Faculty Research Groups
Carlos Simmerling,
Professor
B.A., 1991, University of Illinois at Chicago
Ph.D., 1994, University of Illinois at Chicago
Postdoctoral Researcher, University of California, San Francisco, 1994-1998
2000 AMDeC Young Investigator Award
Phone: (631) 632-1136
Email:
Computational Structural Biology
The goals of a computational chemist are to accurately simulate known properties of molecules, assist in the refinement and interpretation of experimental data and predict the results of future experiments. While quantum mechanical methods can be highly accurate, they are limited in that they currently cannot be applied to large systems such as proteins and nucleic acids, and little or no explicit solvent can be included in the calculations. Since the research in my lab involves relatively large biomolecular systems (such as proteins and nucleic acids) where specific interactions with solvent molecules are often important, we use the methods of molecular mechanics. Typical calculations involve molecular dynamics of the molecule of interest along with thousands of explicit solvent molecules, where the behavior of the molecule as a function of time is used to determine kinetic and thermodynamic properties of the system. These simulations can provide an atomic-detail picture of the behavior of a single molecule, rather than the time- and ensemble-averaged views that come from most experiments.
Research Interests
Program Development
One area of current research in my group is the development of new algorithms and programs for accurate and efficient simulation of large biomolecular systems using state-of-the-art computers. I am a member of the development teams for the widely used AMBER and MOIL suites of programs for molecular mechanics calculations. Among the many features of the programs are energy minimization, molecular dynamics, and calculation of free energies. Currently, we are improving the performance of the programs on massively parallel computers, developing efficient genetic algorithms that include solvent effects, evaluating a variety of methods for the inclusion of long-range electrostatic interactions and development of techniques to enhance conformational sampling during simulations of biologically relevant molecules.
Another area of interest in my lab is the development of tools for the visualization and analysis of the large amounts of data that are generated by our calculations. An example of this development is the program MOIL-View for visualization of the structure and dynamics of biomolecules.
Improved Simulation Methodologies: Conformational Sampling
The single largest roadblock to reliable calculations of structures and relative free energies for complex biomolecular systems is the sampling problem. The number of possible conformations for a flexible molecule increases exponentially with the number of rotatable bonds, rapidly exceeding the number which can realistically be evaluated. Overcoming the sampling limitation would have a tremendous impact on our ability to make significant contributions in many areas, such as docking of flexible ligands, refinement of structures with low resolution or incomplete data, quantitative calculation of effects of amino acid mutations on protein stability, assisting in the engineering of modified or new functions for enzymes and catalytic antibodies, and eventually, the "holy grail" of computational structural biology, the prediction of accurate three-dimensional protein structures from only sequence data. The methods that we develop and use must be compatible with the highest quality representations of the system, such as atomic detail, explicit solvation and accurate treatment of the long-range electrostatics that are critical in simulations of highly charged molecules such as DNA and RNA.
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Image A portion of the simulated protein-RNA interaction in the HIV Rev-RRE complex |
Structure Prediction
While the accurate prediction of structures from sequence data alone is a long-term goal, current projects involve the application of new sampling techniques to the study of systems where at least some data is available. Sources of this data include structures of homologous proteins, low-resolution or incomplete experimental data (such as that from X-ray crystallography or NMR spectroscopy), or low-resolution protein structure predictions from methods that forego atomic detail and explicit solvation.
Molecular Recognition
One current application involves prediction of the conformations of antibody hypervariable (antigen binding) loops. The overall structures of different antibodies are conserved despite their ability to recognize and bind diverse antigens, making them the ultimate biological mechanism for molecular recognition. We are developing methods that will predict these structures, including the locations and roles of key water molecules that often mediate antibody-ligand interactions. We also attempt to model and understand the conformational changes (induced fit) that often take place upon antigen binding, and assist in the development and optimization of catalytic antibodies.
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Image An example of induced fit for the H3 loop in the antibody 17/9 |
Publications
Okur, A. and Simmerling, C., "Hybrid Explicit/Implicit Solvation Methods", Annual Reports in Computational Chemistry 2006, in press.
