The program, abstracts and schedule for the 5 Day eCheminfo Hands-on Drug Discovery Workshop Week (21-25 July 2008) at the Medical Sciences Teaching Center, Oxford University, Oxford, UK is provided below. (follow continuation)
More Information is available at http://www.echeminfo.com/COMTY_training
To complete registration arrangements for the workshop, please contact Nicki.Douglas –(at)- douglasconnect.com, +41 61 851 0461
eCheminfo Oxford 08 Workshop Program & Schedule
Topics: Virtual Screening & Docking; Structure-based Drug Design; Ligand Optimisation & Library Design; Structure Search, Similarity and Property Estimation; Data Mining, Analysis & Visualisation; Pharmacophore Modelling for Lead Identification; Fragment-based Drug Design; QSAR-based Predictive Toxicology; and Quantitative Spectrometric Data-Activity Relationship Modelling.
Monday July 21
13.00 Registration Open
13.30 Introduction, Guidance and Best Practices in Discovery, Barry Hardy, Douglas Connect
14.00 Drug Discovery Modelling Methods, Guest Lecturer TBA
15.00 Poster Session with Refreshments and Sandwiches
16.00 Discussion Session on Class Interests and Problems
17.00-20.00: Structure-focused Pharmacophores for the Identification of Novel Leads
Led by Gerhard Wolber, Inte:Ligand
Virtual screening using 3D pharmacophores has been established as an important and commonly used technique for virtual screening in recent years [1-2]. We demonstrate use and applications for a new software tool (LigandScout) that allows to rapidly and transparently develop high-quality 3D pharmacophore models in a more efficient and intuitive way. Besides the easy and automated creation of pharmacophore models from protein/ligand complexes, LigandScout provides intuitive pharmacophore overlay and interpolation work-flows based on a robust and fast chemical-feature-based alignment algorithm. The underlying methods are scientifically published [3-4] and based on several years of experience in pharmacophore creation, and support for various common pharmacophore formats like the export to Catalyst(tm), MOE(tm) or Phase(tm) allow interoperability to screening platforms from other vendors. The full-featured 3D graphical user interface makes the exploration of the active site and pharmacophore creation within the complex efficient and transparent. Binding site analysis, pharmacophore-based alignment and the creation of shared feature pharmacophores are designed to make LigandScout an essential tool for structure-based drug design in combination with virtual screening. In this half-day workshop we will demonstrate how to derive structure-and ligand-based pharmacophores using the LigandScout modelling environment. The individually developed pharmacophores will be validated against sets of active and inactive molecules for selected targets and subsequently used for virtual screening in larger multi-conformational compound libraries.
 Langer T., Hoffmann R. D. Pharmacophores and Pharmacophore Searches; VCH/Wiley, Methods and Principles in Medicinal Chemistry, Vol. 32, R. Mannhold, H. Kubinyi, G. Folkers, series editors, ISBN: 3527312501 (2006)
 Wolber G., Seidel T., Bendix, F., Langer T. Molecule-pharmacophore superpositioning and pattern matching in computational drug design.Drug Discov Today. 2008 Jan ;13 (1 2):23-9
 Wolber, G.; Dornhofer, A. A.; Langer, T.; Efficient overlay of small organic molecules using 3D pharmacophores J. Comput. Aided Mol. Des.; 2007; 20(12); 773-788.
 Wolber, G.; Langer, T.; LigandScout: 3-D Pharmacophores Derived from Protein-Bound Ligands and Their Use as Virtual Screening Filters. J. Chem. Inf. Model; 2005; 45(1); 160-169.
20.30 Refreshments and Food, St. Edmunds Hall
Tuesday July 22
8.30 Virtual Screening Methods, Barry Hardy, Douglas Connect
9.00-12.30: Discover MED-Hybridiser for innovative Fragment-based Drug Design at PDB scale
Led by Fabrice Moriaud, MEDIT
MED-Hybridiser is an innovative software protocol that generates fragment-based chemical compounds by crossing the Protein Data Bank (PDB) and chemical supplier databases.
