(677a) New Advances in the First Principles Protein 3D Structure Prediction Method ASTRO-FOLD
The ASTRO-FOLD approach  is an ab initio method for the tertiary structure predictions of proteins from their primary amino acid sequences. There have been several advances at various stages of ASTRO-FOLD. These consist of secondary structure prediction using integer linear programming ; distance and angle constraints derivation from secondary structure geometries, residue contact prediction , structural topology prediction and loop prediction; 3D prediction algorithm combining a deterministic global optimization method aBB and conformational space annealing , and near-native structure identification using a novel clustering method  and a high resolution force field .
In addition to the existing first principles secondary structure perdition methods, a consensus secondary structure prediction method using mixed integer linear programming is developed based on 7 well-known secondary structure predictors and it shows better performance than each individual methods. The improvement of derivation of constraints are due to a) residue contact prediction has been enhanced by a new mixed integer linear optimization model which predicts residue contacts and structural topologies for alpha, beta and mixed alpha/beta proteins ; b) a new loop structure prediction method based on iterative improvement of bounds and nonlinear local optimization; c) a new sheet topology prediction method based on support vector machines and integer linear optimization. The protein 3D structure prediction algorithm based on a hybrid method is enhanced by adding/modifying some elements, for example, initial conformation selection using a more detailed torsional angle dynamics annealing procedure and side chain rotamer optimization as an effective local minimizer . In order to identify the near-native structures, a novel traveling-salesman-problem-based clustering method (ICON) has been developed and on average, it selects the top 3.5% of the conformers in the ensemble . The identified structures can then be refined iteratively through chemical shift predictions using SPARTA  and structure predictions using CS23D .
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