MS Reactivity transforms how chemical reactivity landscapes are explored and optimized by deploying two core modules: Nanoreactor for automated, unbiased mechanism discovery, and RxnEnumProfiler for mechanism-guided reactivity optimization.
Serving as the Discovery Engine of the MS Reactivity platform, Nanoreactor is an automated computational framework engineered to discover and map complex chemical reactivity networks (RXNs). Elucidating reaction mechanisms is notoriously difficult because predicting every possible pathway a reaction might follow is nearly impossible—a challenge historically reliant on human expertise and trial-and-error.
Nanoreactor solves this by pairing enhanced-sampling molecular dynamics sampling with scalable energy evaluation protocols to unveil deep mechanistic insights without requiring pre-defined reaction coordinates. By eliminating human bias and manual coordinate mapping, it enables true unsupervised reaction discovery,delivering the foundational mechanistic knowledge needed for downstream reactivity optimization.
Serving as the Optimization Engine of the MS Reactivity platform, RxnEnumProfiler turns mechanistic insights into actionable reaction design. Traditional catalyst and organic reactivity screening relies heavily on manual trial-and-error—a slow, error-prone process that can take years to navigate.
RxnEnumProfiler solves this by systematically enumerating reference reaction networks from target libraries, then screening them using high-throughput quantum mechanical evaluations or machine learning force fields. By delivering precise predictions of selectivity, yields, and kinetic barriers across vast chemical spaces, RxnEnumProfiler bridges computational modeling directly with high-throughput experimentation (HTE).
Dub PA, Hughes TF, and Mustard TJL. J. Chem. Inf. Model. 2026, 66, 16: 10103–10118.
Learn more about the related computational technologies available to progress your research projects.
Quantum mechanics solution for rapid and accurate prediction of molecular structures and properties
A modern, comprehensive force field for accurate molecular simulations
Get more from your ideas by harnessing the power of large-scale chemical exploration and accurate
in silico molecular prediction.
Contact us today to explore how you can leverage advanced simulation and AI/ML for reactivity.
Don’t see your areas of interest above? Reach out so we can help.
Thank you, we’ll be in touch soon.
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.