Accelrys Software, Inc.

The Penn State Research Foundation

Kenneth M Merz, Jr

David J Diller

Marvin Waldman

Steven L Dixon

Kaushik Raha

Ailan Cheng

The present invention provides for the first time a quantum mechanics-based method for scoring protein-ligand interactions and binding affinity predictions, using quantum mechanical Hamiltonians and/or a combined quantum mechanical/molecular mechanical approach, and Poisson-Boltzmann (PB)-based solvation methods. Also provided is a method for using quantum mechanics to describe the enthalpic and solvation effects of binding. The method comprises comparing the calculated binding affinities to experimental values in order to measure the success of the method. The methods disclosed herein may further be used to score protein and drug or protein and inhibitor interactions. The present method can predict the free energy of binding of protein-ligand complexes with high accuracy so as to enable lead optimization, thus serving as a powerful tool in computational drug design.

Quantum mechanics based method for scoring protein-ligand interactions

Molecules are represented as one dimensional strings of atoms having a linear position and a width. One dimensional representations are compared to assess the likelihood of similarity in chemical behavior.

One dimensional molecular representations

A high-throughput molecular docking facility is presented for screening combinatorial libraries to identify binding ligands and ultimately pharmaceutical compounds. The facility employs a pre-docking conformational search to generate multiple solution conformations of a ligand. The molecular docking facility includes: generating a binding site image of the protein, the binding site image having multiple hot spots; matching hot spots of the binding site image to atoms in at least one solution conformation of the multiple solution conformations of the ligand to obtain at least one ligand position relative to the protein in a ligand-protein complex formation; and optimizing the at least one ligand position while allowing translation, orientation and rotatable bonds of the ligand to vary, and while holding the protein fixed.

Molecular docking technique for screening of combinatorial libraries

The present teachings describe a solubility prediction approach that is based, in part, upon quantitative-structure property relationships (QSPR). In various embodiments, the solubility prediction methodology comprises identifying a reduced descriptor set from which a solubility equation is derived. The descriptors used in the solubility equation are based upon simplified structural and molecular features which facilitate researcher understanding and solubility model refinement. Moreover, the present teachings provide solubility prediction relationships that may be used to rapidly screen large libraries or collections of compounds.

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Port Matilda, PA, United States of America

Kenneth M Merz, Jr