50 min
Systematic Analysis of Biomolecular Conformational Ensembles with PENSA | Martin Vögele Molecular Modelling and Drug Discovery
-
- Science
[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides.
Try datamol.io - the open source toolkit that simplifies molecular processing and featurization workflows for machine learning scientists working in drug discovery: https://datamol.io/
If you enjoyed this talk, consider joining the Molecular Modeling and Drug Discovery (M2D2) talks live.
Also, consider joining the M2D2 Slack.
Abstract: Molecular simulations enable the study of biomolecules and their dynamics on an atomistic scale. A common task is to compare several simulation conditions - like mutations or different ligands - to find significant differences and interrelations between them. However, the large amount of data produced for ever larger and more complex systems often renders it difficult to identify the structural features that are relevant for a particular phenomenon. PENSA is a flexible software package that enables a comprehensive and thorough investigation into biomolecular conformational ensembles. It provides a wide variety of featurizations and feature transformations that allow for a complete representation of biomolecules like proteins and nucleic acids, including water and ion cavities within the biomolecular structure, thus avoiding bias that would come with manual selection of features. PENSA implements various methods to systematically compare the distributions of these features across ensembles to find the significant differences between them and identify regions of interest. It also includes a novel approach to quantify the state-specific information between two regions of a biomolecule which allows, e.g., the tracing of information flow to identify signaling pathways. PENSA is a modular open-source library that also comes with convenient tools for loading data and visualizing results in ways that make them quick to process and easy to interpret. This talk will demonstrate its usefulness in real-world examples by showing how it helps to determine molecular mechanisms efficiently.
Speaker: Martin Vögele
Twitter - Prudencio
Twitter - Jonny
Twitter - datamol.io
[DISCLAIMER] - For the full visual experience, we recommend you tune in through our YouTube channel to see the presented slides.
Try datamol.io - the open source toolkit that simplifies molecular processing and featurization workflows for machine learning scientists working in drug discovery: https://datamol.io/
If you enjoyed this talk, consider joining the Molecular Modeling and Drug Discovery (M2D2) talks live.
Also, consider joining the M2D2 Slack.
Abstract: Molecular simulations enable the study of biomolecules and their dynamics on an atomistic scale. A common task is to compare several simulation conditions - like mutations or different ligands - to find significant differences and interrelations between them. However, the large amount of data produced for ever larger and more complex systems often renders it difficult to identify the structural features that are relevant for a particular phenomenon. PENSA is a flexible software package that enables a comprehensive and thorough investigation into biomolecular conformational ensembles. It provides a wide variety of featurizations and feature transformations that allow for a complete representation of biomolecules like proteins and nucleic acids, including water and ion cavities within the biomolecular structure, thus avoiding bias that would come with manual selection of features. PENSA implements various methods to systematically compare the distributions of these features across ensembles to find the significant differences between them and identify regions of interest. It also includes a novel approach to quantify the state-specific information between two regions of a biomolecule which allows, e.g., the tracing of information flow to identify signaling pathways. PENSA is a modular open-source library that also comes with convenient tools for loading data and visualizing results in ways that make them quick to process and easy to interpret. This talk will demonstrate its usefulness in real-world examples by showing how it helps to determine molecular mechanisms efficiently.
Speaker: Martin Vögele
Twitter - Prudencio
Twitter - Jonny
Twitter - datamol.io
50 min