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1.
J Med Virol ; 95(10): e29145, 2023 10.
Artigo em Inglês | MEDLINE | ID: mdl-37804480

RESUMO

Along with the long pandemic of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has come the dilemma of emerging viral variants of concern (VOC), particularly Omicron and its subvariants, able to deftly escape immune surveillance and the otherwise protective effect of current vaccines and antibody drugs. We previously identified a peptide-based pan-CoV fusion inhibitor, termed as EK1, able to bind the HR1 region in viral spike (S) protein S2 subunit. This effectively blocked formation of the six-helix bundle (6-HB) fusion core and, thus, showed efficacy against all human coronaviruses (HCoVs). EK1 is now in phase 3 clinical trials. However, the peptide drug generally lacks oral availability. Therefore, we herein performed a structure-based virtual screening of the libraries of biologically active molecules and identified nine candidate compounds. One is Navitoclax, an orally active anticancer drug by inhibition of Bcl-2. Like EK1 peptide, it could bind HR1 and block 6-HB formation, efficiently inhibiting fusion and infection of all SARS-CoV-2 variants tested, as well as SARS-CoV and MERS-CoV, with IC50 values ranging from 0.5 to 3.7 µM. These findings suggest that Navitoclax is a promising repurposed drug candidate for development as a safe and orally available broad-spectrum antiviral drug to combat the current SARS-CoV-2 and its variants, as well as other HCoVs.


Assuntos
COVID-19 , SARS-CoV-2 , Humanos , Reposicionamento de Medicamentos , Peptídeos , Glicoproteína da Espícula de Coronavírus/metabolismo
2.
Int J Mol Sci ; 24(9)2023 Apr 29.
Artigo em Inglês | MEDLINE | ID: mdl-37175788

RESUMO

Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-CoV-2 mutations resulting in the emergence of new viral strains that can be resistant to the drugs used currently in the clinic necessitate the development of novel potent and broad therapeutic agents targeting different vulnerable spots of the viral proteins. In this study, two deep learning generative models were developed and used in combination with molecular modeling tools for de novo design of small molecule compounds that can inhibit the catalytic activity of SARS-CoV-2 main protease (Mpro), an enzyme critically important for mediating viral replication and transcription. As a result, the seven best scoring compounds that exhibited low values of binding free energy comparable with those calculated for two potent inhibitors of Mpro, via the same computational protocol, were selected as the most probable inhibitors of the enzyme catalytic site. In light of the data obtained, the identified compounds are assumed to present promising scaffolds for the development of new potent and broad-spectrum drugs inhibiting SARS-CoV-2 Mpro, an attractive therapeutic target for anti-COVID-19 agents.


Assuntos
Inteligência Artificial , Tratamento Farmacológico da COVID-19 , Proteases 3C de Coronavírus , Descoberta de Drogas , Bibliotecas de Moléculas Pequenas , Modelos Moleculares , Bibliotecas de Moléculas Pequenas/farmacologia , Bibliotecas de Moléculas Pequenas/uso terapêutico , Proteases 3C de Coronavírus/antagonistas & inibidores , Descoberta de Drogas/métodos , Redes Neurais de Computação
3.
Mol Inform ; 43(1): e202300262, 2024 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-37833243

RESUMO

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find 'consensus compounds'. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding-, cleavage-, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS-CoV-2 treatments.


Assuntos
COVID-19 , SARS-CoV-2 , Humanos , Pandemias , Bioensaio , Descoberta de Drogas
4.
J Biomol Struct Dyn ; : 1-13, 2023 Dec 13.
Artigo em Inglês | MEDLINE | ID: mdl-38088766

RESUMO

The emergence of new Mycobacterium tuberculosis (Mtb) strains resistant to the key drugs currently used in the clinic for tuberculosis treatment can substantially reduce the probability of therapy success, causing the relevance and importance of studies on the development of novel potent antibacterial agents targeting different vulnerable spots of Mtb. In this study, 28,860 compounds from the library of bioactive molecules were screened to identify novel potential inhibitors of ß-ketoacyl-acyl carrier protein synthase I (KasA), one of the key enzymes involved in the biosynthesis of mycolic acids of the Mtb cell wall. In doing so, we used a structure-based virtual screening approach to drug repurposing that included high-throughput docking of the C171Q KasA enzyme with compounds from the library of bioactive molecules including the FDA-approved drugs and investigational drug candidates, assessment of the binding affinity for the docked ligand/C171Q KasA complexes, and molecular dynamics simulations followed by binding free energy calculations. As a result, post-modeling analysis revealed 6 top-ranking compounds exhibiting a strong attachment to the malonyl binding site of the enzyme, as evidenced by the values of binding free energy which are significantly lower than those predicted for the KasA inhibitor TLM5 used in the calculations as a positive control. In light of the data obtained, the identified compounds are suggested to form a good basis for the development of new antitubercular molecules of clinical significance with activity against the KasA enzyme of Mtb.Communicated by Ramaswamy H. Sarma.

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