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PepI-Covid19 is free, web-interface, repository of peptides to target the interaction between human ACE2 and the RBD of the Spike protein of SARS-CoV-2. Since the start of the COVID-19 pandemic, several structures of protein complexes involving ACE2 and RBD as well as monoclonal antibodies and nanobodies have become available. We have leveraged the structural data to design peptides to target the interaction between the RBD of SARS-CoV-2 and ACE2 and SARS-CoV and ACE2, as contrasting exemplar, as well as the dimerization surface of ACE2 monomers. The peptides were modelled using our original method: PiPreD that uses native elements of the interaction between the targeted protein and cognate partner(s) that are subsequently included in the designed peptides. These peptides recapitulate stretches of residues present in the native interface plus novel and highly diverse conformations surrogating key interactions at the interface.

CM2D3 is database containing structural models of the whole human interactome derived both from comparative modeling and data-driven docking. Starting from a consensus interactome derived from integrating several interactomics databases, a strategy was devised to derive structural models by computational means. Currently, CM2D3 includes 33338 structural models of which 5121 derived from comparative modeling and the remaining from docking. Of the latter, the structures of 14554 complexes were derived from monomers modeled by M4T while the rest were modeled with structures as predicted by AlphaFold2.

T-ARDIS (Target-Adverse Reaction Database Integrated Search) database is a resource that provides comprehensive information on proteins and associated ADRs. By combining the information from drug-protein and drug-ADR databases, we statistically identify significant associations between proteins and ADRs. Besides describing the relationship between proteins and ADRs, T-ARDIS provides detailed description about proteins along with the drug and adverse reaction information. Currently T-ARDIS contains over 3000 ADR and 248 targets for a total of more 17 000 pairwise interactions.

CAPS-DB CAPS-DB is a structural classification of helix capping motifs or CAPS compiled from protein structures. Nt and Ct capping motifs have been grouped into structural clusters using a computational method designed to this purpose. Briefly, caps were structurally clustered by using geometrical descriptors and comparing of the main chain phi/psi angles. The RMSD (Root Mean Square Deviation) of C-alpha atoms was used to assess the quality of the clusters. Clusters are organized into a fully browsable tree-like hierarchical model that includes the type of capping (Nt or Ct), geometry and conformation.

PCRPi-DB is a repository of annotated hot spots in protein interfaces using PCRPi , a computational method designed to predict critical or hot spot residues in protein interfaces by combining structural, evolutionary and energy-based information. Hot spots have been annotated in any protein complexes for which the 3D-structure is known, are deposited in the PDB databank, and are solved with a crystal resolution better than 3 Ang. PCRPi-DB is weekly updated.

ArchDB is a compilation of structural classifications of loops extracted from protein structures. Currently, ArchDB contains more than 100,000 loops classified into more than 10,000 subclasses. ArchDB have been successfully applied in structure prediction of loops and functional annotation of proteins. The database provides an easy way to retrieve functional information from protein structures sharing a common motif, to search motifs found in a given SCOP family, superfamily or fold, search for templates to model loop structures, and search for functional loops.