Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation

This study aimed to understand whether or not computer models of saliency could explain landmark saliency. An online survey was conducted and participants were asked to watch videos from a spatial navigation video game (Sea Hero Quest). Participants were asked to pay attention to the environments within which the boat was moving and to rate the perceived saliency of each landmark. In addition, state-of-the-art computer saliency models were used to objectively quantify landmark saliency. No significant relationship was found between objective and subjective saliency measures. This indicates that during passive observation of an environment while being navigated, current automated models of saliency fail to predict subjective reports of visual attention to landmarks

Entropy and a Sub-Group of Geometric Measures of Paths Predict the Navigability of an Environment

Despite extensive research on navigation, it remains unclear which features of an environment predict how difficult it will be to navigate. We analysed 478,170 trajectories from 10,626 participants who navigated 45 virtual environments in the research app-based game Sea Hero Quest. Virtual environments were designed to vary in a range of properties such as their layout, number of goals, visibility (varying fog) and map condition. We calculated 58 spatial measures grouped into four families: task-specific metrics, space syntax configurational metrics, space syntax geometric metrics, and general geometric metrics. We used Lasso, a variable selection method, to select the most predictive measures of navigation difficulty. Geometric features such as entropy, area of navigable space, number of rings and closeness centrality of path networks were among the most significant factors determining the navigational difficulty. By contrast a range of other measures did not predict difficulty, including measures of intelligibility. Unsurprisingly, other task-specific features (e.g. number of destinations) and fog also predicted navigation difficulty. These findings have implications for the study of spatial behaviour in ecological settings, as well as predicting human movements in different settings, such as complex buildings and transport networks and may aid the design of more navigable environments

Molecular mechanism of activation of human musk receptors OR5AN1 and OR1A1 by (R)-muscone and diverse other musk-smelling compounds

We acknowledge support from NSF (CHE-1265679) and NIH (5R01DC014423 subaward) (EB), NIH (5R01 DC014423) (HM), the European Reasearch Council (ERC) and the Engineering Science Research Council (EPSRC) (DO'H), FAPESP and CNPq (RAC), the Chinese Scholarship Council (CSC) for studentship support (MY), National Science Foundation (31070972) (HZ), Science and Technology Commission of Shanghai Municipality (16ZR1418300) (HZ), the Shanghai Eastern Scholar Program (J50201) (HZ). VSB thanks NIH grant 1R01GM106121-01A1 and computational time from NERSC.Understanding olfaction at the molecular level is challenging due to the lack of crystallographic models of odorant receptors (ORs). To better understand the molecular mechanism of OR activation, we focused on chiral (R)-muscone and other musk smelling odorants due to their great importance and widespread use in perfumery and traditional medicine, as well as environmental concerns associated with bioaccumulation of musks with estrogenic/antiestrogenic properties.  We experimentally and computationally examined the activation of human receptors OR5AN1 and OR1A1, recently identified as specifically responding to musk compounds.  OR5AN1 responds at nanomolar concentrations to musk ketone and robustly to macrocyclic sulfoxides and fluorine-substituted macrocyclic ketones; OR1A1 responds only to nitromusks. Structural models of OR5AN1 and OR1A1 based on quantum mechanics/molecular mechanics (QM/MM) hybrid methods were validated through direct comparisons with activation profiles from site-directed mutagenesis experiments and analysis of binding energies for 35 musk-related odorants.  The experimentally found chiral selectivity of OR5AN1 to (R)- over (S)-muscone was also computationally confirmed for muscone and fluorinated (R)-muscone analogs.  Structural models show that OR5AN1, highly responsive to nitromusks over macrocyclic musks, stabilizes odorants by hydrogen bonding to Tyr260 of transmembrane a-helix 6 and hydrophobic interactions with surrounding aromatic residues Phe105, Phe194 and, Phe207.  The binding of OR1A1 to nitromusks is stabilized by hydrogen bonding to Tyr258 along with hydrophobic interactions with surrounding aromatic residues Tyr251 and Phe206.  Hydrophobic/nonpolar and hydrogen bonding interactions contribute, respectively, 77% and 13% to the odorant binding affinities, as shown by an atom-based quantitative structure-activity relationship model.PostprintPeer reviewe

Disulfide Bridges Remain Intact while Native Insulin Converts into Amyloid Fibrils

Amyloid fibrils are β-sheet-rich protein aggregates commonly found in the organs and tissues of patients with various amyloid-associated diseases. Understanding the structural organization of amyloid fibrils can be beneficial for the search of drugs to successfully treat diseases associated with protein misfolding. The structure of insulin fibrils was characterized by deep ultraviolet resonance Raman (DUVRR) and Nuclear Magnetic Resonance (NMR) spectroscopy combined with hydrogen-deuterium exchange. The compositions of the fibril core and unordered parts were determined at single amino acid residue resolution. All three disulfide bonds of native insulin remained intact during the aggregation process, withstanding scrambling. Three out of four tyrosine residues were packed into the fibril core, and another aromatic amino acid, phenylalanine, was located in the unordered parts of insulin fibrils. In addition, using all-atom MD simulations, the disulfide bonds were confirmed to remain intact in the insulin dimer, which mimics the fibrillar form of insulin

Unraveling the photoluminescence response of light-switching ruthenium(II) complexes bound to amyloid-β

