DynaLab: a Google Colab Notebook Making Molecular Dynamics Researchers Accessible to Everyone
Session Number
Project ID: CMPS 43
Advisor(s)
Nick Bayhi, University of Chicago
Discipline
Computer Science
Start Date
17-4-2024 8:15 AM
End Date
17-4-2024 8:30 AM
Abstract
Molecular dynamics simulations (MD) sit at the interface of two fields, computer programming and biology, using the skills of the former to explore concepts and test hypotheses in the latter. MD elucidates protein motions that are vital to understanding a protein’s function and can be used to examine its interactions with its substrates in ways that are not obvious from the structures alone. MD is especially significant in the field of protein engineering, allowing researchers to explore how candidate mutations alter protein functionalities. While MD typically requires supercomputer access and extensive programming knowledge to implement, this barrier can be lowered using Google's Colaboratory Notebooks, which provide free computational resources to anyone with browser access. We have developed Dynalab, a plug-and-play Colab notebook that makes running and analyzing coarse-grained and all-atom simulations possible with minimal training or institutional resources. To showcase Dynalab’s abilities, we used it to examine potential destabilizing mutants of enhanced Green Fluorescent Protein (EGFP) – mutations that make it easier to pull the protein apart, losing its fluorescence. These mutants provide a theoretical basis for developing a ladder of force-sensitive GFP mutants to explore the strength of pulling forces in mechanosensitive protein systems.
DynaLab: a Google Colab Notebook Making Molecular Dynamics Researchers Accessible to Everyone
Molecular dynamics simulations (MD) sit at the interface of two fields, computer programming and biology, using the skills of the former to explore concepts and test hypotheses in the latter. MD elucidates protein motions that are vital to understanding a protein’s function and can be used to examine its interactions with its substrates in ways that are not obvious from the structures alone. MD is especially significant in the field of protein engineering, allowing researchers to explore how candidate mutations alter protein functionalities. While MD typically requires supercomputer access and extensive programming knowledge to implement, this barrier can be lowered using Google's Colaboratory Notebooks, which provide free computational resources to anyone with browser access. We have developed Dynalab, a plug-and-play Colab notebook that makes running and analyzing coarse-grained and all-atom simulations possible with minimal training or institutional resources. To showcase Dynalab’s abilities, we used it to examine potential destabilizing mutants of enhanced Green Fluorescent Protein (EGFP) – mutations that make it easier to pull the protein apart, losing its fluorescence. These mutants provide a theoretical basis for developing a ladder of force-sensitive GFP mutants to explore the strength of pulling forces in mechanosensitive protein systems.