Over2millionpeoplesufferaseriousbacterialinfectioninvolvingantibioticresistanceeveryyearandatleast 23,000dieasadirectresult.Beta-lactamaseenzymescontributetothisresistancebyhydrolyzingantibiotics thatwouldnormallykillbacteria.Carbapenemases,aclassofbeta-lactamaseenzymes,areofparticular concernduetotheirabilitytobreakdownlast-resortantibiotics,carbapenems.Atpresent,thedeterminants thatcontributetothecarbapenemspecificityofthewidespreadKPCfamilyareunknown.KPC-2,a carbapenemase,andCTX-M9,anon-carbapenemase,offeranexemplarypairfortheanalysisofthese determinants.Theiroverallstructuralandmechanisticsimilaritiesallowforthefocusedinvestigationofhowthe 125positionalresiduedifferencesbetweentheseenzymesaltercarbapenemasespecificity.Weproposeto predictandidentifythesubsetsofthese125residuesthatarerequiredforcarbapenemasespecificityinKPC-2 andwouldgrantcarbapenemasespecificitytoCTX-M9.Wewillidentifythesesubsetsthroughtwoconcurrent approaches.Thefirstusesphylogeneticancestralmodelingtocreateanancestralcarbapenemaseanda closelyrelatedancestralnon-carbapenemase.Thisphylogeneticapproachallowsustoinfertwoancestorsof KPC-2andCTX-M9withdifferentcarbapenemasespecificities.Wewillthenusetheseenzymestounderstand thedeterminantsrequiredforcarbapenemasespecificityinasmallermutationalspaceascomparedtotheone forKPC-2andCTX-M9.Thesecondapproachinvolvestheuseofmoleculardynamicssimulationsand sequenceanalysisofKPC-2andCTX-M9toidentifyresiduepositionsmostlikelytoaccountforthisdifferent specificity.Inbothapproaches,wewillcreatemutantvariantsofenzymesthroughmutagenesisassaysand testactivitythroughantibioticresistanceandenzymeassays.Thestudyoftheresiduescontributingto carbapenemaseactivitywillofferinsightintothefunctionaldeterminantsunderlyingthesesimilarenzymesand providenewmethodsofantibioticresistancepredictioninclinicalandpharmaceuticalenvironments.

Public Health Relevance

This project studies the mutations that grant bacteria the ability to breakdown a greater number of antibiotics. By studying how changes to protein dynamics increase the effectiveness of proteins that protect bacteria from antibiotics, we hope to gain a better understanding of antibiotic resistance which can then aid in improving antibiotic design.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
1F31GM113543-01A1
Application #
9261296
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Brown, Patrick
Project Start
2017-01-01
Project End
2018-12-31
Budget Start
2017-01-01
Budget End
2017-12-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Virginia
Department
Biomedical Engineering
Type
Schools of Medicine
DUNS #
065391526
City
Charlottesville
State
VA
Country
United States
Zip Code
22904
Cortina, George A; Kasson, Peter M (2018) Predicting allostery and microbial drug resistance with molecular simulations. Curr Opin Struct Biol 52:80-86
Latallo, M J; Cortina, G A; Faham, S et al. (2017) Predicting allosteric mutants that increase activity of a major antibiotic resistance enzyme. Chem Sci 8:6484-6492