Understanding protein folding: small proteins in silico

Podoplanin Positive Cell-derived Extracellular Vesicles Contribute to Cardiac Amyloidosis After Myocardial Infarction

Background

Amyloidosis is a major long-term complication of chronic disease; however, whether it represents one of the complications of post-myocardial infarction (MI) is yet to be fully understood.

Methods

Using wild-type and knocked-out MI mouse models and characterizing in vitro the exosomal communication between bone marrow-derived macrophages and activated mesenchymal stromal cells (MSC) isolated after MI, we investigated the mechanism behind Serum Amyloid A 3 (SAA3) protein overproduction in injured hearts.

Results

Here, we show that amyloidosis occurs after MI and that amyloid fibers are composed of macrophage-derived SAA3 monomers. SAA3 overproduction in macrophages is triggered by exosomal communication from a subset of activated MSC, which, in response to MI, acquire the expression of a platelet aggregation-inducing type I transmembrane glycoprotein named Podoplanin (PDPN). Cardiac MSC PDPN+ communicate with and activate macrophages through their extracellular vesicles or exosomes. Specifically, MSC PDPN+ derived exosomes (MSC PDPN+ Exosomes) are enriched in SAA3 and exosomal SAA3 protein engages with Toll-like receptor 2 (TRL2) on macrophages, triggering an overproduction and impaired clearance of SAA3 proteins, resulting in aggregation of SAA3 monomers as rigid amyloid deposits in the extracellular space. The onset of amyloid fibers deposition alongside extra-cellular-matrix (ECM) proteins in the ischemic heart exacerbates the rigidity and stiffness of the scar, hindering the contractility of viable myocardium and overall impairing organ function. Using SAA3 and TLR2 deficient mouse models, we show that SAA3 delivered by MSC PDPN+ exosomes promotes post-MI amyloidosis. Inhibition of SAA3 aggregation via administration of a retro-inverso D-peptide, specifically designed to bind SAA3 monomers, prevents the deposition of SAA3 amyloid fibrils, positively modulates the scar formation, and improves heart function post-MI.

Conclusion

Overall, our findings provide mechanistic insights into post-MI amyloidosis and suggest that SAA3 may be an attractive target for effective scar reversal after ischemic injury and a potential target in multiple diseases characterized by a similar pattern of inflammation and amyloid deposition.

NOVELTY AND SIGNIFICANCE

What is known? Accumulation of rigid amyloid structures in the left ventricular wall impairs ventricle contractility.After myocardial infarction cardiac Mesenchymal Stromal Cells (MSC) acquire Podoplanin (PDPN) to better interact with immune cells.Amyloid structures can accumulate in the heart after chronic inflammatory conditions. What information does this article contribute? Whether accumulation of cumbersome amyloid structures in the ischemic scar impairs left ventricle contractility, and scar reversal after myocardial infarction (MI) has never been investigated.The pathophysiological relevance of PDPN acquirement by MSC and the functional role of their secreted exosomes in the context of post-MI cardiac remodeling has not been investigated.Amyloid structures are present in the scar after ischemia and are composed of macrophage-derived Serum Amyloid A (SAA) 3 monomers, although mechanisms of SAA3 overproduction is not established.

SUMMARY OF NOVELTY AND SIGNIFICANCE

Here, we report that amyloidosis, a secondary phenomenon of an already preexisting and prolonged chronic inflammatory condition, occurs after MI and that amyloid structures are composed of macrophage-derived SAA3 monomers. Frequently studied cardiac amyloidosis are caused by aggregation of immunoglobulin light chains, transthyretin, fibrinogen, and apolipoprotein in a healthy heart as a consequence of systemic chronic inflammation leading to congestive heart failure with various types of arrhythmias and tissue stiffness. Although chronic MI is considered a systemic inflammatory condition, studies regarding the possible accumulation of amyloidogenic proteins after MI and the mechanisms involved in that process are yet to be reported. Here, we show that SAA3 overproduction in macrophages is triggered in a Toll-like Receptor 2 (TLR2)-p38MAP Kinase-dependent manner by exosomal communication from a subset of activated MSC, which, in response to MI, express a platelet aggregation-inducing type I transmembrane glycoprotein named Podoplanin. We provide the full mechanism of this phenomenon in murine models and confirm SAA3 amyloidosis in failing human heart samples. Moreover, we developed a retro-inverso D-peptide therapeutic approach, "DRI-R5S," specifically designed to bind SAA3 monomers and prevent post-MI aggregation and deposition of SAA3 amyloid fibrils without interfering with the innate immune response.