MED-Hybridiser is based on the validated MED-SuMo technology, a powerful target-based drug design software that compares any interaction surface against the full PDB in a few minutes. Using MED-SuMo makes it possible to retrieve all MED-Portions (fragment compounds from chemical suppliers) exerting 3D local interaction similarities with your protein of interest. Those MED-Portions are then combined in 3D and compared, using fast structure comparison technology, to chemical supplier databases. As an output of MED-Hybridiser, users obtain a large list of innovative compound showing interactions with the 3D target.
By taking advantage of the PDB quadratic growth, MED-Hybridiser is able to generate large numbers of innovative compounds in many cases. Because MED-portions and all output molecules originate from the selected chemical libraries, it produces material that adheres to the medicinal chemistry area. Compared to other de novo methods in fragment-based drug design, MED-hybridiser is the first protocol to take advantage of both chemical information from the PDB and chemical suppliers lists to deliver new active compounds to medicinal chemists.
13.30-17.00: User-friendly Ligand Filtering and Virtual Screening
Led by Nicola Potter, University of Leeds
We will use the leading edge scientific software of SimBioSys that is both highly accurate and very easy to use. To that end, attendees of this workshop will experience three tools that can make virtual screening a more productive experience. The eHiTS Filter is a ligand based filter that uses the chemical features of a ligand surface to create a pseudo-pharmacophore for rapid screening of large databases. eHiTS is a very accurate fragment-based docking program for both virtual screening and binding pose prediction of ligands. CheVi is an advanced visualization package specifically designed to help users analyze how ligands interact with receptors. In addition, CheVi acts as a front-end GUI to run eHiTS Filter and eHiTS screening / docking jobs.
The workshop will describe a typical work-flow from database to lead and show how tools from SimBioSys can make the process easier. Users will get a hands on lesson on how to use all the tools described above, with specific attention to analysis of interaction results.
Participants will also take home: A FREE unlimited version of the CheVi visualization tool and a two (2) month evaluation version of eHiTS and the eHiTS Filter.
17.00: De Novo Molecular Design and vHTS: a Powerful Strategy for Drug Discovery
Colin W.G.Fishwick, University of Leeds
In silico molecular docking techniques, such as virtual high-throughput screening (VHTS), are powerful approaches to the discovery of new enzyme inhibitors. Additionally, de novo design is a powerful complementary strategy for inhibitor discovery. Here, by using the structural features present within the enzyme only, new inhibitor designs are built-up sequentially according to the requirements of the targeted binding site. Therefore, de novo design is an important technique to use in parallel with VHTS in a particular hit identification campaign, as a good de novo design program will examine structure space larger by many orders of magnitude than that of most virtual libraries currently used for this purpose. We have recently applied both the de novo molecular design computer program SPROUT, and the VHTS program eHiTS to a number of therapeutically attractive enzyme targets and have, in the majority of cases under study, rapidly identified inhibitors in the micromolar range or better.
G.E. Besong, J.M Bostock, W. Stubbings, I. Chopra, A.P. Johnson, D.I. Roper, A.J. Lloyd, and C.W.G. Fishwick. A novel de novo designed inhibitor of D-ala-D-ala ligase from E.coli. Angew. Chem. Int. Ed. Engl., 2005, 44, 6403 - 6.
M.A. Ali, N. Bhogal, J.B.C. Findlay, and C.W.G. Fishwick. The first de novo designed antagonists of the human NK2 receptor. J. Med. Chem, 48, 2005, 5655-58
T. Heikkila, S. Thrumalairajan, M. Davies, A.P. Johnson, G. McConkey, and C.W.G. Fishwick. The first de novo designed inhibitors of plasmodium falciparum dihydroorotate dehydrogenase. Bioorg. Med. Chem. Lett., 2006, 16, 88-92
C. Ramsey, C. Galtier, A.M.W. Stead, A.P. Johnson, T. Heikilla, M. Davies, C.W.G. Fishwick, A.N. Boa, and G. McConkey. J. Med. Chem., 2007, 50, 186 – 191.
