A Non-canonical Voltage-Sensing Mechanism Controls Gating in K2P K(+) Channels.

Two-pore domain (K2P) K(+) channels are major regulators of excitability that endow cells with an outwardly rectifying background "leak" conductance. In some K2P channels, strong voltage-dependent activation has been observed, but the mechanism remains unresolved because they lack a canonical voltage-sensing domain. Here, we show voltage-dependent gating is common to most K2P channels and that this voltage sensitivity originates from the movement of three to four ions into the high electric field of an inactive selectivity filter. Overall, this ion-flux gating mechanism generates a one-way "check valve" within the filter because outward movement of K(+) induces filter opening, whereas inward movement promotes inactivation. Furthermore, many physiological stimuli switch off this flux gating mode to convert K2P channels into a leak conductance. These findings provide insight into the functional plasticity of a K(+)-selective filter and also refine our understanding of K2P channels and the mechanisms by which ion channels can sense voltage.

Mechanisms of anion conduction by coupled glutamate transporters.

Excitatory amino acid transporters (EAATs) are essential for terminating glutamatergic synaptic transmission. They are not only coupled glutamate/Na(+)/H(+)/K(+) transporters but also function as anion-selective channels. EAAT anion channels regulate neuronal excitability, and gain-of-function mutations in these proteins result in ataxia and epilepsy. We have combined molecular dynamics simulations with fluorescence spectroscopy of the prokaryotic homolog GltPh and patch-clamp recordings of mammalian EAATs to determine how these transporters conduct anions. Whereas outward- and inward-facing GltPh conformations are nonconductive, lateral movement of the glutamate transport domain from intermediate transporter conformations results in formation of an anion-selective conduction pathway. Fluorescence quenching of inserted tryptophan residues indicated the entry of anions into this pathway, and mutations of homologous pore-forming residues had analogous effects on GltPh simulations and EAAT2/EAAT4 measurements of single-channel currents and anion/cation selectivities. These findings provide a mechanistic framework of how neurotransmitter transporters can operate as anion-selective and ligand-gated ion channels.

Visualization of the mechanosensitive ion channel MscS under membrane tension.

Mechanosensitive channels sense mechanical forces in cell membranes and underlie many biological sensing processes1-3. However, how exactly they sense mechanical force remains under investigation4. The bacterial mechanosensitive channel of small conductance, MscS, is one of the most extensively studied mechanosensitive channels4-8, but how it is regulated by membrane tension remains unclear, even though the structures are known for its open and closed states9-11. Here we used cryo-electron microscopy to determine the structure of MscS in different membrane environments, including one that mimics a membrane under tension. We present the structures of MscS in the subconducting and desensitized states, and demonstrate that the conformation of MscS in a lipid bilayer in the open state is dynamic. Several associated lipids have distinct roles in MscS mechanosensation. Pore lipids are necessary to prevent ion conduction in the closed state. Gatekeeper lipids stabilize the closed conformation and dissociate with membrane tension, allowing the channel to open. Pocket lipids in a solvent-exposed pocket between subunits are pulled out under sustained tension, allowing the channel to transition to the subconducting state and then to the desensitized state. Our results provide a mechanistic underpinning and expand on the 'force-from-lipids' model for MscS mechanosensation4,11.

Molecular basis for human aquaporin inhibition.

Cancer invasion and metastasis are known to be potentiated by the expression of aquaporins (AQPs). Likewise, the expression levels of AQPs have been shown to be prognostic for survival in patients and have a role in tumor growth, edema, angiogenesis, and tumor cell migration. Thus, AQPs are key players in cancer biology and potential targets for drug development. Here, we present the single-particle cryo-EM structure of human AQP7 at 3.2-Å resolution in complex with the specific inhibitor compound Z433927330. The structure in combination with MD simulations shows that the inhibitor binds to the endofacial side of AQP7. In addition, cancer cells treated with Z433927330 show reduced proliferation. The data presented here serve as a framework for the development of AQP inhibitors.

Molecular dynamics simulations reveal the importance of amyloid-beta oligomer ß-sheet edge conformations in membrane permeabilization.

