Tuning the Slide-Roll Motion Mode of Carbon Nanotubes via Hydroxyl Groups

Controlling the motion of carbon nanotubes is critical in manipulating nanodevices, including nanorobots. Herein, we investigate the motion behavior of SWCNT (10,10) on Si substrate utilizing molecular dynamics simulations. We show that hydroxyl groups have sensitive effect on the carbon nanotube's motion mode. When the hydroxyl groups' ratio on carbon nanotube and silicon substrate surfaces is larger than 10 and 20%, respectively, the motion of carbon nanotube transforms from sliding to rolling. When the hydroxyl groups' ratio is smaller, the slide or roll mode can be controlled by the speed of carbon nanotube, which is ultimately determined by the competition between the interface potential energy and kinetic energy. The change of motion mode holds true for different carbon nanotubes with hydroxyl groups. The chirality has little effect on the motion behavior, as opposed to the diameter, attributed to the hydroxyl groups' ratio. Our study suggests a new route to control the motion behavior of carbon nanotube via hydroxyl groups.

Time-Resolved Neutron Interferometry and the Mechanism of Electromechanical Coupling in Voltage-Gated Ion Channels

The mechanism of electromechanical coupling for voltage-gated ion channels (VGICs) involved in neurological signal transmission, primarily Nav- and Kv-channels, remains unresolved. Anesthetics have been shown to directly impact this mechanism, at least for Kv-channels. Molecular dynamics computer simulations can now predict the structures of VGICs embedded within a hydrated phospholipid bilayer membrane as a function of the applied transmembrane voltage, but significant assumptions are still necessary. Nevertheless, these simulations are providing new insights into the mechanism of electromechanical coupling at the atomic level in 3-D. We show that time-resolved neutron interferometry can be used to investigate directly the profile structure of a VGIC, vectorially oriented within a single hydrated phospholipid bilayer membrane at the solid-liquid interface, as a function of the applied transmembrane voltage in the absence of any assumptions or potentially perturbing modifications of the VGIC protein and/or the host membrane. The profile structure is a projection of the membrane's 3-D structure onto the membrane normal and, in the absence of site-directed deuterium labeling, is provided at substantially lower spatial resolution than the atomic level. Nevertheless, this novel approach can be used to directly test the validity of the predictions from molecular dynamics simulations. We describe the key elements of our novel experimental approach, including why each is necessary and important to providing the essential information required for this critical comparison of "simulation" vs "experiment." In principle, the approach could be extended to higher spatial resolution and to include the effects of anesthetics on the electromechanical coupling mechanism in VGICs.

Investigation of adhesive interactions in the specific targeting of Triptorelin-conjugated PEG-coated magnetite nanoparticles to breast cancer cells

The understanding of adhesive interaction at the nanoscale between functionalized nanoparticles and biological cells is of great importance to develop effective theranostic nanocarriers for targeted cancer therapy. Here, we report a combination of experimental and computational approaches to evaluate the adhesion between Triptorelin (a Luteinizing Hormone-Releasing Hormone (LHRH) agonist)-conjugated poly-(ethylene glycol) (PEG)-coated magnetite nanoparticles (Triptorelin-MNPs) and breast cells. The adhesion forces between Triptorelin-MNPs and normal/cancerous breast cells are obtained using atomic force microscopy. The corresponding work of adhesion is then estimated using Johnson-Kendall-Roberts model. Our results demonstrate that Triptorelin-MNPs have a fourteen-fold greater work of adhesion to breast cancer cells than to normal breast cells. In addition, the work of adhesion between Triptorelin-MNPs and breast cancer cells is found to be three times more than that between unmodified MNPs and breast cancer cells. Hence, the experimental observation indicates that Triptorelin ligands facilitate the specific targeting of breast cancer cells. Furthermore, molecular dynamics simulations are performed to investigate the molecular origins of the adhesive interactions. The simulations reveal that the interactions between molecules (e.g. Triptorelin and PEG) and LHRH receptors are dominated by van der Waals energies, while the interactions of these molecules with cell membrane are dominated by electrostatic interactions. Moreover, both experimental and computational results reveal that PEG serves as an effective coating that enhances adhesive interactions to breast cancer cells that over-express LHRH receptors, while reduces the adhesion to normal breast cells. Our results highlight the potential to develop Triptorelin-MNPs into tumor-specific MRI contrast agents and drug carriers.

STATEMENT OF SIGNIFICANCE

Systematic investigation of adhesive interactions between functionalized nanoparticles and cancer cells is of great importance in developing effective theranostic nanocarriers for targeted cancer therapy. Herein, we use a combination of atomic force microscopy technique and molecular dynamics simulations approach to explore the adhesive interactions at the nanoscale between Triptorelin-conjugated polyethylene glycol (PEG)-coated magnetite nanoparticles and normal/cancerous breast cells. This study characterizes and quantifies the work of adhesion, as well as adhesion forces, at the nanocarrier/cell interfaces, unravels the molecular origins of adhesive interactions and highlights the effectiveness of PEG coatings and Triptorelin ligands in the specific targeting of breast cancer cells. Our findings expand the fundamental understanding of nanoparticle/cell adhesion and provide guidelines for the design of more rational nanocarriers.

Computational prediction of drug solubility in water-based systems: Qualitative and quantitative approaches used in the current drug discovery and development setting

In this review we will discuss recent advances in computational prediction of solubility in water-based solvents. Our focus is set on recent advances in predictions of biorelevant solubility in media mimicking the human intestinal fluids and on new methods to predict the thermodynamic cycle rather than prediction of solubility in pure water through quantitative structure property relationships (QSPR). While the literature is rich in QSPR models for both solubility and melting point, a physicochemical property strongly linked to the solubility, recent advances in the modelling of these properties make use of theory and computational simulations to better predict these properties or processes involved therein (e.g. solid state crystal lattice packing, dissociation of molecules from the lattice and solvation). This review serves to provide an update on these new approaches and how they can be used to more accurately predict solubility, and also importantly, inform us on molecular interactions and processes occurring during drug dissolution and solubilisation.

Physico-chemical properties of aqueous drug solutions: From the basic thermodynamics to the advanced experimental and simulation results

The physical chemical properties of aqueous solutions of model compounds are illustrated in relation to hydration and solubility issues by using three perspectives: thermodynamic, spectroscopic and molecular dynamics simulations. The thermodynamic survey of the fundamental backgrounds of concentration dependence and experimental solubility results show some peculiar behavior of aqueous solutions with several types of similar solutes. Secondly, the use of a variety of experimental spectroscopic devices, operating under different experimental conditions of dimension and frequency, has produced a large amount of structural and dynamic data on aqueous solutions showing the richness of the information produced, depending on where and how the experiment is carried out. Finally, the use of molecular dynamics computational work is presented to highlight how the different types of solute functional groups and surface topologies organize adjacent water molecules differently. The highly valuable contribution of computer simulation studies in providing molecular explanations for experimental deductions, either of a thermodynamic or spectroscopic nature, is shown to have changed the current knowledge of many aqueous solution processes. While this paper is intended to provide a collective view on the latest literature results, still the presentation aims at a tutorial explanation of the potentials of the three methodologies in the field of aqueous solutions of pharmaceutical molecules.

HCM and DCM cardiomyopathy-linked α-tropomyosin mutations influence off-state stability and crossbridge interaction on thin filaments

Calcium regulation of cardiac muscle contraction is controlled by the thin-filament proteins troponin and tropomyosin bound to actin. In the absence of calcium, troponin-tropomyosin inhibits myosin-interactions on actin and induces muscle relaxation, whereas the addition of calcium relieves the inhibitory constraint to initiate contraction. Many mutations in thin filament proteins linked to cardiomyopathy appear to disrupt this regulatory switching. Here, we tested perturbations caused by mutant tropomyosins (E40K, DCM; and E62Q, HCM) on intra-filament interactions affecting acto-myosin interactions including those induced further by myosin association. Comparison of wild-type and mutant human α-tropomyosin (Tpm1.1) behavior was carried out using in vitro motility assays and molecular dynamics simulations. Our results show that E62Q tropomyosin destabilizes thin filament off-state function by increasing calcium-sensitivity, but without apparent affect on global tropomyosin structure by modifying coiled-coil rigidity. In contrast, the E40K mutant tropomyosin appears to stabilize the off-state, demonstrates increased tropomyosin flexibility, while also decreasing calcium-sensitivity. In addition, the E40K mutation reduces thin filament velocity at low myosin concentration while the E62Q mutant tropomyosin increases velocity. Corresponding molecular dynamics simulations indicate specific residue interactions that are likely to redefine underlying molecular regulatory mechanisms, which we propose explain the altered contractility evoked by the disease-causing mutations.

