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.

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.

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.

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.

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.

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.

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 .

The life of proteins under mechanical force.

Although much of our understanding of protein folding comes from studies of isolated protein domains in bulk, in the cellular environment the intervention of external molecular machines is essential during the protein life cycle. During the past decade single molecule force spectroscopy techniques have been extremely useful to deepen our understanding of these interventional molecular processes, as they allow for monitoring and manipulating mechanochemical events in individual protein molecules. Here, we review some of the critical steps in the protein life cycle, starting with the biosynthesis of the nascent polypeptide chain in the ribosome, continuing with the folding supported by chaperones and the translocation into different cell compartments, and ending with proteolysis in the proteasome. Along these steps, proteins experience molecular forces often combined with chemical transformations, affecting their folding and structure, which are measured or mimicked in the laboratory by the application of force with a single molecule apparatus. These mechanochemical reactions can potentially be used as targets for fighting against diseases. Inspired by these insightful experiments, we devise an outlook on the emerging field of mechanopharmacology, which reflects an alternative paradigm for drug design.

The influence of disulfide bonds on the mechanical stability of proteins is context dependent.

Disulfide bonds play a crucial role in proteins, modulating their stability and constraining their conformational dynamics. A particularly important case is that of proteins that need to withstand forces arising from their normal biological function and that are often disulfide bonded. However, the influence of disulfides on the overall mechanical stability of proteins is poorly understood. Here, we used single-molecule force spectroscopy (smFS) to study the role of disulfide bonds in different mechanical proteins in terms of their unfolding forces. For this purpose, we chose the pilus protein FimG from Gram-negative bacteria and a disulfide-bonded variant of the I91 human cardiac titin polyprotein. Our results show that disulfide bonds can alter the mechanical stability of proteins in different ways depending on the properties of the system. Specifically, disulfide-bonded FimG undergoes a 30% increase in its mechanical stability compared with its reduced counterpart, whereas the unfolding force of I91 domains experiences a decrease of 15% relative to the WT form. Using a coarse-grained simulation model, we rationalized that the increase in mechanical stability of FimG is due to a shift in the mechanical unfolding pathway. The simple topology-based explanation suggests a neutral effect in the case of titin. In summary, our results indicate that disulfide bonds in proteins act in a context-dependent manner rather than simply as mechanical lockers, underscoring the importance of considering disulfide bonds both computationally and experimentally when studying the mechanical properties of proteins.

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.

Interplay between the folding mechanism and binding modes in folding coupled to binding processes.

Proteins that fold upon binding to their partners exhibit complex binding behavior such as induced-fit. But the connections between the folding mechanism and the binding mode remain unknown. Here we focus on the high affinity complex between the physiologically and marginally unstable, fast folder PSBD and the E1 subunit of pyruvate dehydrogenase. Using coarse-grained simulations we investigate the binding to E1 of a partially disordered PSBD under two folding scenarios: two-state and downhill. Our simulations show that induced-fit binding requires that PSBD folds-unfolds in the downhill folding regime. In contrast, a two-state folding PSBD must fold completely before it binds. The reason is that effective coupling between folding and binding involves partially folded conformations, which are only sufficiently populated under the downhill folding regime. Our results establish a direct mechanistic link between complex binding and downhill folding, supporting the idea that PSBD operates functionally as a conformational rheostat.

Interplay between partner and ligand facilitates the folding and binding of an intrinsically disordered protein.

Protein-protein interactions are at the heart of regulatory and signaling processes in the cell. In many interactions, one or both proteins are disordered before association. However, this disorder in the unbound state does not prevent many of these proteins folding to a well-defined, ordered structure in the bound state. Here we examine a typical system, where a small disordered protein (PUMA, p53 upregulated modulator of apoptosis) folds to an α-helix when bound to a groove on the surface of a folded protein (MCL-1, induced myeloid leukemia cell differentiation protein). We follow the association of these proteins using rapid-mixing stopped flow, and examine how the kinetic behavior is perturbed by denaturant and carefully chosen mutations. We demonstrate the utility of methods developed for the study of monomeric protein folding, including ß-Tanford values, Leffler α, Φ-value analysis, and coarse-grained simulations, and propose a self-consistent mechanism for binding. Folding of the disordered protein before binding does not appear to be required and few, if any, specific interactions are required to commit to association. The majority of PUMA folding occurs after the transition state, in the presence of MCL-1. We also examine the role of the side chains of folded MCL-1 that make up the binding groove and find that many favor equilibrium binding but, surprisingly, inhibit the association process.

