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Pattern recognition strategies for molecular surfaces. I. Pattern generation using fuzzy set theory.

Thomas E Exner¹, Matthias Keil, Jürgen Brickmann

¹Department of Chemistry, Mathematical Chemistry Research Unit, University of Saskatchewan, 110 Science Place, Saskatoon, SK, Canada, S7N 5C9.

Journal of Computational Chemistry

|July 13, 2002

Summary

A novel method characterizes molecules using topographical and electrostatic surface properties. This approach segments molecular surfaces into patches for analyzing similarities and complementarity between molecules.

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Area of Science:

Computational chemistry
Molecular modeling
Cheminformatics

Background:

Traditional molecular characterization methods often lack detailed surface property analysis.
Understanding local molecular features is crucial for predicting interactions and similarities.

Purpose of the Study:

To introduce a new method for molecular characterization based on molecular surface properties.
To enable analysis of partial similarities and molecular complementarity.

Main Methods:

Utilizing topographical properties, electrostatic potential, local lipophilicity/hydrophilicity, and hydrogen bond density.
Segmenting molecular surfaces into overlapping patches representing local features.
Developing a model approach for molecular surface characterization.

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Main Results:

The method provides a detailed characterization beyond atomistic resolution.
Patches represent characteristic local molecular features effectively.
Demonstrated potential for analyzing molecular similarities and complementarity.

Conclusions:

The patch-based representation offers a versatile approach for molecular analysis.
This method facilitates a general understanding of molecular complementarity.
Further applications of this patch representation will be explored in subsequent studies.