A Grand Canonical Monte Carlo-Brownian dynamics algorithm for simulating ion channels

In vitro antimicrobial, anticancer evaluation, and in silico studies of mannopyranoside analogs against bacterial and fungal proteins: Acylation leads to improved antimicrobial activity

Carbohydrate analogs are an important, well-established class of clinically useful medicinal agents that exhibit potent antimicrobial activity. Thus, we explored the various therapeutic potential of methyl α-D-mannopyranoside (MαDM) analogs, including their ability to synthesize and assess their antibacterial, antifungal, and anticancer properties; additionally, molecular docking, molecular dynamics simulation, and ADMET analysis were performed. The structure of the synthesized MαDM analogs was ascertained by spectroscopic techniques and physicochemical and elemental analysis. In vitro antimicrobial activity was assessed and revealed significant inhibitory effects, particularly against gram-negative bacteria along with the prediction of activity spectra for substances (PASS). Concurrently, MαDM analogs showed good results against antifungal pathogens and exhibited promising anticancer effects in vitro, demonstrating dose-dependent cytotoxicity against Ehrlich ascites carcinoma (EAC) cancer cells while sparing normal cells from compound 5, with an IC50 of 4511.65 µg/mL according to the MTT colorimetric assay. A structure-activity relationship (SAR) study revealed that hexose combined with the acyl chains of decanoyl (C-10) and benzenesulfonyl (C6H5SO2-) had synergistic effects on the bacteria and fungi that were examined. Molecular docking was performed against the Escherichia coli (6KZV) and Candida albicans (1EAG) proteins to acquire insights into the molecular interactions underlying the observed biological activities. The docking results were further supported by 100 ns molecular dynamics simulations, which provided a dynamic view of the stability and flexibility of complexes involving MαDM and its targets. In addition, ADMET analysis was used to evaluate the toxicological and pharmacokinetic profiles. Owing to their promising drug-like properties, these MαDM analogs exhibit potential as prospective therapeutic candidates for future development.

In silico screening of a series of 1,6-disubstituted 1H-pyrazolo[3,4-d]pyrimidines as potential selective inhibitors of the Janus kinase 3

Rheumatoid arthritis is a common chronic disabling inflammatory disease that is characterized by inflammation of the synovial membrane and leads to discomfort. In the current study, twenty-seven 1,6-disubstituted 1H-pyrazolo[3,4-d]pyrimidines were tested as potential selective inhibitors of the tyrosine-protein kinase JAK3 using a number of molecular modeling methods. The activity of the screened derivatives was statistically quantified using multiple linear regression and artificial neural networks. To assess the quality, robustness, and predictability of the generated models, the leave-one-out cross-validation method was applied with favorable results (Q2 = 0.75) and Y-randomization. In addition, the evaluation of the predictive ability of the established model was confirmed by means of an external validation using a composite test set and an applicability domain approach. The covalent docking indicated that the tested 1H-pyrazolo[3,4-d]pyrimidines containing the acrylic aldehyde moiety had irreversible interaction with the residue Cys909 in the active sites of the tyrosine-protein kinase JAK3 by Michael addition. The molecular dynamics for three selected derivatives (compounds 9, 12, and 18) were used to verify the covalent docking by determining the stability of hydrogen bonding interactions with active sites, which are needed to stop tyrosine-protein kinase JAK3. The results obtained showed that the tested compounds containing acrylic aldehyde moiety had favorable binding free energies, indicating a strong affinity for the JAK3 enzyme. Overall, this current study suggests that the tested compounds containing the acrylic aldehyde moiety have the potential to act as anti-JAK3 inhibitors. They could be explored further to be used as treatment options for rheumatoid arthritis.Communicated by Ramaswamy H. Sarma.

In silico discovery of potent and selective Janus kinase 3 (JAK3) inhibitors through 3D-QSAR, covalent docking, ADMET analysis, molecular dynamics simulations, and binding free energy of pyrazolopyrimidine derivatives

Rheumatoid arthritis is a prevalent and debilitating chronic disease worldwide. Targeting Janus kinase 3 (JAK3) has emerged as a crucial molecular strategy to treat this condition. In this study, we employed a comprehensive theoretical approach that included 3D-QSAR, covalent docking, ADMET, and molecular dynamics to propose and optimize new anti-JAK3 compounds. We investigated a series of 28 1H-pyrazolo[3.4-d]pyrimidin-4-amino inhibitors and developed a highly accurate 3D-QSAR model using comparative molecular similarity index analysis (COMSIA). The model predicted with Q2 = 0.59, R2 = 0.96, and R2(Pred) = 0.89, was validated using Y-randomization and external validation methods. Our covalent docking studies identified T3 and T5 as highly potent inhibitors of JAK3 compared to the reference ligand 17. Additionally, we evaluated the ADMET properties and drug similarity of our newly developed compounds and reference ligand, providing critical insights for further optimization of anti-JAK3 medications. Furthermore, MM-GBSA analysis showed promising results for the designed compounds. Finally, we validated our docking results using molecular dynamics simulations, which confirmed the stability of hydrogen bonding contacts with key residues required to block JAK3 activity. Our findings offer new chemical scaffolds and insights that could lead to the development of novel and effective JAK3 therapeutic targets for treating rheumatoid arthritis.Communicated by Ramaswamy H. Sarma.

