Silicon Therapeutics Supports Five Researchers Through Open Science Fellows Program
BOSTON–(BUSINESS WIRE)–#AI—Silicon Therapeutics, a privately-held, fully integrated drug design, discovery and development company focused on small molecule therapeutics, today is pleased to introduce the 2020 members of the Silicon Therapeutics Open Science Fellows Program, which include Dr. Lillian Chong, Dr. Heather Kulik, Dr. Tom Kurtzman, Dr. David Mobley and Dr. Michael Shirts.
Research areas include the development of in silico methods for elucidating the fundamental physical principles associated with biomolecular recognition and protein motion. Specific areas of expertise focus around the company’s proprietary computational physics-driven drug development platform, including enhanced sampling for long-timescale molecular dynamics, quantum mechanical aspects of enzyme function, the critical role of water thermodynamics, robust free energy simulations and the application of statistical thermodynamics to biological systems.
“Open science remains paramount to our culture at Silicon Therapeutics,” said Woody Sherman, Ph.D., chief scientific officer. “This class of Open Science Fellows was carefully selected from academic researchers who have established leadership in their field and promote the open science ethos. Each fellow is working on projects that bears a direct relationship to the key challenges faced by our field.”
The Silicon Therapeutics Open Science Fellows program was created in 2017 to advance the open science movement within the drug discovery industry, facilitating access to scientific knowledge, methods and data, and to support investigators who have demonstrated a commitment to the open science movement through their contributions to open source software. Open science refers to the practice of sharing and development of scientific research through collaborative networks, including publications, data, physical samples and software and making its dissemination accessible and transparent. The benefits of open science include increased availability and accessibility of publicly funded scientific research outputs, the opportunity for more rigorous peer-review processes, greater reproducibility and transparency of research and the possibility of greater impact.
Lillian Chong, Ph.D. is an associate professor at the University of Pittsburgh where her research involves the development and application of molecular simulation approaches to model a variety of biophysical processes. Dr. Chong has pioneered work on enhanced sampling methods, including the weighted ensemble method for simulating rare events such as protein binding, protein switching and chemical reactions. In addition, she has made advances in force fields, specifically the Amber ff15ipq protein force field, including an expansion of this force field (ff15ipq-m) released in 2020 for modeling protein mimetics. Dr. Chong has also developed robust scalable software tools for large-scale simulations, including Weighted Ensemble Simulation Toolkit with Parallelization and Analysis (WESTPA).
Heather Kulik, Ph.D. is an associate professor at the Massachusetts Institute of Technology where her research involves quantum chemistry and machine learning applied to catalysis, transition-metal chemistry, atomistic simulations and enzymes, with a focus on atom-by-atom design of molecules from first-principles. The Kulik group uses first-principles modeling (i.e., quantum mechanics) to unearth fundamental aspects of structure-property relationships in biological enzymes and emerging heterogeneous single-atom catalysts. This approach enables the prediction of new properties, the exploration of million-compound design spaces and the identification of design rules and exceptions that go beyond intuition.
Tom Kurtzman, Ph.D. is an associate professor at Lehman College, City University of New York in the Bronx, N.Y. where his research focuses on the development of computational methods based on statistical thermodynamics that can aid in the discovery and rational design of new drugs. Prof. Kurtzman’s approach applies a combination of statistical mechanical theory and computer simulations to better understand the physical principles governing the molecular recognition between proteins and small molecule drug candidates. His research contributions provide a framework to account for and quantify the role that water plays in molecular recognition.
David Mobley, Ph.D. is a vice chair and professor at the University of California, Irvine, where his research focuses on predicting thermodynamic properties from molecular simulations with an emphasis on problems relating to pharmaceutical drug discovery. These include transfer free energies, protein-ligand docking, binding free energy simulations and small molecule solubility prediction. Methods recently developed and applied have achieved far greater accuracies at computing and predicting binding affinities as compared with previous methods, which are being applied on pharmaceutically relevant proteins. His work focuses on using so-called alchemical free energy techniques for predicting binding affinities using molecular simulations.
Michael Shirts, Ph.D. is an associate professor at the University of Colorado in Boulder where his research centers on computational approaches to understanding and designing molecules with optimized properties. Dr. Shirts develops rigorous methods grounded in statistical thermodynamics which can improve the way we design and characterize molecules at the nanoscale. His focuses include drug design through prediction of physical properties, binding affinities and the design of novel materials, with an emphasis on the development of computational tools. These computational tools can fundamentally change molecular design by making searches through chemical and configurations space much more predictive, reliable and efficient.
ABOUT SILICON THERAPEUTICS
Silicon Therapeutics is a privately-held, fully integrated drug design, research and development company focused on small molecule therapeutics. The Silicon Therapeutics computational physics-driven drug design platform combines quantum physics, statistical thermodynamics, molecular simulations, a dedicated HPC super-computing cluster, purpose-built software, in-house laboratory and clinical development capabilities. The platform was purpose built from the ground up to address difficult targets and use simulations to pioneer a new path for drug design and deliver novel medicines to improve the lives of patients.
Silicon Therapeutics is currently the only company which completely owns the entire spectrum of proprietary physics-driven drug discovery from chip-to-clinic. The company’s lead program is a highly differentiated small molecule STimulator of Interferon Genes (STING) agonist for the treatment of cancer. SNX281 is anticipated to enter the clinic in late 2020. The company’s headquarters are located in Boston and Suzhou, China. To learn more about Silicon Therapeutics, please visit our website at www.silicontx.com or follow us on LinkedIn and Twitter.
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