abstract: Spider dragline silk is an outstanding biopolymer with a strength that exceeds steel by weight and a toughness greater than high-performance fibers like Kevlar. For this reason, structural and dynamic studies on the spider silk are of great importance for developing future biomaterials. The spider dragline silk comprises two silk proteins, Major ampullate Spidroin 1 and 2 (MaSp1 and 2), which are synthesized and stored in the major ampullate (MA) gland of spiders. The initial state of the silk proteins within Black Widow MA glands was probed with solution-state NMR spectroscopy. The conformation dependent chemical shifts information indicates that the silk proteins are unstructured and in random coil conformation. 15N relaxation parameters, T1, T2 and 15N-{1H} steady-state NOE were measured to probe the backbone dynamics for MA silk proteins. These measurements indicate fast sub-nanosecond timescale backbone dynamics for the repetitive core of spider MA proteins indicating that the silk proteins are unfolded, highly flexible random coils in the MA gland. The translational diffusion coefficients of the spider silk proteins within the MA gland were measured using 1H diffusion NMR at 1H sites from different amino acids. A phenomenon was observed where the measured diffusion coefficients decrease with an increase in the diffusion delay used. The mean displacement along the external magnetic field was found to be 0.35 μm and independent of the diffusion delay. The results indicate that the diffusion of silk protein was restricted due to intermolecular cross-linking with only segmental diffusion observable. To understand how a spider converts the unfolded protein spinning dope into a highly structured and oriented in the super fiber,the effect of acidification on spider silk assembly was investigated on native spidroins from the major ampullate (MA) gland fluid excised from Latrodectus hesperus (Black Widow) spiders. The in vitro spider silk assembly kinetics were monitored as a function of pH with a 13C solid-state Magic Angle Spinning (MAS) NMR approach. The results confirm the importance of acidic pH in the spider silk self-assembly process with observation of a sigmoidal nucleation-elongation kinetic profile. The rates of nucleation and elongation and the percentage of β-sheet structure in the grown fibers depend on pH. The secondary structure of the major ampullate silk from Peucetia viridians (Green Lynx) spiders was characterized by X-ray diffraction (XRD) and solid-state NMR spectroscopy. From XRD measurement, β-sheet nano-crystallites were observed that are highly oriented along the fiber axis with an orientational order of 0.980. Compare to the crystalline region, the amorphous region was found to be partially oriented with an orientational order of 0.887. Further, two dimensional 13C-13C through-space and through-bond solid-state NMR experiments provide structural analysis for the repetitive amino acid motifs in the silk proteins. The nano-crystallites are mainly alanine-rich β-sheet structures. The total percentage of crystalline region is determined to be 40.0±1.2 %. 18±1 % of alanine, 60±2 % glycine and 54±2 % serine are determined to be incorporated into helical conformations while 82±1 % of alanine, 40±3 % glycine and 46±2 % serine are in the β-sheet conformation. / Dissertation/Thesis / Doctoral Dissertation Chemistry 2015

abstract: This thesis explores a wide array of topics related to the protein folding problem, ranging from the folding mechanism, ab initio structure prediction and protein design, to the mechanism of protein functional evolution, using multi-scale approaches. To investigate the role of native topology on folding mechanism, the native topology is dissected into non-local and local contacts. The number of non-local contacts and non-local contact orders are both negatively correlated with folding rates, suggesting that the non-local contacts dominate the barrier-crossing process. However, local contact orders show positive correlation with folding rates, indicating the role of a diffusive search in the denatured basin. Additionally, the folding rate distribution of E. coli and Yeast proteomes are predicted from native topology. The distribution is fitted well by a diffusion-drift population model and also directly compared with experimentally measured half life. The results indicate that proteome folding kinetics is limited by protein half life. The crucial role of local contacts in protein folding is further explored by the simulations of WW domains using Zipping and Assembly Method. The correct formation of N-terminal β-turn turns out important for the folding of WW domains. A classification model based on contact probabilities of five critical local contacts is constructed to predict the foldability of WW domains with 81% accuracy. By introducing mutations to stabilize those critical local contacts, a new protein design approach is developed to re-design the unfoldable WW domains and make them foldable. After folding, proteins exhibit inherent conformational dynamics to be functional. Using molecular dynamics simulations in conjunction with Perturbation Response Scanning, it is demonstrated that the divergence of functions can occur through the modification of conformational dynamics within existing fold for β-lactmases and GFP-like proteins: i) the modern TEM-1 lactamase shows a comparatively rigid active-site region, likely reflecting adaptation for efficient degradation of a specific substrate, while the resurrected ancient lactamases indicate enhanced active-site flexibility, which likely allows for the binding and subsequent degradation of different antibiotic molecules; ii) the chromophore and attached peptides of photocoversion-competent GFP-like protein exhibits higher flexibility than the photocoversion-incompetent one, consistent with the evolution of photocoversion capacity. / Dissertation/Thesis / Ph.D. Physics 2014

