# ASMC: investigating the amino acid diversity of enzyme active sites

## TL;DR

This paper introduces an updated version of the ASMC workflow, which improves enzyme active site analysis for better clustering and easier use.

## Contribution

The paper presents a redesigned ASMC workflow with improved methods for predicting enzyme active site clusters.

## Key findings

- The new ASMC version includes updated pocket prediction and clustering methods for better results.
- The workflow now uses a single programming language (Python) for easier maintenance and installation.
- Evaluation on protein families showed improved performance compared to the original version.

## Abstract

The analysis of enzyme active sites is essential for understanding their activity in terms of catalyzed reaction and substrate specificity, providing insights for engineering to obtain targeted properties or modify the substrate scope. In 2010, a first version of the Active Site Modeling and Clustering (ASMC) workflow was published. ASMC predicts isofunctional clusters from enzyme families, based on structural modeling and clustering of active sites. Since then, structure- and sequence-based methods have developed considerably.

We present here a redesign of the ASMC workflow. This new major version includes recent pocket prediction, structural alignment and clustering methods, as well as a refined amino acid distance matrix, thereby improving the relevance of results and reducing the need for laborious manual analysis to obtain relevant clusters. In addition, we have implemented multiple sequence alignment as a possible input for the clustering step, along with an additional script to compare 2D and 3D active sites. Finally, the code has been unified from three to one programming language (Python) to facilitate its installation and maintenance. This new version of ASMC was evaluated on a set of protein families, resulting in overall better performances compared to its original version.

ASMC is supported on Linux operating system and freely available at https://github.com/labgem/ASMC, along with a complete documentation (wiki, tutorial).