Illumination by short-wavelength light inside the blind spot decreases light detectability.

Although the optic disk corresponding to the blind spot contains no classical photoreceptors, it contains photopigment melanopsin. To clarify whether melanopsin is involved in light detection, we conducted detection tasks for light stimuli presented in the normal visual field, with and without another illumination inside the blind spot. We found that a blue blind-spot illumination decreased the light detectability on a dark background. This effect was replicable when it was determined immediately after the blind-spot illumination was turned off, suggesting the contribution of a sluggish system rather than scattering. Moreover, the aforementioned effect was not observed when the blind-spot illumination was in red, indicating wavelength specificity in favor of melanopsin's sensitivity profile. These findings suggest that melanopsin is activated by the blind-spot illumination and thereby interferes with light detection near the absolute threshold. Light detection originating from conventional photoreceptors is modulated by melanopsin-based computation presumably estimating a baseline noise level.

Structure and dynamics of cholesterol-mediated aquaporin-0 arrays and implications for lipid rafts.

Aquaporin-0 (AQP0) tetramers form square arrays in lens membranes through a yet unknown mechanism, but lens membranes are enriched in sphingomyelin and cholesterol. Here, we determined electron crystallographic structures of AQP0 in sphingomyelin/cholesterol membranes and performed molecular dynamics (MD) simulations to establish that the observed cholesterol positions represent those seen around an isolated AQP0 tetramer and that the AQP0 tetramer largely defines the location and orientation of most of its associated cholesterol molecules. At a high concentration, cholesterol increases the hydrophobic thickness of the annular lipid shell around AQP0 tetramers, which may thus cluster to mitigate the resulting hydrophobic mismatch. Moreover, neighboring AQP0 tetramers sandwich a cholesterol deep in the center of the membrane. MD simulations show that the association of two AQP0 tetramers is necessary to maintain the deep cholesterol in its position and that the deep cholesterol increases the force required to laterally detach two AQP0 tetramers, not only due to protein-protein contacts but also due to increased lipid-protein complementarity. Since each tetramer interacts with four such 'glue' cholesterols, avidity effects may stabilize larger arrays. The principles proposed to drive AQP0 array formation could also underlie protein clustering in lipid rafts.

Quantum Effects Explain the Twist Angle in the Helical Structure of DNA.

Why are DNA bases stacked in a double helix structure? We combined three theoretical approaches to demonstrate how one core concept derived from quantum mechanics (Pauli repulsion) annihilates the contribution of dispersion to the π-π stacking. The helical architecture is governed by a combination of exchange and electrostatic forces, a result that is interpreted from both a computational and a biological perspective.

Self-assembly of sustainable plant protein protofilaments into a hydrogel for ultra-low friction across length scales.

Designing plant protein-based aqueous lubricants can be of great potential to achieve sustainability objectives by capitalising on inherent functional groups without using synthetic chemicals; however, such a concept remains in its infancy. Here, we engineer a class of self-assembled sustainable materials by using plant-based protofilaments and their assembly within a biopolymeric hydrogel giving rise to a distinct patchy architecture. By leveraging physical interactions, this material offers superlubricity with friction coefficients of 0.004-to-0.00007 achieved under moderate-to-high (102-to-103 kPa) contact pressures. Multiscale experimental measurements combined with molecular dynamics simulations reveal an intriguing synergistic mechanism behind such ultra-low friction - where the uncoated areas of the protofilaments glue to the surface by hydrophobic interactions, whilst the hydrogel offers the hydration lubrication. The current approach establishes a robust platform towards unlocking an untapped potential of using plant protein-based building blocks across diverse applications where achieving superlubricity and environmental sustainability are key performance indicators.

Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE.

Small-molecule drug design hinges on obtaining co-crystallized ligand-protein structures. Despite AlphaFold2's strides in protein native structure prediction, its focus on apo structures overlooks ligands and associated holo structures. Moreover, designing selective drugs often benefits from the targeting of diverse metastable conformations. Therefore, direct application of AlphaFold2 models in virtual screening and drug discovery remains tentative. Here, we demonstrate an AlphaFold2-based framework combined with all-atom enhanced sampling molecular dynamics and Induced Fit docking, named AF2RAVE-Glide, to conduct computational model-based small-molecule binding of metastable protein kinase conformations, initiated from protein sequences. We demonstrate the AF2RAVE-Glide workflow on three different mammalian protein kinases and their type I and II inhibitors, with special emphasis on binding of known type II kinase inhibitors which target the metastable classical DFG-out state. These states are not easy to sample from AlphaFold2. Here, we demonstrate how with AF2RAVE these metastable conformations can be sampled for different kinases with high enough accuracy to enable subsequent docking of known type II kinase inhibitors with more than 50% success rates across docking calculations. We believe the protocol should be deployable for other kinases and more proteins generally.

