Ps Molecular Dynamics Simulations Research Articles

Molecular bioprospection of Helianthus annuus L. (sunflower) cypselae for antidiabetic therapeutics through network pharmacology, density functional theory and molecular dynamics simulation

Helianthus annuus cypsela (sunflower) is a staple oilseed crop with significant therapeutic applications against diverse diseases including type 2 diabetes mellitus (T2DM). Despite its reported antidiabetic potential, the implicated molecular mechanism of action is yet to be unravelled to date. This study evaluated the molecular mechanism of the antidiabetic activity of sunflower cypsela using network pharmacology (NP), density functional theory, and molecular dynamics (MD) simulation approaches. The six cultivars of sunflower cypsela used were profiled for their secondary metabolites using LC-MS and GC–MS techniques. Subsequently, the genes associated with the identified metabolites were screened against T2DM-associated genes using NP. Based on the KEGG enrichment analysis of the identified common genes, signaling pathways were subsequently identified. The results obtained revealed 87 intersecting genes between the metabolites of sunflower cypsela and T2DM, while the KEGG analysis identified 35 signaling pathways with the PPAR route and its associated genes as the most implicated in T2DM progression with respect to sunflower cypsela. Both MMP1 and PPARA in the PPAR pathways interacted most with the identified metabolites, with CGA (−43.74 kcal/mol), GPA (−41.62 kcal/mol), and CFG (−45.36 kcal/mol) having higher binding free energy than both ROS and MET (reference standards) against MMP1 after 100,000 ps MD simulation. In contrast, ROS (−46.98 kcal/mol) had better affinity against PPARA compared to the top hits of sunflower cypsela. However, against both gene targets, the top hits had significant thermodynamic stability, flexibility, and compactness, which are attributable to their bond interactions and molecular orbital properties. These findings are suggestive of the essential role of the top-hits in the antidiabetic potential of sunflower cypsela through activation of the PPAR signalling pathway and most especially MMP1. In this regard, the modulation of MMP1 and PPARA genes by the identified metabolites of sunflower cypsela may enhance insulin sensitivity and glucose homoeostasis in the management of T2DM.

The discovery of some promising putative binders of KRAS G12D receptor using computer-aided drug discovery approach

A prospective target for the therapy of solid tumors is KRAS G12D, the most prevalent oncogenic KRAS mutation. However, despite decades of research that focused on the identification of druggable compounds against this highly challenging therapeutic cancer target, no drug has been clinically approved for the treatment of KRAS G12D-driven cancers. Herein, we employed computational techniques such as molecular docking and molecular dynamics simulations to investigate small-molecule compounds with the potential to bind putatively with KRAS G12D. The docking screening portrayed three compounds (Quercetin, Psoralidin, and Resveratrol) as promising drug candidates for the receptor target due to their higher binding affinities when compared with a known noncovalent, potent, and selective KRAS G12D inhibitor (MRTX1133). The stability analysis after 100000 ps molecular dynamics simulation suggests Quercetin as a more stable compound when compared with the other simulated chemical entities, including the referenced inhibitor (MRTX1133). In spite of our research findings, it will be too early to conclude the drug candidates can be advanced to the clinic for use with KRAS G12D cancer patients without extensive preclinical and clinical studies.

2D boron-nitride featuring B4 tetrahedros: An efficient photocatalyst for water splitting

Two-dimensional hexagonal boron nitride (h-BN) is an insulator with polar covalent B−N bonds. Based on current research on boron-nitrogen 2D materials and the cluster assembling method, here, we designed five novel monolayers with square lattice formed by tetrahedral B4 units covalently linked to V-group atoms, namely the B4N2, B4P2, B4As2, B4Sb2, and B4Bi2 monolayers, via first-principles calculations. Both the B4N2 and B4P2 have good stability, as demonstrated by high cohesive energies, all positive phonon modes, high in-plane Young's modulus and structural integrity through 5 ps's molecular dynamics simulations at both 300 and 500 K. Moreover, the B4P2 monolayer exhibits metallic properties, whereas the B4N2 monolayer is an indirect bandgap semiconductor with the bandgap of 2.56 eV and appropriate band edge positions, the optical adsorption in UV light region, and high electron mobility for photocatalytic water splitting. Our theoretical study adds new members of 2D boron nitrides (B4N2), which can be used as an efficient photocatalyst for water splitting.