Nonequilibrium switching of segmental states can influence compaction of chromatin

Knowledge about the dynamic nature of chromatin organization is essential to understand the regulation of processes like DNA transcription and repair. The existing models of chromatin assume that protein organization and chemical states along chromatin are static and the 3D organization is purely a result of protein-mediated intra-chromatin interactions. Here we present a new hypothesis that certain nonequilibrium processes, such as switching of chemical and physical states due to nucleosome assembly/disassembly or gene repression/activation, can also simultaneously influence chromatin configurations. To understand the implications of this inherent nonequilibrium switching, we present a block copolymer model of chromatin, with switching of its segmental states between two states, mimicking active/repressed or protein unbound/bound states. We show that competition between switching timescale Tt, polymer relaxation timescale τp, and segmental relaxation timescale τs can lead to non-trivial changes in chromatin organization, leading to changes in local compaction and contact probabilities. As a function of the switching timescale, the radius of gyration of chromatin shows a non-monotonic behavior with a prominent minimum when Tt ≈ τp and a maximum when Tt ≈ τs. We find that polymers with a small segment length exhibit a more compact structure than those with larger segment lengths. We also find that the switching can lead to higher contact probability and better mixing of far-away segments. Our study also shows that the nature of the distribution of chromatin clusters varies widely as we change the switching rate.

Dynamics accelerate the kinetics of ion diffusion through channels: Continuous-time random walk models beyond the mean field approximation

Ion channels are proteins that play a significant role in physiological processes, including neuronal excitability and signal transduction. However, the precise mechanisms by which these proteins facilitate ion diffusion through cell membranes are not well understood. This is because experimental techniques to characterize ion channel activity operate on a time scale too large to understand the role of the various protein conformations on diffusion. Meanwhile, computational approaches operate on a time scale too short to rationalize the observed behavior at the microscopic scale. In this paper, we present a continuous-time random walk model that aims to bridge the scales between the atomistic models of ion channels and the experimental measurement of their conductance. We show how diffusion slows down in complex systems by using 3D lattices that map out the pore geometry of two channels: Nav1.7 and gramicidin. We also introduce spatial and dynamic site disorder to account for system heterogeneity beyond the mean field approximation. Computed diffusion coefficients show that an increase in spatial disorder slows down diffusion kinetics, while dynamic disorder has the opposite effect. Our results imply that microscopic or phenomenological models based on the potential of mean force data overlook the functional importance of protein dynamics on ion diffusion through channels.

Experimental and Theoretical Brownian Dynamics Analysis of Ion Transport During Cellular Electroporation of E. coli Bacteria

Escherichia coli bacterium is a rod-shaped organism composed of a complex double membrane structure. Knowledge of electric field driven ion transport through both membranes and the evolution of their induced permeabilization has important applications in biomedical engineering, delivery of genes and antibacterial agents. However, few studies have been conducted on Gram-negative bacteria in this regard considering the contribution of all ion types. To address this gap in knowledge, we have developed a deterministic and stochastic Brownian dynamics model to simulate in 3D space the motion of ions through pores formed in the plasma membranes of E. coli cells during electroporation. The diffusion coefficient, mobility, and translation time of Ca2+, Mg2+, Na+, K+, and Cl- ions within the pore region are estimated from the numerical model. Calculations of pore's conductance have been validated with experiments conducted at Gustave Roussy. From the simulations, it was found that the main driving force of ionic uptake during the pulse is the one due to the externally applied electric field. The results from this work provide a better understanding of ion transport during electroporation, aiding in the design of electrical pulses for maximizing ion throughput, primarily for application in cancer treatment.

Discovery of anti-colon cancer agents targeting wild-type and mutant p53 using computer-aided drug design

Mutations in the p53 gene are common and occur in over 50% of all cancers, as it is involved in DNA damage repair, cell cycle regulation and apoptosis. Moreover, the p53 gene is mutated in 70% of colon cancers. Therefore, the development of drugs to combat this mutation requires urgent attention. With this in mind, in silico drug design approaches were applied on quinoline derivatives with anticancer activity. In 3D-QSAR study, steric, electrostatic, hydrophobic and H-bond acceptor fields (SEHA) play an important role in prediction and design of new colon cancer compounds. Indeed, the two best CoMSIA/SEHA models with (Q2 = 0.737, R2 = 0.914, R pred 2 = 0.720) and (Q2 = 0.738, R2 = 0.919, R pred 2 = 0.739) show good prediction of human colon carcinoma HCT 116 (p53+/+) and (p53-/-) activities, respectively. Furthermore, the predictive ability and robustness of these models were tested by several validation methods. Molecular docking analyses reveal crucial interactions with the active sites of the p53 protein in both wild type and mutant. Based on these theoretical studies, we designed 10 new compounds with good anticancer activity potential, which were evaluated using ADMET properties. Molecular dynamics simulations were performed to confirm the detailed binding mode of the docking results. Finally, the MM-GBSA based on molecular dynamics simulation confirmed that the designed compounds were able to form stable hydrogen bonding interactions with the crucial residues, which are essential to overcome the p53 mutation in colon cancer.Communicated by Ramaswamy H. Sarma.

Identification of terpenoids as potential inhibitors of SARS-CoV-2 (main protease) and spike (RBD) via computer-aided drug design

The scientific community has been faced with a major challenge in the fight against the SARS-CoV-2 virus responsible for the COVID-19 pandemic, due to the lack of targeted antiviral drugs. To address this issue, we used an in silico approach to screen 23 natural compounds from the terpenoid class for their ability to target key SARS-CoV-2 therapeutic proteins. The results revealed that several compounds showed promising interactions with SARS-CoV-2 proteins, specifically the main protease and the spike receptor binding domain. The molecular docking analysis revealed the importance of certain residues, such as GLY143, SER144, CYS145 and GLU166, in the main protease of the SARS-CoV-2 protein, which play a crucial role in interactions with the ligand. In addition, our study highlighted the importance of interactions with residues GLY496, ARG403, SER494 and ARG393 of the spike receptor-binding domain within the SARS-CoV-2 protein. ADMET and drug similarity analyses were also performed, followed by molecular dynamics and MM-GBSA calculations, to identify potential drugs could be repurposed to combat COVID-19. Indeed, the results suggest that certain terpenoid compounds of plant origin have promising potential as therapeutic targets for SARS-CoV-2. However, additional experimental studies are required to confirm their efficacy as drugs against COVID-19.Communicated by Ramaswamy H. Sarma.

