Atoms to Phenotypes: Molecular Design Principles of Cellular Energy Metabolism.

We report a 100-million atom-scale model of an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium, that reveals the cascade of energy conversion steps culminating in the generation of ATP from sunlight. Molecular dynamics simulations of this vesicle elucidate how the integral membrane complexes influence local curvature to tune photoexcitation of pigments. Brownian dynamics of small molecules within the chromatophore probe the mechanisms of directional charge transport under various pH and salinity conditions. Reproducing phenotypic properties from atomistic details, a kinetic model evinces that low-light adaptations of the bacterium emerge as a spontaneous outcome of optimizing the balance between the chromatophore's structural integrity and robust energy conversion. Parallels are drawn with the more universal mitochondrial bioenergetic machinery, from whence molecular-scale insights into the mechanism of cellular aging are inferred. Together, our integrative method and spectroscopic experiments pave the way to first-principles modeling of whole living cells.

Non-adiabatic molecular dynamics simulations provide new insights into the exciton transfer in the Fenna-Matthews-Olson complex.

A trajectory surface hopping approach, which uses machine learning to speed up the most time-consuming steps, has been adopted to investigate the exciton transfer in light-harvesting systems. The present neural networks achieve high accuracy in predicting both Coulomb couplings and excitation energies. The latter are predicted taking into account the environment of the pigments. Direct simulation of exciton dynamics through light-harvesting complexes on significant time scales is usually challenging due to the coupled motion of nuclear and electronic degrees of freedom in these rather large systems containing several relatively large pigments. In the present approach, however, we are able to evaluate a statistically significant number of non-adiabatic molecular dynamics trajectories with respect to exciton delocalization and exciton paths. The formalism is applied to the Fenna-Matthews-Olson complex of green sulfur bacteria, which transfers energy from the light-harvesting chlorosome to the reaction center with astonishing efficiency. The system has been studied experimentally and theoretically for decades. In total, we were able to simulate non-adiabatically more than 30 ns, sampling also the relevant space of parameters within their uncertainty. Our simulations show that the driving force supplied by the energy landscape resulting from electrostatic tuning is sufficient to funnel the energy towards site 3, from where it can be transferred to the reaction center. However, the high efficiency of transfer within a picosecond timescale can be attributed to the rather unusual properties of the BChl a molecules, resulting in very low inner and outer-sphere reorganization energies, not matched by any other organic molecule, e.g., used in organic electronics. A comparison with electron and exciton transfer in organic materials is particularly illuminating, suggesting a mechanism to explain the comparably high transfer efficiency.

Fast prediction of antibiotic permeability through membrane channels using Brownian dynamics.

The efficient permeation across the Gram-negative bacterial membrane is an important step in the overall process of antibacterial action of a molecule and the one that has posed a significant hurdle on the way toward approved antibiotics. Predicting the permeability for a large library of molecules and assessing the effect of different molecular transformations on permeation rates of a given molecule is critical to the development of effective antibiotics. We present a computational approach for obtaining estimates of molecular permeability through a porin channel in a matter of hours using a Brownian dynamics approach. The fast sampling using a temperature acceleration scheme enables the approximate estimation of permeability using the inhomogeneous solubility diffusion model. Although the method is a significant approximation to similar all-atom approaches tested previously, we show that the present approach predicts permeabilities that correlate fairly well with the respective experimental permeation rates from liposome swelling experiments and accumulation rates from antibiotic accumulation assays, and is significantly, i.e., about 14 times, faster compared with a previously reported approach. The possible applications of the scheme in high-throughput screening for fast permeators are discussed.

Recent progress in atomistic modeling of light-harvesting complexes: a mini review.

In this mini review, we focus on recent advances in the atomistic modeling of biological light-harvesting (LH) complexes. Because of their size and sophisticated electronic structures, multiscale methods are required to investigate the dynamical and spectroscopic properties of such complexes. The excitation energies, in this context also known as site energies, excitonic couplings, and spectral densities are key quantities which usually need to be extracted to be able to determine the exciton dynamics and spectroscopic properties. The recently developed multiscale approach based on the numerically efficient density functional tight-binding framework followed by excited state calculations has been shown to be superior to the scheme based on pure classical molecular dynamics simulations. The enhanced approach, which improves the description of the internal vibrational dynamics of the pigment molecules, yields spectral densities in good agreement with the experimental counterparts for various bacterial and plant LH systems. Here, we provide a brief overview of those results and described the theoretical foundation of the multiscale protocol.

