Dataset Information

Patch Finder Plus (PFplus): a web server for extracting and displaying positive electrostatic patches on protein surfaces.

ABSTRACT: Positively charged electrostatic patches on protein surfaces are usually indicative of nucleic acid binding interfaces. Interestingly, many proteins which are not involved in nucleic acid binding possess large positive patches on their surface as well. In some cases, the positive patches on the protein are related to other functional properties of the protein family. PatchFinderPlus (PFplus) http://pfp.technion.ac.il is a web-based tool for extracting and displaying continuous electrostatic positive patches on protein surfaces. The input required for PFplus is either a four letter PDB code or a protein coordinate file in PDB format, provided by the user. PFplus computes the continuum electrostatics potential and extracts the largest positive patch for each protein chain in the PDB file. The server provides an output file in PDB format including a list of the patch residues. In addition, the largest positive patch is displayed on the server by a graphical viewer (Jmol), using a simple color coding.

SUBMITTER: Shazman S

PROVIDER: S-EPMC1933175 | biostudies-literature | 2007 Jul

REPOSITORIES: biostudies-literature

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Patch Finder Plus (PFplus): a web server for extracting and displaying positive electrostatic patches on protein surfaces.

Shazman Shula S Celniker Gershon G Haber Omer O Glaser Fabian F Mandel-Gutfreund Yael Y

Nucleic acids research 20070530 Web Server issue

Positively charged electrostatic patches on protein surfaces are usually indicative of nucleic acid binding interfaces. Interestingly, many proteins which are not involved in nucleic acid binding possess large positive patches on their surface as well. In some cases, the positive patches on the protein are related to other functional properties of the protein family. PatchFinderPlus (PFplus) http://pfp.technion.ac.il is a web-based tool for extracting and displaying continuous electrostatic posi ...[more]

PMID: 17537808

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Project description:BackgroundSimple sequence repeats (SSRs) have become widely used as molecular markers in plant genetic studies due to their abundance, high allelic variation at each locus and simplicity to analyze using conventional PCR amplification. To study plants with unknown genome sequence, SSR markers from Expressed Sequence Tags (ESTs), which can be obtained from the plant mRNA (converted to cDNA), must be utilized. With the advent of high-throughput sequencing technology, huge EST sequence data have been generated and are now accessible from many public databases. However, SSR marker identification from a large in-house or public EST collection requires a computational pipeline that makes use of several standard bioinformatic tools to design high quality EST-SSR primers. Some of these computational tools are not users friendly and must be tightly integrated with reference genomic databases.ResultsA web-based bioinformatic pipeline, called EST Analysis Pipeline Plus (ESAP Plus), was constructed for assisting researchers to develop SSR markers from a large EST collection. ESAP Plus incorporates several bioinformatic scripts and some useful standard software tools necessary for the four main procedures of EST-SSR marker development, namely 1) pre-processing, 2) clustering and assembly, 3) SSR mining and 4) SSR primer design. The proposed pipeline also provides two alternative steps for reducing EST redundancy and identifying SSR loci. Using public sugarcane ESTs, ESAP Plus automatically executed the aforementioned computational pipeline via a simple web user interface, which was implemented using standard PHP, HTML, CSS and Java scripts. With ESAP Plus, users can upload raw EST data and choose various filtering options and parameters to analyze each of the four main procedures through this web interface. All input EST data and their predicted SSR results will be stored in the ESAP Plus MySQL database. Users will be notified via e-mail when the automatic process is completed and they can download all the results through the web interface.ConclusionsESAP Plus is a comprehensive and convenient web-based bioinformatic tool for SSR marker development. ESAP Plus offers all necessary EST-SSR development processes with various adjustable options that users can easily use to identify SSR markers from a large EST collection. With familiar web interface, users can upload the raw EST using the data submission page and visualize/download the corresponding EST-SSR information from within ESAP Plus. ESAP Plus can handle considerably large EST datasets. This EST-SSR discovery tool can be accessed directly from: http://gbp.kku.ac.th/esap_plus/ .

Project description:BACKGROUND: Machine learning-based methods have been proven to be powerful in developing new fold recognition tools. In our previous work [Zhang, Kochhar and Grigorov (2005) Protein Science, 14: 431-444], a machine learning-based method called DescFold was established by using Support Vector Machines (SVMs) to combine the following four descriptors: a profile-sequence-alignment-based descriptor using Psi-blast e-values and bit scores, a sequence-profile-alignment-based descriptor using Rps-blast e-values and bit scores, a descriptor based on secondary structure element alignment (SSEA), and a descriptor based on the occurrence of PROSITE functional motifs. In this work, we focus on the improvement of DescFold by incorporating more powerful descriptors and setting up a user-friendly web server. RESULTS: In seeking more powerful descriptors, the profile-profile alignment score generated from the COMPASS algorithm was first considered as a new descriptor (i.e., PPA). When considering a profile-profile alignment between two proteins in the context of fold recognition, one protein is regarded as a template (i.e., its 3D structure is known). Instead of a sequence profile derived from a Psi-blast search, a structure-seeded profile for the template protein was generated by searching its structural neighbors with the assistance of the TM-align structural alignment algorithm. Moreover, the COMPASS algorithm was used again to derive a profile-structural-profile-alignment-based descriptor (i.e., PSPA). We trained and tested the new DescFold in a total of 1,835 highly diverse proteins extracted from the SCOP 1.73 version. When the PPA and PSPA descriptors were introduced, the new DescFold boosts the performance of fold recognition substantially. Using the SCOP_1.73_40% dataset as the fold library, the DescFold web server based on the trained SVM models was further constructed. To provide a large-scale test for the new DescFold, a stringent test set of 1,866 proteins were selected from the SCOP 1.75 version. At a less than 5% false positive rate control, the new DescFold is able to correctly recognize structural homologs at the fold level for nearly 46% test proteins. Additionally, we also benchmarked the DescFold method against several well-established fold recognition algorithms through the LiveBench targets and Lindahl dataset. CONCLUSIONS: The new DescFold method was intensively benchmarked to have very competitive performance compared with some well-established fold recognition methods, suggesting that it can serve as a useful tool to assist in template-based protein structure prediction. The DescFold server is freely accessible at http://202.112.170.199/DescFold/index.html.

Dataset Information

Patch Finder Plus (PFplus): a web server for extracting and displaying positive electrostatic patches on protein surfaces.

Publications

Patch Finder Plus (PFplus): a web server for extracting and displaying positive electrostatic patches on protein surfaces.

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