Computational Insights into Reaction Mechanisms and Selectivity in Organic Chemistry
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".
Deadline for manuscript submissions: 28 February 2027 | Viewed by 11
Editor
Interests: computational chemistry; reaction mechanisms; organic reactivity; density functional theory (DFT); reaction selectivity; transition state analysis; molecular modeling; quantum chemical calculations; stereoselectivity; regioselectivity; inorganic chemistry; bioinformatic
Special Issue Information
Dear Colleagues,
Organic chemistry lies at the heart of numerous scientific and technological advances, ranging from pharmaceutical development and materials science to catalysis and sustainable energy applications. Central to this discipline is the understanding of chemical reactivity, reaction pathways, and selectivity, which govern the formation of desired products under specific experimental conditions. Traditionally, mechanistic interpretations in organic chemistry have relied heavily on empirical observations and experimental investigations. However, the increasing complexity of modern synthetic targets has highlighted the need for complementary theoretical approaches capable of providing molecular-level insights into chemical transformations.
Computational chemistry has emerged as a powerful tool for elucidating reaction mechanisms and predicting selectivity in organic reactions. Advances in quantum chemical methods, molecular dynamics simulations, and density functional theory (DFT) calculations have enabled researchers to investigate transient intermediates, transition states, activation barriers, and electronic effects with remarkable accuracy. These computational approaches allow the exploration of mechanistic details that are often inaccessible through experimental techniques alone, thereby bridging the gap between theoretical predictions and laboratory observations.
Reaction selectivity—including regioselectivity, stereoselectivity, and chemoselectivity—plays a critical role in determining the efficiency and practicality of synthetic methodologies. Computational studies provide valuable insights into the energetic and structural factors controlling selectivity, such as orbital interactions, steric effects, solvent influences, and non-covalent interactions. By analyzing potential energy surfaces and electronic properties, computational methods can rationalize experimental outcomes and guide the design of more selective and efficient reactions.
In recent years, the integration of computational modeling with experimental organic chemistry has transformed the development of synthetic strategies. Predictive computational tools have facilitated catalyst optimization, reaction condition screening, and the discovery of novel reaction pathways, significantly reducing experimental costs and accelerating innovation. Furthermore, the application of machine learning and artificial intelligence in computational chemistry is opening new perspectives for automated reaction prediction and mechanistic exploration.
This work focuses on the application of computational methodologies to investigate reaction mechanisms and selectivity in organic chemistry. Through theoretical modeling and electronic structure analysis, the study aims to provide deeper insight into the fundamental factors governing chemical reactivity, thereby contributing to the rational design of efficient and selective organic transformations.
Dr. Alejandro Morales-Bayuelo
Guest Editor
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Keywords
- computational chemistry
- reaction mechanisms
- organic reactivity
- density functional theory (DFT)
- reaction selectivity
- transition state analysis
- molecular modeling
- quantum chemical calculations
- stereoselectivity
- regioselectivity
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