Scientific Report 2006

Molecular Biology

Theoretical and Computational Molecular Biophysics

C.L. Brooks III, C. An, R. Armen, I. Borelli, D. Bostick, D. Braun, L. Bu, J. Chen, M.F. Crowley, O. Guvench, R. Hills, W. Im,* J. Khandogin, I. Khavrutskii, J. Lee, J. Magee,** R. Manige, M. Michino, A. Mitsutake,*** H.D. Nguyen, S. Patel,**** D.J. Price, V. Reddy, H.A. Scheraga,***** C. Shepard, F. Tama,^† I.F. Thorpe, M.C. Tripp, R. Wheeler,^†† C. Wildman, K. Yoshimoto

* Kansas University, Lawrence, Kansas
** University of Manchester, Manchester, England
*** Kelo University, Tokyo, Japan
**** University of Delaware, Newark, Delaware
***** Cornell University, Ithaca, New York
^† University of Arizona, Tucson, Arizona
^†† University of Oklahoma, Norman, Oklahoma

Understanding the forces that determine the structure of proteins, peptides, nucleic acids, and complexes containing these molecules and the processes by which these structures are adopted is essential to complete our knowledge of the molecular nature of structure and function. To address such questions, we use statistical mechanics, molecular simulation, statistical modeling, and quantum chemistry.

Creating atomic-level models to simulate biophysical processes (e.g., protein folding or binding of a ligand to a biological receptor) requires (1) the development of new potential energy functions that accurately represent the atomic interactions and (2) the use of quantum chemistry to aid in determining the parameters for the models. Calculation of thermodynamic properties requires the development and implementation of new theoretical and computational approaches that connect averages over atomistic descriptions to experimentally measurable thermodynamic and kinetic properties.

Interpreting experimental results at more microscopic levels is fueled by the development and investigation of theoretical models for the processes of interest. Massive computational resources are needed to realize these objectives, and this motivates our efforts aimed at the efficient use of new computer architectures, including large supercomputers, Linux Beowulf clusters, computational grids, and Internet-based volunteer supercomputers. Each of the objectives and techniques mentioned represents an ongoing development area within our research program in computational biophysics. The following are highlights of a few specific projects.

Folding, Structure, and Function of Membrane-Bound Proteins

Folding, insertion, assembly, and stability of membrane proteins are directly governed by the unique hydrophilic and hydrophobic environment provided by biological membranes. Modeling this heterogeneous environment is both an obstacle and an essential requisite to experimental and computational studies of the structure and function of membrane proteins. Because of the biological importance and marked presence of membrane proteins in known genomes (i.e., about 30% of all proteins), one aim of modern molecular biophysics should be the development of methods that can be used in experimental studies to understand the structure and function of these systems. We recently developed theoretical methods that enable the exploration of protein insertion and folding in membranes. These methods combine the sampling methods of replica-exchange molecular dynamics with novel generalized Born implicit solvent/implicit membrane continuum electrostatic theories.

A key question these methods allow us to address is the association of integral membrane proteins to form oligomeric structures. Many important functional complexes of membrane proteins exist as oligomers, such as the signal-transducing G protein–coupled receptors and membrane-bound ion channels and transporters. Our recent approach provides a way to predict the structures of these key oligomeric states. Figure 1 shows the predicted oligomeric structures of glycophorin A (functionally a dimer), the tetrameric M2 transmembrane peptide proton channel, and the phospholamban pentameric oligomer. Our calculations provide detailed predictions of the protein-protein interfaces for these systems and may be useful in elucidating the primary oligomerization states. The predicted models shown in the figure are in excellent agreement with existing structural models (from experiments and other model building).

Fig. 1. The predicted structure of dimeric glycophorin A, a dominant structural component of red blood cells, indicates the “classic” GVXXGV helical interface. For the M2 proton channel involved in replication of the influenza virus, the structure of the functional tetrameric proton-conducting channel is shown. In phospholamban, which is localized in the membrane of the cardiac sarcoplasmic reticulum and involved in phosphorylation-controlled regulation of the cardiac calcium pump, the predicted pentameric structure selectively conducts calcium.

Large-Scale Functional Dynamics in Molecular Assemblies

Many naturally occurring machines, such as ribosomes, myosin, and viruses, require large-scale dynamical motions as a component of their normal functioning. These motions involve the “mechanical” reorganization of major parts of the structure of the machine in response to binding of effectors or the addition of energy in the form of thermal fluctuations or provided by chemical catalysis. Exploring and understanding the character and nature of such large-scale reorganization of biological machines are ongoing goals in our laboratory. Using theoretical approaches derived from the treatment of mechanoelastic materials, we developed new structure refinement methods to model large-scale macromolecular assemblies. The methods are based on atomic-level structures of the component macromolecules (e.g., RNAs, DNAs, and proteins) or on single-particle or tomographic images from electron microscopy. Using these new methods, which we call normal mode flexible fitting, we have collaborated with several colleagues in elucidating new structural models for functionally important molecular assemblies.