Oligomeric aggregates of the amyloid-beta peptide(1-42) (Aß42) are regarded as a primary cause of cytotoxicity related to membrane damage in Alzheimer's disease. However, a dynamical and structural characterization of pore-forming Aß42 oligomers at atomic detail has not been feasible. Here, we used Aß42 oligomer structures previously determined in a membrane-mimicking environment as putative model systems to study the pore formation process in phospholipid bilayers with all-atom molecular dynamics simulations. Multiple Aß42 oligomer sizes, conformations, and N-terminally truncated isoforms were investigated on the multi-µs time scale. We found that pore formation and ion permeation occur via edge conductivity and exclusively for ß-sandwich structures that feature exposed side-by-side ß-strand pairs formed by residues 9 to 21 of Aß42. The extent of pore formation and ion permeation depends on the insertion depth of hydrophilic residues 13 to 16 (HHQK domain) and thus on subtle differences in the overall stability, orientation, and conformation of the aggregates in the membrane. Additionally, we determined that backbone carbonyl and polar side-chain atoms from the edge strands directly contribute to the coordination sphere of the permeating ions. Furthermore, point mutations that alter the number of favorable side-chain contacts correlate with the ability of the Aß42 oligomer models to facilitate ion permeation in the bilayer center. Our findings suggest that membrane-inserted, layered ß-sheet edges are a key structural motif in pore-forming Aß42 oligomers independent of their size and play a pivotal role in aggregate-induced membrane permeabilization.

Resolving coupled pH titrations using alchemical free energy calculations.

In a protein, nearby titratable sites can be coupled: the (de)protonation of one may affect the other. The degree of this interaction depends on several factors and can influence the measured p K a . Here, we derive a formalism based on double free energy differences ( Δ Δ G ) for quantifying the individual site p K a values of coupled residues. As Δ Δ G values can be obtained by means of alchemical free energy calculations, the presented approach allows for a convenient estimation of coupled residue p K a s in practice. We demonstrate that our approach and a previously proposed microscopic p K a formalism, can be combined with alchemical free energy calculations to resolve pH-dependent protein p K a values. Toy models and both, regular and constant-pH molecular dynamics simulations, alongside experimental data, are used to validate this approach. Our results highlight the insights gleaned when coupling and microstate probabilities are analyzed and suggest extensions to more complex enzymatic contexts. Furthermore, we find that naïvely computed p K a values that ignore coupling, can be significantly improved when coupling is accounted for, in some cases reducing the error by half. In short, alchemical free energy methods can resolve the p K a values of both uncoupled and coupled residues.

Current State of Open Source Force Fields in Protein-Ligand Binding Affinity Predictions.

In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations are nowadays a popular approach for the accurate affinity ranking of compounds. MD simulations rely on empirical force field parameters, which strongly influence the accuracy of the predicted affinities. Here, we evaluate the ability of six different small-molecule force fields to predict experimental protein-ligand binding affinities in RBFE calculations on a set of 598 ligands and 22 protein targets. The public force fields OpenFF Parsley and Sage, GAFF, and CGenFF show comparable accuracy, while OPLS3e is significantly more accurate. However, a consensus approach using Sage, GAFF, and CGenFF leads to accuracy comparable to OPLS3e. While Parsley and Sage are performing comparably based on aggregated statistics across the whole dataset, there are differences in terms of outliers. Analysis of the force field reveals that improved parameters lead to significant improvement in the accuracy of affinity predictions on subsets of the dataset involving those parameters. Lower accuracy can not only be attributed to the force field parameters but is also dependent on input preparation and sampling convergence of the calculations. Especially large perturbations and nonconverged simulations lead to less accurate predictions. The input structures, Gromacs force field files, as well as the analysis Python notebooks are available on GitHub.

A ß-barrel for oil transport through lipid membranes: Dynamic NMR structures of AlkL.

