Retrospective molecular docking study of WY-25105 ligand to β-secretase and bias of the three-dimensional structure flexibility

β-Secretase (BACE) is a very promising target in the search for a treatment for Alzheimer’s disease using a protein–ligand inhibition approach. Given the many published X-ray structures of BACE protein, structure-based drug design has been used extensively to support new inhibitor discovery programs. Due to the high flexibility and large catalytic site of this protein, sampling of the huge conformational space of the binding site is the big challenge to overcome and is the main limitation of the most widely used docking programs. Incorrect treatment of these pitfalls can introduce bias into ligand docking and could affect the results. This is especially the case with the WY-25105 compound reported by the Wyeth Corporation as a BACE ligand that did not fit into any of the known crystal structures. In the present retrospective study, a set of available X-ray enzyme structures was selected and molecular dynamics simulations were conducted to generate more diverse representative BACE protein conformations. These conformations were then used for a docking study of the WY-25105 compound. The results confirmed the need to use an ensemble of structures in protein–ligand docking for identification of new binding modes in structure-based drug design of BACE inhibitors.

Dynamics in the active site of β-secretase: a network analysis of atomistic simulations

The aspartic protease β-secretase (BACE) catalyzes the hydrolysis of the amyloid precursor protein (APP) which leads to amyloid-β aggregation and, ultimately, the perilous Alzheimer's disease. The conformational dynamics and free energy surfaces of BACE at three steps of the catalytic cycle are studied here by explicit solvent molecular dynamics simulations (multiple runs for a total of 2.2 μs). The overall plasticity of BACE is essentially identical for the three states of the substrate: the octapeptide reactant, gem-diol intermediate, and cleavage products. In contrast, the network of hydrogen bonds in the active site is more stable in the complex of BACE with the gem-diol intermediate than the other two states of the substrate. The spontaneous release of the C-terminal (P1'-P4') fragment of the product follows a single-exponential time dependence with a time constant of 50 ns and does not require the opening of the flap. The fast dissociation of the C-terminal fragment is consistent with the transmembrane location and orientation of APP and its further processing by γ-secretase. On the other hand, the N-terminal (P4-P1) fragment of the product does not exit the BACE active site within the simulation time scale of 80 ns. A unified network analysis of the complexes of BACE with the three states of the substrate provides an estimation of the activation free energy associated with the structural rearrangements that involve only noncovalent interactions. The estimated rearrangement barriers are not negligible (up to 3 kcal/mol) but are significantly smaller than the barrier of the peptide bond hydrolysis reaction.     

Evaluation of protein–ligand affinity prediction using steered molecular dynamics simulations

In computational drug design, ranking a series of compound analogs in a manner that is consistent with experimental affinities remains a challenge. In this study, we evaluated the prediction of protein–ligand binding affinities using steered molecular dynamics simulations. First, we investigated the appropriate conditions for accurate predictions in these simulations. A conic harmonic restraint was applied to the system for efficient sampling of work values on the ligand unbinding pathway. We found that pulling velocity significantly influenced affinity predictions, but that the number of collectable trajectories was less influential. We identified the appropriate pulling velocity and collectable trajectories for binding affinity predictions as 1.25 Å/ns and 100, respectively, and these parameters were used to evaluate three target proteins (FK506 binding protein, trypsin, and cyclin-dependent kinase 2). For these proteins using our parameters, the accuracy of affinity prediction was higher and more stable when Jarzynski’s equality was employed compared with the second-order cumulant expansion equation of Jarzynski’s equality. Our results showed that steered molecular dynamics simulations are effective for predicting the rank order of ligands; thus, they are a potential tool for compound selection in hit-to-lead and lead optimization processes.     

