High-throughput virtual search of small molecules for controlling the mechanical stability of human CD4.

Protein mechanical stability determines the function of a myriad of proteins, especially proteins from the extracellular matrix. Failure to maintain protein mechanical stability may result in diseases and disorders such as cancer, cardiomyopathies, or muscular dystrophy. Thus, developing mutation-free approaches to enhance and control the mechanical stability of proteins using pharmacology-based methods may have important implications in drug development and discovery. Here, we present the first approach that employs computational high-throughput virtual screening and molecular docking to search for small molecules in chemical libraries that function as mechano-regulators of the stability of human cluster of differentiation 4, receptor of HIV-1. Using single-molecule force spectroscopy, we prove that these small molecules can increase the mechanical stability of CD4D1D2 domains over 4-fold in addition to modifying the mechanical unfolding pathways. Our experiments demonstrate that chemical libraries are a source of mechanoactive molecules and that drug discovery approaches provide the foundation of a new type of molecular function, that is, mechano-regulation, paving the way toward mechanopharmacology.

Biallelic variants in SNUPN cause a limb girdle muscular dystrophy with myofibrillar-like features.

Alterations in RNA-splicing are a molecular hallmark of several neurological diseases, including muscular dystrophies where mutations in genes involved in RNA metabolism or characterised by alterations in RNA splicing have been described. Here, we present five patients from two unrelated families with a limb-girdle muscular dystrophy (LGMD) phenotype carrying a biallelic variant in SNUPN gene. Snurportin-1, the protein encoded by SNUPN, plays an important role in the nuclear transport of small nuclear ribonucleoproteins (snRNPs), essential components of the spliceosome. We combine deep phenotyping, including clinical features, histopathology and muscle magnetic resonance image (MRI), with functional studies in patient-derived cells and muscle biopsies to demonstrate that variants in SNUPN are the cause of a new type of LGMD according to current definition. Moreover, an in vivo model in Drosophila melanogaster further supports the relevance of Snurportin-1 in muscle. SNUPN patients show a similar phenotype characterised by proximal weakness starting in childhood, restrictive respiratory dysfunction and prominent contractures, although interindividual variability in terms of severity even in individuals from the same family was found. Muscle biopsy showed myofibrillar-like features consisting of myotilin deposits and Z-disc disorganisation. MRI showed predominant impairment of paravertebral, vasti, sartorius, gracilis, peroneal and medial gastrocnemius muscles. Conservation and structural analyses of Snurportin-1 p.Ile309Ser variant suggest an effect in nuclear-cytosol snRNP trafficking. In patient-derived fibroblasts and muscle, cytoplasmic accumulation of snRNP components is observed, while total expression of Snurportin-1 and snRNPs remains unchanged, which demonstrates a functional impact of SNUPN variant in snRNP metabolism. Furthermore, RNA-splicing analysis in patients' muscle showed widespread splicing deregulation, in particular in genes relevant for muscle development and splicing factors that participate in the early steps of spliceosome assembly. In conclusion, we report that SNUPN variants are a new cause of limb girdle muscular dystrophy with specific clinical, histopathological and imaging features, supporting SNUPN as a new gene to be included in genetic testing of myopathies. These results further support the relevance of splicing-related proteins in muscle disorders.

Atomistic molecular simulations of Aß-Zn conformational ensembles.

The amyloid-forming Aß peptide is able to interact with metal cations to form very stable complexes that influence fibril formation and contribute to the onset of Alzheimer's disease. Multiple structures of peptides derived from Aß in complex with different metals have been resolved experimentally to provide an atomic-level description of the metal-protein interactions. However, Aß is intrinsically disordered, and hence more amenable to an ensemble description. Molecular dynamics simulations can now reach the timescales needed to generate ensembles for these type of complexes. However, this requires accurate force fields both for the protein and the protein-metal interactions. Here we use state-of-the-art methods to generate force field parameters for the Zn(II) cations in a set of complexes formed by different Aß variants and combine them with the Amber99SB*-ILDN optimized force field. Upon comparison of NMR experiments with the simulation results, further optimized with a Bayesian/Maximum entropy approach, we provide an accurate description of the molecular ensembles for most Aß-metal complexes. We find that the resulting conformational ensembles are more heterogeneous than the NMR models deposited in the Protein Data Bank.

Titin domains with reduced core hydrophobicity cause dilated cardiomyopathy.

