Carlos Simmerling

• Computational Structural Biology

  The Simmerling lab at Stony Brook University carries out research in the area of computational structural biology. In particular, the lab focuses on understanding how dynamic structural changes are involved in the behavior of biomolecules, such as proteins and nucleic acids. Recent advances in computer hardware and simulation algorithms have established computational methods as a robust and important component of biomolecular research. These simulations are highly complementary to experimental tools, and methods such as molecular dynamics simulation are able to provide a detailed description of the motions of individual atoms over short timescales that are typically inaccessible to experiment. Simulations are not limited to the averages over time and over large numbers of molecules that prevent crystallographic or NMR experiments from characterizing transiently populated conformations such as important intermediates in multi-step conformational changes. In additional to direct dynamics, treatment of simulation data using statistical mechanics can provide valuable thermodynamic properties such as binding affinities or the free energy profiles resulting from conformational changes.

  Research Interests

  Program Development

  In addition to projects related to specific biological problems, much of the research in the Simmerling lab focuses on the development of new methods for biomolecular simulation. The Simmerling lab develops the Amber simulation package in collaboration with several other research groups. Of particular interest are development of new methods for efficient simulation of conformational changes and development and validation of the molecular mechanics force fields that determine the accuracy of the resulting simulation data.

  Improved Simulation Methodologies: Better Force Fields

  Simulations based on classical mechanical force fields can expose dynamics on the femtosecond to microsecond timescales. However, the force fields and solvent models used must be accurate enough for the conformations observed to correspond to those in reality. The Simmerling Lab develops atomic-detail energy functions that are among the most accurate models currently available for protein dynamics. These include the widely used Amber "SB" (Stony Brook) force fields, such as ff99SB and ff14SB.

  Improved Simulation Methodologies: Better Implicit Solvent Models

  A key problem in computational chemistry and biology is modeling the solvent. Solvation and desolvation usually involve large free-energy driving forces. There are two main ways water is currently modeled. (1) In explicit solvent, individual water molecules are included atomistically. Explicit solvent is the current gold standard in terms of physical accuracy, but it is computationally expensive—often prohibitively so. (2) In implicit solvent, such as the semi-analytical generalized Born model (GB), water is treated more simply as a dielectric continuum.  Also, sampling of global motions is enhanced considerably due to lack of viscosity. Implicit solvent dramatically reduces the computational cost of the popular REMD sampling method (see Aim 2), with fewer replicas, simulated for shorter times.This is much faster, but can lack accuracy. Our group works on developing improved implicit solvent treatments for proteins and nucleic acids, as well as hybrid explicit/implicit solvent models.

  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.

  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

  Biomolecules undergo constant structural changes as they perform their functions. These changes range from small fluctuations of ligands bound tightly to a receptor, to larger but transient breathing events, and even adoption of completely different tertiary structures as occurs during protein folding. In the Simmerling group, we are interested in gaining insight into the biophysics of these changes, the interactions that drive them, and how they are modified in cases of disease or drug resistance. Since most experimental techniques provide averages over time and/or macroscopic numbers of molecules, we use a wide range of computer simulation methods to model these systems and understand the coupling between structure, energy, and dynamics. Each of our projects is closely coupled to experimental work by our collaborators. 

  Many biological molecules, including important drug targets, change conformation as they perform their function. We aim to understand these dynamic events, and to investigate whether targeting the mechanism of conformational change may be more effective therapeutic than the design of inhibitors that mimic the substrate’s chemical properties. The is especially important in cases like HIV-1 protease, where it is believed that drug resistance arises from mutations that change the flexibility of the enzyme, making inhibitors less potent while maintaining function. We have published a series of papers on this important model system, including studies that revealed the opening mechanism, demonstrated that crystal packing can provide misleading structural data, showed how ligands can gain access to the binding site and inactivate the enzyme, and provided new insight into how multi-drug resistance arises from mutations that modulate protease dynamics.

