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Protocols

myPresto specifications

Information


Unique identifier OMICS_21176
Name myPresto
Alternative name Medicinally Yielding Protein Engineering SimulatOr
Software type Toolkit/Suite
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++, Python
Computer skills Advanced
Version 4.412
Stability Stable
Maintained Yes

Subtool


  • psygene-G

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Maintainer


  • person_outline Kota Kasahara

Publication for Medicinally Yielding Protein Engineering SimulatOr

myPresto citations

 (22)
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Phosphorylation of an intrinsically disordered region of Ets1 shifts a multi modal interaction ensemble to an auto inhibitory state

2018
Nucleic Acids Res
PMCID: 5861456
PMID: 29309620
DOI: 10.1093/nar/gkx1297
call_split See protocol

[…] including the Ets1 core domain (). At the final production run, 9 × 106 steps were computed for each of 50 runs (total 540 ns) in the V-McMD scheme (). The computation was performed with the myPresto/psygene-G software (). […]

library_books

A novel rare variant R292H in RTN4R affects growth cone formation and possibly contributes to schizophrenia susceptibility

2017
PMCID: 5611737
PMID: 28892071
DOI: 10.1038/tp.2017.170

[…] )-like domain with weak sequence similarity (sequence identity=19.5%). The program MATRAS was used for the superimposition. The model was then refined using three programs: MODELLER, UCSF Chimera and myPresto. Details of the modeling procedure are provided in the and . […]

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Molecular mechanisms of cooperative binding of transcription factors Runx1–CBFβ–Ets1 on the TCRα gene enhancer

2017
PLoS One
PMCID: 5322934
PMID: 28231333
DOI: 10.1371/journal.pone.0172654
call_split See protocol

[…] are summarized in .For MD simulations, the energy optimization and equilibration runs were performed, using the Gromacs software []. The successive production runs were performed, using the myPresto/psygene-G software []. Amber parm99SB [] with bsc0 parameters [] was applied for the force-field of proteins and DNA. For the solution, the ion parameters determined by Joung and Cheatham [] and the T […]

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Revisiting antibody modeling assessment for CDR H3 loop

2016
PMCID: 5081041
PMID: 27515703
DOI: 10.1093/protein/gzw028
call_split See protocol

[…] and B was used for modeling. The initial structure of the CDR-H3 loop was taken from our previous model (), which had been built with the MODELLER program (), followed by energy minimization with the myPresto/cosgene program (). This structure, named joaAb10m3.pdb, is available at the AMA-II Web site (http://www.3dabmod.com). The other part of the antibody structure was exactly the same as the X-r […]

library_books

Variation of free‐energy landscape of the p53 C‐terminal domain induced by acetylation: Enhanced conformational sampling

2016
J Comput Chem
PMCID: 5242334
PMID: 27735058
DOI: 10.1002/jcc.24494

[…] t ensemble. However, the enhanced sampling method has higher efficiency than conventional sampling does. Later, we discuss statistical properties of the resultant ensembles.We used a computer program psygene–G for V‐McMD with the SHAKE method to fix the covalent‐bond length related to hydrogen atoms, the zero dipole summation method, , to calculate long‐range electrostatic interactions, the veloc […]

library_books

Elastic properties of dynein motor domain obtained from all atom molecular dynamics simulations

2016
PMCID: 4955872
PMID: 27334455
DOI: 10.1093/protein/gzw022

[…] e dynein motor domain, nucleotides, explicit water molecules and ions (size of the systems: approximately one million atoms). To execute the MD simulation of such a large system, we used our program, psygene-G (), which utilizes GPGPUs for acceleration of the non-bonded interactions, including the electrostatic computation by the ZD method. We performed 200-ns MD simulations for both the ADP and A […]


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myPresto institution(s)
College of Life Sciences, Ritsumeikan University, Shiga, Japan; College of Engineering, University of Illinois, Urbana-Champaign, IL, USA; School of Computing, Tokyo Institute of Technology, Tokyo, Japan; Institute for Protein Research, Osaka University, Osaka, Japan; Technology Research Association for Next Generation Natural Products Chemistry, Tokyo, Japan; Molecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
myPresto funding source(s)
Supported by Japan Society for the Promotion of Science KAKENHI (Grant Numbers 24118008, 24240044, 16K18526, and 16K05517). This work was performed in part under the Cooperative Research Program of Institute for Protein Research, Osaka University, CR-16-05.

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