RESISTOR: A New OSPREY Module to Predict Resistance Mutations

Journal of computational biology: A journal of computational molecular cell biology

article

Nathan Guerin¹  Teresa Kaserer²  Bruce R. Donald¹ 

[1] Computer Science,Duke University;Institute of Pharmacy/Pharmaceutical Chemistry, University of Innsbruck;Department of Biochemistry, Duke University Medical Center;Chemistry and Mathematics, Duke University

关键词: cancer;    mutation;    OSPREY;    Pareto;    resistance;    RESISTOR;   

DOI  :  10.1089/cmb.2022.0254

学科分类：生物科学（综合）

来源: Mary Ann Liebert, Inc. Publishers

【 摘 要 】

Computational, in silico prediction of resistance-conferring escape mutations could accelerate the design of therapeutics less prone to resistance. This article describes how to use the Resistor algorithm to predict escape mutations. Resistor employs Pareto optimization on four resistance-conferring criteria—positive and negative design, mutational probability, and hotspot cardinality—to assign a Pareto rank to each prospective mutant. It also predicts the mechanism of resistance, that is, whether a mutant ablates binding to a drug, strengthens binding to the endogenous ligand, or a combination of these two factors, and provides structural models of the mutants. Resistor is part of the free and open-source computational protein design software OSPREY.

【 授权许可】

Unknown