Please cite the following paper Xavier et al. 2016 when using SAnDReS

Stairway to SAnDReS for Windows   

You need to have Python 3 installed on your computer to run SAnDReS. In addition, you also need NumPyMatplotlibscikit-learn, and SciPy. You can make the installation process easier by installing pyzo. While installing them, let's the music play...

Step 1. Install the Pyzo IDE (download here)

Step 2. Install Python environment (download here)

Step 3. Install Scientific packages needed to run SAnDReS. Open Pyzo IEP. To run Pyzo IEP, go to c:\Program Files (x86)\pyzo directory and you will have the pyzo IEP. Double click on pyzo.

In the Pyzo’s shell (IEP), type the following commands:     

     conda install numpy

After finishing NumPy installation, type:

    conda install scipy pyqt matplotlib

    conda install scikit-learn

Step 4. Download SAnDReS 1.0.2 (download here)

Step 5. Unzip the zipped file (sandres.zip) 

Step 6. Copy sandres directory to c:\ .

Step 7. Open a command prompt window and type:

    cd c:\sandres


    python sandres1_GUI.py

This launches GUI window for SAnDReS. That´s it, good sandres session.

See tutorial page for additional information about how to run SAnDReS. You can also start SAnDReS clicking on the sandres.bat file. You may also create a shortcut for SAnDReS right clicking on the sandres.bat file.

Biological Systems Analyzed by SAnDReS

Below you have a list of biological systems that were analyzed using SAnDReS. Each zipped folder has the following files: chklig.in, decoy_results.csv (except for System 2), ensembledock.csv, pdbCodes.csv, polscore.csv, polscore.log, Polscore folder, redock01.csv, scores_all.csv, test_set.csv, and training_set.csv. See tutorial page for additional information about these files.

System 1: Cyclin-Dependent Kinases with Ki Information   ZIP

System 2: Crystallographic structures with resolution higher than 1.5 A and IC50 Information   ZIP

System 3: CSAR 2014 Benchmark Exercise for Coagulation Factor Xa with Ki Information   ZIP  

System 4: Cyclin-Dependent Kinases with IC50 Information   ZIP  

System 5: HIV-1 Protease with Ki Information   ZIP

Related Links  

     -A Database of Useful Decoys: Enhanced (DUDE)     
     -Enzyme Nomenclature Database (Expasy)     
     -Scikit-learn Machine Learning Techniques for Regression   
     -Protein Data Bank (PDB)     
     -UCI Machine Learning Repository   
     -Wolfram Demonstration Projects for Machine Learning   
     -Wolfram Demonstration Projects for Regression     
     -Wolfram Demonstration Projects for Stochastic Gradient Descent