Conformational Dynamics of Loop L3 in OmpF: Implications toward Antibiotic Translocation and Voltage Gating.

In the present work, we delineate the molecular mechanism of a bulky antibiotic permeating through a bacterial channel and uncover the role of conformational dynamics of the constriction loop in this process. Using the temperature accelerated sliced sampling approach, we shed light onto the dynamics of the L3 loop, in particular the F118 to S125 segment, at the constriction regions of the OmpF porin. We complement the findings with single channel electrophysiology experiments and applied-field simulations, and we demonstrate the role of hydrogen-bond stabilization in the conformational dynamics of the L3 loop. A molecular mechanism of permeation is put forward wherein charged antibiotics perturb the network of stabilizing hydrogen-bond interactions and induce conformational changes in the L3 segment, thereby aiding the accommodation and permeation of bulky antibiotic molecules across the constriction region. We complement the findings with single channel electrophysiology experiments and demonstrate the importance of the hydrogen-bond stabilization in the conformational dynamics of the L3 loop. The generality of the present observations and experimental results regarding the L3 dynamics enables us to identify this L3 segment as the source of gating. We propose a mechanism of OmpF gating that is in agreement with previous experimental data that showed the noninfluence of cysteine double mutants that tethered the L3 tip to the barrel wall on the OmpF gating behavior. The presence of similar loop stabilization networks in porins of other clinically relevant pathogens suggests that the conformational dynamics of the constriction loop is possibly of general importance in the context of antibiotic permeation through porins.

How to Enter a Bacterium: Bacterial Porins and the Permeation of Antibiotics.

Despite tremendous successes in the field of antibiotic discovery seen in the previous century, infectious diseases have remained a leading cause of death. More specifically, pathogenic Gram-negative bacteria have become a global threat due to their extraordinary ability to acquire resistance against any clinically available antibiotic, thus urging for the discovery of novel antibacterial agents. One major challenge is to design new antibiotics molecules able to rapidly penetrate Gram-negative bacteria in order to achieve a lethal intracellular drug accumulation. Protein channels in the outer membrane are known to form an entry route for many antibiotics into bacterial cells. Up until today, there has been a lack of simple experimental techniques to measure the antibiotic uptake and the local concentration in subcellular compartments. Hence, rules for translocation directly into the various Gram-negative bacteria via the outer membrane or via channels have remained elusive, hindering the design of new or the improvement of existing antibiotics. In this review, we will discuss the recent progress, both experimentally as well as computationally, in understanding the structure-function relationship of outer-membrane channels of Gram-negative pathogens, mainly focusing on the transport of antibiotics.

Correction: Benchmark and performance of long-range corrected time-dependent density functional tight binding (LC-TD-DFTB) on rhodopsins and light-harvesting complexes.

Correction for 'Benchmark and performance of long-range corrected time-dependent density functional tight binding (LC-TD-DFTB) on rhodopsins and light-harvesting complexes' by Beatrix M. Bold et al., Phys. Chem. Chem. Phys., 2020, 22, 10500-10518, https://doi.org/10.1039/C9CP05753F.

Structural basis for nutrient acquisition by dominant members of the human gut microbiota.

