Abstract 6239: Human computer interface guided approach to accelerate anticancer drug discovery: Application to human estrogen receptor interactome

Abstract

Abstract Structure-based drug discovery of target specific drugs greatly rely on the existence of high resolution X-ray crystal structure of the target proteins. Flexible and dynamic regions including hinges and loops which constitute major protein-protein interaction sites as well as allosteric sites are often beyond the scope of current tools and techniques available for protein folding and modeling. Human ability in recognizing patterns and to solve complex puzzles are far superior to any existing computer program at folding these atypical regions of proteins. We have utilized an unconventional combination of using dynamic three-dimensional protein models as physical human computer interface (HCI) devices and integrated proteomics data to predict flexible and dynamic protein-protein interfaces and allosteric pockets of key regulatory proteins to accelerate compound discovery. To this end, we have successfully utilized 1) Flexible HCI devices to generate an ensemble of dynamic three dimensional structures which includes a subset of biologically active conformations among others (thereby exploring the viable chemical space) and 2) Structure refinement and efficient filtering of biologically active conformations can be accomplished by integrating protein-protein interface and fold proteomics data. Here we present AI ready, HCI guided exploration of human estrogen receptor interactome and early in vitro confirmatory analyses. AI approachs to predict 3D protein structures from amino acid sequences like AlphaFold are often on par with experimentally generated structures and AI-guided structure prediction or docking approaches have been reported to significantly reduce computer time utilization. Streamlining of HCIguided tools to enable access to dynamic druggable pockets in protein targets will accelerate drug discovery. Citation Format: Rajendram V. Rajnarayanan, Aya Alsabagh. Human computer interface guided approach to accelerate anticancer drug discovery: Application to human estrogen receptor interactome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6239.