In silico design of small peptides antagonist against leptin receptor for the treatment of obesity and its associated immune-mediated diseases

Excess adiposity in obese inhibits negatively impacts immune function and host defence. Obesity is characterized by a state of low-grade, chronic inflammation in addition to disturbed levels of circulating nutrients and metabolic hormones. The impact of metabolic abnormalities on obesity-related co-morbidities has undergone intense scrutiny over the past decades. Thus, treatment of obesity and its associated immune-mediated diseases is challenging due to impaired function of leptin system. These disorders are managed through antibiotics and by cytokines replacement. However, the effectiveness of cytokines coupled to the complexity of the cytokine network leads to severe side-effects, which can still occur after careful preclinical evaluation. In addition, synthetic immunotherapeutics carry a degree of risk, time-consuming and expensive. Hence, the complexity of existing therapy and adverse effects emphasizes the need for an alternative approach for the management of immune dysfunction associated with obesity. Computer-aided small molecule antibody technology has been successful in the design of novel biologicals for the diagnosis of diseases and therapeutic interventions. In this study, the crystal structure of leptin receptor (LEPR) complex with monoclonal antibody (9F8 Fab) was explored to predict Ag-Ab interactions using bioinformatics tools. The LEPR of complementarity-determining region (CDR) loops were mutated with published positive control residues of Ser, Thr, Tyr, Trp, and Phe to design a set of 678 peptides which were evaluated through Ag-peptide docking, binding free-energies, and interaction energies. Thus, hypothesized novel peptides can be explored as clinically applicable antagonists for the treatment of obesity and associated immune-mediated diseases.

Identification, expression analysis, and molecular modeling of Iron-deficiency-specific clone 3 (Ids3)-like gene in hexaploid wheat

Graminaceous plants secrete hydroxylated phytosiderophores encoded by the genes iron-deficiency-specific clone 2 (Ids2) and iron-deficiency-specific clone 3 (Ids3). An effort was made to identify a putative ortholog of Hodeum vulgare Ids3 gene in hexaploid wheat. The protein structure of TaIDS3 was modeled using homology modeling and structural behavior of modeled structure was analyzed at 20 ns. The simulation trajectory using molecular dynamics simulation suggested the model to be stable with no large fluctuations in residues and local domain level RMSF values (< 2.4 Å). In addition, the ProFunc results also predict the functional similarity between the proteins of HvIDS3 and its wheat ortholog (TaIDS3). The TaIds3 gene was assigned to the telomeric region of chromosome arm 7AS which supports the results obtained through bioinformatics analysis. The relative expression analysis of TaIds3 indicated that the detectable expression of TaIds3 is induced after 5th day of Fe starvation and increases gradually up to 15th day, and thereafter, it decreases until 35th day of Fe-starvation. This reflects that Fe deficiency directly regulates the induction of TaIds3 in the roots of hexaploid wheat. The identification of HvIds3-like gene in wheat has opened up new opportunities to enhance the nutrient quality in wheat through biofortification program.

Physical Accuracy Leads to Biological Relevance: Best Practices For Simulating Ligand-Gated Ion Channels Interacting With General Anesthetics

Efforts to detect binding modes of general anesthetics (GAs) for pentameric ligand-gated ion channels (pLGICs) are often complicated by a large number of indicated sites, as well as the challenges of ranking sites by affinity and determining which sites are occupied at clinical concentrations. Physics-based computational methods offer a powerful route for determining affinities of ligands to isolated binding sites, but preserving accuracy is essential. This chapter describes a step-by-step approach to multiple methods for identifying candidate sites and quantifying binding affinities and also discusses limitations and common pitfalls.

Aggregation and metal-complexation behaviour of THPP porphyrin in ethanol/water solutions as function of pH

The effect of pH change on 5,10,15,20-Tetrakis(4-hydroxyphenyl)-21H,23H-porphine (THPP) with its aggregation as function of water-ethanol mixture was studied with UV-vis, fluorescence, Raman and computational analysis. In neutral pH, THPP was present as free-base and, increasing the water amount, aggregation occurred with the formation of H- and J-aggregates. The aggregation constant and the concentration of dimers were calculated, other information about the dimer aggregation were evaluated by computational study. In acidic pH, by the insertions of two hydrogens in the porphyrin rings, the porphyrin changed its geometry with a ring deformation confirmed by red-shifted spectrum and quenching in fluorescence; at this low pH, increasing the water amount, the acidic form (THPPH₂)²⁺ resulted more stable due to a polar environment with stronger interaction by hydrogen bonding. In basic pH, reached by NH₄OH, THPP porphyrin was able to react with alkali metals in order to form sitting-atop complex (M₂THPP) confirmed by the typical absorption spectrum of metallo-porphyrin, Raman spectroscopy and by computational analysis.

How structural elements evolving from bacterial to human SLC6 transporters enabled new functional properties

Background

Much of the structure-based mechanistic understandings of the function of SLC6A neurotransmitter transporters emerged from the study of their bacterial LeuT-fold homologs. It has become evident, however, that structural differences such as the long N- and C-termini of the eukaryotic neurotransmitter transporters are involved in an expanded set of functional properties to the eukaryotic transporters. These functional properties are not shared by the bacterial homologs, which lack the structural elements that appeared later in evolution. However, mechanistic insights into some of the measured functional properties of the eukaryotic transporters that have been suggested to involve these structural elements are sparse or merely descriptive.

Results

To learn how the structural elements added in evolution enable mechanisms of the eukaryotic transporters in ways not shared with their bacterial LeuT-like homologs, we focused on the human dopamine transporter (hDAT) as a prototype. We present the results of a study employing large-scale molecular dynamics simulations and comparative Markov state model analysis of experimentally determined properties of the wild-type and mutant hDAT constructs. These offer a quantitative outline of mechanisms in which a rich spectrum of interactions of the hDAT N-terminus and C-terminus contribute to the regulation of transporter function (e.g., by phosphorylation) and/or to entirely new phenotypes (e.g., reverse uptake (efflux)) that were added in evolution.

Conclusions

The findings are consistent with the proposal that the size of eukaryotic neurotransmitter transporter termini increased during evolution to enable more functions (e.g., efflux) not shared with the bacterial homologs. The mechanistic explanations for the experimental findings about the modulation of function in DAT, the serotonin transporter, and other eukaryotic transporters reveal separate roles for the distal and proximal segments of the much larger N-terminus in eukaryotic transporters compared to the bacterial ones. The involvement of the proximal and distal segments — such as the role of the proximal segment in sustaining transport in phosphatidylinositol 4,5-bisphosphate-depleted membranes and of the distal segment in modulating efflux — may represent an evolutionary adaptation required for the function of eukaryotic transporters expressed in various cell types of the same organism that differ in the lipid composition and protein complement of their membrane environment.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0495-6) contains supplementary material, which is available to authorized users.

