Biomedical subjects

Meng-Juei Hsieh

Publications and source records attributed to Meng-Juei Hsieh.

3 recordsLinked to original sources

PubMed2006

New-generation amber united-atom force field.

We have developed a new-generation Amber united-atom force field for simulations involving highly demanding conformational sampling such as protein folding and protein-protein binding. In the new united-atom force field, all hydrogens on aliphatic carbons in all amino acids are united with carbons except those on Calpha. Our choice of explicit representation of all protein backbone atoms aims at minimizing perturbation to protein backbone conformational distributions and to simplify development of backbone torsion terms. Tests with dipeptides and solvated proteins show that our goal is achieved quite successfully. The new united-atom force field uses the same new RESP charging scheme based on B3LYP/cc-pVTZ//HF/6-31g** quantum mechanical calculations in the PCM continuum solvent as that in the Duan et al. force field. van der Waals parameters are empirically refitted starting from published values with respect to experimental solvation free energies of amino acid side-chain analogues. The suitability of mixing new point charges and van der Waals parameters with existing Amber covalent terms is tested on alanine dipeptide and is found to be reasonable. Parameters for all new torsion terms are refitted based on the new point charges and the van der Waals parameters. Molecular dynamics simulations of three small globular proteins in the explicit TIP3P solvent are performed to test the overall stability and accuracy of the new united-atom force field. Good agreements between the united-atom force field and the Duan et al. all-atom force field for both backbone and side-chain conformations are observed. In addition, the per-step efficiency of the new united-atom force field is demonstrated for simulations in the implicit generalized Born solvent. A speedup around two is observed over the Duan et al. all-atom force field for the three tested small proteins. Finally, the efficiency gain of the new united-atom force field in conformational sampling is further demonstrated with a well-known toy protein folding system, an 18 residue polyalanine in distance-dependent dielectric. The new united-atom force field is at least a factor of 200 more efficient than the Duan et al. all-atom force field for ab initio folding of the tested peptide.

Models, Molecular↗

PubMed2004

Physical scoring function based on AMBER force field and Poisson-Boltzmann implicit solvent for protein structure prediction.

A well-behaved physics-based all-atom scoring function for protein structure prediction is analyzed with several widely used all-atom decoy sets. The scoring function, termed AMBER/Poisson-Boltzmann (PB), is based on a refined AMBER force field for intramolecular interactions and an efficient PB model for solvation interactions. Testing on the chosen decoy sets shows that the scoring function, which is designed to consider detailed chemical environments, is able to consistently discriminate all 62 native crystal structures after considering the heteroatom groups, disulfide bonds, and crystal packing effects that are not included in the decoy structures. When NMR structures are considered in the testing, the scoring function is able to discriminate 8 out of 10 targets. In the more challenging test of selecting near-native structures, the scoring function also performs very well: for the majority of the targets studied, the scoring function is able to select decoys that are close to the corresponding native structures as evaluated by ranking numbers and backbone Calpha root mean square deviations. Various important components of the scoring function are also studied to understand their discriminative contributions toward the rankings of native and near-native structures. It is found that neither the nonpolar solvation energy as modeled by the surface area model nor a higher protein dielectric constant improves its discriminative power. The terms remaining to be improved are related to 1-4 interactions. The most troublesome term is found to be the large and highly fluctuating 1-4 electrostatics term, not the dihedral-angle term. These data support ongoing efforts in the community to develop protein structure prediction methods with physics-based potentials that are competitive with knowledge-based potentials.

Algorithms↗

PubMed2004

Enhanced ab initio protein folding simulations in Poisson-Boltzmann molecular dynamics with self-guiding forces.

We have investigated the sampling efficiency in molecular dynamics with the PB implicit solvent when self-guiding forces are added. Compared with a high-temperature dynamics simulation, the use of self-guiding forces in room-temperature dynamics is found to be rather efficient as measured by potential energy fluctuation, gyration radius fluctuation, backbone RMSD fluctuation, number of unique clusters, and distribution of low RMSD structures over simulation time. Based on the enhanced sampling method, we have performed ab initio folding simulations of two small proteins, betabetaalpha1 and villin headpiece. The preliminary data for the folding simulations is presented. It is found that betabetaalpha1 folding proceeds by initiation of the turn and the helix. The hydrophobic collapse seems to be lagging behind or at most concurrent with the formation of the helix. The hairpin stability is weaker than the helix in our simulations. Its role in the early folding events seems to be less important than the more stable helix. In contrast, villin headpiece folding proceeds first by hydrophobic collapse. The formation of helices is later than the collapse phase, different from the betabetaalpha1 folding.

Computer Simulation↗