Application of per-residue energy decomposition to identify the set of amino acids critical for in silico prediction of COX-2 inhibitory activity

Chaudhary, Neha; Aparoy, Polamarasetty

doi:10.1016/j.heliyon.2020.e04944

Cited by 21 publications

(15 citation statements)

References 59 publications

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“…Of note, decomposition of non-bonding energies, namely electrostatic energy and van der Waals interaction, have been shown to correlate with the total binding energy of HDAC2 ligand binding [ 31 ], although without a consideration of entropic term. Our observation of the correlation between the energy decomposition and the actual potency thus confirms the role of per-residue energy as determinant factors for predicting the actual inhibitory activity as previously described [ 69 – 71 ].…”

Section: Resultssupporting

confidence: 89%

Decoding molecular recognition of inhibitors targeting HDAC2 via molecular dynamics simulations and configurational entropy estimation

Tateing

Suree

2022

PLoS ONE

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Molecular recognition by enzymes is a complicated process involving thermodynamic energies governing protein-ligand interactions. In order to aid the estimation of inhibitory activity of compounds targeting an enzyme, several computational methods can be employed to dissect this intermolecular contact. Herein, we report a structural dynamics investigation of an epigenetic enzyme HDAC2 in differentiating its binding to various inhibitors within the sub-sites of its active site. Molecular dynamics (MD) simulation was employed to elucidate the intermolecular interactions as well as the dynamics behavior of ligand binding. MD trajectories of five distinct HDAC2-inhibitor complexes reveal that compounds lacking adequate contacts with the opening rim of the active site possess high fluctuation along the cap portion, thus weakening the overall affinity. Key intermolecular interactions determining the effective binding of inhibitors include hydrogen bonds with Gly154, Asp181, and Tyr308; hydrophobic interactions between Phe155/Phe210 and the linker region; and a pi-stacking with Arg39 at the foot pocket. Decomposition of the binding free energy calculated per-residue by MM/PBSA also indicates that the interactions within the internal foot pocket, especially with residues Met35, Leu144, Gly305, and Gly306, can contribute significantly to the ligand binding. Additionally, configurational entropy of the binding was estimated and compared to the scale of the binding free energy in order to assess its contribution to the binding and to differentiate various ligand partners. It was found that the levels of entropic contribution are comparable among a set of structurally similar carbamide ligands, while it is greatly different for the set of unrelated ligands, ranging from 2.75 to 16.38 kcal/mol for the five inhibitors examined. These findings exemplify the importance of assessing molecular dynamics as well as estimating the entropic contribution in evaluating the ligand binding mechanism.

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Section: Resultssupporting

confidence: 89%

Decoding molecular recognition of inhibitors targeting HDAC2 via molecular dynamics simulations and configurational entropy estimation

Tateing

Suree

2022

PLoS ONE

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“…Per-residue energy decomposition calculation was carried out to gain insight on each amino acid residue contribution towards the binding [ 24 ], the results are as shown in Figure 3 and Figure 4 . All the drugs bound in the N-terminal and C-terminal domain interface, an ATP binding site ( Table S1, Supplementary Materials ).…”

Section: Resultsmentioning

confidence: 99%

“…In preparation for the molecular docking, Protein Data Bank (PDB) was used to obtain the X-ray structure of Msm FadD32 protein (PDB ID: 5D6J) [ 24 ]. The small molecules were retrieved from the ZINC database [ 45 ].…”

Section: Methodsmentioning

confidence: 99%

In Silico Drug Repurposing Approach: Investigation of Mycobacterium tuberculosis FadD32 Targeted by FDA-Approved Drugs

