An Overview of Computational Methods, Tools, Servers, and Databases for Drug Repurposing

Sarvagalla, Sailu; Syed, Safiulla Basha; Coumar, Mohane Selvaraj

doi:10.1016/b978-0-12-816125-8.00025-0

Cited by 20 publications

(9 citation statements)

References 153 publications

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“…Since the last decade, the Drug's use design techniques by computer software has provided very excellent results for drug discovery and research process [22,23], among the effective and useful methods for drug design are the three-dimensional quantitative structure-activity relationship (3D-QSAR), hence to molecular docking and the pharmacokinetic parameters (ADMET). In the purpose to pursue our previous works on antimalarial [24,25,26].…”

Section: Introductionmentioning

confidence: 99%

3D-QSAR, docking and ADMET properties of aurone analogues as antimalarial agents

Hadni

Elhallaoui

2020

Heliyon

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The development of multi-resistant strains of plasmodium parasite has become a global problem, therefore, the discovery of new antimalarial agents is the only available solution. In order to improve and propose new compounds with antimalarial activity, the three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking studies were carried on aurone analogues acting as Qo site inhibitors in cytochrome b. The 3D-QSAR model was established in this study based on the Comparative Molecular Field Analysis (CoMFA) and the Comparative Molecular Similarity Indices Analysis (CoMSIA). The good predictability was obtained using the CoMFA model (Q 2 ¼ 0.5; R 2 ¼ 0.97; R 2 pred ¼ 0.72) and the best CoMSIA model (Q 2 ¼ 0.526; R 2 ¼ 0.915; R 2 pred ¼ 0.765). The predictive capacity of the developed model was evaluated through external validation using a test set compound and an applicability domain technique. In this study, the Steric, electrostatic and hydrogen bond acceptor fields played a key role in antimalarial activity. The results of the molecular docking revealed theoretically the importance of the residues his183 and his82 in the active site of the heme b L , this result was validated by a new assessment method. Based on the previous results, we designed several new potent Cytochrome b inhibitors and their inhibitory activities were predicted by the best model. Furthermore, these new inhibitors were analyzed for their ADMET properties and drug likeness. These results would be of great help in leading optimization for new drug discovery that can solve the problem of multiple drug resistance.

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Section: Introductionmentioning

confidence: 99%

3D-QSAR, docking and ADMET properties of aurone analogues as antimalarial agents

Hadni

Elhallaoui

2020

Heliyon

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“…In recent years, the use of molecular simulation methods in chemoinformatics (chemical molecules) and structural bioinformatics (proteins) has produced very impressive results in the drug discovery process [ 18 , 19 ]. In this study, we have performed a molecular docking study to explore the potential inhibitory activity of some commonly used medicinal plants.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of flavonoids as potential inhibitors of the SARS-CoV-2 main protease and spike RBD: Molecular docking, ADMET evaluation and molecular dynamics simulations

Hadni

Fitri²,

Benjelloun³

et al. 2022

Journal of the Indian Chemical Society

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“…Computer-aided discovery of repurposed drugs helps avoid costly trial-and-error experiments involving cultured cells, biochemical screenings, and live systems . As an example, baricitinib (a rheumatoid arthritis drug) was predicted using artificial intelligence as a repurposed drug , and was later granted an FDA-emergency approval for treatment of COVID-19 in combination with redemsivir. , However, most of the computational studies in the COVID-19 repositioning landscape were found to be lacking support from experimental results.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Consensus Analysis of SARS-CoV-2 Drug Repurposing Campaigns

Mslati

Gentile

Perez

et al. 2021

J. Chem. Inf. Model.

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The current COVID-19 pandemic has elicited extensive repurposing efforts (both small and large scale) to rapidly identify COVID-19 treatments among approved drugs. Herein, we provide a literature review of large-scale SARS-CoV-2 antiviral drug repurposing efforts and highlight a marked lack of consistent potency reporting. This variability indicates the importance of standardizing best practices—including the use of relevant cell lines, viral isolates, and validated screening protocols. We further surveyed available biochemical and virtual screening studies against SARS-CoV-2 targets (Spike, ACE2, RdRp, PL pro , and M pro ) and discuss repurposing candidates exhibiting consistent activity across diverse, triaging assays and predictive models. Moreover, we examine repurposed drugs and their efficacy against COVID-19 and the outcomes of representative repurposed drugs in clinical trials. Finally, we propose a drug repurposing pipeline to encourage the implementation of standard methods to fast-track the discovery of candidates and to ensure reproducible results.

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An Overview of Computational Methods, Tools, Servers, and Databases for Drug Repurposing

Cited by 20 publications

References 153 publications

3D-QSAR, docking and ADMET properties of aurone analogues as antimalarial agents

3D-QSAR, docking and ADMET properties of aurone analogues as antimalarial agents

Evaluation of flavonoids as potential inhibitors of the SARS-CoV-2 main protease and spike RBD: Molecular docking, ADMET evaluation and molecular dynamics simulations

Comprehensive Consensus Analysis of SARS-CoV-2 Drug Repurposing Campaigns

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