Frag1D is a web server for predicting one-dimensional (1D) structure of proteins from amino acid sequences. It predicts three types of 1D structures, i.e. three-state secondary structure (H: Helix, S: Sheet, R: Random Coil), eight-state Shape Strings (R, S, U, V, A, K, G and T, see the definition in Figure 1) and three-state Shape Strings (R, S, U and V to S; A and K to H; G and T to T).

Background: The precise prediction of one-dimensional (1D) protein structure as represented by the protein secondary structure and 1D string of discrete state of dihedral angles (i.e. Shape Strings) is a prerequisite for the successful prediction of three-dimensional (3D) structure as well as protein-protein interaction. We have developed a novel 1D structure prediction method, called Frag1D, based on a straightforward fragment matching algorithm and demonstrated its success in the prediction of three sets of 1D structural alphabets, i.e. the classical three-state secondary structure, three- and eight-state Shape Strings. By exploiting the vast protein sequence and protein structure data available, we have brought secondary-structure prediction closer to the expected theoretical limit. When tested by a leave-one-out cross validation on a non-redundant set of PDB cutting at 30% sequence identity containing 5860 protein chains, the overall per-residue accuracy for secondary-structure prediction, i.e. Q3 is 82.9%. The overall per-residue accuracy for three- and eight-state Shape Strings are 85.1 and 71.5%, respectively. We have also benchmarked our program with the latest version of PSIPRED for secondary structure prediction and our program predicted 0.3% better in Q3 when tested on 2241 chains with the same training set. For Shape Strings, we compared our method with a recently published method with the same dataset and definition as used by that method. Our program predicted at 2.2% better in accuracy for three-state Shape Strings. By quantitatively investigating the effect of data base size on 1D structure prediction we show that the accuracy increases by 1% with every doubling of the database size.

Input to the server is one or several amino acid sequences (up to ) in FASTA format. The user can either paste one or more sequences in the text-area provided, or, alternatively, upload a file in ASCII format.

 Num        residue index in the sequence.
 AA         one-letter amino acid code.
 Sec        Predicted three state secondary structure,
            (H, S and R).
 ConfSec    Confidence of the predicted secondary structure.
 S8         Predicted 8 state Shape String,
            (R, S, U, V, A, K, G and T).
 ConfS8     Confidence of the predicted 8 state Shape String.
 S3         Predicted 3 state Shape String
            (R, S, U, V -> S; A, K -> H; G, T -> T). 
 ConfS3     Confidence of the predicted 3 state Shape String.