  Another example of our research is the recognition of specific DNA sequences by enzymes involved in transcription, translation and repair of DNA. Although the integrity of DNA is essential to maintaining an organism’s genetic code, DNA is continually undergoing a process of damage and repair (thousands of times a day in each cell). While some types of damage involve large and bulky adducts, others involve minor chemical changes that do not appear at first to have a significant impact on DNA structure or stability. We use simulations to help understand how DNA repair enzymes can recognize damaged bases from a vast excess of normal DNA, bind to them with striking specificity, and repair the damage.

https://www.simmerlinglab.org/publications

Rational modulation of the induced-fit conformational change for slow-onset inhibition in M. tuberculosis InhA
Lai, C-T; Li, H; Yu, W; Shah, S; Bommineni, G; Perrone, V; Garcia-Diaz, M; Tonge, P; Simmerling, C., Biochemistry, 2015, 54 (30), 4683-4691
DOI: 10.1021/acs.biochem.5b00284

ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB
Maier, J., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K., Simmerling, C.,Journal of Chemical Theory and Computation, 2015, 11 (8), 3696-3713
DOI: 10.1021/acs.jctc.5b00255

Refinement of Generalized Born Implicit Solvation Parameters for Nucleic Acids and Their Complexes with Proteins
Nguyen, H., Pérez, A., Bermeo, S., Simmerling, C., Journal of Chemical Theory and Computation, 2015, 11 (8), 3714-3728
DOI: 10.1021/acs.jctc.5b00271

Active destabilization of base pairs by a DNA glycosylase wedge initiates damage recognition
Kuznetsov, N. A., Bergonzo, C., Campbell, A. J., Li, H., Mechetin, G. V., de los Santos, C., Grollman, A. P., Fedorova, O. S., Zharkov, D. O., Simmerling, C.,Nucleic Acids Research, 2015, 43 (1), 272-281
DOI: 10.1093/nar/gku1300

Folding Simulations for Proteins with Diverse Topologies Are Accessible in Days with a Physics-Based Force Field and Implicit Solvent
Nguyen, H., Maier, J., Huang, H., Perrone, V., Simmerling, C., Journal of the American Chemical Society, 2014, 136 (40), 13959-13962
DOI: 10.1021/ja503277669

The Role of Select Subtype Polymorphisms on HIV-1 Protease Conformational Sampling and Dynamics
Huang, X., Britto, M., Kear, J., Boone, C., Rocca, J., Simmerling, C., McKenna, R., Bieri, M., Gooley, P., Dunn, B. and Fanucci, G., Journal of Biological Chemistry,2014, 289, 17203-17214 
DOI: 10.1074/jbc.M114.571836

A structural and energetic model for the slow-onset inhibition of the Mycobacterium tuberculosis enoyl-ACP reductase InhA
Li, H.; Lai, C.; Pan, P.; Yu, W.; Liu, N.; Bommineni, G.; Garcia-Diaz, M.;Simmerling, C. .; Tonge, PJ., ACS Chemical Biology, 2014, 9, (4), 986–993 
DOI: 110.1021/cb400896g

Time-Dependent Diaryl Ether Inhibitors of InhA: Structure–Activity Relationship Studies of Enzyme Inhibition, Antibacterial Activity, and in vivo Efficacy
Pan, P., Knudson, SE, Bommineni, GR, Li, H., Lai, C., Liu, N., Garcia-Diaz, M.,Simmerling, C., Patil, SS, Slayden, RA, Tonge, PJ., ChemMedChem, 2014, 9, (4), 776–791 
DOI: 10.1002/cmdc.201300429

Ultrafast Structural Dynamics of BlsA, a Photoreceptor from the Pathogenic Bacterium Acinetobacter baumannii
Brust, R., Haigney, A., Lukacs, A., Gil., A., Hossain, S., Addison, K., Lai, CT, Towrie, M., Greetham, GM, Clark, IP, Illarionov, B., Bacher, A., Kim, RR, Fischer, M., Simmerling, C., Meech, SR and Tonge, PJ,J. Phys. Chem. Lett, 2014, 5, 220-224 
DOI: 10.1021/jz4023738

