YDS Pharmatech, Inc. (“YDS”), today announced that it is presenting at Biotech Showcase™ 2023. YDS is a techbio startup dedicated to building low-data-dependent AI solutions for drug design. It will present the latest achievements of its innovative biophysics simulation-informed AI platform.
Details of the presentation are as follows:
Date: Wednesday, January 11, 2023
Time: 4:30 PM PST
Location: Hilton San Francisco – Union Square, 333 O’Farrell Street, Ballroom Level, San Francisco, CA 94102
Track: Franciscan D (Ballroom Level)
“We are passionate about making computational solutions more valuable to drug discovery. Our MERES® platform enables the design of molecules toward desired properties. So far, we have contributed new IPs to our partners on three challenging targets and we are advancing 6 more drug discovery projects. One key to such a success is that ligand-induced protein changes are thoroughly sampled using our AI-accelerated molecular simulation system which predicts the protein dynamics change upon ligand binding,” said Dr. Xing Che, founder, and CEO of YDS.
“We are delighted that YDS Pharmatech, Inc. will be joining us in San Francisco and presenting at Biotech Showcase this year,” said Sara Demy, CEO of Demy-Colton. “Biotech Showcase is a prime occasion for life science entrepreneurs and investors to come together to discover the potential of innovative technologies that will drive the future of drug discovery.”
About YDS Pharmatech
YDS Pharmatech is a privately held drug design company located in Albany, NY. The company has developed a proprietary drug design engine known as MERES® (Modify-Evaluate-Reinforce-Evolve-Sampling). By leveraging a novel AI and biophysics computational platform, MERES® shifts drug discovery away from random screening and towards an efficient, directed exploration of the chemical space. For more information, please visit yds-pharmatech.com.
YDS Pharmatech’s proprietary de novo structure-based drug design engine, MERES®, leverages evolutionary AI, computational biophysics, and statistical mechanics to optimize drug candidate molecular structure. MERES® requires only one molecule as input to create molecules with new IP values and the specified desired properties. In specific, its ternary co-folding computation sub-platform successfully modeled how different molecular glues regulate CRBN conformations from wide open to tightly closed states and PROTAC-induced ternary structures. This advance our design of TPD candidates from serendipity to structure-based rational design.