Markov state models of protein misfolding.

Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity.

Dependence of internal friction on folding mechanism.

An outstanding challenge in protein folding is understanding the origin of "internal friction" in folding dynamics, experimentally identified from the dependence of folding rates on solvent viscosity. A possible origin suggested by simulation is the crossing of local torsion barriers. However, it was unclear why internal friction varied from protein to protein or for different folding barriers of the same protein. Using all-atom simulations with variable solvent viscosity, in conjunction with transition-path sampling to obtain reaction rates and analysis via Markov state models, we are able to determine the internal friction in the folding of several peptides and miniproteins. In agreement with experiment, we find that the folding events with greatest internal friction are those that mainly involve helix formation, while hairpin formation exhibits little or no evidence of friction. Via a careful analysis of folding transition paths, we show that internal friction arises when torsion angle changes are an important part of the folding mechanism near the folding free energy barrier. These results suggest an explanation for the variation of internal friction effects from protein to protein and across the energy landscape of the same protein.

Aerobic damage to [FeFe]-hydrogenases: activation barriers for the chemical attachment of O2.

[FeFe]-hydrogenases are the best natural hydrogen-producing enzymes but their biotechnological exploitation is hampered by their extreme oxygen sensitivity. The free energy profile for the chemical attachment of O2 to the enzyme active site was investigated by using a range-separated density functional re-parametrized to reproduce high-level ab initio data. An activation free-energy barrier of 13 kcal mol(-1) was obtained for chemical bond formation between the di-iron active site and O2, a value in good agreement with experimental inactivation rates. The oxygen binding can be viewed as an inner-sphere electron-transfer process that is strongly influenced by Coulombic interactions with the proximal cubane cluster and the protein environment. The implications of these results for future mutation studies with the aim of increasing the oxygen tolerance of this enzyme are discussed.

The strongest protein binder is surprisingly labile.

Bacterial adhesins are cell-surface proteins that anchor to the cell wall of the host. The first stage of infection involves the specific attachment to fibrinogen (Fg), a protein found in human blood. This attachment allows bacteria to colonize tissues causing diseases such as endocarditis. The study of this family of proteins is hence essential to develop new strategies to fight bacterial infections. In the case of the Gram-positive bacterium Staphylococcus aureus, there exists a class of adhesins known as microbial surface components recognizing adhesive matrix molecules (MSCRAMMs). Here, we focus on one of them, the clumping factor A (ClfA), which has been found to bind Fg through the dock-lock-latch mechanism. Interestingly, it has recently been discovered that MSCRAMM proteins employ a catch-bond to withstand forces exceeding 2 nN, making this type of interaction as mechanically strong as a covalent bond. However, it is not known whether this strength is an evolved feature characteristic of the bacterial protein or is typical only of the interaction with its partner. Here, we combine single-molecule force spectroscopy, biophysical binding assays, and molecular simulations to study the intrinsic mechanical strength of ClfA. We find that despite the extremely high forces required to break its interactions with Fg, ClfA is not by itself particularly strong. Integrating the results from both theory and experiments we dissect contributions to the mechanical stability of this protein.

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.

Residue-specific α-helix propensities from molecular simulation.

Formation of α-helices is a fundamental process in protein folding and assembly. By studying helix formation in molecular simulations of a series of alanine-based peptides, we obtain the temperature-dependent α-helix propensities of all 20 naturally occurring residues with two recent additive force fields, Amber ff03w and Amber ff99SB(∗). Encouragingly, we find that the overall helix propensity of many residues is captured well by both energy functions, with Amber ff99SB(∗) being more accurate. Nonetheless, there are some residues that deviate considerably from experiment, which can be attributed to two aspects of the energy function: i), variations of the charge model used to determine the atomic partial charges, with residues whose backbone charges differ most from alanine tending to have the largest error; ii), side-chain torsion potentials, as illustrated by the effect of modifications to the torsion angles of I, L, D, N. We find that constrained refitting of residue charges for charged residues in Amber ff99SB(∗) significantly improves their helix propensity. The resulting parameters should more faithfully reproduce helix propensities in simulations of protein folding and disordered proteins.