Artificial Intelligence for Retrosynthetic Planning Needs Both Data and Expert Knowledge
Rapid advancements in artificial intelligence (AI) have enabled breakthroughs across many
scientific disciplines. In organic chemistry, the challenge of planning complex multistep …
scientific disciplines. In organic chemistry, the challenge of planning complex multistep …
Hybrid machine learning approach to predict the site selectivity of iridium-catalyzed arene borylation
E Caldeweyher, M Elkin, G Gheibi… - Journal of the …, 2023 - ACS Publications
The borylation of aryl and heteroaryl C–H bonds is valuable for the site-selective
functionalization of C–H bonds in complex molecules. Iridium catalysts ligated by bipyridine …
functionalization of C–H bonds in complex molecules. Iridium catalysts ligated by bipyridine …
Predictive Minisci late stage functionalization with transfer learning
Structural diversification of lead molecules is a key component of drug discovery to explore
chemical space. Late-stage functionalizations (LSFs) are versatile methodologies capable of …
chemical space. Late-stage functionalizations (LSFs) are versatile methodologies capable of …
Fine-tuning GPT-3 for machine learning electronic and functional properties of organic molecules
We evaluate the effectiveness of fine-tuning GPT-3 for the prediction of electronic and
functional properties of organic molecules. Our findings show that fine-tuned GPT-3 can …
functional properties of organic molecules. Our findings show that fine-tuned GPT-3 can …
Mechanistic Inference from Statistical Models at Different Data-Size Regimes
The chemical sciences are witnessing an influx of statistics into the catalysis literature.
These developments are propelled by modern technological advancements that are leading …
These developments are propelled by modern technological advancements that are leading …
Automated quantum chemistry for estimating nucleophilicity and electrophilicity with applications to retrosynthesis and covalent inhibitors
Reactivity scales such as nucleophilicity and electrophilicity are valuable tools for
determining chemical reactivity and selectivity. However, prior attempts to predict or …
determining chemical reactivity and selectivity. However, prior attempts to predict or …
Active Learning Guided Computational Discovery of Plant-Based Redoxmers for Organic Nonaqueous Redox Flow Batteries
Organic nonaqueous redox flow batteries (O-NRFBs) are promising energy storage devices
due to their scalability and reliance on sourceable materials. However, finding suitable …
due to their scalability and reliance on sourceable materials. However, finding suitable …
Every atom counts: predicting sites of reaction based on chemistry within two bonds
How much chemistry can be described by looking only at each atom, its neighbours and its
next-nearest neighbours? We present a method for predicting reaction sites based only on a …
next-nearest neighbours? We present a method for predicting reaction sites based only on a …
Holistic chemical evaluation reveals pitfalls in reaction prediction models
The prediction of chemical reactions has gained significant interest within the machine
learning community in recent years, owing to its complexity and crucial applications in …
learning community in recent years, owing to its complexity and crucial applications in …
A hybrid machine-learning approach to predict the iridium-catalyzed borylation of C–H bonds
E Caldeweyher, M Elkin, G Gheibi, M Johansson… - 2022 - chemrxiv.org
The borylation of aryl and heteroaryl C–H bonds is valuable for the site-selective
functionalization of C–H bonds in complex molecules. Iridium catalysts ligated by bipyridine …
functionalization of C–H bonds in complex molecules. Iridium catalysts ligated by bipyridine …