Smart electrochemical sensing of xylitol using a combined machine learning and simulation approach

A novel sensor was proposed for the detection of xylitol in sugar free chewing gum using Au nanoparticles (NPs) derived from Callistemon viminalis leaf extract coupled with multiwalled carbon nanotubes (MWCNTs) doped onto glassy carbon electrode (GCE). In comparison to the bare GCE, the modified GCE/MWCNT/AuNPs sensor showed about 45-fold better electrochemical response to xylitol. Under the optimal conditions, the designed sensor achieved a detection limit of 9.8 × 10−6 pM for concentrations ranging from 9.9 × 10−6 to 2.9 × 10−5 pM. The practicability was tested on sugar-free sample yielding recoveries of 97–100% with RSDs of 2.83–3.33%. Machine learning (ML) was used to predict changes in voltammetric signal with changing potential over time demonstrating the fundamental knowledge of the electrochemical reaction. The performance of the Artificial Neural Network (ANN) provides good accuracy and precision in predicting the intensity (I) along with repeated ANN runs, with a mean square error (MSE) of 0.007 (± 0.002) and a determination coefficient (R2) of 0.9992 ± 0.0006. Additionally, the interaction of xylitol on the electrode surfaces were investigated using Monte Carlo adsorption studies and 1000 ps Molecular Dynamics simulations under NVT conditions. According to the frontier molecular orbitals obtained through Density Functional Theory calculations, the reactive sites of xylitol occur at the hydroxyl group on the second carbon. Using complementary measurement techniques, this new strategy exhibits a great potential for rapid detection of xylitol in food and dental products.

In silico study of six FDA approved anti-HCV drugs as inhibitors for NS5 methyltransferase of dengue virus type 2

Background & objectives: Dengue virus infection has become a major health threat. Dengue is a mosquito-borne viral infection caused by a viral RNA of the family Flaviviridae and spread by Aedes mosquitoes. Dengue NS5 methyltransferase is used as a drug target for the disease. Six FDA approved anti-HCV drugs were tested as potential dengue virus type 2 methyltransferase inhibitors using molecular docking analysis seeking potential treatment. Methods: Molecular docking analysis tested six FDA approved anti-HCV drugs, including Elbasvir, Daclatasvir, Ledipasvir, Pibrentasvir, Velpatasvir, and Ombitasvir. Results: 1000 ps molecular dynamics simulation of protein-complex validates its stability. Interpretation & conclusion: The analysis indicates the binding of Ombitasvir with the protein drug target with optimal binding features for further in vitro and in vivo evaluations. Ombitasvir was the optimum candidate ligand compound with binding affinity value (-11.56 ΁ 0.46 kcal/mol) with 2P3Q. Interactions of Ombitasvir with the active site residues of 2P3Q revealed good results for experimental drug testing.

How quickly can we predict trimethoprim resistance using alchemical free energy methods?

The emergence of antimicrobial resistance threatens modern medicine and necessitates more personalized treatment of bacterial infections. Sequencing the whole genome of the pathogen(s) in a clinical sample offers one way to improve clinical microbiology diagnostic services, and has already been adopted for tuberculosis in some countries. A key weakness of a genetics clinical microbiology is it cannot return a result for rare or novel genetic variants and therefore predictive methods are required. Non-synonymous mutations in the S. aureus dfrB gene can be successfully classified as either conferring resistance (or not) by calculating their effect on the binding free energy of the antibiotic, trimethoprim. The underlying approach, alchemical free energy methods, requires large numbers of molecular dynamics simulations to be run. We show that a large number (N = 15) of binding free energies calculated from a series of very short (50 ps) molecular dynamics simulations are able to satisfactorily classify all seven mutations in our clinically derived testset. A result for a single mutation could therefore be returned in less than an hour, thereby demonstrating that this or similar methods are now sufficiently fast and reproducible for clinical use.

