AMIA: an automated workflow for analysing the structural and dynamic effects of protein variants

The effective prioritization of protein variants affecting protein folding and interactions is critical for accurately identifying significant mutations and guiding targeted experimental validation. However, current approaches involve time-consuming manual analyses, with inconsistencies in reproducibility and limited integration of various structural datasets. This highlights the need for an automated, scalable workflow capable of efficiently analysing mutations/variants and their potential effects on protein structure and interactions. To address this, a modular bioinformatics workflow, called Automated Mutation Introduction and Analysis (AMIA), is introduced, integrating various structural analysis tools into a simplified workflow. The pipeline is organized into discrete stages as follows: mutation introduction into protein structures, polar interaction changes, protein fold energy analyses, as well as downstream molecular dynamics simulation analysis, reducing the need for constant user input and output management. In addition, allosteric site determination and small-molecule docking are also optionally available but not part of the standard workflow. Furthermore, performance bottlenecks in large protein datasets are addressed by automating data transformations and parallelizing computations, while workflow consistency and reproducibility are maintained through standardized input/output formats and automated logging. This open-source pipeline automates the visualization of mutation effects on protein structure and dynamic states, aiding in prioritizing variants for experimental validation. It allows researchers to efficiently prioritize specific mutations of mutated systems for experimental validation, reducing the need for manual input and thereby delivering reproducible and scalable insights into the impact of mutations on biological systems. AMIA framework and scripts are freely available at: https://github.com/kbrown3687524/amia for download and installation on Linux and Windows operating system. Scientific contribution The pipeline scientifically contributes to research by integrating static and dynamic structural analyses and provides a comprehensive assessment of mutation effects. It also addresses limitations in manual and fragmented workflows, delivering a reproducible and scalable framework for analysing the structural and dynamic effects of protein variants, with downstream applications in areas such as drug resistance.