The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

Seeing but not believing: the structure of glycerol dehydrogenase initially assumed to be the structure of a survival protein from Salmonella typhimurium

The determination of the crystal structure of a mutant protein using phases based on a previously determined crystal structure of the wild-type protein is often a straightforward molecular-replacement protocol. Such a structure determination may be difficult if there are large-scale structural differences between the wild-type and mutant proteins. In this manuscript, an interesting case is presented of the unintentional crystallization of a contaminant protein which shared some structural features with the presumed target protein, leading to difficulties in obtaining a completely satisfactory molecular-replacement structure solution. It was not immediately evident that the initial structure solution was incorrect owing to the poor quality of the X-ray diffraction data and low resolution. The structure was subsequently determined by improving the quality of the data and following a sequence-independent MarathonMR protocol. The structure corresponded to that of glycerol dehydrogenase, which crystallized as a contaminant, instead of the presumed mutant of a survival protein encoded by Salmonella typhimurium. The reasons why a solution that appeared to be reasonable was obtained with an incorrect protein model are discussed. The results presented here show that a degree of caution is warranted when handling large-scale structure-determination projects.

Structure determination of contaminant proteins using the MarathonMR procedure

In the recent decades, essential steps of protein structure determination such as phasing by multiple isomorphous replacement and multi wave length anomalous dispersion, molecular replacement, refinement of the structure determined and its validation have been fully automated. Several computer program suites that execute all these steps as a pipeline operation have been made available. In spite of these great advances, determination of a protein structure may turn out to be a challenging task for a variety of reasons. It might be difficult to obtain multiple isomorphous replacement or multi wave length anomalous dispersion data or the crystal may have defects such as twinning or pseudo translation. Apart from these usual difficulties, more frequent difficulties have been encountered in recent years because of the large number of projects handled by structural biologists. These new difficulties usually result from contamination of the protein of interest by other proteins or presence of proteins from pathogenic organisms that could withstand the antibiotics used to prevent bacterial contamination. It could also be a result of poor book keeping. Recently, we have developed a procedure called MarathonMR that has the power to resolve some of these problems automatically. In this communication, we describe how the MarathonMR was used to determine four different protein structures that had remained elusive for several years. We describe the plausible reasons for the difficulties encountered in determining these structures and point out that the method presented here could be a validation tool for protein structures deposited in the protein data bank.

Determination of crystal structures of proteins of unknown identity using a marathon molecular replacement procedure: structure of Stenotrophomonas maltophilia phosphate-binding protein

During the past decade, the authors have collected a few X-ray diffraction data sets from protein crystals that appeared to be easy cases of molecular replacement but failed to yield structures even after extensive trials. Here, the use of a large-scale molecular replacement method that explores all structurally characterized domains as phasing models to determine the structure corresponding to two data sets collected at 1.9 and 2.3 Å resolution is reported. These two structures were of the same protein independently crystallized in 2007 and 2011. The structures derived are virtually identical and were found to consist of two compact globular domains connected by a hinge. The high resolution of one of these data sets enabled inference of the amino-acid sequence from the electron-density map. The deduced sequence is nearly identical to that of a protein from the multidrug-resistant bacterium Stenotrophomonas maltophilia. Although the structure of this protein has not been determined previously, it is homologous to the well studied DING proteins which mediate the cellular uptake of phosphate ions. The final electron-density maps from both of the data sets revealed a large density at the interface of the two globular domains that is likely to represent a phosphate ion. Thus, the structure is likely to be that of a phosphate-binding protein encoded by the S. maltophilia genome (SmPBP; PDB entry 5j1d). The nature of the phosphate-binding site of SmPBP closely resembles that of Pseudomonas fluorescens DING (PfluDING), which displays remarkable discrimination between the closely similar phosphate and arsenate ions. The results presented here illustrate that routine crystallization trials may occasionally lead to the serendipitous crystallization of a protein of unknown identity and brute-force molecular replacement through `fold space' might allow the identification of the unknown protein.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 'high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.