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SAnDReS (Statistical Analysis of Docking Results and Scoring functions) is a free and open-source (GNU General Public License) computational environment for the development of machine-learning models for the prediction of ligand-binding affinity. We developed SAnDReS using Python programming language, and SciPy, NumPy, scikit-learn, and Matplotl…

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SAnDReS 2.0

Statistical Analysis of Docking Results and Scoring Functions 2.0 (SAnDReS 2.0)(https://azevedolab.net/sandres.php)

 

SAnDReS 2.0 brings together the most advanced tools for protein-ligand docking simulation and machine-learning modeling. We have the newest version of AutoDock Vina, available in February 2022 (version 1.2.3), as a docking engine. Also, SAnDReS 2.0 uses the latest version of Scikit-Learn, available in February 2022 (version 1.0.2). It has 64 regression methods which allow us to explore the Scoring Function Space (SFS). This exploration of the SFS permits us to have an adequate machine-learning (ML) model for a targeted protein system. SAnDReS predicts binding affinity for a specific protein system with superior performance compared against classical scoring functions. In summary, SAnDReS 2.0 makes it possible for you to design a scoring function adequate to the protein system of your interest.

You need Python 3 installed on your computer to run SAnDReS 2.0. In addition, you need Matplotlib, NumPy, Scikit-Learn, SciPy, and XGBoost. It is also necessary to have MGLTools 1.5.7. You can make the installation of Python packages faster by installing Anaconda.

 

 

SAnDReS User Guide is available here (Flipbook): https://heyzine.com/flip-book/5d80a7bcb7.html

 

SAnDReS User Guide is available here (PDF): https://github.com/azevedolab/sandres/blob/master/sandres_user_guide_2022_03.pdf

 

Installing SAnDReS (Linux)

You should type all commands shown here in a Linux terminal. The easiest way to open a Linux terminal is to use the Ctrl+Alt+T key combination.

Step 1. Download MGLTools 1.5.7 (https://ccsb.scripps.edu/mgltools/downloads/).

Type the following commands:

cd ~

cp Downloads/mgltools_Linux-x86_64_1.5.7_install .

chmod u+x mgltools_Linux-x86_64_1.5.7_install 

./mgltools_Linux-x86_64_1.5.7_install 

Step 2. Download Anaconda Installer for Linux (https://repo.anaconda.com/archive/Anaconda3-2021.11-Linux-x86_64.sh).

Go to the directory where you have the installer file and type the following commands:

chmod u+x Anaconda3-2021.11-Linux-x86_64.sh

./Anaconda3-2021.11-Linux-x86_64.sh

Follow the instructions of the installer. You may use a newer installer, but be sure to have the right installer in the above command lines.

Step 3. To run SAnDReS 2.0 properly, you need Scikit-Learn 1.0.2. To be sure you have version 1.0.2, open a terminal and type the following commands:

python3 -m pip uninstall scikit-learn

python3 -m pip install scikit-learn==1.0.2

Step 4. To install XGBoost (https://xgboost.readthedocs.io/en/latest/install.html#python), type the following command in a terminal:

python3 -m pip install xgboost

Step 5. Download SAnDReS 2.0 (https://github.com/azevedolab/sandres/raw/master/sandres2.zip). Copy the sandres2 zipped directory (sandres2.zip) to wherever you want it and unzip the zipped directory.

Type the following command:

unzip sandres2.zip

cd to sandres2 directory then, type:

python3 sandres2.py

Now you have the GUI window for SAnDReS 2.0.

That´s it, good SAnDReS session!

 

 

Installing SAnDReS (Windows)

Step 1. Install MGLTools 1.5.7 (https://ccsb.scripps.edu/mgltools/downloads/).

Step 2. Install Anaconda (https://www.anaconda.com/download/). Right-click the Windows Start Menu icon and select the Anaconda prompt. From now on, insert all commands in an Anaconda prompt.

Step 3. To run SAnDReS 2.0 properly, you need Scikit-Learn 1.0.2. To be sure you have version 1.0.2, open an Anaconda prompt and type the following commands:

python -m pip uninstall scikit-learn

python -m pip install scikit-learn==1.0.2

Step 4. To install XGBoost (https://xgboost.readthedocs.io/en/latest/install.html#python), type the following command:

python -m pip install xgboost

Step 5. Download SAnDReS 2.0 (https://github.com/azevedolab/sandres/raw/master/sandres2_win.zip). Copy the sandres2_win zipped directory (sandres2_win.zip) to wherever you want it and unzip the zipped directory.

Open an Anaconda Prompt and cd to sandres2_win directory then, type:

python sandres2.py

Now you have the GUI window for SAnDReS 2.0.

That´s it, good SAnDReS session!

About

SAnDReS (Statistical Analysis of Docking Results and Scoring functions) is a free and open-source (GNU General Public License) computational environment for the development of machine-learning models for the prediction of ligand-binding affinity. We developed SAnDReS using Python programming language, and SciPy, NumPy, scikit-learn, and Matplotl…

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