Molecular mechanism of δ-dendrotoxin-potassium channel recognition explored by docking and molecular dynamic simulations

δ-Dendrotoxin, isolated from mamba snake venom, has 57 residues cross-linked by three disulfide bridges. The protein shares a pharmacological activity with other animal toxins, the potent blockade of potassium channels, but is structurally unrelated to toxins of different species. We employed alanine-scanning mutagenesis to explore the molecular mechanism of δ-dendrotoxin binding to potassium channels, using protein-protein docking and molecular dynamic simulations. In our reasonable model of the δ-dendrotoxin-ShaKv1.1 complex, δ-dendrotoxin interacted mainly with the N-terminal region and the turn of two antiparallel β-sheets of the channel. This binding mode could well explain the functional roles of critical residues in δ-dendrotoxin and the ShaKv1.1 channel. Structural analysis indicated that the critical Lys6 residue of δ-dendrotoxin plugged its side chain into a channel selectivity filter. Another two critical δ-dendrotoxin residues, Lys3 and Arg10, were found to contact channel residues through strong polar and nonpolar interactions, especially salt-bridge interactions. As for the ShaKv1.1 channel, the channel turrets were found in the "half-open state," and two of four Glu423 in the turrets of the channel B and D chains could interact, respectively, with Lys3 and Lys26 of δ-dendrotoxin through electrostatic interactions. The essential Asp431 channel residue was found to associate electrostatically with Arg10 of δ-dendrotoxin, and a critical Tyr449 channel residue was just under the channel-interacting surface of δ-dendrotoxin. Together, these novel data may accelerate the structure-function research of toxins in the dendrotoxin family and be of significant value in revealing the diverse interactions between animal toxins and potassium channels.     

Study of the Alzheimer's Aβ40 peptide in SDS micelles using molecular dynamics simulations

The interaction of the Alzheimer's amyloid beta peptide, Aβ40, with sodium dodecyl sulfate (SDS) micelles, together with the self-assembly of SDS molecules around the peptide from an initial random distribution were studied using atomistic and coarse-grained (CG) molecular dynamics simulations. In atomistic simulations, the peptide structure in the micelle was characterized by two helical regions connected through a short hinge. The initial structure of the system was shown to affect the simulation results. The atomistic self-assembly of SDS molecules resulted in a 38-molecule micelle around the peptide, along with some globules and individual molecules. Coarse-grained simulation results, however, did not show such a difference, and at the end of all CG simulations, a complete 60-molecule micelle was obtained, with the peptide located at the interface of the micelle with water. The obtained CG radial density profiles and SDS micelle size and shape properties were identical for all CG simulations.     

Predicting novel binding modes of agonists to β adrenergic receptors using all-atom molecular dynamics simulations

Understanding the binding mode of agonists to adrenergic receptors is crucial to enabling improved rational design of new therapeutic agents. However, so far the high conformational flexibility of G protein-coupled receptors has been an obstacle to obtaining structural information on agonist binding at atomic resolution. In this study, we report microsecond classical molecular dynamics simulations of β(1) and β(2) adrenergic receptors bound to the full agonist isoprenaline and in their unliganded form. These simulations show a novel agonist binding mode that differs from the one found for antagonists in the crystal structures and from the docking poses reported by in silico docking studies performed on rigid receptors. Internal water molecules contribute to the stabilization of novel interactions between ligand and receptor, both at the interface of helices V and VI with the catechol group of isoprenaline as well as at the interface of helices III and VII with the ethanolamine moiety of the ligand. Despite the fact that the characteristic N-C-C-OH motif is identical in the co-crystallized ligands and in the full agonist isoprenaline, the interaction network between this group and the anchor site formed by Asp(3.32) and Asn(7.39) is substantially different between agonists and inverse agonists/antagonists due to two water molecules that enter the cavity and contribute to the stabilization of a novel network of interactions. These new binding poses, together with observed conformational changes in the extracellular loops, suggest possible determinants of receptor specificity.     

