X-ray Scattering Studies of Protein Structural Dynamics

Meisburger, Steve P.; Thomas, William G.; Watkins, Maxwell B.; Ando, Nozomi

doi:10.1021/acs.chemrev.6b00790

Cited by 94 publications

(121 citation statements)

References 325 publications

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“…First characterized using simple ionic crystals in early studies of X-ray diffraction (Lonsdale, 1942), DS has a rich history (Welberry & Weber, 2016) and is a well established technique in smallmolecule crystallography (Welberry, 2004). DS studies in macromolecular crystallography began more recently (Phillips et al, 1980) and now the potential for obtaining information about protein motions is fueling the growing interest in DS (Meisburger et al, 2017).As noted in a previous IUCrJ commentary ( Keen, 2016), accurate modeling of smallmolecule DS requires not only information about the variations of individual molecules or unit cells, but also information about the correlated variations in a more extended environment. Similarly, macromolecular DS studies indicate the importance of modeling interactions across unit-cell boundaries in normal-modes models (Riccardi et al, 2010), as well as the molecular dynamics models (Wall, 2018) of macromolecular diffuse scattering that are shown in this issue.…”

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Interactions that know no boundaries

Wall

2018

Int Union Crystallogr J

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Deviations from an ideal crystal lead to diffuse scattering (DS) intensity, both between and beneath the Bragg peaks in diffraction patterns (Guinier, 1963). First characterized using simple ionic crystals in early studies of X-ray diffraction (Lonsdale, 1942), DS has a rich history (Welberry & Weber, 2016) and is a well established technique in smallmolecule crystallography (Welberry, 2004). DS studies in macromolecular crystallography began more recently (Phillips et al., 1980) and now the potential for obtaining information about protein motions is fueling the growing interest in DS (Meisburger et al., 2017).As noted in a previous IUCrJ commentary ( Keen, 2016), accurate modeling of smallmolecule DS requires not only information about the variations of individual molecules or unit cells, but also information about the correlated variations in a more extended environment. Similarly, macromolecular DS studies indicate the importance of modeling interactions across unit-cell boundaries in normal-modes models (Riccardi et al., 2010), as well as the molecular dynamics models (Wall, 2018) of macromolecular diffuse scattering that are shown in this issue. The liquid-like motions (LLM) model (Caspar et al., 1988), in which the correlated variations are modeled as if the crystal were a soft homogeneous material, explains the overall DS pattern in several protein crystals (Caspar et al., 1988;Clarage et al., 1992;Van Benschoten et al., 2016;Wall, Clarage & Phillips, 1997;Wall, Ealick & Gruner, 1997). However, the consequences of including intermolecular interactions for the accuracy of the LLM model were not clear until now.In this issue, Peck and co-workers (Peck et al., 2018) investigate the importance of intermolecular interactions by assessing the accuracy of two alternative versions of an LLM model (Caspar et al., 1988) (Fig. 1). In the original version of the model, the correlations extend across molecular boundaries (Fig. 1a). In this case, the diffuse intensity is derived from the squared crystal transform, which is sharply peaked. In a modified version of the model, correlations terminate at the molecular boundary (Fig. 1b). In this case, the diffuse intensity is derived from the squared molecular transform of the asymmetric unit (in the cases considered, a single molecule), which is continuous in reciprocal space. In both cases, the transform is blurred; shorter correlation lengths correspond to a larger scale blurring of the transform. Both models are optimized to maximize the agreement with the data, enabling a well controlled comparison.To be consistent with the state of the art (Meisburger et al., 2017), three-dimensional diffuse datasets were used for the comparison, obtained from crystalline cyclophilin A (CypA) (PDB entry 4yuo; Fraser, 2015), WrpA (PDB entry 5f51; Herrou & Crosson, 2015) and alkaline phosphatase (PDB entry 5c66; Peck et al., 2017). The CypA data were the subject of a prior DS study (Van Benschoten et al., 2016) and the others were newly analyzed for this study, providing valuable addi...

