The discovery of drug-like molecules that bind pockets in proteins that are not present in crystallographic structures yet exert allosteric control over activity has generated great interest in ...designing pharmaceuticals that exploit allosteric effects. However, there have only been a small number of successes, so the therapeutic potential of these pockets—called hidden allosteric sites—remains unclear. One challenge for assessing their utility is that rational drug design approaches require foreknowledge of the target site, but most hidden allosteric sites are only discovered when a small molecule is found to stabilize them. We present a means of decoupling the identification of hidden allosteric sites from the discovery of drugs that bind them by drawing on new developments in Markov state modeling that provide unprecedented access to microsecond- to millisecond-timescale fluctuations of a protein’s structure. Visualizing these fluctuations allows us to identify potential hidden allosteric sites, which we then test via thiol labeling experiments. Application of these methods reveals multiple hidden allosteric sites in an important antibiotic target—TEM-1 β-lactamase. This result supports the hypothesis that there are many as yet undiscovered hidden allosteric sites and suggests our methodology can identify such sites, providing a starting point for future drug design efforts. More generally, our results demonstrate the power of using Markov state models to guide experiments.
Significance Rational drug design efforts typically focus on identifying inhibitors that bind to protein active sites. Pockets that are not present in crystallographic structures yet can exert allosteric (i.e., long-range) control over distant active sites present an exciting alternative. However, identifying these hidden allosteric sites is extremely challenging because one usually has to simultaneously find a small molecule that binds to and stabilizes the open conformation of the pocket. Here, we present a means of combining advances in computer modeling—using Markov state models to capture long timescale dynamics—with biophysical experiments to identify hidden allosteric sites without requiring the simultaneous discovery of drug-like compounds that bind them. Using this technology, we discover multiple hidden allosteric sites in a single protein.
Computational imaging enables retrieval of the spatial information of an object with the use of single-pixel detectors. By projecting a series of known random patterns and measuring the backscattered ...intensity, it is possible to reconstruct a two-dimensional (2D) image. We used several single-pixel detectors in different locations to capture the 3D form of an object. From each detector we derived a 2D image that appeared to be illuminated from a different direction, even though only a single digital projector was used for illumination. From the shading of the images, the surface gradients could be derived and the 3D object reconstructed. We compare our result to that obtained from a stereophotogrammetric system using multiple cameras. Our simplified approach to 3D imaging can readily be extended to nonvisible wavebands.
SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression and replication that depend on the structure and dynamics of its constituent proteins. Many protein structures ...have been solved, but far less is known about their relevant conformational changes. To address this challenge, over a million citizen scientists banded together through the Folding@home distributed computing project to create the first exascale computer and simulate 0.1 seconds of the viral proteome. Our adaptive sampling simulations predict dramatic opening of the apo spike complex, far beyond that seen experimentally, explaining and predicting the existence of 'cryptic' epitopes. Different spike variants modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also discover dramatic conformational changes across the proteome, which reveal over 50 'cryptic' pockets that expand targeting options for the design of antivirals. All data and models are freely available online, providing a quantitative structural atlas.
Metal hydride hydrogen compressors: A review Lototskyy, M.V.; Yartys, V.A.; Pollet, B.G. ...
International journal of hydrogen energy,
04/2014, Letnik:
39, Številka:
11
Journal Article
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Metal hydride (MH) thermal sorption compression is an efficient and reliable method allowing a conversion of energy from heat into a compressed hydrogen gas. The most important component of such a ...thermal engine – the metal hydride material itself – should possess several material features in order to achieve an efficient performance in the hydrogen compression. Apart from the hydrogen storage characteristics important for every solid H storage material (e.g. gravimetric and volumetric efficiency of H storage, hydrogen sorption kinetics and effective thermal conductivity), the thermodynamics of the metal–hydrogen systems is of primary importance resulting in a temperature dependence of the absorption/desorption pressures). Several specific features should be optimised to govern the performance of the MH-compressors including synchronisation of the pressure plateaus for multi-stage compressors, reduction of slope of the isotherms and hysteresis, increase of cycling stability and life time, together with challenges in system design associated with volume expansion of the metal matrix during the hydrogenation.
The present review summarises numerous papers and patent literature dealing with MH hydrogen compression technology. The review considers (a) fundamental aspects of materials development with a focus on structure and phase equilibria in the metal–hydrogen systems suitable for the hydrogen compression; and (b) applied aspects, including their consideration from the applied thermodynamic viewpoint, system design features and performances of the metal hydride compressors and major applications.
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•Overview of metal hydride (MH) technology for thermally-driven hydrogen compression.•MH materials for H2 compression: structure, phase equilibria, kinetics, impurities, degradation.•MH compressors as heat engines.•Design features and performances of MH compressors.•Applications of MH compressors.
There is a long-standing debate about whether categories are represented by individual category members (exemplars) or by the central tendency abstracted from individual members (prototypes). ...Neuroimaging studies have shown neural evidence for either exemplar representations or prototype representations, but not both. Presently, we asked whether it is possible for multiple types of category representations to exist within a single task. We designed a categorization task to promote both exemplar and prototype representations and tracked their formation across learning. We found only prototype correlates during the final test. However, interim tests interspersed throughout learning showed prototype and exemplar representations across distinct brain regions that aligned with previous studies: prototypes in ventromedial prefrontal cortex and anterior hippocampus and exemplars in inferior frontal gyrus and lateral parietal cortex. These findings indicate that, under the right circumstances, individuals may form representations at multiple levels of specificity, potentially facilitating a broad range of future decisions.
