title: SIDEpro: a novel machine learning approach for the fast and accurate prediction of side-chain conformations.
abstract: Accurate protein side-chain conformation prediction is crucial for protein modeling and existing methods for the task are widely used; however, faster and more accurate methods are still required. Here we present a new machine learning approach to the problem where an energy function for each rotamer in a structure is computed additively over pairs of contacting atoms. A family of 156 neural networks indexed by amino acid and contacting atom types is used to compute these rotamer energies as a function of atomic contact distances. Although direct energy targets are not available for training, the neural networks can still be optimized by converting the energies to probabilities and optimizing these probabilities using Markov Chain Monte Carlo methods. The resulting predictor SIDEpro makes predictions by initially setting the rotamer probabilities for each residue from a backbone-dependent rotamer library, then iteratively updating these probabilities using the trained neural networks. After convergences of the probabilities, the side-chains are set to the highest probability rotamer. Finally, a post processing clash reduction step is applied to the models. SIDEpro represents a significant improvement in speed and a modest, but statistically significant, improvement in accuracy when compared with the state-of-the-art for rapid side-chain prediction method SCWRL4 on the following datasets: (1) 379 protein test set of SCWRL4; (2) 94 proteins from CASP9; (3) a set of seven large protein-only complexes; and (4) a ribosome with and without the RNA. Using the SCWRL4 test set, SIDEpro's accuracy (χ(1) 86.14%, χ(1+2) 74.15%) is slightly better than SCWRL4-FRM (χ(1) 85.43%, χ(1+2) 73.47%) and it is 7.0 times faster. On the same test set SIDEpro is clearly more accurate than SCWRL4-rigid rotamer model (RRM) (χ(1) 84.15%, χ(1+2) 71.24%) and 2.4 times faster. Evaluation on the additional test sets yield similar accuracy results with SIDEpro being slightly more accurate than SCWRL4-flexible rotamer model (FRM) and clearly more accurate than SCWRL4-RRM; however, the gap in CPU time is much more significant when the methods are applied to large protein complexes. SIDEpro is part of the SCRATCH suite of predictors and available from: http://scratch.proteomics.ics.uci.edu/.
authors.affiliation: Department of Computer Science, University of California, Irvine, California, USA.
authors.forename: Ken
authors.initials: K
authors.lastname: Nagata
authors.forename: Arlo
authors.initials: A
authors.lastname: Randall
authors.forename: Pierre
authors.initials: P
authors.lastname: Baldi
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D001185:Artificial Intelligence; D053453:Caspase 9 / Q000737:chemistry; D003198:Computer Simulation; D008958:Models, Molecular; D017433:Protein Structure, Secondary; D012270:Ribosomes / Q000737:chemistry; D012984:Software
chemical_list: D000596:Amino Acids; D053453:Caspase 9
references.citation: Protein Sci. 1997 Aug;6(8):1661-81
references.pmid: 9260279
references.citation: Biophys J. 1994 May;66(5):1335-40
references.pmid: 8061189
references.citation: Biopolymers. 1999 Aug;50(2):111-31
references.pmid: 10380336
references.citation: Bioinformatics. 2005 Apr 1;21(7):1028-36
references.pmid: 15546935
references.citation: Proteins. 2009 Dec;77(4):778-95
references.pmid: 19603484
references.citation: Proteins. 2007 Mar 1;66(4):814-23
references.pmid: 17206724
references.citation: Proteins. 2008 Nov 1;73(2):271-89
references.pmid: 18655061
references.citation: J Mol Biol. 1993 Mar 20;230(2):543-74
references.pmid: 8464064
references.citation: Protein Sci. 2008 Sep;17(9):1576-85
references.pmid: 18556476
references.citation: J Mol Biol. 2001 Aug 10;311(2):421-30
references.pmid: 11478870
references.citation: Protein Sci. 2002 Feb;11(2):322-31
references.pmid: 11790842
references.citation: Curr Opin Struct Biol. 2002 Aug;12(4):431-40
references.pmid: 12163064
references.citation: Protein Sci. 2003 Sep;12(9):2001-14
references.pmid: 12930999
references.citation: Proteins. 1999 Jan 1;34(1):82-95
references.pmid: 10336385
references.citation: Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W72-6
references.pmid: 15980571
references.citation: J Mol Biol. 1997 Apr 18;267(5):1268-82
references.pmid: 9150411
references.citation: Acta Crystallogr D Biol Crystallogr. 2002 Jun;58(Pt 6  No 1):899-907
references.pmid: 12037327
references.citation: Biophys J. 2003 Aug;85(2):1145-64
references.pmid: 12885659
references.citation: Proteins. 2004 May 15;55(3):656-77
references.pmid: 15103629
references.citation: Nat Struct Biol. 1994 May;1(5):334-40
references.pmid: 7664040
references.citation: J Comput Chem. 2004 Apr 15;25(5):712-24
references.pmid: 14978714
references.citation: J Mol Biol. 1994 Jun 3;239(2):249-75
references.pmid: 8196057
references.citation: J Mol Biol. 2003 Aug 1;331(1):281-99
references.pmid: 12875852