Cheminfostream

Overcoming the challenges to reducing animal experimentation through an Open Source community-based development of in silico methods

In a recent study by the European Chemical Bureau, it has been estimated that the new EU chemical legislation REACH will require 3.9 million additional test animals, if no alternative methods are accepted. The same study shows that it is possible to reduce the number of test animals significantly by utilizing existing experimental data in conjunction with (Quantitative) Structure Activity Relationship ((Q)SAR) models. Chronic and reproductive toxicity, in vivo mutagenicity and carcinogenicity are the endpoints that will require the largest number of test animals within REACH, because no alternative in vitro assays are currently available.

Recent (Q)SAR developments allow a much more accurate prediction of complex toxicological endpoints than a few years ago. This progress has been caused by (i) the development of improved (Q)SAR algorithms and (ii) by the availability of larger and  better curated public databases.

The routine application of these new generation models is however still rare, because

l  Toxicity data has been collected in a variety of different databases.

l  These databases use different formats, that are frequently not compatible with (Q)SAR programs

l  Many databases lack important information for (Q)SAR modeling (e.g. chemical structures)

l  It is hard to integrate confidential in-house data with public data for model building and validation

l  (Q)SAR models have been published in a variety of different formats (ranging from simple regression based equations to full-fledged computer programs)

l  There is no straightforward integration of predictions from various programs

l  There is no commonly accepted framework for the validation of (Q)SAR predictions and many (Q)SAR tools provide limited support for reliable validation procedures

l  The application, interpretation, and development of (Q)SAR models is still difficult for most toxicological experts. It requires a considerable amount of statistical, chemoinformatics and computer science expertise and the procedures are labor intensive and prone to human errors.

The overall objective of the FP7-funded OpenTox is to develop a framework, that provides a unified access to toxicity data, (Q)SAR models, procedures supporting validation and additional information that helps with the interpretation of (Q)SAR predictions. OpenTox will be accessible at three levels:

l  A simple and intuitive interface for toxicological experts, that provides unified access to (Q)SAR predictions, toxicological data, (Q)SAR models and supporting information

l  An expert interface for the streamlined development and validation of new (Q)SAR models

l  An application programming interface (API) for the development, integration and validation of new (Q)SAR algorithms

The OpenTox framework is being developed as an Open Source project to optimize the dissemination and impact, to allow the inspection and review of algorithms and to attract external contributors. Our approach is to closely collaborate with related projects (e.g. OECD QSAR toolbox, CADASTER, Leadscope’s ToxML development), industry users, developers and regulatory authorities to agree on common standards and to avoid duplicated and redundant work.

Do consider joining the OpenTox community effort through signing up on the website!

eCheminfo Virtual Community Activities in Cheminformatics

When I started the eCheminfo community of practice in late 2003 we focused initially on using the approach of virtual conferencing and communications to get the community started.  More recently I have given more attention to developing face-to-face conference and workshop activity and initiating collaborative research. While on this journey it has been personally rewarding to have met and made contact with hundreds of scientists in the international community and to additionally be involved in supporting their networking, career development and research in drug design, discovery and modelling. It has also been rewarding to have just met so many great people and to have had the chance to interact with them, be it on a computer, in a workshop exercise, or on a punt trying to get down the river as we usually do when we are in Oxford.  So far we seem to be better on computer-based physics than boat physics!

And so I have come full circle and can see the need to prioritise the virtual community aspects of eCheminfo further again, to support the continuation of all these worthwhile interactions in the community.  So LinkedIn is one place to start.  I have been on there for some years and we have had a group area, but have not really done much with it.  It has primarily been useful for some introductions between people.  However recent feature additions for discussion, posting of news, job announcements etc. have been added, so it seems worthwhile to try using it more for supporting continuing interactions in the community.  So I am initiating today invitations to the eCheminfo community to join us there for discussion, news and networking on what is happening in the world of drug discovery informatics, cheminformatics, bioinformatics, etc.  Use of the group is intended for scientific and professional exchange purposes only.  As included in our mission we encourage cross-disciplinary cross-sector participation so from medicinal chemists in the pharmaceutical industry through toxicologists in government institutes through PhD students working on their modelling research problems are welcome!

To request joining the eCheminfo LinkedIn group please follow the following link and introduce yourself with a group joining request:

https://www.linkedin.com/e/gis/1173/77EB680070FF/

I also really welcome suggestions from the community there on what you would like to see as further developments in coming years!

Barry

eCheminfo 2009 Drug Discovery meeting at Bryn Mawr - call for contributions

We will hold our fifth annual eCheminfo community of practice meeting on drug discovery informatics at Bryn Mawr College, Philadelphia 13 -16 October 2009.

We invite contributed papers from members of academic, government research and commercial organizations on areas of new research and innovation involving drug discovery research informatics. The work presented should involve innovative new method development or application to drug discovery problems and involving methods from computational chemistry, computational biology, cheminformatics or bioinformatics. Studies including experimental work in medicinal chemistry, screening, in vitro assay development, pre-clinical evaluation, lead optimisation and translational medicine are welcome.

