Multimodal binding and inhibition of bacterial ribosomes by the antimicrobial peptides Api137 and Api88.

Proline-rich antimicrobial peptides (PrAMPs) inhibit bacterial protein biosynthesis by binding to the polypeptide exit tunnel (PET) near the peptidyl transferase center. Api137, an optimized derivative of honeybee PrAMP apidaecin, inhibits protein expression by trapping release factors (RFs), which interact with stop codons on ribosomes to terminate translation. This study uses cryo-EM, functional assays and molecular dynamic (MD) simulations to show that Api137 additionally occupies a second binding site near the exit of the PET and can repress translation independently of RF-trapping. Api88, a C-terminally amidated (-CONH2) analog of Api137 (-COOH), binds to the same sites, occupies a third binding pocket and interferes with the translation process presumably without RF-trapping. In conclusion, apidaecin-derived PrAMPs inhibit bacterial ribosomes by multimodal mechanisms caused by minor structural changes and thus represent a promising pool for drug development efforts.

Single-particle Cryo-EM and molecular dynamics simulations: A perfect match.

Knowledge of the structure and dynamics of biomolecules is key to understanding the mechanisms underlying their biological functions. Single-particle cryo-electron microscopy (cryo-EM) is a powerful structural biology technique to characterize complex biomolecular systems. Here, we review recent advances of how Molecular Dynamics (MD) simulations are being used to increase and enhance the information extracted from cryo-EM experiments. We will particularly focus on the physics underlying these experiments, how MD facilitates structure refinement, in particular for heterogeneous and non-isotropic resolution, and how thermodynamic and kinetic information can be extracted from cryo-EM data.

Reference Data Set for Circular Dichroism Spectroscopy Comprised of Validated Intrinsically Disordered Protein Models.

Circular dichroism (CD) spectroscopy is an analytical technique that measures the wavelength-dependent differential absorbance of circularly polarized light and is applicable to most biologically important macromolecules, such as proteins, nucleic acids, and carbohydrates. It serves to characterize the secondary structure composition of proteins, including intrinsically disordered proteins, by analyzing their recorded spectra. Several computational tools have been developed to interpret protein CD spectra. These methods have been calibrated and tested mostly on globular proteins with well-defined structures, mainly due to the lack of reliable reference structures for disordered proteins. It is therefore still largely unclear how accurately these computational methods can determine the secondary structure composition of disordered proteins. Here, we provide such a required reference data set consisting of model structural ensembles and matching CD spectra for eight intrinsically disordered proteins. Using this set of data, we have assessed the accuracy of several published CD prediction and secondary structure estimation tools, including our own CD analysis package, SESCA. Our results show that for most of the tested methods, their accuracy for disordered proteins is generally lower than for globular proteins. In contrast, SESCA, which was developed using globular reference proteins, but was designed to be applicable to disordered proteins as well, performs similarly well for both classes of proteins. The new reference data set for disordered proteins should allow for further improvement of all published methods.

Infrared spectroscopy reveals metal-independent carbonic anhydrase activity in crotonyl-CoA carboxylase/reductase.

The conversion of CO2 by enzymes such as carbonic anhydrase or carboxylases plays a crucial role in many biological processes. However, in situ methods following the microscopic details of CO2 conversion at the active site are limited. Here, we used infrared spectroscopy to study the interaction of CO2, water, bicarbonate, and other reactants with ß-carbonic anhydrase from Escherichia coli (EcCA) and crotonyl-CoA carboxylase/reductase from Kitasatospora setae (KsCcr), two of the fastest CO2-converting enzymes in nature. Our data reveal that KsCcr possesses a so far unknown metal-independent CA-like activity. Site-directed mutagenesis of conserved active site residues combined with molecular dynamics simulations tracing CO2 distributions in the active site of KsCCr identify an 'activated' water molecule forming the hydroxyl anion that attacks CO2 and yields bicarbonate (HCO3-). Computer simulations also explain why substrate binding inhibits the anhydrase activity. Altogether, we demonstrate how in situ infrared spectroscopy combined with molecular dynamics simulations provides a simple yet powerful new approach to investigate the atomistic reaction mechanisms of different enzymes with CO2.

Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge.

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) a composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Conformational Dynamics of the Most Efficient Carboxylase Contributes to Efficient CO2 Fixation.

