Harnessing Our Understanding Of Water To Identify Druggable Protein Targets and Drive The Development Of Effective Therapeutics

Drug development is an extraordinarily expensive and lengthy process. Recent estimates suggest that the total cost of developing one new drug are steadily increasing and will soon reach £1.5 billion. The timescale for a successful project is 12-15 years. However, success rates in drug development are currently falling. Sensible choices early in the process of drug development are thus vital and can lead to huge cost savings and improved outcomes for patients. The first two steps on the path to developing a new drug are:

(1) Identifying a biological target that is suitable for drug design and will lead to effective therapies.
(2) Determining which chemical compounds are best able to inhibit this biological target to combat disease.

The task of finding suitable biological targets and chemical compounds can be made quicker and more efficient by combining an understanding of the physical basis of disease with powerful computer models. These computer models can aid in the identification of biological targets that will prove fruitful in drug development projects and design compounds whose shapes are most complementary to the shapes of the targeted proteins. This project will use such computer models to increase the effectiveness of both of the stages above, resulting in shorter lead times and fewer dead ends in drug development. This will provide great benefit to society, which must eventually pay the cost of drug development. The project will increase efficiency by utilising the enormous amount of data on the shapes of proteins that has already been collected. Identifying biological targets that are suitable for drug design will be achieved by developing a computer model utilising such data on the shapes of proteins. The results of these calculations will be disseminated via a purpose-built website to allow academic groups and drugs companies to focus their efforts on developing effective treatments. Determining chemical compounds that are able to inhibit specific biological targets will be achieved by collaborating with existing drug development projects at the University of Cambridge, the Medical Research Council Technology arm and other academic and governmental institutes. My contribution will be to develop and optimise software that can design molecules with a higher affinity for their biological target and thus a greater ability to combat diseases. A number of companies sell such software, but it is prohibitively expensive for use in academic work.

My work during the fellowship will focus on a number of key improvements. Existing methods suffer from a number of approximations and do not take advantage of the constant and rapid increase in computer power. The new software will incorporate new theories to circumvent these approximations and will employ the latest computational methods to model the flexibility of proteins and the water molecules that mediate important interactions. The final outcome of this project will be a validated method to improve effectiveness in the development of new medicines. Collaborations with biology and chemistry laboratories will produce the experimental results necessary to test and improve the predictions. This will directly impact the development of therapeutics for diseases such as cancer, malaria and tuberculosis. The improvements in theory and methodology will be very useful within this important field and the software will be freely available to university researchers, extending its value beyond the length of the project. The proposed project will identify new biological targets and generate new chemical compounds to treat disease, benefiting society in the fight against disease.

Water is the most important molecule in biology. The interaction between any two biological molecules must compete with the interactions of the individual molecules with water and thus it is involved in every single intermolecular interaction in an aqueous environment. This also makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. In order to account for hydration thermodynamics, this proposal is focused on inhomogeneous fluid solvation theory (IFST), a statistical mechanical method to determine the enthalpy and entropy of solvation. IFST has a number of advantages that make it superior to many of its alternatives. Explicitly including the thermodynamics of interfacial water molecules is vital, as the subtle balance of enthalpy and entropy means that immobilising a water can favour or disfavour binding. In addition, visualisation of the contributions of spatial subvolumes is a revolutionary approach that transforms the way in which water is viewed, understood and harnessed. The combination of accuracy with elucidative results, calculable on a reasonable timescale, makes IFST a powerful method for studying hydration. Novel extensions to the theory developed in this project will allow computation of binding free energies. IFST will then be used to solve two fundamental problems in drug discovery: the identification of druggable targets and the design of small molecule inhibitors. After validation, the software will be used to identify protein targets containing hot spots suitable for small molecule binding. IFST will also be combined with a molecular design algorithm that incorporates the contributions of structural waters. Collaborations with experimental groups in Cambridge and at the MRCT will allow the software to be applied directly to active drug development projects. These two advances will increase the cost effectiveness of drug development and thus support one of the UK's key industries.

Drug development is an extraordinarily expensive and lengthy process. Recent estimates suggest that the total cost of developing one new drug are steadily increasing and will soon reach £1.5 billion. The timescale for a successful project is 12-15 years. However, success rates in drug development are currently falling. Sensible choices early in the process of drug development are thus vital and can lead to huge cost savings and improved outcomes for patients. The first two steps on the path to developing a new drug are:

(1) Identifying a biological target that is suitable for drug design and will lead to effective therapies.
(2) Determining which chemical compounds are best able to inhibit this biological target to combat disease.

The task of finding suitable biological targets and chemical compounds can be made quicker and more efficient by combining an understanding of the physical basis of disease with powerful computer models. These computer models can aid in the identification of biological targets that will prove fruitful in drug development projects and design compounds whose shapes are most complementary to the shapes of the targeted proteins. This project will use such computer models to increase the effectiveness of both of the stages above, resulting in shorter lead times and fewer dead ends in drug development. This will provide great benefit to society, which must eventually pay the cost of drug development. The project will increase efficiency by utilising the enormous amount of data on the shapes of proteins that has already been collected. Identifying biological targets that are suitable for drug design will be achieved by developing a computer model utilising such data on the shapes of proteins. The results of these calculations will be disseminated via a purpose-built website to allow academic groups and drugs companies to focus their efforts on developing effective treatments. Determining chemical compounds that are able to inhibit specific biological targets will be achieved by collaborating with existing drug development projects at the University of Cambridge, the Medical Research Council Technology arm and other academic and governmental institutes. My contribution will be to develop and optimise software that can design molecules with a higher affinity for their biological target and thus a greater ability to combat diseases. A number of companies sell such software, but it is prohibitively expensive for use in academic work.

My work during the fellowship will focus on a number of key improvements. Existing methods suffer from a number of approximations and do not take advantage of the constant and rapid increase in computer power. The new software will incorporate new theories to circumvent these approximations and will employ the latest computational methods to model the flexibility of proteins and the water molecules that mediate important interactions. The final outcome of this project will be a validated method to improve effectiveness in the development of new medicines. Collaborations with biology and chemistry laboratories will produce the experimental results necessary to test and improve the predictions. This will directly impact the development of therapeutics for diseases such as cancer, malaria and tuberculosis. The improvements in theory and methodology will be very useful within this important field and the software will be freely available to university researchers, extending its value beyond the length of the project. The proposed project will identify new biological targets and generate new chemical compounds to treat disease, benefiting society in the fight against disease.