Rafi, S., Cui, G., Song, K., Cheng, X., Tonge, P. and Simmerling, C., "Insight through MM-PBSA Calculations into the Binding Affinity of Triclosan and Three Analogs for FabI, the E. Coli Enoyl Reductase", J. Med. Chem., in press.
Wickstrom, L., Okur, A., Song, K., Hornak, V., Raleigh, D. and Simmerling, C., "", J. Mol. Biol., in press.
Kelso, C. and Simmerling, C., "Enhanced Sampling Methods for Simulation of Nucleic Acids", in Computational Studies of DNA and RNA, J. Sponer and F. Lankas (Editors), Springer Publishers, in press.
Hornak, V.; Okur, A., Rizzo, R. and Simmerling, C., "HIV-1 Protease Flaps Spontaneously Close to the Correct Structure in Simulations Following Manual Placement of an Inhibitor into the Open State", J. Am. Chem. Soc., 128: 2812 (2006).
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Hornak, V.; Okur, A., Rizzo, R. and Simmerling, C., "HIV-1 protease flaps spontaneously open and reclose in molecular dynamics simulations", Proc. Nat. Acad. Sci. USA, 103:915-920 (2006).
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Okur, A., Wickstrom, L., Layten, M., Geney, R., Song, K., Hornak, V. and Simmerling, C., "Improved Efficiency of Replica Exchange Simulations through Use of a Hybrid Explicit/Implicit Solvation Model", J. Chem. Theory Comput., 2:420, 2006.
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Geney, R., Layten, M., Gomperts, R., Hornak, V. and Simmerling, C., "Investigation of salt bridge stability in a Generalized Born solvent model", J. Chem. Theory Comput., 2:115, 2006.
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Case, D. A.; Cheatham, T. E.; Darden, T.; Gohlke, H.; Luo, R.; Merz, K. M.; Onufriev, A.; Simmerling, C.; Wang, B.; Woods, R. J., "The Amber biomolecular simulation program", J. of Comput. Chem. 26:1668, 2005
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Cheng, X., Kelso, C., Hornak, V., de los Santos, C., Grollman, A. and Simmerling, C., "Dynamic Behavior of DNA Base Pairs Containing 8-oxoguanine", J. Am. Chem. Soc., 127:13906, 2005.
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Roe, D., Hornak, V. and Simmerling, C., "Folding Cooperativity in a Three-stranded ?-sheet Model", J. Mol. Biol., 352, 370-281 (2005)
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Cheng, X., Cui, G., Hornak, V. and Simmerling, C., "Modified Replica Exchange Simulation Methods for Local Structure Refinement". J. Phys. Chem. B, 109, 8220-8230 (2005)
Geney, R., Sun, L., Pera, P., Bernacki, R., Xia, R., Horwitz, S., Simmerling, C., and Ojima, I. "Use of the tubulin-bound paclitaxel conformation for structure-based rational drug design", Chemistry & Biology, 12, 339-348 (2005)
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Kubatzky, K., Liu, W., Goldgraben, K., Simmerling, C., Steven O. Smith, S., and Constantinescu, S., 'Structural Requirements of the Extracellular To Transmembrane Domain Junction for Erythropoietin Receptor Function", J. Biol. Chem., 280, 14844-14854 (2005)
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Roitberg, A. and Simmerling, C., "Foreword", J. Mol. Graphics & Modeling, 22:317, 2004
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Cheng, X., Hornak, V. and Simmerling, C., "Improved Conformational Sampling through an Efficient Combination of Mean-Field Simulation Approaches". J. Phys. Chem. B, 108:426, 2004
Sivaraman, S., Sullivan, T., Johnson. F., Novichenok, P., Cui, G., Simmerling, C., Johnson, F. and Tonge, P. "Inhibition of the Bacterial Enoyl Reductase FabI by Triclosan: A Structure-Reactivity Analysis of FabI Inhibition by Triclosan Analogs", J. Med. Chem., 47:509, 2004
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Hornak, V. and Simmerling, C., "Development of Softcore Potential Functions for Overcoming Steric Barriers in MD", J. Mol. Graphics & Modeling, 22: 403, 2004
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Hornak, V. and Simmerling, C., "Generation of Accurate Protein Loop Conformations through Low-barrier Molecular Dynamics", Proteins: Struct. Func. Genet., 51:577,200314
Okur, A., Strockbine, B., Hornak, V. and Simmerling, C., 'Using PC Clusters to Evaluate the Transferability of Molecular Mechanics Force Fields for Proteins", J. Comput. Chem., 24:21, 2003.