Design of antimalarial agents based on pyrimidine derivatives as methionine aminopeptidase 1b inhibitor: Molecular docking, quantitative structure activity relationships, and molecular dynamics simulation studies

AbstractMalaria is a parasitic disease mainly caused by Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae, and Plasmodium ovale and rarely by animal plasmodium such as Plasmodium knowlesi. Despite the worldwide endorsement of eradicating malaria, the mortality and morbidity of malaria is still high, especially in children of resource‐poor regions of the world. In the current study, a series of 2‐pyridyl pyrimidine derivatives with P. falciparum methionine aminopeptidase 1b (MA1b) inhibitory activity were subjected to quantitative structure, relationship activities, molecular docking, and molecular dynamics simulation to identify the ideal physicochemical characteristics and the drug–receptor interactions of potential antimalarial compounds. The structures were built using HyperChem. A docking study was performed using AutoDock. The obtained quantitative structure activity relationships model has showed that the descriptors MLOGP, E2p, Mor24u, PW2, and H8m mainly affect the antimalarial activity of the series of ligands. The residues His 277, Fe 370, Asp 240, Trp 320, and Tyr 260 of MA1b play a very important role in the drug–enzyme interaction by creating hydrogen bond, π‐cation, and π‐π interactions. To give a complete impression about the pyrimidine derivatives, compound 7 was subjected to 1,000 ps molecular dynamics (MD) simulations. The best structure based on our study was suggested for a future new drug with potential antimalarial compounds.

Molecular Insight into Human Lysozyme and Its Ability to Form Amyloid Fibrils in High Concentrations of Sodium Dodecyl Sulfate: A View from Molecular Dynamics Simulations.

Changes in the tertiary structure of proteins and the resultant fibrillary aggregation could result in fatal heredity diseases, such as lysozyme systemic amyloidosis. Human lysozyme is a globular protein with antimicrobial properties with tendencies to fibrillate and hence is known as a fibril-forming protein. Therefore, its behavior under different ambient conditions is of great importance. In this study, we conducted two 500000 ps molecular dynamics (MD) simulations of human lysozyme in sodium dodecyl sulfate (SDS) at two ambient temperatures. To achieve comparative results, we also performed two 500000 ps human lysozyme MD simulations in pure water as controls. The aim of this study was to provide further molecular insight into all interactions in the lysozyme-SDS complexes and to provide a perspective on the ability of human lysozyme to form amyloid fibrils in the presence of SDS surfactant molecules. SDS, which is an anionic detergent, contains a hydrophobic tail with 12 carbon atoms and a negatively charged head group. The SDS surfactant is known to be a stabilizer for helical structures above the critical micelle concentration (CMC) [1]. During the 500000 ps MD simulations, the helical structures were maintained by the SDS surfactant above its CMC at 300 K, while at 370 K, human lysozyme lost most of its helices and gained β-sheets. Therefore, we suggest that future studies investigate the β-amyloid formation of human lysozyme at SDS concentrations above the CMC and at high temperatures.

Perturbation Approaches for Exploring Protein Binding Site Flexibility to Predict Transient Binding Pockets.

Simulations of the long-time scale motions of a ligand binding pocket in a protein may open up new perspectives for the design of compounds with steric or chemical properties differing from those of known binders. However, slow motions of proteins are difficult to access using standard molecular dynamics (MD) simulations and are thus usually neglected in computational drug design. Here, we introduce two nonequilibrium MD approaches to identify conformational changes of a binding site and detect transient pockets associated with these motions. The methods proposed are based on the rotamerically induced perturbation (RIP) MD approach, which employs perturbation of side-chain torsional motion for initiating large-scale protein movement. The first approach, Langevin-RIP (L-RIP), entails a series of short Langevin MD simulations, each starting with perturbation of one of the side-chains lining the binding site of interest. L-RIP provides extensive sampling of conformational changes of the binding site. In less than 1 ns of MD simulation with L-RIP, we observed distortions of the α-helix in the ATP binding site of HSP90 and flipping of the DFG loop in Src kinase. In the second approach, RIPlig, a perturbation is applied to a pseudoligand placed in different parts of a binding pocket, which enables flexible regions of the binding site to be identified in a small number of 10 ps MD simulations. The methods were evaluated for four test proteins displaying different types and degrees of binding site flexibility. Both methods reveal all transient pocket regions in less than a total of 10 ns of simulations, even though many of these regions remained closed in 100 ns conventional MD. The proposed methods provide computationally efficient tools to explore binding site flexibility and can aid in the functional characterization of protein pockets, and the identification of transient pockets for ligand design.