The protein AlkL is known to increase permeability of the outer membrane of bacteria for hydrophobic molecules, yet the mechanism of transport has not been determined. Differing crystal and NMR structures of homologous proteins resulted in a controversy regarding the degree of structure and the role of long extracellular loops. Here we solve this controversy by determining the de novo NMR structure in near-native lipid bilayers, and by accessing structural dynamics relevant to hydrophobic substrate permeation through molecular-dynamics simulations and by characteristic NMR relaxation parameters. Dynamic lateral exit sites large enough to accommodate substrates such as carvone or octane occur through restructuring of a barrel extension formed by the extracellular loops.

Direct Detection of Bound Ammonium Ions in the Selectivity Filter of Ion Channels by Solid-State NMR.

The flow of ions across cell membranes facilitated by ion channels is an important function for all living cells. Despite the huge amount of structural data provided by crystallography, elucidating the exact interactions between the selectivity filter atoms and bound ions is challenging. Here, we detect bound 15N-labeled ammonium ions as a mimic for potassium ions in ion channels using solid-state NMR under near-native conditions. The non-selective ion channel NaK showed two ammonium peaks corresponding to its two ion binding sites, while its potassium-selective mutant NaK2K that has a signature potassium-selective selectivity filter with four ion binding sites gave rise to four ammonium peaks. Ions bound in specific ion binding sites were identified based on magnetization transfer between the ions and carbon atoms in the selectivity filters. Magnetization transfer between bound ions and water molecules revealed that only one out of four ions in the selectivity filter of NaK2K is in close contact with water, which is in agreement with the direct knock-on ion conduction mechanism where ions are conducted through the channel by means of direct interactions without water molecules in between. Interestingly, the potassium-selective ion channels investigated here (NaK2K and, additionally, KcsA-Kv1.3) showed remarkably different chemical shifts for their bound ions, despite having identical amino acid sequences and crystal structures of their selectivity filters. Molecular dynamics simulations show similar ion binding and conduction behavior between ammonium and potassium ions and identify the origin of the differences between the investigated potassium channels.

Structural basis for antibiotic action of the B1 antivitamin 2'-methoxy-thiamine.

The natural antivitamin 2'-methoxy-thiamine (MTh) is implicated in the suppression of microbial growth. However, its mode of action and enzyme-selective inhibition mechanism have remained elusive. Intriguingly, MTh inhibits some thiamine diphosphate (ThDP) enzymes, while being coenzymatically active in others. Here we report the strong inhibition of Escherichia coli transketolase activity by MTh and unravel its mode of action and the structural basis thereof. The unique 2'-methoxy group of MTh diphosphate (MThDP) clashes with a canonical glutamate required for cofactor activation in ThDP-dependent enzymes. This glutamate is forced into a stable, anticatalytic low-barrier hydrogen bond with a neighboring glutamate, disrupting cofactor activation. Molecular dynamics simulations of transketolases and other ThDP enzymes identify active-site flexibility and the topology of the cofactor-binding locale as key determinants for enzyme-selective inhibition. Human enzymes either retain enzymatic activity with MThDP or preferentially bind authentic ThDP over MThDP, while core bacterial metabolic enzymes are inhibited, demonstrating therapeutic potential.

Pre-Exascale Computing of Protein-Ligand Binding Free Energies with Open Source Software for Drug Design.

Nowadays, drug design projects benefit from highly accurate protein-ligand binding free energy predictions based on molecular dynamics simulations. While such calculations have been computationally expensive in the past, we now demonstrate that workflows built on open source software packages can efficiently leverage pre-exascale computing resources to screen hundreds of compounds in a matter of days. We report our results of free energy calculations on a large set of pharmaceutically relevant targets assembled to reflect industrial drug discovery projects.

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.

Conotoxin κM-RIIIJ, a tool targeting asymmetric heteromeric Kv1 channels.