Computational chemistry for water-splitting electrocatalysis

Electrocatalytic water splitting driven by renewable electricity has attracted great interest in recent years for producing hydrogen with high-purity. However, the practical applications of this technology are limited by the development of electrocatalysts with high activity, low cost, and long durability. In the search for new electrocatalysts, computational chemistry has made outstanding contributions by providing fundamental laws that govern the electron behavior and enabling predictions of electrocatalyst performance. This review delves into theoretical studies on electrochemical water-splitting processes. Firstly, we introduce the fundamentals of electrochemical water electrolysis and subsequently discuss the current advancements in computational methods and models for electrocatalytic water splitting. Additionally, a comprehensive overview of benchmark descriptors is provided to aid in understanding intrinsic catalytic performance for water-splitting electrocatalysts. Finally, we critically evaluate the remaining challenges within this field.

Folding and self-assembly of a small heterotetramer

Designed miniproteins offer a possibility to study folding and association of protein complexes, both experimentally and in silico. Using replica exchange molecular dynamics and the coarse-grain UNRES force field, we have simulated the folding and self-assembly of the heterotetramer BBAThet1, comparing it with that of the homotetramer BBAT1 which has the same size and ββα-fold. For both proteins, association of the tetramer precedes and facilitates folding of the individual chains.

Stability of amyloid oligomers

Molecular simulations are now commonly used to complement experimental techniques in investigating amyloids and their role in human diseases. In this chapter, we will summarize techniques and approaches often used in amyloid simulations and will present recent success stories. Our examples will be focused on lessons learned from molecular dynamics simulations in aqueous environments that start from preformed aggregates. These studies explore the limitations that arise from the choice of force field, the role of mutations in the growth of amyloid aggregates, segmental polymorphism, and the importance of cross-seeding. Furthermore, they give evidence for potential toxicity mechanisms. We finally discuss the role of molecular simulations in the search for aggregation inhibitors.

Folding and self-assembly of a small protein complex

The synthetic homotetrameric ββα (BBAT1) protein possesses a stable quaternary structure with a ββα fold. Because of its small size (a total of 84 residues), the homotetramer is an excellent model system with which to study the self-assembly and protein-protein interactions. We find from replica exchange molecular dynamics simulations with the coarse-grain UNRES force field that the folding and association pathway consists of three well-separated steps, where that association to a tetramer precedes and facilitates folding of the four chains. At room temperature the tetramer exists in an ensemble of diverse structures. The crystal structure becomes energetically favored only when the molecule is put in a dense and crystal-like environment. The observed picture of folding promoted by association may mirror the mechanism according to which intrinsically unfolded proteins assume their functional structure.

Modeling Structural Flexibility of Proteins with Go-Models

Structure-based models are an efficient tool for folding studies of proteins since by construction their energy landscape is only minimal frustrated. However, their intrinsic drawback is a lack of structural flexibility as usually only one target structure is employed to construct the potentials. Hence, a Go-model may not capture differences in mutation-induced protein dynamics, if - as in the case of the disease-related A629P mutant of the Menkes protein ATP7A - the structural differences between mutant and wild type are small. In this work, we introduced three implementations of Go-models that take into account the flexibility of proteins in the NMR ensemble. Comparing the wild type and the mutant A629P of the 75-residue large 6th domain Menkes protein, we find that these new Go-potentials lead to broader distributions than Go-models relying on a single member of the NMR-ensemble. This allows us to detect the transient unfolding of a loosely formed β1β4-sheet in the mutant protein. Our results are consistent with previous simulations using physical force field and an explicit solvent, and suggests a mechanism by which these mutations cause Menkes disease. In addition, the improved Go-models suggest differences in the folding pathway between wild type and mutant, an observation that was not accessible to simulations of this 75-residue protein with a physical all-atom force field and explicit solvent.