Improved Generalized Born Solvent Model Parameters for Protein Simulations
Nguyen, H., Roe, D. R., Simmerling, C., Journal of Chemical Theory and Computation, 2013, 9 (4), 2020-2034
DOI: 10.1021/ct3010485

Development of an Automated Event Detection Algorithm for HIV-1 Protease’s Flap Backbone Dihedral Change
Gee, J., Weaver, E., Shang, Y., Simmerling, C., J. Expt. Sec. Sci., 2013, 2(4)

Thiolactomycin-based beta-Ketoacyl-AcpM Synthase A (KasA) Inhibitors: Fragment-Based Inhibitor Discovery Using Transient One-Dimensional Nuclear Overhauser Effect NMR Spectroscopy
Kapilashrami, K; Bommineni, G; Machutta, C; Kim, P; Lai, C; Simmerling, C; Picart, F; Tonge, PJ, Journal of Biological Chemistry, 2013, 288 , 6045-6052

Backbone 1H, 13C, and 15N Chemical Shift Assignment for HIV-1 Protease Subtypes and Multi-Drug Resistant Variant MDR 769
Huang, X., Veloro, A., De Vera, I., Rocca, J., Simmerling, C., Dunn, B. and Fanucci, G., Biomolecular NMR Assignments, 2013, 7(2), 199-202

Inhibitor-Induced Conformational Shifts and Ligand-Exchange Dynamics for HIV-1 Protease Measured by Pulsed EPR and NMR Spectroscopy
Huang, X; de Vera, IMS; Veloro, AM; Blackburn, ME; Kear, JL; Carter, JD; Rocca, JR; Simmerling, C; Dunn, BM; Fanucci, GE, J. Phys. Chem. B, 2012, 116, 14235-14244

Structural Transitions of Transmembrane Helix 6 in the Formation of Metarhodopsin I
Eilers M, Goncalves J, Ahuja S, Kirkup C, Hirshfeld A, Simmerling C., Reeves P, Sheves M, Smith S., J. Phys. Chem. B, 2012, 116, 10477-10489

Molecular dynamics applied in drug discovery: the case of HIV-1 protease
Shang, Y. and Simmerling, C., Computational Drug Discovery and Design, 2012,819, 527-549

CoA Adducts of 4-Oxo-4-phenylbut-2-enoates: Inhibitors of MenB from the M. tuberculosis Menaquinone Biosynthesis Pathway
Li, x., Liu, N., Zhang, H., Knudson, S., Li, H., Lai, C., Simmerling, C., Slayden, R and Tonge, P., Med. Chem. Letters, 2011, 2, 818-823

Energetic Preference of 8-oxoG Eversion Pathways in a DNA Glycosylase
Bergonzo, C., Campbell, A., de los Santos, C., Grollman, A and Simmerling, C.,Journal of the American Chemical Society, 2011, 133, 14504–14506 
DOI: 10.1021/ja205142d

An Overview of String-Based Path Sampling Methods
Bergonzo, C. and Simmerling, C., Annual Report in Computational Chemistry,2011, 7, 89-97

Improving the description of salt bridge strength and geometry in a Generalized Born model
Shang, Y., Nguyen, H., Wickstrom, L., Okur, A. and Simmerling, C., JJ. Mol. Graphics & Model., 2011, 29, 676-684

Synthesis and Molecular Modeling of a Nitrogen Mustard DNA Interstrand Crosslink
Guainazzi, A., Campbell, A. J., Angelov, T., Simmerling, C., Schärer, O. D. 
Chemistry A European Journal, 2010, 16, 12100-12103
DOI: 10.1002/chem.201002041

An Improved Reaction Coordinate for Nucleic Acid Base Flipping Studies
Song, K., Campbell, A., Bergonzo, C., de los Santos, C., Grollman, A., Simmerling, C.
Journal of Chemical Theory and Computation, 2009, 5 (11), 3105-3113
DOI: 10.1021/ct9001575

A Partial Nudged Elastic Band Implementation for Use with Large or Explicitly Solvated Systems
Bergonzo, C., Campbell, A., Walker, R., Simmerling, C.
International Journal of Quantum Chemistry, 2009, 109, 3781-3790
DOI: 10.1002/qua.22405

