Enhancing Protein-Drug Binding Prediction

Simulating molecular dynamics

Predicting protein-drug binding affinities

life sciences and ehealth

Enhancing Protein-Drug Binding Prediction

Enhancing Protein-Drug Binding Prediction

Predicting protein-drug binding affinities

Drugs typically exert their effects by binding to proteins. Accurate methods are therefore needed to predict protein-drug binding affinities or free energies. However, efficiently computing binding free energies is difficult, and affinity prediction is typically computationally too demanding for proteins of large flexibility. These include many proteins of high relevance to pharmaceutical scientists and toxicologists, such as large families of enzymes involved in drug safety or targeted by anti-cancer drugs.

Combining advanced modelling and eScience technologies

Overcoming current scientific and methodological challenges

As a remedy, this project aims on efficient binding affinity prediction for flexible proteins on an unprecedented scale, by introducing and combining advanced modelling and eScience technologies. For that purpose smart algorithms, molecularsimulation methods, statistical approaches, and efficient computing and data handling techniques will be developed, to overcome current scientific and methodological challenges. These include appropriate and efficient conformational sampling, identification of relevant protein structures, and automatically assigning model interaction parameters and applicability domains.

Binding and affinity predicion plays a key role in cancer therapy or drug safety

eScience workflow for discovery, design and optimization

In this project methodologies will be realized as a heterogeneous efficient computing eScience workflow. For accurate calibration and extensive validation of these models, availability and handling of large sets of accurate experimental data is crucial. These will be available via direct collaborators in academia, TNO and industry (e.g., Bayer), who have shown strong interest into the workflow this project aims to make open source. The eScience workflow will enable accurate and efficient binding and affinity prediction in applied and industrial setting, e.g. in the context of discovery, design and optimization of drugs that bind to flexible proteins with key roles in cancer therapy or drug safety.

Image: Drug binding to receptor protein by Sam Hertig - http://www.samhertig.ch/blog/wp-content/uploads/2015/10/m4v1m2.jpg

eScience Coordinator Dr. Rena Bakhshi

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