The underlying genetic defect in most cases of dilated cardiomyopathy (DCM), a common inherited heart disease, remains unknown. Intriguingly, many patients carry single missense variants of uncertain pathogenicity targeting the giant protein titin, a fundamental sarcomere component. To explore the deleterious potential of these variants, we first solved the wild-type and mutant crystal structures of I21, the titin domain targeted by pathogenic variant p.C3575S. Although both structures are remarkably similar, the reduced hydrophobicity of deeply buried position 3575 strongly destabilizes the mutant domain, a scenario supported by molecular dynamics simulations and by biochemical assays that show no disulfide involving C3575. Prompted by these observations, we have found that thousands of similar hydrophobicity-reducing variants associate specifically with DCM. Hence, our results imply that titin domain destabilization causes DCM, a conceptual framework that not only informs pathogenicity assessment of gene variants but also points to therapeutic strategies counterbalancing protein destabilization.

Rules governing metal coordination in Aß-Zn(II) complex models from quantum mechanical calculations.

Transition metals directly contribute to the neurotoxicity of the aggregates of the amyloid-forming Aß peptide. The understanding and rationalization of the coordination modes of metals to Aß amyloid is, therefore, of paramount importance to understand the capacity of a given metal to promote peptide aggregation. Experimentally, multiple Aß-metal structures have been resolved, which exhibit different modes of coordination in both the monomeric and oligomeric forms of Aß. Although Zn(II) metalloproteins are very abundant and often involve cysteine residues in the first coordination shell, in the case of Aß-Zn(II), though, Zn(II) is coordinated by glutamic/aspartic acid and/or histidine residues exclusively, making for an interesting case study. Here we present a systematic analysis of the underlying chemistry on Aß-Zn(II) coordination, where relative stabilities of different coordination arrangements indicate that a mixture of Glu/Asp and His residues is favored. A detailed comparison between different coordination shell geometries shows that tetrahedral coordination is generally favored in the aqueous phase. Our calculations show an interplay between dative covalent interactions and electrostatics which explains the observed trends. Multiple structures deposited in the Protein Data Bank support our findings, suggesting that the trends found in our work may be transferable to other Zn(II) metalloproteins with this type of coordination.

Influence of metal binding on the conformational landscape of neurofilament peptides.

In order to understand the preferred modes of chelation in metal-binding peptides, quantum mechanical calculations can be used to compute energies, resulting in a hierarchy of binding affinities. These calculations often produce increasing stabilization energies the higher the coordination of the complex. However, as the coordination of a metal increases, the conformational freedom of the polypeptide chain is inevitably reduced, resulting in an entropic penalty. Estimating the magnitude of this penalty from the many different degrees of freedom of biomolecular systems is very challenging, and as a result this contribution to the free energy is often ignored. Here we explore this problem focusing on a family of phosphorylated neuropeptides that bind to aluminum. We find that there is a general negative correlation between both stabilization energy and entropy. Our results suggest that a subtle interplay between enthalpic and entropic forces will determine the population of the most favourable species. Additionally, we discuss the requirements for a possible "Metal Ion Hypothesis" based on our findings.

Phase separation in amino acid mixtures is governed by composition.

Macromolecular phase separation has recently come to immense prominence as it is central to the formation of membraneless organelles, leading to a new paradigm of cellular organization. This type of phase transition, often termed liquid-liquid phase separation (LLPS), is mediated by molecular interactions between biomolecules, including nucleic acids and both ordered and disordered proteins. In the latter case, the separation between protein-dense and -dilute phases is often interpreted using models adapted from polymer theory. Specifically, the "stickers and spacers" model proposes that the formation of condensate-spanning networks in protein solutions originates from the interplay between two classes of residues and that the main determinants for phase separation are multivalency and sequence patterning. The duality of roles of stickers (aromatics like Phe and Tyr) and spacers (Gly and polar residues) may apply more broadly in protein-like mixtures, and the presence of these two types of components alone may suffice for LLPS to take place. In order to explore this hypothesis, we use atomistic molecular dynamics simulations of capped amino acid residues as a minimal model system. We study the behavior of pure amino acids in water for three types of residues corresponding to the spacer and sticker categories and of their multicomponent mixtures. In agreement with previous observations, we find that the spacer-type amino acids fail to phase separate on their own, while the sticker is prone to aggregation. However, ternary amino acid mixtures involving both types of amino acids phase separate into two phases that retain intermediate degrees of compaction and greater fluidity than sticker-only condensates. Our results suggest that LLPS is an emergent property of amino acid mixtures determined by composition.

