ASTRO-FOLD: a combinatorial and global optimization framework for Ab initio prediction of three-dimensional structures of proteins from the amino acid sequence.

[1]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[2]  Richard Wolfenden,et al.  Comparing the polarities of the amino acids: side-chain distribution coefficients between the vapor phase, cyclohexane, 1-octanol, and neutral aqueous solution , 1988 .

[3]  B. Honig,et al.  Calculation of the total electrostatic energy of a macromolecular system: Solvation energies, binding energies, and conformational analysis , 1988, Proteins.

[4]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

[5]  F. Stillinger,et al.  Nonlinear optimization simplified by hypersurface deformation , 1988 .

[6]  G. Rose,et al.  Hydrophobicity of amino acid subgroups in proteins , 1990, Proteins.

[7]  C. Floudas,et al.  A global optimization approach for Lennard‐Jones microclusters , 1992 .

[8]  G. Barton,et al.  Multiple protein sequence alignment from tertiary structure comparison: Assignment of global and residue confidence levels , 1992, Proteins.

[9]  T. Blundell,et al.  Comparative protein modelling by satisfaction of spatial restraints. , 1993, Journal of molecular biology.

[10]  Christodoulos A. Floudas,et al.  Global optimization for molecular conformation problems , 1993, Ann. Oper. Res..

[11]  C. Sander,et al.  Protein structure comparison by alignment of distance matrices. , 1993, Journal of molecular biology.

[12]  B. Rost,et al.  Combining evolutionary information and neural networks to predict protein secondary structure , 1994, Proteins.

[13]  H. Scheraga,et al.  Energy parameters in polypeptides. 10. Improved geometrical parameters and nonbonded interactions for use in the ECEPP/3 algorithm, with application to proline-containing peptides , 1994 .

[14]  J. Thompson,et al.  CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. , 1994, Nucleic acids research.

[15]  B. Rost,et al.  Redefining the goals of protein secondary structure prediction. , 1994, Journal of molecular biology.

[16]  Christodoulos A Floudas,et al.  Global minimum potential energy conformations of small molecules , 1994, J. Glob. Optim..

[17]  C. Floudas,et al.  A deterministic global optimization approach for molecular structure determination , 1994 .

[18]  A Sali,et al.  Comparative protein modeling by satisfaction of spatial restraints. , 1996, Molecular medicine today.

[19]  B. Honig,et al.  Classical electrostatics in biology and chemistry. , 1995, Science.

[20]  Christodoulos A. Floudas,et al.  αBB: A global optimization method for general constrained nonconvex problems , 1995, J. Glob. Optim..

[21]  R A Sayle,et al.  RASMOL: biomolecular graphics for all. , 1995, Trends in biochemical sciences.

[22]  Christodoulos A. Floudas,et al.  Nonlinear and Mixed-Integer Optimization , 1995 .

[23]  Christodoulos A. Floudas,et al.  A deterministic global optimization approach for the protein folding problem , 1995, Global Minimization of Nonconvex Energy Functions: Molecular Conformation and Protein Folding.

[24]  B Honig,et al.  Free energy balance in protein folding. , 1995, Advances in protein chemistry.

[25]  Andrej ⩽ali,et al.  Comparative protein modeling by satisfaction of spatial restraints , 1995 .

[26]  G. Barton,et al.  Protein fold recognition by mapping predicted secondary structures. , 1996, Journal of molecular biology.

[27]  Christodoulos A. Floudas,et al.  A global optimization method, αBB, for process design , 1996 .

[28]  Christodoulos A. Floudas,et al.  Rigorous convex underestimators for general twice-differentiable problems , 1996, J. Glob. Optim..

[29]  Chris Sander,et al.  The FSSP database: fold classification based on structure-structure alignment of proteins , 1996, Nucleic Acids Res..

[30]  C Kooperberg,et al.  Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. , 1997, Journal of molecular biology.

[31]  J. Garnier,et al.  Fold recognition using predicted secondary structure sequences and hidden Markov models of protein folds , 1997, Proteins.

[32]  A. Liwo,et al.  A united‐residue force field for off‐lattice protein‐structure simulations. I. Functional forms and parameters of long‐range side‐chain interaction potentials from protein crystal data , 1997 .

[33]  David C. Jones,et al.  Progress in protein structure prediction. , 1997, Current opinion in structural biology.

[34]  Roland L. Dunbrack,et al.  Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool. , 1997, Journal of molecular biology.