Enhanced Grand Canonical Sampling of Occluded Water Sites Using Nonequilibrium Candidate Monte Carlo

Water molecules play a key role in many biomolecular systems, particularly when bound at protein-ligand interfaces. However, molecular simulation studies on such systems are hampered by the relatively long time scales over which water exchange between a protein and solvent takes place. Grand canonical Monte Carlo (GCMC) is a simulation technique that avoids this issue by attempting the insertion and deletion of water molecules within a given structure. The approach is constrained by low acceptance probabilities for insertions in congested systems, however. To address this issue, here, we combine GCMC with nonequilibium candidate Monte Carlo (NCMC) to yield a method that we refer to as grand canonical nonequilibrium candidate Monte Carlo (GCNCMC), in which the water insertions and deletions are carried out in a gradual, nonequilibrium fashion. We validate this new approach by comparing GCNCMC and GCMC simulations of bulk water and three protein binding sites. We find that not only is the efficiency of the water sampling improved by GCNCMC but that it also results in increased sampling of ligand conformations in a protein binding site, revealing new water-mediated ligand-binding geometries that are not observed using alternative enhanced sampling techniques.

Evaluation of flavonoids as potential inhibitors of the SARS-CoV-2 main protease and spike RBD: Molecular docking, ADMET evaluation and molecular dynamics simulations

The 3CLpro main protease and the RDB spike (s) protein of SARS-CoV-2 are critical targets in the treatment of coronavirus 19 disease (COVID-19), as they are responsible for the COVID-19 replication and infection. With this in mind, Molecular docking of 26 natural compounds belonging to the flavonoid family with the 3CLpro and RBD sites of SARS-CoV-2 has been performed. The docking results revealed that the ligands Silibinin, Tomentin A, Tomentin B, 4′-O-methyldiplacone, Hesperidin Amentoflavone and Bilobetin act as a potential inhibitor of SARS-CoV-2 3CLpro, and that the ligands Herbacetin, Morin, Silibinin, Tomentin E, Amentoflavone, Bilobetin, Baicalein and Quercetin can be potential inhibitors of SARS-CoV-2 RBD. It has been noticed that three ligands can inhibit both sites of SARS-CoV-2, indicating a great potential of these compounds to combat COVID-19. Moreover, molecular docking has been validated by a new validation method based on visual inspiration. Evaluation of ADMET pharmacokinetic properties and the drug likeness in silico revealed that six compounds could be effective drugs against COVID-19. Finally, the docking results were verified by molecular dynamics simulations and MM-GBSA calculation to confirm the stability of hydrogen bonding interactions with crucial residues, which are essential to overcome SARS-CoV-2. These results could direct researchers toward plant-derived compounds that could be further investigated as therapeutic targets against COVID-19 replication and infection.

py-MCMD: Python Software for Performing Hybrid Monte Carlo/Molecular Dynamics Simulations with GOMC and NAMD

py-MCMD, an open-source Python software, provides a robust workflow layer that manages communication of relevant system information between the simulation engines NAMD and GOMC and generates coherent thermodynamic properties and trajectories for analysis. To validate the workflow and highlight its capabilities, hybrid Monte Carlo/molecular dynamics (MC/MD) simulations are performed for SPC/E water in the isobaric-isothermal (NPT) and grand canonical (GC) ensembles as well as with Gibbs ensemble Monte Carlo (GEMC). The hybrid MC/MD approach shows close agreement with reference MC simulations and has a computational efficiency that is 2 to 136 times greater than traditional Monte Carlo simulations. MC/MD simulations performed for water in a graphene slit pore illustrate significant gains in sampling efficiency when the coupled-decoupled configurational-bias MC (CD-CBMC) algorithm is used compared with simulations using a single unbiased random trial position. Simulations using CD-CBMC reach equilibrium with 25 times fewer cycles than simulations using a single unbiased random trial position, with a small increase in computational cost. In a more challenging application, hybrid grand canonical Monte Carlo/molecular dynamics (GCMC/MD) simulations are used to hydrate a buried binding pocket in bovine pancreatic trypsin inhibitor. Water occupancies produced by GCMC/MD simulations are in close agreement with crystallographically identified positions, and GCMC/MD simulations have a computational efficiency that is 5 times better than MD simulations. py-MCMD is available on GitHub at https://github.com/GOMC-WSU/py-MCMD.

A Deep Dive into VDAC1 Conformational Diversity Using All-Atom Simulations Provides New Insights into the Structural Origin of the Closed States

The voltage-dependent anion channel 1 (VDAC1) is a crucial mitochondrial transporter that controls the flow of ions and respiratory metabolites entering or exiting mitochondria. As a voltage-gated channel, VDAC1 can switch between a high-conducting “open” state and a low-conducting “closed” state emerging at high transmembrane (TM) potentials. Although cell homeostasis depends on channel gating to regulate the transport of ions and metabolites, structural hallmarks characterizing the closed states remain unknown. Here, we performed microsecond accelerated molecular dynamics to highlight a vast region of VDAC1 conformational landscape accessible at typical voltages known to promote closure. Conformers exhibiting durable subconducting properties inherent to closed states were identified. In all cases, the low conductance was due to the particular positioning of an unfolded part of the N-terminus, which obstructed the channel pore. While the N-terminal tail was found to be sensitive to voltage orientation, our models suggest that stable low-conducting states of VDAC1 predominantly take place from disordered events and do not result from the displacement of a voltage sensor or a significant change in the pore. In addition, our results were consistent with conductance jumps observed experimentally and corroborated a recent study describing entropy as a key factor for VDAC gating.

