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Updated: Jun 19, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Published on: April 8, 2020

Evaluation of geometric complementarity between molecular surfaces using compactly supported radial basis functions.

Luis A Diago¹, Ernesto Moreno

¹Department of Mechanical Science and Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguroku, PO Box 152-8550, Tokyo, Japan. diago.l.aa@m.titech.ac.jp

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|October 31, 2009

Summary

This study introduces a new scoring function for molecular docking using Compactly Supported Radial Basis Functions (CSRBF). The CSRBF-based function improves the accuracy of identifying correct docking results, reducing false positives in simulations.

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Area of Science:

Computational chemistry
Drug discovery
Bioinformatics

Background:

Molecular docking is crucial for drug discovery, but distinguishing true positives from false positives remains a challenge.
Scoring functions are essential for ranking docking simulation results, with ongoing development for improved accuracy.

Purpose of the Study:

To develop a novel analytical scoring function for molecular docking using Compactly Supported Radial Basis Functions (CSRBF).
To enhance the ability of molecular docking algorithms to discriminate between correct and false positive results.

Main Methods:

Employed Compactly Supported Radial Basis Functions (CSRBF) to generate analytical representations of molecular surfaces.
Integrated these CSRBF-based molecular surface representations into a new scoring function for molecular docking.
Applied the new scoring function to evaluate results from the DOCK program.

Main Results:

The proposed CSRBF-based scoring function demonstrated superior ranking of docking solutions compared to the native contact scoring function of DOCK.
The new method effectively improved the discrimination between correct and false positive docking results.

Conclusions:

The developed analytical scoring function based on CSRBF offers a reliable and efficient method for filtering results in large-scale molecular docking simulations.
This CSRBF approach can be readily integrated into existing docking software to enhance simulation accuracy.