Format

Send to

Choose Destination
Proc Natl Acad Sci U S A. 2010 Aug 3;107(31):13707-12. doi: 10.1073/pnas.1002162107. Epub 2010 Jul 19.

Predicting resistance mutations using protein design algorithms.

Author information

1
Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT 06269, USA.

Abstract

Drug resistance resulting from mutations to the target is an unfortunate common phenomenon that limits the lifetime of many of the most successful drugs. In contrast to the investigation of mutations after clinical exposure, it would be powerful to be able to incorporate strategies early in the development process to predict and overcome the effects of possible resistance mutations. Here we present a unique prospective application of an ensemble-based protein design algorithm, K*, to predict potential resistance mutations in dihydrofolate reductase from Staphylococcus aureus using positive design to maintain catalytic function and negative design to interfere with binding of a lead inhibitor. Enzyme inhibition assays show that three of the four highly-ranked predicted mutants are active yet display lower affinity (18-, 9-, and 13-fold) for the inhibitor. A crystal structure of the top-ranked mutant enzyme validates the predicted conformations of the mutated residues and the structural basis of the loss of potency. The use of protein design algorithms to predict resistance mutations could be incorporated in a lead design strategy against any target that is susceptible to mutational resistance.

PMID:
20643959
PMCID:
PMC2922245
DOI:
10.1073/pnas.1002162107
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center