Improvement of molecular-replacement models with Sculptor.

In molecular replacement, the quality of models can be improved by transferring information contained in sequence alignment to the template structure. A family of algorithms has been developed that make use of the sequence-similarity score calculated from residue-substitution scores smoothed over nearby residues to delete or downweight parts of the model that are unreliable. These algorithms have been implemented in the program Sculptor, together with well established methods that are in common use for model improvement. An analysis of the new algorithms has been performed by studying the effect of algorithm parameters on the quality of models. Benchmarking against existing techniques shows that models from Sculptor compare favourably, especially if the alignment is unreliable. Carrying out multiple trials using alternative models created from the same structure but using different algorithm parameters can significantly improve the success rate

Using SAD data in Phaser.

Phaser is a program that implements likelihood-based methods to solve macromolecular crystal structures, currently by molecular replacement or single-wavelength anomalous diffraction (SAD). SAD phasing is based on a likelihood target derived from the joint probability distribution of observed and calculated pairs of Friedel-related structure factors. This target combines information from the total structure factor (primarily non-anomalous scattering) and the difference between the Friedel mates (anomalous scattering). Phasing starts from a substructure, which is usually but not necessarily a set of anomalous scatterers. The substructure can also be a protein model, such as one obtained by molecular replacement. Additional atoms are found using a log-likelihood gradient map, which shows the sites where the addition of scattering from a particular atom type would improve the likelihood score. An automated completion algorithm adds new sites, choosing optionally among different atom types, adds anisotropic B-factor parameters if appropriate and deletes atoms that refine to low occupancy. Log-likelihood gradient maps can also identify which atoms in a refined protein structure are anomalous scatterers, such as metal or halide ions. These maps are more sensitive than conventional model-phased anomalous difference Fouriers and the iterative completion algorithm is able to find a significantly larger number of convincing sites

Case-controlled structure validation.

Although many factors influence the quality of a macromolecular crystal structure, validation criteria are usually only calibrated using one of these factors, the resolution. For many purposes this is sufficient, but there are times when one wishes to compare one set of structures with another and the comparison may be invalidated by systematic differences between the sets in factors other than resolution. This problem can be circumvented by borrowing from medicine the idea of the case-matched control: each structure of interest is matched with a control structure that has similar values for all relevant factors considered in this study. In addition to resolution, these include the size of the structure (as measured by the volume of the asymmetric unit) and the year of deposition. This approach has been applied to address two questions: whether structures from structural genomics efforts reach the same level of quality as structures from traditional sources and whether the impact factor of the journal in which a structure is published correlates with structure quality. In both cases, once factors influencing quality have been controlled in the comparison, there is little evidence for a systematic difference in quality

Local error estimates dramatically improve the utility of homology models for solving crystal structures by molecular replacement.

Predicted structures submitted for CASP10 have been evaluated as molecular replacement models against the corresponding sets of structure factor amplitudes. It has been found that the log-likelihood gain score computed for each prediction correlates well with common structure quality indicators but is more sensitive when the accuracy of the models is high. In addition, it was observed that using coordinate error estimates submitted by predictors to weight the model can improve its utility in molecular replacement dramatically, and several groups have been identified who reliably provide accurate error estimates that could be used to extend the application of molecular replacement for low-homology cases.Support received from the NIH (grant P01GM063210), the Wellcome Trust (Principal Research Fellowship to R.J.R., grant 082961/Z/07/Z; Strategic Award to the Cambridge Institute for Medical Research), as well as from the Swedish Research Council (621-2012-5270), Swedish e-Science Research Center, and Carl Tryggers Stiftelse to B.W. is gratefully acknowledged.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0969212614004146#

Towards engineering hormone-binding globulins as drug delivery agents.