Screening of potential lead molecules against prioritised targets of multi-drug-resistant-Acinetobacter baumannii – insights from molecular docking,molecular dynamic simulations and in vitro assays

Acinetobacter baumannii, an opportunistic pathogen, has become multi-drug resistant (MDR) to major classes of antibacterial and poses grave threat to public health. The current study focused to screen novel phytotherapeutics against prioritised targets of Acinetobacter baumannii by computational investigation. Fourteen potential drug targets were screened based on their functional role in various biosynthetic pathways and the 3D structures of 9 targets were retrieved from Protein Data Bank and others were computationally predicted. By extensive literature survey, 104 molecules from 48 herbal sources were screened and subjected to virtual screening. Ten clinical isolates of A. baumannii were tested for antibiotic susceptibility towards clinafloxacin, imipenem and polymyxin-E. Computational screening suggested that Ajmalicine ((19α)-16, 17-didehydro-19-methyloxayohimban-16-carboxylic acid methyl ester from Rauwolfia serpentina), Strictamin (Akuammilan-17-oic acid methyl ester from Alstonia scholaris) and Limonin (7, 16-dioxo-7, 16-dideoxylimondiol from Citrus sps) exhibited promising binding towards multiple drug targets of A. baumannii in comparison with the binding between standard drugs and their targets. Limonin displayed promising binding potential (binding energy ?9.8 kcal/mol) towards diaminopimelate epimerase (DapF) and UDP-N-acetylglucosamine 1-carboxyvinyltransferase (MurA). Ajmalicine and Strictamin demonstrated good binding potential (?9.5, ?8.5 kcal/mol, respectively) towards MurA and shikimate dehydrogenase (?7.8 kcal/mol). Molecular dynamic simulations further validated the docking results. In vitro assay suggested that the tested isolates exhibited resistance to clinafloxacin, imipenem and polymyxin-E and the herbal preparations (crude extract) demonstrated a significant antibacterial potential (p ≤ .05). The study suggests that the aforementioned lead candidates and targets can be used for structure-based drug screening towards MDR A. baumannii.     

Interaction models of substrate peptides and β-secretase studied by NMR spectroscopy and molecular dynamics simulation

The formation of β-amyloid peptide (Aβ) is initiated from cleavage of amyloid precursor protein (APP) by a family of protease, α-, β-, and γ-secretase. Sub W, a substrate peptide, consists of 10 amino acids, which are adjacent to the β-cleavage site of wild-type APP, and Sub M is Swedish mutant with double mutations on the left side of the β-cleavage site of APP. Sub W is a normal product of the metabolism of APP in the secretary pathway. Sub M is known to increase the efficiency of β-secretase activity, resulting in a more specific binding model compared to Sub W. Three-dimensional structures of Sub W and Sub M were studied by CD and NMR spectroscopy in water solution. On the basis of these structures, interaction models of β-secretase and substrate peptides were determined by molecular dynamics simulation. Four hydrogen bonds and one water-mediated interaction were formed in the docking models. In particular, the hydrogen bonding network of Sub M-BACE formed spread over the broad region of the active site of β-secretase (P5-P3′), and the side chain of P2-Asn formed a hydrogen bond specifically with the side chain of Arg235. These are more favorable to the cleavage of Sub M by β-secretase than Sub W. The two substrate peptides showed different tendency to bind to β-secretase and this information may useful for drug development to treat and prevent Alzheimer’s disease.     

