Brian K. Radak
Rutgers University
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Publication
Featured researches published by Brian K. Radak.
Proceedings of the National Academy of Sciences of the United States of America | 2013
Hong Gu; Shuming Zhang; Kin Yiu Wong; Brian K. Radak; Thakshila Dissanayake; Daniel L. Kellerman; Qing Dai; Masaru Miyagi; Vernon E. Anderson; Darrin M. York; Joseph A. Piccirilli; Michael E. Harris
Enzymes function by stabilizing reaction transition states; therefore, comparison of the transition states of enzymatic and nonenzymatic model reactions can provide insight into biological catalysis. Catalysis of RNA 2′-O-transphosphorylation by ribonuclease A is proposed to involve electrostatic stabilization and acid/base catalysis, although the structure of the rate-limiting transition state is uncertain. Here, we describe coordinated kinetic isotope effect (KIE) analyses, molecular dynamics simulations, and quantum mechanical calculations to model the transition state and mechanism of RNase A. Comparison of the 18O KIEs on the 2′O nucleophile, 5′O leaving group, and nonbridging phosphoryl oxygens for RNase A to values observed for hydronium- or hydroxide-catalyzed reactions indicate a late anionic transition state. Molecular dynamics simulations using an anionic phosphorane transition state mimic suggest that H-bonding by protonated His12 and Lys41 stabilizes the transition state by neutralizing the negative charge on the nonbridging phosphoryl oxygens. Quantum mechanical calculations consistent with the experimental KIEs indicate that expulsion of the 5′O remains an integral feature of the rate-limiting step both on and off the enzyme. Electrostatic interactions with positively charged amino acid site chains (His12/Lys41), together with proton transfer from His119, render departure of the 5′O less advanced compared with the solution reaction and stabilize charge buildup in the transition state. The ability to obtain a chemically detailed description of 2′-O-transphosphorylation transition states provides an opportunity to advance our understanding of biological catalysis significantly by determining how the catalytic modes and active site environments of phosphoryl transferases influence transition state structure.
Journal of Chemical Theory and Computation | 2015
Brian K. Radak; Melissa Romanus; Tai-Sung Lee; Haoyuan Chen; Ming Huang; Antons Treikalis; Vivekanandan Balasubramanian; Shantenu Jha; Darrin M. York
Replica exchange molecular dynamics has emerged as a powerful tool for efficiently sampling free energy landscapes for conformational and chemical transitions. However, daunting challenges remain in efficiently getting such simulations to scale to the very large number of replicas required to address problems in state spaces beyond two dimensions. The development of enabling technology to carry out such simulations is in its infancy, and thus it remains an open question as to which applications demand extension into higher dimensions. In the present work, we explore this problem space by applying asynchronous Hamiltonian replica exchange molecular dynamics with a combined quantum mechanical/molecular mechanical potential to explore the conformational space for a simple ribonucleoside. This is done using a newly developed software framework capable of executing >3,000 replicas with only enough resources to run 2,000 simultaneously. This may not be possible with traditional synchronous replica exchange approaches. Our results demonstrate 1.) the necessity of high dimensional sampling simulations for biological systems, even as simple as a single ribonucleoside, and 2.) the utility of asynchronous exchange protocols in managing simultaneous resource requirements expected in high dimensional sampling simulations. It is expected that more complicated systems will only increase in computational demand and complexity, and thus the reported asynchronous approach may be increasingly beneficial in order to make such applications available to a broad range of computational scientists.
extreme science and engineering discovery environment | 2013
Brian K. Radak; Melissa Romanus; Emilio Gallicchio; Tai-Sung Lee; Ole Weidner; Nanjie Deng; Peng He; Wei Dai; Darrin M. York; Ronald M. Levy; Shantenu Jha
Replica exchange represents a powerful class of algorithms used for enhanced configurational and energetic sampling in a range of physical systems. Computationally it represents a type of application with multiple scales of communication. At a fine-grained level there is often communication with a replica, typically an MPI process. At a coarse-grained level, the replicas communicate with other replicas -- both temporally as well as in amount of data exchanged. This paper outlines a novel framework developed to support the flexible execution of large-scale replica exchange. The framework is flexible in the sense that it supports different coupling schemes between replicas and is agnostic to the specific underlying simulation -- classical or quantum, serial or parallel simulation. The scalability of the framework is assessed using standard simulation benchmarks. In spite of the increasing communication and coordination requirements as a function of the number of replicas, our framework supports the execution of hundreds replicas without significant overhead. Although there are several specific aspects that will benefit from further optimization, a first working prototype has the ability to fundamentally change the scale of replica exchange simulations possible on production distributed cyberinfrastructure such as XSEDE, as well as support novel usage modes. This paper also represents the release of the framework to the broader biophysical simulation community and provides details on its usage.
