About Us

Committed to improving research and development productivity for organizations around the world through better science and technology.

Discovery Studio & Predictive Sciences Webinars

BIOVIA Discovery Studio® software provides comprehensive modeling and simulation capabilities for computational chemists, computational biologists, and other scientists engaged in small molecule and biotherapeutics-based research. The latest release is a comprehensive product update that extends our portfolio of small molecule drug design and market-leading biological simulation tools.

We invite you to learn how the latest release of Discovery Studio helps improve efficiency and collaboration throughout your organization in this webinar series. These webinars are recommended for people familiar with Discovery Studio.

Webinars will continue to be added, please check back often.

Past Webinars

Title and Speaker

Accelerate Development, Validation and Deployment of QSAR Models
Adrian Stevens, Senior Manager of Modeling & Simulations, BIOVIA

In the past 15 years, automation in drug discovery projects led to massive increases in the amounts of data generated by multifunctional chemistry and biology teams. Data trends and patterns can help project teams make important decisions about what entity to make next in a series. The challenge is how to speed the process and reduce costs.

Developed in collaboration with GSK, the BIOVIA QSAR Workbench automates and accelerates the development, validation, deployment and life cycle management of predictive Quantitative Structure-Activity Relationship (QSAR) models. Join us to learn how to:

  • Reduce QSAR modeling time from days to hours
  • Explore and compare statistical space to identify robust, predictive QSAR models
  • Extend the reach of statistical experts

Live demos of the BIOVIA QSAR Workbench will also be shared.

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Predictive Sciences: A Transformational Opportunity For Pharmaceutical Research And Development
Dr. Chris Waller, Head of Scientific Modeling Platforms at Merck

Pharmaceutical research and development is a time- and data-intensive endeavor that requires the ability to leverage experience and knowledge in order to avoid repeating mistakes of the past, minimize late stage attrition, and help ensure that the molecules we discover and put into development become medicines.

The Predictive Sciences Program at Merck is a comprehensive package of data access, aggregation, predictive modeling, and advanced analytics that will transform productivity by releasing Merck data and the associated computational models to inform the research and development decision making processes. We anticipate a transformational step change through optimizing the use of public data, Merck data, natural language processing, and predictive models for hypothesis generation. This capability will allow scientists to use enhanced judgment in decision making, resulting in reduced attrition and cycle time and increased Merck research and development pipeline productivity. This talk will provide an update on the creation of the predictive sciences platform at Merck.

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Discovery Studio Non-Bond Analysis: Understanding Interactions
Tien Luu, Advisory Scientific Specialist, Life Science

The perception, rationalization and optimization of non-bonded interactions is one of the fundamental challenges in rational drug design. Advancing theory and new experimental evidence for molecular interactions beyond classical hydrogen bonds and hydrophobic effects have necessitated a more sophisticated and comprehensive analysis of the interactions involved in shaping and stabilizing protein conformations, protein-protein, and protein-small molecule interactions. Discovery Studio 4.0 has fully re-engineered and expanded the perception of non-bond interactions, including favorable, unfavorable and unsatisfied interactions. This webinar will present new client visualization tools to quickly and easily capture and render non-bond interactions and server components to rapidly calculate non-bond interactions for post-processing, enrichment of screening results and interaction fingerprint analysis.

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Antibody Design in Discovery Studio 3.5
Anne Goupil, Principal Scientist

In this webinar we will present the new tools that have been implemented in Discovery Studio to work on Antibodies: numbering and alignment tools based on numbering identify Framework templates, Developability Indices calculation. We will also show some examples on how to use these tools in the Discovery Studio interface.

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Computational Scanning Mutagenesis of Proteins and Protein Complexes

Anne Goupil, Principal Scientist, BIOVIA
Adrian Stevens, Senior Product Marketing Manager, BIOVIA

Understanding the effect of mutation to protein stability and on protein binding affinity is key to designing protein therapeutics and also to explaining the effect of naturally occurring mutations to biological events.  We present two novel CHARMm-based computational protocols to calculate the free energy changes of protein stability and binding affinity resulting from amino acid substitutions1.  In contrast to existing published methods, the temperature dependence of energy contributions is included in the physical model.  This is known to be important in understanding and improving the thermal stability of proteins.  Furthermore, the use of Generalized Born solvation model with implicit membrane2 makes the methods applicable to transmembrane proteins.  The calculations are fast and automated so that not only alanine scanning, but complete amino acid scanning can be performed on large set of residues easily.  Validation results and possible application of the method for the purposes of protein design and bioinformatics are discussed.

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The Antibody Humanization Process by CDR Grafting

Leonardo Borras, Head, Protein Engineering, ESBATech LLC

The transfer of antigen binding loops from a non-human antibody donor to a human framework must be performed so that the native loop conformations are retained for binding. Often, antigen binding affinity is greatly reduced or abolished after CDR grafting. This binding activity is only restored after reverting one or more human framework residues to donor equivalents in the humanized antibody. The identification of critical framework residues that contribute to CDR conformation represents the most difficult and unpredictable step in the antibody humanization process. Here antibody modeling procedures and sequence analysis are described to assist the selection of framework mutations in the antibody humanization process.

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An Introduction to Discovery Studio 3.0

Tien Luu - Lead Scientist, Accelrys
Adrian Stevens - Sr. Product Marketing Manager, Accelrys

The release of Accelrys’ Discovery Studio 3.0 in November extends our portfolio of small molecule drug design and market leading biological simulation tools and is focused on bringing new science from Accelrys and our partners, improved performance, and key enhancements to our users. This webinar will introduce users to key enhancements within the client designed to improve usability and encourage collaboration, as well as providing an overview of the new scientific developments.

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