Folding simulations of the A and B domains of protein G

We study wild type and mutants of the A and B domain of protein G using all-atom Go-models. Our data substantiate the usefulness of such simulation for probing the folding mechanism of proteins and demonstrate that multifunnel versions of such models also allow probing of more complicated funnel landscapes. In our case, such models reproduce the experimentally observed distributions of the GA98 and GB98 mutants which differ only by one residue but fold into different structures. They also reveal details on the folding mechanism in these two proteins.

Molecular dynamics

Molecular dynamics (MD) simulation holds the promise of revealing the mechanisms of biological processes in their ultimate detail. It is carried out by computing the interaction forces acting on each atom and then propagating the velocities and positions of the atoms by numerical integration of Newton's equations of motion. In this review, we present an overview of how the MD simulation can be conducted to address computational toxicity problems. The study cases will cover a standard MD simulation performed to investigate the overall flexibility of a cytochrome P450 (CYP) enzyme and a set of more advanced MD simulations to examine the barrier to ion conduction in a human α7 nicotinic acetylcholine receptor (nAChR).

Velocity-scaling optimized replica exchange molecular dynamics of proteins in a hybrid explicit/implicit solvent

We propose a scheme for replica exchange molecular dynamics of proteins in explicit solvent that minimizes the number of required replicas using velocity rescaling. Our approach relies on a hybrid method where the protein evolves at each temperature in an explicit solvent, but replica exchange moves utilize an implicit solvent term. The two terms are coupled through the velocity rescaling. We test the efficiency of this approach for a common test case, the trp-cage protein.

[Prediction of the spatial structure of proteins: emphasis on membrane targets]

Knowledge of the spatial structure of proteins is a prerequisite for both awareness of their functional mechanisms and the framework for rational drug discovery and design. Meanwhile, direct structural determination is often hampered or impractical due to the complexity, expensiveness, and limited capabilities of experimental techniques. These issues are especially pronounced for integral membrane proteins. On numerous occasions, the theoretical prediction of protein structures may facilitate the process by exploiting physical or empirical principles. This paper surveys modern techniques for the prediction of the spatial structure of proteins using computer algorithms, and the main emphasis is placed on the most "complex" targets - membrane proteins (MPs). The first part of the review describes de novo methods based on empirical physical principles; in the second part, a comparative modeling philosophy, which accounts for the structure of related proteins, is described. Special focus is made regarding pharmacologically relevant classes of G-coupled receptors, receptor tyrosine ki-nases, and other MPs. Algorithms for the assessment of the models quality and potential fields of application of computer models are discussed.

Biomolecular Structure and Modeling: Historical Perspective

physics, chemistry, and biology have been connected by a web of causal explanation organized by induction-based theories that telescope into one another. … Thus, quantum theory underlies atomic physics, which is the foundation of reagent chemistry and its specialized offshoot biochemistry, which interlock with molecular biology — essentially, the chemistry of organic macromolecules — and hence, through successively higher levels of organization, cellular, organismic, and evolutionary biology. … Such is the unifying and highly productive understanding of the world that has evolved in the natural sciences.

Microcanonical replica exchange molecular dynamics simulation of proteins

We present microcanonical replica exchange molecular dynamics simulations as an alternative to canonical ones. Its advantage is the easily tunable high acceptance rate for replica exchange. We present the theory, comment on its actual implementation, and demonstrate its application for a common test case, the trp-cage protein.

