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DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics

Traditional informatics in comparative genomics work only with static representations of biomolecules (i.e., sequence and structure), thereby ignoring the molecular dynamics (MD) of proteins that define function in the cell. A comparative approach applied to MD would connect this very short timescal...

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Detalles Bibliográficos
Autores principales: Babbitt, Gregory A., Mortensen, Jamie S., Coppola, Erin E., Adams, Lily E., Liao, Justin K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Biophysical Society 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5883555/
https://www.ncbi.nlm.nih.gov/pubmed/29539389
http://dx.doi.org/10.1016/j.bpj.2018.01.020
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author Babbitt, Gregory A.
Mortensen, Jamie S.
Coppola, Erin E.
Adams, Lily E.
Liao, Justin K.
author_facet Babbitt, Gregory A.
Mortensen, Jamie S.
Coppola, Erin E.
Adams, Lily E.
Liao, Justin K.
author_sort Babbitt, Gregory A.
collection PubMed
description Traditional informatics in comparative genomics work only with static representations of biomolecules (i.e., sequence and structure), thereby ignoring the molecular dynamics (MD) of proteins that define function in the cell. A comparative approach applied to MD would connect this very short timescale process, defined in femtoseconds, to one of the longest in the universe: molecular evolution measured in millions of years. Here, we leverage advances in graphics-processing-unit-accelerated MD simulation software to develop a comparative method of MD analysis and visualization that can be applied to any two homologous Protein Data Bank structures. Our open-source pipeline, DROIDS (Detecting Relative Outlier Impacts in Dynamic Simulations), works in conjunction with existing molecular modeling software to convert any Linux gaming personal computer into a “comparative computational microscope” for observing the biophysical effects of mutations and other chemical changes in proteins. DROIDS implements structural alignment and Benjamini-Hochberg-corrected Kolmogorov-Smirnov statistics to compare nanosecond-scale atom bond fluctuations on the protein backbone, color mapping the significant differences identified in protein MD with single-amino-acid resolution. DROIDS is simple to use, incorporating graphical user interface control for Amber16 MD simulations, cpptraj analysis, and the final statistical and visual representations in R graphics and UCSF Chimera. We demonstrate that DROIDS can be utilized to visually investigate molecular evolution and disease-related functional changes in MD due to genetic mutation and epigenetic modification. DROIDS can also be used to potentially investigate binding interactions of pharmaceuticals, toxins, or other biomolecules in a functional evolutionary context as well.
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spelling pubmed-58835552019-03-13 DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics Babbitt, Gregory A. Mortensen, Jamie S. Coppola, Erin E. Adams, Lily E. Liao, Justin K. Biophys J Computational Tools Traditional informatics in comparative genomics work only with static representations of biomolecules (i.e., sequence and structure), thereby ignoring the molecular dynamics (MD) of proteins that define function in the cell. A comparative approach applied to MD would connect this very short timescale process, defined in femtoseconds, to one of the longest in the universe: molecular evolution measured in millions of years. Here, we leverage advances in graphics-processing-unit-accelerated MD simulation software to develop a comparative method of MD analysis and visualization that can be applied to any two homologous Protein Data Bank structures. Our open-source pipeline, DROIDS (Detecting Relative Outlier Impacts in Dynamic Simulations), works in conjunction with existing molecular modeling software to convert any Linux gaming personal computer into a “comparative computational microscope” for observing the biophysical effects of mutations and other chemical changes in proteins. DROIDS implements structural alignment and Benjamini-Hochberg-corrected Kolmogorov-Smirnov statistics to compare nanosecond-scale atom bond fluctuations on the protein backbone, color mapping the significant differences identified in protein MD with single-amino-acid resolution. DROIDS is simple to use, incorporating graphical user interface control for Amber16 MD simulations, cpptraj analysis, and the final statistical and visual representations in R graphics and UCSF Chimera. We demonstrate that DROIDS can be utilized to visually investigate molecular evolution and disease-related functional changes in MD due to genetic mutation and epigenetic modification. DROIDS can also be used to potentially investigate binding interactions of pharmaceuticals, toxins, or other biomolecules in a functional evolutionary context as well. The Biophysical Society 2018-03-13 2018-03-13 /pmc/articles/PMC5883555/ /pubmed/29539389 http://dx.doi.org/10.1016/j.bpj.2018.01.020 Text en © 2018 Biophysical Society. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Computational Tools
Babbitt, Gregory A.
Mortensen, Jamie S.
Coppola, Erin E.
Adams, Lily E.
Liao, Justin K.
DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics
title DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics
title_full DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics
title_fullStr DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics
title_full_unstemmed DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics
title_short DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics
title_sort droids 1.20: a gui-based pipeline for gpu-accelerated comparative protein dynamics
topic Computational Tools
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5883555/
https://www.ncbi.nlm.nih.gov/pubmed/29539389
http://dx.doi.org/10.1016/j.bpj.2018.01.020
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