Exploring kinetics and mechanism of protein-sugar recognition by surface plasmon resonance

CSM-carbohydrate: protein-carbohydrate binding affinity prediction and docking scoring function

Protein-carbohydrate interactions are crucial for many cellular processes but can be challenging to biologically characterise. To improve our understanding and ability to model these molecular interactions, we used a carefully curated set of 370 protein-carbohydrate complexes with experimental structural and biophysical data in order to train and validate a new tool, cutoff scanning matrix (CSM)-carbohydrate, using machine learning algorithms to accurately predict their binding affinity and rank docking poses as a scoring function. Information on both protein and carbohydrate complementarity, in terms of shape and chemistry, was captured using graph-based structural signatures. Across both training and independent test sets, we achieved comparable Pearson's correlations of 0.72 under cross-validation [root mean square error (RMSE) of 1.58 Kcal/mol] and 0.67 on the independent test (RMSE of 1.72 Kcal/mol), providing confidence in the generalisability and robustness of the final model. Similar performance was obtained across mono-, di- and oligosaccharides, further highlighting the applicability of this approach to the study of larger complexes. We show CSM-carbohydrate significantly outperformed previous approaches and have implemented our method and make all data freely available through both a user-friendly web interface and application programming interface, to facilitate programmatic access at http://biosig.unimelb.edu.au/csm_carbohydrate/. We believe CSM-carbohydrate will be an invaluable tool for helping assess docking poses and the effects of mutations on protein-carbohydrate affinity, unravelling important aspects that drive binding recognition.

Carbohydrate-Protein Interactions: Advances and Challenges

A carbohydrate, also called saccharide in biochemistry, is a biomolecule consisting of carbon (C), hydrogen (H) and oxygen (O) atoms. For example, sugars are low molecular-weight carbohydrates, and starches are high molecular-weight carbohydrates. Carbohydrates are the most abundant organic substances in nature and essential constituents of all living things. Protein-carbohydrate interactions play important roles in many biological processes, such as cell growth, differentiation, and aggregation. They also have broad applications in pharmaceutical drug design. In this review, we will summarize the characteristic features of protein-carbohydrate interactions and review the computational methods for structure prediction, energy calculations, and kinetic studies of protein-carbohydrate complexes. Finally, we will discuss the challenges in this field.

Prediction of protein-carbohydrate complex binding affinity using structural features

Protein-carbohydrate interactions play a major role in several cellular and biological processes. Elucidating the factors influencing the binding affinity of protein-carbohydrate complexes and predicting their free energy of binding provide deep insights for understanding the recognition mechanism. In this work, we have collected the experimental binding affinity data for a set of 389 protein-carbohydrate complexes and derived several structure-based features such as contact potentials, interaction energy, number of binding residues and contacts between different types of atoms. Our analysis on the relationship between binding affinity and structural features revealed that the important factors depend on the type of the complex based on number of carbohydrate and protein chains. Specifically, binding site residues, accessible surface area, interactions between various atoms and energy contributions are important to understand the binding affinity. Further, we have developed multiple regression equations for predicting the binding affinity of protein-carbohydrate complexes belonging to six categories of protein-carbohydrate complexes. Our method showed an average correlation and mean absolute error of 0.731 and 1.149 kcal/mol, respectively, between experimental and predicted binding affinities on a jackknife test. We have developed a web server PCA-Pred, Protein-Carbohydrate Affinity Predictor, for predicting the binding affinity of protein-carbohydrate complexes. The web server is freely accessible at https://web.iitm.ac.in/bioinfo2/pcapred/. The web server is implemented using HTML and Python and supports recent versions of major browsers such as Chrome, Firefox, IE10 and Opera.

Measurement of monovalent and polyvalent carbohydrate-lectin binding by back-scattering interferometry

Carbohydrate-protein binding is important to many areas of biochemistry. Here, backscattering interferometry (BSI) has been shown to be a convenient and sensitive method for obtaining quantitative information about the strengths and selectivities of such interactions. The surfaces of glass microfluidic channels were covalently modified with extravidin, to which biotinylated lectins were subsequently attached by incubation and washing. The binding of unmodified carbohydrates to the resulting avidin-immobilized lectins was monitored by BSI. Dose-response curves that were generated within several minutes and were highly reproducible in multiple wash/measure cycles provided adsorption coefficients that showed mannose to bind to concanavalin A (conA) with 3.7 times greater affinity than glucose consistent with literature values. Galactose was observed to bind selectively and with similar affinity to the lectin BS-1. The avidities of polyvalent sugar-coated virus particles for immobilized conA were much higher than monovalent glycans, with increases of 60-200 fold per glycan when arrayed on the exterior surface of cowpea mosaic virus or bacteriophage Qbeta. Sugar-functionalized PAMAM dendrimers showed size-dependent adsorption, which was consistent with the expected density of lectins on the surface. The sensitivity of BSI matches or exceeds that of surface plasmon resonance and quartz crystal microbalance techniques, and is sensitive to the number of binding events, rather than changes in mass. The operational simplicity and generality of BSI, along with the near-native conditions under which the target binding proteins are immobilized, make BSI an attractive method for the quantitative characterization of the binding functions of lectins and other proteins.