Crotonyl-CoA carboxylase/reductase (Ccr) is one of the fastest CO2 fixing enzymes and has become part of efficient artificial CO2-fixation pathways in vitro, paving the way for future applications. The underlying mechanism of its efficiency, however, is not yet completely understood. X-ray structures of different intermediates in the catalytic cycle reveal tetramers in a dimer of dimers configuration with two open and two closed active sites. Upon binding a substrate, this active site changes its conformation from the open state to the closed state. It is challenging to predict how these coupled conformational changes will alter the CO2 binding affinity to the reaction's active site. To determine whether the open or closed conformations of Ccr affect binding of CO2 to the active site, we performed all-atom molecular simulations of the various conformations of Ccr. The open conformation without a substrate showed the highest binding affinity. The CO2 binding sites are located near the catalytic relevant Asn81 and His365 residues and in an optimal position for CO2 fixation. Furthermore, they are unaffected by substrate binding, and CO2 molecules stay in these binding sites for a longer time. Longer times at these reactive binding sites facilitate CO2 fixation through the nucleophilic attack of the reactive enolate in the closed conformation. We previously demonstrated that the Asn81Leu variant cannot fix CO2. Simulations of the Asn81Leu variant explain the loss of activity through the removal of the Asn81 and His365 binding sites. Overall, our findings show that the conformational dynamics of the enzyme controls CO2 binding. Conformational changes in Ccr increase the level of CO2 in the open subunit before the substrate is bound, the active site closes, and the reaction starts. The full catalytic Ccr cycle alternates among CO2 addition, conformational change, and chemical reaction in the four subunits of the tetramer coordinated by communication between the two dimers.

Why Solvent Response Contributions to Solvation Free Energies Are Compatible with Ben-Naim's Theorem.

We resolve a seeming paradox arising from a common misinterpretation of Ben-Naim's theorem, which rests on the decomposition of the Hamiltonian of a molecular solute/solvent system into solute-solvent and solvent-solvent interactions. According to this theorem, the solvation entropy can also be decomposed into a solute-solvent term and a remaining solvent-solvent term that is commonly referred to as the solvent reorganization term. Crucially, the latter equals the average solvent-solvent interaction energy such that these two solvent-solvent terms cancel and thus do not change the total solvation free energy. This analytical result implies that changes in the solvent-solvent interactions cannot contribute to any thermodynamic driving force. The solvent reorganization term is often identified with the contribution of many-body solvent correlations to the solvation entropy, which seems to imply that these correlations, too, cannot contribute to solvation. However, recent calculations based on atomistic simulations of a solvated globular protein and spatially resolved mutual information expansions revealed substantial contributions of many-body solvent correlations to the solvation free energy, which are not canceled by the enthalpy change of the solvent. Here, we resolved this seeming contradiction and illustrate by two examples─a simple Ising model and a solvated Lennard-Jones particle─that the solvent reorganization entropy and the actual entropy contribution arising from many-body solvent correlations differ both conceptually and numerically. Whereas the solvent reorganization entropy in fact arises from both solvent-solvent as well as solute-solvent interactions and thus has no straightforward intuitive interpretation, the mutual information expansion permits an interpretation in terms of the entropy contribution of solvent-solvent correlations to the solvation free energy.

Structural conservation of antibiotic interaction with ribosomes.

The ribosome is a major target for clinically used antibiotics, but multidrug resistant pathogenic bacteria are making our current arsenal of antimicrobials obsolete. Here we present cryo-electron-microscopy structures of 17 distinct compounds from six different antibiotic classes bound to the bacterial ribosome at resolutions ranging from 1.6 to 2.2 Å. The improved resolution enables a precise description of antibiotic-ribosome interactions, encompassing solvent networks that mediate multiple additional interactions between the drugs and their target. Our results reveal a high structural conservation in the binding mode between antibiotics with the same scaffold, including ordered water molecules. Water molecules are visualized within the antibiotic binding sites that are preordered, become ordered in the presence of the drug and that are physically displaced on drug binding. Insight into RNA-ligand interactions will facilitate development of new antimicrobial agents, as well as other RNA-targeting therapies.

Uncertainties in Markov State Models of Small Proteins.

