Chapter 10
Genetic Algorithm Based Method To Design a Primary Screen for Antirhinovirus Agents 1
2
3
Computer-Aided Molecular Design Downloaded from pubs.acs.org by YORK UNIV on 12/05/18. For personal use only.
E. P. Jaeger , D. C. Pevear, P. J. Felock , G. R. Russo , and A. M . Treasurywala Sterling Winthrop, Inc., 1250 South Collegeville Road, P.O. Box 5000, Collegeville, PA 19426-0900
The human rhinoviruses are the major etiological agents of the common cold in man. Because there are over 100 serologically distinct human rhinoviruses, the design of a common cold treatment requires activity against a broad spectrum of these viruses. It is impractical to test all molecular candidates against all rhinovirus serotypes. Computer methodologies were employed to select a subset of serotypes whose sensitivity to antiviral compounds correlated with the sensitivity of the larger group of viruses. The process involved three steps: i) defining a set of existing molecules which spanned the structural diversity of known human rhinovirus inhibitors; ii) obtaining experimental observations of activity of each of the selected molecules against the larger set of rhinovirus serotypes; and iii) using a genetic algorithm to sort through the resulting biological data and select the serotypes for the new primary screen. The selected subset of viruses provided significantly improved sensitivity prediction over an existing subset of viruses. The method is generally applicable to cases where spectrum or specificity of activity against macromolecular targets is desired. One of the most common questions asked of computational chemistry groups in industry concerns measures of their usefulness in the mainstream activity of designing more specific, potent and useful agents. These questions are basically centered around the issue of impact; i.e., how much impact is the computational effort having on the project. We offer here an example of a rather unique way in which computational efforts have had impact on an ongoing project: the design of potent broad-spectrum antirhinoviral agents. In this case, a result or activity is said to have impact if it causes the project team to do or plan something differendy than what it would in the absence of that result or activity. This impact can be manifested in an explicit project team decision to follow or not to follow a specific course of action. 1
2
3
Current address: 3-Dimensional Pharmaceuticals, 3700 Market Street, Philadelphia, P A 19104 Current address: Merck Research Laboratories, Division of Merck and Company, Inc., West Point, P A 19486 Current address: Virogenetics Corporation, 465 Jordan Road, Troy, N Y 12180 0097-6156/95/0589-0139$12.00/0 © 1995 American Chemical Society
140
COMPUTER-AIDED MOLECULAR DESIGN
There has been an ongoing interest at Sterling Winthrop to design potent agents with a broad spectrum of activity against the major etiologic agents of the common cold, the human rhinoviruses (HRVs). To date more than a hundred strains of HRVs have been isolated and cultured. This large number of viruses made it impractical to screen all new compounds against all of the known serotypes even with high capacity robotic assays. The problem therefore, was to find a smaller set of serotypes that could form the primary screen. The qualities of this subset were: (i) it should be small enough to accomodate the screening of all of the newly synthesized compounds; (ii) it had to be picked in such a way that the results from this subset formed a reliable predictor of the activity that would be found in more complete secondary testing; and (iii) it had to work for the range of structural diversity of compounds that had been synthesized during the project history and it must be able to work for relevant chemical series that might be synthesized in the future. The issue here is not uncommon in the design of primary and secondary biological assays. The screen should not be so specialized to a given chemical series that it would miss good leads from a divergent series of compounds. The approach that we have devised to address this problem is a generic one that holds significant promise not only for the design of more potent H R V inhibitors, but also for any system which would benefit from subset screening. In this report the methods used to address this problem are detailed so as to bring focus on a novel impact that computational methods have made to the progress of a team and also to inspire the wider use of these techniques. The series of compounds that have been synthesized in this project bind in a hydrophobic pocket in the H R V capsid and inhibit the attachment of the virus to the cellular receptor and/or the release of the viral R N A into the cell cytoplasm (7-5). The difficulty of designing broad-spectrum active compounds hinges on the fact that these pockets have slightly different sizes and shapes for each of the serotypes (