Unfolding of the amyloid β-peptide central helix: mechanistic insights from molecular dynamics simulations

Alzheimer's disease (AD) pathogenesis is associated with formation of amyloid fibrils caused by polymerization of the amyloid β-peptide (Aβ), which is a process that requires unfolding of the native helical structure of Aβ. According to recent experimental studies, stabilization of the Aβ central helix is effective in preventing Aβ polymerization into toxic assemblies. To uncover the fundamental mechanism of unfolding of the Aβ central helix, we performed molecular dynamics simulations for wild-type (WT), V18A/F19A/F20A mutant (MA), and V18L/F19L/F20L mutant (ML) models of the Aβ central helix. It was quantitatively demonstrated that the stability of the α-helical conformation of both MA and ML is higher than that of WT, indicating that the α-helical propensity of the three nonpolar residues (18, 19, and 20) is the main factor for the stability of the whole Aβ central helix and that their hydrophobicity plays a secondary role. WT was found to completely unfold by a three-step mechanism: 1) loss of α-helical backbone hydrogen bonds, 2) strong interactions between nonpolar sidechains, and 3) strong interactions between polar sidechains. WT did not completely unfold in cases when any of the three steps was omitted. MA and ML did not completely unfold mainly due to the lack of the first step. This suggests that disturbances in any of the three steps would be effective in inhibiting the unfolding of the Aβ central helix. Our findings would pave the way for design of new drugs to prevent or retard AD.     

Binding modes of phosphotriesterase-like lactonase complexed with δ-nonanoic lactone and paraoxon using molecular dynamics simulations

Phosphotriesterase-like lactonases (PLLs) have received much attention because of their physical and chemical properties. They may have widespread applications in various fields. For example, they show potential for quorum-sensing signaling pathways and organophosphorus (OP) detoxification in agricultural science. However, the mechanism by which PLLs hydrolyze, which involves OP compounds and lactones and a variety of distinct catalytic efficiencies, has only rarely been explored. In the present study, molecular dynamics (MD) simulations were performed to characterize and contrast the structural dynamics of DrPLL, a member of the PLL superfamily in Deinococcus radiodurans, bound to two substrates, δ-nonanoic lactone and paraoxon. It has been observed that there is a 16-fold increase in the catalytic efficiency of the two mutant strains of DrPLL (F26G/C72I) vs. the wild-type enzyme toward the hydrolysis of paraoxon, but an explanation for this behavior is currently lacking. The analysis of the molecular trajectories of DrPLL bound to δ-nonanoic lactone indicated that lactone-induced conformational changes take place in loop 8, which is near the active site. Binding to paraoxon may lead to conformational displacement of loop 1 residues, which could lead to the deformation of the active site and so trigger the entry of the paraoxon into the active site. The efficiency of the F26G/C72I mutant was increased by decreasing the displacement of loop 1 residues and increasing the flexibility of loop 8 residues. These results provide a molecular-level explanation for the experimental behavior.     

Structure and dynamics of two β-peptides in solution from molecular dynamics simulations validated against experiment

We have studied two different beta-peptides in methanol using explicit solvent molecular dynamics simulations and the GROMOS 53A6 force field: a heptapeptide (peptide 1) expected to form a left-handed 3(14)-helix, and a hexapeptide (peptide 2) expected to form a beta-hairpin in solution. Our analysis has focused on identifying and analyzing the stability of the dominant secondary structure conformations adopted by the peptides, as well as on comparing the experimental NOE distance upper bounds and 3J-coupling values with their counterparts calculated on the basis of the simulated ensembles. Moreover, we have critically compared the present results with the analogous results obtained with the GROMOS 45A3 (peptide 1) and 43A1 (peptide 2) force fields. We conclude that within the limits of conformational sampling employed here, the GROMOS 53A6 force field satisfactorily reproduces experimental findings regarding the behavior of short beta-peptides, with accuracy that is comparable to but not exceeding that of the previous versions of the force field. GCE legend Conformational clustering analysis of the simulated ensemble of a ss-hexapeptide with two different simulation setups (a and b). The central members of all of the clusters populating more than 5% of all of the structures are shown, together with the most dominant hydrogen bonds and the corresponding percentages of cluster members containing them.     

