Click the button below to register
July 29, 2021, 3 p.m. BST

Join Now

While traditional structure-based virtual screening has successfully found various hits to move projects forward, there is considerable room for improvement in hit rates, the variety of hit chemotypes, the available IP space examined, and the potency of unoptimized hits. Ultra-large, synthesizable-on-demand libraries from vendors have enabled a ~ 100x expansion of commercially available connection space – which is now billions of connections – while DNA-encoded libraries (DEL) can be even larger.

In this webinar, we explore how machine learning approaches can be used to study these much larger chemical spaces more effectively.

By attending this webinar, you will learn:

  • How the approaches make it easy and cost-effective to find new hits through virtual and DEL screens of billions of substance libraries
  • How machine learning trained on experimental DEL results can reduce false negative rates
  • The benefits of ultra-large screens and how they could replace traditional technologies

Portrait of Matt Repasky, Senior Vice President of Life Sciences Products at Schrödinger

Speaker: Matt Repasky, Senior Vice President, Schrödinger

Matt Repasky is Senior Vice President of Life Sciences Products and head of Schrödinger’s scientific and technical support groups. He received his PhD in chemistry from Yale University in the laboratory of Professor William Jorgensen.

Since joining the company in 2002 as a scientific developer, Repasky has held a number of executive positions, including product manager for the industry-leading docking application Glide since 2006. He has published extensive publications in the area of ​​structure-based virtual screening and has held a leading position in the development of software products in the areas of docking, pharmacophore modeling, conformation generation and QSAR modeling.

Schrödinger company logo

Schrödinger’s industry-leading computing platform for accelerating drug discovery and materials design is used by leading biopharmaceutical and industrial companies, academic institutions and government laboratories around the world. Schrödinger also uses its computing platform on a diverse and extensive pipeline of drug discovery programs in collaboration with pharmaceutical companies and has co-founded leading biotech companies. Schrödinger also uses its platform to drive a pipeline of in-house, one hundred percent drug discovery programs.

Click the button below to register
July 29, 2021, 3 p.m. BST

Join Now

LEAVE A REPLY

Please enter your comment!
Please enter your name here