Methods of protein structure comparison
By Irina Kufareva, Ruben Abagyan. Methods in molecular biology, 2012
592 citations recorded by the source corpus.
Despite its apparent simplicity, the problem of quantifying the differences between two structures of the same protein or complex is non-trivial and continues evolving. In this chapter, we described several methods routinely used to compare computational models to experimental answers in several modeling assessments. The two major classes of measures, positional distance-based and contact-based, were presented, compared and analyzed. The most popular measure of the first class, the global RMSD, is shown to be the least representative of the degree of structural similarity because it is dominated by the largest error. Several distance-dependent algorithms designed to attenuate the drawbacks of RMSD are described. Measures of the second class, contact-based, are shown to be more robust and relevant. We also illustrate the importance of using combined measures, utility-based measures, and the role of the distributions derived from the pairs of experimental structures in interpreting the results.
Subfields: Computational Theory and Mathematics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/6dc4c92296f166f2cc8942f032c56c1b025d8a6b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
In Molecular Biology
Citations in the corpus
- Common activation mechanism of class A GPCRs (2019, background): “…is calculated by summing up a plateau-linear-plateau form atomic contact score adopted from GPCR–CoINPocket (Ngo et al., 2017; Kufareva et al., 2011; Kufareva and Abagyan, 2012; Kufareva et al., 2014a; Kufareva et al., 2013; Kufareva et al., 2014b; Marsden and Abagyan, 2004) for each…”