Markov state models are widely used to describe and analyze protein dynamics based on molecular dynamics simulations, specifically to extract functionally relevant characteristic time scales and motions. Particularly for larger biomolecules such as proteins, however, insufficient sampling is a notorious concern and often the source of large uncertainties that are difficult to quantify. Furthermore, there are several other sources of uncertainty, such as choice of the number of Markov states and lag time, choice and parameters of dimension reduction preprocessing step, and uncertainty due to the limited number of observed transitions; the latter is often estimated via a Bayesian approach. Here, we quantified and ranked all of these uncertainties for four small globular test proteins. We found that the largest uncertainty is due to insufficient sampling and initially increases with the total trajectory length T up to a critical tipping point, after which it decreases as 1/T, thus providing guidelines for how much sampling is required for given accuracy. We also found that single long trajectories yielded better sampling accuracy than many shorter trajectories starting from the same structure. In comparison, the remaining sources of the above uncertainties are generally smaller by a factor of about 5, rendering them less of a concern but certainly not negligible. Importantly, the Bayes uncertainty, commonly used as the only uncertainty estimate, captures only a relatively small part of the true uncertainty, which is thus often drastically underestimated.

Discrimination between cyclic nucleotides in a cyclic nucleotide-gated ion channel.

Cyclic nucleotide-gated ion channels are crucial in many physiological processes such as vision and pacemaking in the heart. SthK is a prokaryotic homolog with high sequence and structure similarities to hyperpolarization-activated and cyclic nucleotide-modulated and cyclic nucleotide-gated channels, especially at the level of the cyclic nucleotide binding domains (CNBDs). Functional measurements showed that cyclic adenosine monophosphate (cAMP) is a channel activator while cyclic guanosine monophosphate (cGMP) barely leads to pore opening. Here, using atomic force microscopy single-molecule force spectroscopy and force probe molecular dynamics simulations, we unravel quantitatively and at the atomic level how CNBDs discriminate between cyclic nucleotides. We find that cAMP binds to the SthK CNBD slightly stronger than cGMP and accesses a deep-bound state that a cGMP-bound CNBD cannot reach. We propose that the deep binding of cAMP is the discriminatory state that is essential for cAMP-dependent channel activation.

Molecular mechanism and energetics of coupling between substrate binding and product release in the F1-ATPase catalytic cycle.

F1-ATPase is a motor protein that couples the rotation of its rotary [Formula: see text] subunit with ATP synthesis or hydrolysis. Single-molecule experiments indicate that nucleotide binding and release events occur almost simultaneously during the synthesis cycle, allowing the energy gain due to spontaneous binding of ADP to one catalytic [Formula: see text] subunit to be directly harnessed for driving the release of ATP from another rather than being dissipated as heat. Here, we examine the unknown mechanism of this coupling that is critical for an exceptionally high mechanochemical efficiency of F1-ATPase by means of all-atom free-energy simulations. We find that nondissipative and kinetically fast progression of the motor in the synthesis direction requires a concerted conformational change involving the closure of the ADP-binding [Formula: see text] subunit followed by the gradual opening of the ATP-releasing [Formula: see text] subunit over the course of the 30 to 40° rotary substep of the [Formula: see text] subunit. This rotary substep, preceding the ATP-dependent metastable state, allows for the recovery of a large portion of the ADP binding energy in the conformation of ATP-bound [Formula: see text] that gradually adopts the low-affinity conformation, captured also by the recent cryo-EM structure of this elusive state. The release of ATP from this nearly open conformation leads to its further opening, which enables the progression of the motor to the next catalytic metastable state. Our simulations explain this energy conversion mechanism in terms of intersubunit and ligand-protein interactions.

Simulation of Complex Biomolecular Systems: The Ribosome Challenge.

Large biomolecular systems are at the heart of many essential cellular processes. The dynamics and energetics of an increasing number of these systems are being studied by computer simulations. Pushing the limits of length- and timescales that can be accessed by current hard- and software has expanded the ability to describe biomolecules at different levels of detail. We focus in this review on the ribosome, which exemplifies the close interplay between experiment and various simulation approaches, as a particularly challenging and prototypic nanomachine that is pivotal to cellular biology due to its central role in translation. We sketch widely used simulation methods and demonstrate how the combination of simulations and experiments advances our understanding of the function of the translation apparatus based on fundamental physics.

Intersubunit Coupling Enables Fast CO2-Fixation by Reductive Carboxylases.

Enoyl-CoA carboxylases/reductases (ECRs) are some of the most efficient CO2-fixing enzymes described to date. However, the molecular mechanisms underlying the extraordinary catalytic activity of ECRs on the level of the protein assembly remain elusive. Here we used a combination of ambient-temperature X-ray free electron laser (XFEL) and cryogenic synchrotron experiments to study the structural organization of the ECR from Kitasatospora setae. The K. setae ECR is a homotetramer that differentiates into a pair of dimers of open- and closed-form subunits in the catalytically active state. Using molecular dynamics simulations and structure-based mutagenesis, we show that catalysis is synchronized in the K. setae ECR across the pair of dimers. This conformational coupling of catalytic domains is conferred by individual amino acids to achieve high CO2-fixation rates. Our results provide unprecedented insights into the dynamic organization and synchronized inter- and intrasubunit communications of this remarkably efficient CO2-fixing enzyme during catalysis.

