The Development of an Automated Computational Workflow to Prioritize
Potential Resistance Variants.
Abstract
The effective prioritization of drug resistance mutations affecting
protein folding and interactions is crucial for treatment success. To
address this, a bioinformatics pipeline, AMIA, is introduced,
integrating various structural analysis tools into a simplified
workflow. By optimizing computational resources, data transformations
are automated, enhancing scalability and reproducibility. AMIA automates
mutation introduction into protein structures, calculates polar
interaction changes, and analyses protein fold energy through
pre-established software tools. Furthermore, it includes automated
molecular dynamics analysis, reducing the need for constant user input
and output management. This open-source pipeline facilitates the
visualization of mutation effects on protein structure and dynamic
states, aiding in prioritizing variants for experimental validation.
AMIA (available at: https://github.com/kbrown3687524/amia) streamlines
computational analysis, contributing to improved treatment regimen
development against drug-resistant mutations.