[35]  Christodoulos A. Floudas,et al.  Deterministic Global Optimization in Design, Control, and Computational Chemistry , 1997 .

[36]  P. Andrew Karplus,et al.  Hydrophobicity regained: Hydrophobicity regained , 1997 .

[37]  Gapped BLAST and PSI-BLAST: A new , 1997 .

[38]  V. Muñoz,et al.  Folding dynamics and mechanism of β-hairpin formation , 1997, Nature.

[39]  P. Karplus,et al.  Hydrophobicity regained. , 1997, Protein science : a publication of the Protein Society.

[40]  Christodoulos A. Floudas,et al.  Global optimization of MINLP problems in Process Synthesis and Design , 1997 .

[41]  Adam Liwo,et al.  A united-residue force field for off-lattice protein-structure simulations. II. Parameterization of short-range interactions and determination of weights of energy terms by Z-score optimization , 1997, J. Comput. Chem..

[42]  Christodoulos A. Floudas,et al.  Prediction of Oligopeptide Conformations via Deterministic Global Optimization , 1997, J. Glob. Optim..

[43]  Jooyoung Lee,et al.  New optimization method for conformational energy calculations on polypeptides: Conformational space annealing , 1997, J. Comput. Chem..

[44]  Adam Liwo,et al.  A united-residue force field for off-lattice protein-structure simulations. I. Functional forms and parameters of long-range side-chain interaction potentials from protein crystal data , 1997, J. Comput. Chem..

[45]  John L. Klepeis,et al.  DIMACS Series in Discrete Mathematicsand Theoretical Computer Science Global Optimization Approaches in Protein Folding andPeptide , 2007 .

[46]  H A Scheraga,et al.  New developments of the electrostatically driven Monte Carlo method: test on the membrane-bound portion of melittin. , 1998, Biopolymers.

[47]  A. Neumaier,et al.  A global optimization method, αBB, for general twice-differentiable constrained NLPs — I. Theoretical advances , 1998 .

[48]  Geoffrey J. Barton,et al.  JPred : a consensus secondary structure prediction server , 1999 .

[49]  A. Liwo,et al.  United‐residue force field for off‐lattice protein‐structure simulations: III. Origin of backbone hydrogen‐bonding cooperativity in united‐residue potentials , 1998 .

[50]  John L. Klepeis,et al.  Predicting solvated peptide conformations via global minimization of energetic atom-to-atom interactions , 1998 .

[51]  C. Adjiman,et al.  A global optimization method, αBB, for general twice-differentiable constrained NLPs—II. Implementation and computational results , 1998 .

[52]  S. Rackovsky,et al.  Conformational analysis of the 20-residue membrane-bound portion of melittin by conformational space annealing. , 1998, Biopolymers.

[53]  Anthony K. Felts,et al.  A branch and bound algorithm for protein structure refinement from sparse NMR data sets. , 1999, Journal of molecular biology.

[54]  Anthony K. Felts,et al.  Protein tertiary structure prediction using a branch and bound algorithm , 1999, Proteins.

[55]  V S Pande,et al.  Molecular dynamics simulations of unfolding and refolding of a beta-hairpin fragment of protein G. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[56]  John L. Klepeis,et al.  Free energy calculations for peptides via deterministic global optimization , 1999 .

[57]  T. Lazaridis,et al.  Understanding b-hairpin formation , 1999 .

[58]  John L. Klepeis,et al.  Predicting peptide structures using NMR data and deterministic global optimization , 1999, J. Comput. Chem..

[59]  R. Copley,et al.  Fold recognition using sequence and secondary structure information , 1999, Proteins.

[60]  A. Liwo,et al.  Protein structure prediction by global optimization of a potential energy function. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[61]  Harold A. Scheraga,et al.  Conformational space annealing by parallel computations: Extensive conformational search of Met‐enkephalin and of the 20‐residue membrane‐bound portion of melittin , 1999 .

[62]  D. Baker,et al.  Improved recognition of native‐like protein structures using a combination of sequence‐dependent and sequence‐independent features of proteins , 1999, Proteins.

[63]  Christodoulos A. Floudas,et al.  Two results on bounding the roots of interval polynomials , 1999 .

[64]  B. Rost,et al.  A modified definition of Sov, a segment‐based measure for protein secondary structure prediction assessment , 1999, Proteins.

[65]  D T Jones,et al.  Protein secondary structure prediction based on position-specific scoring matrices. , 1999, Journal of molecular biology.