Computational methods and theory for ion channel research

Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.

Physics of Selective Conduction and Point Mutation in Biological Ion Channels

We introduce a statistical and linear response theory of selective conduction in biological ion channels with multiple binding sites and possible point mutation. We derive an effective grand-canonical ensemble and generalized Einstein relations for the selectivity filter, assuming strongly coordinated ionic motion, and allowing for ionic Coulomb blockade. The theory agrees well with data from the KcsA K^{+} channel and a mutant. We show that the Eisenman relations for thermodynamic selectivity follow from the condition for fast conduction and find that maximum conduction requires the binding sites to be nearly identical.

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.

Exploring the putative mechanism of allosteric modulations by mixed-action kappa/mu opioid receptor bitopic modulators

The modulation and selectivity mechanisms of seven mixed-action kappa opioid receptor (KOR)/mu opioid receptor (MOR) bitopic modulators were explored. Molecular modeling results indicated that the 'message' moiety of seven bitopic modulators shared the same binding mode with the orthosteric site of the KOR and MOR, whereas the 'address' moiety bound with different subdomains of the allosteric site of the KOR and MOR. The 'address' moiety of seven bitopic modulators bound to different subdomains of the allosteric site of the KOR and MOR may exhibit distinguishable allosteric modulations to the binding affinity and/or efficacy of the 'message' moiety. Moreover, the 3-hydroxy group on the phenolic moiety of the seven bitopic modulators induced selectivity to the KOR over the MOR.

The intrinsically disordered N-terminus of the voltage-dependent anion channel

The voltage-dependent anion channel (VDAC) is a critical β-barrel membrane protein of the mitochondrial outer membrane, which regulates the transport of ions and ATP between mitochondria and the cytoplasm. In addition, VDAC plays a central role in the control of apoptosis and is therefore of great interest in both cancer and neurodegenerative diseases. Although not fully understood, it is presumed that the gating mechanism of VDAC is governed by its N-terminal region which, in the open state of the channel, exhibits an α-helical structure positioned midway inside the pore and strongly interacting with the β-barrel wall. In the present work, we performed molecular simulations with a recently developed force field for disordered systems to shed new light on known experimental results, showing that the N-terminus of VDAC is an intrinsically disordered region (IDR). First, simulation of the N-terminal segment as a free peptide highlighted its disordered nature and the importance of using an IDR-specific force field to properly sample its conformational landscape. Secondly, accelerated dynamics simulation of a double cysteine VDAC mutant under applied voltage revealed metastable low conducting states of the channel representative of closed states observed experimentally. Related structures were characterized by partial unfolding and rearrangement of the N-terminal tail, that led to steric hindrance of the pore. Our results indicate that the disordered properties of the N-terminus are crucial to properly account for the gating mechanism of VDAC.

The voltage-dependent anion channel (VDAC) is a membrane protein playing a pivotal role in the transport of ions or ATP across the mitochondrial outer membrane as well as in the induction of apoptosis. At high enough membrane potential, VDAC is known to transition from an open state to multiple closed states, reducing the flow of ions through the channel and blocking the passage of large metabolites. While the structure of the open state was resolved more than a decade ago, a molecular description of the gating mechanism of the channel is still missing. Here we show that the N-terminus of VDAC is an intrinsically disordered region and that such a property has a profound impact on its dynamics either as a free peptide or as part of the channel. By taking disordered properties of the N-terminus into account, we managed to generate long-lived closed conformations of the channel at experimental values of the membrane potential. Our results provide new insights into the molecular mechanism driving the gating of VDAC.

Millisecond-Long Simulations of Antibiotics Transport through Outer Membrane Channels

To reach their target site inside Gram-negative bacteria, almost all antibiotics need to cross the outer membrane. Computational modeling of such processes can be numerically demanding due to the size of the systems and especially due to the timescales involved. Recently, a hybrid Brownian and molecular dynamics approach, i.e., Brownian dynamics including explicit atoms (BRODEA), has been developed and evaluated for studying the transport of monoatomic ions through membrane channels. Later on, this numerically efficient scheme has been applied to determine the free energy surfaces of the ciprofloxacin and enrofloxacin translocation through the porin OmpC using temperature-accelerated simulations. To improve the usability and accuracy of the approach, schemes to approximate the position-dependent diffusion constant of the molecule while traversing the pore had to be established. To this end, we have studied the translocation of the charged phosphonic acid antibiotic fosfomycin through the porin OmpF from Escherichia coli devising and benchmarking several diffusion models. To test the efficiency and sensitivity of these models, the effect of OmpF mutations on the permeation of fosfomycin was analyzed. Permeation events have been recorded over millisecond-long biased and unbiased simulations, from which thermodynamics and kinetics quantities of the translocation processes were determined. As a result, the use of the BRODEA approach, together with the appropriate diffusion model, was seen to accurately reproduce the findings observed in electrophysiology experiments and all-atom molecular dynamics simulations. These results suggest that the BRODEA approach can become a valuable tool for screening numerous compounds to evaluate their outer membrane permeability, a property important in the development of new antibiotics.

