Hironori Kokubo

Peptide Conformational Preferences in Osmolyte Solutions: Transfer Free Energies of Decaalanine

The nature in which the protecting osmolyte trimethylamine N-oxide (TMAO) and the denaturing osmolyte urea affect protein stability is investigated, simulating a decaalanine peptide model in multiple conformations of the denatured ensemble. Binary solutions of both osmolytes and mixed osmolyte solutions at physiologically relevant concentrations of 2:1 (urea:TMAO) are studied using standard molecular dynamics simulations and solvation free energy calculations. Component analysis reveals the differences in the importance of the van der Waals (vdW) and electrostatic interactions for protecting and denaturing osmolytes. We find that urea denaturation governed by transfer free energy differences is dominated by vdW attractions, whereas TMAO exerts its effect by causing unfavorable electrostatic interactions both in the binary solution and mixed osmolyte solution. Analysis of the results showed no evidence in the ternary solution of disruption of the correlations among the peptide and osmolytes, nor of significant changes in the strength of the water hydrogen bond network.

Trimethylamine N-oxide influence on the backbone of proteins: An oligoglycine model

The study of organic osmolytes has been pivotal in demonstrating the role of solvent effects on the protein backbone in the folding process. Although a thermodynamic description of the interactions between the protein backbone and osmolyte has been well defined, the structural analysis of the effect of osmolyte on the protein backbone has been incomplete. Therefore, we have performed simulations of a peptide backbone model, glycine15, in protecting osmolyte trimethylamine N‐oxide (TMAO) solution, in order to determine the effect of the solution structure on the conformation of the peptide backbone. We show that the models chosen show that the ensemble of backbone structures shifts toward a more collapsed state in TMAO solution as compared with pure water solution. The collapse is consistent with preferential exclusion of the osmolyte caused by unfavorable interactions between osmolyte and peptide backbone. The exclusion is caused by strong triplet correlations of osmolyte, water, and peptide backbone. This provides a clear mechanism showing that even a modest concentration of TMAO forces the protein backbone to adopt a more collapsed structure in the absence of side chain effects. Proteins 2010.

Backbone additivity in the transfer model of protein solvation.

The transfer model implying additivity of the peptide backbone free energy of transfer is computationally tested. Molecular dynamics simulations are used to determine the extent of change in transfer free energy (ΔGtr) with increase in chain length of oligoglycine with capped end groups. Solvation free energies of oligoglycine models of varying lengths in pure water and in the osmolyte solutions, 2M urea and 2M trimethylamine N‐oxide (TMAO), were calculated from simulations of all atom models, and ΔGtr values for peptide backbone transfer from water to the osmolyte solutions were determined. The results show that the transfer free energies change linearly with increasing chain length, demonstrating the principle of additivity, and provide values in reasonable agreement with experiment. The peptide backbone transfer free energy contributions arise from van der Waals interactions in the case of transfer to urea, but from electrostatics on transfer to TMAO solution. The simulations used here allow for the calculation of the solvation and transfer free energy of longer oligoglycine models to be evaluated than is currently possible through experiment. The peptide backbone unit computed transfer free energy of −54 cal/mol/M compares quite favorably with −43 cal/mol/M determined experimentally.

Prediction of membrane protein structures by replica-exchange Monte Carlo simulations: Case of two helices

We test our prediction method of membrane protein structures with glycophorin A transmembrane dimer and analyze the predicted structures in detail. Our method consists of two parts. In the first part, we obtain the amino-acid sequences of the transmembrane helix regions from one of existing WWW servers and use them as an input for the second part of our method. In the second part, we perform a replica-exchange Monte Carlo simulation of these transmembrane helices with some constraints that indirectly represent surrounding lipid and water effects and identify the predicted structure as the global-minimum-energy state. The structure obtained in the case for the dielectric constant epsilon=1.0 is very close to that from the nuclear magnetic resonance experiments, while that for epsilon=4.0 is more packed than the native one. Our results imply that the helix-helix interaction is the main driving force for the native structure formation and that the stability of the native structure is determined by the balance of the electrostatic term, van der Waals term, and torsion term, and the contribution of electrostatic energy is indeed important for correct predictions. The inclusion of atomistic details of side chains is essential for estimating this balance accurately because helices are tightly packed.

Ab initio prediction of protein-ligand binding structures by replica-exchange umbrella sampling simulations.

