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.
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.
| 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 |
