) adopts a 310 helix, but is far less structured than segment 1. As segment 2 interacts with AbpSH3, it becomes more structured, but retains flexibility even in the fully engaged state. Binding simulations reveal that ArkA enters a flexible encounter complex before forming the fully engaged bound complex. In the encounter complex, transient nonspecific hydrophobic and long-range electrostatic contacts form between ArkA and the binding surface of SH3. The encounter complex ensemble includes conformations with segment 1 in both the forward and reverse orientation, suggesting that segment 2 may play a role in stabilizing the correct binding orientation. While the encounter complex forms quickly, the slow step of binding is the transition from the disordered encounter ensemble to the fully engaged state. In this transition, ArkA makes specific contacts with AbpSH3 and buries more hydrophobic surface. Simulating the binding between ApbSH3 and ArkA provides insight into the role of encounter complex intermediates and nonnative hydrophobic interactions for other SH3 domains and IDPs in general.Author SummaryComplex cellular processes are mediated by interactions between proteins, and to determine how these interactions affect cellular function and binding kinetics we often must understand the protein binding pathway. Many protein interaction domains, such as the SH3 domain, bind to intrinsically disordered proteins in a coupled folding and binding process. Using molecular dynamics simulations, we find that the binding of the disordered ArkA peptide to the yeast Abp1p SH3 domain proceeds through a flexible, disordered encounter complex before reaching a stable fully bound state. The encounter complex is stabilized by nonspecific long-range electrostatic interactions and nonspecific hydrophobic interactions between the peptide and domain. Our simulations highlight the important role of hydrophobic interactions in the entire SH3 binding process: both nonspecific hydrophobic contacts in the encounter complex and specific hydrophobic contacts in the fully bound complex. The encounter complex could be key to understanding the functional behavior of SH3 domain interactions because the encounter complex forms very quickly and the transition to the fully bound state is slower. In cells, an SH3 domain may form an encounter complex quickly and nonspecifically with many potential binding partners, allowing it to search for the correct recognition sequence before completing the binding process.


Author(s):  
Shafi Ullah Khan ◽  
Thet.thet Htar

<p>At present, there are no proven agents for the treatment of 2019 coronavirus disease (COVID-19). The available evidence has not allowed guidelines to clearly recommend any drugs outside the context of clinical trials. One of the most important SARS-CoV-2 protein targets for therapeutics is the 3C-like protease (main protease, Mpro). Here in this study we utilize the recently published 6W63 crystal structure of Mpro complexed with a non-covalent inhibitor X77. Various docking methods FRED, HYBRID, CDOCKER and LEADFINDER tools were benchmark to optimally re-dock the co-crystal ligand within the active site of SARS-COV-2 Mpro. This study was restricted to molecular docking without validation by molecular dynamics simulations. CDOCKER was found to depict the exact binding of co-crystal ligand having lowest RMSD of less than 2 A. Interactions with the SARS-COV-2 Mpro may play a key role in fighting against viruses. Dexamethasone was found to bind with a high affinity to the same sites of the SARS-COV-2 Mpro than the Remdesivir. Dexamethasone was forming six hydrogen bonds compared to the three hydrogen bonds formed by Remdesivir within the active site of SARS-COV-2 Mpro. LEU141, GLY143, HIS163, GLU166, GLN192 were the key amino acid residue of SAR-COV-2 Mpro involved in stabilizing the complex between Dexamethasone and SARS-COV-2 Mpro. The results suggest the effectiveness of Dexamethasone as potent drugs against SARS-CoV-2 since it bind tightly to its Mpro. In addition, the results also suggest that dexamethasone as top antiviral treatments option than the Remdesivir with high potential to fight the SARS-CoV-2.</p>


Sign in / Sign up

Export Citation Format

Share Document