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1.
J Phys Chem B ; 128(7): 1595-1605, 2024 Feb 22.
Artigo em Inglês | MEDLINE | ID: mdl-38323915

RESUMO

Alchemical transformations can be used to quantitatively estimate absolute binding free energies at a reasonable computational cost. However, most of the approaches currently in use require knowledge of the correct (crystallographic) pose. In this paper, we present a combined Hamiltonian replica exchange nonequilibrium alchemical method that allows us to reliably calculate absolute binding free energies, even when starting from suboptimal initial binding poses. Performing a preliminary Hamiltonian replica exchange enhances the sampling of slow degrees of freedom of the ligand and the target, allowing the system to populate the correct binding pose when starting from an approximate docking pose. We apply the method on 6 ligands of the first bromodomain of the BRD4 bromodomain-containing protein. For each ligand, we start nonequilibrium alchemical transformations from both the crystallographic pose and the top-scoring docked pose that are often significantly different. We show that the method produces statistically equivalent binding free energies, making it a useful tool for computational drug discovery pipelines.


Assuntos
Simulação de Dinâmica Molecular , Proteínas Nucleares , Ligação Proteica , Termodinâmica , Ligantes , Fatores de Transcrição
2.
J Chem Inf Model ; 61(11): 5320-5326, 2021 11 22.
Artigo em Inglês | MEDLINE | ID: mdl-34723516

RESUMO

We describe a step-by-step protocol for the computation of absolute dissociation free energy with GROMACS code and PLUMED library, which exploits a combination of advanced sampling techniques and nonequilibrium alchemical methodologies. The computational protocol has been automated through an open source Python middleware (HPC_Drug) which allows one to set up the GROMACS/PLUMED input files for execution on high performing computing facilities. The proposed protocol, by exploiting its inherent parallelism and the power of the GROMACS code on graphical processing units, has the potential to afford accurate and precise estimates of the dissociation constants in drug-receptor systems described at the atomistic level. The procedure has been applied to the calculation of the absolute dissociation free energy of PF-07321332, an oral antiviral proposed by Pfizer, with the main protease (3CLpro) of SARS-CoV-2.


Assuntos
COVID-19 , Simulação de Dinâmica Molecular , Antivirais , Entropia , Lactamas , Leucina , Nitrilas , Prolina , SARS-CoV-2
3.
J Chem Theory Comput ; 16(11): 7160-7172, 2020 Nov 10.
Artigo em Inglês | MEDLINE | ID: mdl-33090785

RESUMO

In the context of drug-receptor binding affinity calculations using molecular dynamics techniques, we implemented a combination of Hamiltonian replica exchange (HREM) and a novel nonequilibrium alchemical methodology, called virtual double-system single-box, with increased accuracy, precision, and efficiency with respect to the standard nonequilibrium approaches. The method has been applied for the determination of absolute binding free energies of 16 newly designed noncovalent ligands of the main protease (3CLpro) of SARS-CoV-2. The core structures of 3CLpro ligands were previously identified using a multimodal structure-based ligand design in combination with docking techniques. The calculated binding free energies for four additional ligands with known activity (either for SARS-CoV or SARS-CoV-2 main protease) are also reported. The nature of binding in the 3CLpro active site and the involved residues besides the CYS-HYS catalytic dyad have been thoroughly characterized by enhanced sampling simulations of the bound state. We have identified several noncongeneric compounds with predicted low micromolar activity for 3CLpro inhibition, which may constitute possible lead compounds for the development of antiviral agents in Covid-19 treatment.


Assuntos
Betacoronavirus/enzimologia , Cisteína Endopeptidases/metabolismo , Proteínas não Estruturais Virais/metabolismo , Antivirais/farmacologia , Antivirais/uso terapêutico , COVID-19 , Proteases 3C de Coronavírus , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/virologia , Humanos , Ligantes , Simulação de Acoplamento Molecular , Pandemias , Pneumonia Viral/tratamento farmacológico , Pneumonia Viral/virologia , Inibidores de Proteases/farmacologia , Inibidores de Proteases/uso terapêutico , Ligação Proteica , SARS-CoV-2 , Interface Usuário-Computador , Proteínas não Estruturais Virais/antagonistas & inibidores
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