Subversion of host cell apoptosis is an important survival strategy for viruses to ensure their own proliferation and survival. Certain viruses express proteins homologous in sequence, structure and function to mammalian pro-survival B-cell lymphoma 2 (Bcl-2) proteins, which prevent rapid clearance of infected host cells. In vaccinia virus (VV), the virulence factor F1L was shown to be a potent inhibitor of apoptosis that functions primarily be engaging pro-apoptotic Bim. Variola virus (VAR), the causative agent of smallpox, harbors a homolog of F1L of unknown function. We show that VAR F1L is a potent inhibitor of apoptosis, and unlike all other characterized anti-apoptotic Bcl-2 family members lacks affinity for the Bim Bcl-2 homology 3 (BH3) domain. Instead, VAR F1L engages Bid BH3 as well as Bak and Bax BH3 domains. Unlike its VV homolog, variola F1L only protects against Bax-mediated apoptosis in cellular assays. Crystal structures of variola F1L bound to Bid and Bak BH3 domains reveal that variola F1L forms a domain-swapped Bcl-2 fold, which accommodates Bid and Bak BH3 in the canonical Bcl-2-binding groove, in a manner similar to VV F1L. Despite the observed conservation of structure and sequence, variola F1L inhibits apoptosis using a startlingly different mechanism compared with its VV counterpart. Our results suggest that unlike during VV infection, Bim neutralization may not be required during VAR infection. As molecular determinants for the human-specific tropism of VAR remain essentially unknown, identification of a different mechanism of action and utilization of host factors used by a VAR virulence factor compared with its VV homolog suggest that studying VAR directly may be essential to understand its unique tropism.

Apoptosis is a key innate defence mechanism to eliminate virally infected cells. To counteract premature host-cell apoptosis, poxviruses have evolved numerous molecular strategies, including the use of Bcl-2 proteins, to ensure their own survival. Here, it is reported that the Deerpox virus inhibitor of apoptosis, DPV022, only engages a highly restricted set of death-inducing Bcl-2 proteins, including Bim, Bax and Bak, with modest affinities. Structural analysis reveals that DPV022 adopts a Bcl-2 fold with a dimeric domain-swapped topology and binds pro-death Bcl-2 proteins via two conserved ligand-binding grooves found on opposite sides of the dimer. Structures of DPV022 bound to Bim, Bak and Bax BH3 domains reveal that a partial obstruction of the binding groove is likely to be responsible for the modest affinities of DPV022 for BH3 domains. These findings reveal that domain-swapped dimeric Bcl-2 folds are not unusual and may be found more widely in viruses. Furthermore, the modest affinities of DPV022 for pro-death Bcl-2 proteins suggest that two distinct classes of anti-apoptotic viral Bcl-2 proteins exist: those that are monomeric and tightly bind a range of death-inducing Bcl-2 proteins, and others such as DPV022 that are dimeric and only bind a very limited number of death-inducing Bcl-2 proteins with modest affinities.

Crystallization of macromolecules is famously difficult. By knowing what has worked for others, researchers can ease the process, both in the case where the protein has already been crystallized and in the situation where more general guidelines are needed. The 264 crystallization communications published in Acta Crystallographica Section F in 2012 have been reviewed, and from this analysis some information about trends in crystallization has been gleaned. More importantly, it was found that there are several ways in which the utility of these communications could be increased: to make each individual paper a more complete crystallization record; and to provide a means for taking a snapshot of what the current `best practices' are in the field.

Subversion of host cell apoptotic responses is a prominent feature of viral immune evasion strategies to prevent premature clearance of infected cells. Numerous poxviruses encode structural and functional homologs of the Bcl-2 family of proteins, and vaccinia virus harbors antiapoptotic F1L that potently inhibits the mitochondrial apoptotic checkpoint. Recently F1L has been assigned a caspase-9 inhibitory function attributed to an N-terminal ␣ helical region of F1L spanning residues 1-15 (1) preceding the domain-swapped Bcl-2-like domains. Using a reconstituted caspase inhibition assay in yeast we found that unlike AcP35, a well characterized caspase-9 inhibitor from the insect virus Autographa californica multiple nucleopolyhedrovirus, F1L does not prevent caspase-9-mediated yeast cell death. Furthermore, we found that deletion of the F1L N-terminal region does not impede F1L antiapoptotic activity in the context of a viral infection. Solution analysis of the F1L N-terminal regions using small angle x-ray scattering indicates that the region of F1L spanning residues 1-50 located N-terminally from the Bcl-2 fold is an intrinsically unstructured region. We conclude that the N terminus of F1L is not involved in apoptosis inhibition and may act as a regulatory element in other signaling pathways in a manner reminiscent of other unstructured regulatory elements commonly found in mammalian prosurvival Bcl-2 members including Bcl-x L and Mcl-1.

The process of producing suitable crystals for X-ray diffraction analysis most often involves the setting up of hundreds (or thousands) of individual crystallization trials, each of which must be repeatedly examined for crystals or hints of crystallinity. Currently, the only real way to address this bottleneck is to use an automated imager to capture images of the trials. However, the images still need to be assessed for crystals or other outcomes. Ideally, there would exist some rapid and reliable machine-analysis tool to translate the images into a quantitative result. However, as yet no such tool exists in wide usage, despite this being a well recognized problem. One of the issues in creating robust automatic image-analysis software is the lack of reliable data for training machine-learning algorithms. Here, a mobile application, Cinder, has been developed which allows crystallization images to be scored quickly on a smartphone or tablet. The Cinder scores are inserted into the appropriate table in a crystallization database and are immediately available to the user through a more sophisticated web interface, allowing more detailed analyses. A sharp increase in the number of scored images was observed after Cinder was released, which in turn provides more data for training machine-learning tools.