Sharing chemical information without sharing chemical structure.

Studies to assess the risks of revealing chemical structures by sharing various chemical descriptor data are presented. Descriptors examined include "Lipinski-like" properties, 2D-BCUT descriptors, and a high-dimensional "fingerprint-like" descriptor (MACCs-vector). We demonstrate that unless sufficient precautions are taken, de novo design software such as EA-Inventor is able to derive a unique chemical structure or a set of closely related analogs from some commonly used descriptors. Based on the results of our studies, a set of guidelines or recommendations for safely sharing chemical information without revealing chemical structure is presented. A procedure for assessing the risk of revealing chemical structure when exchanging chemical descriptor information was also developed. The procedure is generic and can be applied to any chemical descriptor or combination of descriptors and to any set of structures to enable a decision about whether the exchange of information can be done without revealing the chemical structures.

GSSI, a general model for solute-solvent interactions. 1. Description of the model.

A novel, semiempirical approach for the general treatment of solute-solvent interactions (GSSI) was developed to enable the prediction of solution-phase properties (e.g., free energies of desolvation, partition coefficients, and membrane permeabilities). The GSSI approach is based on the principle that all solution-phase processes can be modeled in terms of one or more gas-to-solution transfer processes. The free energy of each gas-to-solution transfer process is calculated as the sum of the free energy of cavity formation and the free energy of solute-solvent interaction. The solute's contributions to these free energies are modeled on the basis of various quantities computed from the solute's three-dimensional (3D) structure, whereas the solvent's contributions are modeled by empirically determined regression coefficients. More specifically, the free energy of cavity formation is modeled on the basis of the total solvent-accessible surface area of the solute. The enthalpy of solute-solvent interaction is modeled on the basis of intermolecular interaction potentials calculated at many uniformly distributed points on the solvent-accessible surface of the solute. The entropy of solute-solvent interaction is modeled on the basis of an effective number of rotatable bonds in the solute and by the regression coefficients characteristic of the solvent. The potential utility of the GSSI approach was demonstrated by modeling the free energy of gas-to-solution transfer for 111 solutes in water, 250 solutes in hexadecane, and 84 solutes in octanol.

A novel approach for identifying the surface atoms of macromolecules.

A significant number of atoms lie buried beneath the "molecular surface" of proteins and other biologic macromolecules. Interactions between ligands and these macromolecules are dominated by interactions with the "surface atoms". Although interactions with the "buried" or interior atoms of the macromolecule certainly contribute to the total intermolecular interaction energy, many computer-assisted drug design (CADD) strategies can benefit from the identification of those atoms "on the surface" of proteins and other macromolecules. We have developed a simple, yet novel method to distinguish the surface atoms of macromolecules from the interior atoms which is based on computing the atomic contributions to the solvent-accessible surface (SAS) area. This report describes that method and demonstrates that it compares very favorably with four alternative methods.