Intelligent Computing Lab.
Bioinformatics in NCTU, Taiwan.
Go back to IC Lab

Scoring Card Inspired Protein Analysis System for identification, characterization and mutagenesis of carbohydate-binding proteins

Home | Download | Release 0.2, Last update: Apr 10 2015 

Motivation: High diversity of carbohydrates leads to a great variety of carbohydrate-binding proteins (CBPs), resulting in difficulties of deciphering structure and characteristics of CBPs and designing neolectins for recognizing functional glycocodes. This work proposes a scoring card inspired protein analysis system (SCIPAS) for identification, characterization, and mutagenesis of CBPs.

Results: The SCIPAS system mainly consists of a selection method for informative gene ontology terms, a protein function predictor based on a scoring card method (SCM), and a visualization method SCM-VISU for protein characterization. Retrospective and prospective datasets are established to design a CBP predictor SCMCBP and evaluate SCMCBP by identifying potentially putative CBPs. The propensity scores of amino acids and dipeptides to be CBPs are used to predict and characterize CBPs. Some characteristics were found such as 1) aromatic and polar residues play important roles in binding carbohydrates, and 2) left-hand helix tends to be a nucleation site. Four criteria based on the characteristics are proposed for mutagenesis of CBPs in designing neolectins.

The flowchart of system designs for predicting and characterizing carbohydate binding proteins (CBPs).

Scoring card of carbohydate binding protein propensity scores

Contact with:
Hui-Ling Huang, Shinn-Ying Ho

Related publications of SCM

Huang HL, Charoenkwan P, Kao TF, Lee HC, Chang FL, Huang WL, Ho SJ, Shu LS, Chen WL, Ho SY: Prediction and analysis of protein solubility using a novel scoring card method with dipeptide composition. Bmc Bioinformatics 2012, 13.

Charoenkwan P, Shoombuatong W, Lee HC, Chaijaruwanich J, Huang HL, Ho SY: SCMCRYS: Predicting Protein Crystallization Using an Ensemble Scoring Card Method with Estimating Propensity Scores of P-Collocated Amino Acid Pairs. Plos One 2013, 8(9).