Answering open questions in biology using spatial genomics and structured methods.

Genomics methods have uncovered patterns in a range of biological systems, but obscure important aspects of cell behavior: the shapes, relative locations, movement, and interactions of cells in space. Spatial technologies that collect genomic or epigenomic data while preserving spatial information have begun to overcome these limitations. These new data promise a deeper understanding of the factors that affect cellular behavior, and in particular the ability to directly test existing theories about cell state and variation in the context of morphology, location, motility, and signaling that could not be tested before. Rapid advancements in resolution, ease-of-use, and scale of spatial genomics technologies to address these questions also require an updated toolkit of statistical methods with which to interrogate these data. We present a framework to respond to this new avenue of research: four open biological questions that can now be answered using spatial genomics data paired with methods for analysis. We outline spatial data modalities for each open question that may yield specific insights, discuss how conflicting theories may be tested by comparing the data to conceptual models of biological behavior, and highlight statistical and machine learning-based tools that may prove particularly helpful to recover biological understanding.

Non-local interaction in discrete Ricci curvature-induced biological aggregation.

We investigate the collective dynamics of multi-agent systems in two- and three-dimensional environments generated by minimizing discrete Ricci curvature with local and non-local interaction neighbourhoods. We find that even a single effective topological neighbour suffices for significant order in a system with non-local topological interactions. We also explore topological information flow patterns and clustering dynamics using Hodge spectral entropy and mean Forman-Ricci curvature.

Conserved regulatory motifs in the juxtamembrane domain and kinase N-lobe revealed through deep mutational scanning of the MET receptor tyrosine kinase domain.

MET is a receptor tyrosine kinase (RTK) responsible for initiating signaling pathways involved in development and wound repair. MET activation relies on ligand binding to the extracellular receptor, which prompts dimerization, intracellular phosphorylation, and recruitment of associated signaling proteins. Mutations, which are predominantly observed clinically in the intracellular juxtamembrane and kinase domains, can disrupt typical MET regulatory mechanisms. Understanding how juxtamembrane variants, such as exon 14 skipping (METΔEx14), and rare kinase domain mutations can increase signaling, often leading to cancer, remains a challenge. Here, we perform a parallel deep mutational scan (DMS) of the MET intracellular kinase domain in two fusion protein backgrounds: wild-type and METΔEx14. Our comparative approach has revealed a critical hydrophobic interaction between a juxtamembrane segment and the kinase ⍺C-helix, pointing to potential differences in regulatory mechanisms between MET and other RTKs. Additionally, we have uncovered a ß5 motif that acts as a structural pivot for the kinase domain in MET and other TAM family of kinases. We also describe a number of previously unknown activating mutations, aiding the effort to annotate driver, passenger, and drug resistance mutations in the MET kinase domain.

Additional feedforward mechanism of Parkin activation via binding of phospho-UBL and RING0 in trans.

Loss-of-function Parkin mutations lead to early-onset of Parkinson's disease. Parkin is an auto-inhibited ubiquitin E3 ligase activated by dual phosphorylation of its ubiquitin-like (Ubl) domain and ubiquitin by the PINK1 kinase. Herein, we demonstrate a competitive binding of the phospho-Ubl and RING2 domains towards the RING0 domain, which regulates Parkin activity. We show that phosphorylated Parkin can complex with native Parkin, leading to the activation of autoinhibited native Parkin in trans. Furthermore, we show that the activator element (ACT) of Parkin is required to maintain the enzyme kinetics, and the removal of ACT slows the enzyme catalysis. We also demonstrate that ACT can activate Parkin in trans but less efficiently than when present in the cis molecule. Furthermore, the crystal structure reveals a donor ubiquitin binding pocket in the linker connecting REP and RING2, which plays a crucial role in Parkin activity.

Revealing a hidden conducting state by manipulating the intracellular domains in KV10.1 exposes the coupling between two gating mechanisms.

