The SSIP approach to protein-ligand complex interactions

Year 1: Generic training activities for all first-year student members of the CDT.

Year 2-4: The field of drug discovery faces a dichotomy. It is possible to screen high volume of small molecules but algorithms that do are empirically parametrised and quantify non-covalent interactions. To obtain high quality detail takes a substantial amount of time, skill, and computing power. Both high volume and high quality algorithms, however, use an energy predictor and an optimisation tool that leads the search to equilibrium. We will develop a Surface Site Interaction Point model that uses DFT-calculated detail in quick quantification of interactions. It reliably describes the interaction patterns present between molecules. It reliably predicts solvation energies, and in considering protein-ligand complexes, it can describe non-covalent interactions within a conformation without a need for explicit solvent treatment. Here we show such an approach gives good estimates of binding affinities using a common dataset - CASF-2016. We can predict and quantify interactions present in a complex, therefore providing a path to systematic drug candidate optimisation. If coupled with an optimisation algorithm, this new approach could form a tool for screening ligands, thus yielding a unified approach to drug design that is both swift and accurate.

Who might benefit from this research? How might they benefit from this research?

Students
(a) The major beneficiaries of the CDT will, of course, be the students that train on the program. They will be equipped with a set of skills that will be highly desirable in the organic molecule making industries. Although the proposal is directing towards a need in the pharmaceutical industry, the training and research skills are totally transferable to industries like the argochemical sector (this is an almost seamless transition as the nature of the needs are near identical to that of pharma) but also the fine chemicals industries, CRO's who serve all of these industries. With some adaptation of the skills accrued then the students will also be able to apply their knowledge to problems in the materials industries, like polymers, organic electronics and chemical biology.

(b) Synthesis will also be evolving in academia and students equipped with skills in digital molecular technologies will be at a significant advantage in being apply to implement the skills acquired while training on the CDT. These students could be the rising stars of academia in 10 years time.

(c) The non-research based training will benefit the students by providing a set of transferable skills that will see them thrive in any chosen career.

(d) The industry contacts that will be generated from the variety of interactions planned in the CDT will give students both experience and insight into the machinations of the industrial sector, helping them to gain a different training experience (form industry taught courses) and hands on experience in industrial laboratories.

(e) All student in UCAM will be able to benefit in some way form the CDT. Training courses will not be restricted to CDT students (only courses that require payment will be CDT only, and even then, we will endeavour to make additional places available for non-CDT students). The overall standard of training for all students wil be raised by a CDT, meaning that benefit will be realised across the students of the associated departments. In additional, non CDT students can also be inspired by the research of the CDT and can immerse new techniques into their own groups.

Academic researchers in related fields (PIs)
(a) new research knowledge that results from this program will benefit PIs in UCAM and across the academic community. All research will be pre-competitive, with any commercial interests managed by Cambridge Enterprise

(b) a change in mnidset of how synthetic research is carried out

(c) new collaborations will be generated withing UCAM, but also externally on a national and international level.

(d) better, more closely aligned, interactions with industry as a result of knowledge transfer

(e) access to outstanding students

Broader public
(a) in principle, more potential medicines could be made available by the research of this CDT.

Economy
(a) a new highly skilled workforce literate in disciplines essential to industry needs will be available
(b) higher productivity in industry, faster access to new medicines
(c) spin out opportunities will create jobs and will stimulate the economy
(d) automation will not remove the need for skilled people, it will allow the researchers to think of solutions to the problems we dont yet understand leading to us being able to discover solutions faster