A Novel Method for Characterization of Three-Dimensional Reaction Fields Based on Electrostatic and Steric Interactions toward the Goal of Quantitative Analysis and Understanding of Organic Reactions

A novel characterization method named FRAU (Field-characterization for reaction analysis and understanding), which numerically characterizes field around molecules based on electrostatic and steric interactions with pseudoreactant, has been developed for giving numeric measures of factors controlling reactions. FRAU estimates three kinds of features (FRAU features), i.e., extent of reaction field, electrostatic features, and steric features. Power of the FRAU features as discriminators recognizing similarities and differences of characteristics of structures and roles of reagents in reactions have been examined by 39 reagents containing Mg or B atoms. Similarities in these features were analyzed with the help of a self-organizing map (SOM). Good correspondences were found between the features, structures, and the role of the reagents in reaction. The results show abilities of FRAU to give useful numeric characterization of reagents.

[1]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[2]  J. Gasteiger,et al.  Organische Reaktionen mit Hilfe neuronaler Netze klassifiziert: Michael‐Additionen, Friedel‐Crafts‐Alkylierungen durch Alkene und verwandte Reaktionen , 1996 .

[3]  Mark S. Gordon,et al.  General atomic and molecular electronic structure system , 1993, J. Comput. Chem..

[4]  M. G. Hutchings,et al.  Quantification of effective polarisability. Applications to studies of X-ray photoelectron spectroscopy and alkylamine protonation , 1984 .

[5]  T. Kohonen Self-organized formation of topographically correct feature maps , 1982 .

[6]  J. Gasteiger,et al.  Knowledge Discovery in Reaction Databases: Landscaping Organic Reactions by a Self-Organizing Neural Network , 1997 .

[7]  Heng Li,et al.  Selbstorganisierende Neuronale Netze auf Transputern , 1992, Transputer-Anwender-Treffen.

[8]  J. Gasteiger,et al.  Organic Reactions Classified by Neural Networks: Michael Additions, Friedel–Crafts Alkylations by Alkenes, and Related Reactions† , 1996 .

[9]  Johann Gasteiger,et al.  Berechnung der Ladungsverteilung in konjugierten Systemen durch eine Quantifizierung des Mesomeriekonzeptes , 1985 .

[10]  W. L. Jorgensen,et al.  Computer-assisted mechanistic evaluation of organic reactions. 1. Overview , 1980 .

[11]  Kimito Funatsu,et al.  SOPHIA, a Knowledge Base-Guided Reaction Prediction System - Utilization of a Knowledge Base Derived from a Reaction Database , 1995, J. Chem. Inf. Comput. Sci..

[12]  William L. Jorgensen,et al.  Computer-assisted mechanistic evaluation of organic reactions. 12. pKa predictions for organic compounds in Me2SO , 1986 .

[13]  J. Gasteiger,et al.  Automated derivation of reaction rules for the EROS 6.0 system for reaction prediction , 1990 .

[14]  J. Gasteiger,et al.  ITERATIVE PARTIAL EQUALIZATION OF ORBITAL ELECTRONEGATIVITY – A RAPID ACCESS TO ATOMIC CHARGES , 1980 .

[15]  Johann Gasteiger,et al.  Classification of Organic Reactions: Similarity of Reactions Based on Changes in the Electronic Features of Oxygen Atoms at the Reaction Sites1 , 1998, J. Chem. Inf. Comput. Sci..

[16]  R. Cramer,et al.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. , 1988, Journal of the American Chemical Society.