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- W2045256471 endingPage "1637" @default.
- W2045256471 startingPage "1619" @default.
- W2045256471 abstract "Abstract The three‐dimensional (3‐D) structure prediction of proteins, given their amino acid sequence, is addressed using the first principles–based approach ASTRO‐FOLD 2.0. The key features presented are: (1) Secondary structure prediction using a novel optimization‐based consensus approach, (2) β‐sheet topology prediction using mixed‐integer linear optimization (MILP), (3) Residue‐to‐residue contact prediction using a high‐resolution distance‐dependent force field and MILP formulation, (4) Tight dihedral angle and distance bound generation for loop residues using dihedral angle clustering and non‐linear optimization (NLP), (5) 3‐D structure prediction using deterministic global optimization, stochastic conformational space annealing, and the full‐atomistic ECEPP/3 potential, (6) Near‐native structure selection using a traveling salesman problem‐based clustering approach, ICON, and (7) Improved bound generation using chemical shifts of subsets of heavy atoms, generated by SPARTA and CS23D. Computational results of ASTRO‐FOLD 2.0 on 47 blind targets of the recently concluded CASP9 experiment are presented. © 2011 American Institute of Chemical Engineers AIChE J, 2012" @default.
- W2045256471 created "2016-06-24" @default.
- W2045256471 creator A5031469247 @default.
- W2045256471 creator A5043727603 @default.
- W2045256471 creator A5050187529 @default.
- W2045256471 date "2011-05-31" @default.
- W2045256471 modified "2023-10-17" @default.
- W2045256471 title "ASTRO-FOLD 2.0: An enhanced framework for protein structure prediction" @default.
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