Studies of Drug Resistance and the Dynamic Behavior of HIV-1 Protease through Molecular Dynamics Simulations
Ding, F. and Simmerling, C.
Drug Design: Structure and Ligand-Based Approaches, Cambridge University Press, 87-97, 2010

Drug Pressure Selected Mutations in HIV-1 Protease Alter Flap Conformations
Galiano, L., Ding, F., Veloro, A., Blackburn, M., Simmerling, C.and Fanucci, G.
Journal of the American Chemical Society, 2009, 131 (2), 430-431
DOI: 10.1021/ja807531v

Recent Advances in the Study of the Bioactive Conformation of Taxol
Sun, L., Simmerling, C. and Ojima, I.
ChemMedChem, 2009, 4, 719-731
DOI: 10.1002/cmdc.200900044

Evaluating the Performance of the FF99SB Force Field Based on NMR Scalar Coupling Data
Wickstrom, L., Okur, A. and Simmerling, C.
Biophysical Journal, 2009, 97 (3), 853-856
DOI: 10.1016/j.bpj.2009.04.063

Structural Insights for Designed Alanine-rich Helices: Comparing NMR Helicity Measures and Conformational Ensembles from Molecular Dynamics Simulation
Song, K., Stewart, J., Fesinmeyer, M. Andersen, N., Simmerling, C.
Biopolymers, 2008, 89, 747-760
DOI: 10.1002/bip.21004

Solution Structure of HIV-1 Protease Flaps Probed by Comparison of Molecular Dynamics Simulation Ensembles and EPR Experiments
Ding, F., Layten, M., Simmerling, C.
Journal of the American Chemical Society, 2008, 130 (23), 7184-7185
DOI: 10.1021/ja800893d

Evaluation of salt bridge structure and energetics in peptides using explicit, implicit and hybrid solvation models
Okur, A., Wickstrom, L. and Simmerling, C.
Journal of Chemical Theory and Computation, 2008, 4 (3), 488-498
DOI: 10.1021/ct7002308

Molecular simulations reveal a common binding mode for glycosylase binding of oxidatively damaged DNA lesions
Song, K., Kelso, C., de los Santos, C., Grollman, A. and Simmerling, C.
Journal of the American Chemical Society, 2007, 129 (47), 14536-14537
DOI: 10.1021/ja075128w

Molecular Mechanics Parameters for the FapydG DNA lesion
Song, K., Hornak, V., de los Santos, C., Grollman, A. and Simmerling, C.
Journal of Computational Chemistry, 2007, 29, 17-23
DOI: 10.1002/jcc.20625

Reconciling the Solution and X-ray Structures of the Villin Headpiece Helical Subdomain: Molecular Dynamics Simulations and Double Mutant Cycles Reveal a Stabilizing Cation-Pi Interaction
Wickstrom, L., Bi, Y., Hornak, V., Raleigh, D. and Simmerling, C.
Biochemistry, 2007, 46 (12), 3624-3634
DOI: 10.1021/bi061785+

Coupling of Replica Exchange Simulations to a non-Boltzmann structure reservoir
Roitberg, A., Okur, A. and Simmerling, C.
Journal of Physical Chemistry B, 2007, 111 (10), 2415-2418
DOI: 10.1021/jp068335b

Secondary Structure Bias in Generalized Born Solvent Models: Comparison of Conformational Ensembles and Free Energy of Solvent Polarization from Explicit and Implicit Solvation
Roe, D., Okur, A., Wickstrom, L., Hornak, V. and Simmerling, C.
Journal of Physical Chemistry B, 2007, 111 (7), 1846-1857
DOI: 10.1021/jp066831u

Targeting structural flexibility in HIV-1 protease inhibitor binding
Hornak, V. and Simmerling, C.
Drug Discovery Today, 2007, 12 (3-4), 132-138
DOI: 10.1016/j.drudis.2006.12.011

