Detection of molecular interaction field similarities for the rational drug design of multi-functional inhibitors
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OverviewThe 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 work by modulating the function of target proteins. Other proteins may also be affected due to similarities between their binding-sites. This unintended action may at times lead to the serendipitous discovery of new applications for the particular drug, but often it leads to side effects. The detection of such similarities can lead to the prevention of side effects and be used to develop multi-functional drugs, that is, drugs that interact with more than one target on purpose. We have developed a technique for the detection of 3D atomic similarities. However, rather than the specific relative position of atoms in the surface of binding-sites, their combined effect in terms of interactions (molecular interaction field) is more important in defining what small-molecule may bind to the given binding-site. In other words, distinct atomic configurations may produce similar molecular interaction fields. The technique (IsoMIF) that we propose will detect molecular interaction field similarities. The method will be validated using experimental data within a set of 26 human proteins over-expressed in triple negative breast cancer, a devastating form of breast cancer unresponsive to existing therapies. This will allow us define targets subsets as part of a multi-target approach, while at the same time preventing the targeting of unintended proteins. IsoMIF will have applications in the large-scale analysis of binding-site similarities with application to the rational design of drugs and the prediction of protein function.
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