Recent computational studies of membrane interaction and disruption of human islet amyloid polypeptide: Monomers, oligomers and protofibrils

The amyloid deposits of human islet amyloid polypeptide (hIAPP) are found in type 2 diabetes patients. hIAPP monomer is intrinsically disordered in solution, whereas it can form amyloid fibrils both in vivo and in vitro. Extensive evidence suggests that hIAPP causes the disruption of cellular membrane, and further induces cytotoxicity and the death of islet β-cells in pancreas. The presence of membrane also accelerates the hIAPP fibril formation. hIAPP oligomers and protofibrils in the early stage of aggregation were reported to be the most cytotoxic, disrupting the membrane integrity and giving rise to the pathological process. The detailed molecular mechanisms of hIAPP-membrane interactions and membrane disruption are complex and remain mostly unknown. Here in this review, we focus on recent computational studies that investigated the interactions of full length and fragmentary hIAPP monomers, oligomers and protofibrils with anionic, zwitterionic and mixed anionic-zwitterionic lipid bilayers. We mainly discuss the binding orientation of monomers at membrane surface, the conformational ensemble and the oligomerization of hIAPP inside membranes, the effect of lipid composition on hIAPP oligomers/protofibrils-membrane interactions, and the hIAPP-induced membrane perturbation. This review provides mechanistic insights into the interactions between hIAPP and lipid bilayers with different lipid composition at an atomistic level, which is helpful to understand the hIAPP cytotoxicity mediated by membrane. This article is part of a Special Issue entitled: Protein Aggregation and Misfolding at the Cell Membrane Interface edited by Ayyalusamy Ramamoorthy.

Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis

Background

Non-small cell lung cancer (NSCLC) with activating EGFR mutations, especially exon 19 deletions and the L858R point mutation, is particularly responsive to gefitinib and erlotinib. However, the sensitivity varies for less common and rare EGFR mutations. There are various explanations for the low sensitivity of EGFR exon 20 insertions and the exon 20 T790 M point mutation to gefitinib/erlotinib. However, few studies discuss, from a structural perspective, why less common mutations, like G719X and L861Q, have moderate sensitivity to gefitinib/erlotinib.

Results

To decode the drug sensitivity/selectivity of EGFR mutants, it is important to analyze the interaction between EGFR mutants and EGFR inhibitors. In this paper, the 30 most common EGFR mutants were selected and the technique of protein-ligand interaction fingerprint (IFP) was applied to analyze and compare the binding modes of EGFR mutant-gefitinib/erlotinib complexes. Molecular dynamics simulations were employed to obtain the dynamic trajectory and a matrix of IFPs for each EGFR mutant-inhibitor complex. Multilinear Principal Component Analysis (MPCA) was applied for dimensionality reduction and feature selection. The selected features were further analyzed for use as a drug sensitivity predictor. The results showed that the accuracy of prediction of drug sensitivity was very high for both gefitinib and erlotinib. Targeted Projection Pursuit (TPP) was used to show that the data points can be easily separated based on their sensitivities to gefetinib/erlotinib.

Conclusions

We can conclude that the IFP features of EGFR mutant-TKI complexes and the MPCA-based tensor object feature extraction are useful to predict the drug sensitivity of EGFR mutants. The findings provide new insights for studying and predicting drug resistance/sensitivity of EGFR mutations in NSCLC and can be beneficial to the design of future targeted therapies and innovative drug discovery.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2093-6) contains supplementary material, which is available to authorized users.

The effect of the relative permittivity on the tactoid formation in nanoplatelet systems. A combined computer simulation, SAXS, and osmotic pressure study

The structural properties, and the intracrystalline swelling of Na⁺-, and Ca²⁺-montmorillonite (Na-, and Ca-mmt) have been investigated as an effect of decreasing the relative permittivity of the solvent, i.e. from water to ethanol (EtOH), utilizing the experimental techniques; small angle X-ray scattering (SAXS) and osmotic pressure measurements. The experimental data were compared with the continuum model, utilizing coarse-grained molecular dynamics bulk simulations, Monte Carlo simulations of two infinite parallel surfaces corresponding to two clay platelets, and the strong coupling theory. It was found that it is possible to tune the electrostatic interactions to obtain a transition from a repulsive to an attractive system for the Na-mmt by increasing the EtOH concentration, i.e. the Bjerrum length increases, and hence, the attractive ion-ion correlation forces are enhanced. A qualitative agreement was observed between the simulations and the experimental results. Moreover, a non-monotonic behavior of the intracrystalline swelling of Ca-mmt as a function of EtOH concentration was captured experimentally, where an increase in the osmotic pressure, and hence, an increase in the d-spacing was found at low concentrations, indicating that repulsive short-ranged interactions dominate in the system. Theoretically, the non-monotonic behavior could not be captured with the continuum model, probably due to the limitation that the electrostatic interactions solely enters the Hamiltonian via the Bjerrum length.

Modeling of ultra-small lipid nanoparticle surface charge for targeting glioblastoma

Surface modification of ultra-small nanostructured lipid carriers (usNLC) via introduction of a positive charge is hypothesized to prompt site-specific drug delivery for glioblastoma multiforme (GBM) treatment. A more effective interaction with negatively charged lipid bilayers, including the blood-brain barrier (BBB), will facilitate the nanoparticle access to the brain. For this purpose, usNLC with a particle size of 43.82 ± 0.03 nm and a polydispersity index of 0.224 were developed following a Quality by Design approach. Monomeric and gemini surfactants, either with conventional headgroups or serine-based ones, were tested for the surface modification, and the respective safety and efficacy to target GBM evaluated. A comprehensive in silico-in vitro approach is also provided based on molecular dynamics simulations and cytotoxicity studies. Overall, monomeric serine-derived surfactants displayed the best performance, considering altogether particle size, zeta potential, cytotoxic profile and cell uptake. Although conventional surfactants were able to produce usNLC with suitable physicochemical properties and cell uptake, their use is discouraged due to their high cytotoxicity. This study suggests that monomeric serine-derived surfactants are promising agents for developing nanosystems aiming at brain drug delivery.

Exploring the Viral Channel KcvPBCV-1 Function via Computation

Viral potassium channels (Kcv) are homologous to the pore module of complex \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {K}^+$$\end{document}K+-selective ion channels of cellular organisms. Due to their relative simplicity, they have attracted interest towards understanding the principles of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {K}^+$$\end{document}K+ conduction and channel gating. In this work, we construct a homology model of the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\hbox {Kcv}}_{\text{PBCV-1}}$$\end{document}KcvPBCV-1 open state, which we validate by studying the binding of known blockers and by monitoring ion conduction through the channel. Molecular dynamics simulations of this model reveal that the re-orientation of selectivity filter carbonyl groups coincides with the transport of potassium ions, suggesting a possible mechanism for fast gating. In addition, we show that the voltage sensitivity of this mechanism can originate from the relocation of potassium ions inside the selectivity filter. We also explore the interaction of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\hbox {Kcv}}_{\text{PBCV-1}}$$\end{document}KcvPBCV-1 with the surrounding bilayer and observe the binding of lipids in the area between two adjacent subunits. The model is available to the scientific community to further explore the structure/function relationship of Kcv channels.

A structural preview of aquaporin 8 via homology modeling of seven vertebrate isoforms

Background

Aquaporins (AQPs) facilitate the passage of small neutral polar molecules across membranes of the cell. In animals there are four distinct AQP subfamilies, whereof AQP8 homologues constitute one of the smallest subfamilies with just one member in man. AQP8 conducts water, ammonia, urea, glycerol and H₂O₂ through various membranes of animal cells. This passive channel has been connected to a number of phenomena, such as volume change of mitochondria, ammonia neurotoxicity, and mitochondrial dysfunction related to oxidative stress. Currently, there is no experimentally determined structure of an AQP8, hence the structural understanding of this subfamily is limited. The recently solved structure of the plant AQP, AtTIP2;1, which has structural and functional features in common with AQP8s, has opened up for construction of homology models that are likely to be more accurate than previous models.

