title: Assessing protein conformational sampling and structural stability via de novo design and molecular dynamics simulations.
abstract: Molecular dynamics and de novo techniques, associated to quality parameter sets, have excelled at determining the structure of small proteins with high accuracy. To achieve a detailed description of protein conformations, these methods must critically assess the thermodynamic features of the molecular ensembles. Here, a comparison of the conformational ensemble generated by molecular dynamics and de novo techniques were carried out for six Top7-based proteins carrying gp41 HIV-1 epitopes. The native Top7, a highly stable computationally designed protein, was used as benchmark. Structural stability, flexibility, and secondary structure content were assessed. The consistency of the latter was compared to experimental circular dichroism spectra for all proteins. While both methods are capable to identify the stable from unstable chimeric proteins, the sampled conformational space and flexibility differ significantly in both methods. Molecular dynamics simulations seem to better describe secondary structure content and identify regions responsible for conformational instability. The de novo method, as implemented in Rosetta-a prime tool for protein design, overestimates secondary structure content. On the other hand, its empirical energy function is capable to predict the threshold for protein stability.
authors: Department of Fundamental Chemistry, Federal University of Pernambuco, Recife, PE, 50740-560, Brazil.
authors: Keila C
authors: KC
authors: Cunha
authors: Victor H
authors: VH
authors: Rusu
authors: Isabelle F T
authors: IF
authors: Viana
authors: Ernesto T A
authors: ET
authors: Marques
authors: Rafael
authors: R
authors: Dhalia
authors: Roberto D
authors: RD
authors: Lins
mesh_terms: D056004:Molecular Dynamics Simulation; D011487:Protein Conformation; D017510:Protein Folding; D055550:Protein Stability; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins
keywords: protein engineering; protein stability; structure prediction