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Simmerling, C., Strockbine, B and Roitberg, A., 'All-Atom Structure Prediction and Folding Simulations of a Stable Protein', J. Am. Chem. Soc, 124:11258, 2002.
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Cui, G and Simmerling, C., 'Conformational Heterogeneity Observed in Simulations of a Pyrene-Substitued DNA', J. Am. Chem. Soc., 124:12154, 2002.
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Shewmaker, F., Maskos, K., Simmerling, C. and Landry, S. J. 'The Disordered Mobile Loop of GroES Folds into a Defined ? Hairpin upon Binding GroEL' J. Biol. Chem., 276:33, 2001
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Simmerling, C., Lee, M.R, Ortiz, AR., Kolinski, A., Skolnick, J., Kollman, P.A., 'Combining MONSSTER and LES/PME to Predict Protein Structure from Amino Acid Sequence: Application to the Small Protein CMTI-I', J. Am. Chem. Soc. 122: 8392, 2000
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Simmerling, C., Miller, J. L., and Kollman, P., 'Combined Locally Enhanced Sampling and Particle Mesh Ewald as a Strategy to Locate the Experimental Structure of a Non-helical Nucleic Acid', J. Am. Chem. Soc, 120:7149, 1998.
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Simmerling, C., Fox, T. and Kollman, P., 'The Use of Locally Enhanced Sampling in Free Energy Calculations: Testing and Application to the ??? Anomerization of Glucose', J. Am. Chem. Soc, 120:5771,1998.
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Elber, R., Mohanty, D. and Simmerling, C. "Dynamics of Peptide Folding" in Classical and Quantum Dynamics in Condensed Phase Simulations, B. Berne et al. (eds) World Scientific, Singapore 1998
Case, D.A., Pearlman, D.A., Caldwell, J.A., Cheatham, T.E., Ross, W.S., Simmerling, C.L., Darden, T.A., Merz, K.M., Stanton, R.V., Cheng, A.L., Vincent, J.J., Crowley, M., Ferguson, D.M., Radmer, R.J., Seibel, G.L., Singh, U.C., Weiner, P.K. and Kollman, P.A., AMBER 5, University of California, San Francisco, 1997
Elber, R., Roitberg, A., Simmerling, C., Goldstein, R., Verkhivker, G., Li, H. and Ulitsky, A., 'MOIL- A Program for Simulation of Macromolecules', Computer Physics Communications, 91:159, 1995
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Simmerling, C., Elber, R. and Zhang, J., 'MOIL-View: A Program for Visualization of Structure and Dynamics of Biomolecules and STO: a Program for Computing Stochastic Paths', in Modeling of Biomolecular Structures and Mechanisms, A. Pullman et al. (eds.) Kluwer Acad. Publishers, Netherlands 1995
Simmerling, C. and Elber, R., 'Computer Determination of Peptide Conformations in Water: Different Roads to Structure', Proc. Nat. Acad. Sci. USA, 92:3190, 1995
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Elber, R., Roitberg, A., Simmerling, C., Goldstein, R., Verkhivker, G. and Li, H., 'MOIL- A Molecular Dynamics Program with Emphasis on Conformational Searches and Reaction Path Calculations in Large Biological Molecules' in Statistical Mechanics, Protein Structure and Protein-Substrate Interactions, S Doniach (ed.), Plenum Press, NY (1994)
Simmerling, C. and Elber, R., 'Hydrophobic "Collapse" in a Cyclic Hexapeptide: Computer Simulations of CHDLFC and CAAAAC in Water', J. Am. Chem. Soc., 16:2534 (1994)
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