add protons (hydrogens) to structure

A list of online servers or programs as I know which can add hydrogens on the structures (most likely determined by X-ray crystallography).

1. WHATIF server (http://swift.cmbi.ru.nl/servers/html/index.html)
   –> check “Hydrogen (bonds)” in the left frame
2. Molprobity server (http://molprobity.biochem.duke.edu/)
   –> after uploading a PDB file, you will see “add hydrogen” in the online interface.
3. HAAD: (a computer algorithm for constructing hydrogen atoms from protein heavy-atom structures)
4. PyMOL (Win/Linux/Mac)
5. SPDB (Swiss PDB Viewer)

In my own test, WHATIF is more friendly for other CNS/Xplor-NIH/Haddock-related works because WHATIF generates CNS/Xplor compatible PDB format.

Molprobity generates PDB with added hydrogens but the added hydrogens are ALL numbered as “0”. Thus I have to use other program to reset all atom numbers.

PyMOL adds hydrogens,too (object -> A -> hydrogens -> add) but the nomenclature of hydrogens in proteins seems weird (see below). The hydrogens are named as H01, H02, H03.. etc. I don’t think CNS/Xplor-NIH can take it for further calculation purposes.

[web server] RNA Frabase 2.0

My colleague asked me to know if I can generate/model 3D structure of a short, single chain RNA. I know there are some servers doing such task but I am not sure how reliable the de novo structures are.

Instead of de novo structure model, I found there is a nice website called “RNA Frabase 2.0” (http://rnafrabase.ibch.poznan.pl/) which provides easy-to-use interface.

For example, I put a short RNA sequence “UAUUC” to search the published RNA structures. I got a lot of hits:

The outputs provide very detail information include “secondary structure”, “chain”, “position of start and end in matched sequence”, “method of structure determination”, “source of RNA (class)”, and “resolution”.

From this search and quickly inspect the structure from the Jmol plugin, users can decide  and pick up which RNA structure fragment best fits to their purpose (e.g. linear, circular…).

[web server] protein structural analysis

PDBsum provides service that users can upload their calculated structures for analysis including ramachandran plot, sequence+secondary structural element, etc. The figure below is an example. For self-generated structures, users need to click the link “generate” to upload your PDB files. To know the structural information of published biomolecules at Protein Data Bank, just type the pdb access to get the details.

After a short waiting (to this example, i just waited 10 minutes to get analysis done), an email sent from PDBsum provide users to look the details of the submitted structure. I clicked link at the left down corner to see the information of sequence and location of secondary structures. Other analysis including topology, SAS search and rama plot are also available for self-uploaded structures.

Another web server called “POLYVIEW 2D” also provides similar service. Users can look at the structural information of published structures deposited at PDB or upload their own structures (in PDB format) to draw either single or ensemble views. Two snapshots are shown below.

NOTE. POLYVIEW-3D, another service provided by the same team is an useful web server to generate pictures of target biomolecules without opening the molecular viewers on your own computers. It is very convenient for me when I am away from lab and wanna to see some snapshots of proteins. Highly recommended.

Web Severs for prediction of disordered regions (DRs) in proteins

This list of web severs is obtained from the published paper “Evaluation of disorder predictions in CASP9” by Andriy Kryshtafovych.

List of web servers and the methods descriptions (copy from table III of Kryshtafovych’s paper). Please read the paper for details of methods and performance.

