Abstract

We're facing a challenge in the world of chemistry: our lack of data is slowing down how we can use clever computer programs, known as machine learning, to create powerful new medicines. In this piece, I'll walk you through what we're doing to solve this problem by creating data highways from millions of small molecules, peptides, and cyclic peptides. We are now able to use machine learning to discover and create new functional molecules quickly. Sometimes, these computer-designed molecules are even better than what we can make ourselves! Our next step is to create an infinite loop where we automatically design, build, and test potential new medicines.

Biography

Bradley L. Pentelute is a Professor of Chemistry at MIT (https://pentelutelabmit.com). He is also an Associate Member, Broad Institute of Harvard and MIT, an Extramural Member of the MIT Koch Cancer Institute, and Member, Center for Environmental Health Sciences MIT. He received his undergraduate degree in Psychology and Chemistry from the University of Southern California, and his M.S and Ph.D. in Organic Chemistry from the University of Chicago with Prof. Steve Kent.  He was a postdoctoral fellow in the laboratory of Dr. R. John Collier at Harvard Medical School, Microbiology.   The Pentelute Lab aims to invent new chemistry for the efficient and selective modification of proteins, to ‘hijack’ these biological machines for efficient drug delivery into cells and to create new machines to rapidly and efficiently manufacture peptides and proteins.