Influence of the Nonprotein Amino Acid Mimosine in Peptide Conformational Propensities from Novel Amber Force Field Parameters.

Mimosine is a nonprotein amino acid derived from plants known for its ability to bind to divalent and trivalent metal cations such as Zn2+, Ni2+, Fe2+, or Al3+. This results in interesting antimicrobial and anticancer properties, which make mimosine a promising candidate for therapeutic applications. One possibility is to incorporate mimosine into synthetic short peptide drugs. However, how this amino acid affects the peptide structure is not well understood, reducing our ability to design effective therapeutic compounds. In this work, we used computer simulations to understand this question. We first built parameters for the mimosine residue to be used in combination with two classical force fields of the Amber family. Then, we used atomistic molecular dynamics simulations with the resulting parameter sets to evaluate the influence of mimosine in the structural propensities for this amino acid. We compared the results of these simulations with homologous peptides, where mimosine is replaced by either phenylalanine or tyrosine. We found that the strong dipole in mimosine induces a preference for conformations where the amino acid rings are stacked over more extended conformations. We validated our results using quantum mechanical calculations, which provide a robust foundation for the outcome of our classical simulations.

Prediction of Folding and Unfolding Rates of Proteins with Simple Models.

Large differences exist between the experimentally measured folding and unfolding rates in single-domain proteins, which range from seconds to microseconds. Considerable effort has been dedicated to develop methods for the prediction of these rates using a simple set of rules. Much of this work has focused in identifying structural metrics derived from experimentally resolved protein structures that serve as good predictors of folding rates. An alternative to this ad-hoc methodology is the use of phenomenological free energy models, parametrized with empirical parameters. This alternative approach has become very useful to obtain estimates of folding and, importantly, also unfolding rates with only the information of protein size and secondary structure. Here we present the fundamentals of this type of approach and introduce a recent implementation of this predictive method.

Markov state models from hierarchical density-based assignment.

Markov state models (MSMs) have become one of the preferred methods for the analysis and interpretation of molecular dynamics (MD) simulations of conformational transitions in biopolymers. While there is great variation in terms of implementation, a well-defined workflow involving multiple steps is often adopted. Typically, molecular coordinates are first subjected to dimensionality reduction and then clustered into small "microstates," which are subsequently lumped into "macrostates" using the information from the slowest eigenmodes. However, the microstate dynamics is often non-Markovian, and long lag times are required to converge the relevant slow dynamics in the MSM. Here, we propose a variation on this typical workflow, taking advantage of hierarchical density-based clustering. When applied to simulation data, this type of clustering separates high population regions of conformational space from others that are rarely visited. In this way, density-based clustering naturally implements assignment of the data based on transitions between metastable states, resulting in a core-set MSM. As a result, the state definition becomes more consistent with the assumption of Markovianity, and the timescales of the slow dynamics of the system are recovered more effectively. We present results of this simplified workflow for a model potential and MD simulations of the alanine dipeptide and the FiP35 WW domain.

Nanomechanical Phenotypes in Cardiac Myosin-Binding Protein C Mutants That Cause Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a disease of the myocardium caused by mutations in sarcomeric proteins with mechanical roles, such as the molecular motor myosin. Around half of the HCM-causing genetic variants target contraction modulator cardiac myosin-binding protein C (cMyBP-C), although the underlying pathogenic mechanisms remain unclear since many of these mutations cause no alterations in protein structure and stability. As an alternative pathomechanism, here we have examined whether pathogenic mutations perturb the nanomechanics of cMyBP-C, which would compromise its modulatory mechanical tethers across sliding actomyosin filaments. Using single-molecule atomic force spectroscopy, we have quantified mechanical folding and unfolding transitions in cMyBP-C domains targeted by HCM mutations that do not induce RNA splicing alterations or protein thermodynamic destabilization. Our results show that domains containing mutation R495W are mechanically weaker than wild-type at forces below 40 pN and that R502Q mutant domains fold faster than wild-type. None of these alterations are found in control, nonpathogenic variants, suggesting that nanomechanical phenotypes induced by pathogenic cMyBP-C mutations contribute to HCM development. We propose that mutation-induced nanomechanical alterations may be common in mechanical proteins involved in human pathologies.