The vast complexity of native heteromeric K+ channels is largely unexplored. Defining the composition and subunit arrangement of individual subunits in native heteromeric K+ channels and establishing their physiological roles is experimentally challenging. Here we systematically explored this "zone of ignorance" in molecular neuroscience. Venom components, such as peptide toxins, appear to have evolved to modulate physiologically relevant targets by discriminating among closely related native ion channel complexes. We provide proof-of-principle for this assertion by demonstrating that κM-conotoxin RIIIJ (κM-RIIIJ) from Conus radiatus precisely targets "asymmetric" Kv channels composed of three Kv1.2 subunits and one Kv1.1 or Kv1.6 subunit with 100-fold higher apparent affinity compared with homomeric Kv1.2 channels. Our study shows that dorsal root ganglion (DRG) neurons contain at least two major functional Kv1.2 channel complexes: a heteromer, for which κM-RIIIJ has high affinity, and a putative Kv1.2 homomer, toward which κM-RIIIJ is less potent. This conclusion was reached by (i) covalent linkage of members of the mammalian Shaker-related Kv1 family to Kv1.2 and systematic assessment of the potency of κM-RIIIJ block of heteromeric K+ channel-mediated currents in heterologous expression systems; (ii) molecular dynamics simulations of asymmetric Kv1 channels providing insights into the molecular basis of κM-RIIIJ selectivity and potency toward its targets; and (iii) evaluation of calcium responses of a defined population of DRG neurons to κM-RIIIJ. Our study demonstrates that bioactive molecules present in venoms provide essential pharmacological tools that systematically target specific heteromeric Kv channel complexes that operate in native tissues.

Lipid-protein forces predict conformational changes in a mechanosensitive channel.

The mechanosensitive TREK-2 potassium channel, a member of the K2P family, has essential physiological roles and is, therefore, a pharmaceutical target. A combination of experimental and computational studies have established that of the two known conformations, "up" and "down", membrane tension directly favors the "up" state, which displays a higher conductance. However, these studies did not reveal the exact mechanism by which the membrane affects the channel conformation. In this work, we show that changes in protein-lipid interaction patterns suffice in predicting this conformational change, and pinpoint potentially important residues involved in this phenomenon.

Structure, gating and interactions of the voltage-dependent anion channel.

The voltage-dependent anion channel (VDAC) is one of the most highly abundant proteins found in the outer mitochondrial membrane, and was one of the earliest discovered. Here we review progress in understanding VDAC function with a focus on its structure, discussing various models proposed for voltage gating as well as potential drug targets to modulate the channel's function. In addition, we explore the sensitivity of VDAC structure to variations in the membrane environment, comparing DMPC-only, DMPC with cholesterol, and near-native lipid compositions, and use magic-angle spinning NMR spectroscopy to locate cholesterol on the outside of the ß-barrel. We find that the VDAC protein structure remains unchanged in different membrane compositions, including conditions with cholesterol.

Non-equilibrium approach for binding free energies in cyclodextrins in SAMPL7: force fields and software.

In the current work we report on our participation in the SAMPL7 challenge calculating absolute free energies of the host-guest systems, where 2 guest molecules were probed against 9 hosts-cyclodextrin and its derivatives. Our submission was based on the non-equilibrium free energy calculation protocol utilizing an averaged consensus result from two force fields (GAFF and CGenFF). The submitted prediction achieved accuracy of [Formula: see text] in terms of the unsigned error averaged over the whole dataset. Subsequently, we further report on the underlying reasons for discrepancies between our calculations and another submission to the SAMPL7 challenge which employed a similar methodology, but disparate ligand and water force fields. As a result we have uncovered a number of issues in the dihedral parameter definition of the GAFF 2 force field. In addition, we identified particular cases in the molecular topologies where different software packages had a different interpretation of the same force field. This latter observation might be of particular relevance for systematic comparisons of molecular simulation software packages. The aforementioned factors have an influence on the final free energy estimates and need to be considered when performing alchemical calculations.

Non-active site mutants of HIV-1 protease influence resistance and sensitisation towards protease inhibitors.