An internal docking site stabilizes substrate binding to γ-secretase: Analysis by molecular dynamics simulations

Amyloid precursor protein (APP) is cleaved and processed sequentially by γ-secretase yielding amyloid β (Aβ) peptides of different lengths. Longer Aβ peptides are associated with the formation of neurotoxic plaques related to Alzheimer’s disease. Based on the APP substrate-bound structure of γ-secretase, we investigated the enzyme-substrate interaction using molecular dynamics simulations and generated model structures that represent the sequentially cleaved intermediates during the processing reaction. The simulations indicated an internal docking site providing strong enzyme-substrate packing interaction. In the enzyme-substrate complex, it is located close to the region where the helical conformation of the substrate is interrupted and continues toward the active site in an extended conformation. The internal docking site consists of two non-polar pockets that are preferentially filled by large hydrophobic or aromatic substrate side chains to stabilize binding. Placement of smaller residues such as glycine can trigger a shift in the cleavage pattern during the simulations or results in destabilization of substrate binding. The reduced packing by smaller residues also influences the hydration of the active site and the formation of a catalytically active state. The simulations on processed substrate intermediates and a substrate G33I mutation offer an explanation of the experimentally observed relative increase of short Aβ fragment production for this mutation. In addition, studies on a substrate K28A mutation indicate that the internal docking site opposes the tendency of substrate dissociation due to a hydrophobic mismatch at the membrane boundary caused by K28 during processing and substrate movement toward the enzyme active site. The proposed internal docking site could also be useful for the specific design of new γ-secretase modulators.     

Direct observations of shifts in the β-sheet register of a protein-peptide complex using explicit solvent simulations

Using explicit solvent molecular dynamics simulations, we were able to obtain direct observations of shifts in the hydrogen-bonding register of an intermolecular β-sheet protein-peptide complex. The β-sheet is formed between the FHA domain of cancer marker protein Ki67 (Ki67FHA) and a peptide fragment of the hNIFK signaling protein. Potential encounter complexes of the Ki67FHA receptor and hNIFK peptide are misregistered states of the β-sheet. Rearrangements of one of these misregistered states to the native state were captured in three independent simulations. All three rearrangements occurred by a common mechanism: an aromatic residue of the peptide (F263) anchors into a transient hydrophobic pocket of the receptor to facilitate the formation of native hydrogen bonds. To our knowledge, these simulations provide the first atomically detailed visualizations of a mechanism by which nature might correct for errors in the alignment of intermolecular β-sheets.     

Determination of rarefaction effects on transport properties of nanoscale gas flows using Green–Kubo molecular dynamic simulation

This study aimed to investigate the rarefaction effects on thermal conductivity, viscosity, and density of Argon, Neon and Xenon gas flows in a Platinum nanochannel. Green–Kubo approach with Lenard Jones potential function are used for molecular dynamic simulation. Simulations showed that with decrease in number of atoms, density, viscosity and thermal conductivity decreases, while decrease in nanochannel width in same number of gas atoms leads to increase in viscosity and thermal conductivity.     

Effects of ligands on unfolding of the amyloid β-peptide central helix: mechanistic insights from molecular dynamics simulations

Polymerization of the amyloid β-peptide (Aβ), a process which requires that the helical structure of Aβ unfolds beforehand, is suspected to cause neurodegeneration in Alzheimer's disease. According to recent experimental studies, stabilization of the Aβ central helix counteracts Aβ polymerization into toxic assemblies. The effects of two ligands (Dec-DETA and Pep1b), which were designed to bind to and stabilize the Aβ central helix, on unfolding of the Aβ central helix were investigated by molecular dynamics simulations. It was quantitatively demonstrated that the stability of the Aβ central helix is increased by both ligands, and more effectively by Pep1b than by Dec-DETA. In addition, it was shown that Dec-DETA forms parallel conformations with β-strand-like Aβ, whereas Pep1b does not and instead tends to bend unwound Aβ. The molecular dynamics results correlate well with previous experiments for these ligands, which suggest that the simulation method should be useful in predicting the effectiveness of novel ligands in stabilizing the Aβ central helix. Detailed Aβ structural changes upon loss of helicity in the presence of the ligands are also revealed, which gives further insight into which ligand may lead to which path subsequent to unwinding of the Aβ central helix.     