Abstracts for talks (300-500 words) should be submitted to echeminfo -[at]- douglasconnect.com by 31 March 2009, and be accompanied by a short biography of the presenting author (300-500 words). Abstracts approved by the scientific organizing committee will be selected for scheduling on the conference program. Authors will be notified of acceptance as soon as a review of submitted materials takes place and at the latest by 15 April 2009. Abstracts for posters will continue be accepted for review through 31 August 2009.

The following sessions are currently planned:

Pre-conference Workshop on Drug Binding Affinities
chaired by Scott Brown (Abbott Laboratories) and Judith Lalonde (Bryn Mawr College)

Structure-Based Drug Design: The Roles of Conformation, Water and Hydrogen Bonds
chaired by Alan Cheng (Amgen)

Macromolecular Interactions and Networks
chaired by Emil Alexov (Clemson University)

Structure-Based Drug Design: Advanced Scoring Methods
chaired by Natasja Brooijmans (Wyeth)

Data Analysis and Visualisation Applications in Chemical Biology
chaired by Brian Marsden (Structural Genomics Consortium Oxford)

PDB Ligands
chaired by John Westbrook (Rutgers University)

Predictive Toxicology
chaired by Vladimir Poirikov (Russian Academy of Medical Sciences) and Richard Judson (US EPA)

Predictive ADME and Toxicology workshop in Oxford

For the first time we are holding a predictive ADME and Toxicology workshop in Oxford this summer.  It should be a valuable and rewarding experience that adds to our summer workshop activities there.  I believe we have a really good group of facilitators gathered that should make for an excellent working week. We will take a working, problem-solving approach to case study datasets throughout the week.

Here is the program as a pdf download:

Download ECheminfoADMETProgramOxford09

More detail on the program abstracts and schedule in the continuation below.

Barry

From the Caprivi Delta to 2009 activities

I had an interesting and productive expedition in the Caprivi Delta in Namibia at the end of 2008.  I have posted a description of some experiences there on The Ferryman and look forward to more conservation and sustainable development work later this year and beyond.

But 2009 is here and we are all tired already of the pessimistic news of the year ahead!

Nevertheless, our new OpenTox Predictive Toxicology research project has been progressing and I encourage you to join the community for this exciting project.

We will be holding our discovery informatics workshop week in Oxford again in July, with the interesting addition of a case study approach on kinases this year.  We are also adding a second week dedicated solely to Predictive ADME and Tox problems. Both weeks should be excellent group working experiences.  Please visit the eCheminfo community site for more details.

We are currently planning our community of practice activity for the year, which will include an introduction of new virtual resources and activities, and the planning for our annual meeting at Bryn Mawr in October.  We should make progress I hope on several initiatives including the new PDB ligands initiative of Marc Nicklaus (NIH), the virtual screening intiative and further collaborative projects.  Do contact me on barry.hardy -(at)- douglasconnect.com to discuss further.

Barry

OpenTox Predictive Toxicology Framework

The OpenTox Predictive Toxicology project has now been launched. We welcome collaboration with both developers and users on this project.  A project description follows in the continuation below. Please contact me to discuss collaboration opportunities or your needs in this area.

Barry Hardy

OpenTox Predictive Toxicology eCheminfo InnovationWell cheminformatics chemoinformatics bioinformatics Medicinal Chemistry Computational Chemistry Virtual Screening ADME ADMET QSAR toxicology Molecular Modelling Molecular Modeling pharmaceutical pharma meeting workshop training Critical Path Life Sciences Drug Discovery Research and Development Drug Development Healthcare Innovation Knowledge Management

Schedule for InnovationWell and eCheminfo Autumn 2008 Community of Practice Meeting

I provide below a schedule for the upcoming InnovationWell and eCheminfo Community of Practice meetings at Bryn Mawr.

I also include a location map here which may be useful upon arrival:

Download bryn_mawr_campus_map_douglas_connect_meeting.pdf

[Please follow continuation here to view schedule.]

Chemogenomics eCheminfo cheminformatics chemoinformatics bioinformatics Medicinal Chemistry Computational Chemistry Virtual Screening Molecular Modelling Molecular Modeling pharmaceutical pharma meeting workshop training Oxford Critical Path toxicology Bursary Life Sciences Pharma Drug Discovery Research and Development Drug Development Healthcare Innovation Knowledge Management events

Computer-based Predictive Toxicology: Advances and Impact of Cheminformatics on the Safety-oriented Design of New Products

Current advances in computer-based predictive toxicology offer the potential to create more advanced environments for the screening and prediction of safety issues due to chemical and drug adverse side effects, drug-drug and chemical-system interactions, and chemical and drug toxicologies in the environment and the human body.  Advances in this growing field also offer the potential to replace or reduce the need for animal testing and to reduce later stage clinical trial failures or new product development rejection. Acceleration of progress in practical applications requires the creation of interoperable environments, knowledge sharing, data integration, algorithm development, and extensive validation and testing. 

