Potential Inhibitors of Galactofuranosyltransferase 2 (GlfT2): Molecular Docking, 3D-QSAR, and In Silico ADMETox Studies

A strategy in the discovery of anti-tuberculosis (anti-TB) drug involves targeting the enzymes involved in the biosynthesis of Mycobacterium tuberculosis' (Mtb) cell wall. One of these enzymes is Galactofuranosyltransferase 2 (GlfT2) that catalyzes the elongation of the galactan chain of Mtb cell wall. Studies targeting GlfT2 have so far produced compounds showing minimal inhibitory activity. With the current challenge of designing potential GlfT2 inhibitors with high inhibition activity, computational methods such as molecular docking, receptor-ligand mapping, molecular dynamics, and Three-Dimensional-Quantitative Structure-Activity Relationship (3D-QSAR) were utilized to deduce the interactions of the reported compounds with the target enzyme and enabling the design of more potent GlfT2 inhibitors. Molecular docking studies showed that the synthesized compounds have binding energy values between -3.00 to -6.00 kcal mol-1. Two compounds, #27 and #31, have registered binding energy values of -8.32 ± 0.01, and -8.08 ± 0.01 kcal mol-1, respectively. These compounds were synthesized as UDP-Galactopyranose mutase (UGM) inhibitors and could possibly inhibit GlfT2. Interestingly, the analogs of the known disaccharide substrate, compounds #1-4, have binding energy range of -10.00 to -19.00 kcal mol-1. The synthesized and newly designed compounds were subjected to 3D-QSAR to further design compounds with effective interaction within the active site. Results showed improved binding energy from -6.00 to -8.00 kcal mol-1. A significant increase on the binding affinity was observed when modifying the aglycon part instead of the sugar moiety. Furthermore, these top hit compounds were subjected to in silico ADMETox evaluation. Compounds #31, #70, #71, #72, and #73 were found to pass the ADME evaluation and throughout the screening, only compound #31 passed the predicted toxicity evaluation. This work could pave the way in the design and synthesis of GlfT2 inhibitors through computer-aided drug design and can be used as an initial approach in identifying potential novel GlfT2 inhibitors with promising activity and low toxicity.

An aggregation-volume-bias Monte Carlo investigation on the condensation of a Lennard-Jones vapor below the triple point and crystal nucleation in cluster systems: an in-depth evaluation of the classical nucleation theory

The aggregation-volume-bias Monte Carlo based simulation technique, which has led to our recent success in vapor-liquid nucleation research, was extended to the study of crystal nucleation processes. In contrast to conventional bulk-phase techniques, this method deals with crystal nucleation events in cluster systems. This approach was applied to the crystal nucleation of Lennard-Jonesium under a wide range of undercooling conditions from 35% to 13% below the triple point. It was found that crystal nucleation in these model clusters proceeds initially via a vapor-liquid like aggregation followed by the formation of crystals inside the aggregates. The separation of these two stages of nucleation is distinct except at deeper undercooling conditions where the crystal nucleation barrier was found to diminish. The simulation results obtained for these two nucleation steps are separately compared to the classical nucleation theory (CNT). For the vapor-liquid nucleation step, the CNT was shown to provide a reasonable description of the critical cluster size but overestimate the barrier heights, consistent with previous simulation studies. On the contrary, for the crystal nucleation step, nearly perfect agreement with the barrier heights was found between the simulations and the CNT. For the critical cluster size, the comparison is more difficult as the simulation data were found to be sensitive to the definition of the solid cluster, but a stringent criterion and lower undercooling conditions generally lead to results closer with the CNT. Additional simulations at undercooling conditions of 40% or above indicate a nearly barrierless transition from the liquid to crystalline-like structure for sufficiently large clusters, which leads to further departure of the barrier height predicted by the CNT from the simulation data for the aggregation step. This is consistent with the latest experimental results on argon that show an unusually large underestimation of the nucleation rate by the CNT toward deep undercooling conditions.

