AI for molecular simulations may not need built-in physics to deliver strong results

Simulating how atoms and molecules move over time is a central challenge in computational chemistry and materials science.
Morning Overview on MSN

University of Oregon AI models drug molecule motion before lab tests

A single drug can take more than a decade and an estimated $2.6 billion to bring to market, and much of that time is spent ...
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AI model challenges need for built-in physics in molecular simulations

Researchers from BIFOLD and Google DeepMind have developed MD-ET, a transformer-based molecular dynamics model that omits traditional physics constraints like energy conservation and equivariance.
technologynetworks

Ultra-Robust Machine-Learning Model Can Simulate Molecules at Extreme Temperatures

The study, published in Communications Chemistry, explores the first AI‑powered model that can keep molecular simulations running safely and smoothly, even when molecules are pushed to extreme ...
Business Wire

insitro Partners with Lilly to Build First-in-Kind Machine Learning Models to Advance Small Molecule Drug Discovery

SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)--insitro, a pioneer in machine learning for drug discovery and development, today announced a new collaboration with Eli Lilly and Company (Lilly) to ...
technologynetworks

Machine-Learning Model Enables Ultra-Stable Molecular Simulations at Extreme Temperatures

Researchers at The University of Manchester have created a groundbreaking physics‑informed machine‑learning model that can run molecular simulations for unprecedented lengths of time, even at ...
EurekAlert!

Frontier molecular orbital weighted model based networks for revealing organic delayed fluorescence efficiency

Organic light-emitting diodes (OLEDs) have become a cornerstone in display and lighting technologies, driving the demand for efficient organic thermally activated delayed fluorescence (TADF) materials ...