Identification of 1,2,3-triazole-phthalimide derivatives as potential drugs against COVID-19: a virtual screening, docking and molecular dynamic study

Abstract

In this work we aimed to perform an in silico predictive screening, docking and molecular dynamic study to identify 1,2,3-triazole-phthalimide derivatives as drug candidates against SARS-CoV-2. The in silico prediction of pharmacokinetic and toxicological properties of hundred one 1,2,3-triazole-phtalimide derivatives, obtained from SciFinder® library, were investigated. Compounds that did not show good gastrointestinal absorption, violated the Lipinski's rules, proved to be positive for the AMES test, and showed to be hepatotoxic or immunotoxic in our ADMET analysis, were filtered out of our study. The hit compounds were further subjected to molecular docking on SARS-CoV-2 target proteins. The ADMET analysis revealed that 43 derivatives violated the Lipinski’s rules and 51 other compounds showed to be positive for the toxicity test. Seven 1,2,3-triazole-phthalimide derivatives (A7, A8, B05, E35, E38, E39, and E40) were selected for molecular docking and MFCC—ab initio analysis. The results of molecular docking pointed the derivative E40 as a promising compound interacting with multiple target proteins of SARS-CoV-2. The complex E40-M^pro was found to have minimum binding energy of −10.26 kcal/mol and a general energy balance, calculated by the quantum mechanical analysis, of −8.63 eV. MD simulation and MMGBSA calculations confirmed that the derivatives E38 and E40 have high binding energies of −63.47 ± 3 and −63.31 ± 7 kcal/mol against SARS-CoV-2 main protease. In addition, the derivative E40 exhibited excellent interaction values and inhibitory potential against SAR-Cov-2 main protease and viral nucleocapsid proteins, suggesting this derivative as a potent antiviral for the treatment and/or prophylaxis of COVID-19.

Communicated by Ramaswamy H. Sarma

Keywords:

• Antiviral
• SARS-CoV-2
• phthalimide
• 123-triazole
• MD simulation

Acknowledgement

Vanderlan Nogueira Holanda would like to thank Fundação de Amparo a Ciência e Tecnologia do Estado de Pernambuco (FACEPE) for the graduate scholarship (IBPG-0333-2.08/18).

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

This work was supported by the Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (FACEPE, BFT-109-2.08/18 and BIC-0489-2.13/20) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, PQ-400749/2019-0 and 312675/2018-6), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES code 001), Instituto Aggeu Magalhães and Inova-Fiocruz Program (VPPCB-007-FIO-18-2-85).