Estimating local protein model quality: prospects for molecular replacement

Identifying and Validating MYC:Protein Interactors in Pursuit of Novel Anti-MYC Therapies

By identifying MYC protein-protein interactors, we aim to gain a deeper mechanistic understanding of MYC as a regulator of gene transcription and potent oncoprotein. This information can then be used to devise strategies for disrupting critical MYC protein-protein interactions to inhibit MYC-driven tumorigenesis. In this chapter, we discuss four techniques to identify and validate MYC-interacting partners. First, we highlight BioID, a powerful discovery method used to identify high-confidence proximal interactors in living cells. We also discuss bioinformatic prioritization strategies for the BioID-derived MYC-proximal complexes. Next, we discuss how protein interactions can be validated using techniques such as in vivo-in vitro pull-down assays and the proximity ligation assay (PLA). We conclude with an overview of biolayer interferometry (BLI), a quantitative method used to characterize direct interactions between two proteins in vitro. Overall, we highlight the principles of each assay and provide methodology necessary to conduct these experiments and adapt them to the study of interactors of additional proteins of interest.

Phasertng: directed acyclic graphs for crystallographic phasing

Crystallographic phasing strategies increasingly require the exploration and ranking of many hypotheses about the number, types and positions of atoms, molecules and/or molecular fragments in the unit cell, each with only a small chance of being correct. Accelerating this move has been improvements in phasing methods, which are now able to extract phase information from the placement of very small fragments of structure, from weak experimental phasing signal or from combinations of molecular replacement and experimental phasing information. Describing phasing in terms of a directed acyclic graph allows graph-management software to track and manage the path to structure solution. The crystallographic software supporting the graph data structure must be strictly modular so that nodes in the graph are efficiently generated by the encapsulated functionality. To this end, the development of new software, Phasertng, which uses directed acyclic graphs natively for input/output, has been initiated. In Phasertng, the codebase of Phaser has been rebuilt, with an emphasis on modularity, on scripting, on speed and on continuing algorithm development. As a first application of phasertng, its advantages are demonstrated in the context of phasertng.xtricorder, a tool to analyse and triage merged data in preparation for molecular replacement or experimental phasing. The description of the phasing strategy with directed acyclic graphs is a generalization that extends beyond the functionality of Phasertng, as it can incorporate results from bioinformatics and other crystallographic tools, and will facilitate multifaceted search strategies, dynamic ranking of alternative search pathways and the exploitation of machine learning to further improve phasing strategies.