Results

Here we present homology models of seven vertebrate AQP8s. Modeling based on the AtTIP2;1 structure alone resulted in reasonable models except for the pore being blocked by a phenylalanine that is not present in AtTIP2;1. To achieve an open pore, these models were supplemented with models based on the bacterial water specific AQP, EcAqpZ, creating a chimeric monomeric model for each AQP8 isoform. The selectivity filter (also named the aromatic/arginine region), which defines the permeant substrate profile, comprises five amino acid residues in AtTIP2;1, including a histidine coming from loop C. Compared to AtTIP2;1, the selectivity filters of modelled AQP8s only deviates in that they are slightly more narrow and more hydrophobic due to a phenylalanine replacing the histidine from loop C. Interestingly, the models do not exclude the existence of a side pore beneath loop C similar to that described in the structure of AtTIP2;1.

Conclusions

Our models concur that AQP8s are likely to have an AtTIP2;1-like selectivity filter. The detailed description of the expected configuration of residues in the selectivity filters of AQP8s provides an excellent starting point for planning of as well as rationalizing the outcome of mutational studies. Our strategy to compile hybrid models based on several templates may prove useful also for other AQPs for which structural information is limited.

Electronic supplementary material

The online version of this article (10.1186/s12900-018-0081-8) contains supplementary material, which is available to authorized users.

Insertion of Dengue E into lipid bilayers studied by neutron reflectivity and molecular dynamics simulations

The envelope (E) protein of Dengue virus rearranges to a trimeric hairpin to mediate fusion of the viral and target membranes, which is essential for infectivity. Insertion of E into the target membrane serves to anchor E and possibly also to disrupt local order within the membrane. Both aspects are likely to be affected by the depth of insertion, orientation of the trimer with respect to the membrane normal, and the interactions that form between trimer and membrane. In the present work, we resolved the depth of insertion, the tilt angle, and the fundamental interactions for the soluble portion of Dengue E trimers (sE) associated with planar lipid bilayer membranes of various combinations of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-rac-glycerol (POPG), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), and cholesterol (CHOL) by neutron reflectivity (NR) and by molecular dynamics (MD) simulations. The results show that the tip of E containing the fusion loop (FL) is located at the interface of the headgroups and acyl chains of the outer leaflet of the lipid bilayers, in good agreement with prior predictions. The results also indicate that E tilts with respect to the membrane normal upon insertion, promoted by either the anionic lipid POPG or CHOL. The simulations show that tilting of the protein correlates with hydrogen bond formation between lysines and arginines located on the sides of the trimer close to the tip (K246, K247, and R73) and nearby lipid headgroups. These hydrogen bonds provide a major contribution to the membrane anchoring and may help to destabilize the target membrane.

Assessment of Simple Models for Molecular Simulation of Ethylene Carbonate and Propylene Carbonate as Solvents for Electrolyte Solutions

Progress in understanding liquid ethylene carbonate (EC) and propylene carbonate (PC) on the basis of molecular simulation, emphasizing simple models of interatomic forces, is reviewed. Results on the bulk liquids are examined from the perspective of anticipated applications to materials for electrical energy storage devices. Preliminary results on electrochemical double-layer capacitors based on carbon nanotube forests and on model solid-electrolyte interphase (SEI) layers of lithium ion batteries are considered as examples. The basic results discussed suggest that an empirically parameterized, non-polarizable force field can reproduce experimental structural, thermodynamic, and dielectric properties of EC and PC liquids with acceptable accuracy. More sophisticated force fields might include molecular polarizability and Buckingham-model description of inter-atomic overlap repulsions as extensions to Lennard-Jones models of van der Waals interactions. Simple approaches should be similarly successful also for applications to organic molecular ions in EC/PC solutions, but the important case of Li\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^+$$\end{document}+ deserves special attention because of the particularly strong interactions of that small ion with neighboring solvent molecules. To treat the Li\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^+$$\end{document}+ ions in liquid EC/PC solutions, we identify interaction models defined by empirically scaled partial charges for ion-solvent interactions. The empirical adjustments use more basic inputs, electronic structure calculations and ab initio molecular dynamics simulations, and also experimental results on Li\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^+$$\end{document}+ thermodynamics and transport in EC/PC solutions. Application of such models to the mechanism of Li\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^+$$\end{document}+ transport in glassy SEI models emphasizes the advantage of long time-scale molecular dynamics studies of these non-equilibrium materials.

Vitamin D receptor (VDR) non-synonymous single nucleotide polymorphisms (nsSNPs) affect the calcitriol drug response - A theoretical insight

Pharmacogenetics and pharmacogenomics have become presumptive with advancements in next-generation sequencing technology. In complex diseases, distinguishing the feasibility of pathogenic and neutral disease-causing variants is a time consuming and expensive process. Recent drug research and development processes mainly rely on the relationship between the genotype and phenotype through Single nucleotide polymorphisms (SNPs). The SNPs play an indispensable role in elucidating the individual's vulnerability to disease and drug response. The understanding of the interplay between these leads to the establishment of personalized medicine. In order to address this issue, we developed a computational pipeline of vitamin D receptor (VDR) for SNP centered study by application of elegant molecular docking and molecular dynamics simulation approaches. In a few SNPs the volume of the binding cavities has increased in mutant structures when compared to the wild type, indicating a weakening in interaction (699.1 ų in wild type Vs. 738.8 in Leu230Val, 820.7 ų in Arg247Leu). This also differently reflected in the H-bond interactions and binding free energies -169.93 kcal/mol (wild type) Vs -156.43 kcal/mol (R154W), -105.49 kcal/mol (R274L) in Leu230Val and Arg247Leu respectively. Although we could not find noteworthy changes in the binding free energies and binding pocket in the remaining mutations, the H-bond interactions made these SNPs deleterious. Thus, we further analyzed the H-bond interactions and distances using molecular dynamics (MD) simulation studies.

Molecular dynamics investigation of the mechanical behavior of multi-layered graphyne and its family under tensile loading

This paper aims to study the mechanical properties of the multi-layered graphyne and other members of the graphyne family under the uniaxial tensile loading. For this purpose, molecular dynamics simulations are used. The effects of the size and number of layers on the fracture and elastic properties are studied. It is shown that Young's modulus of the zigzag multi-layered graphyne is slightly larger than armchair one. Comparing the stress-strain curves of the multi-layered graphynes with different number of layers, it is observed that the fracture stress and strain of the nanosheets are inversely related to the number of layers. Investigating the influence of the number of acetylene linkage in the structure of the graphyne-n family on their mechanical properties, it is shown increasing the number of triple bonds leads to weakening the fracture stress and Young's modulus of the nanosheet.

Computational Approaches to Matrix Metalloprotease Drug Design

Matrix metalloproteinases (MMPs) are a family of zinc-containing enzymes required for homeostasis. These enzymes are an important class of drug targets as their over expression is associated with many disease states. Most of the inhibitors reported against this class of proteins have failed in clinical trials due to lack of specificity. In order to assist in drug design endeavors for MMP targets, a computationally tractable pathway is presented, comprising, (1) docking of small molecule inhibitors against the target MMPs, (2) derivation of quantum mechanical charges on the zinc ion in the active site and the amino acids coordinating with zinc including the inhibitor molecule, (3) molecular dynamics simulations on the docked ligand-MMP complexes, and (4) evaluation of binding affinities of the ligand-MMP complexes via an accurate scoring function for zinc containing metalloprotein-ligand complexes. The above pathway was applied to study the interaction of the inhibitor Batimastat with MMPs, which resulted in a high correlation between the predicted and experimental binding free energies, suggesting the potential applicability of the pathway.

Activity-based classification circumvents affinity prediction problems for pyrrolidine carboxamide inhibitors of InhA

Developing reliable structure-based activity prediction models for a particular ligand series can be challenging if the target is flexible and the affinity range of the training compounds is narrow. For a data set of 44 pyrrolidine carboxamide inhibitors of the mycobacterial enoyl-ACP-reductase InhA this proved to be case, as scoring methods of various origin and complexity did not succeed in providing practically useful correlations with experimental inhibition data. In contrast, logistic regression models for activity-based classification trained with combinations of scoring functions led to good separation of the more active inhibitors from the weakest compounds. The approach is suggested as an alternative in cases where classical scoring and ranking procedures fail.

