Summary Clathrin-coated vesicle formation is responsible for membrane traffic to and from the endocytic pathway during receptor-mediated endocytosis and organelle biogenesis, influencing how cells relate to their environment. Generating these vesicles involves self-assembly of clathrin molecules into a latticed coat on membranes that recruits receptors and organizes protein machinery necessary for budding. Here we define a molecular mechanism regulating clathrin lattice formation by obtaining structural information from co-crystals of clathrin subunits. Low resolution X-ray diffraction data (7.9–9.0Å) was analyzed using a combination of molecular replacement with an energyminimized model, and non-crystallographic symmetry averaging. Resulting topological information revealed two conformations of the regulatory clathrin light chain bound to clathrin heavy chain. Based on protein domain positions, mutagenesis and biochemical assays, we identify an electrostatic interaction between the clathrin subunits that allows the observed conformational variation in clathrin light chains to alter the conformation of the clathrin heavy chain and thereby regulate assembly.

Molecular recognition features, MoRFs, are short segments within longer disordered protein regions that bind to globular protein domains in a process known as disorder-to-order transition. MoRFs have been found to play a significant role in signaling and regulatory processes in cells. High-confidence computational identification of MoRFs remains an important challenge. In this work, we introduce MoRFchibi SYSTEM that contains three MoRF predictors: MoRFCHiBi, a basic predictor best suited as a component in other applications, MoRFCHiBi_Light, ideal for high-throughput predictions and MoRFCHiBi_Web, slower than the other two but best for high accuracy predictions. Results show that MoRFchibi SYSTEM provides more than double the precision of other predictors. MoRFchibi SYSTEM is available in three different forms: as HTML web server, RESTful web server and downloadable software at: http://www.chibi.ubc.ca/faculty/joerg-gsponer/gsponer-lab/software/morf_chibi/

The separation of deleterious from benign mutations remains a key challenge in the interpretation of genomic data. Computational methods used to sort mutations based on their potential deleteriousness rely largely on conservation measures derived from sequence alignments. Here, we introduce LIST-S2, a successor to our previously developed approach LIST, which aims to exploit local sequence identity and taxonomy distances in quantifying the conservation of human protein sequences. Unlike its predecessor, LIST-S2 is not limited to human sequences but can assess conservation and make predictions for sequences from any organism. Moreover, we provide a web-tool and downloadable software to compute and visualize the deleteriousness of mutations in user-provided sequences. This web-tool contains an HTML interface and a RESTful API to submit and manage sequences as well as a browsable set of precomputed predictions for a large number of UniProtKB protein sequences of common taxa. LIST-S2 is available at: https://list-s2.msl.ubc.ca/