Editing Protein structure prediction (section)

===Modeling of side-chain conformations===
Accurate packing of the amino acid [[side chain]]s represents a separate problem in protein structure prediction. Methods that specifically address the problem of predicting side-chain geometry include [[dead-end elimination]] and the [[self-consistent mean field (biology)|self-consistent mean field]] methods. The side chain conformations with low energy are usually determined on the rigid polypeptide backbone and using a set of discrete side chain conformations known as "[[rotamer]]s". The methods attempt to identify the set of rotamers that minimize the model's overall energy.

These methods use rotamer libraries, which are collections of favorable conformations for each residue type in proteins. Rotamer libraries may contain information about the conformation, its frequency, and the standard deviations about mean dihedral angles, which can be used in sampling.<ref name="Rotamers21stCentury">{{cite journal |vauthors=Dunbrack RL |title=Rotamer libraries in the 21st century |journal=Current Opinion in Structural Biology |volume=12 |issue=4 |pages=431–40 |date=August 2002 |pmid=12163064 |doi=10.1016/S0959-440X(02)00344-5}}</ref> Rotamer libraries are derived from [[structural bioinformatics]] or other statistical analysis of side-chain conformations in known experimental structures of proteins, such as by clustering the observed conformations for tetrahedral carbons near the staggered (60°, 180°, −60°) values.

Rotamer libraries can be backbone-independent, secondary-structure-dependent, or backbone-dependent. Backbone-independent rotamer libraries make no reference to backbone conformation, and are calculated from all available side chains of a certain type (for instance, the first example of a rotamer library, done by Ponder and [[Frederic M. Richards|Richards]] at Yale in 1987).<ref>{{cite journal |vauthors=Ponder JW, Richards FM |title=Tertiary templates for proteins. Use of packing criteria in the enumeration of allowed sequences for different structural classes |journal=Journal of Molecular Biology |volume=193 |issue=4 |pages=775–91 |date=February 1987 |pmid=2441069 |doi=10.1016/0022-2836(87)90358-5}}</ref> Secondary-structure-dependent libraries present different dihedral angles and/or rotamer frequencies for <math>\alpha</math>-helix, <math>\beta</math>-sheet, or coil secondary structures.<ref>{{cite journal |vauthors=Lovell SC, Word JM, Richardson JS, Richardson DC |title=The penultimate rotamer library |journal=Proteins |volume=40 |issue=3 |pages=389–408 |date=August 2000 |pmid=10861930 |doi=10.1002/1097-0134(20000815)40:3<389::AID-PROT50>3.0.CO;2-2 |s2cid=3055173}}</ref> [[Backbone-dependent rotamer library|Backbone-dependent rotamer libraries]] present conformations and/or frequencies dependent on the local backbone conformation as defined by the backbone dihedral angles <math>\phi</math> and <math>\psi</math>, regardless of secondary structure.<ref name="bbdep2010">{{cite journal |vauthors=Shapovalov MV, Dunbrack RL |title=A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions |journal=Structure |volume=19 |issue=6 |pages=844–58 |date=June 2011 |pmid=21645855 |pmc=3118414 |doi=10.1016/j.str.2011.03.019}}</ref>

The modern versions of these libraries as used in most software are presented as multidimensional distributions of probability or frequency, where the peaks correspond to the dihedral-angle conformations considered as individual rotamers in the lists. Some versions are based on very carefully curated data and are used primarily for structure validation,<ref>{{cite journal |vauthors=Chen VB, Arendall WB, Headd JJ, Keedy DA, Immormino RM, Kapral GJ, Murray LW, Richardson JS, Richardson DC |title=MolProbity: all-atom structure validation for macromolecular crystallography |journal=Acta Crystallographica. Section D, Biological Crystallography |volume=66 |issue=Pt 1 |pages=12–21 |date=January 2010 |pmid=20057044 |pmc=2803126 |doi=10.1107/S0907444909042073|bibcode=2010AcCrD..66...12C }}</ref> while others emphasize relative frequencies in much larger data sets and are the form used primarily for structure prediction, such as the [[Backbone-dependent rotamer library|Dunbrack rotamer libraries]].<ref>{{cite journal |vauthors=Bower MJ, Cohen FE, Dunbrack RL |title=Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool |journal=Journal of Molecular Biology |volume=267 |issue=5 |pages=1268–82 |date=April 1997 |pmid=9150411 |doi=10.1006/jmbi.1997.0926}}</ref>

Side-chain packing methods are most useful for analyzing the protein's [[hydrophobic]] core, where side chains are more closely packed; they have more difficulty addressing the looser constraints and higher flexibility of surface residues, which often occupy multiple rotamer conformations rather than just one.<ref name="voigt2000">{{cite journal |vauthors=Voigt CA, Gordon DB, Mayo SL |title=Trading accuracy for speed: A quantitative comparison of search algorithms in protein sequence design |journal=Journal of Molecular Biology |volume=299 |issue=3 |pages=789–803 |date=June 2000 |pmid=10835284 |doi=10.1006/jmbi.2000.3758 |citeseerx=10.1.1.138.2023}}</ref><ref name="scwrl4">{{cite journal |vauthors=Krivov GG, Shapovalov MV, Dunbrack RL |title=Improved prediction of protein side-chain conformations with SCWRL4 |journal=Proteins |volume=77 |issue=4 |pages=778–95 |date=December 2009 |pmid=19603484 |pmc=2885146 |doi=10.1002/prot.22488}}</ref>