17.45-19.45: Open Work Session on Class Problems
Wednesday July 23
8.30-12.00: Focused Library Design using Combinatorial Docking and Pharmacophore Screening
Led by Jean-Christophe Mozziconacci and Gerd Rather, Schrodinger
Initially, we will dock known p38 MAP kinase inhibitors using Glide in order to inspect the binding modes. Several post-processing methods will be presented. Secondly, CombiGlide will be used to prepare and screen a large combinatorial virtual library based on the core of one of the ligands previously docked. A focused library will be designed, in which optimized p38 MAP kinase ligands are discovered. We will also inspect the Structure Activity Relationship for each attachment point. Finally, a pharmacophore hypothesis will be derived from a known active compound using Phase and a database containing potentially active compounds will be screened.
12.00: Drug Design driven by ADME prediction
Ismael Zamora, Pompeu Fabra University and Lead Molecular Design
One of the many factors to be considered in the discovery and development of a new drug is its elimination. Therefore the integration of the drug metabolism studies into the drug discovery process has been one of the major recent changes in the development of drug candidates. At the beginning of this process, the experimental metabolic techniques were incorporated in the battery of assays to check the molecule properties, later a set of computational filters (i.e. Lipinksky rules,etc) were used to classified the compounds with "good" or "bad" pharmacokinetic characteristic and more recently the computational techniques have been introduced to design compounds with better ADME properties.The aim of the present investigation is to use several computational techniques to rationally design new compounds with improved metabolic properties, but at the same time retaining their pharmacological effects. The model system used in the presented study is the nonsteroidal anti inflammatory drug celecoxib, a COX-2 selective inhibitor and known CYP2C9 substrate.
14.00-17.00: Free time for Class Members to pursue own activities
14.00 (Optional) Group Punting Trip
17.00-20.00: Analysing Chemical Databases using Advanced Structure Searching and Structure Based Predictions
Led by Tim Dudgeon, ChemAxon
To effectively analyse Structure-Activity Relationship (SAR) data you need a flexible approach, as the answer to one question frequently leads to asking a new completely different question. Doing this with large data sets can be slow and cumbersome. This workshop will show how you can rapidly analyse large sets of chemical and biological information using advanced structure searching techniques and prediction of chemical properties. This will be done using the ChemAxon Instant JChem tool which uses the JChem chemical database for storing and seaching chemical information, and Chemical Terms for flexible calculation of simple molecular properties (H-bond donors/acceptors, rotatable bonds etc.) as well and more complex predictions (partitioning, solubility, biovailability etc.).
Thursday July 24
9.00 Advances and Challenges in Safety, Toxicology & Computation, Barry Hardy, Douglas Connect
9.30-13.00: Rapid 3D-QSAR with the Topomer Technology
Led by Ulrike Uhrig, Tripos
In drug discovery, researchers face pressure to get good ideas for lead compounds faster and faster. This requires scientific methods that are extremely rapid while remaining reliable and consistent. This prerequisite is fulfilled by the Topomer technology, which enables rapid and consistent alignments of molecules and makes comparisons of them very easy.
During the workshop we will use the Topomer technology to search for structural elements that can replace a whole structure or just an R-group or a scaffold.
In a next step we will apply this technique for building a 3D-QSAR model that allows for good activity predictions of new interesting compounds.
14.00-17.30: QSAR with Applications to Toxicity
Led by Wojciech Plonka, Fujitsu
This training will focus on Quantitative Structure-Activity Relationships (QSAR) and the prediction of environmentally important properties such as toxicity, carcinogenicity, human intestinal absorption and others. The workshop will be based on the newest release of Fujitsu’s ADMEWORKS ModelBuilder software. This tool is created for building mathematical models that can later be used for predicting various chemical and biological properties of compounds. It also provides the user a friendly and high performance environment. The models are based on values of physicochemical, topological, geometrical, and electronic properties derived from the molecular structure. Descriptor generator programs in ADMEWORKS ModelBuilder come mostly from ADAPT, the software system created by Peter Jurs and coworkers at Pennsylvania State University to study molecular structure - biological activity relationships (SAR) and molecular structure - physicochemical property relationships (SPR) and from MOPAC, the popular semiempirical quantum chemistry package designed by Dr James Stewart.
FQS Poland will provide a demo version of ADMEWORKS ModelBuilder 3,0 for all training participants. The demo version is not limited in any way except the time period which is 21 days.
