One of the key challenges in protein science is determining three dimensional structure from amino acid sequence. Although experimental methods for determining protein structures are providing high resolution structures, they cannot keep the pace at which amino acid sequences are resolved on the scale of entire genomes. Various computational tools have been developed that predict different levels of protein structural hierarchy.
List of important tools for the prediction of protein structure is given below.
| Server | Description |
|---|
| APSSP2 | This server predicts secondary structure of protein's from their amino acid sequence with high accuracy. It uses the multiple alignment, neural network and MBR techniques. This server participates in number of world wide competition like CASP, CAFASP and EVA (Raghava 2002; CASP5 A-31)
|
| PROCLASS | Prediction of structural class of proteins such as Alpha or Beta or Alpha+Beta or Alpha/Beta (Raghava 1999; J. Biosciences 24:176)
|
| PSA | This server allow user to analysis of protein sequence and present the analysis in Graphical and Textual format. This allows property plots of 36 parameter (like Hydrophobicity Plot, Polarity, Charge) of single sequence and multiple sequence alignment (Raghava 2001; Biotech Software and Internet Report, 2:255)
|
| RPFOLD | It allows to predict top 5
similar fold in PDB (Protein DataBank) for a given protein sequence (query).
|
| BTeval | Benchmarking of Beta Turn
prediction methods on-line via Internet (Kaur and Raghava 2002;
Bioinformatics 18:1508-14). The user can see the performance of their
method or existing methods (Kaur and Raghava 2003; Journal of
Bioinformatics and Computational Biology 1:495-504)
|
| BetatTPred2 | Prediction of Beta Turns in
Proteins using Neural Network and multiple alignment techniques. This is
highly accurate method for beta turn prediction (Kaur and Raghava 2003;
Protein Science 12:627).
|
| GammaPred | Prediction of Gamma-turns in
Proteins using Multiple Alignment and Secondary Structure Information (Kaur
and Raghava 2003; Protein Science; 12:923).
|
| AlphaPred | Prediction of Alpha-turns in
Proteins using Multiple Alignment and Secondary Structure Information (Kaur
& Raghava 2004; Proteins 55:83-90).
|
| BetaTPred | A server for predicting Beta
Turns in proteins using existing statistical methods. This allows consensus
prediction from various methods (Kaur and Raghava 2002; Bioinformatics 18:498).
|
| CHpredict | The CHpredict server predict
two types of interactions: C-H...O and C-H...PI interactions. For C-H...O
interaction, the server predicts the residues whose backbone Calpha atoms are
involved in interaction with backbone oxygen atoms and for C-H...PI
interactions, it predicts the residues whose backbone Calpha atoms are
involved in interaction with PI ring system of side chain aromatic moieties.
|
| AR_NHPred | A web server for predicting the
aromatic backbone NH interaction in a given amino acid sequence where the pi
ring of aromatic residues interact with the backbone NH groups. The method is
based on the neural network training on PSI-BLAST generated position specific
matrices and PSIPRED predicted secondary structure (Kaur and Raghava 2004; Febs Lett. 564:47-57)
|
| TBBpred | It predicts the whether a
protein is outer membrane betat-barrel protein or not. It also predicts
transmembrane Beta barrel regions in a given protein sequence. (Natt et al. 2004; Proteins 56:11-8).
|
| Betaturns | This server predicts the beta
turns and their types in a protein from its amino acid sequence (Kaur and
Raghava 2004; Bioinformatics 20:2751-8) .
|
| PEPstr | The Pepstr server predicts the
tertiary structure of small peptides with sequence length varying between 7
to 25 residues. The prediction strategy is based on the realization that
?-turn is an important and consistent feature of small peptides in addition
to regular structures.
|
| BhairPred | Prediction of beta hairpins in
proteins using ANN and SVM techniques. In this method secondary structure and
multiple sequence alignment are used
to predict the beta hairpins (Kumar et al. 2005; Nucleic Acids Res.
33:W154-9)
|
| SARpred | Prediction of real value of
surface accessibility instead of buried or exposed residues in proteins from
amino acid sequence (Garg et al. 2005; Proteins,
|
| OXbench | A
bench-mark for evaluation of protein multiple sequence alignment accuracy (Raghava
et al. 2003; BMC Bioinformatics 4-47).
|
