Detecting 3-D Atomic Similarities

Detection of molecular interaction field similarities for the rational drug design of multi-functional inhibitors

Competition: EXPLORE Program 2011
Funding: $300,000 / 2 years
Beginning: December 2011
Completed project
The aim of this project is to develop and validate a computational program to detect similarities in the binding-sites of drugs. This innovative approach may have applications in the design of drugs and the prediction of protein function.

Overview

The aim of this project is to develop and validate a computational programto detect similarities in the binding-sites of drugs. This innovative approach may have applications in the design of drugs and the prediction of protein function.

Drugs act by modulating the function of target proteins. However, additional off-site non-target proteins may also be affected due to similarities between binding sites. This unintentional action may lead to the serendipitous discovery of new applications for a particular drug, but equally it can result in unwanted safety concerns. Detection of such similarities early in the process of drug discovery may prevent deleterious side effects. On the other hand, rationally designed multifunctional drugs that interact with more than one target may equally be designed upfront with a multitude of potential applications. To achieve this level of specificity in drugs, Dr. Najmanovich proposed to develop a technique for detection of 3D atomic similarities. Rather than limiting the focus on the specific relative position of atoms in the surface of binding-sites, a more global vision of the combined total interactions (termed Molecular Interaction Field; MIF ) is considered critical for selective rational drug design. This permits the identification of distinct atomic configurations across families that produce similar MIFs.

The novel platform will be validated using existing and newly generated experimental data across protein families, and with a subset of human protein kinases over-expressed in triple negative breast cancer, a devastating form of breast cancer that is unresponsive to existing therapies. With such kinases, experimental differential scanning fluorometry binding profile similarities will be compared to MIF similarities. In addition MIF makes it possible to detect off-family potential crossreactivity targets which can be used for rational drug design. Overall, the program will have global application in the large-scale analysis of binding site similarities leading to rational selective design of drugs based on predicted protein functional binding sites.

Impact on the drug discovery process

  • Predict off-target toxicities early in the drug discovery process.
  • Reposition approved drugs in new unmet medical indications.
  • Identify novel drugs with multi-therapeutic opportunities.

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