Nanomechanics combined with HDX reveals allosteric drug binding sites of CFTR NBD1.

Cystic fibrosis (CF) is a frequent genetic disease in Caucasians that is caused by the deletion of F508 (ΔF508) in the nucleotide binding domain 1 (NBD1) of the CF transmembrane conductance regulator (CFTR). The ΔF508 compromises the folding energetics of the NBD1, as well as the folding of three other CFTR domains. Combination of FDA approved corrector molecules can efficiently but incompletely rescue the ΔF508-CFTR folding and stability defect. Thus, new pharmacophores that would reinstate the wild-type-like conformational stability of the ΔF508-NBD1 would be highly beneficial. The most prominent molecule, 5-bromoindole-3-acetic acid (BIA) that can thermally stabilize the NBD1 has low potency and efficacy. To gain insights into the NBD1 (un)folding dynamics and BIA binding site localization, we combined molecular dynamics (MD) simulations, atomic force spectroscopy (AFM) and hydrogen-deuterium exchange (HDX) experiments. We found that the NBD1 α-subdomain with three adjacent strands from the ß-subdomain plays an important role in early folding steps, when crucial non-native interactions are formed via residue F508. Our AFM and HDX experiments showed that BIA associates with this α-core region and increases the resistance of the ΔF508-NBD1 against mechanical unfolding, a phenomenon that could be exploited in future developments of folding correctors.

Estimating ruggedness of free-energy landscapes of small globular proteins from principal component analysis of molecular dynamics trajectories.

The internal dynamics of biomolecules, and hence their function, is governed by the structure of their free-energy landscape. Early flash-photolysis experiments on myoglobin suggested that the free-energy landscapes of proteins are hierarchically structured, with a characteristic distribution of free-energy barriers which gives rise to anomalous diffusion. Analytical results have been derived for one-dimensional or high-dimensional hierarchical free-energy landscapes. Recent improvements in methods and computer performance enable generating sufficiently long molecular dynamics (MD) trajectories to extract dynamics information covering many orders of magnitude, such that the broad distributions of energy barriers of proteins become accessible to quantitative studies of intermediate dimensions. In this work, we present a nonequilibrium method to estimate barrier height distributions from microsecond-long MD simulations. It infers barrier height distributions from anomalous diffusion exponents derived from principal component analysis and by comparison to simple hierarchical lattice models. These models are d-dimensional lattices of states separated by free-energy barriers, the heights of which are distributed as p(ΔG)=1/γexp(-ΔG/γ). The parameter γ quantifies the "ruggedness" of the free-energy landscape in such models. We show that both parameters, i.e., ruggedness and effective dimensionality d, can be inferred from anomalous diffusion exponents. Assuming a similar dependency of anomalous diffusion exponents on γ and d for proteins, we estimate the ruggedness of the free-energy landscapes of 500 small, single-domain globular proteins between 15 and 20 kT per dimension with an estimated accuracy of 4.2 kT and dimensionality between 40 and 60 with an estimated accuracy of 10 dimensions. Remarkably, neither effective dimensionality nor the ruggedness correlates with protein size and both ruggedness and effective dimensionality are much smaller than the scatter of protein sizes. From this finding, we conclude that these two properties of the free-energy landscape of a protein are rather adapted to the particular function of each single protein and that, quite generally, are functionally relevant for globular proteins.

Effects of cryo-EM cooling on structural ensembles.

Structure determination by cryo electron microscopy (cryo-EM) provides information on structural heterogeneity and ensembles at atomic resolution. To obtain cryo-EM images of macromolecules, the samples are first rapidly cooled down to cryogenic temperatures. To what extent the structural ensemble is perturbed during cooling is currently unknown. Here, to quantify the effects of cooling, we combined continuum model calculations of the temperature drop, molecular dynamics simulations of a ribosome complex before and during cooling with kinetic models. Our results suggest that three effects markedly contribute to the narrowing of the structural ensembles: thermal contraction, reduced thermal motion within local potential wells, and the equilibration into lower free-energy conformations by overcoming separating free-energy barriers. During cooling, barrier heights below 10 kJ/mol were found to be overcome, which is expected to reduce B-factors in ensembles imaged by cryo-EM. Our approach now enables the quantification of the heterogeneity of room-temperature ensembles from cryo-EM structures.