The human large intestine is populated by a high density of microorganisms, collectively termed the colonic microbiota, which has an important role in human health and nutrition. The survival of microbiota members from the dominant Gram-negative phylum Bacteroidetes depends on their ability to degrade dietary glycans that cannot be metabolized by the host. The genes encoding proteins involved in the degradation of specific glycans are organized into co-regulated polysaccharide utilization loci, with the archetypal locus sus (for starch utilisation system) encoding seven proteins, SusA-SusG. Glycan degradation mainly occurs intracellularly and depends on the import of oligosaccharides by an outer membrane protein complex composed of an extracellular SusD-like lipoprotein and an integral membrane SusC-like TonB-dependent transporter. The presence of the partner SusD-like lipoprotein is the major feature that distinguishes SusC-like proteins from previously characterized TonB-dependent transporters. Many sequenced gut Bacteroides spp. encode over 100 SusCD pairs, of which the majority have unknown functions and substrate specificities. The mechanism by which extracellular substrate binding by SusD proteins is coupled to outer membrane passage through their cognate SusC transporter is unknown. Here we present X-ray crystal structures of two functionally distinct SusCD complexes purified from Bacteroides thetaiotaomicron and derive a general model for substrate translocation. The SusC transporters form homodimers, with each ß-barrel protomer tightly capped by SusD. Ligands are bound at the SusC-SusD interface in a large solvent-excluded cavity. Molecular dynamics simulations and single-channel electrophysiology reveal a 'pedal bin' mechanism, in which SusD moves away from SusC in a hinge-like fashion in the absence of ligand to expose the substrate-binding site to the extracellular milieu. These data provide mechanistic insights into outer membrane nutrient import by members of the microbiota, an area of major importance for understanding human-microbiota symbiosis.

Machine-learned correction to ensemble-averaged wave packet dynamics.

For a detailed understanding of many processes in nature involving, for example, energy or electron transfer, the theory of open quantum systems is of key importance. For larger systems, an accurate description of the underlying quantum dynamics is still a formidable task, and, hence, approaches employing machine learning techniques have been developed to reduce the computational effort of accurate dissipative quantum dynamics. A downside of many previous machine learning methods is that they require expensive numerical training datasets for systems of the same size as the ones they will be employed on, making them unfeasible to use for larger systems where those calculations are still too expensive. In this work, we will introduce a new method that is implemented as a machine-learned correction term to the so-called Numerical Integration of Schrödinger Equation (NISE) approach. It is shown that this term can be trained on data from small systems where accurate quantum methods are still numerically feasible. Subsequently, the NISE scheme, together with the new machine-learned correction, can be used to determine the dissipative quantum dynamics for larger systems. Furthermore, we show that the newly proposed machine-learned correction outperforms a previously handcrafted one, which, however, improves the results already considerably.

Identification of Single Amino Acid Chiral and Positional Isomers Using an Electrostatically Asymmetric Nanopore.

Chirality is essential in nearly all biological organizations and chemical reactions but is rarely considered due to technical limitations in identifying L/D isomerization. Using OmpF, a membrane channel from Escherichia coli with an electrostatically asymmetric constriction zone, allows discriminating chiral amino acids in a single peptide. The heterogeneous distribution of charged residues in OmpF causes a strong lateral electrostatic field at the constriction. This laterally asymmetric constriction zone forces the sidechains of the peptides to specific orientations within OmpF, causing distinct ionic current fluctuations. Using statistical analysis of the respective ionic current variations allows distinguishing the presence and position of a single amino acid with different chiralities. To explore potential applications, the disease-related peptide ß-Amyloid and its d-Asp1 isoform and a mixture of the icatibant peptide drug (HOE 140) and its d-Ser7 mutant have been discriminated. Both chiral isomers were not applicable to be distinguished by mass spectroscopy approaches. These findings highlight a novel sensing mechanism for identifying single amino acids in single peptides and even for achieving single-molecule protein sequencing.

Spectral densities and absorption spectra of the core antenna complex CP43 from photosystem II.

Besides absorbing light, the core antenna complex CP43 of photosystem II is of great importance in transferring excitation energy from the antenna complexes to the reaction center. Excitation energies, spectral densities, and linear absorption spectra of the complex have been evaluated by a multiscale approach. In this scheme, quantum mechanics/molecular mechanics molecular dynamics simulations are performed employing the parameterized density functional tight binding (DFTB) while the time-dependent long-range-corrected DFTB scheme is applied for the excited state calculations. The obtained average spectral density of the CP43 complex shows a very good agreement with experimental results. Moreover, the excitonic Hamiltonian of the system along with the computed site-dependent spectral densities was used to determine the linear absorption. While a Redfield-like approximation has severe shortcomings in dealing with the CP43 complex due to quasi-degenerate states, the non-Markovian full second-order cumulant expansion formalism is able to overcome the drawbacks. Linear absorption spectra were obtained, which show a good agreement with the experimental counterparts at different temperatures. This study once more emphasizes that by combining diverse techniques from the areas of molecular dynamics simulations, quantum chemistry, and open quantum systems, it is possible to obtain first-principle results for photosynthetic complexes, which are in accord with experimental findings.