Photoluminescent molecules are widely used for real-time monitoring of peptide aggregation. In this Article, we detail both experimental and computational modeling to elucidate the interaction between [Ru(bpy)2dppz](2+) and amyloid-β (Aβ(1-40)) aggregates. The transition from monomeric to fibrillar Aβ is of interest in the study of Alzheimer's disease. Concentration-dependent experiments allowed the determination of a dissociation constant of 2.1 μM, while Job plots provided a binding stoichiometry of 2.6 Aβ monomers per [Ru(bpy)2dppz](2+). Our computational approach that combines molecular docking (both rigid and flexible) and all-atom molecular dynamics (MD) simulations predicts that the hydrophobic cleft between Val18 and Phe20 is a plausible binding site, which could also explain the increase in photoluminescence of [Ru(bpy)2dppz](2+) upon binding. This binding site is parallel to the fibril axis, in marked contrast to the binding site of these complexes in DNA (perpendicular to the DNA axis). Other binding sites may exist at the edges of the Aβ fibril, but they are actually of low abundance in an Aβ fibril several micrometers long. The assignment of the binding site was confirmed by binding studies in an Aβ fragment (Aβ(25-35)) that lacked the amino acids necessary to form the binding site. The agreement between the experimental and computational work is remarkable and provides a general model that can be used for studying the interaction of amyloid-binding molecules to Aβ

Unraveling the Photoluminescence Response of Light-Switching Ruthenium(II) Complexes Bound to Amyloid‑β

Photoluminescent molecules are widely used for real-time monitoring of peptide aggregation. In this Article, we detail both experimental and computational modeling to elucidate the interaction between [Ru­(bpy)₂dppz]²⁺ and amyloid-β (Aβ_1–40) aggregates. The transition from monomeric to fibrillar Aβ is of interest in the study of Alzheimer’s disease. Concentration-dependent experiments allowed the determination of a dissociation constant of 2.1 μM, while Job plots provided a binding stoichiometry of 2.6 Aβ monomers per [Ru­(bpy)₂dppz]²⁺. Our computational approach that combines molecular docking (both rigid and flexible) and all-atom molecular dynamics (MD) simulations predicts that the hydrophobic cleft between Val18 and Phe20 is a plausible binding site, which could also explain the increase in photoluminescence of [Ru­(bpy)₂dppz]²⁺ upon binding. This binding site is parallel to the fibril axis, in marked contrast to the binding site of these complexes in DNA (perpendicular to the DNA axis). Other binding sites may exist at the edges of the Aβ fibril, but they are actually of low abundance in an Aβ fibril several micrometers long. The assignment of the binding site was confirmed by binding studies in an Aβ fragment (Aβ_25–35) that lacked the amino acids necessary to form the binding site. The agreement between the experimental and computational work is remarkable and provides a general model that can be used for studying the interaction of amyloid-binding molecules to Aβ

Entropy and a sub-group of geometric measures of paths predict the navigability of an environment

Despite extensive research on navigation, it remains unclear which features of an environment predict how difficult it will be to navigate. We analysed 478,170 trajectories from 10,626 participants who navigated 45 virtual environments in the research app-based game Sea Hero Quest. Virtual environments were designed to vary in a range of properties such as their layout, number of goals, visibility (varying fog) and map condition. We calculated 58 spatial measures grouped into four families: task-specific metrics, space syntax configurational metrics, space syntax geometric metrics, and general geometric metrics. We used Lasso, a variable selection method, to select the most predictive measures of navigation difficulty. Geometric features such as entropy, area of navigable space, number of rings and closeness centrality of path networks were among the most significant factors determining the navigational difficulty. By contrast a range of other measures did not predict difficulty, including measures of intelligibility. Unsurprisingly, other task-specific features (e.g. number of destinations) and fog also predicted navigation difficulty. These findings have implications for the study of spatial behaviour in ecological settings, as well as predicting human movements in different settings, such as complex buildings and transport networks and may aid the design of more navigable environments

A Redox-Active, Compact Molecule for Cross-Linking Amyloidogenic Peptides into Nontoxic, Off-Pathway Aggregates: In Vitro and In Vivo Efficacy and Molecular Mechanisms

Chemical reagents targeting and controlling amyloidogenic peptides have received much attention for helping identify their roles in the pathogenesis of protein-misfolding disorders. Herein, we report a novel strategy for redirecting amyloidogenic peptides into nontoxic, off-pathway aggregates, which utilizes redox properties of a small molecule (DMPD, N,N-dimethyl-p-phenylenediamine) to trigger covalent adduct formation with the peptide. In addition, for the first time, biochemical, biophysical, and molecular dynamics simulation studies have been performed to demonstrate a mechanistic understanding for such an interaction between a small molecule (DMPD) and amyloid-?? (A??) and its subsequent anti-amyloidogenic activity, which, upon its transformation, generates ligand-peptide adducts via primary amine-dependent intramolecular cross-linking correlated with structural compaction. Furthermore, in vivo efficacy of DMPD toward amyloid pathology and cognitive impairment was evaluated employing 5xFAD mice of Alzheimer???s disease (AD). Such a small molecule (DMPD) is indicated to noticeably reduce the overall cerebral amyloid load of soluble A?? forms and amyloid deposits as well as significantly improve cognitive defects in the AD mouse model. Overall, our in vitro and in vivo studies of DMPD toward A?? with the first molecular-level mechanistic investigations present the feasibility of developing new, innovative approaches that employ redox-active compounds without the structural complexity as next-generation chemical tools for amyloid management.close