Developing β-secretase inhibitors for treatment of Alzheimer's disease

β-Secretase (memapsin 2; BACE-1) is the first protease in the processing of amyloid precursor protein leading to the production of amyloid-β (Aβ) in the brain. It is believed that high levels of brain Aβ are responsible for the pathogenesis of Alzheimer's disease (AD). Therefore, β-secretase is a major therapeutic target for the development of inhibitor drugs. During the past decade, steady progress has been made in the evolution of β-secretase inhibitors toward better drug properties. Recent inhibitors are potent, selective and have been shown to penetrate the blood-brain barrier to inhibit Aβ levels in the brains of experimental animals. Moreover, continuous administration of a β-secretase inhibitor was shown to rescue age-related cognitive decline in transgenic AD mice. A small number of β-secretase inhibitors have also entered early phase clinical trials. These developments offer some optimism for the clinical development of a disease-modifying drug for AD.     

Investigation of the binding mode of (−)-meptazinol and bis-meptazinol derivatives on acetylcholinesterase using a molecular docking method

Molecular docking has been performed to investigate the binding mode of (-)-meptazinol (MEP) with acetylcholinesterase (AChE) and to screen bis-meptazinol (bis-MEP) derivatives for preferable synthetic candidates virtually. A reliable and practical docking method for investigation of AChE ligands was established by the comparison of two widely used docking programs, FlexX and GOLD. In our hands, we had more luck using GOLD than FlexX in reproducing the experimental poses of known ligands (RMSD<1.5 A). GOLD fitness values of known ligands were also in good agreement with their activities. In the present GOLD docking protocol, (-)-MEP seemed to bind with the enzyme catalytic site in an open-gate conformation through strong hydrophobic interactions and a hydrogen bond. Virtual screening of a potential candidate compound library suggested that the most promising 15 bis-MEP derivatives on the list were mainly derived from (-)-MEP with conformations of (S,S) and (SR,RS) and with a 2- to 7-carbon linkage. Although there are still no biological results to confirm the predictive power of this method, the current study could provide an alternate tool for structural optimization of (-)-MEP as new AChE inhibitors. [Figure: see text].     

Finite-size effects of Kirkwood–Buff integrals from molecular simulations

The modelling of thermodynamic properties of liquids from local density fluctuations is relevant to many chemical and biological processes. The Kirkwood–Buff (KB) theory connects the microscopic structure of isotropic liquids with macroscopic properties such as partial derivatives of activity coefficients, partial molar volumes and compressibilities. Originally, KB integrals were formulated for open and infinite systems which are difficult to access with standard Molecular Dynamics (MD) simulations. Recently, KB integrals for finite and open systems were formulated (J Phys Chem Lett. 2013;4:235). From the scaling of KB integrals for finite subvolumes, embedded in larger reservoirs, with the inverse of the size of these subvolumes, estimates for KB integrals in the thermodynamic limit are obtained. Two system size effects are observed in MD simulations: (1) effects due to the size of the simulation box and the size of the finite subvolume embedded in the simulation box, and (2) effects due to computing radial distribution functions (RDF) from a closed and finite system. In this study, we investigate the two effects in detail by computing KB integrals using the following methods: (1) Monte Carlo simulations of finite subvolumes of a liquid with an analytic RDF and (2) MD simulations of a WCA mixture for various simulation box sizes, but at the same thermodynamic state. We investigate the effect of the size of the simulation box and quantify the differences compared to KB integrals computed in the thermodynamic limit. We demonstrate that calculations of KB integrals should not be extended beyond half the size of the simulation box. For finite-size effects related to the RDF, we find that the Van der Vegt correction (J Chem Theory Comput. 2013;9:1347) yields the most accurate results.