Complete Configuration Space Analysis for Structure Determination of Symmetric Homo-oligomers by NMR

Symmetric homo-oligomers (protein complexes with similar subunits arranged symmetrically) play pivotal roles in complex biological processes such as ion transport and cellular regulation. Structure determination of these complexes is necessary in order to gain valuable insights into their mechanisms. Nuclear Magnetic Resonance (NMR) spectroscopy is an experimental technique used for structural studies of such complexes. The data available for structure determination of symmetric homo-oligomers by NMR is often sparse and ambiguous in nature, raising concerns about existing heuristic approaches for structure determination. We have developed an approach that is complete in that it identifies all consistent conformations, data-driven in that it separately evaluates the consistency of structures to data and biophysical constraints and efficient in that it avoids explicit consideration of each of the possible structures separately. By being complete, we ensure that native conformations are not missed. By being data-driven, we are able to separately quantify the information content in the data alone versus data and biophysical modeling. We take a configuration space (degree-of-freedom) approach that provides a compact representation of the conformation space and enables us to efficiently explore the space of possible conformations. This thesis demonstrates that the configuration space-based method is robust to sparsity and ambiguity in the data and enables complete, data-driven and efficient structure determination of symmetric homo-oligomers

LIPIcs, Volume 274, ESA 2023, Complete Volume

LIPIcs, Volume 274, ESA 2023, Complete Volum

Matching non-uniformity for program optimizations on heterogeneous many-core systems

As computing enters an era of heterogeneity and massive parallelism, it exhibits a distinct feature: the deepening non-uniform relations among the computing elements in both hardware and software. Besides traditional non-uniform memory accesses, much deeper non-uniformity shows in a processor, runtime, and application, exemplified by the asymmetric cache sharing, memory coalescing, and thread divergences on multicore and many-core processors. Being oblivious to the non-uniformity, current applications fail to tap into the full potential of modern computing devices.;My research presents a systematic exploration into the emerging property. It examines the existence of such a property in modern computing, its influence on computing efficiency, and the challenges for establishing a non-uniformity--aware paradigm. I propose several techniques to translate the property into efficiency, including data reorganization to eliminate non-coalesced accesses, asynchronous data transformations for locality enhancement and a controllable scheduling for exploiting non-uniformity among thread blocks. The experiments show much promise of these techniques in maximizing computing throughput, especially for programs with complex data access patterns

Mass & secondary structure propensity of amino acids explain their mutability and evolutionary replacements

Why is an amino acid replacement in a protein accepted during evolution? The answer given by bioinformatics relies on the frequency of change of each amino acid by another one and the propensity of each to remain unchanged. We propose that these replacement rules are recoverable from the secondary structural trends of amino acids. A distance measure between high-resolution Ramachandran distributions reveals that structurally similar residues coincide with those found in substitution matrices such as BLOSUM: Asn Asp, Phe Tyr, Lys Arg, Gln Glu, Ile Val, Met → Leu; with Ala, Cys, His, Gly, Ser, Pro, and Thr, as structurally idiosyncratic residues. We also found a high average correlation (\overline{R} R = 0.85) between thirty amino acid mutability scales and the mutational inertia (I X ), which measures the energetic cost weighted by the number of observations at the most probable amino acid conformation. These results indicate that amino acid substitutions follow two optimally-efficient principles: (a) amino acids interchangeability privileges their secondary structural similarity, and (b) the amino acid mutability depends directly on its biosynthetic energy cost, and inversely with its frequency. These two principles are the underlying rules governing the observed amino acid substitutions. © 2017 The Author(s)

Geometric Algorithms for Protein Structure Determination Using Measurements From Nuclear Magnetic Resonance Spectroscopy

<p>In an environment such as a cell, the three-dimensional structure of a protein entirely determines its function. Hence, to understand the mechanics of biochemical processes necessary to sustain life, it is crucial to study the structures of proteins at atomic detail. When life is threatened by viral and bacterial pathogens, structural characterization of the proteins at play yields insights about possible treatments and therapeutics. Measurements from nuclear magnetic resonance spectroscopy (NMR) reveal information about the structures of proteins, but building accurate atomic-resolution models from such measurements is an arduous task. The ambiguity and uncertainty of these measurements, and the challenges of obtaining a sufficient number of measurements to uniquely describe a structure, contribute to the difficulty of protein structure determination by NMR.</p><p>The current widely-used computational methods using NMR measurements for structure determination primarily rely on various incarnations of stochastic optimization. These techniques have been used to determine protein structures of excellent quality, but in the long term, the reliability of these techniques is dubious (and in cases, demonstrably inadequate), especially as we attempt to solve increasingly difficult structures. Stochastic optimization, due to its random nature, may not always report the best solution. Other superior solutions may lie concealed in the landscape of the objective function and remain undiscovered. We therefore seek computational methods for structure determination that are imbued with guarantees about solution quality. In this dissertation, we present methods for protein structure determination by NMR that are able to guarantee structural solutions quantitatively agree with experimental measurements. Although the trade-off for guaranteeing completeness of algorithms for structure determination is often an exponential running time, for some methods, we remarkably obtained polynomial running times in addition to guarantees of completeness.</p>Dissertatio

Evaluating experimental and theoretical measures of protein conformational dynamics