Coherent and incoherent contributions to molecular electron transport.

We numerically isolate the limits of validity of the Landauer approximation to describe charge transport along molecular junctions in condensed phase environments. To do so, we contrast Landauer with exact time-dependent non-equilibrium Green's function quantum transport computations in a two-site molecular junction subject to exponentially correlated noise. Under resonant transport conditions, we find Landauer accuracy to critically depend on intramolecular interactions. By contrast, under nonresonant conditions, the emergence of incoherent transport routes that go beyond Landauer depends on charging and discharging processes at the electrode-molecule interface. In both cases, decreasing the rate of charge exchange between the electrodes and molecule and increasing the interaction strength with the thermal environment cause Landauer to become less accurate. The results are interpreted from a time-dependent perspective where the noise prevents the junction from achieving steady-state and from a fully quantum perspective where the environment introduces dephasing in the dynamics. Using these results, we analyze why the Landauer approach is so useful to understand experiments, isolate regimes where it fails, and propose schemes to chemically manipulate the degree of transport coherence.

Multiscale QM/MM molecular dynamics simulations of the trimeric major light-harvesting complex II.

Photosynthetic processes are driven by sunlight. Too little of it and the photosynthetic machinery cannot produce the reductive power to drive the anabolic pathways. Too much sunlight and the machinery can get damaged. In higher plants, the major Light-Harvesting Complex (LHCII) efficiently absorbs the light energy, but can also dissipate it when in excess (quenching). In order to study the dynamics related to the quenching process but also the exciton dynamics in general, one needs to accurately determine the so-called spectral density which describes the coupling between the relevant pigment modes and the environmental degrees of freedom. To this end, Born-Oppenheimer molecular dynamics simulations in a quantum mechanics/molecular mechanics (QM/MM) fashion utilizing the density functional based tight binding (DFTB) method have been performed for the ground state dynamics. Subsequently, the time-dependent extension of the long-range-corrected DFTB scheme has been employed for the excited state calculations of the individual chlorophyll-a molecules in the LHCII complex. The analysis of this data resulted in spectral densities showing an astonishing agreement with the experimental counterpart in this rather large system. This consistency with an experimental observable also supports the accuracy, robustness, and reliability of the present multi-scale scheme. To the best of our knowledge, this is the first theoretical attempt on this large complex system is ever made to accurately simulate the spectral density. In addition, the resulting spectral densities and site energies were used to determine the exciton transfer rate within a special pigment pair consisting of a chlorophyll-a and a carotenoid molecule which is assumed to play a role in the balance between the light harvesting and quenching modes.

Time-dependent atomistic simulations of the CP29 light-harvesting complex.

Light harvesting as the first step in photosynthesis is of prime importance for life on earth. For a theoretical description of photochemical processes during light harvesting, spectral densities are key quantities. They serve as input functions for modeling the excitation energy transfer dynamics and spectroscopic properties. Herein, a recently developed procedure is applied to determine the spectral densities of the pigments in the minor antenna complex CP29 of photosystem II, which has recently gained attention because of its active role in non-photochemical quenching processes in higher plants. To this end, the density functional-based tight binding (DFTB) method has been employed to enable simulation of the ground state dynamics in a quantum-mechanics/molecular mechanics (QM/MM) scheme for each chlorophyll pigment. Subsequently, the time-dependent extension of the long-range corrected DFTB approach has been used to obtain the excitation energy fluctuations along the ground-state trajectories also in a QM/MM setting. From these results, the spectral densities have been determined and compared for different force fields and to spectral densities from other light-harvesting complexes. In addition, time-dependent and time-independent excitonic Hamiltonians of the system have been constructed and applied to the determination of absorption spectra as well as exciton dynamics.

Large-Peptide Permeation Through a Membrane Channel: Understanding Protamine Translocation Through CymA from Klebsiella Oxytoca*.

