LRIG Logo The Laboratory Robotics Interest Group
Mid Atlantic Chapter

November 2004
Home Up Speakers


The Laboratory Robotics Interest Group
Mid Atlantic Chapter

November 2004 Meeting

Computational Methods


Date:        Wednesday, November 3, 2004
Place:      Somerset Marriott Hotel, 110 Davidson Ave., Somerset, NJ 08873
                    Phone: 732-560-0500, Fax: 732-560-3669
   Social Period -  4:00pm to 6:00pm
                  Meeting & Presentations -  6:00pm to 8:30pm  
Registration: REQUESTED, not required.  Registering will allow us to more accurately gauge seating requirements and refreshment needs.  Register on the web at will be drawings from the web registrants for LRIG laser pointers, photon keyring lights and any other donated prizes.

Door Prizes:
Laser Pointers (LRIG)
Photon Keyring Lights (LRIG)
Door prizes for the drawings gratefully accepted - a great way to get your name out!

Computational chemistry and molecular modeling have emerged as obligatory tools in the drug discovery armentarium under the broad aegis of CHEMINFORMATICS, loosely defined as follows: "mixing of information resources to transform data into information, and information into knowledge, for the intended purpose of making better decisions faster in the arena of drug lead identification and optimization ( As such, the field has benefited from an extraordinary explosion in popularity and awareness. To wit, citation of the term (via Google) has increased from 700 times in July 2000 vs 35,000 times in July 2004 ( LRIG is pleased to offer this session, which will strive to present the 'flavors' of Computational Chemistry, and its associated infrastructure for data management, to our members.

Click here for an overview of Computational Methods.

Food and refreshments will be available FREE OF CHARGE during the Social Period.

There is always a Job posting board at the social. Please encourage your recruiters to give you material to post and distribute. Openings may also be posted at

There is no fee to attend the meeting.

Presentation:  PREDICT modeling and in silico screening for GPCR: From amino acid sequence to the clinic
Sharon Shacham1, Yael Marantz2, Silvia Noiman2, Oren, M Becker2, and Michael, G Kauffman1
(1) Predix Pharmaceuticals, 10K Gill St, Woburn, MA 01801, (2) Predix Pharmaceuticals Ltd, 3 Hayetsira St, Ramat Gan, 52521, Israel

GPCRs constitute a major family of drug targets, involved in many physiological responses. However, the use of structure-based drug discovery methods for GPCRs has been limited by the fact that only one x-ray structure of a non-drugable GPCR (i.e. bovine rhodopsin) is known. The homology between rhodopsin and other GPCRs is very low and existing structural information is not sufficient for accurate structure prediction and drug discovery or optimization using standard homology modeling. Predix Pharmaceuticals has developed a suite of algorithms that permit the structure-based discovery and optimization of drug candidates binding to GPCRs and Ion Channels. Predix' discovery platform includes a novel technology for modeling the 3D structure of any GPCR based solely on its amino-acid sequence (PREDICT); The model is then used initially for in-silico screening against any library. The 50-200 virtual hits with best scores are sent for affinity studies in vitro. In several programs the initial hits were converted into early drug candidates using Predix ICELR-3D platform, which includes novel algorithms for the prediction of oral bioavailability, GPCR selectivity, and potential for QTc prolongation through HERG ion channel binding. The accuracy of the PREDICT models, was extensively validated, including: (a) agreement with rhodopsin X-ray structure; (b) reproduction of site-directed mutagenesis data: (c) PREDICT models yield novel hits with nanomolar activity in binding assays in 6 different programs (d) PRX-0023, a novel, non-azapirone lead clinical candidate 5-HT1A agonist with preclinical activity in anxiety and attention deficit hyperactivity disorder successfully completed Phase I clinical trails.

Presentation:  Strategies for analyzing discovery data
Glenn J. Myatt, Paul Blower, Kevin Cross, Chihae Yang
Leadscope, 1393 Dublin Road, Columbus, Ohio 43215

The presentation will review different approaches for analyzing data sets of chemical structures and biological activity data. Techniques for becoming familiar with the data set will be described including methods for assessing structural diversity. Methods for integrating, assessing and filtering the data set prior to analysis will be described. Depending on the nature of the data set (size, data distribution, and structural diversity) different methods for analyzing the data should be adopted. The presentation will review these alternative chemical structure-based data analysis approaches. Trends in the data may be further qualified by searching other databases, such as collections of toxicity data to determine any known safety liabilities with the chemical series identified. Case studies will be used to illustrate this process.

