Atlantis, a database that integrates structural and functional information at the human proteome residue level and a Model Context Protocol (MCP) connector allows the interrogation of the resource through Large Language Models (LLMs) or agentic frameworks for biomedical research.
Abstract
Understanding protein mechanisms in health and disease requires characterizing the functional roles of individual amino acid residues. To explore the role of residues and their mutations, we have developed Atlantis, a database that integrates structural and functional information at the human proteome residue level. A graph database enables complex queries and the retrieval of integrated information for multiple functional analysis of protein systems. A Model Context Protocol (MCP) connector allows the interrogation of the resource through Large Language Models (LLMs) or agentic frameworks for biomedical research. Atlantis annotates over 11M residues across 20k human proteins, identifying hundreds thousands intra- and inter-protein contacts in PDB as well as AlphaFoldDB structures. We also provide the possibility to analyze and integrate predicted 3D complexes inputted by the user, and we showcased these features on hundreds of AlphaFold-multimer complexes of GPCRs and LRRK2 interaction networks. The tool is freely accessible at https://atlantis.bioinfolab.sns.it/. GRAPHICAL ABSTRACT
Detailed protocols for using Protein Data Bank in Europe (PDBe) PISA API, a new Application Programming Interface (API) for enhanced analysis of protein assembly interfaces, using an updated version of PISA software are presented.
G. D. Leines, Paulyna Magana, S. Nair et al.· Current Protocols· 0 citations
Accurate identification of protein-protein interactions (PPIs) is fundamental for understanding cellular mechanisms and facilitating drug discovery. Although high-throughput experimental methods have expanded the known interactome, they remain resourceintensive and prone to noise. Consequently, computational approaches...
Pantelis Makrygiannis, Nikitas-Rigas Kalogeropoulos, Agorakis Bompotas et al.· International journal on art...· 0 citations
A revised release of the Unkown Mutation Analysis (XMAn) database is introduced by incorporating coding missense and nonsense mutations from the latest versions of the COSMIC Genome Screen Mutants and Cancer Gene Census datasets in two distinct FASTA-formatted peptide databases comprising 3,848,499 and 312,658 variants...
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Mechanistic understanding of viral protein-protein interactions enables global health security and pandemic preparedness, yet experimental characterisation remains difficult, costly, and often restricted to specialised laboratories. Here, we describe an in silico campaign using AlphaFold2 and AlphaFold-Multimer to pred...
Yew-On Han, Riya Narain, Razan Abbara et al.· bioRxiv· 0 citations
It is demonstrated that attention-based protein language models can accurately identify nucleic acid-binding proteins directly from sequence data and reveal biologically meaningful sequence determinants of binding, establishing an interpretable and scalable framework for proteome-wide characterization of protein–nuclei...
Hanjin Kim, Sung-Gwon Lee, Joo-Seong Oh et al.· Bioinformatics Advances· 0 citations
Abstract Summary The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is curr...
Lars Schimmelpfennig, M. Cannon, Quentin Cody et al.· Bioinformatics· 0 citations
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