This server is designed for the prediction of heme binding residues (HEMEs). It will generate an email message containing numeric score for each residue in the input protein sequence that quantifies putative propensity to form a HEMEs. Putative annotations (a given residue is predicted either as a HEME or non-HEME) displayed on the result page are based on the judgement 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 Paste your protein sequence with standard FASTA format:

STEP TWO Select a prediction model:

STEP THREE Set a judgement threshold:

STEP FOUR Provide you email address:


HELP

HEMEsPred accepts only one protein sequence for a sigle prediction. You should input the protein sequence in standard FASTA format. 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 judgement threshold that input in STEP THREE will be used to generate putative annotations. Residues gaining numeric score higher the threshold will be regard as putative HEMEs.

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

Training datasets: HEC-44, HEM-191, HEME-260.

Testing datasets: HEM-22, HEM-18.


Citation

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

Jian Zhang, Haiting Chai, Bo Gao, Guifu Yang and Zhiqiang Ma, 2016, HEMEsPred: Structure-based Ligand-specific Heme Binding Residues Prediction by Using Fast-adaptive Ensemble Learning Scheme, IEEE-ACM Transactions on Computational Biology and Bioinformatics, DOI: 10.1109/TCBB.2016.2615010, PMID: 27775533 link