LARMD: integration of bioinformatic resources to profile ligand-driven protein dynamics with a case on the activation of estrogen receptor

Protein dynamics is central to all biological processes, including signal transduction, cellular regulation and biological catalysis. Among them, in-depth exploration of ligand-driven protein dynamics contributes to an optimal understanding of protein function, which is particularly relevant to drug discovery. Hence, a wide range of computational tools have been designed to investigate the important dynamic information in proteins. However, performing and analyzing protein dynamics is still challenging due to the complicated operation steps, giving rise to great difficulty, especially for nonexperts. Moreover, there is a lack of web protocol to provide online facility to investigate and visualize ligand-driven protein dynamics. To this end, in this study, we integrated several bioinformatic tools to develop a protocol, named Ligand and Receptor Molecular Dynamics (LARMD, http://chemyang.ccnu.edu.cn/ccb/server/LARMD/ and http://agroda.gzu.edu.cn:9999/ccb/server/LARMD/), for profiling ligand-driven protein dynamics. To be specific, estrogen receptor (ER) was used as a case to reveal ERβ-selective mechanism, which plays a vital role in the treatment of inflammatory diseases and many types of cancers in clinical practice. Two different residues (Ile373/Met421 and Met336/Leu384) in the pocket of ERβ/ERα were the significant determinants for selectivity, especially Met336 of ERβ. The helix H8, helix H11 and H7-H8 loop influenced the migration of selective agonist (WAY-244). These computational results were consistent with the experimental results. Therefore, LARMD provides a user-friendly online protocol to study the dynamic property of protein and to design new ligand or site-directed mutagenesis.

Multiscale analysis of the effect of surface charge pattern on a nanopore's rectification and selectivity properties: From all-atom model to Poisson-Nernst-Planck

We report a multiscale modeling study for charged cylindrical nanopores using three modeling levels that include (1) an all-atom explicit-water model studied with molecular dynamics, and reduced models with implicit water containing (2) hard-sphere ions studied with the Local Equilibrium Monte Carlo simulation method (computing ionic correlations accurately), and (3) point ions studied with Poisson-Nernst-Planck theory (mean-field approximation). We show that reduced models are able to reproduce device functions (rectification and selectivity) for a wide variety of charge patterns, that is, reduced models are useful in understanding the mesoscale physics of the device (i.e., how the current is produced). We also analyze the relationship of the reduced implicit-water models with the explicit-water model and show that diffusion coefficients in the reduced models can be used as adjustable parameters with which the results of the explicit- and implicit-water models can be related. We find that the values of the diffusion coefficients are sensitive to the net charge of the pore but are relatively transferable to different voltages and charge patterns with the same total charge.

A Crucial Role for Side-Chain Conformation in the Versatile Charge Selectivity of Cys-Loop Receptors

Whether synaptic transmission is excitatory or inhibitory depends, to a large extent, on whether the ion channels that open upon binding the released neurotransmitter conduct cations or anions. The mechanistic basis of the opposite charge selectivities of Cys-loop receptors has only recently begun to emerge. It is now clear that ionized side chains-whether pore-facing or buried-in the first α-helical turn of the second transmembrane segments underlie this phenomenon and that the electrostatics of backbone atoms are not critically involved. Moreover, on the basis of electrophysiological observations, it has recently been suggested that not only the sign of charged side chains but also their conformation are crucial determinants of cation-anion selectivity. To challenge these ideas with the chemical and structural rigor that electrophysiological observations naturally lack, we performed molecular dynamics, Brownian dynamics, and electrostatics calculations of ion permeation. To this end, we used structural models of the open-channel conformation of the α1 glutamate-gated Cl^- channel and the α1 glycine receptor. Our results provided full support to the notion that the conformation of charged sides chains matters for charge selectivity. Indeed, whereas some rotamers of the buried arginines at position 0' conferred high selectivity for anions, others supported the permeation of cations and anions at similar rates or even allowed the faster permeation of cations. Furthermore, we found that modeling glutamates at position -1' of the anion-selective α1 glycine receptor open-state structure-instead of the five native alanines-switches charge selectivity also in a conformation-dependent manner, with some glutamate rotamers being much more effective at conferring selectivity for cations than others. Regarding pore size, we found that the mere expansion of the pore has only a minimal impact on cation-anion selectivity. Overall, these results bring to light the previously unappreciated impact of side-chain conformation on charge selectivity in Cys-loop receptors.

Rapid and Accurate Determination of Nanopore Ionic Current Using a Steric Exclusion Model

Nanopore sensing has emerged as a versatile approach to detection and identification of biomolecules. Presently, researchers rely on experience and intuition for choosing or modifying the nanopores to detect a target analyte. The field would greatly benefit from a computational method that could relate the atomic-scale geometry of the nanopores and analytes to the blockade nanopore currents they produce. Existing computational methods are either computationally too expensive to be used routinely in experimental laboratories or not sensitive enough to account for the atomic structure of the pore and the analytes. Here, we demonstrate a robust and inexpensive computational approach-the steric exclusion model (SEM) of nanopore conductance-that is orders of magnitude more efficient than all-atom MD and yet is sensitive enough to account for the atomic structure of the nanopore and the analyte. The method combines the computational efficiency of a finite element solver with the atomic precision of a nanopore conductance map to yield unprecedented speed and accuracy of ionic current prediction. We validate our SEM approach through comparison with the current blockades computed using the all-atom molecular dynamics method for a range of proteins confined to a solid-state nanopore, biological channels embedded in a lipid bilayer membranes, and blockade currents produced by DNA homopolymers in MspA. We illustrate potential applications of SEM by computing blockade currents produced by nucleosome proteins in a solid-state nanopore, individual amino acids in MspA, and by testing the effect of point mutations on amino acid distinguishability. We expect our SEM approach to become an integral part of future development of the nanopore sensing field.

Challenges and advances in atomistic simulations of potassium and sodium ion channel gating and permeation

Ion channels are implicated in many essential physiological events such as electrical signal propagation and cellular communication. The advent of K⁺ and Na⁺ ion channel structure determination has facilitated numerous investigations of molecular determinants of their behaviour. At the same time, rapid development of computer hardware and molecular simulation methodologies has made computational studies of large biological molecules in all-atom representation tractable. The concurrent evolution of experimental structural biology with biomolecular computer modelling has yielded mechanistic details of fundamental processes unavailable through experiments alone, such as ion conduction and ion channel gating. This review is a short survey of the atomistic computational investigations of K⁺ and Na⁺ ion channels, focusing on KcsA and several voltage-gated channels from the K_V and Na_V families, which have garnered many successes and engendered several long-standing controversies regarding the nature of their structure-function relationship. We review the latest advancements and challenges facing the field of molecular modelling and simulation regarding the structural and energetic determinants of ion channel function and their agreement with experimental observations.