Quantifying the passage of the large peptide protamine (Ptm) across CymA, a passive channel for cyclodextrin uptake, is in the focus of this study. Using a reporter-pair-based fluorescence membrane assay we detected the entry of Ptm into liposomes containing CymA. The kinetics of the Ptm entry was independent of its concentration suggesting that the permeation through CymA is the rate-limiting factor. Furthermore, we reconstituted single CymA channels into planar lipid bilayers and recorded the ion current fluctuations in the presence of Ptm. To this end, we were able to resolve the voltage-dependent entry of single Ptm peptide molecules into the channel. Extrapolation to zero voltage revealed about 1-2 events per second and long dwell times, in agreement with the liposome study. Applied-field and steered molecular dynamics simulations added an atomistic view of the permeation events. It can be concluded that a concentration gradient of 1 µm Ptm leads to a translocation rate of about one molecule per second and per channel.

Computational Modeling of Ion Transport in Bulk and through a Nanopore Using the Drude Polarizable Force Field.

In the past two decades, molecular dynamics simulations have become the method of choice for elucidating the transport mechanisms of ions through various membrane channels. Often, these simulations heavily rely on classical nonpolarizable force fields (FFs), which lack electronic polarizability in the treatment of the electrostatics. The recent advancements in the Drude polarizable FF lead to a complete set of parameters for water, ions, protein, and lipids, allowing for a more realistic modeling of membrane proteins. However, the quality of these Drude FFs remains untested for such systems. Here, we examine the quality of this FF set in two ways, i.e., (i) in simple ionic aqueous solution simulations and (ii) in more complex membrane channel simulations. First, the aqueous solutions of KCl, NaCl, MgCl2, and CaCl2 salts are simulated using the polarizable Drude and the nonpolarizable CHARMM36 FFs. The bulk conductivity has been estimated for both FF sets using applied-field simulations for several concentrations and temperatures in the case of all investigated salts and compared to experimental findings. An excellent improvement in the ability of the Drude FF to reproduce the experimental bulk conductivities for KCl, NaCl, and MgCl2 solutions can be observed but not in the case of CaCl2. Moreover, the outer membrane channel OmpC from the bacterium Escherichia coli has been employed to examine the ability of the polarizable and nonpolarizable FFs to reproduce ion transport-related quantities known from experiment. Unbiased and applied-field simulations have been performed in the presence of KCl using both FF sets. Unlike for the bulk systems of aqueous salt solutions, it has been found that the Drude FF is not accurate in modeling KCl transport properties across the OmpC porin.

Flexible Fitting of Small Molecules into Electron Microscopy Maps Using Molecular Dynamics Simulations with Neural Network Potentials.

Despite significant advances in resolution, the potential for cryo-electron microscopy (EM) to be used in determining the structures of protein-drug complexes remains unrealized. Determination of accurate structures and coordination of bound ligands necessitates simultaneous fitting of the models into the density envelopes, exhaustive sampling of the ligand geometries, and, most importantly, concomitant rearrangements in the side chains to optimize the binding energy changes. In this article, we present a flexible-fitting pipeline where molecular dynamics flexible fitting (MDFF) is used to refine structures of protein-ligand complexes from 3 to 5 Å electron density data. Enhanced sampling is employed to explore the binding pocket rearrangements. To provide a model that can accurately describe the conformational dynamics of the chemically diverse set of small-molecule drugs inside MDFF, we use QM/MM and neural-network potential (NNP)/MM models of protein-ligand complexes, where the ligand is represented using the QM or NNP model, and the protein is represented using established molecular mechanical force fields (e.g., CHARMM). This pipeline offers structures commensurate to or better than recently submitted high-resolution cryo-EM or X-ray models, even when given medium to low-resolution data as input. The use of the NNPs makes the algorithm more robust to the choice of search models, offering a radius of convergence of 6.5 Å for ligand structure determination. The quality of the predicted structures was also judged by density functional theory calculations of ligand strain energy. This strain potential energy is found to systematically decrease with better fitting to density and improved ligand coordination, indicating correct binding interactions. A computationally inexpensive protocol for computing strain energy is reported as part of the model analysis protocol that monitors both the ligand fit as well as model quality.

Benchmark and performance of long-range corrected time-dependent density functional tight binding (LC-TD-DFTB) on rhodopsins and light-harvesting complexes.

