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AI3SD Video: The “almost druggable” genome

AI3SD Video: The “almost druggable” genome
AI3SD Video: The “almost druggable” genome
This talk will briefly introduce the “Illuminating the Druggable Genome” knowledge management center, with focus on its protein-centric data aggregator, Pharos (https://pharos.nih.gov/), and the DrugCentral online pharmaceutical compendium (https://drugcentral.org/). Using Pharos/DrugCentral data, we then examine the question, “what proteins that could potentially be ligandable, are currently not?”, in a disease context. To do this, we examine proteins available in the RSCB PDB (https://www.rcsb.org/) – the “PDB-ome” => 347 proteins that lack known ligands; Proteins for which chemical matter is known, N=2644 – the “SAR-ome” => of these, 115 proteins meet the “ligandable” criteria; the “Pocket-ome”, i.e., proteins that have a close – by sequence identity – homologue with known 3D structure, which leads to ~700 ligandable proteins with PDB structures; 180 that have close homologues but lack 3D structures; and N=2623 proteins that could be modeled with reasonable confidence; last but not least, the “Phen-ome”, which looks at this entire list (N = 6742) from the perspective of rare and common diseases, GWAS and mouse phenotype data, etc, and narrows down the previous lists. The “almost druggable genome” contains 715 ligandable (3D exists) proteins, 180 proteins for which chemical matter is likely to be found, and at least 100 proteins that could be subject to chemical probe optimization.
AI, AI3SD Event, Artificial Intelligence, Machine Intelligence, Machine Learning, ML, Proteins
Oprea, Tudor
78c05477-e2d0-4199-9520-316b0cbcf32a
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Oprea, Tudor
78c05477-e2d0-4199-9520-316b0cbcf32a
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420

Oprea, Tudor (2021) AI3SD Video: The “almost druggable” genome. Frey, Jeremy G., Niranjan, Mahesan and Kanza, Samantha (eds.) AI 4 Proteins Seminar Series 2021. 14 Apr - 17 Jun 2021. (doi:10.5258/SOTON/P0105).

Record type: Conference or Workshop Item (Other)

Abstract

This talk will briefly introduce the “Illuminating the Druggable Genome” knowledge management center, with focus on its protein-centric data aggregator, Pharos (https://pharos.nih.gov/), and the DrugCentral online pharmaceutical compendium (https://drugcentral.org/). Using Pharos/DrugCentral data, we then examine the question, “what proteins that could potentially be ligandable, are currently not?”, in a disease context. To do this, we examine proteins available in the RSCB PDB (https://www.rcsb.org/) – the “PDB-ome” => 347 proteins that lack known ligands; Proteins for which chemical matter is known, N=2644 – the “SAR-ome” => of these, 115 proteins meet the “ligandable” criteria; the “Pocket-ome”, i.e., proteins that have a close – by sequence identity – homologue with known 3D structure, which leads to ~700 ligandable proteins with PDB structures; 180 that have close homologues but lack 3D structures; and N=2623 proteins that could be modeled with reasonable confidence; last but not least, the “Phen-ome”, which looks at this entire list (N = 6742) from the perspective of rare and common diseases, GWAS and mouse phenotype data, etc, and narrows down the previous lists. The “almost druggable genome” contains 715 ligandable (3D exists) proteins, 180 proteins for which chemical matter is likely to be found, and at least 100 proteins that could be subject to chemical probe optimization.

Video
AI4Proteins-Seminar-Series-TudorOprea-170621 - Version of Record
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More information

Published date: 17 June 2021
Additional Information: Tudor Oprea is Professor and Chief, Translational Informatics Division, Department of Internal Medicine, UNM School of Medicine, Albuquerque, New Mexico (USA); and Guest Professor at the universities of Gothenburg (Sweden) and Copenhagen (Denmark). He holds an MD PhD from the University of Medicine and Pharmacy, Timişoara, Romania. Dr. Oprea co-authored over 260 publications, 10 US patents, and edited 2 books on drug discovery. His current research is to develop validated artificial intelligence models for target selection in drug discovery by combining numerical and text-mined information to model human health. Oprea serves as PI for the Illuminating the Druggable Genome Knowledge Management Center.
Venue - Dates: AI 4 Proteins Seminar Series 2021, 2021-04-14 - 2021-06-17
Keywords: AI, AI3SD Event, Artificial Intelligence, Machine Intelligence, Machine Learning, ML, Proteins

Identifiers

Local EPrints ID: 450167
URI: http://eprints.soton.ac.uk/id/eprint/450167
PURE UUID: 4ea2a863-4d8b-46cd-8aec-de399a8a813e
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489

Catalogue record

Date deposited: 14 Jul 2021 16:45
Last modified: 28 Jul 2021 01:54

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