Mapping allostery through computational glycine scanning and correlation analysis of residue-residue contacts

Understanding allosteric mechanisms is essential for the physical control of molecular switches and downstream cellular responses. However, it is difficult to decode essential allosteric motions in a high-throughput scheme. A general two-pronged approach to performing automatic data reduction of simulation trajectories is presented here. The first step involves coarse-graining and identifying the most dynamic residue-residue contacts. The second step is performing principal component analysis of these contacts and extracting the large-scale collective motions expressed via these residue-residue contacts. We demonstrated the method using a protein complex of nuclear receptors. Using atomistic modeling and simulation, we examined the protein complex and a set of 18 glycine point mutations of residues that constitute the binding pocket of the ligand effector. The important motions that are responsible for the allostery are reported. In contrast to conventional induced-fit and lock-and-key binding mechanisms, a novel "frustrated-fit" binding mechanism of RXR for allosteric control was revealed.

Probing the Nucleation Mechanism for the Binary n-Nonane/1-Alcohol Series with Atomistic Simulations

The AVUS-HR approach, which combines histogram reweighting with aggregation-volume-bias Monte Carlo nucleation simulations using self-adaptive umbrella sampling, was extended to multicomponent nucleation systems. It was applied to investigate the homogeneous vapor-liquid nucleation for the binary n-nonane/1-alcohol series, including the n-nonane/methanol, n-nonane/ethanol, n-nonane/1-propanol, n-nonane/1-butanol, n-nonane/1-hexanol, and n-nonane/1-decanol systems. The simple transferable potentials for phase equilibria-united atom force field was used in this investigation. It was found that the nucleation free energy (NFE) contour plots obtained for these binary n-nonane/1-alcohol nucleation systems exhibit rather interesting mechanistic features, some of which are distinct from other binary systems previously studied (such as water/ethanol and water/n-nonane). In addition, the NFE profiles show a subtle evolution with the increase in alcohol chain length, from a somewhat two-pathway type of shape as observed for the n-nonane/methanol system to a more normal single-pathway one for systems involving longer alcohols (1-hexanol and 1-decanol). In contrast, the NFE maps obtained for the other three binary systems involving those medium-length alcohols display the most striking feature with the saddle point stretched almost all the way from the n-nonane-enriched to the alcohol-enriched domain, implying that multiple pathways coexist on the nucleation map. These free energy profiles were shown to be consistent with the non-ideal nucleation behavior observed experimentally for this binary series, namely, a rather reluctant conucleation of the alcohols with n-nonane. In particular, this non-ideal behavior becomes more severe with a decrease in the alcohol chain length. Also, analysis of the compositions of the critical nuclei indicates a reluctant mixing behavior between these two species, i.e., depletion of the alcohol at low alcohol activity or depletion of n-nonane at low n-nonane activity, in agreement with the experimental interpretations. Furthermore, a microscopic inhomogeneity is present inside these critical nuclei, that is, alcohols aggregate via hydrogen bonds forming alcohol-enriched domains.

Machine Learning for Predicting Electron Transfer Coupling

Electron transfer coupling is a critical factor in determining electron transfer rates. This coupling strength can be sensitive to details in molecular geometries, especially intermolecular configurations. Thus, studying charge transporting behavior with a full first-principle approach demands a large amount of computation resources in quantum chemistry (QC) calculation. To address this issue, we developed a machine learning (ML) approach to evaluate electronic coupling. A prototypical ML model for an ethylene system was built by kernel ridge regression with Coulomb matrix representation. Since the performance of the ML models highly dependent on their building strategies, we systematically investigated the generality of the ML models, the choice of features and target labels. The best ML model trained with 40 000 samples achieved a mean absolute error of 3.5 meV and greater than 98% accuracy in predicting phases. The distance and orientation dependence of electronic coupling was successfully captured. Bypassing QC calculation, the ML model saved 10-10⁴ times the computation cost. With the help of ML, reliable charge transport models and mechanisms can be further developed.

Water mediated attraction between repulsive ions: A cluster-based simulation approach

Could two like ions be attractive to each other in the presence of water? To address this question and to further interrogate the intriguing solvent effects at a molecular level on multiply charged species, a "bottom-up" simulation approach was formulated, from which the inter-ionic potential of mean force and other properties were monitored closely with the gradual addition of the water molecules. This approach was first tested on a commonly studied ion pair (namely, Na+ and Cl-), where excellent agreement with the published bulk-phase data was found. Further application of this approach to the like-ion pair indicated that an attractive interaction between two anions or two cations can be induced by the addition of an appropriate number of water molecules. This result corroborates a recent experimental report of an intriguing folding of a dianionic polymer into a more compact structure with the addition of water molecules in gas phase as well as previous theoretical findings of possible attraction between like-ion pairs in bulk aqueous phases.