We have developed a prediction method for the binding structures of ligands with proteins. Our method consists of three steps. First, replica‐exchange umbrella sampling simulations are performed along the distance between a putative binding site of a protein and a ligand as the reaction coordinate. Second, we obtain the potential of mean force (PMF) of the unbiased system using the weighted histogram analysis method and determine the distance that corresponds to the global minimum of PMF. Third, structures that have this global‐minimum distance and energy values around the average potential energy are collected and analyzed using the principal component analysis. We predict the binding structure as the global‐minimum free energy state on the free energy landscapes along the two major principal component axes. As test cases, we applied our method to five protein–ligand complex systems. Starting from the configuration in which the protein and the ligand are far away from each other in each system, our method predicted the ligand binding structures in excellent agreement with the experimental data from Protein Data Bank.

Prediction of transmembrane helix configurations by replica-exchange simulations

We propose a method for predicting helical membrane protein structures by computer simulations. Our method consists of two parts. In the first part, amino-acid sequences of the transmembrane helix regions are obtained from one of existing WWW servers. In the second part, we perform a replica-exchange simulation of these transmembrane helices with some constraints and identify the predicted structure as the global-minimum-energy state. We have tested the second part of the method with the dimeric transmembrane domain of glycophorin A. The structure obtained from the prediction was in close agreement with the experimental data.

Two‐dimensional replica‐exchange method for predicting protein–ligand binding structures

We have developed a two‐dimensional replica‐exchange method for the prediction of protein–ligand binding structures. The first dimension is the umbrella sampling along the reaction coordinate, which is the distance between a protein binding pocket and a ligand. The second dimension is the solute tempering, in which the interaction between a ligand and a protein and water is weakened. The second dimension is introduced to make a ligand follow the umbrella potential more easily and enhance the binding events, which should improve the sampling efficiency. As test cases, we applied our method to two protein‐ligand complex systems (MDM2 and HSP 90‐alpha). Starting from the configuration in which the protein and the ligand are far away from each other in each system, our method predicted the ligand binding structures in excellent agreement with the experimental data from Protein Data Bank much faster with the improved sampling efficiency than the replica‐exchange umbrella sampling method that we have previously developed.

Prediction of Protein-Ligand Binding Structures by Replica-Exchange Umbrella Sampling Simulations: Application to Kinase Systems.

We have applied our prediction method, which is based on the replica-exchange umbrella sampling for protein-ligand binding structures, to two kinase systems (p38 and JNK3) with two different ligand molecules for each kinase. Starting from configurations in which the protein and the ligand are far away from each other, our method predicted the ligand binding structures in excellent agreement with the experimental data from PDB in all four cases, which suggests the general applicability of our method to kinase systems. In addition, the protein flexibility was shown to be essential to predict the correct binding structure for one of the systems, where dihydroquinolinone was bound to p38 alpha kinase (PDB ID: 1OVE ).

Classification and prediction of low-energy membrane protein helix configurations by replica-exchange Monte Carlo method

The effectiveness of our classification and prediction method for transmembrane helix configurations of membrane proteins by replica-exchange simulations is tested with glycophorin A transmembrane dimer. Replica-exchange simulations can sample wide configurational space without getting trapped in local-minimum free energy states and we can find stable structures at low temperatures. We classify low-energy configurations into clusters of similar structures by the principal component analysis. These clusters are identified as the global-minimum and local-minimum free energy states. Our classifications revealed that there are only two major groups of similar structures in the case of the simulation with the dielectric constant e= 1.0 and five such groups in the case of e= 4.0. The global-minimum free energy state in the case of e= 1.0 is very close to the structure of the NMR experiments and the prediction was successful, while in the case of e= 4.0 not the global-minimum but a local-minimum free energy stat...

Analysis of Helix-Helix Interactions of Bacteriorhodopsin by Replica-Exchange Simulations

We performed long-time replica-exchange Monte Carlo simulations of bacteriorhodopsin transmembrane helices, which made it possible that wide conformational space was sampled. Using only the helix-helix interactions and starting from random initial configurations, we obtained the nativelike helix arrangement successfully and predicted a part of the configurations (three helices out of seven) precisely. By the principal component analysis we classified low-energy structures into some clusters of similar structures, and we showed that the above nativelike three-helix configuration is reproduced properly in most clusters and that not only the van der Waals interactions but also the electrostatic interactions contributed to the stabilization of the native structures.