Simulations can provide tremendous insight into the atomistic details of biological mechanisms, but micro- to millisecond timescales are historically only accessible on dedicated supercomputers. We ...demonstrate that cloud computing is a viable alternative that brings long-timescale processes within reach of a broader community. We used Google's Exacycle cloud-computing platform to simulate two milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β2AR. Markov state models aggregate independent simulations into a single statistical model that is validated by previous computational and experimental results. Moreover, our models provide an atomistic description of the activation of a G-protein-coupled receptor and reveal multiple activation pathways. Agonists and inverse agonists interact differentially with these pathways, with profound implications for drug design.
The immune checkpoint receptor PD-1 and its ligand, PD-L1, have emerged as key regulators of anti-tumor immunity in humans. Recently, we reported an ultra-high-affinity PD-1 mutant, termed ...high-affinity consensus (HAC) PD-1, which shows superior therapeutic efficacy in mice compared with antibodies. However, the molecular details underlying the action of this agent remain incompletely understood, and a molecular view of PD-1/PD-L1 interactions in general is only beginning to emerge. Here, we report the structure of HAC PD-1 in complex with PD-L1, showing that it binds PD-L1 using a unique set of polar interactions. Biophysical studies and long-timescale molecular dynamics experiments reveal the mechanisms by which ten point mutations confer a 35,000-fold enhancement in binding affinity, and offer atomic-scale views of the role of conformational dynamics in PD-1/PD-L1 interactions. Finally, we show that the HAC PD-1 exhibits pH-dependent affinity, with pseudo-irreversible binding in a low pH setting akin to the tumor microenvironment.
•Structure of engineered PD-1 receptor with ligand PD-L1 shows basis for high affinity•Polar interaction increases conformational stability of the complex•Mutant PD-1 binding affinity is strongly pH dependent•Binding is essentially irreversible in acidic conditions
Pascolutti et al. describe the biophysical basis for enhanced binding of a mutant PD-1 to its ligand PD-L1, regulators of anti-tumor immunity in humans. The authors also characterize wild-type and mutant PD-1 using long-timescale molecular dynamics. The mutant PD-1/PD-L1 interaction is enhanced in acidic pH, suggesting utility as a microenvironment-targeted therapeutic.
To date, the slowest-folding proteins folded ab initio by all-atom molecular dynamics simulations have had folding times in the range of nanoseconds to microseconds. We report simulations of several ...folding trajectories of NTL9(1-39), a protein which has a folding time of approximately 1.5 ms. Distributed molecular dynamics simulations in implicit solvent on GPU processors were used to generate ensembles of trajectories out to approximately 40 micros for several temperatures and starting states. At a temperature less than the melting point of the force field, we observe a small number of productive folding events, consistent with predictions from a model of parallel uncoupled two-state simulations. The posterior distribution of the folding rate predicted from the data agrees well with the experimental folding rate (approximately 640/s). Markov State Models (MSMs) built from the data show a gap in the implied time scales indicative of two-state folding and heterogeneous pathways connecting diffuse mesoscopic substates. Structural analysis of the 14 out of 2000 macrostates transited by the top 10 folding pathways reveals that native-like pairing between strands 1 and 2 only occurs for macrostates with p(fold) > 0.5, suggesting beta(12) hairpin formation may be rate-limiting. We believe that using simulation data such as these to seed adaptive resampling simulations will be a promising new method for achieving statistically converged descriptions of folding landscapes at longer time scales than ever before.
The aggregation of amyloid beta (Aβ) peptides plays an important role in the development of Alzheimer's disease. Despite extensive effort, it has been difficult to characterize the secondary and ...tertiary structure of the Aβ monomer, the starting point for aggregation, due to its hydrophobicity and high aggregation propensity. Here, we employ extensive molecular dynamics simulations with atomistic protein and water models to determine structural ensembles for Aβ42, Aβ40, and Aβ42-E22K (the Italian mutant) monomers in solution. Sampling of a total of >700 microseconds in all-atom detail with explicit solvent enables us to observe the effects of peptide length and a pathogenic mutation on the disordered Aβ monomer structural ensemble. Aβ42 and Aβ40 have crudely similar characteristics but reducing the peptide length from 42 to 40 residues reduces β-hairpin formation near the C-terminus. The pathogenic Italian E22K mutation induces helix formation in the region of residues 20–24. This structural alteration may increase helix-helix interactions between monomers, resulting in altered mechanism and kinetics of Aβ oligomerization.
Protein folded states are kinetic hubs Bowman, Gregory R; Pande, Vijay S
Proceedings of the National Academy of Sciences - PNAS,
06/2010, Letnik:
107, Številka:
24
Journal Article
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Understanding molecular kinetics, and particularly protein folding, is a classic grand challenge in molecular biophysics. Network models, such as Markov state models (MSMs), are one potential ...solution to this problem. MSMs have recently yielded quantitative agreement with experimentally derived structures and folding rates for specific systems, leaving them positioned to potentially provide a deeper understanding of molecular kinetics that can lead to experimentally testable hypotheses. Here we use existing MSMs for the villin headpiece and NTL9, which were constructed from atomistic simulations, to accomplish this goal. In addition, we provide simpler, humanly comprehensible networks that capture the essence of molecular kinetics and reproduce qualitative phenomena like the apparent two-state folding often seen in experiments. Together, these models show that protein dynamics are dominated by stochastic jumps between numerous metastable states and that proteins have heterogeneous unfolded states (many unfolded basins that interconvert more rapidly with the native state than with one another) yet often still appear two-state. Most importantly, we find that protein native states are hubs that can be reached quickly from any other state. However, metastability and a web of nonnative states slow the average folding rate. Experimental tests for these findings and their implications for other fields, like protein design, are also discussed.
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