RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a 'living data resource.' Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

Criterion-free measurement of motion transparency perception at different speeds.

Transparency perception often occurs when objects within the visual scene partially occlude each other or move at the same time, at different velocities across the same spatial region. Although transparent motion perception has been extensively studied, we still do not understand how the distribution of velocities within a visual scene contribute to transparent perception. Here we use a novel psychophysical procedure to characterize the distribution of velocities in a scene that give rise to transparent motion perception. To prevent participants from adopting a subjective decision criterion when discriminating transparent motion, we used an "odd-one-out," three-alternative forced-choice procedure. Two intervals contained the standard-a random-dot-kinematogram with dot speeds or directions sampled from a uniform distribution. The other interval contained the comparison-speeds or directions sampled from a distribution with the same range as the standard, but with a notch of different widths removed. Our results suggest that transparent motion perception is driven primarily by relatively slow speeds, and does not emerge when only very fast speeds are present within a visual scene. Transparent perception of moving surfaces is modulated by stimulus-based characteristics, such as the separation between the means of the overlapping distributions or the range of speeds presented within an image. Our work illustrates the utility of using objective, forced-choice methods to reveal the mechanisms underlying motion transparency perception.

Position matching between the visual fields in strabismus.

The misalignment of visual input in strabismus disrupts positional judgments. We measured positional accuracy in the extrafoveal visual field (1°-7° eccentricity) of a large group of strabismic subjects and a normal control group to identify positional distortions associated with the direction of strabismus. Subjects performed a free localization task in which targets were matched in opposite hemifields whilst fixating on a central cross. The constant horizontal error of each response was taken as a measure of accuracy, in addition to radial and angular error. In monocular conditions, all stimuli were viewed by one eye; thus, the error reflected spatial bias. In dichoptic conditions, the targets were seen by separate eyes; thus, the error reflected the perceived stimulus shift produced by ocular misalignment in addition to spatial bias. In both viewing conditions, both groups showed reliable over- and underestimations of visual field position, here termed a compression of response coordinates. The normal group showed compression in the left periphery, regardless of eye of stimulation. The strabismic group showed a visual field-specific compression that was clearly associated with direction of strabismus. The variation in perceived shift of strabismic subjects was largely accounted for by the biases present in monocular viewing, suggesting that binocular correspondence was uniform in the tested region. The asymmetric strabismic compression could not be reproduced in normal subjects through prism viewing, and its presence across viewing conditions suggests a hemifield-specific change in spatial coding induced by long-standing ocular misalignment.

Design of a single-chain polypeptide tetrahedron assembled from coiled-coil segments.

Protein structures evolved through a complex interplay of cooperative interactions, and it is still very challenging to design new protein folds de novo. Here we present a strategy to design self-assembling polypeptide nanostructured polyhedra based on modularization using orthogonal dimerizing segments. We designed and experimentally demonstrated the formation of the tetrahedron that self-assembles from a single polypeptide chain comprising 12 concatenated coiled coil-forming segments separated by flexible peptide hinges. The path of the polypeptide chain is guided by a defined order of segments that traverse each of the six edges of the tetrahedron exactly twice, forming coiled-coil dimers with their corresponding partners. The coincidence of the polypeptide termini in the same vertex is demonstrated by reconstituting a split fluorescent protein in the polypeptide with the correct tetrahedral topology. Polypeptides with a deleted or scrambled segment order fail to self-assemble correctly. This design platform provides a foundation for constructing new topological polypeptide folds based on the set of orthogonal interacting polypeptide segments.

Putting the pieces together: integrative modeling platform software for structure determination of macromolecular assemblies.

A set of software tools for building and distributing models of macromolecular assemblies uses an integrative structure modeling approach, which casts the building of models as a computational optimization problem where information is encoded into a scoring function used to evaluate candidate models.

The effect of normal aging and age-related macular degeneration on perceptual learning.