Ab Initio Modeling of Li/Li6PS5Cl Interface Formation in Lithium Solid State Batteries

Several sulfide glasses, glass-ceramics or ceramics have been developed as promising electrolytes, mainly based on binary and ternary systems, including Li2S and P2S5 with ternary components such as P2S3, GeS2 and P2O5. Currently, Li10GeP2S12 exhibits one of the highest lithium ionic conductivities, 12 mS/cm at room temperature1 which is even higher then that of liquid electrolytes. However, this material is costly, because Ge is expensive. Recently, a relatively new family of sulfide ceramics, so-called Li-argyrodites, Li6PS5X (X = Cl, Br, I), has been studied and high ionic conductivity (7 mS/cm at 298 K) has been observed.2 These materials can provide a balance of efficiency and price and can be used as solid electrolyte in electrochemical devices, for example, in Li-batteries. However, in this case, one of the questions is how stable Li6PS5X in contact with Li-electrode. To study this problem, we have built the Li6PS5Cl structure and performed ReaxFF reactive force field and ab initio molecular dynamics simulations of this structure, as well as a Li/Li6PS5Cl interface. Figure 1 shows our optimized Li/Li6PS5Cl interface model with eight layers of Li [the BCC 3x3 (100) surface] and six layers of Li6PS5Cl [the (100) surface]. During optimization, PS4 at the interface quickly decomposed, breaking P-S bonds and producing new P-Li bonds and Li-S bonds. The radial distribution function (RDF) also confirms these bonding changes: the P-S peak decreases, while new peaks of P-Li appear in a short range (2-3 Å). Integrating RDF shows that the coordination number of S to P decreases, and in the same time the number of Li coordinated to P increases. Since the decomposition occurs during the optimization, we conclude that these decomposition reactions might be barrierless. This indicates that Li6PS5Cl is unstable in contact with Li metal. The quick decomposition of the Li6PS5Cl electrolyte may attribute to the weak bonding between P and S and, therefore, the chemical instability may be a general problem for P-S based solid electrolytes. The Li-ion diffusion is significantly slower in the interface compared to that in the Li6PS5Cl bulk structure. One of the possible solutions of this problem might be partial oxidation of the interface, using strong P-O bonds to replace weak P-S bonds. This may decrease the ionic conductivity of the interface. Therefore, the oxidized layer should be thin enough in order not to decrease the overall conductivity of the system to the unacceptable value. We built a corresponding model and after the energy minimization of the modified interface, no decomposition was observed. To further investigate stability of the Li/Li6PS5Cl interface, a molecular dynamics (MD) simulation was carried out at 298 K. We find that after the 100 ps MD simulation, the partially oxidized interface still remains very stable. However, to make a firm conclusion about stability of the interface studied, a longer MD simulation is required. Such a simulation is in process. Authors gratefully acknowledge support from Bosch Energy Research Network Grant No. 13.01.CC11. References J. Hassoun, R. Verrelli, P. Reale, S. Panero, G. Mariotto, S. Greenbaum, B. Scrosati, J. Power Sources 229, 117-122, 2013.H.-J. Deiseroth, S.-T. Kong, H. Eckert, J. Vannahme, C. Reiner, T. Zaiβ, M. Schlosser, Angew. Chem. Int. Ed. 47, 755-758, 2008. Figure 1

Large-Scale Quantum-Mechanical Molecular Dynamics Simulations Using Density-Functional Tight-Binding Combined with the Fragment Molecular Orbital Method.

The fully analytic gradient is developed for density-functional tight-binding (DFTB) combined with the fragment molecular orbital (FMO) method (FMO-DFTB). The response terms arising from the coupling of the electronic state to the embedding potential are derived, and the gradient accuracy is demonstrated on water clusters and a polypeptide. The radial distribution functions (RDFs) obtained with FMO-DFTB are found to be similar to those from conventional DFTB, while the computational cost is greatly reduced; for 256 water molecules one molecular dynamics (MD) step takes 73.26 and 0.68 s with full DFTB and FMO-DFTB, respectively, showing a speed-up factor of 108. FMO-DFTB/MD is applied to 100 ps MD simulations of liquid hydrogen halides and is found to reproduce experimental RDFs reasonably well.