Improving Convergence of Replica Exchange Simulations through Coupling to a High Temperature Structure Reservoir
Okur, A., Roe, D., Cui, G., Hornak, V. and Simmerling, C.
Journal of Chemical Theory and Computation, 2007, 3 (2), 557-568
DOI: 10.1021/ct600263e

Generalized Born model with a simple, robust molecular volume correction
Mongan, J., Simmerling, C., McCammon, J. A., Case, D.and Onufriev, A.
Journal of Chemical Theory and Computation, 2007, 3 (1), 156-169
DOI: 10.1021/ct600085e

HIV-1 protease flaps spontaneously open and reclose in molecular dynamics simulations
Hornak, V., Okur, A., Rizzo, R. and Simmerling, C.
Proceedings of the National Academy of Sciences of the United States of America,2006, 103 (4), 915-920
DOI: 10.1073/pnas.0508452103

HIV-1 Protease Flaps Spontaneously Close to the Correct Structure in Simulations Following Manual Placement of an Inhibitor into the Open State
Hornak, V.; Okur, A., Rizzo, R. and Simmerling, C.
Journal of the American Chemical Society, 2006, 128 (9), 2812-2813
DOI: 10.1021/ja058211x

Simulating HIV-1 Protease at its Most Vulnerable Instant
Simmerling, C. and Gomperts, R.
Scientific Computing, 2006, 7, 32-34

Enhanced Sampling Methods for Simulation of Nucleic Acids
Kelso, C. and Simmerling, C.
Computational Studies of DNA and RNA, Springer Publishers, 147-186, 2006

The open structure of a multi drug resistant HIV-1 protease is stabilized by crystal packing contacts 
Layten, M., Hornak, V. and Simmerling, C. 
Journal of Amercian Chemical Society , 2006, 128 (41), 13360-13361 
DOI: 10.1021/ja065133k 

Structure of Acyl Carrier Protein Bound to FabI, the FASII Enoyl Reductase from Escherichia Coli 
Rafi, S., Novichenok, P., Kolappan, S., Zhang, X., Strattor, C., Rawat, R., Kisker, C., Simmerling, C. and Tonge, P. 
Journal of Biological Chemistry , 2006 , 281 (51), 39285-39293 
DOI: 10.1074/jbc.M608758200 

The Unfolded State of the Villin Headpiece Helical Subdomain: Computational Studies of the Role of Locally Stabilized Structure 
Wickstrom, L., Okur, A., Song, K., Hornak, V., Raleigh, D. and Simmerling, C.
Journal of Molecular Biology , 2006, 360 (5), 1094-1107 
DOI: 10.1016/j.jmb.2006.04.070 

Computational analysis of the binding mode of 8-oxo-guanine to formamidopyrimidine-DNA glycosylase 
Song, K., Hornak, V., de los Santos, C., Grollman, A. and Simmerling, C.
Biochemistry , 2006 , 45 (36), 10886-10894 
DOI: 10.1021/bi060380m 

Insight through MM-PBSA Calculations into the Binding Affinity of Triclosan and Three Analogs for FabI, the E. Coli Enoyl Reductase 
Rafi, S., Cui, G., Song, K., Cheng, X., Tonge, P. and Simmerling, C.
Journal of Medicinal Chemistry, 2006 , 49 (15), 4574-4580 
DOI: 10.1021/jm060222t 

Comparison of multiple Amber force fields and development of improved protein backbone parameters 
Hornak, V., Abel, R., Okur, A., Strockbine, B., Roitberg, A. and Simmerling, C. 
Proteins: Structure, Function and Bioinformatics , 2006 , 3 (3), 712-725 
DOI: 10.1002/prot.21123 

Investigation of salt bridge stability in a Generalized Born solvent model 
Geney, R., Layten, M., Gomperts, R., Hornak, V. and Simmerling, C. 
Journal of Chemical Theory and Computation, 2006 , 2 (1), 115-127 
DOI: 10.1021/ct050183l 

Improved Efficiency of Replica Exchange Simulations through Use of a Hybrid Explicit/Implicit Solvation Model 
Okur, A., Wickstrom, L., Layten, M., Geney, R., Song, K., Hornak, V. and Simmerling, C. 
Journal of Chemical Theory and Computation, 2006 , 2 (2), 420-433 
DOI: 10.1021/ct050196z 

