Victor Batista
John Gamble Kirkwood Professor of ChemistryCards
About
Research
Publications
2026
A Flexible Indolocarbazole Ligand Platform for Tunable Multinuclear Metal Complexes
Decavoli C, Jelušić J, Krajewski S, Batista V, Brudvig G. A Flexible Indolocarbazole Ligand Platform for Tunable Multinuclear Metal Complexes. Journal Of The Chinese Chemical Society 2026 DOI: 10.1002/jccs.70197.Peer-Reviewed Original ResearchMultinuclear metal complexesLigand platformMetal complexesMetal-metal separationWater oxidation catalystsCu-Cu separationMetal-metal distancesSolid-state assemblyDiiridium complexesDinuclear unitsDonor strengthDonor powerMolecular pocketsCopper coordinationEnzyme active siteOxide catalystsCatalytic activityCu-CuActive siteRotational freedomComputational studyOxidation limitSmall moleculesLigandSeparationAsymmetry Control in a Parametric Oscillator for the Quantum Simulation of Chemical Activation
de Albornoz A, Cortiñas R, Schäfer M, Frattini N, Allen B, Cabral D, Videla P, Khazaei P, Geva E, Batista V, Devoret M. Asymmetry Control in a Parametric Oscillator for the Quantum Simulation of Chemical Activation. PRX Quantum 2026, 7: 020309. DOI: 10.1103/71yp-fqns.Peer-Reviewed Original ResearchAsymmetric double-wellQuantum regimeQuantum simulationParametric oscillatorDouble-wellKerr parametric oscillatorJosephson junction circuitsDouble-well systemThird-order nonlinearityDissipative tunnelingTunneling resonancesTunneling rateJunction circuitQuantum mechanicsParametric processesReaction dynamicsWeak asymmetryEnergy levelsParameter spaceQuantumProton transfer reactionsReaction coordinateLow noiseTunnelAsymmetryMechanism of Tyrosine-Driven Deprotonation in Photosystem II Revealed by Multiscale Simulations
Liu J, Yang K, Lampert J, Armstrong W, Brudvig G, Batista V. Mechanism of Tyrosine-Driven Deprotonation in Photosystem II Revealed by Multiscale Simulations. Journal Of The American Chemical Society 2026, 148: 9255-9267. PMID: 41730138, DOI: 10.1021/jacs.5c13000.Peer-Reviewed Original ResearchConceptsElectron paramagnetic resonanceProton transferOxygen-evolving complexTR-SFXMolecular dynamicsPhotothermal beam deflectionTime-resolved X-ray absorption spectroscopyTime-resolved serial femtosecond crystallographyLight-induced water oxidationHydrogen bond symmetryX-ray absorption spectroscopyHydrogen bond dynamicsElectron density shiftsIntermediate S-statesQuantum mechanics/molecular mechanicsHydrogen bond networkSerial femtosecond crystallographyWater ligandsWater oxidationHydrogen bondsElectron transferRedox eventsRedox transitionsDeprotonationFemtosecond crystallographyComputational Evolution of Anti-PD‑1 Antibodies Induces Structural Refolding for High-Affinity Interactions
Shi Y, Kim Y, Liu P, Wang J, Tang S, Batista V. Computational Evolution of Anti-PD‑1 Antibodies Induces Structural Refolding for High-Affinity Interactions. Biochemistry 2026, 65: 517-520. PMID: 41671420, DOI: 10.1021/acs.biochem.5c00574.Peer-Reviewed Original ResearchError-Mitigation Enabled Multicomponent Quantum Simulations beyond the Born–Oppenheimer Approximation
Cabral D, Allen B, Pavošević F, Hammes-Schiffer S, Díez-Valle P, Baker J, Saxena G, Kyaw T, Batista V. Error-Mitigation Enabled Multicomponent Quantum Simulations beyond the Born–Oppenheimer Approximation. Journal Of Chemical Theory And Computation 2026, 22: 1760-1769. PMID: 41665240, DOI: 10.1021/acs.jctc.5c01911.Peer-Reviewed Original ResearchBorn-Oppenheimer approximationQuantum simulationNuclear degreesBorn-OppenheimerComputed ground-state energiesNuclear degrees of freedomError mitigation protocolUnitary coupled clusterGround-state energyNuclear quantum effectsSuperconducting hardwarePositronium hydrideQuantum protonsJastrow ansatzQuantum effectsOrbital formalismQuantum hardwareDegrees of freedomChemical accuracyMolecular hydrogenMolecular systemsSimulations of molecular systemsAnsatzError mitigationQuantum
2025
Distal Mutations Rewire Allosteric Networks to Control Substrate Specificity in PTP1B
