Toward Atomistic Modeling of Irreversible Covalent Inhibitor Binding Kinetics.
J Chem Inf Model
; 59(9): 3955-3967, 2019 09 23.
Article
em En
| MEDLINE
| ID: mdl-31425654
Covalent inhibitors have emerged as an important drug class in recent years, largely due to their many unique advantages as compared to noncovalent inhibitors, including longer duration of action, lower prolonged systemic exposure, higher potency, and selectivity. However, the potential off-target toxicity of covalent inhibitors, particularly of irreversible covalent inhibitors, represents a great challenge in covalent drug development. Therefore, accurate calculation of protein covalent inhibitor reaction kinetics to guide the design of selective inhibitors would greatly benefit covalent drug discovery efforts. In the present paper, we present a computational method to calculate the relative reaction kinetics between congeneric irreversible covalent inhibitors and their protein receptors. The method combines density functional theory calculations of the transition state barrier height of the rate-limiting step for reaction between the warhead of the inhibitor and a single protein residue, and molecular-mechanics-based free energy calculations to account for the interactions between the ligand in the transition state and the protein environment. The method was tested on four pharmaceutically interesting irreversible covalent binding systems involving 28 ligands; the mean unsigned error (MUE) of the relative reaction rate for all pairs of ligands between the predictions and experimental results for these tested systems is 0.79 log unit. This is to our knowledge the first time where the reaction kinetics of protein irreversible covalent inhibition have been directly calculated with physics-based free energy calculation methods and transition state theory. We anticipate the outstanding accuracy demonstrated here across a broad range of target classes will have a strong impact on the design of selective covalent inhibitors.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Proteínas
/
Modelos Moleculares
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
J Chem Inf Model
Assunto da revista:
INFORMATICA MEDICA
/
QUIMICA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Estados Unidos