• First, it uses PSI-BLAST (Altschul et al., NAR, 1997) to search the target sequence against NCBI Non-Redundant sequence database to construct a profile. The profile is used to search a template library built from the proteins in Protein Data Bank (Berman et al., Nucleic Acids Res., 2000) to identify templates.



• Second, if some significant templates are identified (e-value <= 0.001), it generates a structure model for the target using Modeller (Sali and Blundell, JMB, 1993) based on the template structures. Multiple significant templates are combined to improve model quality if available. Then it uses a domain parsing tool PDP ((Alexandrov and Shindyalov, Bioinformatics, 2003) to parse the model into domains. If the parsed domains do not cover the whole target sequence, DOMAC will assign the uncovered regions to the adjacent domains.



• If no significant template is found, DOMAC will invoke the ab initio domain predictor DOMpro to predict domains. DOMpro (Cheng et al., Data Mining and Knowledge Discovery, 2006) uses neural networks in conjunction with sequence profile, predicted secondary structure, and relative solvent accessibility to predict domain boundary.

• Inputs to the web server include target name, sequence, and email address. It usually takes less than 15 minutes to process one query, depending on the server load and sequence length. Sequence must be entered as a plain sequence of amino acids. Maximum sequence length allowed is 1500.



• Domain prediction outputs include the user-defined target name, the protein sequence, the predicted domain number, the start and end positions of each domain, and the method (template-based or ab initio) used to make the prediction. For template-based prediction, it also reports the PDB codes of the templates used to make the prediction.

Dataset Download

• CAS7 sequences  and CASP7 domain definition
• Protein sequences of the benchmark2 of the Holland's dataset and Holland's domain definition