CoeViz 2: Protein Graphs Derived From Amino Acid Covariance

Abstract

Proteins by and large carry out their molecular functions in a folded state when residues, distant in sequence, assemble together in 3D space to bind a ligand, catalyze a reaction, form a channel, or exert another concerted macromolecular interaction. It has been long recognized that covariance of amino acids between distant positions within a protein sequence allows for the inference of long range contacts to facilitate 3D structure modeling. In this work, we investigated whether covariance analysis may reveal residues involved in the same molecular function. Building upon our previous work, CoeViz, we have conducted a large scale covariance analysis among 7,595 non-redundant proteins with resolved 3D structures to assess 1) whether the residues with the same function coevolve, 2) which covariance metric captures such couplings better, and 3) how different molecular functions compare in this context. We found that the chi-squared metric is the most informative for the identification of coevolving functional sites, followed by the Pearson correlation-based, whereas mutual information is the least informative. Of the seven categories of the most common natural ligands, including coenzyme A, dinucleotide, DNA/RNA, heme, metal, nucleoside, and sugar, the trace metal binding residues display the most prominent coupling, followed by the sugar binding sites. We also developed a web-based tool, CoeViz 2, that enables the interactive visualization of covarying residues as cliques from a larger protein graph. CoeViz 2 is publicly available at https://research.cchmc.org/CoevLab/.

Hydrophobicity-Driven Increases in Editing in Mitochondrial mRNAs during the Evolution of Kinetoplastids

“…Prediction of the protein structure was made using the RoseTTAFold server ( https://robetta.bakerlab.org/submit.php ) ( Baek et al 2021 ), and the structure was drawn with the software ChimeraX v1.2.5 ( Pettersen et al 2021 ). Coevolving sites were analyzed by using CoeViz2 ( Corcoran et al 2021 ) with a 20-amino acid alphabet, and the Uniprot-Uniref90 database to build the multiple sequence alignment. Surface-exposed amino acids in the above structures and in protein structures of the complex I downloaded from NCBI Protein (accession: 5XTD) were calculated by determining the SASA using the server of the Center for Informational Biology ( http://cib.cf.ocha.ac.jp/bitool/ASA/ ).…”

Structural and Evolutionary Adaptations of Nei-Like DNA Glycosylases Proteins Involved in Base Excision Repair of Oxidative DNA Damage in Vertebrates

“…The CoeViz 2, a web-based program [ 43 ], was used to conduct a targeted and quick assessment of protein features, such as structural and functional regions, and give a variable analysis and visual representations of paired coevolution of amino acids. We used CoeViz analysis with two covariance metrics [ 44 ] to obtain the complete protein sequences of the proteins NEIL1, NEIL2, and NEIL3, which were used for phylogenetic analysis to assess the positions of covarying sites and large coincides with domains of the protein and used circular visuals for the understanding of residue interactions.…”

Covalent drugs targeting histidine – an unexploited opportunity?

“…19 One reason for this is that the p K a range of histidine often translates to the residue acting either as a proton acceptor or donor in its catalytic mechanisms. Additionally, histidine is far more frequently represented in DNA/RNA binding sites than cysteine for example 20 and it regularly acts as a catalytic nucleophile for phosphates. 19…”

“…19 One reason for this is that the pK a range of histidine often translates to the residue acting either as a proton acceptor or donor in its catalytic mechanisms. Additionally, histidine is far more frequently represented in DNA/RNA binding sites than cysteine for example 20 and it regularly acts as a catalytic nucleophile for phosphates. 19 Importantly, histidine has a low surface frequency compared to other amino acids 6,18 and has one of the highest preferences to be within 4.5 Å of drugs and drug-like compounds in binding sites, as determined by an analysis of protein structures in the PDB.…”