Structural and energetic basis for the molecular recognition of dual synthetic vs. natural inhibitors of EGFR/HER2

Activation of EGFR starts by ligand binding at the extracellular domain which results in homo and heterodimerization, leading to phosphorylation, activation of downstream signaling pathways which upregulate expression of genes, proliferation and angiogenesis. Abnormalities in the expression of EGFR play a critical role in the development of different types of cancer. HER2 is the preferred heterodimerization partner for EGFR; this biological characteristic together with the high percentage of structural homology has been exploited in the design of dual synthetic inhibitors against EGFR/HER2. Herein we combined structural data and molecular dynamics (MD) simulations coupled to an MMGBSA approach to provide insight into the binding mechanism between two dual synthetics (lapatinib and TAK-285) and one dual natural inhibitor (EGCG) which target EGFR/HER2. In addition, we proposed some EGCG derivatives which were filtered through in silico screening. Structural analysis demonstrated that the coupling of synthetic, natural or newly designed compounds impacts the conformational space of EGFR and HER2 differently. Energetic analysis points out that lapatinib and TAK-285 have better affinity for inactive EGFR than the active EGFR state or HER2, whereas some EGCG derivatives seem to form binding affinities similar to those observed for lapatinib or TAK-285.

The structural determinants of the bitopic binding mode of a negative allosteric modulator of the dopamine D2 receptor

SB269652 is a negative allosteric modulator of the dopamine D₂ receptor (D₂R) yet possesses structural similarity to ligands with a competitive mode of interaction. In this study, we aimed to understand the ligand-receptor interactions that confer its allosteric action. We combined site-directed mutagenesis with molecular dynamics simulations using both SB269652 and derivatives from our previous structure activity studies. We identify residues within the conserved orthosteric binding site (OBS) and a secondary binding pocket (SBP) that determine affinity and cooperativity. Our results indicate that interaction with the SBP is a requirement for allosteric pharmacology, but that both competitive and allosteric derivatives of SB269652 can display sensitivity to the mutation of a glutamate residue (E95^2.65) within the SBP. Our findings provide the molecular basis for the differences in affinity between SB269652 derivatives, and reveal how changes to interactions made by the primary pharmacophore of SB269652 in the orthosteric pocket can confer changes in the interactions made by the secondary pharmacophore in the SBP. Our insights provide a structure-activity framework towards rational optimization of bitopic ligands for D₂R with tailored competitive versus allosteric properties.

Molecular Basis of Ligand Dissociation from G Protein-Coupled Receptors and Predicting Residence Time

G protein-coupled receptors (GPCRs) are integral membrane proteins and represent the largest class of drug targets. During the past decades progress in structural biology has enabled the crystallographic elucidation of the architecture of these important macromolecules. It also provided atomic-level visualization of ligand-receptor interactions, dramatically boosting the impact of structure-based approaches in drug discovery. However, knowledge obtained through crystallography is limited to static structural information. Less information is available showing how a ligand associates with or dissociates from a given receptor, whose importance is in fact increasingly recognized by the drug research community. Owing to recent advances in computer power and algorithms, molecular dynamics stimulations have become feasible that help in analyzing the kinetics of the ligand binding process. Here, we review what is currently known about the dynamics of GPCRs in the context of ligand association and dissociation, as determined through both crystallography and computer simulations. We particularly focus on the molecular basis of ligand dissociation from GPCRs and provide case studies that predict ligand dissociation pathways and residence time.

Mechanism Responsible for Intercalation of Dimethyl Sulfoxide in Kaolinite: Molecular Dynamics Simulations

Intercalation is the promising strategy to expand the interlayer region of kaolinite for their further applications. Herein, the adaptive biasing force (ABF) accelerated molecular dynamics simulations were performed to calculate the free energies involved in the kaolinite intercalation by dimethyl sulfoxide (DMSO). Additionally, the classical all atom molecular dynamics simulations were carried out to calculate the interfacial interactions between kaolinite interlayer surfaces and DMSO with the aim at exploring the underlying force that drives the DMSO to enter the interlayer space. The results showed that the favorable interaction of DMSO with both kaolinite interlayer octahedral surface and tetrahedral surface can help in introducing DMSO enter kaolinite interlayer. The hydroxyl groups on octahedral surface functioned as H-donors attracting the S=O groups of DMSO through hydrogen bonding interaction. The tetrahedral surface featuring hydrophobic property attracted the methyl groups of DMSO through hydrophobic interaction. The results provided a detailed picture of the energetics and interlayer structure of kaolinite-DMSO intercalate.

Replica Exchange Molecular Dynamics: A Practical Application Protocol with Solutions to Common Problems and a Peptide Aggregation and Self-Assembly Example

Protein aggregation is associated with many human diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and type II diabetes (T2D). Understanding the molecular mechanism of protein aggregation is essential for therapy development. Molecular dynamics (MD) simulations have been shown as powerful tools to study protein aggregation. However, conventional MD simulations can hardly sample the whole conformational space of complex protein systems within acceptable simulation time as it can be easily trapped in local minimum-energy states. Many enhanced sampling methods have been developed. Among these, the replica exchange molecular dynamics (REMD) method has gained great popularity. By combining MD simulation with the Monte Carlo algorithm, the REMD method is capable of overcoming high energy-barriers easily and of sampling sufficiently the conformational space of proteins. In this chapter, we present a brief introduction to REMD method and a practical application protocol with a case study of the dimerization of the 11-25 fragment of human islet amyloid polypeptide (hIAPP(11-25)), using the GROMACS software. We also provide solutions to problems that are often encountered in practical use, and provide some useful scripts/commands from our research that can be easily adapted to other systems.

Molecular Modeling of Chemoreceptor:Ligand Interactions

Docking algorithms have been widely used to elucidate ligand:receptor interactions that are important in biological function. Here, we introduce an in-house developed docking-refinement protocol that combines the following innovative features. (1) The use of multiple short molecular dynamics (MD) docking simulations, with residues within the binding pocket of the receptor unconstrained, so that the binding modes of the ligand in the binding pocket may be exhaustively examined. (2) The initial positioning of the ligand within the binding pocket based on complementary shape, and the use of both harmonic and quartic spherical potentials to constrain the ligand in the binding pocket during multiple short docking simulations. (3) The selection of the most probable binding modes generated by the short docking simulations using interaction energy calculations, as well as the subsequent application of all-atom MD simulations and physical-chemistry based free energy calculations to elucidate the most favorable binding mode of the ligand in complex with the receptor. In this chapter, we provide step-by-step instructions on how to computationally investigate the binding of small-molecule ligands to protein receptors by examining as control and test cases, respectively, the binding of L-serine and R-3,4-dihydroxymandelic acid (R-DHMA) to the Escherichia coli chemoreceptor Tsr. Similar computational strategies can be used for the molecular modeling of a series of ligand:protein receptor interactions.

YASARA: A Tool to Obtain Structural Guidance in Biocatalytic Investigations

In biocatalysis, structural knowledge regarding an enzyme and its substrate interactions complements and guides experimental investigations. Structural knowledge regarding an enzyme or a biocatalytic reaction system can be generated through computational techniques, such as homology- or molecular modeling. For this type of computational work, a computer program developed for molecular modeling of proteins is required. Here, we describe the use of the program YASARA Structure. Protocols for two specific biocatalytic applications, including both homology modeling and molecular modeling such as energy minimization, molecular docking simulations and molecular dynamics simulations, are shown. The applications are chosen to give realistic examples showing how structural knowledge through homology and molecular modeling is used to guide biocatalytic investigations and protein engineering studies.

Studying Kv Channels Function using Computational Methods

In recent years, molecular modeling techniques, combined with MD simulations, provided significant insights on voltage-gated (Kv) potassium channels intrinsic properties. Among the success stories are the highlight of molecular level details of the effects of mutations, the unraveling of several metastable intermediate states, and the influence of a particular lipid, PIP₂, in the stability and the modulation of Kv channel function. These computational studies offered a detailed view that could not have been reached through experimental studies alone. With the increase of cross disciplinary studies, numerous experiments provided validation of these computational results, which endows an increase in the reliability of molecular modeling for the study of Kv channels. This chapter offers a description of the main techniques used to model Kv channels at the atomistic level.