The treatment of many diseases such as cancer requires the use of drugs that can cause severe side effects. Off-target toxicity can often be reduced simply by directing the drugs specifically to sites of diseases. Amidst increasingly sophisticated methods of targeted drug delivery, we observed that Nature has already evolved elegant means of sending biological molecules to where they are needed. One such example is corticosteroid binding globulin (CBG), the major carrier of the anti-inflammatory hormone, cortisol. Targeted release of cortisol is triggered by cleavage of CBG's reactive centre loop by elastase, a protease released by neutrophils in inflamed tissues. This work aimed to establish the feasibility of exploiting this mechanism to carry therapeutic agents to defined locations. The reactive centre loop of CBG was altered with site-directed mutagenesis to favour cleavage by other proteases, to alter the sites at which it would release its cargo. Mutagenesis succeeded in making CBG a substrate for either prostate specific antigen (PSA), a prostate-specific serine protease, or thrombin, a key protease in the blood coagulation cascade. PSA is conspicuously overproduced in prostatic hyperplasia and is, therefore, a good way of targeting hyperplastic prostate tissues. Thrombin is released during clotting and consequently is ideal for conferring specificity to thrombotic sites. Using fluorescence-based titration assays, we also showed that CBG can be engineered to bind a new compound, thyroxine-6-carboxyfluorescein, instead of its physiological ligand, cortisol, thereby demonstrating that it is possible to tailor the hormone binding site to deliver a therapeutic drug. In addition, we proved that the efficiency with which CBG releases bound ligand can be increased by introducing some well-placed mutations. This proof-of-concept study has raised the prospect of a novel means of targeted drug delivery, using the serpin conformational change to combat the problem of off-target effects in the treatment of diseases.The research was funded by the Wellcome Trust (http://www.wellcome.ac.uk/) grant no. 082961/Z/07/Z to RJR and was facilitated by a Wellcome Trust Strategic Award to the Cambridge Institute for Medical Research. WLC was supported by the Singapore government’s Agency for Science, Technology and Research (http://www.astar.edu.sg/). AZ was supported by a Senior Research Fellowship from the British Heart Foundation (http://www.bhf.org.uk). RJR is supported by a Principal Research Fellowship from the Wellcome Trust.This is the final published version. It originally appeared in PLOS ONE at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0113402

Likelihood-based estimation of substructure content from single-wavelength anomalous diffraction (SAD) intensity data.

SAD phasing can be challenging when the signal-to-noise ratio is low. In such cases, having an accurate estimate of the substructure content can determine whether or not the substructure of anomalous scatterer positions can successfully be determined. Here, a likelihood-based target function is proposed to accurately estimate the strength of the anomalous scattering contribution directly from the measured intensities, determining a complex correlation parameter relating the Bijvoet mates as a function of resolution. This gives a novel measure of the intrinsic anomalous signal. The SAD likelihood target function also accounts for correlated errors in the measurement of intensities from Bijvoet mates, which can arise from the effects of radiation damage. When the anomalous signal is assumed to come primarily from a substructure comprising one anomalous scatterer with a known value of f'' and when the protein composition of the crystal is estimated correctly, the refined complex correlation parameters can be interpreted in terms of the atomic content of the primary anomalous scatterer before the substructure is known. The maximum-likelihood estimation of substructure content was tested on a curated database of 357 SAD cases with useful anomalous signal. The prior estimates of substructure content are highly correlated to the content determined by phasing calculations, with a correlation coefficient (on a log-log basis) of 0.72

Implications of AlphaFold2 for crystallographic phasing by molecular replacement.

The AlphaFold2 results in the 14th edition of Critical Assessment of Structure Prediction (CASP14) showed that accurate (low root-mean-square deviation) in silico models of protein structure domains are on the horizon, whether or not the protein is related to known structures through high-coverage sequence similarity. As highly accurate models become available, generated by harnessing the power of correlated mutations and deep learning, one of the aspects of structural biology to be impacted will be methods of phasing in crystallography. Here, the data from CASP14 are used to explore the prospects for changes in phasing methods, and in particular to explore the prospects for molecular-replacement phasing using in silico models

Measuring and using information gained by observing diffraction data.

The information gained by making a measurement, termed the Kullback-Leibler divergence, assesses how much more precisely the true quantity is known after the measurement was made (the posterior probability distribution) than before (the prior probability distribution). It provides an upper bound for the contribution that an observation can make to the total likelihood score in likelihood-based crystallographic algorithms. This makes information gain a natural criterion for deciding which data can legitimately be omitted from likelihood calculations. Many existing methods use an approximation for the effects of measurement error that breaks down for very weak and poorly measured data. For such methods a different (higher) information threshold is appropriate compared with methods that account well for even large measurement errors. Concerns are raised about a current trend to deposit data that have been corrected for anisotropy, sharpened and pruned without including the original unaltered measurements. If not checked, this trend will have serious consequences for the reuse of deposited data by those who hope to repeat calculations using improved new methods