FlexPred – Protein Fluctuation Prediction using SVR

FlexPred

:: DESCRIPTION

FlexPred predicts real-value fluctuation of each residues in a query protein structure. Predication can be performed for single-chain, complex proteins, and computational models.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Methods Mol Biol. 2017;1484:175-186. doi: 10.1007/978-1-4939-6406-2_13.
Predicting Real-Valued Protein Residue Fluctuation Using FlexPred.
Peterson L, Jamroz M, Kolinski A, Kihara D

BindML/BindML+ – Detecting Protein-Protein Interaction Interface Propensity

BindML/BindML+

:: DESCRIPTION

BindML predicts protein-protein interaction sites in a query protein structure by using evolutionary information.

BindML+ further classifies a binding site to permanent and transient interaction.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

BindML/BindML+: Detecting Protein-Protein Interaction Interface Propensity from Amino Acid Substitution Patterns.
Wei Q, La D, Kihara D.
Methods Mol Biol. 2017;1529:279-289.

GMQ – Prediction of Local Quality of Protein Structure Models Considering Spatial Neighbors

GMQ

:: DESCRIPTION

GMQ (Graph-based Model Quality assessment method) is a protein quality assessment program which employs conditional random field. The program gives a binary prediction that predicts a modeled residue has an error within a C-alpha distance cutoff or not.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

GMQ

:: MORE INFORMATION

Citation

Sci Rep. 2017 Jan 11;7:40629. doi: 10.1038/srep40629.
Prediction of Local Quality of Protein Structure Models Considering Spatial Neighbors in Graphical Models.
Shin WH, Kang X, Zhang J, Kihara D.

Dove – A Deep-learning based dOcking decoy eValuation mEthod

Dove

:: DESCRIPTION

Dove is a deep learning based protein docking model evluation method.It will use the atom information such as postions, types, energy scores in the interface area to judge if the docking model is reasonable.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

Dove

:: MORE INFORMATION

Citation

Bioinformatics. 2019 Nov 20. pii: btz870. doi: 10.1093/bioinformatics/btz870. [Epub ahead of print]
Protein Docking Model Evaluation by 3D Deep Convolutional Neural Networks.
Wang X, Terashi G, Christoffer CW, Zhu M, Kihara D.

MAINMAST 1.0 – MAINchain Model trAcing using Spanning Tree from a EM map

MAINMAST 1.0

:: DESCRIPTION

MAINMAST is a de novo modeling protocol to build an entire protein 3D model directly from near-atomic resolution EM map.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

MAINMAST

:: MORE INFORMATION

Citation

De novo main-chain modeling with MAINMAST in 2015/2016 EM Model Challenge.
Terashi G, Kihara D.
J Struct Biol. 2018 Nov;204(2):351-359. doi: 10.1016/j.jsb.2018.07.013.

VisGrid – Identify Pockets in Protein Surfaces

VisGrid

:: DESCRIPTION

The VisGrid algorithm identifies geometric features of protein surfaces using an intuitive concept of the visibility.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 VisGrid

:: MORE INFORMATION

Citation

Characterization of local geometry of protein surfaces with the visibility criterion.
Li B, Turuvekere S, Agrawal M, La D, Ramani K, Kihara D.
Proteins. 2008 May 1;71(2):670-83.

LZerD / Multi-LZerD / PI-LZerD – (Multiple) Protein-Protein Docking Algorithm

LZerD / Multi-LZerD / PI-LZerD

:: DESCRIPTION

LZerD: Protein-Protein Docking Algorithm

Multi-LZerD: protein docking for asymmetric complexes

PI-LZerD: Protein Docking Prediction Using Predicted Protein-Protein Interfaces

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  Linux
  • C++ Compiler

:: DOWNLOAD

  LZerD / Multi-LZerD / PI-LZerD

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2012 Jan 10;13:7. doi: 10.1186/1471-2105-13-7.
Protein docking prediction using predicted protein-protein interface.
Li B1, Kihara D.

