Editing Protein structure prediction (section)

===Comparative protein modeling===

Comparative protein modeling uses previously solved structures as starting points, or templates. This is effective because it appears that although the number of actual proteins is vast, there is a limited set of [[tertiary structure|tertiary]] [[structural motif]]s to which most proteins belong. It has been suggested that there are only around 2,000 distinct protein folds in nature, though there are many millions of different proteins. The comparative protein modeling can combine with the evolutionary covariation in the structure prediction.<ref>{{cite journal |last1=Jin |first1=Shikai |last2=Chen |first2=Mingchen |last3=Chen |first3=Xun |last4=Bueno |first4=Carlos |last5=Lu |first5=Wei |last6=Schafer |first6=Nicholas P. |last7=Lin |first7=Xingcheng |last8=Onuchic |first8=José N. |last9=Wolynes |first9=Peter G. |title=Protein Structure Prediction in CASP13 Using AWSEM-Suite |journal=Journal of Chemical Theory and Computation |date=9 June 2020 |volume=16 |issue=6 |pages=3977–3988 |doi=10.1021/acs.jctc.0c00188|pmid=32396727 |s2cid=218618842}}</ref>

These methods may also be split into two groups:<ref name="zhang2008"/>
* [[Homology modeling]] is based on the reasonable assumption that two [[Homology (biology)#Homology of sequences in genetics|homologous]] proteins will share very similar structures. Because a protein's fold is more evolutionarily conserved than its amino acid sequence, a target sequence can be modeled with reasonable accuracy on a very distantly related template, provided that the relationship between target and template can be discerned through [[sequence alignment]]. It has been suggested that the primary bottleneck in comparative modelling arises from difficulties in alignment rather than from errors in structure prediction given a known-good alignment.<ref name="zhang2005">{{cite journal |vauthors=Zhang Y, Skolnick J |title=The protein structure prediction problem could be solved using the current PDB library |journal=Proceedings of the National Academy of Sciences of the United States of America |volume=102 |issue=4 |pages=1029–34 |date=January 2005 |pmid=15653774 |pmc=545829 |doi=10.1073/pnas.0407152101 |bibcode=2005PNAS..102.1029Z |doi-access=free}}</ref> Unsurprisingly, homology modelling is most accurate when the target and template have similar sequences.
* [[Threading (protein sequence)|Protein threading]]<ref name="bowie1991">{{cite journal |vauthors=Bowie JU, Lüthy R, Eisenberg D |title=A method to identify protein sequences that fold into a known three-dimensional structure |journal=Science |volume=253 |issue=5016 |pages=164–70 |date=July 1991 |pmid=1853201 |doi=10.1126/science.1853201 |bibcode=1991Sci...253..164B}}</ref> scans the amino acid sequence of an unknown structure against a database of solved structures. In each case, a [[Statistical potential|scoring function]] is used to assess the compatibility of the sequence to the structure, thus yielding possible three-dimensional models. This type of method is also known as '''3D-1D fold recognition''' due to its compatibility analysis between three-dimensional structures and linear protein sequences. This method has also given rise to methods performing an '''inverse folding search''' by evaluating the compatibility of a given structure with a large database of sequences, thus predicting which sequences have the potential to produce a given fold.