Ratchet, swivel, tilt and roll: a complete description of subunit rotation in the ribosome.

Protein synthesis by the ribosome requires large-scale rearrangements of the 'small' subunit (SSU; ∼1 MDa), including inter- and intra-subunit rotational motions. However, with nearly 2000 structures of ribosomes and ribosomal subunits now publicly available, it is exceedingly difficult to design experiments based on analysis of all known rotation states. To overcome this, we developed an approach where the orientation of each SSU head and body is described in terms of three angular coordinates (rotation, tilt and tilt direction) and a single translation. By considering the entire RCSB PDB database, we describe 1208 fully-assembled ribosome complexes and 334 isolated small subunits, which span >50 species. This reveals aspects of subunit rearrangements that are universal, and others that are organism/domain-specific. For example, we show that tilt-like rearrangements of the SSU body (i.e. 'rolling') are pervasive in both prokaryotic and eukaryotic (cytosolic and mitochondrial) ribosomes. As another example, domain orientations associated with frameshifting in bacteria are similar to those found in eukaryotic ribosomes. Together, this study establishes a common foundation with which structural, simulation, single-molecule and biochemical efforts can more precisely interrogate the dynamics of this prototypical molecular machine.

Biotin-painted proteins have thermodynamic stability switched by kinetic folding routes.

Biotin-labeled proteins are widely used as tools to study protein-protein interactions and proximity in living cells. Proteomic methods broadly employ proximity-labeling technologies based on protein biotinylation in order to investigate the transient encounters of biomolecules in subcellular compartments. Biotinylation is a post-translation modification in which the biotin molecule is attached to lysine or tyrosine residues. So far, biotin-based technologies proved to be effective instruments as affinity and proximity tags. However, the influence of biotinylation on aspects such as folding, binding, mobility, thermodynamic stability, and kinetics needs to be investigated. Here, we selected two proteins [biotin carboxyl carrier protein (BCCP) and FKBP3] to test the influence of biotinylation on thermodynamic and kinetic properties. Apo (without biotin) and holo (biotinylated) protein structures were used separately to generate all-atom structure-based model simulations in a wide range of temperatures. Holo BCCP contains one biotinylation site, and FKBP3 was modeled with up to 23 biotinylated lysines. The two proteins had their estimated thermodynamic stability changed by altering their energy landscape. In all cases, after comparison between the apo and holo simulations, differences were observed on the free-energy profiles and folding routes. Energetic barriers were altered with the density of states clearly showing changes in the transition state. This study suggests that analysis of large-scale datasets of biotinylation-based proximity experiments might consider possible alterations in thermostability and folding mechanisms imposed by the attached biotins.

Shedding Light on the Inhibitory Mechanisms of SARS-CoV-1/CoV-2 Spike Proteins by ACE2-Designed Peptides.

Angiotensin-converting enzyme 2 (ACE2) is the host cellular receptor that locks onto the surface spike protein of the 2002 SARS coronavirus (SARS-CoV-1) and of the novel, highly transmissible and deadly 2019 SARS-CoV-2, responsible for the COVID-19 pandemic. One strategy to avoid the virus infection is to design peptides by extracting the human ACE2 peptidase domain α1-helix, which would bind to the coronavirus surface protein, preventing the virus entry into the host cells. The natural α1-helix peptide has a stronger affinity to SARS-CoV-2 than to SARS-CoV-1. Another peptide was designed by joining α1 with the second portion of ACE2 that is far in the peptidase sequence yet grafted in the spike protein interface with ACE2. Previous studies have shown that, among several α1-based peptides, the hybrid peptidic scaffold is the one with the highest/strongest affinity for SARS-CoV-1, which is comparable to the full-length ACE2 affinity. In this work, binding and folding dynamics of the natural and designed ACE2-based peptides were simulated by the well-known coarse-grained structure-based model, with the computed thermodynamic quantities correlating with the experimental binding affinity data. Furthermore, theoretical kinetic analysis of native contact formation revealed the distinction between these processes in the presence of the different binding partners SARS-CoV-1 and SARS-CoV-2 spike domains. Additionally, our results indicate the existence of a two-state folding mechanism for the designed peptide en route to bind to the spike proteins, in contrast to a downhill mechanism for the natural α1-helix peptides. The presented low-cost simulation protocol demonstrated its efficiency in evaluating binding affinities and identifying the mechanisms involved in the neutralization of spike-ACE2 interaction by designed peptides. Finally, the protocol can be used as a computer-based screening of more potent designed peptides by experimentalists searching for new therapeutics against COVID-19.

The dynamics of subunit rotation in a eukaryotic ribosome.

Protein synthesis by the ribosome is coordinated by an intricate series of large-scale conformational rearrangements. Structural studies can provide information about long-lived states, however biological kinetics are controlled by the intervening free-energy barriers. While there has been progress describing the energy landscapes of bacterial ribosomes, very little is known about the energetics of large-scale rearrangements in eukaryotic systems. To address this topic, we constructed an all-atom model with simplified energetics and performed simulations of subunit rotation in the yeast ribosome. In these simulations, the small subunit (SSU; ~1MDa) undergoes spontaneous and reversible rotations (~8°). By enabling the simulation of this rearrangement under equilibrium conditions, these calculations provide initial insights into the molecular factors that control dynamics in eukaryotic ribosomes. Through this, we are able to identify specific inter-subunit interactions that have a pronounced influence on the rate-limiting free-energy barrier. We also show that, as a result of changes in molecular flexibility, the thermodynamic balance between the rotated and unrotated states is temperature-dependent. This effect may be interpreted in terms of differential molecular flexibility within the rotated and unrotated states. Together, these calculations provide a foundation, upon which the field may begin to dissect the energetics of these complex molecular machines.