Structure of native lens connexin 46/50 intercellular channels by cryo-EM

Gap junctions establish direct pathways for cell-to-cell communication through the assembly of twelve connexin subunits that form intercellular channels connecting neighbouring cells. Co-assembly of different connexin isoforms produces channels with unique properties and enables communication across cell types. Here we used single-particle cryo-electron microscopy to investigate the structural basis of connexin co-assembly in native lens gap junction channels composed of connexin 46 and connexin 50 (Cx46/50). We provide the first comparative analysis to connexin 26 (Cx26), which-together with computational studies-elucidates key energetic features governing gap junction permselectivity. Cx46/50 adopts an open-state conformation that is distinct from the Cx26 crystal structure, yet it appears to be stabilized by a conserved set of hydrophobic anchoring residues. 'Hot spots' of genetic mutations linked to hereditary cataract formation map to the core structural-functional elements identified in Cx46/50, suggesting explanations for many of the disease-causing effects.

Lipid composition and salt concentration as regulatory factors of the anion selectivity of VDAC studied by coarse-grained molecular dynamics simulations

The voltage-dependent anion channel (VDAC) is a mitochondrial outer membrane protein whose fundamental function is to facilitate and regulate the flow of metabolites between the cytosol and the mitochondrial intermembrane space. Using coarse-grained molecular dynamics simulations, we investigated the dependence of VDAC selectivity towards small inorganic anions on two factors: the ionic strength and the lipid composition. In agreement with experimental data we found that VDAC becomes less anion selective with increasing salt concentration due to the screening of a few basic residues that point into the pore lumen. The molecular dynamics simulations provide insight into the regulation mechanism of VDAC selectivity by the composition in the lipid membrane and suggest that the ion distribution is differently modulated by POPE compared to the POPC bilayer. This occurs through the more persistent interactions of acidic residues located at both rims of the β-barrel with head groups of POPE which in turn impact the electrostatic potential and thereby the selectivity of the pore. This mechanism occurs not only in POPE single component membranes but also in a mixed POPE/POPC bilayer by an enrichment of POPE over POPC lipids on the surface of VDAC. Thus we show here that computationally-inexpensive coarse-grained simulations are able to capture, in a semi-quantitative way, essential features of VDAC anion selectivity and could pave the way toward a molecular level understanding of metabolite transport in natural membranes.

Controlling ion transport through nanopores: modeling transistor behavior

We present a modeling study of a nanopore-based transistor computed by a mean-field continuum theory (Poisson–Nernst–Planck, PNP) and a hybrid method including particle simulation (Local Equilibrium Monte Carlo, LEMC) that is able to take ionic correlations into account including the finite size of ions.

Incorporating Born solvation energy into the three-dimensional Poisson-Nernst-Planck model to study ion selectivity in KcsA K^{+} channels

Potassium channels are much more permeable to potassium than sodium ions, although potassium ions are larger and both carry the same positive charge. This puzzle cannot be solved based on the traditional Poisson-Nernst-Planck (PNP) theory of electrodiffusion because the PNP model treats all ions as point charges, does not incorporate ion size information, and therefore cannot discriminate potassium from sodium ions. The PNP model can qualitatively capture some macroscopic properties of certain channel systems such as current-voltage characteristics, conductance rectification, and inverse membrane potential. However, the traditional PNP model is a continuum mean-field model and has no or underestimates the discrete ion effects, in particular the ion solvation or self-energy (which can be described by Born model). It is known that the dehydration effect (closely related to ion size) is crucial to selective permeation in potassium channels. Therefore, we incorporated Born solvation energy into the PNP model to account for ion hydration and dehydration effects when passing through inhomogeneous dielectric channel environments. A variational approach was adopted to derive a Born-energy-modified PNP (BPNP) model. The model was applied to study a cylindrical nanopore and a realistic KcsA channel, and three-dimensional finite element simulations were performed. The BPNP model can distinguish different ion species by ion radius and predict selectivity for K^{+} over Na^{+} in KcsA channels. Furthermore, ion current rectification in the KcsA channel was observed by both the PNP and BPNP models. The I-V curve of the BPNP model for the KcsA channel indicated an inward rectifier effect for K^{+} (rectification ratio of ∼3/2) but indicated an outward rectifier effect for Na^{+} (rectification ratio of ∼1/6).

Multiscale modeling of a rectifying bipolar nanopore: explicit-water versus implicit-water simulations

In a multiscale modeling approach, we present computer simulation results for a rectifying bipolar nanopore at two modeling levels. In an all-atom model, we use explicit water to simulate ion transport directly with the molecular dynamics technique. In a reduced model, we use implicit water and apply the Local Equilibrium Monte Carlo method together with the Nernst-Planck transport equation. This hybrid method makes the fast calculation of ion transport possible at the price of lost details. We show that the implicit-water model is an appropriate representation of the explicit-water model when we look at the system at the device (i.e., input vs. output) level. The two models produce qualitatively similar behavior of the electrical current for different voltages and model parameters. Looking at the details of concentration and potential profiles, we find profound differences between the two models. These differences, however, do not influence the basic behavior of the model as a device because they do not influence the z-dependence of the concentration profiles which are the main determinants of current. These results then address an old paradox: how do reduced models, whose assumptions should break down in a nanoscale device, predict experimental data? Our simulations show that reduced models can still capture the overall device physics correctly, even though they get some important aspects of the molecular-scale physics quite wrong; reduced models work because they include the physics that is necessary from the point of view of device function. Therefore, reduced models can suffice for general device understanding and device design, but more detailed models might be needed for molecular level understanding.

