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GAČR 14-29032P
Efficient chemical space exploration using multi-objective optimization
2014 - 2016
Recently, we have developed a method for a systematic generation of the chemical space lying between a given pair of small organic molecules. The intended use follows the similar property principle stating that "similar compounds have similar properties". Thus, if a pair of molecules shows a similar function molecules close in the chemical space should behave alike.
Our approach has two major drawbacks which we would like to tackle in the proposed project - 1) a path (subspace) between the input molecules is not guaranteed to be found and 2) the exploration process is driven purely by structure and does not take into account physicochemical and biological properties of generated compounds. In order to solve the first problem we propose to use an approach inspired by scaffold hopping. We will utilize multiple scaffold types retaining different levels of structural information to reduce the complexity of the chemical space. We propose that a path in a less complex chemical space is more likely to be identified. In the second part of the project we will modify the exploration process so it will not be performed in the structural space but in the biologically more meaningful space of features such as, e.g., ADME/Tox properties. This will be done by projecting starting molecules into multidimensional space of the physicochemical and/or biological properties, and using multi-objective optimization to drive the exploration towards the desired optima. Finally, we propose a way how to mix scaffold hopping and bioactivity based exploration into a novel chemical space exploration approach.
Principal investigator : David Hoksza