2022

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Background: Despite the enormous efforts made towards combating tuberculosis (TB), the disease remains a major global threat. Hence, new drugs with novel mechanisms against TB are urgently needed. Fatty acid degradation protein D32 (FadD32) has been identified as a promising drug target against TB, the protein is required for the biosynthesis of mycolic acids, hence, essential for the growth and multiplication of the mycobacterium. However, the FadD32 mechanism upon the binding of FDA-approved drugs is not well established. Herein, we applied virtual screening (VS), molecular docking, and molecular dynamic (MD) simulation to identify potential FDA-approved drugs against FadD32. Methodology/Results: VS technique was found promising to identify four FDA-approved drugs (accolate, sorafenib, mefloquine, and loperamide) with higher molecular docking scores, ranging from −8.0 to −10.0 kcal/mol. Post-MD analysis showed that the accolate hit displayed the highest total binding energy of −45.13 kcal/mol. Results also showed that the accolate hit formed more interactions with FadD32 active site residues and all active site residues displayed an increase in total binding contribution. RMSD, RMSF, Rg, and DCCM analysis further supported that the presence of accolate exhibited more structural stability, lower bimolecular flexibility, and more compactness into the FadD32 protein. Conclusions: Our study revealed accolate as the best potential drug against FadD32, hence a prospective anti-TB drug in TB therapy. In addition, we believe that the approach presented in the current study will serve as a cornerstone to identifying new potential inhibitors against a wide range of biological targets.

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“…The g_mmpbsa uses Assisted Poisson Boltzmann Solver (APBS) program for computing polar solvation energy and Solvent Accessible Surface Area (SASA) model for polar solvation energy (Miller et al, 2012 ). MM-PBSA calculations were performed for the last 25 ns of the simulation trajectory after convergence (Chaudhary and Aparoy, 2020 ). Based on MM-PBSA calculations and interaction profile, nine molecules were selected for inhibition assays and were procured from Sigma.…”

Section: Methodsmentioning

confidence: 99%

Repurposing of FDA Approved Drugs Against SARS-CoV-2 Papain-Like Protease: Computational, Biochemical, and in vitro Studies

et al. 2022

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The pandemic caused by SARS-CoV-2 (SCoV-2) has impacted the world in many ways and the virus continues to evolve and produce novel variants with the ability to cause frequent global outbreaks. Although the advent of the vaccines abated the global burden, they were not effective against all the variants of SCoV-2. This trend warrants shifting the focus on the development of small molecules targeting the crucial proteins of the viral replication machinery as effective therapeutic solutions. The PLpro is a crucial enzyme having multiple roles during the viral life cycle and is a well-established drug target. In this study, we identified 12 potential inhibitors of PLpro through virtual screening of the FDA-approved drug library. Docking and molecular dynamics simulation studies suggested that these molecules bind to the PLpro through multiple interactions. Further, IC50 values obtained from enzyme-inhibition assays affirm the stronger affinities of the identified molecules for the PLpro. Also, we demonstrated high structural conservation in the catalytic site of PLpro between SCoV-2 and Human Coronavirus 229E (HCoV-229E) through molecular modelling studies. Based on these similarities in PLpro structures and the resemblance in various signalling pathways for the two viruses, we propose that HCoV-229E is a suitable surrogate for SCoV-2 in drug-discovery studies. Validating our hypothesis, Mefloquine, which was effective against HCoV-229E, was found to be effective against SCoV-2 as well in cell-based assays. Overall, the present study demonstrated Mefloquine as a potential inhibitor of SCoV-2 PLpro and its antiviral activity against SCoV-2. Corroborating our findings, based on the in vitro virus inhibition assays, a recent study reported a prophylactic role for Mefloquine against SCoV-2. Accordingly, Mefloquine may further be investigated for its potential as a drug candidate for the treatment of COVID.

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Application of per-residue energy decomposition to identify the set of amino acids critical for in silico prediction of COX-2 inhibitory activity

Cited by 21 publications

References 59 publications

Decoding molecular recognition of inhibitors targeting HDAC2 via molecular dynamics simulations and configurational entropy estimation

Decoding molecular recognition of inhibitors targeting HDAC2 via molecular dynamics simulations and configurational entropy estimation

In Silico Drug Repurposing Approach: Investigation of Mycobacterium tuberculosis FadD32 Targeted by FDA-Approved Drugs

Repurposing of FDA Approved Drugs Against SARS-CoV-2 Papain-Like Protease: Computational, Biochemical, and in vitro Studies

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