Welcome to KVFinder-web’s documentation!

Welcome to the KVFinder-web documentation, this page was built to help you get started with our web-based application for cavity detection and characterization.

KVFinder-web overview

KVFinder-web [4] is an open-source web-based application of an updated version of parKVFinder software [3] (v1.2.0) for cavity detection and characterization of any type of biomolecular structure. The characterization includes spatial, depth, constitutional and hydropathy characterization.

We provide a publicly available KVFinder-web at https://kvfinder-web.cnpem.br.

KVFinder-web components

The KVFinder-web has two independent components:

RESTful web service: KVFinder-web service;
Graphical web portal: KVFinder-web portal.

Client-side applications

To broaden the range of possibilities for user interaction, we also provide additional client-side applications, that are:

PyMOL KVFinder-web Tools: a graphical PyMOL plugin.
HTTP client: an example of a Python HTTP client;

Both client-side applications sends job via HTTP requests to the KVFinder-web service, customize detection parameters and process job results.

parKVFinder

parKVFinder [3] uses grid-and-sphere-based methods to detect, characterize and visualize any type of biomolecular cavity. The cavity detection procedure applies a dual-probe algorithm based on the theory of mathematical morphology, originally implemented in KVFinder [5].

Recently, parKVFinder (v1.2.0) has been integrated with additional features, such as depth calculation and Eisenberg & Weiss [2] hydropathy characterization, which are implemented in pyKVFinder [1].

Now, cavity characterization includes spatial, depth, constitutional and hydropathy properties. The depth characterization defines depths for each cavity point, shown in the B-factor, and calculates the average and maximum depth per cavity. The constitutional characterization includes amino acids that form the identified cavities. The hydropathy characterization maps Eisenberg & Weiss hydrophobicity scale at surface points, shown in the Q-factor, and estimates average hydropathy per cavity.

Furthermore, parKVFinder has a standalone version available as an easy-to-use PyMOL plugin with an intuitive graphical user interface that allows users to explore customizable parameters for cavity detection and characterization.