Carbohydrate-binding protein identification by coupling structural similarity searching with binding affinity prediction

Abstract

Carbohydrate-binding proteins (CBPs) are potential biomarkers and drug targets. However, the interactions between carbohydrates and proteins are challenging to study experimentally and computationally because of their low binding affinity, high flexibility, and the lack of a linear sequence in carbohydrates as exists in RNA, DNA, and proteins. Here, we describe a structure-based function-prediction technique called SPOT-Struc that identifies carbohydrate-recognizing proteins and their binding amino acid residues by structural alignment program SPalign and binding affinity scoring according to a knowledge-based statistical potential based on the distance-scaled finite-ideal gas reference state (DFIRE). The leave-one-out cross-validation of the method on 113 carbohydrate-binding domains and 3442 noncarbohydrate binding proteins yields a Matthews correlation coefficient of 0.56 for SPalign alone and 0.63 for SPOT-Struc (SPalign + binding affinity scoring) for CBP prediction. SPOT-Struc is a technique with high positive predictive value (79% correct predictions in all positive CBP predictions) with a reasonable sensitivity (52% positive predictions in all CBPs). The sensitivity of the method was changed slightly when applied to 31 APO (unbound) structures found in the protein databank (14/31 for APO versus 15/31 for HOLO). The result of SPOT-Struc will not change significantly if highly homologous templates were used. SPOT-Struc predicted 19 out of 2076 structural genome targets as CBPs. In particular, one uncharacterized protein in Bacillus subtilis (1oq1A) was matched to galectin-9 from Mus musculus. Thus, SPOT-Struc is useful for uncovering novel carbohydrate-binding proteins. SPOT-Struc is available at http://sparks-lab.org.

SPOT‐Ligand: Fast and effective structure‐based virtual screening by binding homology search according to ligand and receptor similarity

“…In this article, we built our SPOT-Ligand method based on the successful function prediction methods for protein-DNA, [19,20] protein-RNA, [21,22] and protein-glycan [23] binding.…”

YesU from Bacillus subtilis preferentially binds fucosylated glycans

“…We had previously predicted, using SPOT-struc, YesU to be a carbohydrate binding protein 13 with specificity similar to the Man-binding protein VIP36 (pdbID: 2e6v) 17,18 . VIP36 exhibits a typical β-sandwich and jellyroll fold 17,18 that is a common structural characteristic of the ConA-like lectin/glucanse superfamily 15 .…”

“…In 2005, Structural Classification of Proteins–extended (SCOPe) classed YesU as a beta protein with a galectin-like fold, being a member of the concanavalin-A (ConA) like lectins/glucanses superfamily 15 possessing a β-sandwich structure comprising 12–14 strands organised as 2 sheets to form a jellyroll topology 16 . Our SPOT-Struc analysis specifically matched YesU to the integral membrane mammalian protein VIP36 (2e6v) 13 , a known leguminous type lectin with a β-sandwich and jellyroll fold 17,18 that recognizes high Man-type glycans 19 .…”

“…Highly aligned structures are followed by a binding affinity prediction to further remove potentially false positive CBPs. Using this method we predicted several structural genome targets as CBPs, one of which was YesU from Bacillus subtilis (RCSB Protein Data Bank code 1oq1) 13 .…”

Protein–RNA and protein–glycan recognitions in light of amino acid codes

“…Currently, we have a number of methods for the biochemical identification of the protein-glycan interactome for defined glycans and for the identification of the protein-glycan interactome for specific proteins [40]. The biochemical and structural properties of identified proteins are effectively processed into informative models for the prediction and mapping of GBPs [43][44][45][46]. The same approach as for protein-RNA recognition is applied for protein-glycan recognition.…”