Dataset Information

Bioinformatics Approaches to Predict Mutation Effects in the Binding Site of the Proangiogenic Molecule CD93.

ABSTRACT: The transmembrane glycoprotein CD93 has been identified as a potential new target to inhibit tumor angiogenesis. Recently, Multimerin-2 (MMRN2), a pan-endothelial extracellular matrix protein, has been identified as a ligand for CD93, but the interaction mechanism between these two proteins is yet to be studied. In this article, we aim to investigate the structural and functional effects of induced mutations on the binding domain of CD93 to MMRN2. Starting from experimental data, we assessed how specific mutations in the C-type lectin-like domain (CTLD) affect the binding interaction profile. We described a four-step workflow in order to predict the effects of variations on the inter-residue interaction network at the PPI, based on evolutionary information, complex network metrics, and energetic affinity. We showed that the application of computational approaches, combined with experimental data, allowed us to gain more in-depth molecular insights into the CD93-MMRN2 interaction, offering a platform for developing innovative therapeutics able to target these molecules and block their interaction. This comprehensive molecular insight might prove useful in drug design in cancer therapy.

SUBMITTER: Cicaloni V

PROVIDER: S-EPMC9638713 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Bioinformatics Approaches to Predict Mutation Effects in the Binding Site of the Proangiogenic Molecule CD93.

Cicaloni Vittoria V Karmakar Malancha M Frusciante Luisa L Pettini Francesco F Visibelli Anna A Orlandini Maurizio M Galvagni Federico F Mongiat Maurizio M Silk Michael M Nardi Federica F Ascher David D Santucci Annalisa A Spiga Ottavia O

Frontiers in bioinformatics 20220621

The transmembrane glycoprotein CD93 has been identified as a potential new target to inhibit tumor angiogenesis. Recently, Multimerin-2 (MMRN2), a pan-endothelial extracellular matrix protein, has been identified as a ligand for CD93, but the interaction mechanism between these two proteins is yet to be studied. In this article, we aim to investigate the structural and functional effects of induced mutations on the binding domain of CD93 to MMRN2. Starting from experimental data, we assessed how ...[more]

PMID: 36353214

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Project description:BackgroundAccurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites.DescriptionUsing a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST) algorithm. SMID records are available for viewing at http://smid.blueprint.org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60%) of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives.ConclusionBy focusing on protein domain-small molecule interactions, SMID is able to cluster similar interactions and detect subtle binding patterns that would not otherwise be obvious. Using SMID-BLAST, small molecule targets can be predicted for any protein sequence, with the only limitation being that the small molecule must exist in the PDB. Validation results and specific examples within illustrate that SMID-BLAST has a high degree of accuracy in terms of predicting both the small molecule ligand and binding site residue positions for a query protein.

Dataset Information

Bioinformatics Approaches to Predict Mutation Effects in the Binding Site of the Proangiogenic Molecule CD93.

Publications

Bioinformatics Approaches to Predict Mutation Effects in the Binding Site of the Proangiogenic Molecule CD93.

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