Discovery of potent Covid‐19 main protease inhibitors using integrated drug‐repurposing strategy

T, Muthu Kumar; Rohini, K.; James, Nicola; Shanthi,; Ramanathan, K.

doi:10.1002/bab.2159

Cited by 4 publications

(2 citation statements)

References 55 publications

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“…For each conformation, the complex structures obtained by docking were subjected to the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) scoring function to calculate the binding free energy (Schrödinger, 2023). MM-GBSA, a free-energy prediction method that strikes a balance between accuracy and speed, is widely used for affinity-based virtual screening and optimization of docking structures. − For each inhibitor, the conformation with the lowest binding free energy was selected. We also investigated the similarity between the structures of the 91 inhibitors and the 41 inhibitors with complex structures determined by X-ray.…”

Section: Methodsmentioning

confidence: 99%

Accurate Characterization of Binding Kinetics and Allosteric Mechanisms for the HSP90 Chaperone Inhibitors Using AI-Augmented Integrative Biophysical Studies

Xu,

Zhang,

Zhao

et al. 2024

JACS Au

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The binding kinetics of drugs to their targets are gradually being recognized as a crucial indicator of the efficacy of drugs in vivo, leading to the development of various computational methods for predicting the binding kinetics in recent years. However, compared with the prediction of binding affinity, the underlying structure and dynamic determinants of binding kinetics are more complicated. Efficient and accurate methods for predicting binding kinetics are still lacking. In this study, quantitative structure−kinetics relationship (QSKR) models were developed using 132 inhibitors targeting the ATP binding domain of heat shock protein 90α (HSP90α) to predict the dissociation rate constant (k off ), enabling a direct assessment of the drug−target residence time. These models demonstrated good predictive performance, where hydrophobic and hydrogen bond interactions significantly influence the k off prediction. In subsequent applications, our models were used to assist in the discovery of new inhibitors for the N-terminal domain of HSP90α (N-HSP90α), demonstrating predictive capabilities on an experimental validation set with a new scaffold. In X-ray crystallography experiments, the loop-middle conformation of apo N-HSP90α was observed for the first time (previously, the loop-middle conformation had only been observed in holo-N-HSP90α structures). Interestingly, we observed different conformations of apo N-HSP90α simultaneously in an asymmetric unit, which was also observed in a holo-N-HSP90α structure, suggesting an equilibrium of conformations between different states in solution, which could be one of the determinants affecting the binding kinetics of the ligand. Different ligands can undergo conformational selection or alter the equilibrium of conformations, inducing conformational rearrangements and resulting in different effects on binding kinetics. We then used molecular dynamics simulations to describe conformational changes of apo N-HSP90α in different conformational states. In summary, the study of the binding kinetics and molecular mechanisms of N-HSP90α provides valuable information for the development of more targeted therapeutic approaches.

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Section: Methodsmentioning

confidence: 99%

Accurate Characterization of Binding Kinetics and Allosteric Mechanisms for the HSP90 Chaperone Inhibitors Using AI-Augmented Integrative Biophysical Studies

Xu,

Zhang,

Zhao

et al. 2024

JACS Au

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“…Additionally, the emergence and rapid spreading of novel SARS-CoV-2 across the globe enhanced the use of in silico tools such as integrated machine-learning-based drug-repurposing strategies. Although the outputs of such studies await further experimental confirmation, compounds resulting from these analyses have much better in silico safety profiles when compared to existing antivirals inhibiting SARS-CoV-2 proteases [72].…”

Section: "Tailored" Inhibitors For Better Bioavailability and Reduced Toxicitymentioning

confidence: 99%

Protease Inhibition—An Established Strategy to Combat Infectious Diseases

Sojka

Šnebergerová

Robbertse

2021

IJMS

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Therapeutic agents with novel mechanisms of action are urgently needed to counter the emergence of drug-resistant infections. Several decades of research into proteases of disease agents have revealed enzymes well suited for target-based drug development. Among them are the three recently validated proteolytic targets: proteasomes of the malarial parasite Plasmodium falciparum, aspartyl proteases of P. falciparum (plasmepsins) and the Sars-CoV-2 viral proteases. Despite some unfulfilled expectations over previous decades, the three reviewed targets clearly demonstrate that selective protease inhibitors provide effective therapeutic solutions for the two most impacting infectious diseases nowadays—malaria and COVID-19.

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Discovery of potent Covid‐19 main protease inhibitors using integrated drug‐repurposing strategy

Rohini

James

et al. 2021

Biotech and App Biochem

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The emergence and rapid spreading of novel SARS-CoV-2 across the globe represent an imminent threat to public health. Novel antiviral therapies are urgently needed to overcome this pandemic. Given the significant role of the main protease of Covid-19 for virus replication, we performed a drug-repurposing study using the recently deposited main protease structure, 6LU7. For instance, pharmacophore-and e-pharmacophore-based hypotheses such as AARRH and AARR, respectively, were developed using available small molecule inhibitors and utilized in the screening of the DrugBank repository. Further, a hierarchical docking protocol was implemented with the support of the Glide algorithm. The resultant compounds were then examined for their binding free energy against the main protease of Covid-19 by means of the Prime-MM/GBSA algorithm. Most importantly, the machine learning-based AutoQSAR algorithm was used to predict the antiviral activities of resultant compounds. The hit molecules were also examined for their drug-likeness and toxicity parameters through the QikProp algorithm. Finally, the hit compounds activity against the main protease was validated using molecular dynamics simulation studies. Overall, the present analysis yielded two potential inhibitors (DB02986 and DB08573) that are predicted to bind with the main protease of Covid-19 better than currently used drug molecules such as N3 (cocrystallized native ligand), lopinavir, and ritonavir.

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Discovery of potent Covid‐19 main protease inhibitors using integrated drug‐repurposing strategy

Cited by 4 publications

References 55 publications

Accurate Characterization of Binding Kinetics and Allosteric Mechanisms for the HSP90 Chaperone Inhibitors Using AI-Augmented Integrative Biophysical Studies

Accurate Characterization of Binding Kinetics and Allosteric Mechanisms for the HSP90 Chaperone Inhibitors Using AI-Augmented Integrative Biophysical Studies

Protease Inhibition—An Established Strategy to Combat Infectious Diseases

Discovery of potent Covid‐19 main protease inhibitors using integrated drug‐repurposing strategy

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