Hybrid Methods for Macromolecular Modeling by Molecular Mechanics Simulations with Experimental Data

Hybrid approaches for the modeling of macromolecular complexes that combine computational molecular mechanics simulations with experimental data are discussed. Experimental data for biological molecular structures are often low-resolution, and thus, do not contain enough information to determine the atomic positions of molecules. This is especially true when the dynamics of large macromolecules are the focus of the study. However, computational modeling can complement missing information. Significant increase in computational power, as well as the development of new modeling algorithms allow us to model structures of biological macromolecules reliably, using experimental data as references. We review the basics of molecular mechanics approaches, such as atomic model force field, and coarse-grained models, molecular dynamics simulation and normal mode analysis and describe how they could be used for flexible fitting hybrid modeling with experimental data, especially from cryo-EM and SAXS.

Design of Drugs by Filtering Through ADMET, Physicochemical and Ligand-Target Flexibility Properties

There is a synergistic interaction between medicinal chemistry, chemoinformatics, and bioinformatics. The last one includes analyses of sequences as well as structural analysis which employ computational techniques such as docking studies and molecular dynamics (MD) simulations. Over the last years these techniques have allowed the development of new accurate computational tools for drug design. As a result, there have been an increased number of publications where computational methods such as pharmacophore modeling, de novo drug design, evaluation of physicochemical properties, and analysis of ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties have been quite useful for eliminating the compounds with poor physicochemical or toxicological properties. Furthermore, using MD simulations and docking analysis, it is possible to estimate the binding energy of the protein-ligand complexes by using scoring functions, as well as to structurally depict the binding pose of the compounds on proteins, in order to select the best evaluated compounds for subsequent synthetizing and evaluation through biological assays. In this work, we describe some computational tools that have been used for structure-based drug design of new compounds that target histone deacetylases (HDACs), which are known to be potential targets in cancer and parasitic diseases.

Nanoscale Dynamics and Energetics of Proteins and Protein-Nucleic Acid Complexes in Classical Molecular Dynamics Simulations

The present article describes techniques for classical simulations of proteins and protein-nucleic acid complexes, revealing their dynamics and protein-substrate binding energies. The approach is based on classical atomistic molecular dynamics (MD) simulations of the experimentally determined structures of the complexes. MD simulations can provide dynamics of complexes in realistic solvents on microsecond timescales, and the free energy methods are able to provide Gibbs free energies of binding of substrates, such as nucleic acids, to proteins. The chapter describes methodologies for the preparation of computer models of biomolecular complexes and free energy perturbation methodology for evaluating Gibbs free energies of binding. The applications are illustrated with examples of snapshots of proteins and their complexes with nucleic acids, as well as the precise Gibbs free energies of binding.

Fundamental interfacial mechanisms underlying electrofreezing

This article reviews the fundamental interfacial mechanisms underlying electrofreezing (promotion of ice nucleation via the application of an electric field). Electrofreezing has been an active research topic for many decades, with applications in food preservation, cryopreservation, cryogenics and ice formation. There is substantial literature detailing experimental and simulations-based studies, which aim to understand the complex mechanisms underlying accelerated ice nucleation in the presence of electric fields and electrical charge. This work provides a critical review of all such studies. It is noted that application-focused studies of electrofreezing are excluded from this review; such studies have been previously reviewed in literature. This review focuses only on fundamental studies, which analyze the physical mechanisms underlying electrofreezing. Topics reviewed include experimental studies on electrofreezing (DC and AC electric fields), pyroelectricity-based control of freezing, molecular dynamics simulations of electrofreezing, and thermodynamics-based explanations of electrofreezing. Overall, it is seen that electrofreezing can enable disruptive advancements in the control of liquid-to-solid phase change, and that our current understanding of the underlying mechanisms can be significantly improved through further studies of various interfacial effects coming into play.

In Silico Evaluation of Variable pH on the Binding of Epidermal Growth Factor Receptor Ectodomain to its Ligand Through Molecular Dynamics Simulation in Tumors

Many aggressive and metastatic cancer cell types show Warburg Effect; therefore, it is a possible adaptation helping cancer cells to rapidly divide and utilize the glycolytic intermediates for biosynthesis of ribose sugars (for nucleotide biosynthesis), fatty acid synthesis (lipids for membrane synthesis), NADPH (cellular currency for reductive biosynthesis) and lactate. This in due course results in decrease of extracellular pH, leading to acidic tumor micro-environment. EGFR is a crucial cell surface signaling receptor implicated in cancer cell survival and progression. This warrants studying the effect of the acidic micro-environmental conditions on the binding of the EGFR cell surface receptor to one of its natural extracellular ligand EGF. We exploited in silico approaches: molecular dynamics simulation at variable pH and MM-GBSA free energy of binding calculation method to evaluate the effect of this change in microenvironmental pH. Through the present study it is reported that at pH 6.6 the EGFR binds to EGF with decreased free energy of binding as compared to pH 7.2.

Conformational landscapes of membrane proteins delineated by enhanced sampling molecular dynamics simulations

The expansion of computational power, better parameterization of force fields, and the development of novel algorithms to enhance the sampling of the free energy landscapes of proteins have allowed molecular dynamics (MD) simulations to become an indispensable tool to understand the function of biomolecules. The temporal and spatial resolution of MD simulations allows for the study of a vast number of processes of interest. Here, we review the computational efforts to uncover the conformational free energy landscapes of a subset of membrane proteins: ion channels, transporters and G-protein coupled receptors. We focus on the various enhanced sampling techniques used to study these questions, how the conclusions come together to build a coherent picture, and the relationship between simulation outcomes and experimental observables.

Molecular dynamics analysis on axial buckling of functionalized carbon nanotubes in thermal environment

Molecular dynamics simulations are conducted to investigate the buckling characteristics of functionalized carbon nanotubes (f-CNTs) under axial compression at various temperatures. The influences of functionalization, content of functional groups, chirality and diameter, as well as temperature on buckling response of pristine and functionalized CNTs are investigated. It is found that the buckling capacity of CNTs deteriorates drastically by functionalization, though the increase in the content of functional groups slightly enhances their stability. Besides, the results show that temperature considerably contributes to the stability of nanotubes but interestingly it has the most pronounced impact on pristine CNTs than functionalized ones, as defective CNTs.

Reduced state transition barrier of CDK6 from open to closed state induced by Thr177 phosphorylation and its implication in binding modes of inhibitors

BACKGROUND

CDK6 is considered as a highly validated anticancer drug target due to its essential role in regulating cell cycle progression at G1 restriction point. Activation of CDK6 requires the phosphorylation of Thr177 on A-loop, but the structural insights of the activation mechanism remain unclear.

METHODS

Herein, all-atoms molecular dynamics (MD) simulations were used to study the effects of Thr177 phosphorylation on the dynamic structure of CDK6-Vcyclin complex.

RESULTS

MD results indicated that the free energy barrier of the transition from open to closed state decreased ~47.2% after Thr177 phosphorylation. Key steps along the state transition process were obtained from a cluster analysis. Binding preference of ten different inhibitors to open or closed state were also investigated through molecular docking along with MD simulations methods.

CONCLUSIONS

Our results indicated that Thr177 phosphorylation increased the flexibility around the ATP-binding pocket. The transition of the ATP-binding pocket between open and closed states should be considered for understanding the binding of CDK6 inhibitors.

GENERAL SIGNIFICANCE

This work could deepen the understanding of CDKs activation mechanism, and provide useful information for the discovery of new CDKs inhibitors with high affinity and specificity.