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Interactions that know no boundaries

Wall

2018

Int Union Crystallogr J

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“…56 A second approach, which has not been done, would take advantage of a phenomenon known as diffuse scattering. 57 Diffuse scattering is the weak, continuous X-ray scattering that results from imperfections in a crystal. The lack of perfect constructive and destructive interference arising from these imperfections results in some scattering around and beneath Bragg peaks.…”

Section: An Intertwined Historymentioning

confidence: 99%

“…A potentially powerful application of diffuse scattering is in giving physical meaning to the B-factors obtained by crystallography. 57 Of the various types of disorder that we may see in the diffuse scattering pattern, the most exciting is the correlated motions that underlie protein allostery. 66 Solution-based small- and wide-angle X-ray scattering (SAXS/WAXS) provides yet another method for observing protein dynamics.…”

Section: An Intertwined Historymentioning

confidence: 99%

“…66 Solution-based small- and wide-angle X-ray scattering (SAXS/WAXS) provides yet another method for observing protein dynamics. 57 While not a high-resolution technique, it is unique in that it probes macromolecules in solution, meaning that experimental conditions can be easily varied. Thus, SAXS/WAXS can provide a means to explore the full extent of the conformational landscape as a function of any number of solution conditions.…”

Section: An Intertwined Historymentioning

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X-rays in the Cryo-Electron Microscopy Era: Structural Biology’s Dynamic Future

Shoemaker

Ando

2018

Biochemistry

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Over the past several years, single-particle cryo-electron microscopy (cryo-EM) has emerged as a leading method for elucidating macromolecular structures at near-atomic resolution, rivaling even the established technique of X-ray crystallography. Cryo-EM is now able to probe proteins as small as hemoglobin (64 kDa), while avoiding the crystallization bottleneck entirely. The remarkable success of cryo-EM has called into question the continuing relevance of X-ray methods, particularly crystallography. To say that the future of structural biology is either cryo-EM or crystallography, however, would be misguided. Crystallography remains better suited to yield precise atomic coordinates of macromolecules under a few hundred kDa in size, while the ability to probe larger, potentially more disordered assemblies is a distinct advantage of cryo-EM. Likewise, crystallography is better equipped to provide high-resolution dynamic information as a function of time, temperature, pressure, and other perturbations, whereas cryo-EM offers increasing insight into conformational and energy landscapes, particularly as algorithms to deconvolute conformational heterogeneity become more advanced. Ultimately, the future of both techniques depends on how their individual strengths are utilized to tackle questions on the frontiers of structural biology. Structure determination is just one piece of a much larger puzzle: a central challenge of modern structural biology is to relate structural information to biological function. In this perspective, we share insight from several leaders in the field and examine the unique and complementary ways in which X-ray methods and cryo-EM can shape the future of structural biology.

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Docking, Scoring, and Virtual Screening in Drug Discovery

Spyrakis

Sarkar

Kellogg

2021

Burger's Medicinal Chemistry and Drug Discovery

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Since its introduction about four decades ago, docking and scoring are now the very heart of structure‐based drug design. The past 10–20 years have seen a plethora of docking and scoring tools successfully integrated into drug discovery pipelines. Interestingly, while artificial intelligence is now receiving significant attention in the computational modeling arena, docking and scoring have long utilized these techniques. This comprehensive summary highlights some of the most significant achievements of docking and scoring, reviews the current status, provides descriptions of many of the tools available, comments on some of the outstanding challenges facing the paradigm, and offers perspectives and advice on best practices for users. While significant development is still needed in docking of flexible molecules and accurate Gibb's free energy predictions, docking and scoring are very useful when handled by experienced practitioners, but less so if treated as a “black box.” Lastly, we present a hypothetical case so beginners may appreciate the nuances of setting up a docking study. Focus in docking is now shifting toward parallel applications, i.e. protein–protein, protein–oligosaccharide, protein–DNA, or protein–RNA docking and polypharmacology. In summary, this article is intended to elucidate the nuances of the subject, while providing guidelines for practical implementation of effective workflows in drug discovery and structural biology.

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X-ray Scattering Studies of Protein Structural Dynamics

Cited by 94 publications

References 325 publications

Interactions that know no boundaries

Interactions that know no boundaries

X-rays in the Cryo-Electron Microscopy Era: Structural Biology’s Dynamic Future

Docking, Scoring, and Virtual Screening in Drug Discovery

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