We are soliciting papers, abstracts and referees for a special session on cheminformatics that will concentrate on the development and applications of molecular similarity and diversity methods for accelerated drug discovery. This track will be held as part of the Pacific Symposium on Biocomputing (PSB-00), Hawaii, January 2000.

Background and Areas of Interest.

We live in the age of "–ics". Genomics, proteomics, genetics, bioinformatics, cheminformatics are a few examples of recent terms that refer to relatively new and rapidly growing areas of both academic and industrial research. This growth implies an unprecedented accumulation of biomolecular information stored in ever growing databases. These include both gene databases and various databases of organic molecules, which contain millions of individual molecular entries. All these molecular information has to be stored, manipulated, understood and used, in a rational way, in designing new drugs. Computational analysis of molecular diversity and similarity, database mining, combinatorial library design has become one of the most vital areas of biocomputing.

It is well known that many genes and their products have an interesting yet unidentified function, and the analysis of sequence-structure-function relationships has been a traditional area of interest of previous PSB conferences. Perhaps it is less obvious but experimental medicinal chemists face, in many respects, the same type of problems as experimental biologists. Practically every chemical has certain, frequently unknown, biological effect (cf. gene sequences with unknown function). There is a huge array of chemical molecules (cf. millions of genes), many of which could potentially be drugs, but their specificity against a particular biological target is yet to be determined (as well, in many cases, as the target itself). The computational aspects of macromolecular vs. chemical database analysis appear strikingly common yet complementary. Indeed, the exact challenge is that of matchmaking: how to find the right drugs for the right targets? Both computational chemists and computational biologists address this challenge by developing fast and accurate methods of biomolecular database analysis and using these analyses to enhance our ability to discover or design lead molecules of pharmaceutical significance. These approaches rely on our understanding of three-dimensional structure of both organic and biological macromolecules and the development of rigorous quantitative models that explain experimental structure-activity (for organic molecules) and sequence-structure-function (for macromolecules) relationships. This similarity of computational aspects of macromolecular vs. chemical computing makes it especially interesting to include a session on the analysis of chemical diversity and similarity within the framework of PSB2000.

The proposed session will address novel methods and developing ideas in the areas of chemical database analysis and bioactive structure prediction. More specifically, we plan to discuss novel metrics and functions for the description and comparison of organic molecules, current approaches to diversity and similarity sampling of molecular databases, combinatorial library design applications, and quantitative modeling of structure-activity relationships (QSAR).

Full paper submission and publication is required for oral presentations. Each full paper will be reviewed by at least three independent referees. PSB publications are indexed on Medline and should be viewed as short journal articles. Accepted papers will be published in a hard-bound archival proceedings, and the best of these will be presented orally to the entire conference. Poster and demo sessions are available for researchers who wish to exhibit their work, but do not wish to prepare a full paper. Researchers participating in the poster session should submit an abstract.

All papers must be submitted to altman@smi.stanford.edu in electronic format. Papers should be submitted by July 12. Please format your paper according to instructions found at ftp://ftp-smi.stanford.edu/pub/altman/psb/. Papers are limited to 12 pages within this format. Each paper must be accompanied by a cover letter. The cover letter must state the following:

* The email address of the corresponding author

* The specific PSB session that should review the paper or abstract

* The submitted paper contains original, unpublished results, and is not currently under consideration elsewhere.

* All co-authors concur with the contents of the paper.

Travel Support

In previous years, PSB has been able to offer partial travel support to a number of participants. See the PSB website for more information and travel application forms.

For additional information contact:

Professor Robert S. Pearlman
Laboratory for Molecular Graphics
and Theoretical Modeling
College of Pharmacy
University of Texas
Austin, TX 78712
Tel. 512-471-3383

Email: PEARLMAN@VAX.PHR.UTEXAS.EDU

Alexander Tropsha, Ph.D.
Associate Professor, Director
the Laboratory for Molecular Modeling
CB # 7360, Beard Hall
School of Pharmacy
University of North Carolina
Chapel Hill, NC 27599-7360
Tel. (919) 966-2955
Fax (919) 966-0204

Email: alex_tropsha@unc.edu