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A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors
Published on: December 7, 2014
Evaluation of residue variability in a conformation-specific context and during evolutionary sequence reconstruction
Felipe A M Otsuka1,2, Sinisa Bjelic1
1Department of Chemistry and Biomedical Sciences, Linnaeus University, Kalmar, Sweden.
Abstract:
Diseases with readily available therapies may eventually prevail against the specific treatment by the acquisition of resistance. The constitutively active Abl1 tyrosine kinase known to cause chronic myeloid leukemia is an example, where patients may experience relapse after small inhibitor drug treatment. Mutations in the Abl1 tyrosine kinase domain (Abl1-KD) are a critical source of resistance and their emergence depends on the conformational states that have been observed experimentally: the inactive state, the active state, and the intermediate inactive state that resembles Src kinase. Understanding how resistant positions and amino acid identities are determined by selection pressure during drug treatment is necessary to improve future drug development or treatment decisions. We carry out in silico site-saturation mutagenesis over the Abl1-KD structure in a conformational context to evaluate the in situ and conformational stability energy upon mutation. Out of the 11 studied resistant positions, we determined that 7 of the resistant mutations favored the active conformation of Abl1-KD with respect to the inactive state. When, instead, the sequence optimization was modeled simultaneously at resistant positions, we recovered five known resistant mutations in the active conformation. These results suggested that the Abl1 resistance mechanism targeted substitutions that favored the active conformation. Further sequence variability, explored by ancestral reconstruction in Abl1-KD, showed that neutral genetic drift, with respect to amino acid variability, was specifically diminished in the resistant positions. Since resistant mutations are susceptible to chance with a certain probability of fixation, combining methodologies outlined here may narrow and limit the available sequence space for resistance to emerge, resulting in more robust therapeutic treatments over time.
Insights
Drug resistance in chronic myeloid leukemia (CML) can emerge from mutations in the Abl1 tyrosine kinase domain. Understanding these mutations
Area of Science:
- Biochemistry
- Structural Biology
- Computational Biology
Background:
- Acquired resistance to targeted therapies, particularly small molecule inhibitors, is a significant clinical challenge in diseases like chronic myeloid leukemia (CML).
- The Abl1 tyrosine kinase, constitutively active in CML, is a primary target, but mutations in its kinase domain (Abl1-KD) lead to drug resistance and patient relapse.
- Emergence of resistance mutations is linked to distinct conformational states of Abl1-KD: inactive, active, and an intermediate inactive state.
Purpose of the Study:
- To investigate how selection pressure during drug treatment determines resistant positions and amino acid identities in Abl1-KD.
- To computationally evaluate the impact of mutations on Abl1-KD conformational stability and energy.
- To inform future drug development and treatment strategies for CML by understanding resistance mechanisms.
Main Methods:
- In silico site-saturation mutagenesis was performed on the Abl1-KD structure within a conformational context.
- Evaluation of in situ and conformational stability energy changes upon mutation.
- Ancestral reconstruction analysis to explore sequence variability at resistant positions.
Main Results:
- Seven out of eleven studied resistant positions showed mutations favoring the active conformation of Abl1-KD over the inactive state.
- Simultaneous sequence optimization at resistant positions identified five known resistant mutations, all favoring the active conformation.
- Ancestral reconstruction revealed diminished neutral genetic drift at resistant positions, suggesting selection pressure against variability.
Conclusions:
- Abl1 resistance mechanisms are driven by substitutions that promote the active conformation of the kinase domain.
- Computational approaches combining mutagenesis and ancestral reconstruction can identify resistance-driving mutations and predict conformational preferences.
- Limiting the sequence space available for resistance mutations through targeted strategies could lead to more durable therapeutic outcomes in CML.