Slow Folding of a Helical Protein: Large Barriers, Strong Internal Friction, or a Shallow, Bumpy Landscape?

The rate at which a protein molecule folds is determined by opposing energetic and entropic contributions to the free energy that shape the folding landscape. Delineating the extent to which they impact the diffusional barrier-crossing events, including the magnitude of internal friction and barrier height, has largely been a challenging task. In this work, we extract the underlying thermodynamic and dynamic contributions to the folding rate of an unusually slow-folding helical DNA-binding domain, PurR, which shares the characteristics of ultrafast downhill-folding proteins but nonetheless appears to exhibit an apparent two-state equilibrium. We combine equilibrium spectroscopy, temperature-viscosity-dependent kinetics, statistical mechanical modeling, and coarse-grained simulations to show that the conformational behavior of PurR is highly heterogeneous characterized by a large spread in melting temperatures, marginal thermodynamic barriers, and populated partially structured states. PurR appears to be at the threshold of disorder arising from frustrated electrostatics and weak packing that in turn slows down folding due to a shallow, bumpy landscape and not due to large thermodynamic barriers or strong internal friction. Our work highlights how a strong temperature dependence on the pre-exponential could signal a shallow landscape and not necessarily a slow-folding diffusion coefficient, thus determining the folding timescales of even millisecond folding proteins and hints at possible structural origins for the shallow landscape.

Theoretical characterization of Al(III) binding to KSPVPKSPVEEKG: Insights into the propensity of aluminum to interact with key sequences for neurofilament formation.

Classical molecular dynamic simulations and density functional theory are used to unveil the interaction of aluminum with various phosphorylated derivatives of the fragment KSPVPKSPVEEKG (NF13), a major multiphosphorylation domain of human neurofilament medium (NFM). Our calculations reveal the rich coordination chemistry of the resultant structures with a clear tendency of aluminum to form multidentate structures, acting as a bridging agent between different sidechains and altering the local secondary structure around the binding site. Our evaluation of binding energies allows us to determine that phosphorylation has an increase in the affinity of these peptides towards aluminum, although the interaction is not as strong as well-known chelators of aluminum in biological systems. Finally, the presence of hydroxides in the first solvation layer has a clear damping effect on the binding affinities. Our results help in elucidating the potential structures than can be formed between this exogenous neurotoxic metal and key sequences for the formation of neurofilament tangles, which are behind of some of the most important degenerative diseases.

Competitive binding of HIF-1α and CITED2 to the TAZ1 domain of CBP from molecular simulations.

Many intrinsically disordered proteins (IDPs) are involved in complex signalling networks inside the cell. Their particular binding modes elicit different types of responses that can be subtly regulated. Here we study the binding of two disordered transactivation domains from proteins HIF-1α and CITED2, whose binding to the TAZ1 domain of CBP is critical for the hypoxic response. Experiments have shown that both IDPs compete for their shared partner, and that this competition is mediated by the formation of a ternary intermediate state. Here we use computer simulations with a coarse-grained model to provide a detailed molecular description of this intermediate. We find that the conserved LP(Q/E)L motif may have a critical role in the displacement of HIF-1α by CITED2 and show a possible mechanism for the transition from the intermediate to the bound state. We also explore the role of TAZ1 dynamics in the binding. The results of our simulations are consistent with many of the experimental observations and provide a detailed view of the emergent properties in the complex binding of these IDPs.

An Abl-FBP17 mechanosensing system couples local plasma membrane curvature and stress fiber remodeling during mechanoadaptation.

Cells remodel their structure in response to mechanical strain. However, how mechanical forces are translated into biochemical signals that coordinate the structural changes observed at the plasma membrane (PM) and the underlying cytoskeleton during mechanoadaptation is unclear. Here, we show that PM mechanoadaptation is controlled by a tension-sensing pathway composed of c-Abl tyrosine kinase and membrane curvature regulator FBP17. FBP17 is recruited to caveolae to induce the formation of caveolar rosettes. FBP17 deficient cells have reduced rosette density, lack PM tension buffering capacity under osmotic shock, and cannot adapt to mechanical strain. Mechanistically, tension is transduced to the FBP17 F-BAR domain by direct phosphorylation mediated by c-Abl, a mechanosensitive molecule. This modification inhibits FBP17 membrane bending activity and releases FBP17-controlled inhibition of mDia1-dependent stress fibers, favoring membrane adaptation to increased tension. This mechanoprotective mechanism adapts the cell to changes in mechanical tension by coupling PM and actin cytoskeleton remodeling.

