AI4Proteins: Protein-Ligand Structure Prediction for GPCR Drug Design – Dr Chris De Graaf скачать в хорошем качестве

AI4Proteins: Protein-Ligand Structure Prediction for GPCR Drug Design – Dr Chris De Graaf

This seminar forms part of the AI3SD and RSC-CICAG AI4Proteins Series. This series is sponsored by Arctoris and Schrödinger. This video is the sixth talk in the Protein Structure Prediction Conference. Protein-Ligand Structure Prediction for GPCR Drug Design – Dr Chris De Graaf Abstract From GPCR Structure Prediction to Structural GPCR-Ligand Interaction Prediction – The conserved TM helical fold of G Protein-Coupled Receptors (GPCRs) and progress in GPCR structural biology continues to provide homology modeling templates for protein structure prediction. – Novel structures of GPCR-ligand complexes solved at Sosei Heptares and elsewhere continue to reveal a diversity of protein-ligand binding sites and binding modes that are challenging to predict. Appreciating the Devil’s in the Details of Structure-Based GPCR Drug Design – Novel structural insights into the GPCRome can be complemented by pharmacological, biophysical, and computational studies and data to identify and predict structural determinants of ligand-receptor binding and selectivity. – Orthogonal physics-based (Molecular Dynamics, e.g. Free Energy Perturbation FEP+, WaterMap from Schrödinger) and empirical (e.g. GRID and WaterFLAP from Molecular Discovery) structure-based drug design methods to target lipophilic hotspots and modulate water networks across GPCR families. Chemogenomic View to Navigate Structural GPCR-Ligand Interaction Space – Integrated GPCR-ligand chemogenomics views that combine structural, pharmacological, and chemical data allow the exploration of receptor-ligand interaction space for structure-based GPCR drug design. Bio: Dr. Chris de Graaf is Head of Computational Chemistry at Sosei Heptares, an international biopharmaceutical group focused on the design and development of new medicines originating from its proprietary GPCR-targeted StaR® technology and Structure-Based Drug Design platform capabilities (www.soseiheptares.com). In this role Chris is leading the development and application of structural cheminformatics and computer-assisted drug design approaches across the GPCRome to help Sosei Heptares advance a broad and deep pipeline of partnered and in-house drug candidates in multiple therapeutic areas including neurology, immuno-oncology, gastroenterology, inflammation and rare/specialty diseases. Further details from this series can be found at: https://www.ai3sd.org/ai4proteins This video is an output from the AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) which is funded by EPSRC under Grant Number EP/S000356/1 DOI Link: http://dx.doi.org/10.5258/SOTON/P0112