A Novel Subshape Molecular Descriptor

Abstract

Molecules with similar shapes and features often have similar biological activity. Several computational approaches search chemical databases for new leads or templates based on overall molecular shape similarity. However, active molecules often present critical subshapes that are required for binding, which may be missed by comparing overall shape similarity. We present a new approach to compare molecular shapes of different sizes and to calculate subshape similarity. We developed a skeletal representation of the shape which is topologically unrelated to covalent chemical connectivity. This simplifies rotational and translational sampling. We test initial possible alignments by matching similar triangles. This triangle-matching filter rapidly eliminates most geometrically impossible matches. Surviving matches are filtered further in successive stages. These stages involve direction, feature, and shape matching procedures. Our approach is applied to several situations demonstrating lead discovery and evolution.

Accurate prediction of the blood–brain partitioning of a large set of solutes using ab initio calculations and genetic neural network modeling

“…Today, a wide variety of descriptors has been reported to use in QSAR analysis. [36][37][38][39][40] Recent progress in computational hardware and the development of efficient algorithms have assisted the routine development of molecular quantum chemical calculations. Quantum chemical calculations can, in principle, express all of the electronic and geometric properties of molecules and their interactions.…”

STRAPS v1.0: evaluating a methodology for predicting electron impact ionisation mass spectra for the aerosol mass spectrometer

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