The work in this thesis focuses on the study of three main aspects of proteins, viz, Protein structure, stability, and dynamics. Chapter 1 is a general introduction to the topics studied in this thesis. Chapter 2 deals with the first aspect, i.e., protein structure in which we describe an approach to use saturation mutagenesis phenotypes to guide protein structure prediction. Chapters 3 and 4 discuss how to increase protein stability using surface electrostatics, and Chapter 5 details a method to predict whether a proline substitution in a given protein would be stabilizing or destabilizing. Hence, Chapters 3-5 can be associated with the second aspect, i.e., protein stability. The third aspect, namely protein dynamics, is dealt with in Chapters 6 and 7 which study conformational dynamics of adenylate kinase. Protein structure prediction is a difficult problem with two major bottlenecks, namely, generation of accurate models and the selection of the most appropriate models from a large pool of decoys. In Chapter 2, the problem of model discrimination is addressed using mutant phenotype information derived from saturation mutagenesis library. A library of ~1500 single-site mutants of the E. coli toxin CcdB (Controller of Cell Division or Death B) has been previously constructed in our lab. The pooled library was characterized in terms of individual mutant phenotypes at various expression levels which were derived from the relative populations of mutants at each expression level. The relative populations of mutants were estimated using deep sequencing. Mutational tolerances were derived from the phenotypic data and were used to define an empirical parameter which correlated with a structural parameter, residue depth. We further studied how this new parameter can be used for model discrimination. Increasing protein stability in a rational way is a challenging problem and has been addressed by various approaches. One of the most commonly used approaches is optimization of protein core residues. Recently, optimization of protein surface electrostatics has been shown to be a useful approach for increasing stability of proteins. In Chapter 3, from analyses of a dataset of ~1750 non-homologues proteins, we show that proteins having a pI away from physiological pH, possess a significant fraction of unfavorably placed charged amino acids on their surface. One way to increase protein stability in such cases might be to alter these surface charges. This hypothesis was validated experimentally by making charge reversal mutations at putative unfavorable positions on the surface of maltose binding protein, MBP. The observed stabilization can potentially be increased by combining multiple individually stabilizing mutations. Different combinations of such mutations were made and tested in Chapter 4 to decide which mutants can be combined to achieve net stabilization. Ideas were tested through systematic experimentation which involved generation of two-site, three-site, and four-site mutations. A maximum increase in melting temperature (Tm) of 3-4 °C over wild-type protein was achieved upon combination of individually stabilizing mutants. Proline (Pro) has two special stereo-chemical properties when it is a part of a polypeptide chain. First the φ value of Pro has a very constrained distribution and second, Pro lacks an amide hydrogen. Due to these properties, introduction of Pro might perturb stability/activity of the protein. In Chapter 5 we describe a procedure to accurately predict the effects of Pro introduction on protein stability. Pro scanning mutagenesis was carried out on the model protein CcdB and the in vivo activity of the individual mutants was also examined. A decision tree was constructed, using the special stereo-chemical properties of Pro to maximize correlation of predicted phenotype with the in vivo activity. Binary classification as perturbing or non-perturbing of every Pro substitution was possible using the decision tree. The performance of the decision tree was assessed on various test systems, and the average accuracy was found to be ~75%. The role of conformational dynamics in enzyme catalysis has been explored in great detail in the literature. In Chapter 6, with the help of very long (350 ns), fully atomistic, explicit solvent molecular dynamics simulations, we studied conformational dynamics of adenylate kinase. We found the existence of a relatively stable state which lies intermediate between the open and closed conformations of the enzyme. The finding was further confirmed by computing a two dimensional configurational free energy surface when motions along each of the two movable domains (LID and NMP) are considered as reaction coordinates. We also discussed possible roles of the intermediate state during enzyme catalysis. The role of water in stabilization of intermediate states was also discussed. In Chapter 7, we studied dynamical coupling between LID and NMP domains of adenylate kinase during domain opening. Our observation suggests that the LID domain should start opening prior to the NMP domain. On the domain opening trajectory, the free energy surface of LID domain was found to be very rugged. We discuss a possible role of water in the ruggedness of the domain motions. The Appendix contains 3 supplementary parts of the thesis. Appendix I is a mutant dataset obtained from 454 sequencing analysis. It includes the normalized number of reads per mutation at each expression level along with mutational sensitivity score. Appendix II is parameters used for one of the electrostatic calculations. Appendix III contains a list of PDB ids used for database analysis in surface electrostatics work discussed in Chapter 3.