We investigated whether perceptual learning could be used to improve peripheral word identification speed. The relationship between the magnitude of learning and age was established in normal participants to determine whether perceptual learning effects are age invariant. We then investigated whether training could lead to improvements in patients with age-related macular degeneration (AMD). Twenty-eight participants with normal vision and five participants with AMD trained on a word identification task. They were required to identify three-letter words, presented 10° from fixation. To standardize crowding across each of the letters that made up the word, words were flanked laterally by randomly chosen letters. Word identification performance was measured psychophysically using a staircase procedure. Significant improvements in peripheral word identification speed were demonstrated following training (71% ± 18%). Initial task performance was correlated with age, with older participants having poorer performance. However, older adults learned more rapidly such that, following training, they reached the same level of performance as their younger counterparts. As a function of number of trials completed, patients with AMD learned at an equivalent rate as age-matched participants with normal vision. Improvements in word identification speed were maintained at least 6 months after training. We have demonstrated that temporal aspects of word recognition can be improved in peripheral vision with training across a range of ages and these learned improvements are relatively enduring. However, training targeted at other bottlenecks to peripheral reading ability, such as visual crowding, may need to be incorporated to optimize this approach.

Estimation of cortical magnification from positional error in normally sighted and amblyopic subjects.

We describe a method for deriving the linear cortical magnification factor from positional error across the visual field. We compared magnification obtained from this method between normally sighted individuals and amblyopic individuals, who receive atypical visual input during development. The cortical magnification factor was derived for each subject from positional error at 32 locations in the visual field, using an established model of conformal mapping between retinal and cortical coordinates. Magnification of the normally sighted group matched estimates from previous physiological and neuroimaging studies in humans, confirming the validity of the approach. The estimate of magnification for the amblyopic group was significantly lower than the normal group: by 4.4 mm deg(-1) at 1° eccentricity, assuming a constant scaling factor for both groups. These estimates, if correct, suggest a role for early visual experience in establishing retinotopic mapping in cortex. We discuss the implications of altered cortical magnification for cortical size, and consider other neural changes that may account for the amblyopic results.

SAXS Merge: an automated statistical method to merge SAXS profiles using Gaussian processes.

Small-angle X-ray scattering (SAXS) is an experimental technique that allows structural information on biomolecules in solution to be gathered. High-quality SAXS profiles have typically been obtained by manual merging of scattering profiles from different concentrations and exposure times. This procedure is very subjective and results vary from user to user. Up to now, no robust automatic procedure has been published to perform this step, preventing the application of SAXS to high-throughput projects. Here, SAXS Merge, a fully automated statistical method for merging SAXS profiles using Gaussian processes, is presented. This method requires only the buffer-subtracted SAXS profiles in a specific order. At the heart of its formulation is non-linear interpolation using Gaussian processes, which provides a statement of the problem that accounts for correlation in the data.

Optimized atomic statistical potentials: assessment of protein interfaces and loops.

MOTIVATION: Statistical potentials have been widely used for modeling whole proteins and their parts (e.g. sidechains and loops) as well as interactions between proteins, nucleic acids and small molecules. Here, we formulate the statistical potentials entirely within a statistical framework, avoiding questionable statistical mechanical assumptions and approximations, including a definition of the reference state. RESULTS: We derive a general Bayesian framework for inferring statistically optimized atomic potentials (SOAP) in which the reference state is replaced with data-driven 'recovery' functions. Moreover, we restrain the relative orientation between two covalent bonds instead of a simple distance between two atoms, in an effort to capture orientation-dependent interactions such as hydrogen bonds. To demonstrate this general approach, we computed statistical potentials for protein-protein docking (SOAP-PP) and loop modeling (SOAP-Loop). For docking, a near-native model is within the top 10 scoring models in 40% of the PatchDock benchmark cases, compared with 23 and 27% for the state-of-the-art ZDOCK and FireDock scoring functions, respectively. Similarly, for modeling 12-residue loops in the PLOP benchmark, the average main-chain root mean square deviation of the best scored conformations by SOAP-Loop is 1.5 Å, close to the average root mean square deviation of the best sampled conformations (1.2 Å) and significantly better than that selected by Rosetta (2.1 Å), DFIRE (2.3 Å), DOPE (2.5 Å) and PLOP scoring functions (3.0 Å). Our Bayesian framework may also result in more accurate statistical potentials for additional modeling applications, thus affording better leverage of the experimentally determined protein structures. AVAILABILITY AND IMPLEMENTATION: SOAP-PP and SOAP-Loop are available as part of MODELLER (http://salilab.org/modeller).