Computational membrane biophysics: From ion channel interactions with drugs to cellular function

The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Comparison of mechanistic transport cycle models of ABC exporters

ABC (ATP binding cassette) transporters, ubiquitous in all kingdoms of life, carry out essential substrate transport reactions across cell membranes. Their transmembrane domains bind and translocate substrates and are connected to a pair of nucleotide binding domains, which bind and hydrolyze ATP to energize import or export of substrates. Over four decades of investigations into ABC transporters have revealed numerous details from atomic-level structural insights to their functional and physiological roles. Despite all these advances, a comprehensive understanding of the mechanistic principles of ABC transporter function remains elusive. The human multidrug resistance transporter ABCB1, also referred to as P-glycoprotein (P-gp), is one of the most intensively studied ABC exporters. Using ABCB1 as the reference point, we aim to compare the dominating mechanistic models of substrate transport and ATP hydrolysis for ABC exporters and to highlight the experimental and computational evidence in their support. In particular, we point out in silico studies that enhance and complement available biochemical data. “This article is part of a Special Issue entitled: Beyond the Structure Function Horizon of Membrane Proteins edited by Ute Hellmich, Rupak Doshi and Benjamin McIlwain.”

Coming to Grips with Ambiguity: Ion Mobility-Mass Spectrometry for Protein Quaternary Structure Assignment

Multiprotein complexes are central to our understanding of cellular biology, as they play critical roles in nearly every biological process. Despite many impressive advances associated with structural characterization techniques, large and highly-dynamic protein complexes are too often refractory to analysis by conventional, high-resolution approaches. To fill this gap, ion mobility-mass spectrometry (IM-MS) methods have emerged as a promising approach for characterizing the structures of challenging assemblies due in large part to the ability of these methods to characterize the composition, connectivity, and topology of large, labile complexes. In this Critical Insight, we present a series of bioinformatics studies aimed at assessing the information content of IM-MS datasets for building models of multiprotein structure. Our computational data highlights the limits of current coarse-graining approaches, and compelled us to develop an improved workflow for multiprotein topology modeling, which we benchmark against a subset of the multiprotein complexes within the PDB. This improved workflow has allowed us to ascertain both the minimal experimental restraint sets required for generation of high-confidence multiprotein topologies, and quantify the ambiguity in models where insufficient IM-MS information is available. We conclude by projecting the future of IM-MS in the context of protein quaternary structure assignment, where we predict that a more complete knowledge of the ultimate information content and ambiguity within such models will undoubtedly lead to applications for a broader array of challenging biomolecular assemblies. Graphical Abstract ᅟ.

Modeling of flux, binding and substitution of urea molecules in the urea transporter dvUT

Urea transporters (UTs) are transmembrane proteins that transport urea molecules across cell membranes and play a crucial role in urea excretion and water balance. Modeling the functional characteristics of UTs helps us understand how their structures accomplish the functions at the atomic level, and facilitates future therapeutic design targeting the UTs. This study was based on the crystal structure of Desulfovibrio vulgaris urea transporter (dvUT). To model the binding behavior of urea molecules in dvUT, we constructed a cooperative binding model. To model the substitution of urea by the urea analogue N,N'-dimethylurea (DMU) in dvUT, we calculated the occupation probability of DMU along the urea pore and the ratio of the occupation probabilities of DMU at the external (Sext) and internal (Sint) binding sites, and we established the mutual substitution rule for binding and substitution of urea and DMU. Based on these calculations and modelings, together with the use of the Monte Carlo (MC) method, we further modeled the urea flux in dvUT, equilibrium urea binding to dvUT, and the substitution of urea by DMU in the dvUT. Our modeling results are in good agreement with the existing experimental functional data. Furthermore, the modelings have discovered the microscopic process and mechanisms of those functional characteristics. The methods and the results would help our future understanding of the underlying mechanisms of the diseases associated with impaired UT functions and rational drug design for the treatment of these diseases.

Structure-function studies of BPP-BrachyNH2 and synthetic analogues thereof with Angiotensin I-Converting Enzyme

The vasoactive proline-rich oligopeptide termed BPP-BrachyNH₂ (H-WPPPKVSP-NH₂) induces in vitro inhibitory activity of angiotensin I-converting enzyme (ACE) in rat blood serum. In the present study, the removal of N-terminal tryptophan or C-terminal proline from BPP-BrachyNH₂ was investigated in order to predict which structural components are important or required for interaction with ACE. Furthermore, the toxicological profile was assessed by in silico prediction and in vitro MTT assay. Two BPP-BrachyNH₂ analogues (des-Trp¹-BPP-BrachyNH₂ and des-Pro⁸-BPP-BrachyNH₂) were synthesized, and in vitro and in silico ACE inhibitory activity and toxicological profile were assessed. The des-Trp¹-BPP-BrachyNH₂ and des-Pro⁸-BPP-BrachyNH₂ were respectively 3.2- and 29.5-fold less active than the BPP-BrachyNH₂-induced ACE inhibitory activity. Molecular Dynamic and Molecular Mechanics Poisson-Boltzmann Surface Area simulations (MM-PBSA) demonstrated that the ACE/BBP-BrachyNH₂ complex showed lower binding and van der Wall energies than the ACE/des-Pro⁸-BPP-BrachyNH₂ complex, therefore having better stability. The removal of the N-terminal tryptophan increased the in silico predicted toxicological effects and cytotoxicity when compared with BPP-BrachyNH₂ or des-Pro⁸-BPP-BrachyNH₂. Otherwise, des-Pro⁸-BPP-BrachyNH₂ was 190-fold less cytotoxic than BPP-BrachyNH₂. Thus, the removal of C-terminal proline residue was able to markedly decrease both the BPP-BrachyNH₂-induced ACE inhibitory and cytotoxic effects assessed by in vitro and in silico approaches. In conclusion, the aminoacid sequence of BPP-BrachyNH₂ is essential for its ACE inhibitory activity and associated with an acceptable toxicological profile. The perspective of the interactions of BPP-BrachyNH₂ with ACE found in the present study can be used for development of drugs with differential therapeutic profile than current ACE inhibitors.

Functional mapping of the N-terminal arginine cluster and C-terminal acidic residues of Kir6.2 channel fused to a G protein-coupled receptor

Ion channel-coupled receptors (ICCRs) are original man-made ligand-gated ion channels created by fusion of G protein-coupled receptors (GPCRs) to the inward-rectifier potassium channel Kir6.2. GPCR conformational changes induced by ligand binding are transduced into electrical current by the ion channel. This functional coupling is closely related to the length of the linker region formed by the GPCR C-terminus (C-ter) and Kir6.2N-terminus (N-ter). Manipulating the GPCR C-ter length allows to finely tune the channel regulation, both in amplitude and sign (opening or closing Kir6.2). In this work, we demonstrate that the primary sequence of the channel N-terminal domain is an additional parameter for the functional coupling with GPCRs. As for all Kir channels, a cluster of basic residues is present in the N-terminal domain of Kir6.2 and is composed of 5 arginines which are proximal to the GPCR C-ter in the fusion proteins. Using a functional mapping approach, we demonstrate the role of specific arginines (R27 and R32) for the function of ICCRs, indicating that the position and not the cluster of positively-charged arginines is critical for the channel regulation by the GPCR. Following observations provided by molecular dynamics simulation, we explore the hypothesis of interaction of these arginines with acidic residues, and using site-directed mutagenesis, we identified aspartate D307 and glutamate E308 residues as critical for the function of ICCRs. These results demonstrate the critical role of the N-terminal and C-terminal charged residues of Kir6.2 for its allosteric regulation by the fused GPCR.