BACKGROUND: HIV-1 can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs. In HIV-1 protease, a majority of resistance-associated mutations that develop in response to therapy with protease inhibitors are found in the protease's active site that serves also as a binding pocket for the protease inhibitors, thus directly impacting the protease-inhibitor interactions. Some resistance-associated mutations, however, are found in more distant regions, and the exact mechanisms how these mutations affect protease-inhibitor interactions are unclear. Furthermore, some of these mutations, e.g. N88S and L76V, do not only induce resistance to the currently administered drugs, but contrarily induce sensitivity towards other drugs. In this study, mutations N88S and L76V, along with three other resistance-associated mutations, M46I, I50L, and I84V, are analysed by means of molecular dynamics simulations to investigate their role in complexes of the protease with different inhibitors and in different background sequence contexts. RESULTS: Using these simulations for alchemical calculations to estimate the effects of mutations M46I, I50L, I84V, N88S, and L76V on binding free energies shows they are in general in line with the mutations' effect on [Formula: see text] values. For the primary mutation L76V, however, the presence of a background mutation M46I in our analysis influences whether the unfavourable effect of L76V on inhibitor binding is sufficient to outweigh the accompanying reduction in catalytic activity of the protease. Finally, we show that L76V and N88S changes the hydrogen bond stability of these residues with residues D30/K45 and D30/T31/T74, respectively. CONCLUSIONS: We demonstrate that estimating the effect of both binding pocket and distant mutations on inhibitor binding free energy using alchemical calculations can reproduce their effect on the experimentally measured [Formula: see text] values. We show that distant site mutations L76V and N88S affect the hydrogen bond network in the protease's active site, which offers an explanation for the indirect effect of these mutations on inhibitor binding. This work thus provides valuable insights on interplay between primary and background mutations and mechanisms how they affect inhibitor binding.

Enhancing NMR derived ensembles with kinetics on multiple timescales.

Nuclear magnetic resonance (NMR) has the unique advantage of elucidating the structure and dynamics of biomolecules in solution at physiological temperatures, where they are in constant movement on timescales from picoseconds to milliseconds. Such motions have been shown to be critical for enzyme catalysis, allosteric regulation, and molecular recognition. With NMR being particularly sensitive to these timescales, detailed information about the kinetics can be acquired. However, nearly all methods of NMR-based biomolecular structure determination neglect kinetics, which introduces a large approximation to the underlying physics, limiting both structural resolution and the ability to accurately determine molecular flexibility. Here we present the Kinetic Ensemble approach that uses a hierarchy of interconversion rates between a set of ensemble members to rigorously calculate Nuclear Overhauser Effect (NOE) intensities. It can be used to simultaneously refine both temporal and structural coordinates. By generalizing ideas from the extended model free approach, the method can analyze the amplitudes and kinetics of motions anywhere along the backbone or side chains. Furthermore, analysis of a large set of crystal structures suggests that NOE data contains a surprising amount of high-resolution information that is better modeled using our approach. The Kinetic Ensemble approach provides the means to unify numerous types of experiments under a single quantitative framework and more fully characterize and exploit kinetically distinct protein states. While we apply the approach here to the protein ubiquitin and cross validate it with previously derived datasets, the approach can be applied to any protein for which NOE data is available.

CHARMM36m: an improved force field for folded and intrinsically disordered proteins.

The all-atom additive CHARMM36 protein force field is widely used in molecular modeling and simulations. We present its refinement, CHARMM36m (http://mackerell.umaryland.edu/charmm_ff.shtml), with improved accuracy in generating polypeptide backbone conformational ensembles for intrinsically disordered peptides and proteins.

The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations.

Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host-guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure reproducibility, and we observe differences between seemingly converged predictions ranging approximately from 0.3 to 1.0 kcal/mol, even with almost identical simulations parameters and system setup (e.g., Lennard-Jones cutoff, ionic composition). Further work will be required to completely identify the exact source of these discrepancies. Among the conclusions emerging from the data, we found that Hamiltonian replica exchange-while displaying very small variance-can be affected by a slowly-decaying bias that depends on the initial population of the replicas, that bidirectional estimators are significantly more efficient than unidirectional estimators for nonequilibrium free energy calculations for systems considered, and that the Berendsen barostat introduces non-negligible artifacts in expanded ensemble simulations.