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Quantitative Structure–Selectivity Relationships in Enantioselective Catalysis: Past, Present, and Future
journal contribution
posted on 2019-12-27, 21:44 authored by Andrew
F. Zahrt, Soumitra V. Athavale, Scott E. DenmarkThe dawn of the 21st century has brought with it a surge
of research
related to computer-guided approaches to catalyst design. In the past
two decades, chemoinformatics, the application of informatics to solve
problems in chemistry, has increasingly influenced prediction of activity
and mechanistic investigations of organic reactions. The advent of
advanced statistical and machine learning methods, as well as dramatic
increases in computational speed and memory, has contributed to this
emerging field of study. This review summarizes strategies to employ
quantitative structure−selectivity relationships (QSSR) in
asymmetric catalytic reactions. The coverage is structured by initially
introducing the basic features of these methods. Subsequent topics
are discussed according to increasing complexity of molecular representations.
As the most applied subfield of QSSR in enantioselective catalysis,
the application of local parametrization approaches and linear free
energy relationships (LFERs) along with multivariate modeling techniques
is described first. This section is followed by a description of global
parametrization methods, the first of which is continuous chirality
measures (CCM) because it is a single parameter derived from the global
structure of a molecule. Chirality codes, global, multivariate descriptors,
are then introduced followed by molecular interaction fields (MIFs),
a global descriptor class that typically has the highest dimensionality.
To highlight the current reach of QSSR in enantioselective transformations,
a comprehensive collection of examples is presented. When combined
with traditional experimental approaches, chemoinformatics holds great
promise to predict new catalyst structures, rationalize mechanistic
behavior, and profoundly change the way chemists discover and optimize
reactions.
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Keywords
enantioselective catalysisMIFCCMchemoinformaticEnantioselective Catalysisparametrization methodsparametrization approachesmultivariate modeling techniqueschirality measuresenantioselective transformationsdescriptor classmultivariate descriptorsQSSRLFER21 st centuryenergy relationshipscatalyst designChirality codesinteraction fieldsSubsequent topicsway chemistsapplicationcatalyst structures
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