One recent advance came in exploring the structure of the ribosome in complex with the SecY protein-conducting channel (PCC). The translocation of secreted and membrane proteins across or into cell membranes occurs through PCCs. Using an electron cryomicroscopy reconstruction of the Escherichia coli PCC, which consisted of SecY complexed with the ribosome and a nascent chain containing a signal anchor, we observed the components of protein synthesis and translocation, including mRNA, 3 tRNAs, the nascent chain, and features of both a translocating PCC and a second, nontranslocating PCC bound to mRNA hairpins (Fig. 2). Normal mode flexible fitting of the SecYEb structure into the PCC electron microscopy densities favors a front-to-front arrangement of 2 SecYEG complexes in the PCC and supports channel formation by the opening of 2 linked SecY halves during polypeptide translocation. From the models elucidated by the combination of electron cryomicroscopy and modeling based on normal mode flexible fitting, we were able to develop a model for cotranslational protein translocation.

Fig. 2. Electron cryomicroscopy image of the ribosome with 2 bound PCCs obtained during the modeling of structural components of the SecY dimer into the electron density for the nontranslocating and translocating PCCs. The figure on the lower right illustrates the structure of the SecY dimer fit into the experimental electron density map by using normal mode flexible fitting. NNMF indicates normal mode flexible fitting.

Publications

Chen, J., Im, W., Brooks, C.L. III. Application of torsion angle molecular dynamics for efficient sampling of protein conformations. J. Comput. Chem. 26:1565, 2005.

Chen, J., Im, W., Brooks, C.L. III. Balancing solvation and intramolecular interactions: toward a consistent generalized Born force field. J. Am. Chem. Soc. 128:3728, 2006.

Im, W., Chen, J., Brooks, C.L. III. Peptide and protein folding and conformational equilibria: theoretical treatment of electrostatics and hydrogen bonding with implicit solvent models. Adv. Protein Chem. 72:173, 1005.

Khandogin, J., Brooks, C.L. III. Constant pH molecular dynamics with proton tautomerism. Biophys. J. 89:141, 2005.

Khavrutskii, I.V., Byrd, R.H., Brooks, C.L. III. A line integral reaction path approximation for large systems via nonlinear constrained optimization: application to alanine dipeptide and the β-hairpin of protein G. J. Chem. Phys. 124:194903, 2006.

Konecny, R., Trylska, J., Tama, F., Zhang, D., Baker, N.A., Brooks, C.L. III, McCammon, J.A. Electrostatic properties of cowpea chlorotic mottle virus and cucumber mosaic virus capsids. Biopolymers 82:106, 2005.

Mitra, K., Schaffitzel, C., Shaikh, T., Tama, F., Jenni, S., Brooks, C.L. III, Ban, N., Frank, J. Structure of the E. coli protein-conducting channel bound to a translating ribosome. Nature 438:318, 2005.

Natarajan, P., Lander, G.C., Shepherd, C.M., Reddy, V.S., Brooks, C.L. III, Johnson, J.E. Exploring icosahedral virus structures with VIPER. Nat. Rev. Microbiol. 3:809, 2005.

Patel, S., Brooks, C.L. III. Fluctuating charge force fields: recent developments and applications from small molecules to macromolecular biological systems. Mol. Simul. 32:231, 2006.

Patel, S., Brooks, C.L. III. Revisiting the hexane-water interface via molecular dynamics simulations using nonadditive alkane-water potentials. J. Chem. Phys. 124:204706, 2006.

Patel, S., Brooks, C.L. III. Structure, thermodynamics, and liquid-vapor equilibrium of ethanol from molecular-dynamics simulations using nonadditive interactions. J. Chem. Phys. 123:164502, 2005.

Price, D.J., Brooks, C.L. III. Detailed considerations for a balanced and broadly applicable force field: a study of substituted benzenes modeled with OPLS-AA. J. Comput. Chem. 26:1529, 2005.

Tama, F., Brooks, C.L. III. Symmetry, form, and shape: guiding principles for robustness in macromolecular machines. Annu. Rev. Biophys. Biomol. Struct. 35:115, 2006.

Tama, F., Brooks, C.L. III. Unveiling molecular mechanisms of biological functions in large macromolecular assemblies using elastic network normal mode analysis. In: Normal Mode Analysis: Theory and Applications to Biological and Chemical Systems. Cui, Q., Bahar, I. (Eds.). Chapman & Hall/CRC Press, Boca Raton, FL, 2006, p. 111. Mathematical and Computational Biology Series.

Taufer, M., An, C., Kerstens, A., Brooks, C.L. III. Predictor@Home: a “protein structure prediction supercomputer” based on global computing. IEEE Trans. Parallel Distributed Syst. 7:786, 2006.

Thorpe, I.F., Brooks, C.L. III. Conformational substates modulate hydride transfer in dihydrofolate reductase. J. Am. Chem. Soc. 127:12997, 2005.

Trylska, J., McCammon, J.A., Brooks, C.L. III. Exploring assembly energetics of the 30S ribosomal subunit using an implicit solvent approach. J. Am. Chem. Soc. 127:11125, 2005.

Yadav, M.K., Leman, L.J., Price, D.J., Brooks, C.L. III, Stout, C.D., Ghadiri, M.R. Coiled coils at the edge of configurational heterogeneity: structural analyses of parallel and antiparallel homotetrameric coiled coils reveal configurational sensitivity to a single solvent-exposed amino acid substitution. Biochemistry 45:4463, 2006.