Duan L.,East China Normal University |
Duan L.,Shandong Normal University |
Liu X.,East China Normal University |
Zhang J.Z.H.,East China Normal University |
And 3 more authors.
Journal of the American Chemical Society | Year: 2016
Efficient and reliable calculation of protein-ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to protein- ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in protein-ligand binding, the new method calculates the entropic component (interaction entropy or -TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the standard normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calculation of this effect. © 2016 American Chemical Society.
Lei J.,Nanjing University |
Zhou Y.,Nanjing University |
Xie D.,Nanjing University |
Xie D.,Anhui University of Science and Technology |
And 2 more authors.
Journal of the American Chemical Society | Year: 2015
Aspirin, one of the oldest and most common anti-inflammatory agents, has recently been shown to reduce cancer risks. The principal pharmacological effects of aspirin are known to arise from its covalent modification of cyclooxygenase-2 (COX-2) through acetylation of Ser530, but the detailed mechanism of its biochemical action and specificity remains to be elucidated. In this work, we have filled this gap by employing a state-of-the-art computational approach, Born-Oppenheimer molecular dynamics simulations with ab initio quantum mechanical/molecular mechanical potential and umbrella sampling. Our studies have characterized a substrate-assisted inhibition mechanism for aspirin acetylating COX: it proceeds in two successive stages with a metastable tetrahedral intermediate, in which the carboxyl group of aspirin serves as the general base. The computational results confirmed that aspirin would be 10-100 times more potent against COX-1 than against COX-2, and revealed that this inhibition specificity between the two COX isoforms can be attributed mainly to the difference in kinetics rate of the covalent inhibition reaction, not the aspirin-binding step. The structural origin of this differential inhibition of the COX enzymes by aspirin has also been elucidated. © 2014 American Chemical Society.
Margul D.T.,New York University |
Tuckerman M.E.,New York University |
Tuckerman M.E.,Courant Institute of Mathematical Sciences |
Tuckerman M.E.,Center for Computational Chemistry at Shanghai
Journal of Chemical Theory and Computation | Year: 2016
Molecular dynamics remains one of the most widely used computational tools in the theoretical molecular sciences to sample an equilibrium ensemble distribution and/or to study the dynamical properties of a system. The efficiency of a molecular dynamics calculation is limited by the size of the time step that can be employed, which is dictated by the highest frequencies in the system. However, many properties of interest are connected to low-frequency, long time-scale phenomena, requiring many small time steps to capture. This ubiquitous problem can be ameliorated by employing multiple time-step algorithms, which assign different time steps to forces acting on different time scales. In such a scheme, fast forces are evaluated more frequently than slow forces, and as the former are often computationally much cheaper to evaluate, the savings can be significant. Standard multiple time-step approaches are limited, however, by resonance phenomena, wherein motion on the fastest time scales limits the step sizes that can be chosen for the slower time scales. In atomistic models of biomolecular systems, for example, the largest time step is typically limited to around 5 fs. Previously, we introduced an isokinetic extended phase-space algorithm (Minary et al. Phys. Rev. Lett. 2004, 93, 150201) and its stochastic analog (Leimkuhler et al. Mol. Phys. 2013, 111, 3579) that eliminate resonance phenomena through a set of kinetic energy constraints. In simulations of a fixed-charge flexible model of liquid water, for example, the time step that could be assigned to the slow forces approached 100 fs. In this paper, we develop a stochastic isokinetic algorithm for multiple time-step molecular dynamics calculations using a polarizable model based on fluctuating dipoles. The scheme developed here employs two sets of induced dipole moments, specifically, those associated with short-range interactions and those associated with a full set of interactions. The scheme is demonstrated on the polarizable AMOEBA water model. As was seen with fixed-charge models, we are able to obtain large time steps exceeding 100 fs, allowing calculations to be performed 10 to 20 times faster than standard thermostated molecular dynamics. © 2016 American Chemical Society.
Zhou J.,Sun Yat Sen University |
Li M.,Sun Yat Sen University |
Chen N.,Sun Yat Sen University |
Wang S.,New York University |
And 4 more authors.
ACS Chemical Biology | Year: 2015
Development of isoform-selective histone deacetylase (HDAC) inhibitors is of great biological and medical interest. Among 11 zinc-dependent HDAC isoforms, it is particularly challenging to achieve isoform inhibition selectivity between HDAC1 and HDAC2 due to their very high structural similarities. In this work, by developing and applying a novel de novo reaction-mechanism-based inhibitor design strategy to exploit the reactivity difference, we have discovered the first HDAC2-selective inhibitor, β-hydroxymethyl chalcone. Our bioassay experiments show that this new compound has a unique time-dependent selective inhibition on HDAC2, leading to about 20-fold isoform-selectivity against HDAC1. Furthermore, our ab initio QM/MM molecular dynamics simulations, a state-of-the-art approach to study reactions in biological systems, have elucidated how the β-hydroxymethyl chalcone can achieve the distinct time-dependent inhibition toward HDAC2. © 2014 American Chemical Society.
Sirin G.S.,New York University |
Zhang Y.,New York University |
Zhang Y.,Center for Computational Chemistry at Shanghai
Journal of Physical Chemistry A | Year: 2014
Acetylcholinesterase (AChE) is a crucial enzyme in the cholinergic nerve system that hydrolyzes acetylcholine (ACh) and terminates synaptic signals by reducing the effective concentration of ACh in the synaptic clefts. Organophosphate compounds irreversibly inhibit AChEs, leading to irreparable damage to nerve cells. By employing Born-Oppenheimer ab initio QM/MM molecular dynamics simulations with umbrella sampling, a state-of-the-art approach to simulate enzyme reactions, we have characterized the covalent inhibition mechanism between AChE and the nerve toxin soman and determined its free energy profile for the first time. Our results indicate that phosphonylation of the catalytic serine by soman employs an addition-elimination mechanism, which is highly associative and stepwise: in the initial addition step, which is also rate-limiting, His440 acts as a general base to facilitate the nucleophilic attack of Ser200 on the soman's phosphorus atom to form a trigonal bipyrimidal pentacovalent intermediate; in the subsequent elimination step, Try121 of the catalytic gorge stabilizes the leaving fluorine atom prior to its dissociation from the active site. Together with our previous characterization of the aging mechanism of soman inhibited AChE, our simulations have revealed detailed molecular mechanistic insights into the damaging function of the nerve agent soman. © 2014 American Chemical Society.