Computational Tools for Medicinal Chemists Increasing the Dimensions of Drug Discovery. Dr Robert Scoffin CEO
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1 Computational Tools for Medicinal Chemists Increasing the Dimensions of Drug Discovery Dr Robert Scoffin CE
2 Agenda > Building Desktop Tools - A History > About Cresset BioMolecular Discovery > Fields, what fields? > 2D -> 2 ½ D -> 3D ->? > Where s the value in 3D? > Cresset Applications > torchv10 Med.Chem. focused 1-by-1 and small libraries > forgev10 Comp.Chem. focused design and QSAR > sparkv10 automated isostere generation and analysis > Applications in Medicinal Chemistry > PDE-5 Examples
3 Building Desktop Tools A History
4 Rob Scoffin - A History > PhD at xford extensive use of ChemDraw and ChemX > 1991 Joined xford Molecular to develop emesis (desktop molecular modelling for Apple Mac) and ISIS (expert modelling and visualization tool for SGI and IBM RS/6000) > Developed Iditis (3D protein structure relational database) > Product manager for small molecule products > 1995 Part of acquisition team for CAChe (desktop QM for Mac and PC) > Co-led development in collaboration with Glaxo Wellcome of DIVA (desktop visualisation and analysis for PC) > CambridgeSoft developed first prototype of an EL for synthetic chemists > Amedis developed predictive ADMET tools for bench scientists > CambridgeSoft deployed EL systems across global pharma, biotech and academia development focused on adding value to all scientific disciplines > Cresset desktop computational tools for expert and non-expert users
5 TSAR > Molecular spreadsheet > Broad range of expert tools for SAR and QSAR > ot designed for nonexpert use
6 CAChe > Versions released with a focus on bench scientists bring QM to the desktop
7 The Genesis of DIVA > Discussions with George Purvis (CAChe Scientific) and Frank Brown (Glaxo) on how to develop modelling tools for bench scientists lead to a collaborative software development project with embedded developers on-site in RTP > First step is to interview broad range of scientists to understand pressing needs and gaps in their toolkit > nrushing developments in HTS and HTC meant that most pressing needs were in visualization and analysis of thousands of compounds across tens of assays > Product plan for DIVA is the result: > Able to load millions of data points (first HTS screen was 100,000 compounds across 10 assays) > Able to process and analyse data sets to help answer critical questions: > What do I make next? > What do I test next?
8 DIVA v1.0 > Relied heavily on molecular spreadsheet UI > Introduced concept of tile view > Powerful, yet simple visualization (e.g. 2D, 3D, 4D graphs) allied to complex statistical analysis (clustering, recursive partitioning, PLS, etc.)
9 EL > Prototype had single-step synthesis pages only > Added multi-step reactions > Added CombiChem support > Added flexible and configurable experiments to support all disciplines and functions
10 Perspective > Making expert-level science accessible to medicinal chemists (broadly, not just the geek in the group) is HARD > Address vital questions: > What do I make next? > What do I test next? > Recognize that drug discovery is a process scientists need enough information to make a decision on how to proceed at each step can t wait to gather all information before providing an analysis
11 Perspective > Fire the imagination! > Fix day-to-day annoyances as a way to encourage use > EL e-signatures meant no more lab book signing parties! > Automated stoichiometry calculations and reagent look-up was a huge driver of compliance
12 About Cresset BioMolecular Discovery or K, that s cheminformatics dealt with, what about molecular modeling?
13 Cresset Summary > Cresset supplies software tools and consulting services to life sciences customers > Particular focus on molecular design within drug discovery > Users include: > Medicinal chemists > Computational chemists > Patent officers
14 Cresset Summary > Cresset s solutions enable: > Deeper understanding of actual drug activity > Prediction of likely activity for novel compounds > Unique underlying technology provides a much more accurate representation of drug-protein interactions than other computational approaches > Proven techniques through an extensive portfolio of successful consulting projects F F F H 2 S Br
15 Field Points Condensed representation of electrostatic, hydrophobic and shape properties ( protein s view ) > Molecular field extrema ( field points ) F F F H 2 S Br 2D 3D Molecular Electrostatic Potential (MEP) Field Points = Positive = egative = Shape = Hydrophobic
16 Field Points - an analogy H 2 S F F F Br 2D drawing very useful for synthesis planning, quick recognition of structural type, IP protection, etc. ot particularly useful for understanding shape and interactions with proteins. 3D representation of shape and electronic properties very useful for understanding complex characteristics and interactions. ot useful for rapidly analyzing large numbers of molecules to e.g. find matches. Field point representation allows for rapid analysis of collections of molecules, whilst retaining the ability to understand shape and electronic properties.
17 Explanatory Power of Fields Field points give you new insights into your molecule Aromatic π cloud H acceptor +ve ionic H-bond acceptor H H H H Aromatic in-plane H donor H-bond donor Hydrophobes Field point size show importance -ve ionic Stickiest surfaces (high vdw) = Positive = egative = Shape = Hydrophobic 17
18 Bioisosteres PDE III Biologically relevant method for comparing molecules Bioisosteres 20
19 Cresset Applications > Ligand-based virtual screening > Diverse lead like hits > Large library design > HTS rescue > Bioisostere generation and replacement > ew chemistry directions > Patent protection > Patent busting > Expert computational tool for SAR, QSAR and design > Build predictive models > Improve design > Singles > Libraries > Med.Chem. tool for SAR and design > Relate chemical series > Understand shape and electrostatic properties > Play models built in forgev10 to predict activity or properties
20 Applications in Medicinal Chemistry
21 What Does it Take to Apply Comp. to Med.? F F F H 2 S Br > Solve every day problems and help to address: > What to make next? > What to test next? > Reliable algorithms > Clear and simple UI > Easy integration with drawing tools and presentation tools > Idea generation not answer provision > Allow the chemist to be more successful and more creative
22 Applications in Med. Chem. > Compound Design > Detailed single-compound design > Small library design > SAR Analysis > Structure-based design > Pharmacophore assessment > Reactivity assessment > Patent protection
23 PDE-5 Examples
24 PDE-5 Inhibitors Viagra Levitra - Cialis H + S H H + S H Viagra (Sildenafil) H Levitra (Vardenafil) H H Cialis (Tadalafil) 27
25 Viagra versus Levitra 28
26 29 Viagra Isostere Replacements H S H + Viagra (Sildenafil) S H + H S H + S H + ovartis compound 100nM #1 Result
27 Thank you! 30
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