Presentation:  A High-Performance Workflow Automation System for Drug Discovery
Dr. Srini Chari; General Manager, Solutions
TurboWorx, Inc.

Many scientific problems are solved by analyzing large quantities of data using multiple compute-intensive applications linked together in complex ways. In pharmaceutical research and development, identifying lead compounds requires first computing various properties for large numbers of individual compounds, filtering the compounds based on specific property-based criteria, and performing further modeling and simulation calculations.
Today networked computing environments can be excellent platforms for processing these computational workflows because they make available large numbers of highly capable individual machines. However, the job of creating, managing, and deploying distributed workflows is daunting to most users. Very few of them are able to write robust programs or scripts that deal with issues such as authenticating users, selecting proper machines to run given applications, moving data between applications, and handling application errors and hardware failures.
In this talk we will address solutions effectively address all these issues and more. Users benefit from reduced development effort and execution time, leading to increased personnel productivity and higher analysis throughput. The TurboWorx Enterprise system allows computational workflows to be built visually, using boxes to represent application and data access tasks, and using directed lines to specify task dependencies and data paths. At runtime, the system dynamically decomposes each workflow job into its constituent tasks and arranges for task execution on appropriate compute nodes. The system also coordinates all the task executions in order to honor task dependencies and to ensure efficient data transfer along specified data paths.
This system also provides an open, extensible environment that includes visual tools that make it easy to add to the system any application that can be run from a command line. Furthermore, it offers rich support for fault tolerance, custom user authentication, data parallelism, and flow controls. To those scientists who need to analyze large amounts of data using complex computational pipelines, TurboWorx Enterprise will be an invaluable solution.

Presentation:  PredictionBase for Screeners
Scott Lee

The pharmaceutical industry is under mounting commercial pressure to increase NMEs, while containing costs. Automated screening has led to greater efficiency, but has not delivered large numbers of NMEs as originally hoped. It has, however, generated vast amounts of information. The key to solving this problem lies in unlocking the knowledge in databases, such as ActivityBase to learn from past experimentation and direct activities to find hits faster and just as importantly fail early.

IDBS has developed PredictionBase, a software suite that can help HTS biologists make intelligent decisions to identify successful candidates while minimizing unnecessary testing. PredictionBase puts practical in silico prediction in the hands of screeners, rather than confining it to a few expert users.

In this presentation, we demonstrate how PredictionBase is used to:

?Generate validated prediction models
?Direct screening campaigns in order to enrich hit rates
?Provide early alerts of ADME/T problems and develop knowledge models to guide effective assay selection
?Filter virtual or corporate compounds libraries for more focused screening campaigns



Leverage Your Time!

LRIG is pleased to announce the arrangement of a 15% tuition discount for LRIG members for Owicki Consulting's short courses on Methods in Drug Discovery, to be held 3-5 November 2004 in this same venue. If you are not a member, consider joining LRIG so that you can take advantage of the discount. Simply click on

Fluorescence Assays
All day November 3 and morning of November 4, 2004

Enzyme & Binding Assays
Afternoon of November 4 and all day November 5, 2004

Topics for the Fluorescence course:
Fluorescence fundamentals
Labels and labeling chemistries
Interferences and limitations
Survey of principal fluorescence methods
Biochemical and cellular applications

Topics for the Enzyme & Binding course:
Enzyme kinetics
Enzyme inhibition: Competitive, noncompetitive, uncompetitive, irreversible, and promiscuous
Multiple-substrate enzymes
Binding equilibria and kinetics
Deviations from classical textbook behavior
Optimizing enzyme and binding assays for primary vs. secondary screening
Understanding mechanisms and extracting information from your data
Discussion of commercial data-analysis and simulation software
Case studies, including receptor binding, kinases, and proteases

For details, see  Pre-registration is required for these short courses - download the form at: 2004 Short Course Registration Form.pdf

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