Jie J Liang

US Patent:

20030149537, Aug 7, 2003

Filed:

Nov 27, 2002

Appl. No.:

10/306296

Inventors:

Thomas Binkowski - Wheaton IL, US
Larissa Adamian - Naperville IL, US
Jie Liang - River Forest IL, US

International Classification:

G06F019/00

US Classification:

702/027000

Abstract:

Structural alignment methods are described that compare the sequences of two or more structural features of molecules. The methods provide for a rigorous statistical analysis that can detect structural similarities in molecules regardless of the similarity in their primary sequences. Thus, the methods can be used to predict and explain functional properties of molecules from their three-dimensional conformation. The methods use databases of different structural features against which a query sequence can be searched. By combining the search results from the various databases, the functional properties of molecules can be predicted and serve as a basis for the efficient design of ligands, substrate analogues, inhibitors or pharmaceutical species thereof.

US Patent:

61820164, Jan 30, 2001

Filed:

Aug 22, 1997

Appl. No.:

8/918624

Inventors:

Jie Liang - King of Prussia PA
Herbert Edelsbrunner - Champaign IL

International Classification:

G01N 3350

US Classification:

702 22

Abstract:

A molecular classification method is based on a space filling description of a molecule. The three dimensional body corresponding to the space filling molecular structure is divided into Voronoi regions to provide a basis for efficiently processing local structural information. A Delaunay triangulation provides a basis for systematically processing information relating to the Voronoi regions into shape descriptors in the form of topological elements. Preferably, additional shape and/or property descriptors are included in the classification method. The classification methods generally are used to identify similarities between molecules that can be used as property predictors for a variety of applications. Generally, the property predictions are the basis for selection of compounds for incorporation into efficacy evaluations.