Characterizing the effects of multidirectional motion adaptation.

Recent sensory experience can alter our perception and change the response characteristics of sensory neurons. These effects of sensory adaptation are a ubiquitous property of perceptual systems and are believed to be of fundamental importance to sensory coding. Yet we know little about how adaptation to stimulus ensembles affects our perception of the environment as most psychophysical experiments employ adaptation protocols that focus on prolonged exposure to a single visual attribute. Here, we investigate how concurrent adaptation to multiple directions of motion affects perception of subsequently presented motion using the direction aftereffect. In different conditions, observers adapted to a stimulus ensemble comprised of dot directions sampled from different distributions or to bidirectional motion. Increasing the variance of normally distributed directions reduced the magnitude of the peak direction aftereffect and broadened its tuning profile. Sampling of asymmetric Gaussian and uniform distributions resulted in shifts of direction aftereffect tuning profiles consistent with changes in the perceived global direction of the adapting stimulus. Adding dots in a direction opposite or orthogonal to a unidirectional adapting stimulus led to a pronounced reduction in the direction aftereffect. A simple population-coding model, in which adaptation selectively alters the responsivity of direction-selective neurons, can accommodate the effects of multidirectional adaptation on the perceived direction of motion.

Perceptual learning reconfigures the effects of visual adaptation.

Our sensory experiences over a range of different timescales shape our perception of the environment. Two particularly striking short-term forms of plasticity with manifestly different time courses and perceptual consequences are those caused by visual adaptation and perceptual learning. Although conventionally treated as distinct forms of experience-dependent plasticity, their neural mechanisms and perceptual consequences have become increasingly blurred, raising the possibility that they might interact. To optimize our chances of finding a functionally meaningful interaction between learning and adaptation, we examined in humans the perceptual consequences of learning a fine discrimination task while adapting the neurons that carry most information for performing this task. Learning improved discriminative accuracy to a level that ultimately surpassed that in an unadapted state. This remarkable improvement came at a price: adapting directions that before learning had little effect elevated discrimination thresholds afterward. The improvements in discriminative accuracy grew quickly and surpassed unadapted levels within the first few training sessions, whereas the deterioration in discriminative accuracy had a different time course. This learned reconfiguration of adapted discriminative accuracy occurred without a concomitant change to the characteristic perceptual biases induced by adaptation, suggesting that the system was still in an adapted state. Our results point to a functionally meaningful push-pull interaction between learning and adaptation in which a gain in sensitivity in one adapted state is balanced by a loss of sensitivity in other adapted states.

Perceptual learning reduces crowding in amblyopia and in the normal periphery.

Amblyopia is a developmental visual disorder of cortical origin, characterized by crowding and poor acuity in central vision of the affected eye. Crowding refers to the adverse effects of surrounding items on object identification, common only in normal peripheral but not central vision. We trained a group of adult human amblyopes on a crowded letter identification task to assess whether the crowding problem can be ameliorated. Letter size was fixed well above the acuity limit, and letter spacing was varied to obtain spacing thresholds for central target identification. Normally sighted observers practiced the same task in their lower peripheral visual field. Independent measures of acuity were taken in flanked and unflanked conditions before and after training to measure crowding ratios at three fixed letter separations. Practice improved the letter spacing thresholds of both groups on the training task, and crowding ratios were reduced after posttest. The reductions in crowding in amblyopes were associated with improvements in standard measures of visual acuity. Thus, perceptual learning reduced the deleterious effects of crowding in amblyopia and in the normal periphery. The results support the effectiveness of plasticity-based approaches for improving vision in adult amblyopes and suggest experience-dependent effects on the cortical substrates of crowding.

