A Diffeomorphic Aging Model for Adult Human Brain from Cross-Sectional Data

Normative aging trends of the brain can serve as an important reference in the assessment of neurological structural disorders. Such models are typically developed from longitudinal brain image data – follow-up data of the same subject over different time points. In practice, obtaining such longitudinal data is difficult. We propose a method to develop an aging model for a given population, in the absence of longitudinal data, by using images from different subjects at different time points, the so-called cross-sectional data. We define an aging model as a diffeomorphic deformation on a structural template derived from the data and propose a method that develops topology preserving aging model close to natural aging. The proposed model is successfully validated on two public cross-sectional datasets which provide templates constructed from different sets of subjects at different age points.

3D particle averaging and detection of macromolecular symmetry in localization microscopy

Single molecule localization microscopy offers in principle resolution down to the molecular level, but in practice this is limited primarily by incomplete fluorescent labeling of the structure. This missing information can be completed by merging information from many structurally identical particles. In this work, we present an approach for 3D single particle analysis in localization microscopy which hugely increases signal-to-noise ratio and resolution and enables determining the symmetry groups of macromolecular complexes. Our method does not require a structural template, and handles anisotropic localization uncertainties. We demonstrate 3D reconstructions of DNA-origami tetrahedrons, Nup96 and Nup107 subcomplexes of the nuclear pore complex acquired using multiple single molecule localization microscopy techniques, with their structural symmetry deducted from the data.

Molecular basis of ligand recognition and activation of human V2 vasopressin receptor

The V2 vasopressin receptor (V2R) is a class A G protein-coupled receptor (GPCR) and plays a vital role in controlling water homeostasis upon stimulation by the natural peptide arginine vasopressin (AVP). Thus, V2R has attracted intense interest as a drug target for diabetes insipidus, nocturia, and hyponatremia. However, how AVP recognizes and activates V2R remains elusive. Here, we report the 2.6 Å resolution structure of V2R bound to AVP and the stimulatory G protein Gs, determined by cryo-electron microscopy (cryo-EM). In this complex, AVP presents a unique cyclic conformation formed by an intramolecular disulfide bond and engages the orthosteric binding pocket of V2R in a ligand-specific mode. Comparison of the AVP–V2R–Gs complex to previously reported Gs-coupled class A GPCRs reveals distinct structural features, including a smaller outward movement of TM5 and TM6 and the concomitant shift of Gs protein. Our detailed structural analysis provides a framework for understanding AVP recognition and V2R activation, thereby offering a structural template for drug design targeting V2R.

Specificities of modeling membrane proteins using multi-template homology modeling

Structures of membrane proteins are challenging to determine experimentally and currently represent only about 2% of the structures in the ProteinDataBank. Because of this disparity, methods for modeling membrane proteins are fewer and of lower quality than those for modeling soluble proteins. However, better expression, crystallization, and cryo-EM techniques have prompted a recent increase in experimental structures of membrane proteins, which can act as templates to predict the structure of closely related proteins through homology modeling. Because homology modeling relies on a structural template, it is easier and more accurate than fold recognition methods or de novo modeling, which are used when the sequence similarity between the query sequence and the sequence of related proteins in structural databases is below 25%. In homology modeling, a query sequence is mapped onto the coordinates of a single template and refined. With the increase in available templates, several templates often cover overlapping segments of the query sequence. Multi-template modeling can be used to identify the best template for local segments and join them into a single model. Here we provide a protocol for modeling membrane proteins from multiple templates in the Rosetta software suite. This approach takes advantage of several integrated frameworks, namely RosettaScripts, RosettaCM, and RosettaMP with the membrane scoring function.

Structure-based mechanism of preferential complex formation by apoptosis signal–regulating kinases

Apoptosis signal–regulating kinases (ASK1, ASK2, and ASK3) are activators of the p38 and c-Jun N-terminal kinase (JNK) mitogen-activated protein kinase (MAPK) pathways. ASK1–3 form oligomeric complexes known as ASK signalosomes that initiate signaling cascades in response to diverse stress stimuli. Here, we demonstrated that oligomerization of ASK proteins is driven by previously uncharacterized sterile-alpha motif (SAM) domains that reside at the carboxy-terminus of each ASK protein. SAM domains from ASK1–3 exhibited distinct behaviors, with the SAM domain of ASK1 forming unstable oligomers, that of ASK2 remaining predominantly monomeric, and that of ASK3 forming a stable oligomer even at a low concentration. In contrast to their behavior in isolation, the ASK1 and ASK2 SAM domains preferentially formed a stable heterocomplex. The crystal structure of the ASK3 SAM domain, small-angle x-ray scattering, and mutagenesis suggested that ASK3 oligomers and ASK1-ASK2 complexes formed discrete, quasi-helical rings through interactions between the mid-loop of one molecule and the end helix of another molecule. Preferential ASK1-ASK2 binding was consistent with mass spectrometry showing that full-length ASK1 formed hetero-oligomeric complexes incorporating large amounts of ASK2. Accordingly, disrupting the association between SAM domains impaired ASK activity in the context of electrophilic stress induced by 4-hydroxy-2-nonenal (HNE). These findings provide a structural template for how ASK proteins assemble foci that drive inflammatory signaling and reinforce the notion that strategies to target ASK proteins should consider the concerted actions of multiple ASK family members.

DIMERBOW: exploring possible GPCR dimer interfaces

Motivation G protein-coupled receptors (GPCRs) can form homo-, heterodimers and larger order oligomers that exert different functions than monomers. The pharmacological potential of such complexes is hampered by the limited information available on the type of complex formed and its quaternary structure. Several GPCR structures in the Protein Data Bank display crystallographic interfaces potentially compatible with physiological interactions. Results Here, we present DIMERBOW, a database and web application aimed to visually browse the complete repertoire of potential GPCR dimers present in solved structures. The tool is suited to help finding the best possible structural template to model GPCR homomers. Availability and implementation DIMERBOW is available at http://lmc.uab.es/dimerbow/. Supplementary information Supplementary data are available at Bioinformatics online.