α,β‐Dehydrogenation Adjacent to Sulfur‐ and Phosphorus‐ Containing Compounds
Sun Y, Newhouse T. α,β‐Dehydrogenation Adjacent to Sulfur‐ and Phosphorus‐ Containing Compounds. Angewandte Chemie 2024 DOI: 10.1002/ange.202411859.Peer-Reviewed Original ResearchAllyl methyl carbonateDeuterium incorporation studiesOrganozinc intermediatesMethyl carbonateReaction sequencePhosphorus-containing compoundsSide productsPhosphorus groupsReaction optimizationReactionSulfurDiverse array of substratesArray of substratesDiastereoselectivitiesSubstrateDeuteriumFormationIntermediateCompoundsα,β‐Dehydrogenation Adjacent to Sulfur‐ and Phosphorus‐ Containing Compounds
Sun Y, Newhouse T. α,β‐Dehydrogenation Adjacent to Sulfur‐ and Phosphorus‐ Containing Compounds. Angewandte Chemie International Edition 2024, e202411859. PMID: 39264684, DOI: 10.1002/anie.202411859.Peer-Reviewed Original ResearchAllyl methyl carbonateDeuterium incorporation studiesOrganozinc intermediatesMethyl carbonateReaction sequencePhosphorus-containing compoundsSide productsPhosphorus groupsReaction optimizationReactionSulfurDiverse array of substratesArray of substratesDiastereoselectivitiesSubstrateDeuteriumFormationIntermediateCompoundsSite-specific template generative approach for retrosynthetic planning
Shee Y, Li H, Zhang P, Nikolic A, Lu W, Kelly H, Manee V, Sreekumar S, Buono F, Song J, Newhouse T, Batista V. Site-specific template generative approach for retrosynthetic planning. Nature Communications 2024, 15: 7818. PMID: 39251606, PMCID: PMC11385523, DOI: 10.1038/s41467-024-52048-4.Peer-Reviewed Original ResearchComplexity of chemical spaceRetrosynthetic planningGenerative machine learning methodsChemical spaceTarget compoundsChemical transformationsChemical synthesisReaction templatesSynthetic pathwaySmall moleculesGenerative machine learningMoleculesReactionMachine learning methodsSynthesisUser selectionSynthonsLearning methodsMachine learningGeneration approachReactantsRetrosynthesisInterconversionCompoundsLigand-Based Principal Component Analysis Followed by Ridge Regression: Application to an Asymmetric Negishi Reaction
Kelly H, Sreekumar S, Manee V, Cuomo A, Newhouse T, Batista V, Buono F. Ligand-Based Principal Component Analysis Followed by Ridge Regression: Application to an Asymmetric Negishi Reaction. ACS Catalysis 2024, 14: 5027-5038. DOI: 10.1021/acscatal.3c06230.Peer-Reviewed Original ResearchPd-catalyzed Negishi cross-coupling reactionsC-C bond-forming reactionsNegishi cross-coupling reactionsP-chiral monophosphorus ligandsCross-coupling reactionsP-stacking interactionsBond-forming reactionsElectronic descriptorsNegishi reactionMonophosphorus ligandsCatalytic systemChemical spaceEnantioselectivityChemical understandingLigandReactionSelective inversionDescriptorsRidge regressionStericallyChemicalPrincipal component analysisMechanistic knowledgeRidge regression modelElectronComprehensive Mechanistic Analysis of Palladium- and Nickel-Catalyzed α,β-Dehydrogenation of Carbonyls via Organozinc Intermediates
Bodnar A, Szewczyk S, Sun Y, Chen Y, Huang A, Newhouse T. Comprehensive Mechanistic Analysis of Palladium- and Nickel-Catalyzed α,β-Dehydrogenation of Carbonyls via Organozinc Intermediates. The Journal Of Organic Chemistry 2024, 89: 3123-3132. PMID: 38377547, PMCID: PMC11000628, DOI: 10.1021/acs.joc.3c02572.Peer-Reviewed Original ResearchOrganozinc intermediatesOrganic synthesisC-C bond formationElectron-withdrawing groupsReactivity of PdAdjacent electron‐withdrawing groupConversion of alkanesAnalysis of palladiumNickel catalysisDFT calculationsKIE experimentsStoichiometric reactionBond formationReaction typesSmall moleculesComprehensive mechanistic analysisPalladiumDegree of unsaturationCentral transformationEfficient strategyIntermediateRate studiesReactionSynthesisPd