Exploring the parameter space of the coarse-grained UNRES force field by random search: selecting a transferable medium-resolution force field

We explored the energy-parameter space of our coarse-grained UNRES force field for large-scale ab initio simulations of protein folding, to obtain good initial approximations for hierarchical optimization of the force field with new virtual-bond-angle bending and side-chain-rotamer potentials which we recently introduced to replace the statistical potentials. 100 sets of energy-term weights were generated randomly, and good sets were selected by carrying out replica-exchange molecular dynamics simulations of two peptides with a minimal alpha-helical and a minimal beta-hairpin fold, respectively: the tryptophan cage (PDB code: 1L2Y) and tryptophan zipper (PDB code: 1LE1). Eight sets of parameters produced native-like structures of these two peptides. These eight sets were tested on two larger proteins: the engrailed homeodomain (PDB code: 1ENH) and FBP WW domain (PDB code: 1E0L); two sets were found to produce native-like conformations of these proteins. These two sets were tested further on a larger set of nine proteins with alpha or alpha + beta structure and found to locate native-like structures of most of them. These results demonstrate that, in addition to finding reasonable initial starting points for optimization, an extensive search of parameter space is a powerful method to produce a transferable force field.

Monte Carlo, harmonic approximation, and coarse-graining approaches for enhanced sampling of biomolecular structure

The rugged energy landscape of biomolecules and associated large-scale conformational changes have triggered the development of many innovative enhanced sampling methods, either based or not based on molecular dynamics (MD) simulations. Surveyed here are methods in the latter class - including Monte Carlo methods, harmonic approximations, and coarse graining - many of which yield valuable conformational insights into biomolecular structure and flexibility, despite altered kinetics. MD-based methods are surveyed in an upcoming issue of F1000 Biology Reports.

Computer simulations of the refolding of sperm whale apomyoglobin from high-temperature denaturated state

The refolding mechanism of apomyoglobin (apoMb) subsequent to high-temperature unfolding has been examined using computer simulations with atomic level detail. The folding of this protein has been extensively studied experimentally, providing a large database of folding parameters which can be probed using simulations. In the present study, 4-folding trajectories of apoMb were computed starting from coiled structures. A crystal structure of sperm whale myoglobin taken from the Protein Data Bank was used to construct the final native conformation by removal of the heme group followed by energy optimization. The initial unfolded conformations were obtained from high-temperature molecular dynamics simulations. Room-temperature refolding trajectories at neutral pH were obtained using the stochastic difference equation in length algorithm. The folding trajectories were compared with experimental results and two previous molecular dynamics studies at low pH. In contrast to the previous simulations, an extended intermediate with large helical content was not observed. In the present study, a structural collapse occurs without formation of helices or native contacts. Once the protein structure is more compact (radius of gyration<18 A) secondary and tertiary structures appear. These results suggest that apoMb follows a different folding pathway after high-temperature denaturation.

Conformation of a coarse-grained protein chain (an aspartic acid protease) model in effective solvent by a bond-fluctuating Monte Carlo simulation

In a coarse-grained description of a protein chain, all of the 20 amino acid residues can be broadly divided into three groups: Hydrophobic (H) , polar (P) , and electrostatic (E) . A protein can be described by nodes tethered in a chain with a node representing an amino acid group. Aspartic acid protease consists of 99 residues in a well-defined sequence of H , P , and E nodes tethered together by fluctuating bonds. The protein chain is placed on a cubic lattice where empty lattice sites constitute an effective solvent medium. The amino groups (nodes) interact with the solvent (S) sites with appropriate attractive (PS) and repulsive (HS) interactions with the solvent and execute their stochastic movement with the Metropolis algorithm. Variations of the root mean square displacements of the center of mass and that of its center node of the protease chain and its gyration radius with the time steps are examined for different solvent strength. The structure of the protease swells on increasing the solvent interaction strength which tends to enhance the relaxation time to reach the diffusive behavior of the chain. Equilibrium radius of gyration increases linearly on increasing the solvent strength: A slow rate of increase in weak solvent regime is followed by a faster swelling in stronger solvent. Variation of the gyration radius with the time steps suggests that the protein chain moves via contraction and expansion in a somewhat quasiperiodic pattern particularly in strong solvent.