A multiple-step <i>in silico</i> screening protocol to identify allosteric inhibitors of Spike–hACE2 binding

Zhai, Jingchen; He, Xibing; Man, Viet Hoang; Sun, Yuchen; Ji, Beihong; Cai, Lianjin; Wang, Junmei

doi:10.1039/d1cp04736a

Cited by 9 publications

(6 citation statements)

References 43 publications

(40 reference statements)

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“…18 Taking the calculated results and visual analysis, 4 compounds (3719810, 17980455, 10199019, and 17823867) were identified with reasonable binding poses in two targets, and their molecular docking scores are shown in Table 1. The docking scores of the 4 compounds were from À7.025 to À10.156 lower than À7.0 kcal mol À1 , 72 which indicated that all molecules were able to effectively bind in hNET and hDAT, and reflected to some extent their abilities to combine with targets. Their docking poses and the conformations of the 4 compounds are illustrated in the ESI, † Fig.…”

Section: Compound Selection Based On Homology Modeling and Molecular ...mentioning

confidence: 93%

A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression

Wang

Yan

Dong

et al. 2023

Phys. Chem. Chem. Phys.

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Section: Compound Selection Based On Homology Modeling and Molecular ...mentioning

confidence: 93%

A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression

Wang

Yan

Dong

et al. 2023

Phys. Chem. Chem. Phys.

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“…A library of drug-like molecules and a smaller library of validated allosteric modulators were compiled for screening against site A (Figure 4) and site B (Figure 5). Library 1 consisted of 200 drug-like compounds from ZINC database that showed SARS-CoV-2 in vitro activity [57]. For this library, we used the compounds with the highest affinity for the two druggable sites on the RBD [57].…”

Section: Simulations Of the Sars-cov-2 Spike Trimers And Analysis Of ...mentioning

confidence: 99%

“…Utilizing screening data from the SARS-CoV-2 cytopathic effect reduction assay, two iterative rounds of virtual screening of small molecules were then performed against SARS-CoV-2, resulting in the identification of ACE2 allosteric inhibitors [56]. A large-scale computational study presented a multiple-step in silico screening protocol to identify allosteric inhibitors of S-ACE2 binding in which a compound library containing 77,448 antiviral compounds was screened using molecular docking and binding affinity calculations [57]. The use of screening of library of organic dyes and related drug-like compounds led to the identification of several small-molecule compounds, showing promising broad-spectrum inhibition of the S-ACE2 interactions acting as blockers of viral attachment for SARS-CoV-2 [58].…”

Section: Introductionmentioning

confidence: 99%

“…These binding sites included the allosteric site located at the junction of SD1 and SD2 and flanked by residues F541, K557, and I587 on one protomer and I834, F855, M740, and D745 of the neighboring protomer (referred to as site A) [33] and the allosteric site targeted by sialic acid (referred to as site B) which is flanked by residues R403, D495, R408, S375, and K378 [35]. The first set of docked small molecules (referred to as Library 1) consisted of 200 drug-like compounds that showed in vitro activity against SARS-CoV-2 [57]. This library of drug-like molecules was screened to (a) evaluate whether the two experimentally validated allosteric binding sites in the S trimers could serve as a drug binding pocket for these compounds and (b) determine structural and energetic determinants of ligand binding in the known allosteric binding sites and suggest putative allosteric inhibitors based on the rigorously computed binding energetics.…”

Section: Introductionmentioning

confidence: 99%

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Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking

Gupta,

Verkhivker

2024

IJMS

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Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.

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“…Despite the decrease in deaths after the beginning of the vaccination programs, the continuous mutation of the virus has reduced the protective efficacy of the available vaccines and monoclonal antibodies (mAbs) ( Harvey et al, 2021 ; McCarthy et al, 2021 ; Cox et al, 2023 ). Moreover, only a few drugs have shown some degree of efficacy in treating the infection and its complications, with some of them being reported to present severe side effects, resistance, and rebound phenomena ( Kobryn et al, 2021 ; Anderson et al, 2022 ; Charness et al, 2022 ; Zhai et al, 2022 ; Iketani et al, 2023 ; Moghadasi et al, 2023 ). Thus, intensive research has been carried out to find efficient therapies for the treatment and prevention of the current and future coronavirus outbreaks.…”

Section: Introductionmentioning

confidence: 99%

Investigation of protein-protein interactions and hotspot region on the NSP7-NSP8 binding site in NSP12 of SARS-CoV-2

Lima Neto,

Bezerra,

Barbosa

et al. 2024

Front. Mol. Biosci.

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Background: The RNA-dependent RNA polymerase (RdRp) complex, essential in viral transcription and replication, is a key target for antiviral therapeutics. The core unit of RdRp comprises the nonstructural protein NSP12, with NSP7 and two copies of NSP8 (NSP81 and NSP82) binding to NSP12 to enhance its affinity for viral RNA and polymerase activity. Notably, the interfaces between these subunits are highly conserved, simplifying the design of molecules that can disrupt their interaction.Methods: We conducted a detailed quantum biochemical analysis to characterize the interactions within the NSP12-NSP7, NSP12-NSP81, and NSP12-NSP82 dimers. Our objective was to ascertain the contribution of individual amino acids to these protein-protein interactions, pinpointing hotspot regions crucial for complex stability.Results: The analysis revealed that the NSP12-NSP81 complex possessed the highest total interaction energy (TIE), with 14 pairs of residues demonstrating significant energetic contributions. In contrast, the NSP12-NSP7 complex exhibited substantial interactions in 8 residue pairs, while the NSP12-NSP82 complex had only one pair showing notable interaction. The study highlighted the importance of hydrogen bonds and π-alkyl interactions in maintaining these complexes. Intriguingly, introducing the RNA sequence with Remdesivir into the complex resulted in negligible alterations in both interaction energy and geometric configuration.Conclusion: Our comprehensive analysis of the RdRp complex at the protein-protein interface provides invaluable insights into interaction dynamics and energetics. These findings can guide the design of small molecules or peptide/peptidomimetic ligands to disrupt these critical interactions, offering a strategic pathway for developing effective antiviral drugs.

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A multiple-step in silico screening protocol to identify allosteric inhibitors of Spike–hACE2 binding

Abstract: While the COVID-19 pandemic keeps deteriorating, the effective medicines target the life cycle of SARS-CoV-2 are still under development. With more highly infective and dangerous variants of the coronavirus emerged,...

Cited by 9 publications

References 43 publications

A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression

A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression

Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking

Investigation of protein-protein interactions and hotspot region on the NSP7-NSP8 binding site in NSP12 of SARS-CoV-2

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