Personalia: Pre-SheffieldPersonalia: SheffieldDepartmental contextResearch context: IResearch context: IIResearch context: areas of expertiseSlide 7MSc Chemoinformatics: historyMSc Chemoinformatics: aimsChemoinformatics challengesPersonalia: Pre-Sheffield•Batchelor’s degree in Chemistry at Oxford•Pre-university job in my local public library system•Chemistry or information science?•MSc degree in information science in 1975•Place at SheffieldPersonalia: Sheffield•Introduction to computing during the MSc•Influence of Mike Lynch and George Vleduts•Dissertation project building on previous work in the Department on the automatic indexing of chemical reactions•Already a distinguished departmental record especially in techniques for 2D substructure searching•Subsequent doctoral and post-doctoral study and then a faculty position in 1979Departmental context•The Department has for long been the premier library science department in the UK with wide range of research areas•Chemoinformatics is but one area of research, and an area that is tangential to the Department’s principal teaching and research fociResearch context: I•An Information Studies department•Focus on data structures and algorithms, rather than details of chemistry and biology•Application of techniques from other disciplines•Automatic Control and Systems Engineering, Chemistry, Computer Science, Molecular Biology and Biotechnology•Particular interest in relationship with information retrieval techniquesResearch context: II•Early work of group focused on database searching, but increased interest from late 80s in drug discovery applications•Docking, pharmacophore mapping, virtual screening, molecular diversity•Extensive collaborations with industrial partners•AstraZeneca, CCDC, GlaxoSmithKline, Novartis, Pfizer, Syngenta and Tripos, inter aliaResearch context: areas of expertise•Graph isomorphism procedures•Use for chemical and biological structure matching applications•Similarity and cluster analysis•Use for virtual screening and compound selection•Evolutionary algorithms•Many chemoinformatics applications are combinatorial in natureResearch context: areas of expertise•Detailed and extended comparative tests•Operational systems require algorithms of proven effectiveness, efficiency and applicability•Examples•Bron-Kerbosch clique detection algorithm•Tanimoto Coefficient for fingerprint-based similarity searching•Jarvis-Patrick and Ward methods for database clustering•Ullmann subgraph isomorphism algorithmMSc Chemoinformatics: history•World-wide industry shortage•August 1999: ACS COMP symposium•November 1999: ABPI EPSRC; Sheffield University; representatives from pharmaceutical industry•December 1999: EPSRC call for proposals•Masters Level Training Packages (MTPs), with Chemoinformatics as one of the priority areas•Successful bid supported by a range of pharmaceutical, agrochemical and software companies•10 studentships over 5 years from September 2000•Tuition and 2/3 maintenance (1/3 coming from industry)MSc Chemoinformatics: aims•Develop an awareness of IM and IT techniques used in the design and implementation of chemoinformatics systems•Enable students to demonstrate skills learned by carrying out a small-scale industrially relevant chemoinformatics research project•Basic structure•Two semesters of taught modules •One semester dissertation working at the site of one of the companies supporting the programmeChemoinformatics challenges•2D and 3D methods for virtual screening•Why does the former normally work better, despite being a far less precise molecular characterisation?•Combination methods in chemoinformatics•There are lots of different tools – how to integrate them so that they can work together to enhance performance (however