CSIR-Informatics Portal

This server allow to predict the secondary structure of protein's from their amino acid sequence. This is an advanced version of our PSSP server, which participated in CASP3 and in CASP4. PSSP was also part of CAFASP2.

The Ar_NHPred server predicts 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.

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)

The aim of BetaTPred2 server is to predict ß turns in proteins from multiple alignment by using neural network from the given amino acid sequence. For ß turn prediction, it uses the position specific score matrices generated by PSI-BLAST and secondary structure predicted by PSIPRED.

The aim of Betaturns server is to predict different types of turns such as Types I, II, IV, VIII and non-specific in a given amino acid sequence. The method is based on neural network. It uses two feed-forward back-propagation neural networks with a single hidden layer, where the first sequence-to-structure network is trained on PSI-BLAST generated position specific matrices

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)

The CHpredict server predict two types of interactions: C-H...O and C-H...π interactions. For C-H...O interaction, the server predicts the residues whose backbone Cα atoms are involved in interaction with backbone oxygen atoms and for C-H...π interactions, it predicts the residues whose backbone Cα atoms are involved in interaction with π ring system of side chain aromatic moieties.

The GammaPred server predicts the gamma turn residues in the given protein sequence. The method is based on the neural network training on PSI-BLAST generated position specific matrices and PSIPRED predicted secondary structure.

OXBench includes data and software to evaluate the accuracy of protein multiple sequence alignments.

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 β-turn is an important and consistent feature of small peptides in addition to regular structures.

This server allow to predict the class of protein from its amino acid sequence. It predict weather protein belong to class Alpha or Beta or Alpha+Beta or Alpha/Beta. This method is based on a statistical method descibed in Raghava, G P S (1999) Procalss: A computer program for predicting the protein structural classes. J. Biosciences 24, 176.

ccPDB (Compilation and Creation of datasets from PDB) is designed to provide service to scientific community working in the field of function or structure annoation of proteins.

PSAweb is a web server, developed to analyze the amino acid sequence and multiple sequence alignment of proteins. This is a comprehensive on-line Internet tool that allows the rapid visualization of an analysis, by output in GIF format.

A fold recognition server for searching protein fold in PDB. It is based on seaquence similarity search and secondary structure alignment technique.

SARpred, a neural network based method predicts the real value of surface acessibility (SA) by using multiple sequence alignment. In this method, two feed forward, back-propagation networks are used.

Transmembrane Beta Barrel prediction server predicts the transmembrane Beta barrel regions in a given protein sequence. The server uses a forked strategy for predicting residues which are in transmembrane beta barrel regions.