CHARMM: the Biomolecular Simulation Program

CHARMM: The Biomolecular Simulation Program B. R. BROOKS,1* C. L. BROOKS III,2,3* A. D. MACKERELL, Jr.,4* L. NILSSON,5* R. J. PETRELLA,6,7* B. ROUX,8* Y. WON,9* G. ARCHONTIS, C. BARTELS, S. BORESCH, A. CAFLISCH, L. CAVES, Q. CUI, A. R. DINNER, M. FEIG, S. FISCHER, J. GAO, M. HODOSCEK, W. IM, K. KUCZERA, T. LAZARIDIS, J. MA, V. OVCHINNIKOV, E. PACI, R. W. PASTOR, C. B. POST, J. Z. PU, M. SCHAEFER, B. TIDOR, R. M. VENABLE, H. L. WOODCOCK, X. WU, W. YANG, D. M. YORK, M. KARPLUS6,10* 1Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892 2Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109 3Department of Biophysics, University of Michigan, Ann Arbor, Michigan 48109 4Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland 21201 5Department of Biosciences and Nutrition, Karolinska Institutet, SE-141 57, Huddinge, Sweden 6Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138 7Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115 8Department of Biochemistry and Molecular Biology, University of Chicago, Gordon Center for Integrative Science, Chicago, Illinois 60637 9Department of Chemistry, Hanyang University, Seoul 133-792, Korea 10Laboratoire de Chimie Biophysique, ISIS, Universite´ de Strasbourg, 67000 Strasbourg, France Received 12 September 2008; Revised 24 February 2009; Accepted 3 March 2009 DOI 10.1002/jcc.21287 Published online 14 May 2009 in Wiley InterScience (www.interscience.wiley.com). Abstract: CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estima- tors, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983. q 2009 Wiley Periodicals, Inc. J Comput Chem 30: 1545–1614, 2009 Key words: biomolecular simulation; CHARMM program; molecular mechanics; molecular dynamics; molecular modeling; biophysical computation; energy function I. Introduction Additional Supporting Information may be found in the online version of this article. Understanding how biological macromolecular systems (proteins, Correspondence to: B. R. Brooks; e-mail: [email protected] or nucleic acids, lipid membranes, carbohydrates, and their com- C. L. Brooks III; e-mail: [email protected] or A. D. MacKerell, Jr.; plexes) function is a major objective of current research by com- e-mail: [email protected] or L. Nilsson; e-mail: Lennart. putational chemists and biophysicists. The hypothesis underlying [email protected] or R. J. Petrella; e-mail: [email protected] or computational models of biological macromolecules is that the B. Roux; e-mail: [email protected] or Y. Won; e-mail: won@hanyang. behavior of such systems can be described in terms of the basic ac.kr or M. Karplus; e-mail: [email protected] physical principles governing the interactions and motions of Contract/grant sponsors: NSF, NIH, DOE, Accelrys, CNRS, NHLBI q 2009 Wiley Periodicals, Inc. 1546 Brooks et al. • Vol. 30, No. 10 • Journal of Computational Chemistry their elementary atomic constituents. The models are, thus, ics), was not included in that publication because an article was rooted in the fundamental laws of physics and chemistry, includ- not prepared in time for the issue. CHARMM was first described ing electrostatics, quantum mechanics and statistical mechanics. in JCC in 1983,22 although its earlier implementations had The challenge now is in the development and application of already been used to study biomolecules for a number of methods, based on such well-established principles, to shed light years.23 on the structure, function, and properties of often complex bio- CHARMM is a general and flexible molecular simulation and molecular systems. With the advent of computers, the scope of modeling program that uses classical (empirical and semiempiri- molecular dynamics (MD; see footnote for naming conventions)y cal) and quantum mechanical (QM) (semiempirical or ab initio) and other simulation techniques has evolved from the study of energy functions for molecular systems of many different simple hard-sphere models of liquids in the 1950s,1 to that of classes, sizes, and levels of heterogeneity and complexity. The models of more complex atomic and molecular liquids in the original version of the program, although considerably smaller 1960s,2,3 and to the study of proteins in the 1970s.4 Biological and more limited than CHARMM is at present, made it possible macromolecular systems of increasing size and complexity, to build the system of interest, optimize the configuration using including nucleic acids, viruses, membrane proteins, and macro- energy minimization techniques, perform a normal mode or MD molecular assemblies, are now being investigated using these simulation, and analyze the simulation results to determine struc- computational methods. tural, equilibrium, and dynamic properties. This version of The power and usefulness of atomic models based on realis- CHARMM22,24 was able to treat isolated molecules, molecules tic microscopic interactions for investigating the properties of a in solution, and molecules in crystalline solids. The information wide variety of biomolecules, as well as other chemical systems, for computations on proteins, nucleic acids, prosthetic groups has been amply demonstrated. The methodology and applica- (e.g., heme groups), and substrates was available as part of the tions have been described in numerous books5–10 and program. A large set of analysis facilities was provided, which reviews.11–13 Studies of such systems have now reached a point included static structure and energy comparisons, time series, where computational models often have an important role in the correlation functions and statistical properties of molecular design and interpretation of experiments. Of particular interest is dynamic trajectories, and interfaces to computer graphics pro- the possibility of employing molecular simulations to obtain in- grams. Over the years, CHARMM has been ported to many dif- formation that is difficult to determine experimentally.14,15 A ferent machines and platforms, in both serial and parallel imple- dictionary definition of ‘‘simulation’’ is, in fact, ‘‘the examina- mentations of the code; and it has been made to run efficiently tion of a problem, often not subject to direct experimentation,’’ on many types of computer systems, from single processor PCs, and it is this broad meaning that is intended here. Typical stud- Mac and Linux workstations, to machines based on vectorial or ies range from those concerned with the structures, energies, and multicore processors, to distributed-memory clusters of Linux vibrational frequencies of small molecules, through those dealing machines, and large, shared-memory supercomputer installations. with Monte Carlo and MD simulations of pure liquids and solu- Equally important, the structure of the program has provided a tions, to analyses of the conformational energies and fluctuations robust framework for incorporating new ideas and methodolo- of large molecules in solution or in crystal environments. gies—many of which did not even exist when CHARMM was As the field of biomolecular computation continues to evolve, first designed and coded in the late 1970s. Some examples are it is essential to retain maximum flexibility and to have available implicit solvent representations, free energy perturbation meth- a wide range of computational methods for the implementation ods, structure refinement based on X-ray or NMR data, transi- of novel ideas in research and its applications. The need to have tion path sampling, locally enhanced sampling with multiple an integrated approach for the development and application of copies, discretized Feynman path integral simulations, quantum such computational biophysical methods has led to the introduc- mechanical/molecular mechanical (QM/MM) simulations, and tion of a number of general-purpose programs, some of which the treatment of induced polarization. The ability of the basic are widely distributed in academic and commercial environ- framework of CHARMM to accommodate new methods without ments. Several16–21 were described in a special 2005 issue of large-scale restructuring of the code is one of the major Journal of Computational Chemistry (JCC). One

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