Traditional computational protein design (CPD) calculations model sequence perturbations and evaluate their stabilities using a single fixed protein backbone template in an approach referred to as single‐state design (SSD). However, certain design objectives require the explicit consideration of multiple conformational states. Cases where a multistate framework may be advantageous over the single‐state approach include the computer aided discovery of new enzyme substrates, the prediction of protein stabilities, and the design of protein dynamics. These design objectives can be tackled using multistate design (MSD). However, it is often the case that a design objective requires the consideration of a protein state having no available structure information. For such circumstances the multistate framework cannot be applied. In this thesis I present the development of two template and ensemble preparation methodologies and their application to three projects. The purpose of which is to demonstrate the necessary ensemble modeling strategies to overcome limitations in available structure information. Particular emphasis is placed on the ability to recapitulate experimental data to guide modelling of the design space. Specifically, the use of MSD allowed for the accurate prediction of a methyltransferase recognition motif and new substrates, the prediction of mutant sequence stabilities with quantitative accuracy, and the design of dynamics into the rigid Gβ1 scaffold producing a set of dynamic variants whose tryptophan residue exchanges between two conformations on the millisecond timescale. Implementation of both the ensemble, coordinate perturbation followed by energy minimization (PertMin), and template, rotamer optimization followed by energy minimization (ROM), generation protocols developed here allow for exploration and manipulation of the structure space enabling the success of these applications.

<div><p>The cellular protein pool exists in a state of dynamic equilibrium, such that a balance between protein synthesis and degradation is maintained to sustain protein homeostasis. This equilibrium is essential for normal cellular functions and hence alteration in protein dynamics has several pathological implications in developing and adult tissues. Recent progress in mass spectrometry (MS) and metabolic labeling techniques has advanced our understanding of the mechanisms of protein regulation in cultured cells and less complicated multicellular organisms. However, methods for the analysis of the dynamics of intra- and extra-cellular proteins in embryonic and adult tissues remain lacking.</p><p>To address this gap, we developed a metabolic labeling technique that enables labeling the nascent murine proteome via injection of non-canonical amino acids (ncAAs), which can be selectively enriched by “clickable” tags for identification and quantification. Using this technique, we developed a MS-based method for the selective identification and quantification of the intra- and extra-cellular newly synthesized proteins in developing murine tissues. We then applied this technique to study the dynamic regulation of extracellular matrix (ECM) proteins during embryonic and adolescent musculoskeletal development. We show that the applied technique enables resolving differences in the nascent proteome of different developmental time points with high temporal resolution. The technique can also reveal protein dynamic information that cannot be captured by the traditional proteomic techniques. Additionally, we identified key ECM components that play roles in musculoskeletal development to provide insights into the mechanisms of musculoskeletal tissue regeneration.</p><p>To fully characterize our labeling technique, we developed a mathematical model to describe the biodistribution kinetics of azidohomoalanine (Aha), the most widely used ncAA, in murine tissues. The model enabled measuring the relative rates of protein synthesis and turnover in different tissues and predicting the effect of different dosing regimens of Aha on the degree of protein labeling. Finally, we analyzed the plasma metabolome of Aha-injected mice to investigate the impact of Aha incorporation on normal physiology. The analysis revealed that Aha administration into mice does not significantly perturb metabolic functions. Taken together, the findings presented in this dissertation demonstrate the utility of the ncAA labeling technique in mapping protein dynamics in mammalian tissues. This will ultimately have a significant impact on our understanding of protein regulation in health and disease. </p></div><br>

No description available.

