Navraj S. Pannu

Crystallography & NMR system: A new software suite for macromolecular structure determination.

A new software suite, called Crystallography & NMR System (CNS), has been developed for macromolecular structure determination by X-ray crystallography or solution nuclear magnetic resonance (NMR) spectroscopy. In contrast to existing structure-determination programs, the architecture of CNS is highly flexible, allowing for extension to other structure-determination methods, such as electron microscopy and solid-state NMR spectroscopy. CNS has a hierarchical structure: a high-level hypertext markup language (HTML) user interface, task-oriented user input files, module files, a symbolic structure-determination language (CNS language), and low-level source code. Each layer is accessible to the user. The novice user may just use the HTML interface, while the more advanced user may use any of the other layers. The source code will be distributed, thus source-code modification is possible. The CNS language is sufficiently powerful and flexible that many new algorithms can be easily implemented in the CNS language without changes to the source code. The CNS language allows the user to perform operations on data structures, such as structure factors, electron-density maps, and atomic properties. The power of the CNS language has been demonstrated by the implementation of a comprehensive set of crystallographic procedures for phasing, density modification and refinement. User-friendly task-oriented input files are available for nearly all aspects of macromolecular structure determination by X-ray crystallography and solution NMR.

Overview of the CCP4 suite and current developments

An overview of the CCP4 software suite for macromolecular crystallography is given.

REFMAC5 for the refinement of macromolecular crystal structures

The general principles behind the macromolecular crystal structure refinement program REFMAC5 are described.

Shiga-like toxins are neutralized by tailored multivalent carbohydrate ligands

The diseases caused by Shiga and cholera toxins account for the loss of millions of lives each year. Both belong to the clinically significant subset of bacterial AB5 toxins consisting of an enzymatically active A subunit that gains entry to susceptible mammalian cells after oligosaccharide recognition by the B5 homopentamer. Therapies might target the obligatory oligosaccharide–toxin recognition event, but the low intrinsic affinity of carbohydrate–protein interactions hampers the development of low-molecular-weight inhibitors. The toxins circumvent low affinity by binding simultaneously to five or more cell-surface carbohydrates. Here we demonstrate the use of the crystal structure of the B5 subunit of Escherichia coli O157:H7 Shiga-like toxin I (SLT-I) in complex with an analogue of its carbohydrate receptor to design an oligovalent, water-soluble carbohydrate ligand (named STARFISH), with subnanomolar inhibitory activity. The in vitro inhibitory activity is 1–10-million-fold higher than that of univalent ligands and is by far the highest molar activity of any inhibitor yet reported for Shiga-like toxins I and II. Crystallography of the STARFISH/Shiga-like toxin I complex explains this activity. Two trisaccharide receptors at the tips of each of five spacer arms simultaneously engage all five B subunits of two toxin molecules.

Improved Structure Refinement Through Maximum Likelihood

When crystal structures of proteins or small molecules are used to address questions of scientific relevance, the accuracy and precision of the atomic coordinates are crucial. Accordingly, the atomic model is generally improved by refining it to improve agreement with the observed diffraction data. The refinement of crystal structures is conventionally based on least-squares methods but such procedures are handicapped since conditions necessary for the use of the least-squares target are not satisfied. It is proposed here that refinement should be based on maximum likelihood and two maximum-likelihood targets have been implemented in the program XPLOR. Preliminary tests with protein structures give dramatic results. Compared to least-squares refinement, maximum-likelihood refinement can achieve more than twice the improvement in average phase error. The resulting electron-density maps are correspondingly clearer and suffer less from model bias.

How vitronectin binds PAI-1 to modulate fibrinolysis and cell migration

The interaction of the plasma protein vitronectin with plasminogen activator inhibitor-1 (PAI-1) is central to human health. Vitronectin binding extends the lifetime of active PAI-1, which controls hemostasis by inhibiting fibrinolysis and has also been implicated in angiogenesis. The PAI-1–vitronectin binding interaction also affects cell adhesion and motility. For these reasons, elevated PAI-1 activities are associated both with coronary thrombosis and with a poor prognosis in many cancers. Here we show the crystal structure at a resolution of 2.3 Å of the complex of the somatomedin B domain of vitronectin with PAI-1. The structure of the complex explains how vitronectin binds to and stabilizes the active conformation of PAI-1. It also explains the tissue effects of PAI-1, as PAI-1 competes for and sterically blocks the interaction of vitronectin with cell surface receptors and integrins. Structural understanding of the essential biological roles of the interaction between PAI-1 and vitronectin opens the prospect of specifically designed blocking agents for the prevention of thrombosis and treatment of cancer.

