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Structures of the Streptococcus sanguinis SrpA Binding Region with Human Sialoglycans Suggest Features of the Physiological Ligand.

ABSTRACT: Streptococcus sanguinis is a leading cause of bacterial infective endocarditis, a life-threatening infection of heart valves. S. sanguinis binds to human platelets with high avidity, and this adherence is likely to enhance virulence. Previous studies suggest that a serine-rich repeat adhesin termed SrpA mediates the binding of S. sanguinis to human platelets via its interaction with sialoglycans on the receptor GPIb?. However, in vitro binding assays with SrpA and defined sialoglycans failed to identify specific high-affinity ligands. To improve our understanding of the interaction between SrpA and human platelets, we determined cocrystal structures of the SrpA sialoglycan binding region (SrpABR) with five low-affinity ligands: three sialylated trisaccharides (sialyl-T antigen, 3'-sialyllactose, and 3'-sialyl-N-acetyllactosamine), a sialylated tetrasaccharide (sialyl-LewisX), and a sialyl galactose disaccharide component common to these sialoglyans. We then combined structural analysis with mutagenesis to further determine whether our observed interactions between SrpABR and glycans are important for binding to platelets and to better map the binding site for the physiological receptor. We found that the sialoglycan binding site of SrpABR is significantly larger than the sialoglycans cocrystallized in this study, which suggests that binding of SrpA to platelets either is multivalent or occurs via a larger, disialylated glycan.

SUBMITTER: Loukachevitch LV

PROVIDER: S-EPMC5388602 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Structures of the Streptococcus sanguinis SrpA Binding Region with Human Sialoglycans Suggest Features of the Physiological Ligand.

Loukachevitch Lioudmila V LV Bensing Barbara A BA Yu Hai H Zeng Jie J Chen Xi X Sullam Paul M PM Iverson T M TM

Biochemistry 20161011 42

Streptococcus sanguinis is a leading cause of bacterial infective endocarditis, a life-threatening infection of heart valves. S. sanguinis binds to human platelets with high avidity, and this adherence is likely to enhance virulence. Previous studies suggest that a serine-rich repeat adhesin termed SrpA mediates the binding of S. sanguinis to human platelets via its interaction with sialoglycans on the receptor GPIbα. However, in vitro binding assays with SrpA and defined sialoglycans failed to ...[more]

PMID: 27685666

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Project description:BACKGROUND: Protein-ligand interactions are key processes in triggering and controlling biological functions within cells. Prediction of protein binding regions on the protein surface assists in understanding the mechanisms and principles of molecular recognition. In silico geometrical shape analysis plays a primary step in analyzing the spatial characteristics of protein binding regions and facilitates applications of bioinformatics in drug discovery and design. Here, we describe the novel software, PLB-SAVE, which uses parallel processing technology and is ideally suited to extract the geometrical construct of solid angles from surface atoms. Representative clusters and corresponding anchors were identified from all surface elements and were assigned according to the ranking of their solid angles. In addition, cavity depth indicators were obtained by proportional transformation of solid angles and cavity volumes were calculated by scanning multiple directional vectors within each selected cavity. Both depth and volume characteristics were combined with various weighting coefficients to rank predicted potential binding regions. RESULTS: Two test datasets from LigASite, each containing 388 bound and unbound structures, were used to predict binding regions using PLB-SAVE and two well-known prediction systems, SiteHound and MetaPocket2.0 (MPK2). PLB-SAVE outperformed the other programs with accuracy rates of 94.3% for unbound proteins and 95.5% for bound proteins via a tenfold cross-validation process. Additionally, because the parallel processing architecture was designed to enhance the computational efficiency, we obtained an average of 160-fold increase in computational time. CONCLUSIONS: In silico binding region prediction is considered the initial stage in structure-based drug design. To improve the efficacy of biological experiments for drug development, we developed PLB-SAVE, which uses only geometrical features of proteins and achieves a good overall performance for protein-ligand binding region prediction. Based on the same approach and rationale, this method can also be applied to predict carbohydrate-antibody interactions for further design and development of carbohydrate-based vaccines. PLB-SAVE is available at http://save.cs.ntou.edu.tw.

Dataset Information

Structures of the Streptococcus sanguinis SrpA Binding Region with Human Sialoglycans Suggest Features of the Physiological Ligand.

Publications

Structures of the Streptococcus sanguinis SrpA Binding Region with Human Sialoglycans Suggest Features of the Physiological Ligand.

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