No description available.

The liquid-liquid phase separation (LLPS) of biomolecules is a phenomenon which received a lot of attention in the last years because it is not only related to theformation of membraneless organelles but also to neurodegenerative diseases. Lysozyme is a globular protein that undergoes LLPS in a buffer salt system andfor that it is well investigated with several techniques like microscopy, dynamic lightscattering (DLS) or small-angle X-ray scattering. In this work we investigate the effect of temperature, solvent and sample con-centration on the diffusion coefficient, the hydrodynamic radius and the viscosity oflysozyme using a DLS setup. Furthermore, the influence of these parameters on thecluster formation is addressed. Finally, we investigate the question if the LLPS oflysozyme in a buffer environment effects the formation of dynamic clusters.

Most existing studies of receptor signaling are qualitative, which can lead scientists to misinterpret or overlook key information about the extent and timing of key events. To overcome these shortcomings, we have applied quantitative approaches to characterize receptor activation and signaling events. Most signaling studies focus on events occurring at a particular level in the system (e.g., on the membrane, at the level of phosphorylation of intracellular signaling molecules, or at the level of transcription). Instead, we are interested in taking a longitudinal view of signaling by achieving a quantitative understanding of a single signaling pathway from initial stimulation of the receptor by its growth factor (GF) ligand, through to gene expression, and functional cellular responses. As a model system for our studies, we used the growth factor receptor tyrosine kinase, REarranged during Transfection (RET), which requires a ligand and a glycosylphosphatidylinositol-anchored co-receptor for activation. RET mediates the response of cells to members of the glial cell-line derived neurotrophic factor (GDNF) family of neurotrophins, which are important in the development and maintenance of a subset of neuronal cells as well as in other cell types and tissues. We have characterized the molecular mechanisms of RET activation and signaling by pursuing the following four aims: 1) We developed a sensitive and robust luciferase reporter gene assay for RET signaling. 2) We characterized the dynamic relationship between receptor activation and downstream signaling events, including gene transcription and translation of three target genes. 3) We used the reporter gene assay, and other detection approaches, to test and quantify crosstalk between RET and other GF receptors. 4) We developed a FRET reporter system to enable monitoring of the assembly of the activated RET receptor complex on cells, as a means to distinguish between ligand-induced oligomerization and pre-associated oligomer mechanisms. Through these four aims, we have established new methods to quantitatively elucidate mechanisms of GF receptor activation, new insights into how signals are propagated from the receptor to the nucleus and into a functional response, and have established crosstalk between RET and other GF receptor pathways.

Indiana University-Purdue University Indianapolis (IUPUI) / Misregulation of protein signaling pathways is the basis for many human diseases, and thus 95% of Food and Drug Administration approved drugs target proteins. Proteins are dynamic entities which can undergo transitions to reach different conformational states. The conformational state of a protein, or its three-dimensional shape, is intricately linked to functions, such as association with endogenous or exogenous binding partners, or catalysis. Thus, it is of interest to the pharmacological community to understand the mechanisms of protein conformational state transitions in order to better target and control protein functions. In two case studies, I show the importance of understanding protein dynamics in protein function and drug design. In the case of human immunodeficiency virus-1 (HIV-1) protease, a tremendous “open-and-closed” conformational transition is revealed by Molecular Dynamics Simulations (MDS). Through observing the dramatic difference in effectiveness of two Darunavir inhibitor derivatives differentiated by a single atom at locking the protease in the closed conformation, we discovered the residues and mechanism that lead to the protease’s conformational transition. This mechanism also explained the significant difference in the binding conformation and binding affinity of these two inhibitors. This study provides insight on how to improve the potency and anti-viral capacity of these compounds. In the second case study, MDS enabled us to observe the conformational transitions of a family of seven isoforms known as the 14-3-3 proteins. Many vital cellular processes involve all or select 14-3-3 isoforms, making this family very difficult to target. Through MDS, I discovered different conformational samplings among these 14-3-3 isoforms which were then validated by SAXS. Subsequently, a FRET-based ligand binding assay was developed which can screen for preferential 14-3-3 isoform binding of endogenous ligands, giving hope that using conformations unique to a 14-3-3 isoform of interest can provide a method for selective drug design. / 2022-03-09