Enhanced Sampling Methods for Simulation of Nucleic Acids 
Kelso, C. and Simmerling, C. 
in Computational Studies of DNA and RNA, J. Sponer and F. Lankas (Editors), Springer Publishers, 2006 , 147-168 

Hybrid Explicit/Implicit Solvation Methods 
Okur, A. and Simmerling, C. 
Annual Reports in Computational Chemistry , 2006 , 2 , 97-109 
DOI: 

Structural Requirements of the Extracellular To Transmembrane Domain Junction for Erythropoietin Receptor Function 
Kubatzky, K., Liu, W., Goldgraben, K., Simmerling, C., Steven O. Smith, S., and Constantinescu, S. 
Journal of Biological Chemistry , 2005 , 280 (15), 14844-14854 
DOI: 10.1074/jbc.M411251200 

Use of the tubulin-bound paclitaxel conformation for structure-based rational drug design 
Geney, R., Sun, L., Pera, P., Bernacki, R., Xia, R., Horwitz, S., Simmerling, C., and Ojima, I. 
Chemistry & Biology , 2005 , 12 (3), 339-348 
DOI: 10.1016/j.chembiol.2005.01.004 

Folding Cooperativity in a Three-stranded beta-sheet Model 
Roe, D., Hornak, V. and Simmerling, C. 
Journal of Molecular Biology, 2005, 352 (2), 370-381 
DOI: 10.1016/j.jmb.2005.07.036 

Dynamic Behavior of DNA Base Pairs Containing 8-oxoguanine 
Cheng, X., Kelso, C., Hornak, V., de los Santos, C., Grollman, A. and Simmerling, C. 
Journal of American Chemical Society, 2005 , 127 (40), 13906-13918 
DOI: 10.1021/ja052542s 

The Amber biomolecular simulation program 
Case, D. A.; Cheatham, T. E.; Darden, T.; Gohlke, H.; Luo, R.; Merz, K. M.; Onufriev, A.; Simmerling, C.; Wang, B.; Woods, R. J. 
Journal of Computational Chemistry, 2005 , 26 , 1668- 
DOI: 

Modified Replica Exchange Simulation Methods for Local Structure Refinement 
Cheng, X., Cui, G., Hornak, V. and Simmerling, C. 
Journal of Physical Chemistry B, 2005, 109 (16), 8220-8230 
DOI: 10.1021/jp045437y 

Improved Conformational Sampling through an Efficient Combination of Mean-Field Simulation Approaches 
Cheng, X., Hornak, V. and Simmerling, C.
Journal of Physical Chemistry, 2004 , 108 (1), 426-437 
DOI: 10.1021/jp034505y 

Development of Softcore Potential Functions for Overcoming Steric Barriers in MD 
Hornak, V. and Simmerling, C. 
Journal of Molecular Graphics & Modelnig , 2004 , 22 (5), 405-413 
DOI: 10.1016/j.jmgm.2003.12.007 

Inhibition of the Bacterial Enoyl Reductase FabI by Triclosan: A Structure-Reactivity Analysis of FabI Inhibition by Triclosan Analogs 
Sivaraman, S., Sullivan, T., Johnson. F., Novichenok, P., Cui, G., Simmerling, C., Johnson, F. and Tonge, P. 
Journal of Medicinal Chemistry , 2004 , 47 (3), 509-518 
DOI: 10.1021/jm030182i 

Foreword: Conformational Sampling Special Issue 
Roitberg, A. and Simmerling, C. 
Journal of Molecular Graphics & Modeling, 2004, 22 (5), 317 
DOI: 10.1016/j.jmgm.2004.03.015 

Using PC Clusters to Evaluate the Transferability of Molecular Mechanics Force Fields for Proteins 
Okur, A., Strockbine, B., Hornak, V. and Simmerling, C. 
Journal of Computational Chemistry , 2003 , 24 (1), 21-31 
DOI: 10.1002/jcc.10184 

