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A non-redundant dataset of inter-residue lysine-lysine solvent accessible surface distances in homo-oligomeric protein complexes.

ABSTRACT: This article contains inter-residue solvent accessible surface distances between lysines in a comprehensive dataset homo-oligomeric protein complex structures, downloaded from 3D Complex database. Solvent Accessible Surface Distances were calculated with Jwalk algorithm. To avoid unnecessary redundancy due to symmetry, we calculated only distances originating from the first subunit of each protein complex. Redundancy was further reduced by including only the shortest of the two possible inter-subunit alternatives in the final non-redundant dataset. For each protein complexes we also calculated weight ob subunits, number of lysines radius of gyration and average distances. This data can be used for structural analyses of homo-oligomeric protein complexes and for further optimization of distance-based restraints, such as those based on data obtained from chemical cross-linking coupled with mass spectrometry.

SUBMITTER: Gaber A

PROVIDER: S-EPMC6909155 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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A non-redundant dataset of inter-residue lysine-lysine solvent accessible surface distances in homo-oligomeric protein complexes.

Gaber Aljaž A

Data in brief 20191118

This article contains inter-residue solvent accessible surface distances between lysines in a comprehensive dataset homo-oligomeric protein complex structures, downloaded from 3D Complex database. Solvent Accessible Surface Distances were calculated with Jwalk algorithm. To avoid unnecessary redundancy due to symmetry, we calculated only distances originating from the first subunit of each protein complex. Redundancy was further reduced by including only the shortest of the two possible inter-su ...[more]

PMID: 31871982

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Project description:BackgroundProtein inter-residue contact maps provide a translation and rotation invariant topological representation of a protein. They can be used as an intermediary step in protein structure predictions. However, the prediction of contact maps represents an unbalanced problem as far fewer examples of contacts than non-contacts exist in a protein structure.In this study we explore the possibility of completely eliminating the unbalanced nature of the contact map prediction problem by predicting real-value distances between residues. Predicting full inter-residue distance maps and applying them in protein structure predictions has been relatively unexplored in the past.ResultsWe initially demonstrate that the use of native-like distance maps is able to reproduce 3D structures almost identical to the targets, giving an average RMSD of 0.5Å. In addition, the corrupted physical maps with an introduced random error of ±6Å are able to reconstruct the targets within an average RMSD of 2Å.After demonstrating the reconstruction potential of distance maps, we develop two classes of predictors using two-dimensional recursive neural networks: an ab initio predictor that relies only on the protein sequence and evolutionary information, and a template-based predictor in which additional structural homology information is provided. We find that the ab initio predictor is able to reproduce distances with an RMSD of 6Å, regardless of the evolutionary content provided. Furthermore, we show that the template-based predictor exploits both sequence and structure information even in cases of dubious homology and outperforms the best template hit with a clear margin of up to 3.7Å.Lastly, we demonstrate the ability of the two predictors to reconstruct the CASP9 targets shorter than 200 residues producing the results similar to the state of the machine learning art approach implemented in the Distill server.ConclusionsThe methodology presented here, if complemented by more complex reconstruction protocols, can represent a possible path to improve machine learning algorithms for 3D protein structure prediction. Moreover, it can be used as an intermediary step in protein structure predictions either on its own or complemented by NMR restraints.

Project description:BackgroundInversion Symmetry is a generalization of the second Chargaff rule, stating that the count of a string of k nucleotides on a single chromosomal strand equals the count of its inverse (reverse-complement) k-mer. It holds for many species, both eukaryotes and prokaryotes, for ranges of k which may vary from 7 to 10 as chromosomal lengths vary from 2Mbp to 200 Mbp. Building on this formalism we introduce the concept of k-mer distances between chromosomes. We formulate two k-mer distance measures, D1 and D2, which depend on k. D1 takes into account all k-mers (for a single k) appearing on single strands of the two compared chromosomes, whereas D2 takes into account both strands of each chromosome. Both measures reflect dissimilarities in global chromosomal structures.ResultsAfter defining the various distance measures and summarizing their properties, we also define proximities that rely on the existence of synteny blocks between chromosomes of different bacterial strains. Comparing pairs of strains of bacteria, we find negative correlations between synteny proximities and k-mer distances, thus establishing the meaning of the latter as measures of evolutionary distances among bacterial strains. The synteny measures we use are appropriate for closely related bacterial strains, where considerable sections of chromosomes demonstrate high direct or reversed equality. These measures are not appropriate for comparing different bacteria or eukaryotes. K-mer structural distances can be defined for all species. Because of the arbitrariness of strand choices, we employ only the D2 measure when comparing chromosomes of different species. The results for comparisons of various eukaryotes display interesting behavior which is partially consistent with conventional understanding of evolutionary genomics. In particular, we define ratios of minimal k-mer distances (KDR) between unmasked and masked chromosomes of two species, which correlate with both short and long evolutionary scales.Conclusionsk-mer distances reflect dissimilarities among global chromosomal structures. They carry information which aggregates all mutations. As such they can complement traditional evolution studies , which mainly concentrate on coding regions.

Dataset Information

A non-redundant dataset of inter-residue lysine-lysine solvent accessible surface distances in homo-oligomeric protein complexes.

Publications

A non-redundant dataset of inter-residue lysine-lysine solvent accessible surface distances in homo-oligomeric protein complexes.

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