Although medicinal research has made tremendous advancements in the past decades, the expense and time associated with today’s drug design process is still overwhelming and the time it takes for a conceived lead compound to emerge as a marketed drug is well above a decade. Drug companies has invested large sums of money and time in high throughput screening (HTS), which still responds with low hit rates. Avoiding unproductive syntheses is a worthy goal not only in terms of cost and time efficiency but also environmental responsibility - as the amount of waste products from organic syntheses are greatly reduced. We believe a computational program that could provide us with highly accurate predictions of biological activity will be one solution to this critical problem.
In the present project, computational, organic and biological chemists team up in a feedback loop involving software development, computer-assisted drug design, modern chemical synthesis, and biochemical testing. Within this system, group members follow the lead compound from its moment of conception to its final performance in biochemical testing. The outcomes of this compound’s development are then reported to those members developing the software, and modifications or improvements in the software occur before the whole cycle begins again. The vested interest that the group shares for each prospective candidate helps to expedite the feedback process. We have decided to focus on three particular enzymes – Dipeptidyl Peptidase IV (DPP-IV), Cyclophilin A (Cyp A), and Prolyl Oligopeptidase (POP) – implicated primarily in diabetes, AIDS, and Alzheimer’s disease, respectively. These enzymes have been also implicated in cancer (DPP-IV) and rheumatoid arthritis (Cyp A) research.
At the heart of this medicinal chemistry project is our innovative software, FITTED (Flexiblity Induced Through Targeted Evolution) which seeks to improve current drug design by accurately predicting the biological activity of proposed target compounds. We are developing this software in the hopes that in the future it can be used universally and applied to a large scope of physiological macromolecules, greatly improving efficiency in the world of drug design. The software we are inventing recognizes some of the most challenging elements of macromolecule structure and environment; molecular flexibility and solvation effects are two realistic aspects of chemical systems that are repeatedly ignored or greatly simplified in the use and programming of many other currently available modeling software.
Our immediate goals for the software include the improvement of our genetic algorithm for docking to flexible proteins, the development of a coarse-grained / knowledge-based force field, and the inclusion of explicit bridging water molecules. Much progress has been made so far in all these areas, and all the while the software is being evaluated for its actual success in real systems outside the computer. Our first generation of synthesized compounds has coincided with the preliminary and non automated version of our software; the next generation of compounds will be in response to the revised versions, and so on. The very first synthesized compounds are presently evaluated for their inhibitory potency. Throughout the project, there will be constant dialogue between the programmers and the medicinal chemists which will help to improve both the candidate compounds and the actual software being produced.