[66]  David C. Jones,et al.  GenTHREADER: an efficient and reliable protein fold recognition method for genomic sequences. , 1999, Journal of molecular biology.

[67]  M. Karplus,et al.  Understanding beta-hairpin formation. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[68]  V A Eyrich,et al.  Prediction of protein tertiary structure to low resolution: performance for a large and structurally diverse test set. , 1999, Journal of molecular biology.

[69]  Christodoulos A. Floudas,et al.  Deterministic global optimization - theory, methods and applications , 2010, Nonconvex optimization and its applications.

[70]  Adam Liwo,et al.  Efficient parallel algorithms in global optimization of potential energy functions for peptides, proteins, and crystals , 2000 .

[71]  Liisa Holm,et al.  DaliLite workbench for protein structure comparison , 2000, Bioinform..

[72]  Vijay S. Pande,et al.  Mechanical Unfolding of a β-Hairpin Using Molecular Dynamics , 2000 .

[73]  D. Higgins,et al.  T-Coffee: A novel method for fast and accurate multiple sequence alignment. , 2000, Journal of molecular biology.

[74]  Liam J. McGuffin,et al.  The PSIPRED protein structure prediction server , 2000, Bioinform..

[75]  A. Sali,et al.  Modeling of loops in protein structures , 2000, Protein science : a publication of the Protein Society.

[76]  R Samudrala,et al.  Ab initio construction of protein tertiary structures using a hierarchical approach. , 2000, Journal of molecular biology.

[77]  S. Brenner,et al.  Expectations from structural genomics , 2008, Protein science : a publication of the Protein Society.

[78]  Richard Bonneau,et al.  Rosetta in CASP4: Progress in ab initio protein structure prediction , 2001, Proteins.

[79]  A. Sali,et al.  Protein Structure Prediction and Structural Genomics , 2001, Science.

[80]  C Venclovas,et al.  Comparative modeling of CASP4 target proteins: Combining results of sequence search with three‐dimensional structure assessment , 2001, Proteins.

[81]  Adam Liwo,et al.  Development of Physics-Based Energy Functions that Predict Medium-Resolution Structures for Proteins of the α, β, and α/β Structural Classes , 2001 .

[82]  A M Gronenborn,et al.  Solution structure, backbone dynamics and chitin binding of the anti-fungal protein from Streptomyces tendae TU901. , 2001, Journal of molecular biology.

[83]  J Skolnick,et al.  Defrosting the frozen approximation: PROSPECTOR— A new approach to threading , 2001, Proteins.

[84]  J Lundström,et al.  Pcons: A neural‐network–based consensus predictor that improves fold recognition , 2001, Protein science : a publication of the Protein Society.

[85]  J. Skolnick,et al.  Ab initio protein structure prediction via a combination of threading, lattice folding, clustering, and structure refinement , 2001, Proteins.

[86]  John L. Klepeis,et al.  Deterministic Global Optimization and Ab Initio Approaches for the Structure Prediction of Polypeptides, Dynamics of Protein Folding, and Protein‐Protein Interactions , 2002 .

[87]  John L. Klepeis,et al.  Ab initio prediction of helical segments in polypeptides , 2002, J. Comput. Chem..

[88]  Cinque S. Soto,et al.  Evaluating conformational free energies: The colony energy and its application to the problem of loop prediction , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[89]  Paul A. Bates,et al.  Domain Fishing: a first step in protein comparative modelling , 2002, Bioinform..

[90]  Richard A Friesner,et al.  A novel fold recognition method using composite predicted secondary structures , 2002, Proteins.

[91]  Eckart Bindewald,et al.  A divide and conquer approach to fast loop modeling. , 2002, Protein engineering.

[92]  John L. Klepeis,et al.  Prediction of β‐sheet topology and disulfide bridges in polypeptides , 2003, J. Comput. Chem..

[93]  John L. Klepeis,et al.  A new class of hybrid global optimization algorithms for peptide structure prediction: integrated hybrids , 2003 .

[94]  J L Klepeis,et al.  Hybrid global optimization algorithms for protein structure prediction: alternating hybrids. , 2003, Biophysical journal.

[95]  John L. Klepeis,et al.  Ab initio Tertiary Structure Prediction of Proteins , 2003, J. Glob. Optim..

[96]  Adam Zemla,et al.  Critical assessment of methods of protein structure prediction (CASP)‐round V , 2005, Proteins.