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Three-Dimensional Shape Modeling and Analysis of Brain Structures

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Shape-based virtual screening with volumetric aligned molecular shapes.

David Ryan Koes¹, Carlos J Camacho

¹Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania.

Journal of Computational Chemistry

|July 23, 2014

Summary

This summary is machine-generated.

We introduce Volumetric Aligned Molecular Shapes (VAMS), a novel method for shape-based virtual screening. VAMS efficiently screens millions of molecular shapes, accelerating drug discovery by prefiltering candidates for complex algorithms.

Keywords:

GSS tree molecular shape shape constraints shape indexing virtual screening

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Area of Science:

Computational Chemistry
Cheminformatics
Drug Discovery

Background:

Shape-based virtual screening is crucial for identifying ligands with similar molecular shapes and functions.
Existing methods can be computationally intensive, necessitating efficient prefiltering strategies.

Purpose of the Study:

To introduce and evaluate Volumetric Aligned Molecular Shapes (VAMS), a new shape-based virtual screening method.
To demonstrate VAMS's effectiveness as a prefilter for accelerating computationally demanding search algorithms.

Main Methods:

VAMS utilizes efficient data structures for encoding and searching molecular shapes.
A novel minimum/maximum shape constraint query enables precise molecular shape specification.
Performance was benchmarked against two other algorithms using 102 protein targets and over 32 million molecular shapes.

Main Results:

VAMS demonstrated effective shape-based virtual screening capabilities.
The method proved successful in prefiltering molecular shapes to accelerate subsequent analyses.
VAMS searches millions of shapes efficiently, with constraint searches completing in fractions of a second.

Conclusions:

VAMS offers a competitive performance-to-runtime trade-off compared to existing algorithms.
The VAMS method is a valuable tool for accelerating virtual screening in drug discovery.
Its efficient shape constraint queries make it highly suitable for large-scale molecular shape analysis.