Numerous opportunities exist in this field for scientific advances, but also for innovation, service and product development, and value creation. Additionally, significant collaboration approaches are a scientific, industry and society imperative to advance this field and the safety of new products and all society members.  Collaborative approaches need to support the multidisciplinary networking and collaboration between computer scientists, biologists, chemists, toxicologists, product development and clinical and environmental researchers, and to network groups, centers, initiatives, projects and data into interoperable semantic frameworks, systems, knowledge bases and virtual organisations.

At our Predictive Toxicology session chaired by Artem Cherkasov (University of British Columbia) running 17 October 2008 at Bryn Mawr recent developments in the field of predictive toxicology will be presented and discussed.

The session will be preceded the evening of October 16 by a Knowledge Café to discuss Collaboration Opportunities in Predictive ADME & Predictive Toxicology.

A description of the session with presentation abstracts follows.  Please add your comments, discussion or questions at the end of the post.

Predictive Toxicology

http://echeminfo.com/COMTY_confprog08predtox

(Please follow continuation here to read abstracts.  Comments can be made at the end.)

Predictive ADME: guiding the lead development and optimization process

The prediction of absorption, distribution, metabolism, and excretion (ADME) properties has become increasingly important as failures late in the drug discovery process become more costly. Increasingly, stringent in vitro and in vivo requirements have been placed on the hit-to-lead and lead optimization stages of the drug discovery process. Although it is tempting to dismiss ADME modeling and simply conduct an in vitro or in vivo experiment to get “the correct answer”, this approach is not practical. A skilled, competent medicinal chemist working on a lead optimization program can easily conceive of far more compounds than can reasonably be synthesized during the time of a lead optimization effort. In vivo studies are expensive and time-consuming and may become the rate-limiting step for some projects, particularly for small pharmaceutical companies. Rather than providing “the correct answer”, modeling provides a means of “stacking the deck” in favor of the medicinal chemistry effort, increasing the likelihood that a given compound will show the desired effect in vitro or in vivo.

At our Predictive ADME session chaired by Anthony Klon running October 16 at Bryn Mawr recent developments in the predictive modeling of ADME properties will be presented and discussed. Speakers will present their research into modeling microsomal stability, drug-drug interactions, and membrane transport processes such as blood-brain barrier penetration, intestinal absorption, and skin penetration. One topic of the accompanying discussions will be the appropriateness of relevant biological endpoints for ADME/PK modeling.

The session will be followed in the evening by a Knowledge Café to discuss Collaboration Opportunities in Predictive ADME & Predictive Toxicology.

A description of the session with presentation abstracts follows.  Please add your comments, discussion or questions at the end of the post.

Predictive ADME

http://echeminfo.com/COMTY_confprog08adme

(Please follow continuation here to read abstracts.  Comments can be made at the end.)

PDB Ligands: Analysing their Structure and Binding Data

The mechanism of action of the majority of therapeutic small-molecule drugs is based on formation of a non-covalent complex with a protein binding site. In spite of the availability of thousands of crystal structures of such small-molecule ligands, important aspects of the ligand binding process are still poorly understood or at least controversially discussed. These range from fundamental biophysical aspects such as ligand conformational energies to practical aspects such as the chemical identity of the ligand 3D structure deposited in, and/or perceived from, the Protein Data Bank (PDB). A similar situation exists regarding binding data, in terms of availability as well as quality of the experimental data.

The following questions need to be addressed:
- What do we have in terms of 3D structural and binding data for ligands?
- Where are these data? How accessible, how interconnected are the databases containing them?
- To what use are these data being put? What have we learned about ligand energies?
- What are the problems, and what's still missing?
- Do we need to, and can we, annotate PDB ligands with a reliability and quality score?

Ideally, we need to build a consensus on some of these questions, or at least on how to approach them in a concerted effort in order to further our understanding of protein-ligand interactions.

On 16-17 October 2008 we will hold an eCheminfo Community of Practice conference session at Bryn Mawr College, Philadelphia to address these questions related to PDB Ligands.  The session will be chaired by Marc Nicklaus (National Institutes of Health) and includes a knowledgeable panel of speakers and discussion leaders including John Westbrook (Rutgers), Howard J Feldman (CCG, Canada), Igor V. Filippov (NCI), Raul Cachau (ATP, SAIC-Frederick), Vincent T. Moy (University of Miami), Fabrice Moriaud (MEDIT, France), Paul Hawkins (OpenEye), Yulia Borodina (NCBI), Gerhard Wolber (Inte:Ligand, Austria), Marc Nicklaus (NCI), James P. Snyder (Emory), Anne Chaka (NIST), Esther Kellenberger (University of Strasbourg, France), Jim Dunbar (University of Michigan), and Janna Wehrle (NIGMS). A description of the session with presentation abstracts follows:

PDB Ligands: Analysing their Structure and Binding Data

http://echeminfo.com/COMTY_confprog08pdbligands

(Please follow continuation here to read abstracts)