Abstract B096: canSAR, a cancer research and drug discovery knowledgebase

Abstract

canSAR (http://cansar.icr.ac.uk) is a freely available, multidisciplinary, cancer-focused knowledgebase developed to bring together information from genomic, transcriptomic, protein, pathway, chemical, pharmacologic, and 3D structural data. canSAR provides a powerful, uniqu,e and user-friendly portal to enable translational research and to help generate and test hypotheses and support scientific decision-making in drug discovery both before and after target selection. With its three alternative approaches to examine druggability, canSAR represents the most comprehensive public druggability assessment resource. canSAR provides 3D-structure-based druggability assessment for more than 3,100,000 cavities on more than 391,000 protein chains; ligand-based druggability assessment for 8,197 human proteins; and, more recently, protein network-based druggability results for 13,345 human proteins. Together these provide a powerful enabler for target selection and validation for drug discovery. Druggability assessments are presented alongside data from resources including 224,000 clinical trials from ClinicalTrials.gov, drug indications from Cancer.gov, target gene expression from TCGA for cell lines, and patient samples to provide a detailed picture of the target’s biologic context. Recent updates to canSAR include integration of ChEMBL 23 and additional curation of a protein-protein interaction network of 13,500 nodes. canSAR is currently used by more than 65,000 users annually from both academia and industry, and we will illustrate how canSAR can empower decision making in translational drug discovery. Citation Format: Elizabeth A. Coker, Patrizio Di Micco, Joesph E. Tym, Costas Mitsopoulos, Angeliki Komianou, Albert A. Antolin, Bissan Al-Lazikani. canSAR, a cancer research and drug discovery knowledgebase [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr B096.

Protein modeling, molecular network and molecular dynamics study of newly sequenced interleukin‐18 (IL‐18) gene in Mus musculus

“…Further, by exploring the relationship between the network dynamics and structure of proteins, genes and other biomolecules, a deep insight into the biological and physiological processes can be achieved. Earlier, a large number of studies carried out in this context, reports the interaction of different genes and proteins and other gene networks, which lead to a target site for drug discovery (Cuadrado et al, 2018;Coker et al, 2018;Ryu, Kim, & Lee, 2018;Yadav & Tripathi, 2018).…”