Computational analysis of missense mutations from the human Macrophage Migration Inhibitory Factor (MIF) protein by Molecular Dynamics Simulations and Dynamic Residue Network Analysis:
- Kimuda, Phillip M, Brown, David K, Amamuddy, Olivier S, Ross, Caroline J, Matovu, Enock, Tastan Bishop, Özlem
- Authors: Kimuda, Phillip M , Brown, David K , Amamuddy, Olivier S , Ross, Caroline J , Matovu, Enock , Tastan Bishop, Özlem
- Date: 2019
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/163238 , vital:41021 , https://doi.org/10.21955/aasopenres.1115054.1
- Description: Missense mutations are changes in the DNA that result in a change in the amino acid sequence. Depending on their location within the protein they can have a negative impact on how the protein functions. This is especially important for proteins involved in the body’s response to infection and diseases. Macrophage migration inhibitory factor (MIF) is one such protein that functions to recruit white blood cells to sites of inflammation.
- Full Text:
- Date Issued: 2019
- Authors: Kimuda, Phillip M , Brown, David K , Amamuddy, Olivier S , Ross, Caroline J , Matovu, Enock , Tastan Bishop, Özlem
- Date: 2019
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/163238 , vital:41021 , https://doi.org/10.21955/aasopenres.1115054.1
- Description: Missense mutations are changes in the DNA that result in a change in the amino acid sequence. Depending on their location within the protein they can have a negative impact on how the protein functions. This is especially important for proteins involved in the body’s response to infection and diseases. Macrophage migration inhibitory factor (MIF) is one such protein that functions to recruit white blood cells to sites of inflammation.
- Full Text:
- Date Issued: 2019
MD-TASK: a software suite for analyzing molecular dynamics trajectories
- Brown, David K, Penkler, David L, Amamuddy, Olivier S, Ross, Caroline J, Atilgan, Ali R, Atilgan, Canan, Tastan Bishop, Özlem
- Authors: Brown, David K , Penkler, David L , Amamuddy, Olivier S , Ross, Caroline J , Atilgan, Ali R , Atilgan, Canan , Tastan Bishop, Özlem
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/125138 , vital:35735 , https://doi.10.1093/bioinformatics/btx349
- Description: Molecular dynamics (MD) determines the physical motions of atoms of a biological macromolecule in a cell-like environment and is an important method in structural bioinformatics. Traditionally, measurements such as root mean square deviation, root mean square fluctuation, radius of gyration, and various energy measures have been used to analyze MD simulations. Here, we present MD-TASK, a novel software suite that employs graph theory techniques, perturbation response scanning, and dynamic cross-correlation to provide unique ways for analyzing MD trajectories.
- Full Text:
- Date Issued: 2017
- Authors: Brown, David K , Penkler, David L , Amamuddy, Olivier S , Ross, Caroline J , Atilgan, Ali R , Atilgan, Canan , Tastan Bishop, Özlem
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/125138 , vital:35735 , https://doi.10.1093/bioinformatics/btx349
- Description: Molecular dynamics (MD) determines the physical motions of atoms of a biological macromolecule in a cell-like environment and is an important method in structural bioinformatics. Traditionally, measurements such as root mean square deviation, root mean square fluctuation, radius of gyration, and various energy measures have been used to analyze MD simulations. Here, we present MD-TASK, a novel software suite that employs graph theory techniques, perturbation response scanning, and dynamic cross-correlation to provide unique ways for analyzing MD trajectories.
- Full Text:
- Date Issued: 2017
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