MasterMSM: A Package for Constructing Master Equation Models of Molecular Dynamics.

Markov state models (MSMs) have become one of the most important techniques for understanding biomolecular transitions from classical molecular dynamics (MD) simulations. MSMs provide a systematized way of accessing the long time kinetics of the system of interest from the short-time scale microscopic transitions observed in simulation trajectories. At the same time, they provide a consistent description of the equilibrium and dynamical properties of the system of interest, and they are ideally suited for comparisons against experiment. A few software packages exist for building MSMs, which have been widely adopted. Here we introduce MasterMSM, a new Python package that uses the master equation formulation of MSMs and provides a number of new algorithms for building and analyzing these models. We demonstrate some of the most distinctive features of the package, including the estimation of rates, definition of core-sets for transition based assignment of states, the estimation of committors and fluxes, and the sensitivity analysis of the emerging networks. The package is available at https://github.com/daviddesancho/MasterMSM .

Instrumental Effects in the Dynamics of an Ultrafast Folding Protein under Mechanical Force.

The analysis and interpretation of single molecule force spectroscopy (smFS) experiments is often complicated by hidden effects from the measuring device. Here we investigate these effects in our recent smFS experiments on the ultrafast folding protein gpW, which has been previously shown to fold without crossing a free energy barrier in the absence of force (i.e., downhill folding). Using atomic force microscopy (AFM) smFS experiments, we found that a very small force of ∼5 pN brings gpW near its unfolding midpoint and results in two-state (un)folding patterns that indicate the emergence of a force-induced free energy barrier. The change in the folding regime is concomitant with a 30,000-fold slowdown of the folding and unfolding times, from a few microseconds that it takes gpW to (un)fold at the midpoint temperature to seconds in the AFM. These results are puzzling because the barrier induced by force in the folding free energy landscape of gpW is far too small to account for such a difference in time scales. Here we use recently developed theoretical methods to resolve the origin of the strikingly slow dynamics of gpW under mechanical force. We find that, while the AFM experiments correctly capture the equilibrium distance distribution, the measured dynamics are entirely controlled by the response of the cantilever and polyprotein linker, which is much slower than the protein conformational dynamics. This interpretation is likely applicable to the folding of other small biomolecules in smFS experiments, and becomes particularly important in the case of systems with fast folding dynamics and small free energy barriers, and for instruments with slow response times.

Mechanical architecture and folding of E. coli type 1 pilus domains.

Uropathogenic Escherichia coli attach to tissues using pili type 1. Each pilus is composed by thousands of coiled FimA domains followed by the domains of the tip fibrillum, FimF-FimG-FimH. The domains are linked by non-covalent ß-strands that must resist mechanical forces during attachment. Here, we use single-molecule force spectroscopy to measure the mechanical contribution of each domain to the stability of the pilus and monitor the oxidative folding mechanism of a single Fim domain assisted by periplasmic FimC and the oxidoreductase DsbA. We demonstrate that pilus domains bear high mechanical stability following a hierarchy by which domains close to the tip are weaker than those close to or at the pilus rod. During folding, this remarkable stability is achieved by the intervention of DsbA that not only forms strategic disulfide bonds but also serves as a chaperone assisting the folding of the domains.

MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations.

Molecular dynamics (MD) simulations can model the interactions between macromolecules with high spatiotemporal resolution but at a high computational cost. By combining high-throughput MD with Markov state models (MSMs), it is now possible to obtain long time-scale behavior of small to intermediate biomolecules and complexes. To model the interactions of many molecules at large length scales, particle-based reaction-diffusion (RD) simulations are more suitable but lack molecular detail. Thus, coupling MSMs and RD simulations (MSM/RD) would be highly desirable, as they could efficiently produce simulations at large time and length scales, while still conserving the characteristic features of the interactions observed at atomic detail. While such a coupling seems straightforward, fundamental questions are still open: Which definition of MSM states is suitable? Which protocol to merge and split RD particles in an association/dissociation reaction will conserve the correct bimolecular kinetics and thermodynamics? In this paper, we make the first step toward MSM/RD by laying out a general theory of coupling and proposing a first implementation for association/dissociation of a protein with a small ligand (A + B ⇌ C). Applications on a toy model and CO diffusion into the heme cavity of myoglobin are reported.