Molecular Modeling Investigation of Folic Acid Conjugation to MDM2 Inhibitors for Enhanced Cellular Uptake and Target Binding.

The activation of tumor suppressor p53 protein through inhibition of its interaction with the oncogenic Murine Double Minute 2 (MDM2) protein presents a novel therapeutic strategy against cancer. Accordingly, several small-molecule inhibitors have been developed that mimic three hydrophobic groups of p53 involved in p53-MDM2 binding and thus block the p53-binding pocket on MDM2. Interestingly, presence of a fourth, solvent-exposed hydrophilic moiety in these MDM2 inhibitors is shown to enhance their binding to MDM2 by protecting the inhibitor-MDM2 binding interface from surrounding solvent. In this context, we hypothesized that vitamin folic acid (FA) may prove to be suitable as the hydrophilic cover for enhancing activity of present MDM2 inhibitors. The proposed conjugation of FA to MDM2 inhibitors may also lead to their enhanced and selective uptake by cancer cells, owing to significantly higher expression of the FA receptors on cancer cells compared to normal cells. Therefore, based on our novel hypothesis we designed FA-conjugated MDM2 inhibitors and investigated their binding with MDM2 protein as well as the FA receptor. Specifically, a molecular modeling approach combining flexible receptor docking and molecular mechanics energy minimization calculations revealed highly favorable interactions of FA-conjugated MDM2 inhibitors with both MDM2 protein and the FA receptor as compared to native crystal ligands. Furthermore, these binding interactions were found to be stable using 50,000 ps molecular dynamics simulations. In summary, the newly-designed molecules of this kind, with better MDM2 target binding and enhanced cellular uptake potential, may prove highly useful against cancer and thus warrant further experimental investigations.

Electronic excitation energies in dimers between radical ions presenting long, multicenter bonding.

The formation of long, multicenter dimers between radical ions is usually monitored through UV-vis spectroscopy given the characteristic low-energy absorption band that they exhibit, not observed for the parent monomers. In this work, the performance of CASPT2, RASPT2, and TD-DFT methods for obtaining excitation energies of the long, multicenter bonded π-[TCNE]2(2-) and π-[TTF]2(2+) dimers has been addressed (TCNE = tetracyanoethylene; TTF = tetrathiafulvalene). The impact of the active space on the vertical electronic transitions computed at the RASPT2 and CASPT2 levels has been tested against experimentally observed absorption bands. Analogous tests have been carried out for a wide variety of density functionals within the TD-DFT formalism. Our calculations show that whereas CASPT2 predicts very accurate excitation energies for the π-[TCNE]2(2-), the mean absolute error for π-[TTF]2(2+) is higher for CASPT2 than for TD-DFT calculations, whenever pure density functionals or low % HF exchange hybrid functionals are used. Hybrid functionals with high % HF exchange (and thus RSH functionals) conduct to large errors on the excitation energies in both dimers. Furthermore, vertical electronic transitions are also obtained for 100 configurations extracted from a 45 ps molecular dynamics (CPMD) simulation aimed at providing an accurate description of the thermal fluctuation effects of a π-[TCNE]2(2-) dimer in dichloromethane. These thermal effects explain the shape of the experimental UV-vis spectrum, where the lowest HOMO → LUMO absorption presents a broad band and the following HOMO-1 → LUMO absorption exhibits a narrower band.

Blood-brain barrier transport studies, aggregation, and molecular dynamics simulation of multiwalled carbon nanotube functionalized with fluorescein isothiocyanate.

In this study, the ability of a multiwalled carbon nanotube functionalized with fluorescein isothiocyanate (MWCNT–FITC) was assessed as a prospective central nervous system-targeting drug delivery system to permeate the blood–brain barrier. The results indicated that the MWCNT–FITC conjugate is able to penetrate microvascular cerebral endothelial monolayers; its concentrations in the Transwell® system were fully equilibrated after 48 hours. Cell viability test, together with phase-contrast and fluorescence microscopies, did not detect any signs of MWCNT–FITC toxicity on the cerebral endothelial cells. These microscopic techniques also revealed presumably the intracellular localization of fluorescent MWCNT–FITCs apart from their massive nonfluorescent accumulation on the cellular surface due to nanotube lipophilic properties. In addition, the 1,000 ps molecular dynamics simulation in vacuo discovered the phenomenon of carbon nanotube aggregation driven by van der Waals forces via MWCNT–FITC rapid dissociation as an intermediate phase.

