Visualizing protein–ligand binding with chemical energy-wise decomposition (CHEWD): application to ligand binding in the kallikrein-8 S1 Site

Raza, Saad; Ranaghan, Kara E.; Kamp, Marc W. van der; Woods, Christopher; Mulholland, Adrian J.; Azam, Syed Sikander

doi:10.1007/s10822-019-00200-4

Cited by 17 publications

(13 citation statements)

References 56 publications

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“…Raza et al have shown that in comparison to the MM/PBSA analysis, the WaterSwap method identifies more residues with significant contribution to the calculated binding energies [86]. Additional insight can be obtained from the WaterSwap calculations as the binding free energy can be decomposed in terms of individual residue contributions.…”

Section: Resultsmentioning

confidence: 99%

“…It is important to emphasize that the interaction energies calculated through this method are not directly comparable to experimental results (e.g., ΔΔ G for mutated enzymes) nor will they sum to the total binding energy; however, this type of decomposition analysis might be useful for the identification of residues that have the largest effects on the binding energy. The residue decomposition can be visualized and analyzed using the CHEWD plugin for Chimera or PyMol [86]. The residue decomposition indicates favorable and unfavorable interactions, information that is useful for lead development.…”

Section: Resultsmentioning

confidence: 99%

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Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

Kiani

Ranaghan

Jabeen

et al. 2019

IJMS

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The Cytochrome P450 family of heme-containing proteins plays a major role in catalyzing phase I metabolic reactions, and the CYP3A4 subtype is responsible for the metabolism of many currently marketed drugs. Additionally, CYP3A4 has an inherent affinity for a broad spectrum of structurally diverse chemical entities, often leading to drug–drug interactions mediated by the inhibition or induction of the metabolic enzyme. The current study explores the binding of selected highly efficient CYP3A4 inhibitors by docking and molecular dynamics (MD) simulation protocols and their binding free energy calculated using the WaterSwap method. The results indicate the importance of binding pocket residues including Phe57, Arg105, Arg106, Ser119, Arg212, Phe213, Thr309, Ser312, Ala370, Arg372, Glu374, Gly481 and Leu483 for interaction with CYP3A4 inhibitors. The residue-wise decomposition of the binding free energy from the WaterSwap method revealed the importance of binding site residues Arg106 and Arg372 in the stabilization of all the selected CYP3A4-inhibitor complexes. The WaterSwap binding energies were further complemented with the MM(GB/PB)SA results and it was observed that the binding energies calculated by both methods do not differ significantly. Overall, our results could guide towards the use of multiple computational approaches to achieve a better understanding of CYP3A4 inhibition, subsequently leading to the design of highly specific and efficient new chemical entities with suitable ADMETox properties and reduced side effects.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

Kiani

Ranaghan

Jabeen

et al. 2019

IJMS

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“…A molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) approach 50 , 51 was employed to estimate the free energy of binding of the S-peptide to the different receptors ( Table S1 ). MM-PBSA calculations have emerged as an efficient and useful method to determine binding free energies, 50 , 51 and are widely used to study protein-ligand interactions in medicinal chemistry, 52 – 54 including in drug design for nAChRs. 55 , 56 The favourable calculated binding energies suggest stable complex formation between the S-peptide and all three nAChRs ( Table S1 ).…”

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confidence: 99%

Simulations support the interaction of the SARS-CoV-2 spike protein with nicotinic acetylcholine receptors

Oliveira

Ibarra

Bermúdez

et al. 2020

Preprint

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Changeux et al. recently suggested that the SARS-CoV-2 spike (S) protein may interact with nicotinic acetylcholine receptors (nAChRs). Such interactions may be involved in pathology and infectivity. Here, we use molecular simulations of validated atomically detailed structures of nAChRs, and of the S protein, to investigate this "nicotinic hypothesis". We examine the binding of the Y674-R685 loop of the S protein to three nAChRs, namely the human α4β2 and α7 subtypes and the muscle-like αβγδ receptor from Tetronarce californica. Our results indicate that Y674-R685 has affinity for nAChRs and the region responsible for binding contains the PRRA motif, a four-residue insertion not found in other SARS-like coronaviruses. In particular, R682 has a key role in the stabilisation of the complexes as it forms interactions with loops A, B and C in the receptors binding pocket. The conformational behaviour of the bound Y674-R685 region is highly dependent on the receptor subtype, adopting extended conformations in the α4β2 and α7 complexes and more compact ones when bound to the muscle-like receptor. In the α4β2 and αβγδ complexes, the interaction of Y674-R685 with the receptors forces the loop C region to adopt an open conformation similar to other known nAChR antagonists. In contrast, in the α7 complex, Y674-R685 penetrates deeply into the binding pocket where it forms interactions with the residues lining the aromatic box, namely with TrpB, TyrC1 and TyrC2. Estimates of binding energy suggest that Y674-R685, forms stable complexes with all three nAChR subtypes, but has highest affinity for the muscle-type receptor. Analyses of the simulations of the full-length S protein show that the Y674-R685 region is accessible for binding, and suggest a potential binding orientation of the S protein with nAChRs.

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“…The energy contribution of each residue for the complexes formed by the Zinc 69 and Zinc 70 obtained by the MM-GBSA method are shown in Figure 9. In this gure on the right side is show the residue contributions to binding energies using the plugin CHEWD [53] with Chimera software. From this, favorable interactions are at the blue of the color scale, that is, those that contribute to the stabilization of ligand into complex, while the red color represents interaction by residue with positive values and corresponds to unfavorable interactions values.…”

Section: Molecular Dynamics Analysismentioning

confidence: 99%

Pharmacophore-based Virtual Screening From Phytocannabinoids for Anti-obesity Activity

Correia

Ferreira

Lima

et al. 2021

Preprint

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Search for new pharmacological alternatives for obesity is based on the design and development of compounds that can aid in weight loss so that they can be used safely and effectively over a long period while maintaining their function. The endocannabinoid system is related to obesity by increasing orexigenic signals and reducing satiety signals. Cannabis sativa is a medicinal plant of polypharmaceutical potential that has been widely studied for various medicinal purposes. The in silico evaluation of their natural cannabinoids (also called phytocannabinoids) for anti-obesity purpose stems from the existence of synthetic cannabinoid compounds that have already presented this result, but which did not guarantee patient safety. In order to find new molecules from C. sativa phytocannabinoids, with the potential to interact with the pharmacological target cannabinoid receptor 1, a pharmacophore-based virtual screening was performed, including the evaluation of physicochemical, pharmacokinetic, toxicological predictions and molecular docking. The results obtained from the ZINC12 database pointed to Zinc 69 (ZINC33053402) and Zinc 70 (ZINC19084698) molecules as promising anti-obesity agents. Molecular Dynamics (MD) studies discloses that both complexes were stable by analyzing the RMSD (Root Mean Square Deviation) values, and the binding free energy values demonstrate that the selected structures can interact and inhibit their catalytic activity.

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Visualizing protein–ligand binding with chemical energy-wise decomposition (CHEWD): application to ligand binding in the kallikrein-8 S1 Site

Cited by 17 publications

References 56 publications

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

Simulations support the interaction of the SARS-CoV-2 spike protein with nicotinic acetylcholine receptors

Pharmacophore-based Virtual Screening From Phytocannabinoids for Anti-obesity Activity

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