Protein-carbohydrate and protein-protein interactions: using models to better understand and predict specific molecular recognition

Any molecular recognition event results in a change in the free energy of the system. The extent of this change is related to the association constant, such that the more negative the free energy change is, the tighter the interaction between receptor and ligand. Protein-carbohydrate interactions play a critical role in signal transduction, innate immunity, and metabolism. Modeling these interactions is somewhat complicated by the inherent flexibility of carbohydrates as well as their relatively large number of functional groups. An empirical scoring function for docking carbohydrates to proteins, specifically tailored to predict both the correct binding orientation and free energy of binding of the carbohydrate-ligand/protein-receptor complex, will be presented. This new scoring function can predict free energies of binding to within 1.1 kcal/mol residual standard error, a definite improvement over existing scoring functions that result in standard errors well over 2 kcal/mol. Application of automated docking methodology to determine carbohydrate recognition specificity of the C-type lectin, human surfactant protein D, will also be presented. In the second part of the thesis, the role of pi-stacking interactions (e.g. between Tyr side chains) in stabilizing protein folds will be discussed. A 17-residue peptide derived from the naturally occurring anti-microbial peptide tachyplesin I was investigated using NMR spectroscopy. NOE cross-peaks were observed, confirming the existence of this interaction in solution. In the final part of the thesis, a quantitative NMR investigation into the self-association behavior of the regulatory domains of several Tec family member kinases will be presented. Of particular interest, self-association within Bruton\u27s tyrosine kinase (Btk) regulatory domains occurs through the formation of an asymmetric homodimer. Together this work demonstrates the importance of rigorous biophysical characterization of biomolecular recognition events and the interdependence of computational modeling and experimentation

Classification of RNA structure change by “gazing” at experimental data

Motivation: Mutations (or Single Nucleotide Variants) in folded RiboNucleic Acid structures that cause local or global conformational change are riboSNitches. Predicting riboSNitches is challenging, as it requires making two, albeit related, structure predictions. The data most often used to experimentally validate riboSNitch predictions is Selective 2′ Hydroxyl Acylation by Primer Extension, or SHAPE. Experimentally establishing a riboSNitch requires the quantitative comparison of two SHAPE traces: wild-type (WT) and mutant. Historically, SHAPE data was collected on electropherograms and change in structure was evaluated by ‘gel gazing.’ SHAPE data is now routinely collected with next generation sequencing and/or capillary sequencers. We aim to establish a classifier capable of simulating human ‘gazing’ by identifying features of the SHAPE profile that human experts agree ‘looks’ like a riboSNitch

Transcending the prediction paradigm: novel applications of SHAPE to RNA function and evolution

Selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) provides information on RNA structure at single-nucleotide resolution. It is most often used in conjunction with RNA secondary structure prediction algorithms as a probabilistic or thermodynamic restraint. With the recent advent of ultra-high-throughput approaches for collecting SHAPE data, the applications of this technology are extending beyond structure prediction. In this review, we discuss recent applications of SHAPE data in the transcriptomic context and how this new experimental paradigm is changing our understanding of these experiments and RNA folding in general. SHAPE experiments probe both the secondary and tertiary structure of an RNA, suggesting that model-free approaches for within and comparative RNA structure analysis can provide significant structural insight without the need for a full structural model. New methods incorporating SHAPE at different nucleotide resolutions are required to parse these transcriptomic data sets to transcend secondary structure modeling with global structural metrics. These 'multiscale' approaches provide deeper insights into RNA global structure, evolution, and function in the cell. For further resources related to this article, please visit the WIREs website

On the Characterization of Microporous Carbon Blacks by Various Techniques

It is shown that the combination of different techniques, based on the adsorption of vapors and on calorimetry, can lead to the unambiguous characterization of carbonaceous materials. The case of a microporous carbon black, with pores in the range 0.35–1.2 nm, is used as an example

Local RNA Structural Changes Induced by Crystallization are Revealed by SHAPE

We present a simple approach to locate sites that undergo conformational changes upon crystallization by comparative structural mapping of the same RNA in three different environments. As a proof of principle, we probed the readily crystallized P4–P6ΔC209 domain from the Tetrahymena thermophila group I intron in a native solution, in a solution mimicking the crystallization drop, and in crystals. We chose the selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry, which monitors the flexibility and the conformation of each nucleotide. First, SHAPE successfully revealed the structural changes that occur during the crystallization process. Specifically, 64% of the nucleotides implicated in packing contacts and present in the portion of the molecule analyzed were identified. Second, reactivity differences for some of these nucleotides were already observed in the crystallization solution, suggesting that the crystallization buffer locked down a particular structure that was favorable to crystal formation. Third, the probing of a known structure extends our understanding of the structural basis for the SHAPE reaction by suggesting that reactivity is enhanced by a C2′-endo sugar pucker. Furthermore, by identifying local conformational changes of the RNA that take place during crystallization, SHAPE could be combined with the in vitro selection of stable mutants to rationalize the design of RNA candidates for crystallization

Ligand Specificity Modulated by Prolyl Imide Bond Cis/Trans Isomerization in the Itk SH2 Domain: A Quantitative NMR Study

The Src homology 2 (SH2) domain of interleukin-2 tyrosine kinase (Itk) binds two separate ligands:  a phosphotyrosine-containing peptide and the Itk Src homology 3 (SH3) domain. Binding specificity for these ligands is regulated via cis/trans isomerization of the Asn 286−Pro 287 imide bond in the Itk SH2 domain. In this study, we develop a novel method of analyzing chemical shift perturbation and cross-peak volumes to measure the affinities of both ligands for each SH2 conformer. We find that the cis imide bond containing SH2 conformer exhibits a 3.5-fold higher affinity for the Itk SH3 domain compared with binding of the trans conformer to the same ligand, while the trans conformer binds phosphopeptide with a 4-fold greater affinity than the cis-containing SH2 conformer. In addition to furthering the understanding of this system, the method presented here will be of general application in quantitatively determining the specificities of conformationally heterogeneous systems that use a molecular switch to regulate binding between multiple distinct ligands

Arg343 in Human Surfactant Protein D Governs Discrimination between Glucose and N-Acetylglucosamine Ligands

Surfactant protein D (SP-D), one of the members of the collectin family of C-type lectins, is an important component of pulmonary innate immunity. SP-D binds carbohydrates in a calcium-dependent manner, but the mechanisms governing its ligand recognition specificity are not well understood. SP-D binds glucose (Glc) stronger than N-acetylglucosamine (GlcNAc). Structural superimposition of hSP-D with mannose- binding protein C (MBP-C) complexed with GlcNAc reveals steric clashes between the ligand and the side chain of Arg343 in hSP-D. To test whether Arg343contributes to Glc \u3e GlcNAc recognition specificity, we constructed a computational model of Arg343→Val (R343V) mutant hSP-D based on homology with MBP-C. Automated docking of α-Me-Glc and α-Me-GlcNAc into wild-type hSP-D and the R343V mutant of hSP-D suggests that Arg343 is critical in determining ligand-binding specificity by sterically prohibiting one binding orientation. To empirically test the docking predictions, an R343V mutant recombinant hSP-D was constructed. Inhibition analysis shows that the R343V mutant binds both Glc and GlcNAc with higher affinity than the wild-type protein and that the R343V mutant binds Glc and GlcNAc equally well. These data demonstrate that Arg343 is critical for hSP-D recognition specificity and plays a key role in defining ligand specificity differences between MBP and SP-D. Additionally, our results suggest that the number of binding orientations contributes to monosaccharide binding affinity