The KCNH family of potassium channels serves relevant physiological functions in both excitable and non-excitable cells, reflected in the massive consequences of mutations or pharmacological manipulation of their function. This group of channels shares structural homology with other voltage-gated K+ channels, but the mechanisms of gating in this family show significant differences with respect to the canonical electromechanical coupling in these molecules. In particular, the large intracellular domains of KCNH channels play a crucial role in gating that is still only partly understood. Using KCNH1(KV10.1) as a model, we have characterized the behavior of a series of modified channels that could not be explained by the current models. With electrophysiological and biochemical methods combined with mathematical modeling, we show that the uncovering of an open state can explain the behavior of the mutants. This open state, which is not detectable in wild-type channels, appears to lack the rapid flicker block of the conventional open state. Because it is accessed from deep closed states, it elucidates intermediate gating events well ahead of channel opening in the wild type. This allowed us to study gating steps prior to opening, which, for example, explain the mechanism of gating inhibition by Ca2+-Calmodulin and generate a model that describes the characteristic features of KCNH channels gating.

The Reduction of Cervical Hyperlordosis and Resolution of Craniocervical Symptoms in an Adolescent Female: A Chiropractic Biophysics Case Report With Long-Term Follow-Up.

Cervical hyperlordosis is a rare condition in the pediatric population. We present a unique case of the application of Chiropractic Biophysics® (CBP®) technique protocols to reduce a hyperlordotic cervical spine corresponding with many craniocervical symptoms, including chronic migraines and neck pain. A 15-year-old female presented with chronic headaches, neck pain, and neck stiffness among other complaints following a martial arts sprain injury several months prior. There were many positive orthopedic tests and limited range of motion. Radiographs revealed a cervical hyperlordosis and a right lateral head translation. CBP® treatment was given and involved cervical distraction traction as well as corrective exercises twice a week for 12 weeks, and then monthly for one year with a complementary home program. After 12 weeks, there was a full recovery from migraines and neck pain correlating with an 8° reduction in lordosis and correction of head translation. At 15 months, the patient remained well and achieved a 13° total reduction in the neck curve. This is the first case documenting the successful application of CBP® methods to reduce cervical spine hyperlordosis in peer-reviewed literature. We propose too much curve may be as detrimental as too little curve in the cervical spine with respect to causing adverse stresses and strains in the surrounding soft tissues leading to pathological processes and nociceptive tendencies.

Resolution of Chronic Migraine Headaches and Improvement in Cervical Spine Kyphosis Following Chiropractic BioPhysics® (CBP®) Treatment: A Case Report With a Seven-Month Follow-Up.

We present a chronic migraine (CM) patient demonstrating significant improvement in subjective and objective reported outcome measures with deeper cervical lordosis parameters and reduced forward head posture on radiographs. A 29-year-old male suffered from CM reporting significant pain and disability with aural, sensory, and motor disturbances during the migraine headaches. Aura with visual disturbances, abnormal facial and extremity sensation, sporadic motor weakness, and other signs of CM were found in the patient's history since age 10. The patient reported previous physical therapy, manual chiropractic, and over-the-counter medications. Migraine-specific prescriptions without long-term reduction in pain and disability were reported. The pain and suffering had been reported to be worsening, and he sought Chiropractic BioPhysics® (CBP®) spine and postural rehabilitation protocols. These protocols were used to increase cervical lordosis, reduce coronal imbalances, increase mobility, and create better posture. These protocols include specific prescriptions based on radiography for postural exercises, postural mirror image® (MI®)traction, and specific spinal manipulative therapy (SMT) focused on posture. All outcome measures improved with the resolution of all initial symptoms of CM. There was a 16° improvement in cervical lordosis, a 30% decrease in headache disability, and additional improvements. These improvements were maintained at a seven-month follow-up during which the patient received infrequent maintenance treatments. This successful treatment of a patient with CM with long-term follow-up adds to evidence that CBP® spinal structural rehabilitation may prove effective and serve as a possible tool for clinicians, physicians, and therapists to treat CM.

Nature heals: An informational entropy account of self-organization and change in field psychotherapy.

This paper reviews biophysical models of psychotherapeutic change based on synergetics and the free energy principle. These models suggest that introducing sensory surprise into the patient-therapist system can lead to self-organization and the formation of new attractor states, disrupting entrenched patterns of thoughts, emotions, and behaviours. We propose that the therapist can facilitate this process by cultivating epistemic trust and modulating embodied attention to allow surprising affective states to enter shared awareness. Transient increases in free energy enable the update of generative models, expanding the range of experiences available within the patient-therapist phenomenal field. We hypothesize that patterns of disorganization at behavioural and physiological levels, indexed by increased entropy, complexity, and lower determinism, are key markers and predictors of psychotherapeutic gains. Future research should investigate how the therapist's openness to novelty shapes therapeutic outcomes.

Cryo-EM structure of the CBC-ALYREF complex.

