Machine learning-enabled retrobiosynthesis of molecules
Retrobiosynthesis provides an effective and sustainable approach to producing functional
molecules. The past few decades have witnessed a rapid expansion of biosynthetic …
molecules. The past few decades have witnessed a rapid expansion of biosynthetic …
Machine intelligence for chemical reaction space
Discovering new reactions, optimizing their performance, and extending the synthetically
accessible chemical space are critical drivers for major technological advances and more …
accessible chemical space are critical drivers for major technological advances and more …
Grammar prompting for domain-specific language generation with large language models
Large language models (LLMs) can learn to perform a wide range of natural language tasks
from just a handful of in-context examples. However, for generating strings from highly …
from just a handful of in-context examples. However, for generating strings from highly …
RetroBioCat as a computer-aided synthesis planning tool for biocatalytic reactions and cascades
As the enzyme toolbox for biocatalysis has expanded, so has the potential for the
construction of powerful enzymatic cascades for efficient and selective synthesis of target …
construction of powerful enzymatic cascades for efficient and selective synthesis of target …
Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
The field of predictive chemistry relates to the development of models able to describe how
molecules interact and react. It encompasses the long-standing task of computer-aided …
molecules interact and react. It encompasses the long-standing task of computer-aided …
Improving few-and zero-shot reaction template prediction using modern hopfield networks
Finding synthesis routes for molecules of interest is essential in the discovery of new drugs
and materials. To find such routes, computer-assisted synthesis planning (CASP) methods …
and materials. To find such routes, computer-assisted synthesis planning (CASP) methods …
Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP
The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus
valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user …
valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user …
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery--A Focus on Affinity Prediction Problems with Noise Annotations
AI-aided drug discovery (AIDD) is gaining increasing popularity due to its promise of making
the search for new pharmaceuticals quicker, cheaper and more efficient. In spite of its …
the search for new pharmaceuticals quicker, cheaper and more efficient. In spite of its …
Data sharing in chemistry: lessons learned and a case for mandating structured reaction data
The past decade has seen a number of impressive developments in predictive chemistry
and reaction informatics driven by machine learning applications to computer-aided …
and reaction informatics driven by machine learning applications to computer-aided …
Retrosynthesis prediction with an iterative string editing model
Retrosynthesis is a crucial task in drug discovery and organic synthesis, where artificial
intelligence (AI) is increasingly employed to expedite the process. However, existing …
intelligence (AI) is increasingly employed to expedite the process. However, existing …