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For downloading myPresto newest version. myPresto is a program suite composed of several molecular simulations for drug development.

Medicinally Yielding PRotein Engineering SimulaTOr

myPresto is a program suite composed of several molecular simulations for drug development.

This page is for downloading free program myPresto newest version.

How to cite

Program / MethodReferences (Please cite the following for each program or method used.)
myPresto portal IMSBIO CO., Ltd. Tokyo
Easy myPresto FiatLux, Tokyo
myPresto General /
cosgene /
filling potential
The Filling Potential Method: A Method for Estimating the Free Energy Surface for Protein-Ligand Docking
Yoshifumi Fukunishi, Yoshiaki Mikami, and Haruki Nakamura
The Journal of Physical Chemistry B 2003 107 (47), 13201-13210
DOI: 10.1021/jp035478e
SRPGThe Filling Potential Method: A Method for Estimating the Free Energy Surface for Protein-Ligand Docking
Yoshifumi Fukunishi, Yoshiaki Mikami, and Haruki Nakamura
The Journal of Physical Chemistry B 2003 107 (47), 13201-13210
DOI: 10.1021/jp035478e

Protein-Ligand Binding Free Energy Calculation by the Smooth Reaction Path Generation (SRPG) Method
Y Fukunishi, D Mitomo, H Nakamura
Journal of chemical information and modeling 2009 49 (8), 1944-1951
psygene /
psygene-G /
zero-dipole method
The Filling Potential Method: A Method for Estimating the Free Energy Surface for Protein-Ligand Docking
Yoshifumi Fukunishi, Yoshiaki Mikami, and Haruki Nakamura
The Journal of Physical Chemistry B 2003 107 (47), 13201-13210
DOI: 10.1021/jp035478e

Molecular dynamics simulations accelerated by GPU for biological macromolecules with a non-Ewald scheme for electrostatic interactions
T Mashimo, Y Fukunishi, N Kamiya, Y Takano, I Fukuda, H Nakamura
Journal of chemical theory and computation 2013 9 (12), 5599-5609
Receptor-ligand dockingSimilarities among receptor pockets and among compounds: analysis and application to in silico ligand screening
Y Fukunishi, Y Mikami, H Nakamura
Journal of Molecular Graphics and Modelling 2005 24 (1), 34-45
sievgeneNMR : Receptor-ligand dockingSimilarities among receptor pockets and among compounds: analysis and application to in silico ligand screening
Y Fukunishi, Y Mikami, H Nakamura
Journal of Molecular Graphics and Modelling 2005 24 (1), 34-45

Protein-ligand docking guided by ligand pharmacophore-mapping experiment by NMR
Y Fukunishi, Y Mizukoshi, K Takeuchi, I Shimada, H Takahashi, H. Nakamura.
Journal of Molecular Graphics and Modelling 2011 31, 20-27
SBDD : Multile-target screening methodSimilarities among receptor pockets and among compounds: analysis and application to in silico ligand screening
Y Fukunishi, Y Mikami, H Nakamura
Journal of Molecular Graphics and Modelling 2005 24 (1), 34-45

Multiple target screening method for robust and accurate in silico ligand screening
Y Fukunishi, Y Mikami, S Kubota, H Nakamura
Journal of Molecular Graphics and Modelling 2006 25 (1), 61-70

Noise reduction method for molecular interaction energy: application to in silico drug screening and in silico target protein screening
Y Fukunishi, S Kubota, H Nakamura
Journal of chemical information and modeling 2006 46 (5), 2071-2084
DOI: 10.1021/ci060152z
LBDD : Doking-score index methodSimilarities among receptor pockets and among compounds: analysis and application to in silico ligand screening
Y Fukunishi, Y Mikami, H Nakamura
Journal of Molecular Graphics and Modelling 2005 24 (1), 34-45

Classification of chemical compounds by protein? compound docking for use in designing a focused library
Y Fukunishi, Y Mikami, K Takedomi, M Yamanouchi, H Shima, …
Journal of Medicinal Chemistry 2006 49 (2), 523-533
DOI: 10.1021/jm050480a

An Efficient in Silico Screening Method Based on the Protein-Compound Affinity Matrix and Its Application to the Design of a Focused Library for Cytochrome P450 (CYP) Ligands
Y Fukunishi, S Hojo, H Nakamura
Journal of chemical information and modeling 2006 46 (6), 2610-2622
DOI: 10.1021/ci600334u
LigandBoxAdvanced in-silico drug screening to achieve high hit ratio -Development of 3D-compound database-
Y Fukunishi, Y Sugihara, Y Mikami, K Sakai, H Kusudo, H Nakamura
Synthesiology English edition 2009 2 (1), 64-72

LigandBox: a database for 3D structures of chemical compounds
T Kawabata, Y Sugihara, Y Fukunishi, H Nakamura
Biophysics 2013 9, 113-121
MVOA new method for in-silico drug screening and similarity search using molecular dynamics maximum volume overlap (MD-MVO) method
Y Fukunishi, H Nakamura
Journal of Molecular Graphics and Modelling 2009 27 (5), 628-636

Prediction of protein-ligand complex structure by docking software guided by other complex structures
Y Fukunishi, H Nakamura
Journal of Molecular Graphics and Modelling 2008 26 (6), 1030-1033
MolSiteSimilarities among receptor pockets and among compounds: analysis and application to in silico ligand screening
Y Fukunishi, Y Mikami, H Nakamura
Journal of Molecular Graphics and Modelling 2005 24 (1), 34-45

Prediction of ligand‐binding sites of proteins by molecular docking calculation for a random ligand library
Y Fukunishi, H Nakamura
Protein Science 2010 20 (1), 95-106
synthetic accessibilityPrediction of synthetic accessibility based on commercially available compound databases
Y Fukunishi, T Kurosawa, Y Mikami, H Nakamura
Journal of chemical information and modeling 2014 54 (12), 3259-3267
docking-score QSARSimilarities among receptor pockets and among compounds: analysis and application to in silico ligand screening
Y Fukunishi, Y Mikami, H Nakamura
Journal of Molecular Graphics and Modelling 2005 24 (1), 34-45

Quantitative Structure‐activity Relationship (QSAR) Models for Docking Score Correction
Y Fukunishi, S Yamasaki, I Yasumatsu, K Takeuchi, T Kurosawa, Nakamura..
Molecular informatics 2016 36 (1-2), 1600013

Prediction of protein-compound binding energies from known activity data: docking‐score‐based method and its applications
Y Fukunishi, Y Yamashita, T Mashimo, H Nakamura
Molecular Informatics 2018 37 (6-7), 1700120
Molecular-property predictionPrediction of Passive Membrane Permeability by Semi‐Empirical Method Considering Viscous and Inertial Resistances and Different Rates of Conformational Change and Diffusion
Y Fukunishi, T Mashimo, T Kurosawa, Y Wakabayashi, HK Nakamura, K Takeuchi.
Molecular Informatics 2019 39 (1-2), 1900071

Quantitative analysis of aggregation-solubility relationship by in-silico solubility prediction
T Mashimo, Y Fukunishi, M Orita, N Katayama, S Fujita, H Nakamura
International Journal of High Throughput Screening, 2010 99-107
DOI: 10.2147/IJHTS.S9735