Biophysical Society Thematic Meeting | Hamburg 2022

Biophysics at the Dawn of Exascale Computers

Tuesday Speaker Abstracts

SEARCHING CHEMICAL SPACE AND PROTEIN SPACE IN THE ERA OF ACCURATE PROTEIN STRUCTURE PREDICTION Chaok Seok 1,2 ; Jiho Sim 1 ; Sohee Kwon 1 ; Changsoo Lee 1 ; Jonghun Won 2 ; 1 Seoul National University, Department of Chemistry, Seoul, South Korea 2 Galux Inc, Seoul, South Korea Protein structure prediction has become highly accurate by the big sequence and structure data and the recent advances in deep learning techniques. The extensive repertoire of predicted protein structures provides a new opportunity for discovering new chemicals and proteins that regulate the physiological functions of proteins that were not explored by structure-based computations before. We have been developing tools for searching chemical space and protein space for such purposes. We have predicted small-molecule binding sites and corresponding chemicals for all proteins in the human proteome using a similarity-based docking method. We have also developed a technique for predicting putative binding proteins in human proteome and corresponding binding poses for a given chemical by combining similarity-based and ab initio prediction methods. However, more accurate methods for predicting protein-chemical and protein-protein interactions are necessary for more effective functional studies and drug discovery. We thus discuss our ongoing efforts to improve protein-chemical and protein-protein docking accuracy using machine-learned energy.

SERIAL DIFFRACTIVE IMAGING AND CRYSTALLOGRAPHY WITH INTENSE X-RAY SOURCES

Henry Chapman DESY, Germany No Abstract

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