GROMACS in the Cloud: A Global Supercomputer to Speed Up Alchemical Drug Design.

We assess costs and efficiency of state-of-the-art high-performance cloud computing and compare the results to traditional on-premises compute clusters. Our use case is atomistic simulations carried out with the GROMACS molecular dynamics (MD) toolkit with a particular focus on alchemical protein-ligand binding free energy calculations. We set up a compute cluster in the Amazon Web Services (AWS) cloud that incorporates various different instances with Intel, AMD, and ARM CPUs, some with GPU acceleration. Using representative biomolecular simulation systems, we benchmark how GROMACS performs on individual instances and across multiple instances. Thereby we assess which instances deliver the highest performance and which are the most cost-efficient ones for our use case. We find that, in terms of total costs, including hardware, personnel, room, energy, and cooling, producing MD trajectories in the cloud can be about as cost-efficient as an on-premises cluster given that optimal cloud instances are chosen. Further, we find that high-throughput ligand-screening can be accelerated dramatically by using global cloud resources. For a ligand screening study consisting of 19 872 independent simulations or ∼200 µs of combined simulation trajectory, we made use of diverse hardware available in the cloud at the time of the study. The computations scaled-up to reach peak performance using more than 4 000 instances, 140 000 cores, and 3 000 GPUs simultaneously. Our simulation ensemble finished in about 2 days in the cloud, while weeks would be required to complete the task on a typical on-premises cluster consisting of several hundred nodes.

Bending-torsional elasticity and energetics of the plus-end microtubule tip.

SignificanceThe mechanochemical basis of microtubule growth, which is essential for the normal function and division of eukaryotic cells, has remained elusive and controversial, despite extensive work. In particular, recent findings have created the paradox that the microtubule plus-end tips look very similar during both growing and shrinking phases, thereby challenging the traditional textbook picture. Our large-scale atomistic simulations resolve this paradox and explain microtubule growth and shrinkage dynamics as a process governed by energy barriers between protofilament conformations, the heights of which are in turn fine-tuned by different nucleotide states, thus implementing an information-driven Brownian ratchet.

Folding of VemP into translation-arresting secondary structure is driven by the ribosome exit tunnel.

The ribosome is a fundamental biomolecular complex that synthesizes proteins in cells. Nascent proteins emerge from the ribosome through a tunnel, where they may interact with the tunnel walls or small molecules such as antibiotics. These interactions can cause translational arrest with notable physiological consequences. Here, we studied the arrest caused by the regulatory peptide VemP, which is known to form α-helices inside the ribosome tunnel near the peptidyl transferase center under specific conditions. We used all-atom molecular dynamics simulations of the entire ribosome and circular dichroism spectroscopy to study the driving forces of helix formation and how VemP causes the translational arrest. To that aim, we compared VemP dynamics in the ribosome tunnel with its dynamics in solution. We show that the VemP peptide has a low helical propensity in water and that the propensity is higher in mixtures of water and trifluorethanol. We propose that helix formation within the ribosome is driven by the interactions of VemP with the tunnel and that a part of VemP acts as an anchor. This anchor might slow down VemP progression through the tunnel enabling α-helix formation, which causes the elongation arrest.

Small-sample limit of the Bennett acceptance ratio method and the variationally derived intermediates.

Free energy calculations based on atomistic Hamiltonians provide microscopic insight into the thermodynamic driving forces of biophysical or condensed matter systems. Many approaches use intermediate Hamiltonians interpolating between the two states for which the free energy difference is calculated. The Bennett acceptance ratio (BAR) and variationally derived intermediates (VI) methods are optimal estimator and intermediate states in that the mean-squared error of free energy calculations based on independent sampling is minimized. However, BAR and VI have been derived based on several approximations that do not hold for very few sample points. Analyzing one-dimensional test systems, we show that in such cases BAR and VI are suboptimal and that established uncertainty estimates are inaccurate. Whereas for VI to become optimal, less than seven samples per state suffice in all cases; for BAR the required number increases unboundedly with decreasing configuration space densities overlap of the end states. We show that for BAR, the required number of samples is related to the overlap through an inverse power law. Because this relation seems to hold universally and almost independent of other system properties, these findings can guide the proper choice of estimators for free energy calculations.