Discrimination between Distant Homologs and Structural Analogs: Lessons from Manually Constructed, Reliable Data Sets

Abstract

A natural way to study protein sequence, structure, and function is to put them in the context of evolution. Homologs inherit similarities from their common ancestor, while analogs converge to similar structures due to a limited number of energetically favorable ways to pack secondary structural elements. Using novel strategies, we previously assembled two reliable databases of homologs and analogs. In this study, we compare these two data sets and develop a support vector machine (SVM)-based classifier to discriminate between homologs and analogs. The classifier uses a number of well-known similarity scores. We observe that although both structure scores and sequence scores contribute to SVM performance, profile sequence scores computed based on structural alignments are the best discriminators between remote homologs and structural analogs. We apply our classifier to a representative set from the expert-constructed database, Structural Classification of Proteins (SCOP). The SVM classifier recovers 76% of the remote homologs defined as domains in the same SCOP superfamily but from different families. More importantly, we also detect and discuss interesting homologous relationships between SCOP domains from different superfamilies, folds, and even classes.

Exploration of Uncharted Regions of the Protein Universe

“…In agreement with trends described in a recent paper [36], the number of corresponding residues in the structural alignments between DUF structures assigned as putative analogs with their potential homologs tend to be smaller and the corresponding C α RMSD values of these pairs tend to be higher than the values for the other two categories of proteins assigned as putative homologs and recognizable homologs (see Figure 3C). However, the profiles of structural similarities in these three groups are very similar, suggesting that most proteins from the group of putative analogs may be, in fact, distant, but not readily recognizable, homologs of previously characterized protein families.…”

Protein structure determination by exhaustive search of Protein Data Bank derived databases

“…Our results suggest that the limit of sequence identity for successful WS-MR search is low enough to allow our method to extend to models that would otherwise be missed by methods that are based on sequence alignment for template selection (29). Both remote homologues and structural analogs (30) can be detected by WS-MR, with specific examples where models with an identity of 11.6% and an RMSD under 3 Å can be correctly placed and distinguished from negative results. We also show that low completeness with structure coverage of as little as 12% can be sufficient for good WS-MR template models, however in these cases high sequence identity and structural similarity for the covered area are required.…”

Protein structure alignment beyond spatial proximity

“…MALISAM contains 130 protein pairs and the two proteins in any pair are structural analogs with different SCOP37 folds. There is strong evidence indicating that proteins in a MALIDUP pair are not homologs38. Therefore, MALIDUP are the most challenging benchmark among these three.…”