Protocol for predicting drug-resistant protein mutations to an ERK2 inhibitor using RESISTOR
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Updated: Aug 8, 2026
A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors
Published on: December 7, 2014
Nathan Guerin1, Teresa Kaserer2, Bruce R Donald3
1Department of Computer Science, Duke University, Durham, NC 27708, USA.
Abstract:
Prospective predictions of drug-resistant protein mutants could improve the design of therapeutics less prone to resistance. Here, we describe RESISTOR, an algorithm that uses structure- and sequence-based criteria to predict resistance mutations. We demonstrate the process of using RESISTOR to predict ERK2 mutants likely to arise in melanoma ablating the efficacy of the ERK1/2 inhibitor SCH772984. RESISTOR is included in the free and open-source computational protein design software OSPREY. For complete details on the use and execution of this protocol, please refer to Guerin et al..1.
Insights
Predicting drug-resistant protein mutations is key for developing better therapeutics. The RESISTOR algorithm uses sequence and structure data to forecast these mutations, aiding in the design of more effective drugs.
Area of Science:
- Computational biology
- Drug discovery
- Protein engineering
Background:
- Drug resistance in proteins is a major challenge in therapeutic development.
- Predictive algorithms can accelerate the design of therapeutics with reduced resistance.
- ERK1/2 inhibitors are crucial in melanoma treatment but face resistance issues.
Purpose of the Study:
- To introduce RESISTOR, a novel algorithm for predicting drug-resistant protein mutations.
- To demonstrate RESISTOR's application in identifying potential resistance mutations for ERK2 in melanoma.
- To integrate RESISTOR into the OSPREY computational protein design software.
Main Methods:
- RESISTOR algorithm development utilizing structure- and sequence-based criteria.
- Application of RESISTOR to predict mutations in ERK2 relevant to SCH779284 resistance.
- Integration of RESISTOR within the OSPREY open-source software.
Main Results:
- RESISTOR successfully predicts potential resistance mutations in ERK2.
- The algorithm aids in understanding resistance mechanisms against ERK1/2 inhibitors like SCH779284.
- RESISTOR is available as part of the OSPREY software package.
Conclusions:
- Prospective prediction of resistance mutations using RESISTOR can guide therapeutic design.
- RESISTOR offers a valuable tool for computational protein design and drug development.
- The algorithm facilitates the creation of more robust and effective therapeutics against drug resistance.
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