Dumbbells and onions in ternary nucleation

Molecular simulations for a ternary nucleation system (water/n-nonane/1-butanol) demonstrate a more complex nucleation mechanism than previously thought, where critical nuclei with different compositions are present even for a given vapour-phase composition; the spatial distribution in these critical nuclei is heterogeneous and dumbbell and onion motifs are found; in the former, water and nonane nano-droplets are connected through a butanol handle, while in the latter a water core is surrounded by a nonane corona with an interfacial butanol shell.

Stability and sugar recognition ability of ricin-like carbohydrate binding domains

Lectins are a class of proteins known for their novel binding to saccharides. Understanding this sugar recognition process can be crucial in creating structure-based designs of proteins with various biological roles. We focus on the sugar binding of a particular lectin, ricin, which has two β-trefoil carbohydrate-binding domains (CRDs) found in several plant protein toxins. The binding ability of possible sites of ricin-like CRD has been puzzling. The apo and various (multiple) ligand-bound forms of the sugar-binding domains of ricin were studied by molecular dynamics simulations. By evaluating structural stability, hydrogen bond dynamics, flexibility, and binding energy, we obtained a detailed picture of the sugar recognition of the ricin-like CRD. Unlike what was previously believed, we found that the binding abilities of the two known sites are not independent of each other. The binding ability of one site is positively affected by the other site. While the mean positions of different binding scenarios are not altered significantly, the flexibility of the binding pockets visibly decreases upon multiple ligand binding. This change in flexibility seems to be the origin of the binding cooperativity. All the hydrogen bonds that are strong in the monoligand state are also strong in the double-ligand complex, although the stability is much higher in the latter form due to cooperativity. These strong hydrogen bonds in a monoligand state are deemed to be the essential hydrogen bonds. Furthermore, by examining the structural correlation matrix, the two domains are structurally one entity. Galactose hydroxyl groups, OH4 and OH3, are the most critical parts in both site 1α and site 2γ recognition.

The Promiscuity of Allosteric Regulation of Nuclear Receptors by Retinoid X Receptor

The promiscuous protein retinoid X receptor (RXR) displays essential allosteric regulation of several members in the nuclear hormone receptor superfamily via heterodimerization and (anti)cooperative binding of cognate ligands. Here, the structural basis of the positive allostery of RXR and constitutive androstane receptor (CAR) is revealed. In contrast, a similar computational approach had previously revealed the mechanism for negative allostery in the complex of RXR and thyroid receptor (TR). By comparing the positive and negative allostery of RXR complexed with CAR and TR respectively, we reported the promiscuous allosteric control involving RXR. We characterize the allosteric mechanism by expressing the correlated dynamics of selected residue-residue contacts which was extracted from atomistic molecular dynamics simulation and statistical analysis. While the same set of residues in the binding pocket of RXR may initiate the residue-residue interaction network, RXR uses largely different sets of contacts (only about one-third identical) and allosteric modes to regulate TR and CAR. The promiscuity of RXR control may originate from multiple factors, including (1) the frustrated fit of cognate ligand 9c to the RXR binding pocket and (2) the different ligand-binding features of TR (loose) versus CAR (tight) to their corresponding cognate ligands.

Fractal aggregates in protein crystal nucleation

Monte Carlo simulations of homogeneous nucleation for a protein model with an exceedingly short-ranged attractive potential yielded a nonconventional crystal nucleation mechanism, which proceeds by the formation of fractal, low-dimensional aggregates followed by a concurrent collapse and increase of the crystallinity of these aggregates to become compact ordered nuclei. This result corroborates a recently proposed two-step mechanism for protein crystal nucleation from solution.

Effects of truncation of the peptide chain on the secondary structure and bioactivities of palmitoylated anoplin