MultiFit: a web server for fitting multiple protein structures into their electron microscopy density map.

Advances in electron microscopy (EM) allow for structure determination of large biological assemblies at increasingly higher resolutions. A key step in this process is fitting multiple component structures into an EM-derived density map of their assembly. Here, we describe a web server for this task. The server takes as input a set of protein structures in the PDB format and an EM density map in the MRC format. The output is an ensemble of models ranked by their quality of fit to the density map. The models can be viewed online or downloaded from the website. The service is available at; http://salilab.org/multifit/ and http://bioinfo3d.cs.tau.ac.il/.

Neural computations governing spatiotemporal pooling of visual motion signals in humans.

The brain estimates visual motion by decoding the responses of populations of neurons. Extracting unbiased motion estimates from early visual cortical neurons is challenging because each neuron contributes an ambiguous (local) representation of the visual environment and inherently variable neural response. To mitigate these sources of noise, the brain can pool across large populations of neurons, pool the response of each neuron over time, or a combination of the two. Recent psychophysical and physiological work points to a flexible motion pooling system that arrives at different computational solutions over time and for different stimuli. Here we ask whether a single, likelihood-based computation can accommodate the flexible nature of spatiotemporal motion pooling in humans. We examined the contribution of different computations to human observers' performance on two global visual motion discriminations tasks, one requiring the combination of motion directions over time and another requiring their combination in different relative proportions over space and time. Observers' perceived direction of global motion was accurately predicted by a vector average readout of direction signals accumulated over time and a maximum likelihood readout of direction signals combined over space, consistent with the notion of a flexible motion pooling system that uses different computations over space and time. Additional simulations of observers' performance with a population decoding model revealed a more parsimonious solution: flexible spatiotemporal pooling could be accommodated by a single computation that optimally pools motion signals across a population of neurons that accumulate local motion signals on their receptive fields at a fixed rate over time.

UCSF Chimera, MODELLER, and IMP: an integrated modeling system.

Structural modeling of macromolecular complexes greatly benefits from interactive visualization capabilities. Here we present the integration of several modeling tools into UCSF Chimera. These include comparative modeling by MODELLER, simultaneous fitting of multiple components into electron microscopy density maps by IMP MultiFit, computing of small-angle X-ray scattering profiles and fitting of the corresponding experimental profile by IMP FoXS, and assessment of amino acid sidechain conformations based on rotamer probabilities and local interactions by Chimera.

Integrative structure modeling of macromolecular assemblies from proteomics data.

Proteomics techniques have been used to generate comprehensive lists of protein interactions in a number of species. However, relatively little is known about how these interactions result in functional multiprotein complexes. This gap can be bridged by combining data from proteomics experiments with data from established structure determination techniques. Correspondingly, integrative computational methods are being developed to provide descriptions of protein complexes at varying levels of accuracy and resolution, ranging from complex compositions to detailed atomic structures.

Transfer of perceptual learning between different visual tasks.

Practice in most sensory tasks substantially improves perceptual performance. A hallmark of this 'perceptual learning' is its specificity for the basic attributes of the trained stimulus and task. Recent studies have challenged the specificity of learned improvements, although transfer between substantially different tasks has yet to be demonstrated. Here, we measure the degree of transfer between three distinct perceptual tasks. Participants trained on an orientation discrimination, a curvature discrimination, or a 'global form' task, all using stimuli comprised of multiple oriented elements. Before and after training they were tested on all three and a contrast discrimination control task. A clear transfer of learning was observed, in a pattern predicted by the relative complexity of the stimuli in the training and test tasks. Our results suggest that sensory improvements derived from perceptual learning can transfer between very different visual tasks.

MODBASE, a database of annotated comparative protein structure models and associated resources.

MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by MODPIPE, an automated modeling pipeline that relies primarily on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE currently contains 5,152,695 reliable models for domains in 1,593,209 unique protein sequences; only models based on statistically significant alignments and/or models assessed to have the correct fold are included. MODBASE also allows users to calculate comparative models on demand, through an interface to the MODWEB modeling server (http://salilab.org/modweb). Other resources integrated with MODBASE include databases of multiple protein structure alignments (DBAli), structurally defined ligand binding sites (LIGBASE), predicted ligand binding sites (AnnoLyze), structurally defined binary domain interfaces (PIBASE) and annotated single nucleotide polymorphisms and somatic mutations found in human proteins (LS-SNP, LS-Mut). MODBASE models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/).

Can perceptual learning be used to treat amblyopia beyond the critical period of visual development?

BACKGROUND: Amblyopia presents early in childhood and affects approximately 3% of western populations. The monocular visual acuity loss is conventionally treated during the 'critical periods' of visual development by occluding or penalising the fellow eye to encourage use of the amblyopic eye. Despite the measurable success of this approach in many children, substantial numbers of people still suffer with amblyopia later in life because either they were never diagnosed in childhood, did not respond to the original treatment, the amblyopia was only partially remediated, or their acuity loss returned after cessation of treatment. PURPOSE: In this review, we consider whether the visual deficits of this largely overlooked amblyopic group are amenable to conventional and innovative therapeutic interventions later in life, well beyond the age at which treatment is thought to be effective. RECENT FINDINGS: There is a considerable body of evidence that residual plasticity is present in the adult visual brain and this can be harnessed to improve function in adults with amblyopia. Perceptual training protocols have been developed to optimise visual gains in this clinical population. Results thus far are extremely encouraging; marked visual improvements have been demonstrated, the perceptual benefits transfer to new visual tasks and appear to be relatively enduring. The essential ingredients of perceptual training protocols are being incorporated into video game formats, facilitating home-based interventions. SUMMARY: Many studies support perceptual training as a tool for improving vision in amblyopes beyond the critical period. Should this novel form of treatment stand up to the scrutiny of a randomised controlled trial, clinicians may need to re-evaluate their therapeutic approach to adults with amblyopia.

Linking Multi-Modal MRI to Clinical Measures of Visual Field Loss After Stroke.

Loss of vision across large parts of the visual field is a common and devastating complication of cerebral strokes. In the clinic, this loss is quantified by measuring the sensitivity threshold across the field of vision using static perimetry. These methods rely on the ability of the patient to report the presence of lights in particular locations. While perimetry provides important information about the intactness of the visual field, the approach has some shortcomings. For example, it cannot distinguish where in the visual pathway the key processing deficit is located. In contrast, brain imaging can provide important information about anatomy, connectivity, and function of the visual pathway following stroke. In particular, functional magnetic resonance imaging (fMRI) and analysis of population receptive fields (pRF) can reveal mismatches between clinical perimetry and maps of cortical areas that still respond to visual stimuli after stroke. Here, we demonstrate how information from different brain imaging modalities-visual field maps derived from fMRI, lesion definitions from anatomical scans, and white matter tracts from diffusion weighted MRI data-provides a more complete picture of vision loss. For any given location in the visual field, the combination of anatomical and functional information can help identify whether vision loss is due to absence of gray matter tissue or likely due to white matter disconnection from other cortical areas. We present a combined imaging acquisition and visual stimulus protocol, together with a description of the analysis methodology, and apply it to datasets from four stroke survivors with homonymous field loss (two with hemianopia, two with quadrantanopia). For researchers trying to understand recovery of vision after stroke and clinicians seeking to stratify patients into different treatment pathways, this approach combines multiple, convergent sources of data to characterize the extent of the stroke damage. We show that such an approach gives a more comprehensive measure of residual visual capacity-in two particular respects: which locations in the visual field should be targeted and what kind of visual attributes are most suited for rehabilitation.