|
|
|
|
|
|
|
pete in a very competitive world. Yet gleaning this data from the millions of known compounds is a daunting task. Storage, search, and retrieval of molecular information presents unique challenges to the development of computerized databases, which is a field unto itself [34,35]. |
|
|
|
|
|
|
|
|
Recent advances in molecular biology and protein and nucleic acid sequencing provide other database and data-mining challenges. These techniques now provide vast amounts of data on genomic structure and protein sequences and, it is hoped, will eventually provide the entire human genome. Included in this data will be the sequences of new, currently unknown, protein targets, such as key regulatory enzymes and receptors. A number of new companies have been formed for the purpose of extracting such sequences and a number of large companies have either purchased this information, have entered alliances with the smaller companies, or are developing their own effort. Coordinating this mass of information and providing rapid and convenient access to it requires the development of new software tools and easier use and access of old ones. Even more challenging is the task of shifting through the data to find the most promising pharmaceutical targets since identification and especially biochemical characterization of all of the protein targets in the near future will be impossible. This emerging field of Bioinformatics is making use of established approaches as well as extending these approaches to assist in the tasks of nucleic acid and protein sequence database development and search, protein identification, and protein structure prediction [36,37]. |
|
|
|
|
|
|
|
|
Although CADD is most often thought of as playing a role in drug discovery, the techniques of computational chemistry have also made inroads into other stages of pharmaceutical development. These include the use of structure-activity relationship methods for the prediction of toxicity of intermediates in chemical plants and the use of computer-aided synthesis in development efforts [38]. Although the fields lie beyond this review, computational methods are now routinely used in designing and optimizing chemical plants. Even apart from discovery efforts, molecular databases play an important role in information systems for archiving the large amount of data regarding the structures and biological activities of molecules that accumulates in a pharmaceutical company. |
|
|
|
|
|
|
|
|
V. Where Does CADD Fit Within a Drug Discovery Program? |
|
|
|
|
|
|
|
|
Computational methods do not replace experiment and will not do so. Rather, they can form a valuable partnership with experiment by providing estimates when experiments are difficult, expensive, or impossible and by coordinating the data that experiment provides. The intensity of the specialties that |
|
|
|
|
|