Molecular biologists have traditionally interpreted the B-factor data of a protein crystal structure as a reflection of the protein's conformational flexibility. Crystallographers, in contrast, are wary of assigning too much significance to B-factors since they can also be attributed to processes unrelated to conformational dynamics such as experimental imprecision; crystal imperfections; or rigid body motion. In this study, the usefulness of both isotropic and anisotropic B-factors as measures of conformational dynamics were evaluated using high resolution structures. Alpha-carbon B-factor values were analysed in relation to structural properties generally accepted to be correlates of conformational variability. The influence of secondary structure, amino acid type, surface exposure, distance to the centre of mass and packing density were investigated. The results support the argument that B-factors measure conformational variability by demonstrating that atoms with the highest B-factors are typically located in regions expected to have a high degree of conformational freedom. Nevertheless, the results also highlight some of the limitations of crystallographic data. Despite using high quality crystal structures, only very general qualitative trends between B-factors values and the properties investigated could be established. Thus, B-factors appear to be influenced, to a significant degree, by the numerous sources of error in a crystallographic experiment. By considering proteins with multiple published crystal structures, the existence of consensus B-factor profiles were identified. These consensus profiles were hypothesised to represent the dynamics within the crystal with a high degree of accuracy since much of the variation between individual experiments would be eliminated. However, when compared against measurements derived from molecular dynamic simulations, these consensus profiles only weakly correlated with the predictions of the computer models. Therefore, although there is some evidence to suggest that B-factors reflect conformational variability, B-factors cannot be assumed to be reliable descriptors of the internal dynamics of a protein within a crystal

Directed evolution and structural analysis of an OB-fold domain towards a specifc binding reagent

Interactions between proteins are a central concept in biology, and understanding and manipulation of these interactions is key to advancing biological science. Research into antibodies as customised binding molecules provided the foundation for development of the field of protein “scaffolds” for molecular recognition, where functional residues are mounted on to a stable protein platform. Consequently, the immunoglobulin domain has been describes as “nature’s paradigm” for a scaffold, and has been widely researched to make engineered antibodies better tools for specific applications. However, limitations in their use have lead to a number of non-immunoglobulin domains to be investigated as customisable scaffolds, to replace or complement antibodies. To be considered a scaffold, a protein domain must show an evolutionarily conserved hydrophobic core in diverse functional contexts. The study presented here investigated the oligosaccharide/oligonucleotide-binding (OB) fold as scaffold, which is a 5-standed β-barrel seen in diverse organisms with no sequence conservation. The term “Obody” was coined to describe engineered OB-folds. This thesis examined a previously engineered Obody with affinity for lysozyme (KD = 40 μM) in complex with its ligand by x-ray crystallography (resolution 2.75 Å) which revealed the atomic details of binding. Affinity maturation for lysozyme was undertaken by phage display directed evolution. Gene libraries were constructed by combinatorial PCR incorporating site-specific randomised codons identified by examination of the structure in complex with lysozyme, or by random generation of point mutations by error-prone PCR. Overall a 100-fold improvement in affinity was achieved (KD = 600 nM). To investigate the structural basis of the affinity maturation, two further Obody-lysozyme complexes were solved by x-ray crystallography, one at a KD of 5 μM (resolution 1.96 Å), one at 600 nM (resolution 1.86 Å). Analysis of the structures revealed changes in individual residue arrangements, as well as rigid-body changes in the relative orientation of the Obody and lysozyme molecules in complex. Directed evolution of Obodies as protein binding reagents remains a challenge, but this study demonstrates their potential. The structures presented here will contribute invaluable insights for the future design of improved Obodies

Development of crystallographic methods for phasing highly modulated macromolecular structures

[eng] Pathologies that result in highly modulated intensities in macromolecular crystal structures pose a challenge for structure solution. To address this issue two studies have been performed: a theoretical study of one of these pathologies, translational non- crystallographic symmetry (tNCS), and a practical study of paradigms of highly modulated macromolecular structures, coiled-coils. tNCS is a structural situation in which multiple, independent copies of a molecular assembly are found in similar orientations in the crystallographic asymmetric unit. Structure solution is problematic because the intensity modulations caused by tNCS cause the intensity distribution to differ from a Wilson distribution. If the tNCS is properly detected and characterized, expected intensity factors for each reflection that model the modulations observed in the data can be refined against a likelihood function to account for the statistical effects of tNCS. In this study, a curated database of 80482 protein structures from the PDB was analysed to investigate how tNCS manifests in the Patterson function. These studies informed the algorithm for detection of tNCS, which includes a method for detecting the tNCS order in any commensurate modulation. In the context of automated structure solution pipelines, the algorithm generates a ranked list of possible tNCS associations in the asymmetric unit, which can be explored to efficiently maximize the probability of structure solution. Coiled-coils are ubiquitous protein folding motifs present in a wide range of proteins that consist of two or more α-helices wrapped around each other to form a supercoil. Despite the apparent simplicity of their architecture, solution by molecular replacement is challenging due to the helical irregularities found in these domains, tendency to form fibers, large dimensions in their typically anisometric asymmetric units, low-resolution and anisotropic diffraction. In addition, the internal symmetry of the helices and their alignment in preferential directions gives rise to systematic overlap of Patterson vectors, a Patterson map that indicates tNCS is present, and intensity modulations similar to those in true tNCS. In this study, we have explored fragment phasing on a pool of 150 coiled-coils with ARCIMBOLDO_LITE, an ab initio phasing approach that combines fragment location with Phaser and density modification and autotracing with SHELXE. The results have been used to identify limits and bottlenecks in coiled-coil phasing that have been addressed in a specific mode for solving coiled-coils, allowing the solution of 95% of the test set and four previously unknown structures, and extending the resolution limit from 2.5 Å to 3.0 Å