Consensus scoring model for the molecular docking study of mTOR kinase inhibitor

The discovery of mammalian target of rapamycin (mTOR) kinase inhibitors has always been a research hotspot of antitumor drugs. Consensus scoring used in the docking study of mTOR kinase inhibitors usually improves hit rate of virtual screening. Herein, we attempt to build a series of consensus scoring models based on a set of the common scoring functions. In this paper, twenty-five kinds of mTOR inhibitors (16 clinical candidate compounds and 9 promising preclinical compounds) are carefully collected, and selected for the molecular docking study used by the Glide docking programs within the standard precise (SP) mode. The predicted poses of these ligands are saved, and revaluated by twenty-six available scoring functions, respectively. Subsequently, consensus scoring models are trained based on the obtained rescoring results by the partial least squares (PLS) method, and validated by Leave-one-out (LOO) method. In addition, three kinds of ligand efficiency indices (BEI, SEI, and LLE) instead of pIC₅₀ as the activity could greatly improve the statistical quality of build models. Two best calculated models 10 and 22 using the same BEI indice have following statistical parameters, respectively: for model 10, training set R² = 0.767, Q² = 0.647, RMSE = 0.024, and for test set R² = 0.932, RMSE = 0.026; for model 22, raining set R² = 0.790, Q² = 0.627, RMSE = 0.023, and for test set R² = 0.955, RMSE = 0.020. These two consensus scoring model would be used for the docking virtual screening of novel mTOR inhibitors.     

Combining flow and dependence analyses to expose redundant array accesses

The success of large-scale, hierarchical and distributed shared memory systems hinges on our ability to reduce delays resulting from remote accesses to shared data. To facilitate this, we present a compile-time algorithm for analyzing programs with doall-style parallelism to determine when read and write accesses to shared data areredundant (unnecessary). One identified, redundant remote accesses can be replaced by local accesses or eliminated entirely. This optimization improves program performance in two ways. First, slow memory accesses are replaced by faster ones. Second, the time to perform other remote memory accesses may be reduced as a result of the decreased traffic level. We also show how the information obtained through redundancy analysis can be used for other compiler optimizations such as prefetching and cache management.     

Investigating detailed interactions between novel PAR1 antagonist F16357 and the receptor using docking and molecular dynamic simulations

Currently, Vorapaxar is the only recently FDA-approved antiplatelet drug targeting Protease-activated receptor 1 (PAR1). However, a novel antagonist, F16357, has been shown to prevent painful bladder syndrome, also known as interstitial cystitis (IC). Unfortunately, there is no high resolution structure of the F16357-receptor complex, hindering its optimization as a therapeutic agent. In this study, we used docking and molecular dynamic (MD) simulations to investigate the detailed interactions between F16357 and PAR1 at a molecular level. The recently solved crystal structure of human PAR1 complexed with Vorapaxar was used in our docking of F16357 into the binding pocket of the receptor. To enhance binding pose selection, F16357 was docked first without constraints and then with a positional constraint to invert its orientation to become similar to that of Vorapaxar. The three systems, with crystal Vorapaxar, F16357 and an inverted F16357, were subjected to 3.0 μs MD simulations. The MM-GBSA binding energy analysis showed that F16357 binds more strongly in a pose obtained from an unrestrained docking than in the inverted pose from a restrained docking; and Vorapaxar binds more strongly than F17357. This ordering is consistent with the experimental pIC₅₀ values. Our structural data showed subtle changes in the binding pose between Vorapaxar and F16357. Transmembrane helices 1, 2, 5, and 7 were most significantly affected; most notably a large kink at F279^5.47 in TM helix 5 of the Vorapaxar complex was completely absent in the F16357 complex. The results of this study facilitate the future development of other therapeutic PAR1 antagonists.     

Assessment of new anti-HER2 ligands using combined docking,QM/MM scoring and MD simulation

In the development of new anti-cancer drugs to tackle the problem of resistance to current chemotherapeutic agents, a new series of anti-HER2 (human epidermal growth factor receptors 2) agents has been synthesized and investigated using different computational methods. Although non-selective, the most active inhibitor in the new series shows higher activity toward HER2 than EGFR. The induced fit docking protocol (IFD) is performed to find possible binding poses of the new inhibitors in the active site of the HER2 receptor. Molecular dynamic simulations of the inhibitor–protein complexes for the two most active compounds from the new series are carried out. Simulations stability is checked using different stability parameters. Different scoring functions are employed.     

Applying capacity analyses to psychophysical evaluation of multisensory interactions

Determining when, if, and how information from separate sensory channels has been combined is a fundamental goal of research on multisensory processing in the brain. This can be a particular challenge in psychophysical data, as there is no direct recording of neural output. The most common way to characterize multisensory interactions in behavioral data is to compare responses to multisensory stimulation with the race model, a model of parallel, independent processing constructed from the probability of responses to the two unisensory stimuli which make up the multisensory stimulus. If observed multisensory reaction times are faster than those predicted by the model, it is inferred that information from the two channels is being combined rather than processed independently. Recently, behavioral research has been published employing capacity analyses where comparisons between two conditions are carried out at the level of the integrated hazard function. Capacity analyses seem to be particularly appealing technique for evaluating multisensory functioning, as they describe relationships between conditions across the entire distribution curve, are relatively easy and intuitive to interpret. The current paper presents capacity analysis of a behavioral data set previously analyzed using the race model. While applications of capacity analyses are still somewhat limited due to their novelty, it is hoped that this exploration of capacity and race model analyses will encourage the use of this promising new technique both in multisensory research and other applicable fields.     

