Download Pocket Estimation For Pc ((LINK))

PockDrug workflow is divided into three different phases: (a) identifying protein pocket(s) (Input & pocket estimation methods) , (b) PockDrug: fast computation of physico-chemical and geometry descriptors to characterize pocket(s) (c) Output: pocket(s) druggability prediction. In the first phase two query types can be submitted:

The main function of PockDrug-Server is to predict pocket druggability through the Druggability section. To do so, two types of query can be submitted: Pocket structure Protein structure A. Druggability prediction for protein pocket structure estimated by the user: PockDrug-Sever allows users to predict druggability probability for a protein pocket estimated using an estimation pocket approach/ software of his choice. In this case, the required input is the , which corresponds to a PDB format file listing the atom pocket coordinates. The corresponding protein PDB file is also required to compute pocket descriptors and its predicted druggability probability.

Download Pocket Estimation For Pc

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The protein structure corresponds to:a PDB code; a PDB protein file; or a file of PDB code list. For this type of query PockDrug-Server protocol is divided into two main steps:Step 1: pocket(s) estimation using one or both different pocket estimation methods proposed by our web server; Step 2: pocket druggability probability prediction. For each pocket, previously estimated in step 1, pocket druggability probability and standard deviation are provided by PockDrug model. Protein query can be an apo or a holo protein. In the case of a holo-protein the ligand can be included in the protein file or uploaded apart so an optional field for ligand information is additionally proposed. The user can also submit a single job for a set of apo or holo proteins in the form of a list of PDB codes. In this case the same previous protocol is applied so for each PDB code included in the list, pocket(s) is (are) estimated and its corresponding druggability probability is then predicted.

For these three types of protein structure information, prox and/or fpocket estimation methods can be choosen.

This method is based on ligand proximity information giving the user the possibility of choosing a threshold going from 4 to 12 (by step of 0.5 ) in order to extract the protein atoms localized within the chosen distance of the ligand. Indeed, this threshold choice was recently shown to have a strong influence on the pocket descriptors (2) and it seems pertinent to give the user the opportunity to choose it. Two commonly used distance thresholds are recommended: 4 as used by Krasowski et al. (3), to enable the extraction of a well-defined pocket limited to short ligand interactions (as hydrogen bonds or ionic interactions) and 5.5 , to enable the identification of all significant contact points and a more complete environment of the binding site. This method is suitable for holo-proteins and threshold of 4 is chosen by default.

not guided by the ligand information, is an automated geometry-based method based on the decomposition of a 3D protein into Voronoi polyhedrals. It extracts all the pockets from the apo- or holo- protein surface using spheres of varying diameters. Its advantages include calculation speed and satisfactory performance in terms of overlaying known binding sites with the predicted sites (4). This method is used by default since it is suitable for both apo- and holo- proteins.

Only in single entry mode (submission of PDB ID or PDB structure), and when prox estimation method is checked, the field allowing user to submit ligand information is visible. In multiple entry mode, where a PDB ID code list is provided, and this optional ligand field is no more accessible.

3 types of ligand information input are possible:

After this first stage of pocket estimation, in the background some geometrical and physico-chemical pocket descriptors and protein descriptors involved in PockDrug model are computed, in the aim to predict pocket druggability. In the following part, the output details will be displayed.

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Workflow presenting the different steps of PockDrug-Server protocol. It is divided into four main parts, from top to bottom: input information (in clear blue), pocket estimation methods (in pink), PockDrug druggability prediction (in green) and the output display (in blue).

Example of PockDrug-Server output using acetylcholinesterase protein structure (1EVE). (A) The results display of pocket estimated using prox4 estimation method sorted by descending order of druggability probability; (B) the result display of pocket estimated using fpocket estimation method sorted by descending order of druggability probability.

Interestingly, in addition to pocket binding E20, out of 16 estimated pockets using fpocket estimation method PockDrug-Server predicted five other pockets as druggable. These five pockets correspond to high druggability probabilities (more than 0.63) and could be of interest in the case of AChE, which is an important target to treat alzheimer disease and other central nervous system diseases. So combining different pocket estimation methods, especially those that do not need any prior ligand position information, allows the identification of new potential druggable pockets.

On the other hand, different methods of pocket estimation that have been used to construct PockDrug model enable us to provide, to our knowledge, the unique free web server proposing a druggability prediction that overcomes the limits and inaccuracies of pocket estimations and is efficient with different pocket estimation methods.

The fact that PockDrug-Server accepts as input any structure in the PDB format, the user can estimate and predict pockets druggability not only for X-Ray or nuclear magnetic resonance structures but also for models obtained by homology (apo form) or by docking (holo form).

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