CHARMM-GUI 10 years for biomolecular modeling and simulation

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. © 2016 Wiley Periodicals, Inc.

Gating of Connexin Channels by transjunctional-voltage: Conformations and models of open and closed states

Voltage is an important physiologic regulator of channels formed by the connexin gene family. Connexins are unique among ion channels in that both plasma membrane inserted hemichannels (undocked hemichannels) and intercellular channels (aggregates of which form gap junctions) have important physiological roles. The hemichannel is the fundamental unit of gap junction voltage-gating. Each hemichannel displays two distinct voltage-gating mechanisms that are primarily sensitive to a voltage gradient formed along the length of the channel pore (the transjunctional voltage) rather than sensitivity to the absolute membrane potential (V_m or V_i-o). These transjunctional voltage dependent processes have been termed V_j- or fast-gating and loop- or slow-gating. Understanding the mechanism of voltage-gating, defined as the sequence of voltage-driven transitions that connect open and closed states, first and foremost requires atomic resolution models of the end states. Although ion channels formed by connexins were among the first to be characterized structurally by electron microscopy and x-ray diffraction in the early 1980's, subsequent progress has been slow. Much of the current understanding of the structure-function relations of connexin channels is based on two crystal structures of Cx26 gap junction channels. Refinement of crystal structure by all-atom molecular dynamics and incorporation of charge changing protein modifications has resulted in an atomic model of the open state that arguably corresponds to the physiologic open state. Obtaining validated atomic models of voltage-dependent closed states is more challenging, as there are currently no methods to solve protein structure while a stable voltage gradient is applied across the length of an oriented channel. It is widely believed that the best approach to solve the atomic structure of a voltage-gated closed ion channel is to apply different but complementary experimental and computational methods and to use the resulting information to derive a consensus atomic structure that is then subjected to rigorous validation. In this paper, we summarize our efforts to obtain and validate atomic models of the open and voltage-driven closed states of undocked connexin hemichannels. This article is part of a Special Issue entitled: Gap Junction Proteins edited by Jean Claude Herve.

Multiscale modeling of a rectifying bipolar nanopore: Comparing Poisson-Nernst-Planck to Monte Carlo

In the framework of a multiscale modeling approach, we present a systematic study of a bipolar rectifying nanopore using a continuum and a particle simulation method. The common ground in the two methods is the application of the Nernst-Planck (NP) equation to compute ion transport in the framework of the implicit-water electrolytemodel. The difference is that the Poisson-Boltzmann theory is used in the Poisson-Nernst-Planck (PNP) approach, while the Local Equilibrium Monte Carlo (LEMC) method is used in the particle simulation approach (NP+LEMC) to relate the concentration profile to the electrochemical potential profile. Since we consider a bipolar pore which is short and narrow, we perform simulations using two-dimensional PNP. In addition, results of a non-linear version of PNP that takes crowding of ions into account are shown. We observe that the mean field approximation applied in PNP is appropriate to reproduce the basic behavior of the bipolar nanopore (e.g., rectification) for varying parameters of the system (voltage, surface charge,electrolyte concentration, and pore radius). We present current data that characterize the nanopore's behavior as a device, as well as concentration, electrical potential, and electrochemical potential profiles.

Accessing gap-junction channel structure-function relationships through molecular modeling and simulations

Background

Gap junction channels (GJCs) are massive protein channels connecting the cytoplasm of adjacent cells. These channels allow intercellular transfer of molecules up to ~1 kDa, including water, ions and other metabolites. Unveiling structure-function relationships coded into the molecular architecture of these channels is necessary to gain insight on their vast biological function including electrical synapse, inflammation, development and tissular homeostasis. From early works, computational methods have been critical to analyze and interpret experimental observations. Upon the availability of crystallographic structures, molecular modeling and simulations have become a valuable tool to assess structure-function relationships in GJCs. Modeling different connexin isoforms, simulating the transport process, and exploring molecular variants, have provided new hypotheses and out-of-the-box approaches to the study of these important channels.

Methods

Here, we review foundational structural studies and recent developments on GJCs using molecular modeling and simulation techniques, highlighting the methods and the cross-talk with experimental evidence.

Results and discussion

By comparing results obtained by molecular modeling and simulations techniques with structural and functional information obtained from both recent literature and structural databases, we provide a critical assesment of structure-function relationships that can be obtained from the junction between theoretical and experimental evidence.

Simulating Current-Voltage Relationships for a Narrow Ion Channel Using the Weighted Ensemble Method

Ion channels are responsible for a myriad of fundamental biological processes via their role in controlling the flow of ions through water-filled membrane-spanning pores in response to environmental cues. Molecular simulation has played an important role in elucidating the mechanism of ion conduction, but connecting atomistically detailed structural models of the protein to electrophysiological measurements remains a broad challenge due to the computational cost of reaching the necessary time scales. Here, we introduce an enhanced sampling method for simulating the conduction properties of narrow ion channels using the Weighted ensemble (WE) sampling approach. We demonstrate the application of this method to calculate the current–voltage relationship as well as the nonequilibrium ion distribution at steady-state of a simple model ion channel. By direct comparisons with long brute force simulations, we show that the WE simulations rigorously reproduce the correct long-time scale kinetics of the system and are capable of determining these quantities using significantly less aggregate simulation time under conditions where permeation events are rare.