Surface plasmon resonance study of protein-carbohydrate interactions using biotinylated sialosides

Lectins are carbohydrate binding proteins found in plants, animals, and microorganisms. They serve as important models for understanding protein-carbohydrate interactions at the molecular level. We report here the fabrication of a novel sensing interface of biotinylated sialosides to probe lectin-carbohydrate interactions using surface plasmon resonance spectroscopy (SPR). The attachment of carbohydrates to the surface using biotin-NeutrAvidin interactions and the implementation of an inert hydrophilic hexaethylene glycol spacer (HEG) between the biotin and the carbohydrate result in a well-defined interface, enabling desired orientational flexibility and enhanced access of binding partners. The specificity and sensitivity of lectin binding were characterized using Sambucus nigra agglutinin (SNA) and other lectins including Maackia amurensis lectin (MAL), concanavalin A (Con A), and wheat germ agglutinin (WGA). The results indicate that alpha2,6-linked sialosides exhibit high binding affinity to SNA, while alteration in sialyl linkage and terminal sialic acid structure compromises the affinity by a varied degree. Quantitative analysis yields an equilibrium dissociation constant (KD) of 777 +/- 93 nM for SNA binding to Neu5Ac alpha2,6-LHEB. Transient SPR kinetics confirms the K D value from the equilibrium binding studies. A linear relationship was obtained in the 10-100 microg/mL range with limit of detection of approximately 50 nM. Weak interactions with MAL, Con A, and WGA were also quantified. The control experiment with bovine serum albumin indicates that nonspecific interaction on this surface is insignificant over the concentration range studied. Multiple experiments can be performed on the same substrate using a glycine stripping buffer, which selectively regenerates the surface without damaging the sialoside or the biotin-NeutrAvidin interface. This surface design retains a high degree of native affinity for the carbohydrate motifs, allowing distinction of sialyl linkages and investigation pertaining to the effect of functional group on binding efficiency. It could be easily modified to identify and quantify binding patterns of any low-affinity biologically relevant systems, opening new avenues for probing carbohydrate-protein interactions in real time.

Evaluation of α-d-mannopyranoside glycolipid micelles–lectin interactions by surface plasmon resonance method

It is established that achieving higher binding affinities in carbohydrate-protein interactions requires multivalent presentations of the sugar ligands at the receptor binding site. Several inhibition, calorimetric, mass balance, and other studies have reiterated the beneficial effects of molecular level clustering of the sugar ligands for tight binding to the receptors. We have undertaken an effort to study the multivalent effects involving larger assemblies, represented by micelles, and their lectin interactions. The micelles were constituted with monomer bearing one- or two-sugar moieties at the monomolecular level and with varying the distances between the sugar moieties. Micellar aggregation studies and dynamic light scattering (DLS) studies afforded details of the aggregation numbers and the hydrodynamic diameters of various glycolipid (GL) micelles. The GL micelles were used as analytes of surface plasmon resonance (SPR) experiments on a lectin concanavalin A (Con A)-immobilized surface. SPR studies of the micelle-lectin interactions demonstrate that the ligand-receptor binding can be fit into the bivalent analyte model of interaction. Furthermore, micelles formed from two-sugar containing GLs are able to elicit favorable kinetic association rate constants in comparison to the micelles constituted with one-sugar containing GLs. The kinetic rate constants across the micelles and the effect of the sugar valencies in the GLs are discussed.

Survey of the year 2003 commercial optical biosensor literature

In the year 2003 there was a 17% increase in the number of publications citing work performed using optical biosensor technology compared with the previous year. We collated the 962 total papers for 2003, identified the geographical regions where the work was performed, highlighted the instrument types on which it was carried out, and segregated the papers by biological system. In this overview, we spotlight 13 papers that should be on everyone's 'must read' list for 2003 and provide examples of how to identify and interpret high-quality biosensor data. Although we still find that the literature is replete with poorly performed experiments, over-interpreted results and a general lack of understanding of data analysis, we are optimistic that these shortcomings will be addressed as biosensor technology continues to mature.

Kinetic and structural analysis of the increased affinity of enoyl-ACP (acyl-carrier protein) reductase for triclosan in the presence of NAD+

The binding of enoyl-ACP (acyl-carrier protein) reductase from Plasmodium falciparum (PfENR) with its substrates and inhibitors has been analysed by SPR (surface plasmon resonance). The binding of the substrate analogue crotonoyl-CoA and coenzyme NADH to PfENR was monitored in real time by observing changes in response units. The binding constants determined for crotonoyl-CoA and NADH were 1.6x10(4) M(-1) and 1.9x10(4) M(-1) respectively. Triclosan, which has recently been demonstrated as a potent antimalarial agent, bound to the enzyme with a binding constant of 1.08x10(5) M(-1). However, there was a 300-fold increase in the binding constant in the presence of NAD+. The increase in the binding constant was due to a 17 times increase in the association rate constant (k(1)) from 741 M(-1) x s(-1) to 1.3x10(4) M(-1) x s(-1) and a 16 times decrease in the dissociation rate constant (k(-1)) from 6.84x10(-3) s(-1) to 4.2x10(-4) s(-1). These values are in agreement with those determined by steady-state kinetic analysis of the inhibition reaction [Kapoor, Reddy, Krishnasastry, N. Surolia and A. Surolia (2004) Biochem. J. 381, 719-724]. In SPR experiments, the binding of NAD+ to PfENR was not detected. However, a binding constant of 6.5x10(4) M(-1) was obtained in the presence of triclosan. Further support for these observations was provided by the crystal structures of the binary and ternary complexes of PfENR. Thus the dramatic enhancement in the binding affinity of both triclosan and NAD+ in the ternary complex can be explained by increased van der Waals contacts in the ternary complex, facilitated by the movement of residues 318-324 of the substrate-binding loop and the nicotinamide ring of NAD+. Interestingly, the results of the present study also provide a rationale for the increased affinity of NAD+ for the enzyme in the ternary complex.