• PrDOS2 (http://prdos.hgc.jp/cgi-bin/top.cgi)
  SVM algorithm based on sequence profiles combined with a template-based predictor.
• DisoPred3C (http://bioinf.cs.ucl.ac.uk/disopred)
  SVM trained on high-resolution X-ray structures. Uses profiles from 15 positions around each residue as an input vector.
• MULTICOM-refine (http://casp.rnet.missouri.edu/predisorder.html)
  One-Dimensional Recursive Neural Network (1D-RNN). Predicts the disorder probability of each residue along a protein sequence taking as input the sequence profile, predicted secondary structure, and solvent accessibility.
• Zhou-Spine-D (http://http://sparks.informatics.iupui.edu/SPINE-D/)
  Two-layered Neural Network followed by a filter. The input features include residue-level and window-level information calculated from amino acid sequence, seven representative physical parameters, PSI-BLAST profile, predicted secondary structure and solvent accessibility torsion-angle fluctuation.
• Zhou-Spine-DM (http://http://sparks.informatics.iupui.edu/SPINE-DM/)
  Meta approach that employs a two-layer Neural Network with a filter. Combines input from six disorder predictors: VSL2, DISOPred2, DisPro1.0, IUPred and SPINE-D (above).
• CBRC_Poodle (http://mbs.cbrc.jp/poodle/poodle-i.html)
  SVM integrating three own SVM predictors: Poodle-S  and Poodle- L specialized in short and long disorder regions, respectively, and Poodle-W  targeting unfolded protein prediction.
• biomine_dr_pdb, biomine_dr_pdb_c (http://biomine-ws.ece.ualberta.ca/MFDp.html)
  Two meta + SVM approaches. Combine predictions from DISOPred2, DISOclust and IUPred, and additionally use predicted secondary structure, solvent accessibility, B-factors and backbone dihedral torsion angles in SVM learning.
• GSmetaDisorderMD, GSmetaserver (http://iimcb.genesilico.pl/metadisorder/)
  Two Genetic Algorithms combining predictions from GSmetaDisorder (consensus of 13 DR servers) and GSmetaDisorder3D (consensus of missing residues in multiple sequence alignments produced by fold recognition methods). The two methods use different weight optimization scores.
• OnD-CRF (http://babel.ucmp.umu.se/ond-crf/)
  Machine learning technique based on Conditional Random Fields. Uses only sequence and predicted secondary structure as inputs.
• Mason (http://www.cs.gmu.edu/~mlbio/svmprat)
  SVM method integrating flexible window-based profile kernels and predicted secondary structure.
• McGuffin (as DISOClust on all CASP9 3D server models) (http://www.reading.ac.uk/bioinf/DISOclust/)
  DISOClust server was tested in CASP9 as a server group (IntFOLD- DR) and a human-expert group (McGuffin). Both groups exploited the same approach based on conservation of ordered residues within multiple structures. The McGuffin group used consensus of all 3D server models submitted to CASP, while IntFOLD-DR – only of those available from the in-house nFOLD4 method.

[web] online predictions of natively unfolded regions in protein

Natively unfolded protein, or so called intrinsically disordered protein, natively disordered protein is a growing topic for protein chemist. Try to collect sever online servers doing sequence-based prediction of the natively unfolded regions in a protein.

• Tango: A computer algorithm for prediction of aggregating regions in unfolded polypeptide chains

  Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nat Biotechnol. 2004 Oct;22(10):1302-6. Epub 2004 Sep 12. Fernandez-Escamilla AM, Rousseau F, Schymkowitz J, Serrano L. [link]

• AGGRESCAN: a server for the prediction and evaluation of “hot spots” of aggregation in polypeptides.

  reference: AGGRESCAN: a server for the prediction and evaluation of “hot spots” of aggregation in polypeptides. BMC Bioinformatics. 2007 Feb 27;8:65. Conchillo-Solé O, de Groot NS, Avilés FX, Vendrell J, Daura X, Ventura S. [link]

• The Ucon server [predictionprotein.org]

  reference:

  Natively unstructured regions in proteins identified from contact predictions. Bioinformatics. 2007 Aug 20, Schlessinger A, Punta M, Rost B. [link]

• PreLink Prediction of Linker Regions in Protein Sequence

  reference:

  Prediction of unfolded segments in a protein sequence based on amino acid composition.

  Bioinformatics. 2005 May 1;21(9):1891-900. Epub 2005 Jan 18. Coeytaux K, Poupon A. [link]

More sites will be added soon….

My Linux has been running for 148 days

As the attached picture, it works very well! Yes! I love linux, I love SuSE, I love open source!

It is a Petium II 433 with 512 MB, 10 GB HD out of fashion PC, but didn't reduce the performace in the last 5 month. Great jobs!

 

PDBSum announces topology diagrams for protein domains

NOTE (Nov.4th, 2011): I have made a new post showing how to generat such topology figure using online service provided by PDBSum.

Please click this post “[web server] protein structural analysis” to read new post.

 

Like what you see above, it’s a protein topology diagram (sample: 1PJW.pdb). Starting on Feb Sixth, 2006, the PDBSum (http://www.ebi.ac.uk/thornton-srv/databases/pdbsum/)  announces the new service which provides the topology diagram of the coordinate file in Protein Data Bank (http://www.rcsb.org/pdb).

PDBsum intergrated many programs such as Procheck, WhatIF, Rasmol script and others. I really like the topology diagram generated by PDBSum, though I can’t find the source code from there. Hope they will release the source codes or compiled files for people who want to generate the topology diagrams of their fresh, before-submitting PDBs.