Computational study of the binding mechanism of medium chain acyl-CoA synthetase with substrate in Methanosarcina acetivorans

The acyl-AMP forming family of adenylating enzymes catalyzes the formation of acyl-CoA from an acyl substrate, ATP, and CoA, which is a metabolite of many catabolic and anabolic processes. The medium-chain acyl-CoA synthetase from Methanosarcina acetivorans, designated Macs_Ma, uses 2-methylbutyrate as its preferred substrate. It is reported that the interaction between the sidechain of Cys298 and Lys256 of this enzyme is important for the catalytic activity. The mutation of these residues resulted in the changes of the structure stability and the reduced or absence catalytic activity. In the present study, the binding mechanism between the substrate 2-methylbutyrate- AMP (2MeBA) and Macs_Ma were explored by integrating multiple computational methods including molecular docking, molecular dynamics simulations, binding free energy calculation, active site access channel analysis and principal component analysis. The binding free energy between WT, mutated Macs and substrate was calculated by MM-GBSA method, which indicated that the binding affinity between this enzyme and substrate was stronger in the WT than that in the mutated forms (K256L, K256T and C298Y). Per-residue binding free energy decomposition identified some residues, such as Gly327, Phe350, Gly351, Gln352 and Lys461, which are important for the enzyme and substrate binding affinity. The access channels of the mutant system (Macs^K256L, Macs^K256T and Macs^C298Y) were found to be different from those in the wild-type systems. It suggested that K256L and C298Y induced larger flexibility to the overall protein compared with the WT, whereas K256T induced larger flexibility to the partial protein compared with the WT by PCA vector porcupines. This study provides novel insight to understand the substrate binding mechanism of Macs and useful information for the rational enzyme design.

Elucidation of the molecular mechanism of heat shock proteins and its correlation with K722Q mutations in Lon protease

Cells withstand the effects of temperature change with the help of small heat shock proteins IbpA and IbpB. The IbpAB protein complex interacts with Lon protease in their free form and gets degraded at physiological temperature when there is no temperature stress. However, the proteolytic degradation of IbpAB is diminished when Lon is mutated. The mutation K722Q in Lon brings about some structural changes so that the proteolytic interactions between the heat shock proteins with that of the mutated Lon protease are lost. However, the detailed molecular aspects of the interactions are not yet fully understood. In the present, we made an attempt to analyze the biochemical aspects of the interactions between the small heat shock proteins IbpAB with wild type and mutant Lon protease. We for the first time deciphered the molecular details of the mechanism of interaction of small heat shock proteins with Lon protease bearing K722Q mutation i.e. the interaction pattern of heat shock proteins with mutant Lon protease at physiological temperature in absence of proteolytic machinery. Our study may therefore be useful to elucidate the mechanistic details of the correlation with IbpA, IbpB and Lon protease.

Structural dynamics of wild type and mutated forms of human L1 endonuclease and insights into its sequence specific nucleic acid binding mechanism: A molecular dynamics study

Biomolecular recognition of proteins and nucleic acids is mainly mediated by their structural features and the molecular dynamics simulations approach has been used to explore this recognition processes at the atomic level. L1-Endonuclease, an enzyme involved in L1 retrotransposition, cleaves the TA junction DNA (5'-TTTT/AA-3') and expresses high specificity for target site recognition. The present study highlights the structural features of L1-endonuclease as well as DNA responsible for such specific recognition. Especially, the importance of βB6-B5 hairpin loop in DNA recognition has been elucidated by analyzing the dynamics of Thr192 mutated L1-endonuclease. In addition, simulations of the endonuclease complexed with DNA substrates (sequences having TA and CG junctions) revealed the specificity of L1 endonuclease towards TA junction. Molecular dynamics simulations revealed that the βB6-B5 hairpin loop protrudes well into the minor groove of DNA having TA junction and induces DNA bending such that the width of minor groove is increased. Such endonuclease induced bending of TA junction DNA sequence positions the scissile phosphodiester bond of DNA for cleavage. The innate property of minor groove widening in TA junction than in CG junction is utilized by the βB6-βB5 hairpin loop of endonuclease while recognizing the DNA sequences. The present study also highlights the role of Mg²⁺ cation in catalysis and attempts to explore the possible target site DNA cleavage mechanism.

Decoupled side chain and backbone dynamics for proton translocation - M2 of influenza A

The 97 amino acid bitopic membrane protein M2 of influenza A forms a tetrameric bundle in which two of the monomers are covalently linked via a cysteine bridge. In its tetrameric assembly the protein conducts protons across the viral envelope and within intracellular compartments during the infectivity cycle of the virus. A key residue in the translocation of the protons is His-37 which forms a planar tetrad in the configuration of the bundle accepting and translocating the incoming protons from the N terminal side, exterior of the virus, to the C terminal side, inside the virus. With experimentally available data from NMR spectroscopy of the transmembrane domains of the tetrameric M2 bundle classical MD simulations are conducted with the protein bundle in different protonation stages in respect to His-37. A full correlation analysis (FCA) of the data sets with the His-37 tetrad either in a fully four times unprotonated or protonated state, assumed to mimic high and low pH in vivo, respectively, in both cases reveal asymmetric backbone dynamics. His-37 side chain rotation dynamics is increased at full protonation of the tetrad compared to the dynamics in the fully unprotonated state. The data suggest that proton translocation can be achieved by decoupled side chain or backbone dynamics. Graphical abstract Visualization of the tetrameric bundle of the transmembrane domains of M2 of influenza A after 200 ns of MD simulations (upper left). The four histidine residues 37 are either not protonated as in M2⁰ or fully protonated is in M2⁴⁺. The asymmetric dynamics of the backbones are shown after a full correlation analysis (FCA) in blue (lower left). The rotational dynamics of the χ2 dihedral angles of the histidines in M2⁰ (upper right) are less than those in M2⁴⁺ (lower right).

Trichoderma virens β-glucosidase I (BGLI) gene; expression in Saccharomyces cerevisiae including docking and molecular dynamics studies

BACKGROUND

Cellulose, a linear polymer of β 1-4, linked glucose, is the most abundant renewable fraction of plant biomass (lignocellulose). It is synergistically converted to glucose by endoglucanase (EG) cellobiohydrolase (CBH) and β-glucosidase (BGL) of the cellulase complex. BGL plays a major role in the conversion of randomly cleaved cellooligosaccharides into glucose. As it is well known, Saccharomyces cerevisiae can efficiently convert glucose into ethanol under anaerobic conditions. Therefore, S.cerevisiae was genetically modified with the objective of heterologous extracellular expression of the BGLI gene of Trichoderma virens making it capable of utilizing cellobiose to produce ethanol.

RESULTS

The cDNA and a genomic sequence of the BGLI gene of Trichoderma virens was cloned in the yeast expression vector pGAPZα and separately transformed to Saccharomyces cerevisiae. The size of the BGLI cDNA clone was 1363 bp and the genomic DNA clone contained an additional 76 bp single intron following the first exon. The gene was 90% similar to the DNA sequence and 99% similar to the deduced amino acid sequence of 1,4-β-D-glucosidase of T. atroviride (AC237343.1). The BGLI activity expressed by the recombinant genomic clone was 3.4 times greater (1.7 x 10-3 IU ml-1) than that observed for the cDNA clone (5 x 10-4 IU ml-1). Furthermore, the activity was similar to the activity of locally isolated Trichoderma virens (1.5 x 10-3 IU ml-1). The estimated size of the protein was 52 kDA. In fermentation studies, the maximum ethanol production by the genomic and the cDNA clones were 0.36 g and 0.06 g /g of cellobiose respectively. Molecular docking results indicated that the bare protein and cellobiose-protein complex behave in a similar manner with considerable stability in aqueous medium. The deduced binding site and the binding affinity of the constructed homology model appeared to be reasonable. Moreover, it was identified that the five hydrogen bonds formed between the amino acid residues of BGLI and cellobiose are mainly involved in the integrity of enzyme-substrate association.

CONCLUSIONS

The BGLI activity was remarkably higher in the genomic DNA clone compared to the cDNA clone. Cellobiose was successfully fermented into ethanol by the recombinant S.cerevisiae genomic DNA clone. It has the potential to be used in the industrial production of ethanol as it is capable of simultaneous saccharification and fermentation of cellobiose. Homology modeling, docking studies and molecular dynamics simulation studies will provide a realistic model for further studies in the modification of active site residues which could be followed by mutation studies to improve the catalytic action of BGLI.