This server is designed for the prediction of DNA-binding Residues (DBRs). It will generate an email message containing numeric score for each residue of the query protein sequence(s) that quantifies putative propensity to form a DBR. Putative annotations (a given residue is predicted either as a DBR or non-DBR) displayed on the result page are based on the preset threshold input in this page. All comments, suggestions or requests regarding our work are welcome. For more information, please contact biocomputinglab@sina.com.

Please follow the four steps below to make a prediction

STEP ONE Provide you email address:

STEP TWO Paste your protein sequence with standard FASTA format:

  Click Here to Use Example Protein Sequence

STEP THREE Set a searching threshold:

STEP FOUR Set a judgement threshold:

HELP

DQPred-DBR accepts only one protein sequence for a sigle prediction. The protein sequence should be in standard FASTA format, which begins with a symbol ">". The format of the input protein sequence is as follows:

    Line 1: > PDB ID or UniProtKB ID or any other annotation(s)

    Line 2: protein sequence (1-letter amino acid encoding)

The searching threshold that input in STEP THREE will be used to mapping potentially-instructive samples in our sample pool. Due to the limitation of our searching rules, DQPred-DBR only accept a valid searching threshold ranging from 0.4 to 1. If you pay more attention on the potential DNA-bindning residues, we suggest a little low value for it. In another case, if you would like to obtain some DNA-binding residues with high accuracy, we suggest a little high value for it.

The judgement threshold that input in STEP FOUR will be used to generate putative annotations. Residues gaining numeric score higher the threshold will be regard as putative DBRs.

We will send a message reporting the detailed prediction result to the email address you input once the current prediction is finished. For more information in respect to its content, please make a try and see the result.

Materials

Sample pool: dataset used for DNA-binding residues Download

Citation

Upon the usage the users are requested to use the following citation:

Haiting Chai, Jian Zhang, Guifu Yang and Zhiqiang Ma, 2017, An evolution-based DNA-binding residues predictor by using dynamic query-driven learning scheme, Molecular BioSystems, DOI: 10.1039/C6MB00626D, PMID: 27730230 link

Acknowledgments

We acknowledge with thanks the following databases and software used as a part of this server:

RCSB PDB - RCSB Protein Data Bank

BLAST - Basic Local Alignment Search Tool

CD-HIT - Cluster Database at High Identity with Tolerance

LIBSVM - A Library for Support Vector Machines