The chromophores of rhodopsins (Rh) and light-harvesting (LH) complexes still represent a major challenge for a quantum chemical description due to their size and complex electronic structure. Since gradient corrected and hybrid density functional approaches have been shown to fail for these systems, only range-separated functionals seem to be a promising alternative to the more time consuming post-Hartree-Fock approaches. For extended sampling of optical properties, however, even more approximate approaches are required. Recently, a long-range corrected (LC) functional has been implemented into the efficient density functional tight binding (DFTB) method, allowing to sample the excited states properties of chromophores embedded into proteins using quantum mechanical/molecular mechanical (QM/MM) with the time-dependent (TD) DFTB approach. In the present study, we assess the accuracy of LC-TD-DFT and LC-TD-DFTB for rhodopsins (bacteriorhodopsin (bR) and pharaonis phoborhodopsin (ppR)) and LH complexes (light-harvesting complex II (LH2) and Fenna-Matthews-Olson (FMO) complex). This benchmark study shows the improved description of the color tuning parameters compared to standard DFT functionals. In general, LC-TD-DFTB can exhibit a similar performance as the corresponding LC functionals, allowing a reliable description of excited states properties at significantly reduced cost. The two chromophores investigated here pose complementary challenges: while huge sensitivity to external field perturbation (color tuning) and charge transfer excitations are characteristic for the retinal chromophore, the multi-chromophoric character of the LH complexes emphasizes a correct description of inter-chromophore couplings, giving less importance to color tuning. None of the investigated functionals masters both systems simultaneously with satisfactory accuracy. LC-TD-DFTB, at the current stage, although showing a systematic improvement compared to TD-DFTB cannot be recommended for studying color tuning in retinal proteins, similar to some of the LC-DFT functionals, because the response to external fields is still too weak. For sampling of LH-spectra, however, LC-TD-DFTB is a viable tool, allowing to efficiently sample absorption energies, as shown for three different LH complexes. As the calculations indicate, geometry optimization may overestimate the importance of local minima, which may be averaged over when using trajectories. Fast quantum chemical approaches therefore may allow for a direct sampling of spectra in the near future.

Fosfomycin Permeation through the Outer Membrane Porin OmpF.

Fosfomycin is a frequently prescribed drug in the treatment of acute urinary tract infections. It enters the bacterial cytoplasm and inhibits the biosynthesis of peptidoglycans by targeting the MurA enzyme. Despite extensive pharmacological studies and clinical use, the permeability of fosfomycin across the bacterial outer membrane is largely unexplored. Here, we investigate the fosfomycin permeability across the outer membrane of Gram-negative bacteria by electrophysiology experiments as well as by all-atom molecular dynamics simulations including free-energy and applied-field techniques. Notably, in an electrophysiological zero-current assay as well as in the molecular simulations, we found that fosfomycin can rapidly permeate the abundant Escherichia coli porin OmpF. Furthermore, two triple mutants in the constriction region of the porin have been investigated. The permeation rates through these mutants are slightly lower than that of the wild type but fosfomycin can still permeate. Altogether, this work unravels molecular details of fosfomycin permeation through the outer membrane porin OmpF of E. coli and moreover provides hints for understanding the translocation of phosphonic acid antibiotics through other outer membrane pores.

Chebyshev hierarchical equations of motion for systems with arbitrary spectral densities and temperatures.

The time evolution in open quantum systems, such as a molecular aggregate in contact with a thermal bath, still poses a complex and challenging problem. The influence of the thermal noise can be treated using a plethora of schemes, several of which decompose the corresponding correlation functions in terms of weighted sums of exponential functions. One such scheme is based on the hierarchical equations of motion (HEOM), which is built using only certain forms of bath correlation functions. In the case where the environment is described by a complex spectral density or is at a very low temperature, approaches utilizing the exponential decomposition become very inefficient. Here, we utilize an alternative decomposition scheme for the bath correlation function based on Chebyshev polynomials and Bessel functions to derive a HEOM approach up to an arbitrary order in the environmental coupling. These hierarchical equations are similar in structure to the popular exponential HEOM scheme, but are formulated using the derivatives of the Bessel functions. The proposed scheme is tested up to the fourth order in perturbation theory for a two-level system and compared to benchmark calculations for the case of zero-temperature quantum Ohmic and super-Ohmic noise. Furthermore, the benefits and shortcomings of the present Chebyshev-based hierarchical equations are discussed.