Nvidia patents method to predict how molecules bind using AI
Nvidia describes a method for training machine learning models to predict how strongly molecules stick together in biological systems. The approach combines labeled data with generated, unlabeled data to improve the accuracy of these predictions.
In the filing’s own words
In various examples, methods for training machine learning models to predict a binding affinity between molecules in a biological complex using supervised and unsupervised learning techniques includes generating an unlabeled training data set based on random perturbation applied to biological complexes included in a labeled training data set, wherein: the labeled training data set includes a plurality of samples of biological complexes, and each respective sample of a biological complex is associated with a calculated binding affinity between molecules in the respective sample; training a predictive model to predict binding affinity of a first molecule to a second molecule based on a first loss associated with the labeled training data set and a second loss associated with the unlabeled training data set; and deploying the trained predictive model.
What exactly they claim (claim 1)
1. A processor-implemented method, comprising: generating an unlabeled training data set based on random perturbation applied to biological complexes included in a labeled training data set, wherein: the labeled training data set includes a plurality of samples of biological complexes, and each respective sample of a biological complex is associated with a calculated binding affinity between molecules in the respective sample; training a predictive model to predict binding affinity of a first molecule to a second molecule based on a first loss associated with the labeled training data set and a second loss associated with the unlabeled training data set; and deploying the trained predictive model.
Facts
- Company
- Nvidia (NVIDIA Corporation)
- Official title
- DUAL-LOSS FRAMEWORK FOR ACCURATE BINDING AFFINITY PREDICTION IN BIOLOGICAL COMPLEXES
- Publication number
- US20260310971A1
- Application number
- 19093581
- Filed
- Mar 28, 2025
- Published
- Oct 8, 2026
- Inventors
- 4
- Claims
- 20
Classified under
G06N 3/088 Physics & computingMore from Nvidia in AI & software
- Nvidia patents AI coach that analyzes your gameplay to suggest strategies Oct 13, 2026
- Nvidia patents AI system that writes and voices character conversations Sep 10, 2026
- Nvidia patents system that uses AI to find bugs in game videos Sep 17, 2026
- Nvidia patents AI method to make digital characters move realistically Sep 8, 2026
- Nvidia patents AI system that builds image generators from text prompts Sep 15, 2026
Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.