SUMMIT: October 5, 2021 | 9:00 a.m. – 3:00 p.m. | Phoenix Biomedical Campus

LOCATION: Biomedical Sciences Partnership Building (BSPB) | 475 N. 5th Street, Phoenix, AZ 85004; Rooms E113/115

Speaker: Anil Nair, PhD

Vice President, Chemistry & in silico Drug Discovery, Icagen – A Ligand Company Ligand Pharmaceuticals

Presentation: Q&A:

11:50 AM – 12:20 PM 12:20 – 12:25 PM

Title:

“in silico Drug Discovery: Reality over hype – Application of computer-aided drug design in an industrial environment”

Abstract: in silico drug discovery technologies have been employed routinely in finding new drugs in the past several decades. Recently, computer-aided drug design scientists have been exploring the use of artificial intelligence (AI) based approaches in drug design. A lot of hype has been created in this space, despite the impact of AI is scarce in the drug design field. This presentation will focus on the strength and limitation of in silico strategies, including AI for drug discovery with a strong focus on physics-based computer simulations. Representative example case studies, where we implemented a predict first strategy in discovery of new drug candidates will be discussed. The technical/scientific strategies covered here are, very long molecular dynamics simulations of macromolecular targets, such as proteins, to account for their flexibilities, modeling of protein- ligands interactions, physics-based prediction of protein-ligand binding affinities, in silico screening, deep learning based long short-term memory (LSTM) models built using neural nets for prediction of physicochemical properties etc. Although a lot of hype has been created, AI based approaches has a long way to go to be impactful in the drug discovery space. However, a balanced use of physics-based simulations and a data-driven hypothesis generated design strategies will be very much useful in identifying lead candidates faster for information rich targets.