Professor Peter Willett

Research Projects

Open-Access Mega Journals and the Future of Scholarly Communication

Open-access 'mega-journals' are an emerging publishing trend which has the potential to reshape the way researchers share their findings, remoulding the academic publishing market and radically changing the nature and reach of scholarship. This project will investigate the influence of mega-journals in the academic community and beyond.

Bio-renewable Formulation - 6 month extension

Bio-renewable Formulation Information and Knowledge Management System

Innovative ICT can play a crucial role in many innovation processes, but its potential is not always exploited in many industries. A route to innovation in formulated product industries is the exploitation of materials in what would otherwise be lost to waste streams from current manufacturing processes. This is exciting both in terms of realising additional value from manufacturing, but also in reduced utilisation of unsustainable material sources and exploitation of novel feedstocks for novel functional materials with new application benefits. This project will develop an information system based on highly innovative information technologies with the capability to rapidly identify the feedstock and functional material opportunities for formulated products, and demonstrate its value in rapid bio-derived surfactant discovery. It aims to support chemical using industries where environmental impact, sustainability and materials security are increasingly significant drivers of innovation alongside improved performance in formulated products. Project partners are Unilever, British Sugar, Croda, Cybula, University of Manchester and University of Liverpool

N8 Biohub Information and Knowledge Management System

The overall aim of this project is to build, and demonstrate the value of, an information system (IS) to support the creation of a "Bio-Hub" centred on the N8 university group. The IS will demonstrate how functional ingredients from simple transformations of sustainable plant & waste feedstocks can be identified more quickly and recommend the best feedstocks for a particular function. It will address two big data problems using clever algorithms: semantic extraction of the available domain literature (terabytes) and optimised global search algorithms to explore the combinatorially large number of transformation products (up to petabytes). The innovations are in the creation of robust enough algorithms to run semi-autonomously in an information system and in bringing these together with all the other components. The value will be demonstrated for specific feedstocks and applications, but the ICTs will be selected for simple extension to, and maintenance of, the overall information domain. Project partners are Unilever, British Sugar, Croda, Cybula and University of Manchester.

AstraZeneca Collaboration - Pharmacophores

The project involved the development of a new multiobjective optimisation method for pharmacophore identification from sets of active compounds. A pharmacophore describes the three-dimensional arrangement of chemical features required for a small molecule to bind to a receptor and the aim of this project was to deduce the pharmacophore from a series of active compounds in the absence of the structure of the receptor itself. This involves superposing the compounds so that their common features are overlaid.

Sanofi-Sheffield collaboration

Array design for lead optimisation in pharmaceutical research

This EPSRC-funded project focused on the development of tools to assist medicinal chemists in the design of compound arrays during the lead optimisation stage of drug discovery. Lead optimisation is a complex, time-consuming task, in which chemists seek to obtain a promising balance among potency, off-target interactions, toxicity, and pharmacokinetic behaviour, to identify a candidate molecule to progress to clinical trials. The focus has been on inverse QSAR, that is, determining the structural change necessary to achieve a desired change in property. This was been approached through retrospective studies of lead optimisation projects within the GSK archive and the development of computational tools that can be applied in prospective array design to inform decision making by chemists. These included a novel context-sensitive approach to matched molecular-pairs analysis.

Vector Analysis of 2D Fingerprints and Screening Data

Support tools for automatic pharmacophore generation

Johnson and Johnson PhD

Richmond Continuation

Mining molecular bioassay data

Cheminformatics methods for HTS and profiling data analysis

PhD studentship

Development of novel methods for protein surface representation and comparison

Generation of 3D Hyperstructures

Use of graph-theoretical methods in computation chemistry for pattern identification

Probabilistic prediction of bioactivity

Genome Analysis Using DNA Structure

Discrete Mathematical Approaches to Chemical Information Retrieval