PrankWeb is an online resource providing an interface to P2Rank, a state-of-the-art method for ligand binding site prediction. P2Rank is a template-free machine learning method based on the prediction of local chemical neighborhood ligandability centered on points placed on a solvent-accessible protein surface. Points with a high ligandability score are then clustered to form the resulting ligand binding sites. In addition, PrankWeb provides a web interface enabling users to easily carry out the prediction and visually inspect the predicted binding sites via an integrated sequence-structure view. Moreover, PrankWeb can determine sequence conservation for the input molecule and use this in both the prediction and result visualization steps. Alongside its online visualization options, PrankWeb also offers the possibility of exporting the results as a PyMOL script for offline visualization. The web frontend communicates with the server side via a REST API. In high-throughput scenarios, therefore, users can utilize the server API directly, bypassing the need for a web-based frontend or installation of the P2Rank application. PrankWeb is available at http://prankweb.cz/, while the web application source code and the P2Rank method can be accessed at https://github.com/jendelel/PrankWebApp and https://github.com/rdk/p2rank, respectively.

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PrankWeb is an online resource providing an interface to P2Rank, a state-of-the-art ligand binding site prediction method. P2Rank is a template-free machine learning method which is based on the prediction of ligandability of local chemical neighborhoods centered on points placed on a solvent accessible surface of a protein. Points with high ligandability score are then clustered to form the resulting ligand binding sites. On top of that, PrankWeb then provides a web interface enabling users to easily carry out the prediction and visually inspect the predicted binding sites via an integrated sequence-structure view. Moreover, PrankWeb can determine sequence conservation for the input molecule and use it in both the prediction and results visualization steps. Alongside its online visualization options, PrankWeb also offers the possibility to export the results as a PyMOL script for offline visualization. The web frontend communicates with the serer side via a REST API. Therefore, in high-throughput scenarios users can utilize the server API directly, bypassing the need for a webbased front end or installation of the P2Rank application. PrankWeb is available at

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