Computational studies with flavonoids and terpenoids as BRPF1 inhibitors: in silico biological activity prediction, molecular docking, molecular dynamics simulations, MM/PBSA calculations

Yalçın, Gözde

doi:10.1080/1062936x.2022.2096113

Cited by 1 publication

(1 citation statement)

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“…Acute myeloid leukemia (AML), a morphologically, clinically, and genetically heterogeneous disorder caused by mutations in myeloid differentiation and proliferation, has severely imperiled patients’ lives around the world [ 1 , 2 , 3 ]. Drug design is the creative process of finding specific small molecules that can obstruct or enhance the functions of biological targets based on the action mechanism of the drug and target [ 4 , 5 , 6 , 7 ]. Designing small molecules that inhibit the activity of bromodomain-containing proteins (BRDs) is a promising therapeutic strategy to treat many kinds of diseases, including cancer, inflammation, and cardiovascular and autoimmune diseases [ 8 , 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

Wang

et al. 2023

Molecules

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BRD9 and TAF1(2) have been regarded as significant targets of drug design for clinically treating acute myeloid leukemia, malignancies, and inflammatory diseases. In this study, multiple short molecular dynamics simulations combined with the molecular mechanics generalized Born surface area method were employed to investigate the binding selectivity of three ligands, 67B, 67C, and 69G, to BRD9/TAF1(2) with IC50 values of 230/59 nM, 1400/46 nM, and 160/410 nM, respectively. The computed binding free energies from the MM-GBSA method displayed good correlations with that provided by the experimental data. The results indicate that the enthalpic contributions played a critical factor in the selectivity recognition of inhibitors toward BRD9 and TAF1(2), indicating that 67B and 67C could more favorably bind to TAF1(2) than BRD9, while 69G had better selectivity toward BRD9 over TAF1(2). In addition, the residue-based free energy decomposition approach was adopted to calculate the inhibitor–residue interaction spectrum, and the results determined the gatekeeper (Y106 in BRD9 and Y1589 in TAF1(2)) and lipophilic shelf (G43, F44, and F45 in BRD9 and W1526, P1527, and F1528 in TAF1(2)), which could be identified as hotspots for designing efficient selective inhibitors toward BRD9 and TAF1(2). This work is also expected to provide significant theoretical guidance and insightful molecular mechanisms for the rational designs of efficient selective inhibitors targeting BRD9 and TAF1(2).

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Section: Introductionmentioning

confidence: 99%

Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

Wang

et al. 2023

Molecules

View full text Add to dashboard Cite

show abstract

Computational studies with flavonoids and terpenoids as BRPF1 inhibitors: in silico biological activity prediction, molecular docking, molecular dynamics simulations, MM/PBSA calculations

Cited by 1 publication

References 54 publications

Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

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