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Free-energy perturbation simulation on transition states and redesign of butyrylcholinesterase.

ABSTRACT: It is recognized that an ideal anti-cocaine treatment is to accelerate cocaine metabolism by producing biologically inactive metabolites via a route similar to the primary cocaine-metabolizing pathway, i.e., butyrylcholinesterase (BChE)-catalyzed hydrolysis of cocaine. BChE mutants with a higher catalytic activity against (-)-cocaine are highly desired for use as an exogenous enzyme in humans. To develop a rational design for high-activity mutants, we carried out free-energy perturbation (FEP) simulations on various mutations of the transition-state structures in addition to the corresponding free-enzyme structures by using an extended FEP procedure. The FEP simulations on the mutations of both the free-enzyme and transition-state structures allowed us to calculate the mutation-caused shift of the free-energy change from the free enzyme (BChE) to the transition state, and thus to theoretically predict the mutation-caused shift of the catalytic efficiency (k(cat)/K(M)). The computational predictions are supported by the kinetic data obtained from the wet experiments, demonstrating that the FEP-based computational design approach is promising for rational design of high-activity mutants of an enzyme. One of the BChE mutants designed and discovered in this study has an approximately 1800-fold improved catalytic efficiency against (-)-cocaine compared to wild-type BChE. The high-activity mutant may be therapeutically valuable.

SUBMITTER: Yang W

PROVIDER: S-EPMC2717303 | biostudies-literature | 2009 Mar

REPOSITORIES: biostudies-literature

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Free-energy perturbation simulation on transition states and redesign of butyrylcholinesterase.

Yang Wenchao W Pan Yongmei Y Zheng Fang F Cho Hoon H Tai Hsin-Hsiung HH Zhan Chang-Guo CG

Biophysical journal 20090301 5

It is recognized that an ideal anti-cocaine treatment is to accelerate cocaine metabolism by producing biologically inactive metabolites via a route similar to the primary cocaine-metabolizing pathway, i.e., butyrylcholinesterase (BChE)-catalyzed hydrolysis of cocaine. BChE mutants with a higher catalytic activity against (-)-cocaine are highly desired for use as an exogenous enzyme in humans. To develop a rational design for high-activity mutants, we carried out free-energy perturbation (FEP) s ...[more]

PMID: 19254552

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Project description:Free-energy calculations play an important role in the application of computational chemistry to a range of fields, including protein biochemistry, rational drug design, or materials science. Importantly, the free-energy difference is directly related to experimentally measurable quantities such as partition and adsorption coefficients, water activity, and binding affinities. Among several techniques aimed at predicting free-energy differences, perturbation approaches, involving the alchemical transformation of one molecule into another through intermediate states, stand out as rigorous methods based on statistical mechanics. However, despite the importance of free-energy calculations, the applicability of the perturbation approaches is still largely impeded by a number of challenges, including the definition of the perturbation path, i.e., alchemical changes leading to the transformation of one molecule to the other. To address this, an automatic perturbation topology builder based on a graph-matching algorithm is developed, which can identify the maximum common substructure (MCS) of two or multiple molecules and provide the perturbation topologies suitable for free-energy calculations using the GROMOS and the GROMACS simulation packages. Various MCS search options are presented leading to alternative definitions of the perturbation pathway. Moreover, perturbation topologies generated using the default multistate MCS search are used to calculate the changes in free energy between lysine and its two post-translational modifications, 3-methyllysine and acetyllysine. The pairwise free-energy calculations performed on this test system led to a cycle closure of 0.5 ± 0.3 and 0.2 ± 0.2 kJ mol-1, with GROMOS and GROMACS simulation packages, respectively. The same relative free energies between the three states are obtained by employing the enveloping distribution sampling (EDS) approach when compared to the pairwise perturbations. Importantly, this toolkit is made available online as an open-source Python package (https://github.com/drazen-petrov/SMArt).

Project description:The rapid growth of structural information for G-protein-coupled receptors (GPCRs) has led to a greater understanding of their structure, function, selectivity, and ligand binding. Although novel ligands have been identified using methods such as virtual screening, computationally driven lead optimization has been possible only in isolated cases because of challenges associated with predicting binding free energies for related compounds. Here, we provide a systematic characterization of the performance of free-energy perturbation (FEP) calculations to predict relative binding free energies of congeneric ligands binding to GPCR targets using a consistent protocol and no adjustable parameters. Using the FEP+ package, first we validated the protocol, which includes a full lipid bilayer and explicit solvent, by predicting the binding affinity for a total of 45 different ligands across four different GPCRs (adenosine A2AAR, β1 adrenergic, CXCR4 chemokine, and δ opioid receptors). Comparison with experimental binding affinity measurements revealed a highly predictive ranking correlation (average spearman ρ = 0.55) and low root-mean-square error (0.80 kcal/mol). Next, we applied FEP+ in a prospective project, where we predicted the affinity of novel, potent adenosine A2A receptor (A2AR) antagonists. Four novel compounds were synthesized and tested in a radioligand displacement assay, yielding affinity values in the nanomolar range. The affinity of two out of the four novel ligands (plus three previously reported compounds) was correctly predicted (within 1 kcal/mol), including one compound with approximately a tenfold increase in affinity compared to the starting compound. Detailed analyses of the simulations underlying the predictions provided insights into the structural basis for the two cases where the affinity was overpredicted. Taken together, these results establish a protocol for systematically applying FEP+ to GPCRs and provide guidelines for identifying potent molecules in drug discovery lead optimization projects.

Dataset Information

Free-energy perturbation simulation on transition states and redesign of butyrylcholinesterase.

Publications

Free-energy perturbation simulation on transition states and redesign of butyrylcholinesterase.

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