Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores

Abstract

As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for co-evolution between pairs of positions. Co-evolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of co-evolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded co-evolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; “central” positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise co-evolution scores: Instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints – detectable by divergent algorithms – that occur at key protein locations. Finally, we discuss the fact that multiple patterns co-exist in evolutionary data that, together, give rise to emergent protein functions.

Using Evolution to Guide Protein Engineering: The Devil IS in the Details

“…For example, in a comparison of two sets of scores, Jaccard analyses can quantify the similarities across all possible thresholds (18). A second approach is to defer thresholding until the final step in the analysis, which prevents the loss of top positions that only emerge from downstream calculations (7).…”

“…Some studies use all 20 a.a. to calculate sequence entropy, whereas others group a.a. by chemically similar side chains. Our studies used all 20 a.a. and a stringent value for sequence entropy to define conserved positions (7,18,19); this context is used in this Biophysical Perspective. Second, conservation can be identified via the use of a.a. substitution matrices (e.g., BLOSUM-62 (20)).…”

“…The relationships among evolution, biophysics, and structure were recently reviewed (6). In parallel, dozens of computer algorithms have been developed to analyze amino acid (a.a.) changes in protein sequence alignments, with the rationale that nonrandom patterns of change reflect evolutionary constraints at important positions (7)(8)(9)(10)(11)(12)(13)(14)(15)(16). One class of algorithms identifies positions for which a.a. changes correlate with phylogeny.…”

AlloRep: A Repository of Sequence, Structural and Mutagenesis Data for the LacI/GalR Transcription Regulators

“…In addition to providing information about family-wide properties, this table can be used to convert the numbering of each subfamily alignment into that of the family alignment, using the program MARS-Prot (https://github.com/djparente/MARS) [24]. The alignments for each subfamily are stored as rows in the table “seq2_subfam_alignments” (Figure 1 in [22]).…”

“…For the subfamilies represented by the new PSI pdb structures, a structure-based reference alignment was constructed with PROMALS3D [44] and integrated into the whole family alignment with the program MARS-Prot (https://github.com/djparente/MARS) [24]. For all new homologs, subfamily alignments were constructed using MUSCLE [45] and representative sequences were integrated into the whole family alignment with MARS-Prot.…”