Cloud-based simulation of the binding capacities of target drug compounds

The journey for a drug from invention to market is a long one. It has been estimated that the time required to develop a new drug de novo ranges between 10 and 17 years; that is, if it ever makes it. The chance for a new drug to actually make it to market is only 1:5,000, with costs of an average of US$ 403 million per new drug. Repositioning existing drugs for new indications (i.e., new diseases) could deliver the productivity increases that the industry needs. A prerequisite for drug repurposing is drug promiscuity (polypharmacology) –a drug’s ability to bind to several targets. In this experiment, we employed a pipeline of algorithms for measuring structural similarity between proteins and consequently infer drug off-target interactions (side-effects) and identify potential therapeutic features of existing drugs. It is anticipated that such improvements would boost the competitive advantage of SMEs, which can perform these analyses on behalf of pharmaceutical companies that wish to reduce the cost of wet lab tests, whilst finding new targets for their compounds, thus receiving a share from the market of drug development and patenting. Our application areas address life sciences, health care, and drug discovery more specifically.