Anoplin (GLLKRIKTLL-NH₂) is of current interest due to its short sequence and specificity towards bacteria. Recent studies on anoplin have shown that truncation and acylation compromises its antimicrobial activity and specificity, respectively. In this study, truncated analogues (pal-ano-9 to pal-ano-5) of palmitoylated anoplin (pal-anoplin) were synthesized to determine the effects of C-truncation on its bioactivities. Moreover, secondary structure of each analogue using circular dichroism (CD) spectroscopy was determined to correlate with bioactivities. Interestingly, pal-anoplin, pal-ano-9 and pal-ano-6 were helical in water, unlike anoplin. In contrast, pal-ano-8, pal-ano-7 and pal-ano-5, with polar amino acid residues at the C-terminus, were random coil in water. Nevertheless, all the peptides folded into helical structures in 30% trifluoroethanol/water (TFE/H₂O) except for the shortest analogue pal-ano-5. Hydrophobicity played a significant role in the enhancement of activity against bacteria E. coli and S. aureus as all lipopeptides including the random coil pal-ano-5 were more active than the parent anoplin. Meanwhile, the greatest improvement in activity against the fungus C. albicans was observed for pal-anoplin analogues (pal-ano-9 and pal-ano-6) that were helical in water. Although, hydrophobicity is a major factor in the secondary structure and antimicrobial activity, it appears that the nature of amino acids at the C-terminus also influence folding of lipopeptides in water and its antifungal activity. Moreover, the hemolytic activity of the analogues was found to correlate with hydrophobicity, except for the least hemolytic, pal-ano-5. Since most of the analogues are more potent and shorter than anoplin, they are promising drug candidates for further development.

Structural Dynamics of Neighboring Water Molecules of N-Isopropylacrylamide Pentamer

Poly(N-isopropylacrylamide) (PNIPAM) is a popular polymer widely used in smart hydrogel synthesis due to its thermo-responsive behavior in aqueous medium. Aqueous PNIPAM hydrogels can reversibly swell and collapse below and above their lower critical solution temperature (LCST), respectively. The present work used molecular dynamics simulations to explore the behavior of water molecules surrounding the side chains of a NIPAM pentamer in response to temperature changes (273-353 K range) near its experimental LCST (305 K). Results suggest a strong inverse correlation of temperature with water density and hydrophobic hydration character of the first coordination shell around the isopropyl groups. Integrity of the first and second coordination shells is further characterized by polygon ring analysis. Predominant occurrence of pentagons suggests clathrate-like behavior of both shells at lower temperatures. This predominance is eventually overtaken by 4-membered rings as temperature is increased beyond 303 and 293 K for the first and second coordination shells, respectively, losing their clathrate-like property. It is surmised that this temperature-dependent stability of the coordination shells is one of the important factors that controls the reversible swell-collapse mechanism of PNIPAM hydrogels.

Swimming motility plays a key role in the stochastic dynamics of cell clumping

Dynamic cell-to-cell interactions are a prerequisite to many biological processes, including development and biofilm formation. Flagellum induced motility has been shown to modulate the initial cell-cell or cell-surface interaction and to contribute to the emergence of macroscopic patterns. While the role of swimming motility in surface colonization has been analyzed in some detail, a quantitative physical analysis of transient interactions between motile cells is lacking. We examined the Brownian dynamics of swimming cells in a crowded environment using a model of motorized adhesive tandem particles. Focusing on the motility and geometry of an exemplary motile bacterium Azospirillum brasilense, which is capable of transient cell-cell association (clumping), we constructed a physical model with proper parameters for the computer simulation of the clumping dynamics. By modulating mechanical interaction ('stickiness') between cells and swimming speed, we investigated how equilibrium and active features affect the clumping dynamics. We found that the modulation of active motion is required for the initial aggregation of cells to occur at a realistic time scale. Slowing down the rotation of flagellar motors (and thus swimming speeds) is correlated to the degree of clumping, which is consistent with the experimental results obtained for A. brasilense.

Molecular Affinity of Mabolo Extracts to an Octopamine Receptor of a Fruit Fly

Essential oils extracted from plants are composed of volatile organic compounds that can affect insect behavior. Identifying the active components of the essential oils to their biochemical target is necessary to design novel biopesticides. In this study, essential oils extracted from Diospyros discolor (Willd.) were analyzed using gas chromatography mass spectroscopy (GC-MS) to create an untargeted metabolite profile. Subsequently, a conformational ensemble of the Drosophila melanogaster octopamine receptor in mushroom bodies (OAMB) was created from a molecular dynamics simulation to resemble a flexible receptor for docking studies. GC-MS analysis revealed the presence of several metabolites, i.e. mostly aromatic esters. Interestingly, these aromatic esters were found to exhibit relatively higher binding affinities to OAMB than the receptor's natural agonist, octopamine. The molecular origin of this observed enhanced affinity is the π -stacking interaction between the aromatic moieties of the residues and ligands. This strategy, computational inspection in tandem with untargeted metabolomics, may provide insights in screening the essential oils as potential OAMB inhibitors.

