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A Self-Organizing Algorithm for Molecular Alignment and Pharmacophore Development

Summary: A Self-Organizing Algorithm for Molecular Alignment
and Pharmacophore Development
Johnson & Johnson Pharmaceutical Research and Development, L.L.C., 665 Stockton Drive,
Exton, Pennsylvania 19341
Received 23 July 2007; Revised 29 August 2007; Accepted 11 September 2007
DOI 10.1002/jcc.20854
Published online 12 November 2007 in Wiley InterScience (www.interscience.wiley.com).
Abstract: We present a method for simultaneous three-dimensional (3D) structure generation and pharmacophore-
based alignment using a self-organizing algorithm called Stochastic Proximity Embedding (SPE). Current flexible
molecular alignment methods either start from a single low-energy structure for each molecule and tweak bonds or
torsion angles, or choose from multiple conformations of each molecule. Methods that generate structures and align
them iteratively (e.g., genetic algorithms) are often slow. In earlier work, we used SPE to generate good-quality 3D
conformations by iteratively adjusting pairwise distances between atoms based on a set of geometric rules, and
showed that it samples conformational space better and runs faster than earlier programs. In this work, we run SPE
on the entire ensemble of molecules to be aligned. Additional information about which atoms or groups of atoms in
each molecule correspond to points in the pharmacophore can come from an automatically generated hypothesis or
be specified manually. We add distance terms to SPE to bring pharmacophore points from different molecules closer
in space, and also to line up normal/direction vectors associated with these points. We also permit pharmacophore
points to be constrained to lie near external coordinates from a binding site. The aligned 3D molecular structures are


Source: Agrafiotis, Dimitris K. - Molecular Design and Informatics Group, Johnson & Johnson Pharmaceutical Research and Development


Collections: Chemistry; Computer Technologies and Information Sciences