Since the first crystal structure determinations of αβ T cell receptors (TCRs) bound to class I MHC-peptide (pMHC) antigens in 1996, a sizable database of 24 class I and class II TCR/pMHC complexes has been accumulated that now defines a substantial degree of structural variability in TCR/pMHC recognition. Recent determination of free and bound γδ TCR structures has enabled comparisons of the modes of antigen recognition by αβ and γδ T cells and antibodies. Crystal structures of TCR accessory (CD4, CD8) and coreceptor molecules (CD3ɛδ, CD3ɛγ) have further advanced our structural understanding of most of the components that constitute the TCR signaling complex. Despite all these efforts, the structural basis for MHC restriction and signaling remains elusive as no structural features that define a common binding mode or signaling mechanism have yet been gleaned from the current set of TCR/pMHC complexes. Notwithstanding, the impressive array of self, foreign (microbial), and autoimmune TCR complexes have uncovered the diverse ways in which antigens can be specifically recognized by TCRs.

TIP47 (tail-interacting protein of 47 kD) was characterized as a cargo selection device for mannose 6-phosphate receptors (MPRs), directing their transport from endosomes to the trans-Golgi network. In contrast, our current analysis shows that cytosolic TIP47 is not recruited to organelles of the biosynthetic and endocytic pathways. Knockdown of TIP47 expression had no effect on MPR distribution or trafficking and did not affect lysosomal enzyme sorting. Therefore, our data argue against a function of TIP47 as a sorting device. Instead, TIP47 is recruited to lipid droplets (LDs) by an amino-terminal sequence comprising 11-mer repeats. We show that TIP47 has apolipoprotein-like properties and reorganizes liposomes into small lipid discs. Suppression of TIP47 blocked LD maturation and decreased the incorporation of triacylglycerol into LDs. We conclude that TIP47 functions in the biogenesis of LDs.

The Drug Design Data Resource (D3R) ran Grand Challenge 2 (GC2) from September 2016 through February 2017. This challenge was based on a dataset of structures and affinities for the nuclear receptor farnesoid X receptor (FXR), contributed by F. Hoffmann-La Roche. The dataset contained 102 IC50 values, spanning six orders of magnitude, and 36 high-resolution co-crystal structures with representatives of four major ligand classes. Strong global participation was evident, with 49 participants submitting 262 prediction submission packages in total. Procedurally, GC2 mimicked Grand Challenge 2015 (GC2015), with a Stage 1 subchallenge testing ligand pose prediction methods and ranking and scoring methods, and a Stage 2 subchallenge testing only ligand ranking and scoring methods after the release of all blinded co-crystal structures. Two smaller curated sets of 18 and 15 ligands were developed to test alchemical free energy methods. This overview summarizes all aspects of GC2, including the dataset details, challenge procedures, and participant results. We also consider implications for progress in the field, while highlighting methodological areas that merit continued development. Similar to GC2015, the outcome of GC2 underscores the pressing need for methods development in pose prediction, particularly for ligand scaffolds not currently represented in the Protein Data Bank (http://www.pdb.org), and in affinity ranking and scoring of bound ligands.