Journal of Chemical Theory and Computation | 2017
Brian K. Radak; Christophe Chipot; Donghyuk Suh; Sunhwan Jo; Wei Jiang; James C. Phillips; Klaus Schulten; Benoît Roux
An increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementation of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.
Journal of Chemical Physics | 2016
Brian K. Radak; Benoît Roux
Hybrid algorithms combining nonequilibrium molecular dynamics and Monte Carlo (neMD/MC) offer a powerful avenue for improving the sampling efficiency of computer simulations of complex systems. These neMD/MC algorithms are also increasingly finding use in applications where conventional approaches are impractical, such as constant-pH simulations with explicit solvent. However, selecting an optimal nonequilibrium protocol for maximum efficiency often represents a non-trivial challenge. This work evaluates the efficiency of a broad class of neMD/MC algorithms and protocols within the theoretical framework of linear response theory. The approximations are validated against constant pH-MD simulations and shown to provide accurate predictions of neMD/MC performance. An assessment of a large set of protocols confirms (both theoretically and empirically) that a linear work protocol gives the best neMD/MC performance. Finally, a well-defined criterion for optimizing the time parameters of the protocol is proposed and demonstrated with an adaptive algorithm that improves the performance on-the-fly with minimal cost.
Journal of Chemical Theory and Computation | 2017
Ming Huang; Thakshila Dissanayake; Erich R. Kuechler; Brian K. Radak; Tai-Sung Lee; Timothy J. Giese; Darrin M. York
The computational efficiency of approximate quantum mechanical methods allows their use for the construction of multidimensional reaction free energy profiles. It has recently been demonstrated that quantum models based on the neglect of diatomic differential overlap (NNDO) approximation have difficulty modeling deoxyribose and ribose sugar ring puckers and thus limit their predictive value in the study of RNA and DNA systems. A method has been introduced in our previous work to improve the description of the sugar puckering conformational landscape that uses a multidimensional B-spline correction map (BMAP correction) for systems involving intrinsically coupled torsion angles. This method greatly improved the adiabatic potential energy surface profiles of DNA and RNA sugar rings relative to high-level ab initio methods even for highly problematic NDDO-based models. In the present work, a BMAP correction is developed, implemented, and tested in molecular dynamics simulations using the AM1/d-PhoT semiempirical Hamiltonian for biological phosphoryl transfer reactions. Results are presented for gas-phase adiabatic potential energy surfaces of RNA transesterification model reactions and condensed-phase QM/MM free energy surfaces for nonenzymatic and RNase A-catalyzed transesterification reactions. The results show that the BMAP correction is stable, efficient, and leads to improvement in both the potential energy and free energy profiles for the reactions studied, as compared with ab initio and experimental reference data. Exploration of the effect of the size of the quantum mechanical region indicates the best agreement with experimental reaction barriers occurs when the full CpA dinucleotide substrate is treated quantum mechanically with the sugar pucker correction.
Journal of Chemical Theory and Computation | 2013
Timothy J. Giese; Haoyuan Chen; Thakshila Dissanayake; George M. Giambaşu; Hugh Heldenbrand; Ming Huang; Erich R. Kuechler; Tai-Sung Lee; Maria T. Panteva; Brian K. Radak; Darrin M. York
Journal of Chemical Theory and Computation | 2013
Tai-Sung Lee; Brian K. Radak; Anna Pabis; Darrin M. York
Journal of Chemical Theory and Computation | 2014
Tai-Sung Lee; Brian K. Radak; Ming Huang; Kin Yiu Wong; Darrin M. York
Journal of Physical Chemistry B | 2013
Brian K. Radak; Michael E. Harris; Darrin M. York