Current state of theoretical and experimental studies of the voltage-dependent anion channel (VDAC)

Voltage-dependent anion channel (VDAC), the major channel of the mitochondrial outer membrane provides a controlled pathway for respiratory metabolites in and out of the mitochondria. In spite of the wealth of experimental data from structural, biochemical, and biophysical investigations, the exact mechanisms governing selective ion and metabolite transport, especially the role of titratable charged residues and interactions with soluble cytosolic proteins, remain hotly debated in the field. The computational advances hold a promise to provide a much sought-after solution to many of the scientific disputes around solute and ion transport through VDAC and hence, across the mitochondrial outer membrane. In this review, we examine how Molecular Dynamics, Free Energy, and Brownian Dynamics simulations of the large β-barrel channel, VDAC, advanced our understanding. We will provide a short overview of non-conventional techniques and also discuss examples of how the modeling excursions into VDAC biophysics prospectively aid experimental efforts. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Key diffusion mechanisms involved in regulating bidirectional water permeation across E. coli outer membrane lectin

Capsular polysaccharides (CPSs) are major bacterial virulent determinants that facilitate host immune evasion. E. coli group1 K30_CPS is noncovalently attached to bacterial surface by Wzi, a lectin. Intriguingly, structure based phylogenetic analysis indicates that Wzi falls into porin superfamily. Molecular dynamics (MD) simulations further shed light on dual role of Wzi as it also functions as a bidirectional passive water specific porin. Such a functional role of Wzi was not realized earlier, due to the occluded pore. While five water specific entry points distributed across extracellular & periplasmic faces regulate the water diffusion involving different mechanisms, a luminal hydrophobic plug governs water permeation across the channel. Coincidently, MD observed open state structure of “YQF” triad is seen in sugar-binding site of sodium-galactose cotransporters, implicating its involvement in K30_CPS surface anchorage. Importance of Loop 5 (L5) in membrane insertion is yet another highlight. Change in water diffusion pattern of periplasmic substitution mutants suggests Wzi’s role in osmoregulation by aiding in K30_CPS hydration, corroborating earlier functional studies. Water molecules located inside β-barrel of Wzi crystal structure further strengthens the role of Wzi in osmoregulation. Thus, interrupting water diffusion or L5 insertion may reduce bacterial virulence.

Computational support for a scaffolding mechanism of centriole assembly

Centrioles are essential for forming cilia, flagella and centrosomes. Successful centriole assembly requires proteins of the SAS-6 family, which can form oligomeric ring structures with ninefold symmetry in vitro. While important progress has been made in understanding SAS-6 protein biophysics, the mechanisms enabling ring formation in vivo remain elusive. Likewise, the mechanisms by which a nascent centriole forms near-orthogonal to an existing one are not known. Here, we investigate possible mechanisms of centriole assembly using coarse-grained Brownian dynamics computer simulations in combination with a rate equation approach. Our results suggest that without any external factors, strong stabilization associated with ring closure would be needed to enable efficient ring formation. Strikingly, our simulations reveal that a scaffold-assisted assembly mechanism can trigger robust ring formation owing to local cooperativity, and that this mechanism can also impart orthogonalilty to centriole assembly. Overall, our findings provide novel insights into the organizing principles governing the assembly of this important organelle.

Hybrid finite element and Brownian dynamics method for charged particles

Diffusion is often the rate-determining step in many biological processes. Currently, the two main computational methods for studying diffusion are stochastic methods, such as Brownian dynamics, and continuum methods, such as the finite element method. A previous study introduced a new hybrid diffusion method that couples the strengths of each of these two methods, but was limited by the lack of interactions among the particles; the force on each particle had to be from an external field. This study further develops the method to allow charged particles. The method is derived for a general multidimensional system and is presented using a basic test case for a one-dimensional linear system with one charged species and a radially symmetric system with three charged species.

An electrostatic mechanism for Ca(2+)-mediated regulation of gap junction channels

Gap junction channels mediate intercellular signalling that is crucial in tissue development, homeostasis and pathologic states such as cardiac arrhythmias, cancer and trauma. To explore the mechanism by which Ca(2+) blocks intercellular communication during tissue injury, we determined the X-ray crystal structures of the human Cx26 gap junction channel with and without bound Ca(2+). The two structures were nearly identical, ruling out both a large-scale structural change and a local steric constriction of the pore. Ca(2+) coordination sites reside at the interfaces between adjacent subunits, near the entrance to the extracellular gap, where local, side chain conformational rearrangements enable Ca(2+)chelation. Computational analysis revealed that Ca(2+)-binding generates a positive electrostatic barrier that substantially inhibits permeation of cations such as K(+) into the pore. Our results provide structural evidence for a unique mechanism of channel regulation: ionic conduction block via an electrostatic barrier rather than steric occlusion of the channel pore.

Simulations of outer membrane channels and their permeability

Channels in the outer membrane of Gram-negative bacteria provide essential pathways for the controlled and unidirectional transport of ions, nutrients and metabolites into the cell. At the same time the outer membrane serves as a physical barrier for the penetration of noxious substances such as antibiotics into the bacteria. Most antibiotics have to pass through these membrane channels to either reach cytoplasmic bound targets or to further cross the hydrophobic inner membrane. Considering the pharmaceutical significance of antibiotics, understanding the functional role and mechanism of these channels is of fundamental importance in developing strategies to design new drugs with enhanced permeation abilities. Due to the biological complexity of membrane channels and experimental limitations, computer simulations have proven to be a powerful tool to investigate the structure, dynamics and interactions of membrane channels. Considerable progress has been made in computer simulations of membrane channels during the last decade. The goal of this review is to provide an overview of the computational techniques and their roles in modeling the transport across outer membrane channels. A special emphasis is put on all-atom molecular dynamics simulations employed to better understand the transport of molecules. Moreover, recent molecular simulations of ion, substrate and antibiotics translocation through membrane pores are briefly summarized. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.