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The Development of an Automated Computational Workflow to Prioritize Potential Resistance Variants.
  • Keaghan Brown,
  • Ruben Cloete
Keaghan Brown
University of the Western Cape
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Ruben Cloete
University of the Western Cape

Corresponding Author:[email protected]

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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.
11 Jul 2024Submitted to Clinical Applications
18 Jul 2024Submission Checks Completed
18 Jul 2024Assigned to Editor
18 Jul 2024Review(s) Completed, Editorial Evaluation Pending
18 Jul 2024Reviewer(s) Assigned