The effect of ligand affinity to the contact dynamics of the ligand binding domain of thyroid hormone receptor - retinoid X receptor

Ligand-based allostery has been gaining attention for its importance in protein regulation and implication in drug design. One of the interesting cases of protein allostery is the thyroid hormone receptor - retinoid x receptor (TR:RXR), which regulates the gene expression of important physiological processes, such as development and metabolism. It is regulated by the TR native ligand triiodothyronine (T3), which displays anticooperative behavior to the RXR ligand 9-cis retinoic acid (9C). In contrast to this anticooperative behavior, 9C has been shown to increase the activity of TR:RXR. Here we probed the influence of the affinity and the interactions of the TR ligand to the allostery of the TR:RXR through contact dynamics and residue networks. The TR ligand analogs were designed to have higher (G2) and lower (N1) binding energies than T3 when docked to the TR:RXR(9C) complex. The aqueous TR(N1/T3/G2):RXR(9C) complexes were subjected to 30 ns all-atom simulations using theNAMD. The program CAMERRA was used to capture the subtle perturbations of TR:RXR by mapping the residue contact dynamics. Various parts of the TR ligands; including the hydrophilic head, the iodine substituents, and the ligand tail; have been probed for their significance in ligand affinity. The results on the T3 and G2 complexes suggest that ligand affinity can be utilized as a predictor for anticooperative systems on which ligand is more likely to dissociate or remain bound. All 3 complexes also display distinct contact networks for cross-dimer signalling and ligand communication. Understanding ligand-based allostery could potentially unveil secrets of ligand-regulated protein dynamics, a foundation for the design of better and more efficient allosteric drugs.

In Silico insights on enhancing thermostability and activity of a plant Fructosyltransferase from Pachysandra terminalis via introduction of disulfide bridges

Drawbacks of industrially-used fructosyltransferases (FTs) such as low optimum temperature and low fructooligosaccharides (FOS) yield necessitates the search for engineered FTs that are highly thermostable and active. With the availability of the first plant FT crystal structure from Pachysandra terminalis (PDB ID: 3UGH), computer-aided protein engineering of plant FT is now feasible. To obtain insights on the effect of specific mutations i.e. disulfide bridge introduction, wild-type and mutant FTs were subjected to a 15 μs Martini Coarse-grained Molecular Dynamics (CGMD) simulations at 303 K and 334 K. We report here the five mutants, M31C-Q49C, L144C-S193C, P34C-W300C, S219C-L226C and V470C-S498C with enhanced thermostabilities and/or activities relative to the wild type. Interestingly, M31C-Q49C, which is located within the catalytic-carrying blade of the catalytic domain, has an activity enhancement at both temperatures. At 334 K, three mutations, L144C-S193C, P34C-W300C and V470C-S498C, achieved thermostability relative to the wild type. Intriguingly, both activity and stability enhancement exhibited only at 334 K can be achieved provided that the mutation is located either on the catalytic-carrying residue blade of the catalytic domain or on the non-catalytic domain. Our results suggest that V470C-S498C and L144C-S193C are promising mutants and that domain-specific approach may be exploited to customize enzyme properties.

pH-Dependent Conformations of an Antimicrobial Spider Venom Peptide, Cupiennin 1a, from Unbiased HREMD Simulations

Cupiennin 1a is an antimicrobial peptide found in the venom of the spider Cupiennius salei. A highly cationic peptide, its cell lysis activity has been found to vary between neutral and charged membranes. In this study, Hamiltonian replica-exchange molecular dynamics (HREMD) was used to determine the conformational ensemble of the peptide in both charged (pH 3) and neutral (pH 11) states. The obtained free energy landscapes demonstrated the conformational diversity of the neutral peptide. At high pH, the peptide was found to adopt helix-hinge-helix and disordered structures. At pH 3, the peptide is structured with a high propensity toward α-helices. The presence of these α-helices seems to assist the peptide in recognizing membrane surfaces. These results highlight the importance of the charged residues in the stabilization of the peptide structure and the subsequent effects of pH on the peptide's conformational diversity and membrane activity. These findings may provide insights into the antimicrobial activity of Cupiennin 1a and other amphipathic linear peptides toward different cell membranes.