Global connectivity of hub residues in Oncoprotein structures encodes genetic factors dictating personalized drug response to targeted Cancer therapy.

The efficacy and mechanisms of therapeutic action are largely described by atomic bonds and interactions local to drug binding sites. Here we introduce global connectivity analysis as a high-throughput computational assay of therapeutic action – inspired by the Google page rank algorithm that unearths most “globally connected” websites from the information-dense world wide web (WWW). We execute short timescale (30 ps) molecular dynamics simulations with high sampling frequency (0.01 ps), to identify amino acid residue hubs whose global connectivity dynamics are characteristic of the ligand or mutation associated with the target protein. We find that unexpected allosteric hubs – up to 20Å from the ATP binding site, but within 5Å of the phosphorylation site – encode the Gibbs free energy of inhibition (ΔGinhibition) for select protein kinase-targeted cancer therapeutics. We further find that clinically relevant somatic cancer mutations implicated in both drug resistance and personalized drug sensitivity can be predicted in a high-throughput fashion. Our results establish global connectivity analysis as a potent assay of protein functional modulation. This sets the stage for unearthing disease-causal exome mutations and motivates forecast of clinical drug response on a patient-by-patient basis. We suggest incorporation of structure-guided genetic inference assays into pharmaceutical and healthcare Oncology workflows.

Computationally efficient and accurate enantioselectivity modeling by clusters of molecular dynamics simulations.

Computational approaches could decrease the need for the laborious high-throughput experimental screening that is often required to improve enzymes by mutagenesis. Here, we report that using multiple short molecular dynamics (MD) simulations makes it possible to accurately model enantioselectivity for large numbers of enzyme-substrate combinations at low computational costs. We chose four different haloalkane dehalogenases as model systems because of the availability of a large set of experimental data on the enantioselective conversion of 45 different substrates. To model the enantioselectivity, we quantified the frequency of occurrence of catalytically productive conformations (near attack conformations) for pairs of enantiomers during MD simulations. We found that the angle of nucleophilic attack that leads to carbon-halogen bond cleavage was a critical variable that limited the occurrence of productive conformations; enantiomers for which this angle reached values close to 180° were preferentially converted. A cluster of 20-40 very short (10 ps) MD simulations allowed adequate conformational sampling and resulted in much better agreement to experimental enantioselectivities than single long MD simulations (22 ns), while the computational costs were 50-100 fold lower. With single long MD simulations, the dynamics of enzyme-substrate complexes remained confined to a conformational subspace that rarely changed significantly, whereas with multiple short MD simulations a larger diversity of conformations of enzyme-substrate complexes was observed.

ReaxFF molecular dynamics simulations of non-catalytic pyrolysis of triglyceride at high temperatures

In order to investigate the initiation mechanisms associated with the pyrolysis of triglyceride that could potentially be used as petrochemical replacements, we carried out 500 ps molecular dynamics simulations employing the ReaxFF reactive force field using tripalmitin as the model molecule at 1500 and 2000 K. We find that the primary decomposition reactions of tripalmitin initiate with the successive scission of the alkyl-oxygen bond to form three straight chain C16H31O2˙ (RCOO˙) radicals and C3H5˙ radical. The deoxygenated alkyl chain is produced through the decarboxylation of the RCOO˙ radical with concurrent production of CO2. The resulting alkyl and C3H5˙ radicals further undergo recombination and decomposition to yield mainly alkanes and alkenes, with the actual product distribution being dependent on reaction temperature. β-Scission plays an important role in alkyl chain decomposition with a concomitant release of C2H4. Compared to 1500 K, this reaction is accelerated at 2000 K. In addition, the formation of cyclic hydrocarbon is also observed at 2000 K. As opposed to previous proposed Diels–Alder reactions or intramolecular cyclizations of alkenyl radicals mechanisms, it is found that cyclopentane could be produced by intramolecular cyclization of a biradical.

