Literature DB >> 25552560

Protein design algorithms predict viable resistance to an experimental antifolate.

Stephanie M Reeve1, Pablo Gainza2, Kathleen M Frey1, Ivelin Georgiev2, Bruce R Donald3, Amy C Anderson4.   

Abstract

Methods to accurately predict potential drug target mutations in response to early-stage leads could drive the design of more resilient first generation drug candidates. In this study, a structure-based protein design algorithm (K* in the OSPREY suite) was used to prospectively identify single-nucleotide polymorphisms that confer resistance to an experimental inhibitor effective against dihydrofolate reductase (DHFR) from Staphylococcus aureus. Four of the top-ranked mutations in DHFR were found to be catalytically competent and resistant to the inhibitor. Selection of resistant bacteria in vitro reveals that two of the predicted mutations arise in the background of a compensatory mutation. Using enzyme kinetics, microbiology, and crystal structures of the complexes, we determined the fitness of the mutant enzymes and strains, the structural basis of resistance, and the compensatory relationship of the mutations. To our knowledge, this work illustrates the first application of protein design algorithms to prospectively predict viable resistance mutations that arise in bacteria under antibiotic pressure.

Entities:  

Keywords:  DHFR; MRSA; antifolate; drug resistance; protein design

Mesh:

Substances:

Year:  2014        PMID: 25552560      PMCID: PMC4311853          DOI: 10.1073/pnas.1411548112

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  24 in total

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Authors:  S C Lovell; J M Word; J S Richardson; D C Richardson
Journal:  Proteins       Date:  2000-08-15

2.  Efficient a priori identification of drug resistant mutations using Dead-End Elimination and MM-PBSA.

Authors:  Maria Safi; Ryan H Lilien
Journal:  J Chem Inf Model       Date:  2012-06-13       Impact factor: 4.956

3.  Predicting resistance mutations using protein design algorithms.

Authors:  Kathleen M Frey; Ivelin Georgiev; Bruce R Donald; Amy C Anderson
Journal:  Proc Natl Acad Sci U S A       Date:  2010-07-19       Impact factor: 11.205

4.  Predicting drug-resistant mutations of HIV protease.

Authors:  Hiroshi Ishikita; Arieh Warshel
Journal:  Angew Chem Int Ed Engl       Date:  2008       Impact factor: 15.336

5.  A single amino acid substitution in Staphylococcus aureus dihydrofolate reductase determines trimethoprim resistance.

Authors:  G E Dale; C Broger; A D'Arcy; P G Hartman; R DeHoogt; S Jolidon; I Kompis; A M Labhardt; H Langen; H Locher; M G Page; D Stüber; R L Then; B Wipf; C Oefner
Journal:  J Mol Biol       Date:  1997-02-14       Impact factor: 5.469

Review 6.  Structure-based methods for predicting target mutation-induced drug resistance and rational drug design to overcome the problem.

Authors:  Ge-Fei Hao; Guang-Fu Yang; Chang-Guo Zhan
Journal:  Drug Discov Today       Date:  2012-07-10       Impact factor: 7.851

7.  Increased hydrophobic interactions of iclaprim with Staphylococcus aureus dihydrofolate reductase are responsible for the increase in affinity and antibacterial activity.

Authors:  Christian Oefner; Monica Bandera; Andreas Haldimann; Heike Laue; Henk Schulz; Seema Mukhija; Sandro Parisi; Laurent Weiss; Sergio Lociuro; Glenn E Dale
Journal:  J Antimicrob Chemother       Date:  2009-02-11       Impact factor: 5.790

8.  Structural comparison of chromosomal and exogenous dihydrofolate reductase from Staphylococcus aureus in complex with the potent inhibitor trimethoprim.

Authors:  Holly Heaslet; Melissa Harris; Kelly Fahnoe; Ronald Sarver; Henry Putz; Jeanne Chang; Chakrapani Subramanyam; Gabriela Barreiro; J Richard Miller
Journal:  Proteins       Date:  2009-08-15

9.  Analysis of mutational resistance to trimethoprim in Staphylococcus aureus by genetic and structural modelling techniques.

Authors:  Anna A Vickers; Nicola J Potter; Colin W G Fishwick; Ian Chopra; Alex J O'Neill
Journal:  J Antimicrob Chemother       Date:  2009-04-21       Impact factor: 5.790

10.  Accurate calculation of mutational effects on the thermodynamics of inhibitor binding to p38α MAP kinase: a combined computational and experimental study.

Authors:  Shun Zhu; Sue M Travis; Adrian H Elcock
Journal:  J Chem Theory Comput       Date:  2013-07-09       Impact factor: 6.006

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  24 in total

1.  BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.

Authors:  Jonathan D Jou; Swati Jain; Ivelin S Georgiev; Bruce R Donald
Journal:  J Comput Biol       Date:  2016-01-08       Impact factor: 1.479

2.  Improved energy bound accuracy enhances the efficiency of continuous protein design.

Authors:  Kyle E Roberts; Bruce R Donald
Journal:  Proteins       Date:  2015-05-08

3.  Computationally optimized deimmunization libraries yield highly mutated enzymes with low immunogenicity and enhanced activity.

Authors:  Regina S Salvat; Deeptak Verma; Andrew S Parker; Jack R Kirsch; Seth A Brooks; Chris Bailey-Kellogg; Karl E Griswold
Journal:  Proc Natl Acad Sci U S A       Date:  2017-06-12       Impact factor: 11.205

4.  cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design.

Authors:  Yuchao Pan; Yuxi Dong; Jingtian Zhou; Mark Hallen; Bruce R Donald; Jianyang Zeng; Wei Xu
Journal:  J Comput Biol       Date:  2016-05-06       Impact factor: 1.479

Review 5.  Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics.

Authors:  Tatiana Maximova; Ryan Moffatt; Buyong Ma; Ruth Nussinov; Amarda Shehu
Journal:  PLoS Comput Biol       Date:  2016-04-28       Impact factor: 4.475

6.  Computational Analysis of Energy Landscapes Reveals Dynamic Features That Contribute to Binding of Inhibitors to CFTR-Associated Ligand.

Authors:  Graham T Holt; Jonathan D Jou; Nicholas P Gill; Anna U Lowegard; Jeffrey W Martin; Dean R Madden; Bruce R Donald
Journal:  J Phys Chem B       Date:  2019-11-27       Impact factor: 2.991

7.  Rational design of proteins that exchange on functional timescales.

Authors:  James A Davey; Adam M Damry; Natalie K Goto; Roberto A Chica
Journal:  Nat Chem Biol       Date:  2017-10-23       Impact factor: 15.040

8.  BBK* (Branch and Bound Over K*): A Provable and Efficient Ensemble-Based Protein Design Algorithm to Optimize Stability and Binding Affinity Over Large Sequence Spaces.

Authors:  Adegoke A Ojewole; Jonathan D Jou; Vance G Fowler; Bruce R Donald
Journal:  J Comput Biol       Date:  2018-03-13       Impact factor: 1.479

9.  Minimization-Aware Recursive K*: A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape.

Authors:  Jonathan D Jou; Graham T Holt; Anna U Lowegard; Bruce R Donald
Journal:  J Comput Biol       Date:  2019-12-06       Impact factor: 1.479

10.  Protein Design by Provable Algorithms.

Authors:  Mark A Hallen; Bruce R Donald
Journal:  Commun ACM       Date:  2019-10       Impact factor: 4.654

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