Proteins. 2012 Jul;80(7):1818-33. doi: 10.1002/prot.24079. Epub 2012 May 8.
Multi-LZerD: multiple protein docking for asymmetric complexes.
Esquivel-Rodríguez J1, Yang YD, Kihara D.

BMC Proc. 2012 Nov 13;6 Suppl 7:S4. doi: 10.1186/1753-6561-6-S7-S4. Epub 2012 Nov 13.
Effect of conformation sampling strategies in genetic algorithm for multiple protein docking.
Esquivel-Rodríguez J1, Kihara D.

Methods Mol Biol. 2014;1137:209-34. doi: 10.1007/978-1-4939-0366-5_15.
Pairwise and multimeric protein-protein docking using the LZerD program suite.
Esquivel-Rodriguez J1, Filos-Gonzalez V, Li B, Kihara D.

AmberTools 19 – Molecular Dynamics Simulation

AmberTools 19

:: DESCRIPTION

AmberTools consists of several independently developed packages that work well by themselves, and with Amber (Assisted Model Building with Energy Refinement) itself. The suite can also be used to carry out complete (non-periodic) molecular dynamics simulations (using NAB), with generalized Born solvent models.

AmberTools consists of 7 main codes
NAB build molecules; run MD or distance geometry, using generalized Born, Poisson-Boltzmann or 3D-RISM implicit solvent models
antechamber Create force fields for general organic molecules
ptraj Analyze trajectories from Amber or CHARMM
tleap and xleap Basic preparation program for Amber simulations
sleap replaces and expands tleap
sqm semiempirical and DFTB quantum chemistry program
pbsa Performs numerical solutions to Poisson-Boltzmann models

::DEVELOPER

AMBER Team

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux /  MacOsX / Window with Cygwin

:: DOWNLOAD

AmberTools

:: MORE INFORMATION

Citation

D.A. Case, T.E. Cheatham, III, T. Darden, H. Gohlke, R. Luo, K.M. Merz, Jr., A. Onufriev, C. Simmerling, B. Wang and R. Woods.
The Amber biomolecular simulation programs.
J. Computat. Chem. 26, 1668-1688 (2005).

DOCK 6.9 – Docking Molecules to each other

DOCK 6.9

:: DESCRIPTION

DOCK addresses the problem of “docking” molecules to each other. In general, “docking” is the identification of the low-energy binding modes of a small molecule, or ligand, within the active site of a macromolecule, or receptor, whose structure is known. A compound that interacts strongly with, or binds, a receptor associated with a disease may inhibit its function and thus act as a drug. Solving the docking problem computationally requires an accurate representation of the molecular energetics as well as an efficient algorithm to search the potential binding modes.

::DEVELOPER

DOCK Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

DOCK

:: MORE INFORMATION

Lang, P.T., Brozell, S.R., Mukherjee, S., Pettersen, E.T., Meng, E.C., Thomas, V., Rizzo, R.C., Case, D.A., James, T.L., Kuntz, I.D.
DOCK 6: Combining Techniques to Model RNA-Small Molecule Complexes.
RNA 15:1219-1230, 2009.

UCSF Chimera 1.14 – Molecular Modeling System

UCSF Chimera 1.14

:: DESCRIPTION

UCSF Chimera is a highly extensible program for interactive visualization and analysis of molecular structures and related data, including density maps, supramolecular assemblies, sequence alignments, docking results, trajectories, and conformational ensembles. High-quality images and animations can be generated. Chimera includes complete documentation and several tutorials, and can be downloaded free of charge for academic, government, non-profit, and personal use.

::DEVELOPER

the Resource for Biocomputing, Visualization, and Informatics (RBVI) at UCSF

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux /  MacOsX / Window

:: DOWNLOAD

UCSF Chimera

:: MORE INFORMATION

Citation:

UCSF Chimera–a visualization system for exploratory research and analysis. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. J Comput Chem. 2004 Oct;25(13):1605-12.