Drug Design

Our drug design projects involve situations when a number of partners collaborate to jointly solve molecular design problems as an early stage step in a drug discovery situation. The partners may involve commercial organisations, academic labs, and individual consultants who form a Virtual Organisation (VO) to collaborate on running the project, that typically has been historically carried out at a pharmaceutical organisation. The knowledge and experience of the partners involved is a critical resource and success factor for the project as is the ability to collaborate effectively. Additional resources include computer software and machinery for molecular design, modelling and virtual screening, experimental lab facilities for running assays and experiments on predicted hits for the problem studied, and supporting Information and Communications Technology (ICT) infrastructure. A significant amount of activity involving analysis, interpretation of results, synthesis and discussion is involved in many steps of the research process.

Computer-based models of Protein targets, Protein-Ligand and Protein-Protein interactions are built based on existing knowledge from target moleculecrystal structures, physical chemistry and applications of bioinformatics and cheminformatics methods. A variety of methods including virtual screening, docking, pharmacophore-based design and free energy simulation methods are applied to the design of drug candidate molecules and their affinity for the target based on interactions such as involving specific hydrogen bonding and hydrophobic interactions with the active site of an enzyme. Holistic approaches to design also take into account specificity, cross-target interactions, Lipinski’s rule of 5 on druglikedness, ADME and toxicity properties of candidate molecules. Predictions are tested in the laboratory using a variety of experimental screening methods. High Throughput Screening (HTS) can be used to examine the activities of libraries of molecules against a target, whereas High Content Assays may probe a specific toxicity mechanism and property of a molecule.

A Lessons Learned process is run at the end of every significant process in the collaborative research workflow and prioritised lessons are documented into the VO knowledge base. Best Practices are agreed and documented at the start of the project. If best or better practices are discovered during the Lessons Learned process (e.g., on discussing “what went well”), they are documented into the VO knowledge base for future reference.