2.1 and 1.8 angstrom average C-alpha RMSD structure predictions on two small proteins, HP-36 and S15

Citation
Mr. Lee et al., 2.1 and 1.8 angstrom average C-alpha RMSD structure predictions on two small proteins, HP-36 and S15, J AM CHEM S, 123(6), 2001, pp. 1040-1046
Citations number
32
Categorie Soggetti
Chemistry & Analysis",Chemistry
Journal title
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
ISSN journal
00027863 → ACNP
Volume
123
Issue
6
Year of publication
2001
Pages
1040 - 1046
Database
ISI
SICI code
0002-7863(20010214)123:6<1040:2A1AAC>2.0.ZU;2-A
Abstract
On two different small proteins, the 36-mer villin headpiece domain (HP-36) and the 65-mer structured region of ribosomal protein (S15), several model predictions from the ab initio approach Rosetta were subjected to molecula r dynamics simulations for refinement. After clustering the resulting traje ctories into conformational families, the average molecular mechanics-Poiss on Boltzmann/surface area (MM-PBSA) free energies and alpha carbon (C-alpha ) RMSDs were then calculated for each family. Those conformational families with the lowest average free energies also contained the best C-alpha RMSD structures (1.4 Angstrom for S15 and HP-36 core) and the lowest average C- alpha RMSDs (1.8 Angstrom for S15, 2.1 Angstrom for HP-36 core). For compar ison, control simulations starting with the two experimental structures wer e very stable, each consisting of a single conformational family, with an a verage C-alpha RMSD of 1.3 Angstrom for S15 and 1.2 Angstrom for HP-36 core (1.9 Angstrom over all residues). In addition, the average free energies' ranks (Spearman rank, r(s)) correlate well with the average C-alpha RMSDs ( r(s) = 0.77 for HP-36, r(s) = 0.83 for S15). Molecular dynamics simulations combined with the MM-PBSA free energy function provide a potentially power ful tool for the protein structure prediction community in allowing for bot h high-resolution structural refinement and accurate ranking of model predi ctions. With all of the information that genomics is now providing, this me thodology may allow for advances in going from sequence to structure.