Extension-Dependent Drift Velocity and Diffusion (DrDiff) Directly Reconstructs the Folding Free Energy Landscape of Atomic Force Microscopy Experiments.

Two equilibrium force microscopy trajectories [q(t)] of high-precision single-molecule spectroscopy assays were analyzed: the pulling of an HIV RNA hairpin and of a 3-aa sequence of the bacteriorhodopsin membrane protein. Both present hundreds of two-state folding transitions, and their free-energy [F(q)] landscapes were previously obtained by deconvolving time signals with the inverse Boltzmann and pfold methods. In this letter, the two F profiles were reconstructed directly from the measured time-series by the drift-diffusion (DrDiff) framework that characterized the effective conformational drift-velocity [v(q)] and diffusion [D(q)] coefficients. The two thermodynamic F profiles reconstructed with DrDiff directly from q(t) were in good agreement with those previously obtained from the deconvolved time signals. q(t) trajectories simulated with a two-dimensional framework in which the diffusion coefficient of the pulling setup (q coordinate) differed from the molecule (x coordinate) were also analyzed by DrDiff. The performance in reconstructing F was investigated in different conditions of diffusion anisotropy in the simulated time-series using Brownian dynamics. In addition, recently developed theories were used in order to evaluate the quality of the analysis performed in the experimental time series: the memory effects and the intrinsic biomolecular dynamic properties after connecting the probe to the molecule. With the 2-dimensional diffusive models and the additional analyses, it is proposed that the different physical regimes imposed by the stiffer probes of the two biomolecules will have an impact in the measured extension-dependent D and, thus, in the reconstruction of F by DrDiff. Stiffer AFM probes may reflect the molecular behavior more faithfully and reconstruction of F might be more successful. The reported quantities extracted directly from q(t) highlights the current state of the biomolecule characterization by force spectroscopy experiments: it is still challenging despite the recent advances, yet it is very promising.

The Role of Electrostatics and Folding Kinetics on the Thermostability of Homologous Cold Shock Proteins.

Understanding which aspects contribute to the thermostability of proteins is a challenge that has persisted for decades, and it is of great relevance for protein engineering. Several types of interactions can influence the thermostability of a protein. Among them, the electrostatic interactions have been a target of particular attention. Aiming to explore how this type of interaction can affect protein thermostability, this paper investigated four homologous cold shock proteins from psychrophilic, mesophilic, thermophilic, and hyperthermophilic organisms using a set of theoretical methodologies. It is well-known that electrostatics as well as hydrophobicity are key-elements for the stabilization of these proteins. Therefore, both interactions were initially analyzed in the native structure of each protein. Electrostatic interactions present in the native structures were calculated with the Tanford-Kirkwood model with solvent accessibility, and the amount of hydrophobic surface area buried upon folding was estimated by measuring both folded and extended structures. On the basis of Energy Landscape Theory, the local frustration and the simplified alpha-carbon structure-based model were modeled with a Debye-Hückel potential to take into account the electrostatics and the effects of an implicit solvent. Thermodynamic data for the structure-based model simulations were collected and analyzed using the Weighted Histogram Analysis and Stochastic Diffusion methods. Kinetic quantities including folding times, transition path times, folding routes, and Φ values were also obtained. As a result, we found that the methods are able to qualitatively infer that electrostatic interactions play an important role on the stabilization of the most stable thermophilic cold shock proteins, showing agreement with the experimental data.

Drift-diffusion (DrDiff) framework determines kinetics and thermodynamics of two-state folding trajectory and tunes diffusion models.

The stochastic drift-diffusion (DrDiff) theory is an approach used to characterize the dynamical properties of simulation data. With new features in transition times analyses, the framework characterized the thermodynamic free-energy profile [F(Q)], the folding time (τf), and transition path time (τTP) by determining the coordinate-dependent drift-velocity [v(Q)] and diffusion [D(Q)] coefficients from trajectory time traces. In order to explore the DrDiff approach and to tune it with two other methods (Bayesian analysis and fep1D algorithm), a numerical integration of the Langevin equation with known D(Q) and F(Q) was performed and the inputted coefficients were recovered with success by the diffusion models. DrDiff was also applied to investigate the prion protein (PrP) kinetics and thermodynamics by analyzing folding/unfolding simulations. The protein structure-based model, the well-known Go¯-model, was employed in a coarse-grained Cα level to generate long constant-temperature time series. PrP was chosen due to recent experimental single-molecule studies in D and τTP that stressed the importance and the difficulty of probing these quantities and the rare transition state events related to prion misfolding and aggregation. The PrP thermodynamic double-well F(Q) profile, the "X" shape of τf(T), and the linear shape of τTP(T) were predicted with v(Q) and D(Q) obtained by the DrDiff algorithm. With the advance of single-molecule techniques, the DrDiff framework might be a useful ally for determining kinetic and thermodynamic properties by analyzing time observables of biomolecular systems. The code is freely available at https://github.com/ronaldolab/DrDiff.