Generation of Accurate Protein Loop Conformations through Low-barrier Molecular Dynamics 
Hornak, V. and Simmerling, C. 
Proteins: Structure, Function, Genetics, 2003 , 51 (4), 577-590 
DOI: 10.1002/prot.10363 

All-Atom Structure Prediction and Folding Simulations of a Stable Protein 
Simmerling, C., Strockbine, B and Roitberg, A. 
Journal of American Chemical Society, 2002 , 124 (38), 11258-11259 
DOI: 10.1021/ja0273851 

Conformational Heterogeneity Observed in Simulations of a Pyrene-Substitued DNA 
Cui, G and Simmerling, C. 
Journal of American Chemical Society, 2002, 124 (41), 12154-12164 
DOI: 10.1021/ja026825l 

The Disordered Mobile Loop of GroES Folds into a Defined beta Hairpin upon Binding GroEL 
Shewmaker, F., Maskos, K., Simmerling, C. and Landry, S. J. 
Journal of Biological Chemistry , 2001 , 276 (33), 31257-31264 
DOI: 10.1074/jbc.M102765200 

Combining MONSSTER and LES/PME to Predict Protein Structure from Amino Acid Sequence: Application to the Small Protein CMTI-I 
Simmerling, C., Lee, M.R, Ortiz, AR., Kolinski, A., Skolnick, J., Kollman, P.A.
Journal of American Chemical Society , 2000 , 122 (35), 8392-8402 
DOI: 10.1021/ja993119k 

Combined Locally Enhanced Sampling and Particle Mesh Ewald as a Strategy to Locate the Experimental Structure of a Non-helical Nucleic Acid 
Simmerling, C., Miller, J. L., and Kollman, P. 
Journal of American Chemical Society , 1998 , 120 (29), 7149-7155 
DOI: 10.1021/ja9727023 

The Use of Locally Enhanced Sampling in Free Energy Calculations: Testing and Application to the alpha -> beta Anomerization of Glucose 
Simmerling, C., Fox, T. and Kollman, P. 
Journal of American Chemical Society , 1998 , 120 (23), 5771-5782 
DOI: 10.1021/ja972457n 

AMBER 5
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., 
University of California, San Francisco, 1997 

Dynamics of Peptide Folding 
Elber, R., Mohanty, D. and Simmerling, C. 
in Classical and Quantum Dynamics in Condensed Phase Simulations, B. Berne et. al. (eds.) World Scientific, Singapore , 1998 

MOIL- A Program for Simulation of Macromolecules 
Elber, R., Roitberg, A., Simmerling, C., Goldstein, R., Verkhivker, G., Li, H. and Ulitsky, A.
Comp. Phys. Comm., 1995 , 91 (1-3), 159-189 
DOI: 10.1016/0010-4655(95)00047-J 

MOIL-View: A Program for Visualization of Structure and Dynamics of Biomolecules and STO: a Program for Computing Stochastic Paths 
Simmerling, C., Elber, R. and Zhang, J., 
in Modeling of Biomolecular Structures and Mechanisms, A. Pullman et al. (eds.) Kluwer Acad. Publishers, Netherlands , 1995 

Computer Determination of Peptide Conformations in Water: Different Roads to Structure 
Simmerling, C. and Elber, R. 
Proceedings of the National Academics of Sciences USA , 1995 , 92 (8), 3190-3193 
DOI: 

Hydrophobic “Collapse” in a Cyclic Hexapeptide: Computer Simulations of CHDLFC and CAAAAC in Water 
Simmerling, C. and Elber, R. 
Journal of American Chemical Society , 1994 , 16 (6), 2534-2547 
DOI: 10.1021/ja00085a038 

MOIL- A Molecular Dynamics Program with Emphasis on Conformational Searches and Reaction Path Calculations in Large Biological Molecules 
Elber, R., Roitberg, A., Simmerling, C., Goldstein, R., Verkhivker, G. and Li, H. 
in Statistical Mechanics, Protein Structure and Protein-Substrate Interactions, S Doniach (ed.), Plenum Press, NY , 1994