The active conformation of plasminogen activator inhibitor 1, a target for drugs to control fibrinolysis and cell adhesion

BACKGROUND Plasminogen activator inhibitor 1 (PAI-1) is a serpin that has a key role in the control of fibrinolysis through proteinase inhibition. PAI-1 also has a role in regulating cell adhesion processes relevant to tissue remodeling and metastasis; this role is mediated by its binding to the adhesive glycoprotein vitronectin rather than by proteinase inhibition. Active PAI-1 is metastable and spontaneously transforms to an inactive latent conformation. Previous attempts to crystallize the active conformation of PAI-1 have failed. RESULTS The crystal structure of a stable quadruple mutant of PAI-1(Asn150-->His, Lys154-->Thr, Gln319-->Leu, Met354-->Ile) in its active conformation has been solved at a nominal 3 A resolution. In two of four independent molecules within the crystal, the flexible reactive center loop is unconstrained by crystal-packing contacts and is disordered. In the other two molecules, the reactive center loop forms intimate loop-sheet interactions with neighboring molecules, generating an infinite chain within the crystal. The overall conformation resembles that seen for other active inhibitory serpins. CONCLUSIONS The structure clarifies the molecular basis of the stabilizing mutations and the reduced affinity of PAI-1, on cleavage or in the latent form, for vitronectin. The infinite chain of linked molecules also suggests a new mechanism for the serpin polymerization associated with certain diseases. The results support the concept that the reactive center loop of an active serpin is flexible and has no defined conformation in the absence of intermolecular contacts. The determination of the structure of the active form constitutes an essential step for the rational design of PAI-1 inhibitors.

Automatic protein structure solution from weak X-ray data.

Determining new protein structures from X-ray diffraction data at low resolution or with a weak anomalous signal is a difficult and often an impossible task. Here we propose a multivariate algorithm that simultaneously combines the structure determination steps. In tests on over 140 real data sets from the protein data bank, we show that this combined approach can automatically build models where current algorithms fail, including an anisotropically diffracting 3.88 Å RNA polymerase II data set. The method seamlessly automates the process, is ideal for non-specialists and provides a mathematical framework for successfully combining various sources of information in image processing.

The application of multivariate statistical techniques improves single-wavelength anomalous diffraction phasing.

Recently, there has been a resurgence in phasing using the single-wavelength anomalous diffraction (SAD) experiment; data from a single wavelength in combination with techniques such as density modification have been used to solve macromolecular structures, even with a very small anomalous signal. Here, a formulation for SAD phasing and refinement employing multivariate statistical techniques is presented. The equation developed accounts explicitly for the correlations among the observed and calculated Friedel mates in a SAD experiment. The correlated SAD equation has been implemented and test cases performed on real diffraction data have revealed better results compared with currently used programs in terms of correlation with the final map and obtaining more reliable phase probability statistics.

X-ray refinement significantly underestimates the level of microscopic heterogeneity in biomolecular crystals

Biomolecular X-ray structures typically provide a static, time- and ensemble-averaged view of molecular ensembles in crystals. In the absence of rigid-body motions and lattice defects, B-factors are thought to accurately reflect the structural heterogeneity of such ensembles. In order to study the effects of averaging on B-factors, we employ molecular dynamics simulations to controllably manipulate microscopic heterogeneity of a crystal containing 216 copies of villin headpiece. Using average structure factors derived from simulation, we analyse how well this heterogeneity is captured by high-resolution molecular-replacement-based model refinement. We find that both isotropic and anisotropic refined B-factors often significantly deviate from their actual values known from simulation: even at high 1.0 Å resolution and Rfree of 5.9%, B-factors of some well-resolved atoms underestimate their actual values even sixfold. Our results suggest that conformational averaging and inadequate treatment of correlated motion considerably influence estimation of microscopic heterogeneity via B-factors, and invite caution in their interpretation.