17.30-19.30: Open Work Session on Class Problems
Friday July 25
09.00-10.00: An In Silico Approach to Rational Antipsychotic Drug Design using Spectral Data Activity Relationships
Bill Massey, LITMUS Molecular Design
Spectral Data Activity Relationship (SDAR) modeling is a computational method that uses the steric and electronic characteristics of small molecules (that determine their biological activity), as measured through spectral data, by which accurate models of a molecule’s biological activity can be created. SDAR modeling can be used to screen molecules for a particular activity (e.g., efficacy, toxicity) or to design novel drugs having a set of desired characteristics with a high degree of accuracy. The present program’s purpose was to use spectral modeling to create a series of atypical antipsychotic drug candidates predicted to have targeted characteristics that meet unmet medical needs in the treatment of schizophrenia. Spectral models were created using a random 10% cross-validation process and published human experimental data. Highly accurate spectral models were created for D2 (q210% = 0.96) and 5-HT2A (q210% = 0.99) receptor binding affinities, antipsychotic activity, agranulocytosis activity, agranulocytosis relative risk (q210% = 0.98), and hERG inhibition (q210% = 1.0). Data extracted from the spectral models were used to create 125 new atypical antipsychotic drug candidates. When screened against the spectral models, 83 drug candidates were predicted to have antipsychotic activity (confidence >80%), 21 of those 83 had the desired receptor binding profiles, and after toxicity prediction, 12 were selected for synthesis and further development. The drug development process through the lead selection stage usually takes years and hundreds of millions of dollars. Using spectral modeling and rational drug design principles, the entire process took 3 months. These time and cost savings realized through spectral modeling could have positive ramifications for the economics of the pharmaceutical industry.
10.00-13.00: Application of Quantitative Spectrometric Data-Activity Relationship Models (QSDAR) to Toxicity Prediction
Led by Richard Beger, FDA
This workshop will go through the steps for developing QSDAR models and predicting unknowns from a QSDAR models. The prediction of 13C NMR spectra, the binning of the 13C NMR spectra, the statistical building of the QSDAR models, and predictions of unknowns in QSDAR modeling will be covered. The workshop will explicitly cover QSDAR development for toxic equivalency factors (TEFs) of the 29 polychlorinated dioxin-like compounds (polychlorinated dibenzodioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), or polychlorinated biphenyls (PCBs)) for which non-zero TEFs have been defined. The QSDAR model predicted TEFs as 0.037 and 0.004, respectively, for 1,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and 1,2,3,4,7-pentachlorodibenzo-p-dioxin (PeCDD), both of which are among the 390 congeners for which zero value TEFs are assumed. A QSDAR model of relative potency (REP) values estimated values as 0.115 and 0.020, respectively. Both models indicated that these two congeners are likely to exhibit significant dioxin-like toxicity. If very many such congeners should have non-zero values, TEF-based risk assessments of some dioxin, furan, or PCB contaminated sites or foods may be underestimating toxicity. We used a luciferase gene expression in vitro assay based on mouse liver cells to determine experimental REPs of 0.027 and 0.013, for 1,3,7,8-TCDD and 1,2,3,4,7-PeCDD, respectively. The corresponding QSDAR-estimated and gene-expression assayed values were in close agreement. We proposed QSDAR estimates as first approximations that give reasonably accurate estimates. This study showed that QSDAR prediction followed by a relatively inexpensive in vitro assay could be used to nominate a few candidates among hundreds for expensive in vivo evaluation. Success here suggested that in silico and in vitro nomination protocols may enable practical risk assessment for toxic endpoints when members of a large chemical family display different degrees of toxicity operating through a common mechanism.
14.00-17.00: De Novo Scaffold Replacement and Virtual Screening
Led by Peter Oledzki, BioSolveIT
The workshop will be a combination of using FlexX 3.0 protein-ligand docking and a new ligand-based scaffold replacement tool, Recore. Each user will follow a structured interactive demonstration of the new FlexX-GUI and Recore to first gain familiarity on how to use each individual tool. Recore will be utilised to show how easy scaffold replacement can be performed on a variety of known active compounds using a sandbox fragment space. The workshop will continue with users performing docking studies with FlexX. The pitfalls users need to be aware of in docking protocol preparation will be highlighted and users will then proceed to perform various docking studies using further examples provided.
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