Back

A language model assistant for biocatalysis

Nana Teukam, Y. G.; Grisoni, F.; Manica, M.

2024-11-18 bioengineering
10.1101/2024.11.15.623739 bioRxiv
Show abstract

Language model assistants have transformed how researchers interact with computational tools, offering unprecedented capabilities in understanding and generating complex scientific queries. We introduce a language model assistant for biocatalysis (LM-ABC), a computational tool designed to streamline workflows in enzyme engineering research. LM-ABC integrates a large language model with domain-specific modules to facilitate biocatalysis research through natural language inputs. Its architecture employs the Reasoning and Acting (ReACT) framework for dynamic tool selection and chaining, enabling functionalities like binding site extraction and molecular dynamics simulations. LM-ABC can interpret and process user queries in the form of natural language, and interface with existing computational resources to generate relevant results for enzyme engineering. Additionally, LM-ABC is available via both command-line and web-based interfaces, which lowers the barriers for its usage and integration in various disciplines. Provided as open-source software, the LM-ABC contributes to the application of language models in computational biology, potentially accelerating enzyme engineering research processes.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.