Development of an Experimental-Computational Integrated Technology to Address the Residence Time of GPCR Ligands

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G protein-coupled receptors (GPCRs) are cell surface receptors that constitute the largest superfamily of membrane proteins, translating chemical messages from outside the cell into responses inside the cell, regulating almost every aspect of cellular activity. GPCRs have enormous physiological and biomedical importance, being the primary site of action of 60% of modern drugs. There are over 800 human GPCRs known today, involved in a diversity of diseases including cancer, pain, inflammation, depression and anxiety. Despite this, drugs have been developed for just 50 of these GPCRs. This renders GPCRs one of the most important classes of current pharmacological targets. Despite a huge effort by the pharmaceutical industry to design novel drugs for GPCR targets, there is tremendous attrition along R&D pipelines. Many promising drug candidates eventually fail in clinical trials due to a demonstrated lack of efficacy. A retrospective analysis of those that have successfully made it to the market has revealed that their beneficial effects in patients may be attributed to their long drug-target residence times (RTs) - the length of time for which a drug (ligand) stays bound to its receptor target. There is substantial evidence that ~70% of long RT therapeutics displayed higher efficacy than comparable faster-dissociating drugs, supporting a growing recognition that drug-target RT may be of even greater importance than affinity, therapeutically. Recentl publications have emphasized the pivotal role of RT optimisation in the early phases of drug discovery, suggesting that detailed structure-based studies of RT should be introduced in the early phases of drug discovery to prevent "fail late, fail expensive" scenarios. However, it should be emphasized that the criteria for "long" or "short" RT may vary for different targets and for different clinical indications. For therapies requiring prolonged target occupancy, a long RT drug offers advantages, as it remains bound to the target and continuously exerts its pharmacological effect even when most of the free drug has already been eliminated from blood circulation. On the other hand, there are cases where a mechanism-based toxicity can outweigh the therapeutic advantages of long receptor occupancy and a rapidly-dissociating short RT compound would be preferred. A sizeable gap exists between current academic research directed at understanding the kinetics and molecular details of the drug binding process and the needs of the pharmaceutical industry. This gap must be bridged in order to successfully apply academic knowledge to the drug discovery process. The general requirements of the pharmaceutical industry from any drug discovery approach are: (1) the method should be universally applicable to drug discovery projects; (2) the method should be effective and cost-efficient; and, (3) it should satisfy the immediate need for such information to be provided in "real-time". Currently, no technology for RT can satisfy all of these requirements. Efforts to include RT in the drug development process have focused on the adoption of either experimental or computational approaches. Each is very promising but provides only half the picture. Experimental methods can measure the RT but can't rationalize why certain compounds have longer RT than the others or suggest ways to modify a ligand's structure to improve its RT profile. On the other hand, computational methods are only able to provide this essential information if robust experimental data are available.This FLIP proposal aims, through collaboration between academia and industry, to combine experimental and computational methods in an integrated methodology that will provide a powerful tool to optimise the RTs of ligands in the early stage of drug development in a way that meets the needs of the pharmaceutical industry and brings benefit to people suffering from disorders caused or influenced by defects in GPCRs.