ChemaPhore can dock one molecule at a time, but its full power comes into play for virtual screening of compound libraries. When we analyze data, we include not only scores and results from a single one-docking run, but look at all results and data available, possibly including experimental results for all compounds in a library. Scoring includes detailed information about the specific binding site of a target, and, to some extent, its flexibility, adds Dr. Treutlein.
We are not really focused on predicting exact binding affinities of single molecules, but on the question of how to make the most out of the available databoth virtual and realto help enhance the compounds, Dr. Burns says. Cytopias synthetic chemistry is focused on high-value compounds. When comparing efficiency at predicting hits with ChemaPhore versus actual wet-screening data, efficiencies have ranged from two- to more than ten-fold, depending on the diversity of the screen set examined.
De Novo Pharmaceuticals (www.denovopharma.com) is removing some of the inherent uncertainties by incorporating protein flexibility and chemical tractability enhancements in Reflex, the new incarnation of SkelGen. Designed for work in-house and with collaborative partners, Reflex incorporates flexibility, selectivity, and improved assessments of ligands, thus allowing a schema to be produced to determine how the compound can be synthesized. In the kinase family, for example, Reflex has helped develop specific ligands for each known ligand binding site and for promiscuous ligands throughout the entire family, says Nikolay Todorov, Ph.D., principal scientist.
So, if you have a related protein, you can design a compound that is selective for one and not the others, adds Philip Dean, Ph.D., CSO. As you build up a small compound structure in a site, you allow the site to flex on the fly, unlike previous rigid models, says Dr. Dean. Reflex handles induced fit designs, which allows these models to change throughout their development.
Competitive Workflow, by Cyprotex (www.cyprotex.com), takes a different approach to in silico design by modeling and automating what people actually do, according to David Leahy, Ph.D., consultant and former CTO for Cyprotex.
This software architecture provides exhaustive modeling by implementing every step, multiple times and reacting to changes. New data or methods cause the whole process to reactivate. When new ADME data is added, for example, the whole process is rerun automatically, says Dr. Leahy. Modeling is tightly coupled with our experimental data so is specific to chemotype. It captures the expertise of human scientists in software and is a learning environment, so successful methods are reinforced. We think we can extend that application to most in silico design processes.