Wang X, Anderson R, Liu J, Batista V, Loria J. Distal Mutations Rewire Allosteric Networks to Control Substrate Specificity in PTP1B. Biochemistry 2025, 64: 4661-4674. PMID: 41292192, PMCID: PMC12877921, DOI: 10.1021/acs.biochem.5c00539.Peer-Reviewed Original ResearchConceptsSubstrate specificityAcidic loopControl substrate specificityRegulation of cellular signaling pathwaysDistal allosteric siteWild-type enzymeCatalytic mechanismAllosteric siteProtein tyrosine phosphataseActive-site dynamicsCellular signaling pathwaysCommunity network analysisAllosteric mutantsProtein tyrosine phosphatase 1BMicrosecond molecular dynamics simulationsSubstrate preferencePhosphotyrosine peptidesAllosteric regulationAllosteric communicationDistal mutationsTyrosine phosphatase 1BTyrosine phosphataseEnzymatic dynamicsSignaling pathwayCatalytic centerAtomistic modulation of MIF‐2 structure, catalysis, and biological signaling via cysteine residues and a small molecule, Ebselen
Widjaja V, D'Orazio S, Das P, Rajendran D, Takada X, Shi Y, Varghese I, Lam Y, DaSilva N, Wang J, Batista V, Bhandari V, Lisi G. Atomistic modulation of MIF‐2 structure, catalysis, and biological signaling via cysteine residues and a small molecule, Ebselen. Protein Science 2025, 34: e70344. PMID: 41099614, PMCID: PMC12529878, DOI: 10.1002/pro.70344.Peer-Reviewed Original ResearchConceptsMIF-2Small moleculesBiological functionsMolecular dynamics simulationsMIF trimerMacrophage migration inhibitory factorNuclear magnetic resonanceRegulation of macrophage migration inhibitory factorD-dopachrome tautomeraseSelenylsulfide bondAllosteric crosstalkAllosteric switchDynamics simulationsAllosteric pathwaysBiochemical functionsConformational transitionCysteine residuesProximal cysteineStructural biologyBiological signalsQuaternary structureAllosteric mechanismSignaling activityCatalysisD-dopachromeDynamic and structural insights into allosteric regulation on MKP5 a dual-specificity phosphatase
Skeens E, Maschietto F, Manjula R, Shillingford S, Murphy J, Lolis E, Batista V, Bennett A, Lisi G. Dynamic and structural insights into allosteric regulation on MKP5 a dual-specificity phosphatase. Nature Communications 2025, 16: 7011. PMID: 40745179, PMCID: PMC12313947, DOI: 10.1038/s41467-025-62150-w.Peer-Reviewed Original ResearchMeSH KeywordsAllosteric RegulationAllosteric SiteCatalytic DomainCrystallography, X-RayDual-Specificity PhosphatasesHumansMagnetic Resonance SpectroscopyMitogen-Activated Protein Kinase PhosphatasesMolecular Dynamics Simulationp38 Mitogen-Activated Protein KinasesPhosphorylationProtein BindingProtein ConformationConceptsMitogen-activated protein kinaseMAPK bindingMolecular mechanismsCatalytic mechanismDual-specificity phosphataseMechanism of dephosphorylationAllosteric siteMolecular dynamics simulationsNMR spectroscopy approachesP38 mitogen-activated protein kinaseCatalytic domainAllosteric regulationRegulatory interplayProtein kinaseCrucial residuesConformational flexibilityDynamics simulationsActive siteStructural insightsMolecular pictureAllosteric pocketDephosphorylationY435MKP5Spectroscopy approachCorrection to “A Hybrid Transformer Architecture with a Quantized Self-Attention Mechanism Applied to Molecular Generation”
Smaldone A, Shee Y, Kyro G, Farag M, Chandani Z, Kyoseva E, Batista V. Correction to “A Hybrid Transformer Architecture with a Quantized Self-Attention Mechanism Applied to Molecular Generation”. Journal Of Chemical Theory And Computation 2025, 21: 7726-7726. PMID: 40744647, DOI: 10.1021/acs.jctc.5c01204.Commentaries, Editorials and LettersQuantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries
Smaldone A, Shee Y, Kyro G, Xu C, Vu N, Dutta R, Farag M, Galda A, Kumar S, Kyoseva E, Batista V. Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries. Chemical Reviews 2025, 125: 5436-5460. PMID: 40479601, DOI: 10.1021/acs.chemrev.4c00678.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsQuantum machine learningQuantum computationGate-based quantum computersQuantum-classical approachVariational quantum circuitsQuantum neural networkDrug discoveryQuantum circuitsMachine learningContext of drug discoveryMolecular property predictionQuantumMolecular generationProperty predictionNeural networkLearning