Scoring function for predicting protein-ligand binding affinities

X-Score is basically a "scoring function", which computes the binding affinities of the given ligand molecules to their target protein. It can be applied to structure-based drug design studies in combination with molecular docking or de novo structure generation programs. X-Score is developed by Dr. Renxiao Wang in Dr. Shaomeng Wang's group at the Department of Internal Medicine, University of Michigan Medical School. The first paper that reported X-Score was published on Journal of Computer-Aided Molecular Design, 16: 1126, 2002. Note that X-Score was formerly known as X-CScore for a short while. To learn more about the X-Score program, please read the X-Score on-line manual.

X-Score is released to the public for free. The latest release is X-Score v1.2. You can download the program by clicking the link below. You will go through a license agreement and fill in some necessary registration information. Once we have received your signed license agreement, we will send you instructions of how to log on our server and download the X-Score package. The X-Score v1.2 package includes the program (executable and source codes), user manual, examples, references and the protein-ligand complex data set originally used for developing X-Score.

Click here to get the X-Score v1.2 package now!

Comparative Evaluation of Eleven Scoring Functions for Molecular Docking
J. Med. Chem. 2003, 46, 2287-2303.

Recently, we have evaluated X-Score v1.1 together with other 10 scoring functions through molecular docking experiments. Below is the test set used in that study. It includes the coordinates of 100 protein-ligand complexes together with the results of all of the scoring functions evaluated in this study.

Click here to download the test set used in this study now (dockset.tar.gz, ~34MB)

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Questions of obtaining the program, please contact Dr. Chao-Yie Yang.

These web pages are maintained by Dr. Chao-Yie Yang and Dr. Renxiao Wang. The latest update is made on 06/22/2017.