Machine Learning

X-Chem and Structural Genomics Consortium announced collaboration

X-Chem, a global leader in innovative drug discovery services, and the Structural Genomics Consortium (SGC), a public-private partnership dedicated to accelerating drug discovery through open science, announced that they have entered a collaboration aimed at creating new chemical tools to study human proteins. The goal is to generate DNA-encoded library (DEL) screening data for large numbers of under-addressed proteins in the human proteome — ultimately allowing drug discovery and machine learning (ML) experts from around the world to use the data to unlock disease targets of the future.

Under the agreement, X-Chem will deploy its proprietary DEL platform to create datasets for proteins chosen and supplied by the SGC. These datasets, curated in an ML-ready format, will be posted to a public portal to be used for model building. These models will enable the development of tool compounds that will unlock future disease targets, a key goal of the SGC’s Target 2035 initiative. The early stages of the collaboration will be focused on screening and data generation, but X-Chem and the SGC expect the DEL-ML data portal will be ready for public access starting in early 2024.

“X-Chem was the first to show that high-quality DEL datasets can support model building, and our successful collaboration with X-Chem on multiple unprecedented targets supports the scaling of their innovative approach,” said Aled Edwards, S.G., Ph.D., founder and CEO of the SGC. “We look forward to making our screening data publicly available so as to enable biological and computational researchers worldwide to collaborate openly with us to identify the disease targets of the future.”

Matt Clark, Ph.D., CEO of X-Chem, said, “The SGC is dedicated to unlocking the human proteome through innovative science and open collaboration. We are thrilled that X-Chem will be a partner in their mission to understand all proteins in the human genome. Our DEL platform is the perfect technology for such high-throughput, high-quality data generation.”

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