Molecular docking, molecular dynamics simulation, and QSAR model on potent thiazolidine-4-carboxylic acid inhibitors of influenza neuraminidase

In the current work, the relationship between the structure and activity of a series of novel thiazolidine-4-carboxylic acid derivatives as potent influenza virus neuraminidase inhibitors was studied using docking, molecular dynamics (MD) simulations, and QSAR analysis. A 7,000 ps MD simulation in a cubic water box were employed to build 3D structure of the 2HU4 in a water environment. After reaching the equilibrium, the inhibitors were docked into the 2HU4 to realize the binding site of the enzyme. The docking analysis showed that the interaction of the inhibitors with residues Arg371, Arg430, Gly429, Ile427, Lys432, Pro431, Trp403, and Tyr347 plays an important role in the activities of the inhibitors. The docked configurations of the inhibitors with the lowest free energy were used to calculate the most feasible descriptors. The selected descriptors were related to the inhibitory activities using stepwise multiple linear regression, classification and regression trees, and least squares support vector regression techniques. The satisfactory results (R p 2 = 0.883, Q LOO 2 = 0.872, R L25%O 2 = 0.835, RMSELOO = 0.310, and RMSEL25%O = 0.352) demonstrate that CART-LS-SVR models present the relationship between influenza virus neuraminidase inhibitors activity and molecular descriptors clearly. An energetic analysis based on MD calculations, revealed that the potency of the most active compound binding is governed by electrostatic and van der Waals contacts. The results provide a set of useful guidelines for the rational design of novel influenza virus neuraminidase inhibitors.

Docking, molecular dynamics simulation studies, and structure-based QSAR model on cytochrome P450 2A6 inhibitors

In this study, we used molecular docking and molecular dynamics (MD) simulation studies to analyze the interactions of a series of naphthalene and non-naphthalene derivatives (n = 38) as potent inhibitors of cytochrome P450 2A6 (CYP2A6) and to construct a structure-based quantitative structure activity relationship (QSAR) model. A 6000 ps MD simulation in a cubic water box were employed to build 3D structure of the CYP2A6 in a water environment. After reaching the equilibrium, the most potent inhibitor (2-bromonaphthalene) was docked into the CYP2A6 to realize the binding site of the enzyme. The docking analysis showed that π–π interaction of the inhibitors with four phenylalanine residues at positions of 107, 111, 118, and 480 plays an important role in the activities of the inhibitors. Then, an additional 6000 ps MD simulation was performed on the complex of the CYP2A6–2-bromonaphthalene to explore the effect of the inhibitor on the stability of the protein–inhibitor complex. Radius of gyration values for CYP2A6 and CYP2A6–2-bromonaphthalene complex were 2.23 ± 0.01 and 2.21 ± 0.01 nm, respectively, which revealed that the structure of the CYP2A6 in the presence of 2-bromonaphthalene has not changed. Finally, all the inhibitors docked into the enzyme and the docked configuration of the inhibitors with the lowest free energy was used to calculate the most feasible descriptors. The selected descriptors were related to the inhibitory activities using multiple linear regression (MLR) and least squares support vector regression (LS-SVR) models. The Q2 values for MLR and LS-SVR were 0.695 and 0.728, respectively.

Inhibitor and Substrate Binding by Angiotensin-Converting Enzyme: Quantum Mechanical/Molecular Mechanical Molecular Dynamics Studies

Angiotensin-converting enzyme (ACE) is an important zinc-dependent hydrolase responsible for converting the inactive angiotensin I to the vasoconstrictor angiotensin II and for inactivating the vasodilator bradykinin. However, the substrate binding mode of ACE has not been completely understood. In this work, we propose a model for an ACE Michaelis complex based on two known X-ray structures of inhibitor-enzyme complexes. Specifically, the human testis angiotensin-converting enzyme (tACE) complexed with two clinic drugs were first investigated using a combined quantum mechanical and molecular mechanical (QM/MM) approach. The structural parameters obtained from the 550 ps molecular dynamics simulations are in excellent agreement with the X-ray structures, validating the QM/MM approach. Based on these structures, a model for the Michaelis complex was proposed and simulated using the same computational protocol. Implications to ACE catalysis are discussed.