Relative stability of de novo four-helix bundle proteins: insights from coarse grained molecular simulations

Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation

Designing entirely new protein structures remains challenging because we do not fully understand the biophysical determinants of folding stability. Yet, some protein folds are easier to design than others. Previous work identified the 43-residue ɑββɑ fold as especially challenging: The best designs had only a 2% success rate, compared to 39 to 87% success for other simple folds [G. J. Rocklin et al., Science 357, 168-175 (2017)]. This suggested the ɑββɑ fold would be a useful model system for gaining a deeper understanding of folding stability determinants and for testing new protein design methods. Here, we designed over 10,000 new ɑββɑ proteins and found over 3,000 of them to fold into stable structures using a high-throughput protease-based assay. NMR, hydrogen-deuterium exchange, circular dichroism, deep mutational scanning, and scrambled sequence control experiments indicated that our stable designs fold into their designed ɑββɑ structures with exceptional stability for their small size. Our large dataset enabled us to quantify the influence of universal stability determinants including nonpolar burial, helix capping, and buried unsatisfied polar atoms, as well as stability determinants unique to the ɑββɑ topology. Our work demonstrates how large-scale design and test cycles can solve challenging design problems while illuminating the biophysical determinants of folding.

The Pierced Lasso Topology Leptin has a Bolt on Dynamic Domain Composed by the Disordered Loops I and III

Leptin is an important signaling hormone, mostly known for its role in energy expenditure and satiety. Furthermore, leptin plays a major role in other proteinopathies, such as cancer, marked hyperphagia, impaired immune function, and inflammation. In spite of its biological relevance in human health, there are no NMR resonance assignments of the human protein available, obscuring high-resolution characterization of the soluble protein and/or its conformational dynamics, suggested as being important for receptor interaction and biological activity. Here, we report the nearly complete backbone resonance assignments of human leptin. Chemical shift-based secondary structure prediction confirms that in solution leptin forms a four-helix bundle including a pierced lasso topology. The conformational dynamics, determined on several timescales, show that leptin is monomeric, has a rigid four-helix scaffold, and a dynamic domain, including a transiently formed helix. The dynamic domain is anchored to the helical scaffold by a secondary hydrophobic core, pinning down the long loops of leptin to the protein body, inducing motional restriction without a well-defined secondary or tertiary hydrogen bond stabilized structure. This dynamic region is well suited for and may be involved in functional allosteric dynamics upon receptor binding.

Physical properties of phospholipids and integral proteins and their biofunctional roles in pulmonary surfactant from molecular dynamics simulation

This work deals with a quantitative investigation of the physical properties of pulmonary surfactant near melting temperature. To this end, we make use of molecular dynamics simulations, using the MARTINI coarse-grained model, for determining the physical properties of the system, such as the potential energy, the specific heat, the microstructure, the diffusion laws, and the elastic properties of the surfactant. The microstructure is studied by computation of the radial-distribution-function upon varying the distance between constituents (lipid molecules or proteins). The diffusion phenomenon is investigated by determination of the mean-squared-displacement and the time dependent velocity-autocorrelation-function for various values of temperature. We show that the dynamics of lipids and proteins exhibit a subdiffusion regime (slow movement) due to the cage effect within pulmonary surfactant. From the obtained mean-squared-displacement, we get the values of the self-diffusion-coefficients and the anomalous exponents at different temperatures close to the melting temperature. For the mathematical description of the cage effect, we make use of the scale relations in terms of the waiting time probability distribution. The last study is concerned with determination of the dependence of the lateral stress upon the strain of pulmonary surfactant, which is found to be linear, and from which we deduce the lateral-elastic-modulus.

The membrane protein KCNQ1 potassium ion channel: Functional diversity and current structural insights

BACKGROUND

Ion channels play crucial roles in cellular biology, physiology, and communication including sensory perception. Voltage-gated potassium (Kv) channels execute their function by sensor activation, pore-coupling, and pore opening leading to K⁺ conductance.

SCOPE OF REVIEW

This review focuses on a voltage-gated K⁺ ion channel KCNQ1 (Kv 7.1). Firstly, discussing its positioning in the human ion chanome, and the role of KCNQ1 in the multitude of cellular processes. Next, we discuss the overall channel architecture and current structural insights on KCNQ1. Finally, the gating mechanism involving members of the KCNE family and its interaction with non-KCNE partners.

MAJOR CONCLUSIONS

KCNQ1 executes its important physiological functions via interacting with KCNE1 and non-KCNE1 proteins/molecules: calmodulin, PIP₂, PKA. Although, KCNQ1 has been studied in great detail, several aspects of the channel structure and function still remain unexplored. This review emphasizes the structural and biophysical studies of KCNQ1, its interaction with KCNE1 and non-KCNE1 proteins and focuses on several seminal findings showing the role of VSD and the pore domain in the channel activation and gating properties.

GENERAL SIGNIFICANCE

KCNQ1 mutations can result in channel defects and lead to several diseases including atrial fibrillation and long QT syndrome. Therefore, a thorough structure-function understanding of this channel complex is essential to understand its role in both normal and disease biology. Moreover, unraveling the molecular mechanisms underlying the regulation of this channel complex will help to find therapeutic strategies for several diseases.