In eukaryotes, RNAs transcribed by RNA Pol II are modified at the 5' end with a 7-methylguanosine (m7G) cap, which is recognized by the nuclear cap binding complex (CBC). The CBC plays multiple important roles in mRNA metabolism, including transcription, splicing, polyadenylation, and export. It promotes mRNA export through direct interaction with a key mRNA export factor, ALYREF, which in turn links the TRanscription and EXport (TREX) complex to the 5' end of mRNA. However, the molecular mechanism for CBC-mediated recruitment of the mRNA export machinery is not well understood. Here, we present the first structure of the CBC in complex with an mRNA export factor, ALYREF. The cryo-EM structure of CBC-ALYREF reveals that the RRM domain of ALYREF makes direct contact with both the NCBP1 and NCBP2 subunits of the CBC. Comparing CBC-ALYREF with other cellular complexes containing CBC and/or ALYREF components provides insights into the coordinated events during mRNA transcription, splicing, and export.

A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features.

Cellular phenotypic heterogeneity is an important hallmark of many biological processes and understanding its origins remains a substantial challenge. This heterogeneity often reflects variations in the chromatin structure, influenced by factors such as viral infections and cancer, which dramatically reshape the cellular landscape. To address the challenge of identifying distinct cell states, we developed artificial intelligence of the nucleus (AINU), a deep learning method that can identify specific nuclear signatures at the nanoscale resolution. AINU can distinguish different cell states based on the spatial arrangement of core histone H3, RNA polymerase II or DNA from super-resolution microscopy images. With only a small number of images as the training data, AINU correctly identifies human somatic cells, human-induced pluripotent stem cells, very early stage infected cells transduced with DNA herpes simplex virus type 1 and even cancer cells after appropriate retraining. Finally, using AI interpretability methods, we find that the RNA polymerase II localizations in the nucleoli aid in distinguishing human-induced pluripotent stem cells from their somatic cells. Overall, AINU coupled with super-resolution microscopy of nuclear structures provides a robust tool for the precise detection of cellular heterogeneity, with considerable potential for advancing diagnostics and therapies in regenerative medicine, virology and cancer biology.

Exploring protein structural ensembles: Integration of sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling methods.

Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure-function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.

PPI-hotspotID for detecting protein-protein interaction hot spots from the free protein structure.

Experimental detection of residues critical for protein-protein interactions (PPI) is a time-consuming, costly, and labor-intensive process. Hence, high-throughput PPI-hot spot prediction methods have been developed, but they have been validated using relatively small datasets, which may compromise their predictive reliability. Here, we introduce PPI-hotspotID, a novel method for identifying PPI-hot spots using the free protein structure, and validated it on the largest collection of experimentally confirmed PPI-hot spots to date. We explored the possibility of detecting PPI-hot spots using (i) FTMap in the PPI mode, which identifies hot spots on protein-protein interfaces from the free protein structure, and (ii) the interface residues predicted by AlphaFold-Multimer. PPI-hotspotID yielded better performance than FTMap and SPOTONE, a webserver for predicting PPI-hot spots given the protein sequence. When combined with the AlphaFold-Multimer-predicted interface residues, PPI-hotspotID yielded better performance than either method alone. Furthermore, we experimentally verified several PPI-hotspotID-predicted PPI-hot spots of eukaryotic elongation factor 2. Notably, PPI-hotspotID can reveal PPI-hot spots not obvious from complex structures, including those in indirect contact with binding partners. PPI-hotspotID serves as a valuable tool for understanding PPI mechanisms and aiding drug design. It is available as a web server (https://ppihotspotid.limlab.dnsalias.org/) and open-source code (https://github.com/wrigjz/ppihotspotid/).

The Arthropoda-specific Tramtrack group BTB protein domains use previously unknown interface to form hexamers.

BTB (bric-a-brack, Tramtrack, and broad complex) is a diverse group of protein-protein interaction domains found within metazoan proteins. Transcription factors contain a dimerizing BTB subtype with a characteristic N-terminal extension. The Tramtrack group (TTK) is a distinct type of BTB domain, which can multimerize. Single-particle cryo-EM microscopy revealed that the TTK-type BTB domains assemble into a hexameric structure consisting of three canonical BTB dimers connected through a previously uncharacterized interface. We demonstrated that the TTK-type BTB domains are found only in Arthropods and have undergone lineage-specific expansion in modern insects. The Drosophila genome encodes 24 transcription factors with TTK-type BTB domains, whereas only four have non-TTK-type BTB domains. Yeast two-hybrid analysis revealed that the TTK-type BTB domains have an unusually broad potential for heteromeric associations presumably through a dimer-dimer interaction interface. Thus, the TTK-type BTB domains are a structurally and functionally distinct group of protein domains specific to Arthropodan transcription factors.