title: EvoDesign: De novo protein design based on structural and evolutionary profiles.
abstract: Protein design aims to identify new protein sequences of desirable structure and biological function. Most current de novo protein design methods rely on physics-based force fields to search for low free-energy states following Anfinsen's thermodynamic hypothesis. A major obstacle of such approaches is the inaccuracy of the force field design, which cannot accurately describe the atomic interactions or distinguish correct folds. We developed a new web server, EvoDesign, to design optimal protein sequences of given scaffolds along with multiple sequence and structure-based features to assess the foldability and goodness of the designs. EvoDesign uses an evolution-profile-based Monte Carlo search with the profiles constructed from homologous structure families in the Protein Data Bank. A set of local structure features, including secondary structure, torsion angle and solvation, are predicted by single-sequence neural-network training and used to smooth the sequence motif and accommodate the physicochemical packing. The EvoDesign algorithm has been extensively tested in large-scale protein design experiments, which demonstrate enhanced foldability and structural stability of designed sequences compared with the physics-based designing methods. The EvoDesign server is freely available at http://zhanglab.ccmb.med.umich.edu/EvoDesign.
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109 USA.
authors.forename: Pralay
authors.initials: P
authors.lastname: Mitra
authors.forename: David
authors.initials: D
authors.lastname: Shultis
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D019143:Evolution, Molecular; D020407:Internet; D009010:Monte Carlo Method; D011487:Protein Conformation; D015202:Protein Engineering / Q000379:methods*; D020539:Sequence Analysis, Protein; D012984:Software