Development of a High-Throughput Fluorescence Polarization Assay to Detect Inhibitors of the FAK-Paxillin Interaction

Focal adhesion kinase (FAK) is a promising cancer drug target due to its massive overexpression in multiple solid tumors and its critical role in the integration of signals that control proliferation, invasion, apoptosis, and metastasis. Previous FAK drug discovery and high-throughput screening have exclusively focused on the identification of inhibitors that target the kinase domain of FAK. Because FAK is both a kinase and scaffolding protein, the development of novel screening assays that detect inhibitors of FAK protein-protein interactions remains a critical need. In this report, we describe the development of a high-throughput fluorescence polarization (FP) screening assay that measures the interactions between FAK and paxillin, a focal adhesion-associated protein. We designed a tetramethylrhodamine (TAMRA)-tagged paxillin peptide based on the paxillin LD2 motif that binds to the focal adhesion targeting (FAT) domain with significant dynamic range, specificity, variability, stability, and a Z'-factor suitable for high-throughput screening. In addition, we performed a pilot screen of 1593 compounds using this FP assay, showing its feasibility for high-throughput drug screening. Finally, we identified three compounds that show dose-dependent competition of FAT-paxillin binding. This assay represents the first described high-throughput screening assay for FAK scaffold inhibitors and can accelerate drug discovery efforts for this promising drug target.

Using a second-order differential model to fit data without baselines in protein isothermal chemical denaturation

In vitro protein stability studies are commonly conducted via thermal or chemical denaturation/renaturation of protein. Conventional data analyses on the protein unfolding/(re)folding require well-defined pre- and post-transition baselines to evaluate Gibbs free-energy change associated with the protein unfolding/(re)folding. This evaluation becomes problematic when there is insufficient data for determining the pre- or post-transition baselines. In this study, fitting on such partial data obtained in protein chemical denaturation is established by introducing second-order differential (SOD) analysis to overcome the limitations that the conventional fitting method has. By reducing numbers of the baseline-related fitting parameters, the SOD analysis can successfully fit incomplete chemical denaturation data sets with high agreement to the conventional evaluation on the equivalent completed data, where the conventional fitting fails in analyzing them. This SOD fitting for the abbreviated isothermal chemical denaturation further fulfills data analysis methods on the insufficient data sets conducted in the two prevalent protein stability studies.

Computational study of elements of stability of a four-helix bundle protein biosurfactant

Biosurfactants are surface-active molecules produced principally by microorganisms. They are a sustainable alternative to chemically-synthesized surfactants, having the advantages of being non-toxic, highly functional, eco-friendly and biodegradable. However they are currently only used in a few industrial products due to costs associated with production and purification, which exceed those for commodity chemical surfactants. DAMP4, a member of a four-helix bundle biosurfactant protein family, can be produced in soluble form and at high yield in Escherichia coli, and can be recovered using a facile thermal phase-separation approach. As such, it encompasses an interesting synergy of biomolecular and chemical engineering with prospects for low-cost production even for industrial sectors. DAMP4 is highly functional, and due to its extraordinary thermal stability it can be purified in a simple two-step process, in which the combination of high temperature and salt leads to denaturation of all contaminants, whereas DAMP4 stays stable in solution and can be recovered by filtration. This study aimed to characterize and understand the fundamental drivers of DAMP4 stability to guide further process and surfactant design studies. The complementary use of experiments and molecular dynamics simulation revealed a broad pH and temperature tolerance for DAMP4, with a melting point of 122.4 °C, suggesting the hydrophobic core as the major contributor to thermal stability. Simulation of systematically created in silico variants of DAMP4 showed an influence of number and location of hydrophilic mutations in the hydrophobic core on stability, demonstrating a tolerance of up to three mutations before a strong loss in stability occurred. The results suggest a consideration of a balance of stability, functionality and kinetics for new designs according to their application, aiming for maximal functionality but at adequate stability to allow for cost-efficient production using thermal phase separation approaches.

Coarse-Grained Simulations of Protein Backbone Dynamics. 1. Local Sterics Define the Dihedral Angles

Here, we present a coarse-grained model targeted for implicit solvent simulations of unfolded or intrinsically disordered proteins. The hierarchical model with its nonspherical building blocks allows one to reproduce the local dynamics of the backbone with simple harmonic bonds and steric collisions between a small number of atoms at the correct off-center positions on the building blocks. Here in part 1, we also describe the implementation of the global shape of the protein chain and the extended local interactions that add a first secondary structure bias, which will subsequently be augmented by additional hydrophobic interactions, hydrogen bonds, and dipole dipole couplings along the backbone. Due to its hierarchical setup, the model has a near-atomistic resolution on the local scale and the overall numerical efficiency of a coarse-grained model such that even long protein chains can be simulated efficiently.

Space warping order parameters and symmetry: application to multiscale simulation of macromolecular assemblies

Coarse-grained features of macromolecular assemblies are understood via a set of order parameters (OPs) constructed in terms of their all-atom configuration. OPs are shown to be slowly changing in time and capture the large-scale spatial features of macromolecular assemblies. The relationship of these variables to the classic notion of OPs based on symmetry breaking phase transitions is discussed. OPs based on space warping transformations are analyzed in detail as they naturally provide a connection between overall structure of an assembly and all-atom configuration. These OPs serve as the basis of a multiscale analysis that yields Langevin equations for OP dynamics. In this context, the characteristics of OPs and PCA modes are compared. The OPs enable efficient all-atom multiscale simulations of the dynamics of macromolecular assemblies in response to changes in microenvironmental conditions, as demonstrated on the structural transitions of cowpea chlorotic mottle virus capsid (CCMV) and RNA of the satellite tobacco mosaic virus (STMV).