Tunable approximations to control time-to-solution in an HPC molecular docking Mini-App

The Journal of Supercomputing - The drug discovery process involves several tasks to be performed in vivo, in vitro and in silico. Molecular docking is a task typically performed in silico. It aims...     

Application of numerical optimization methods to molecular docking on graphics processing units

This paper is devoted to analyzing numerical optimization methods for solving the problem of molecular docking. Some additional requirements for optimization methods that take into account certain architectural features of graphics processing units (GPUs) have been formulated. A promising optimization method for use on graphics processors has been selected, its implementation is described, and its efficiency and accuracy have been estimated.     

A strategic solution to optimize molecular docking simulations using Fully-Flexible Receptor models

Molecular docking simulations are commonly used to identify and optimize drug candidates by examining the interactions between the target protein and small chemical ligands. This procedure is computationally expensive, especially when the receptor is treated as an ensemble of molecular dynamic conformations, namely the Fully-Flexible Receptor (FFR) model. An FFR model can vary from thousands to millions of conformations. Handling molecular docking experiments on FFR models with flexible ligands still constitutes a big challenge, since it may take hours, days, or even months to be completely executed for a single ligand. Moreover, thousands of molecular docking results are quite hard to be analyzed by a domain expert, who typically explores results starting with FEB and RMSD values. This paper addresses the high computational demand to exhaustively execute molecular docking simulations on FFR models, as well as the problem of accurately selecting a small set of representative docking results to be analyzed by a domain expert. Our approach is twofold: (1) we make use of the wFReDoW environment to decrease the dimension of the FFR model during docking experiments, trying to maintain the quality in the resulting reduced models, and (2) we perform careful analyses on docking results to select a set of representative candidate poses. Our simulation results show that the proposed method is able to achieve a trade-off between accuracy and computational cost. This is evidenced from the accuracy in wFReDoW results, which contain 96% of the snapshots within the set of the 100 best FEB values when only 67% of snapshots from the FFR model were docked.     

Exploiting OpenMP and OpenACC to accelerate a geometric approach to molecular docking in heterogeneous HPC nodes

The Journal of Supercomputing - In drug discovery, molecular docking is the task in charge of estimating the position of a molecule when interacting with the docking site. This task is usually used...     

A mechanistic approach to explore novel HDAC1 inhibitor using pharmacophore modeling, 3D- QSAR analysis,molecular docking,density functional and molecular dynamics simulation study

Deregulated epigenetic activity of Histone deacetylase 1 (HDAC1) in tumor development and carcinogenesis pronounces it as promising therapeutic target for cancer treatment. HDAC1 has recently captured the attention of researchers owing to its decisive role in multiple types of cancer. In the present study a multistep framework combining ligand based 3D-QSAR, molecular docking and Molecular Dynamics (MD) simulation studies were performed to explore potential compound with good HDAC1 binding affinity. Four different pharmacophore hypotheses Hypo1 (AADR), Hypo2 (AAAH), Hypo3 (AAAR) and Hypo4 (ADDR) were obtained. The hypothesis Hypo1 (AADR) with two hydrogen bond acceptors (A), one hydrogen bond donor (D) and one aromatics ring (R) was selected to build 3D-QSAR model on the basis of statistical parameter. The pharmacophore hypothesis produced a statistically significant QSAR model, with co-efficient of correlation r² = 0.82 and cross validation correlation co-efficient q² = 0.70. External validation result displays high predictive power with r² (o) value of 0.88 and r² (m) value of 0.58 to carry out further in silico studies. Virtual screening result shows ZINC70450932 as the most promising lead where HDAC1 interacts with residues Asp99, His178, Tyr204, Phe205 and Leu271 forming seven hydrogen bonds. A high docking score (−11.17 kcal/mol) and lower docking energy −37.84 kcal/mol) displays the binding efficiency of the ligand. Binding free energy calculation was done using MM/GBSA to access affinity of ligands towards protein. Density Functional Theory was employed to explore electronic features of the ligands describing intramolcular charge transfer reaction. Molecular dynamics simulation studies at 50 ns display metal ion (Zn)-ligand interaction which is vital to inhibit the enzymatic activity of the protein.     

Three-dimensional molecular field analyses of octopaminergic agonists and antagonists for the locust neuronal octopamine receptor class 3

The quantitative structure-activity relationship (QSAR) of a set of 70 octopaminergic agonists and 20 antagonists against octopamine receptor class 3 (OAR3) in locust nervous tissue was analyzed by molecular field analysis (MFA). MFA of these compounds evaluated effectively the energy between a probe and a molecular model at a series of points defined by a rectangular grid. Contour surfaces for the molecular fields are presented. These results provide useful information in the characterization and differentiation of octopaminergic receptor types and subtypes.     

Single-coordinate-driving method for molecular docking: application to modeling of guest inclusion in cyclodextrin

An extension of the computer program CICADA has been developed that allows us to use the single-coordinate-driving (SCD) method for flexible molecular docking. The docking procedure is composed of three independent space rotations, three independent translations, and the torsions selected by the user. One of the coordinates is driven; the other coordinates are relaxed. This procedure follows low-energy wells on the potential energy surface of the entire system. The program allows us to dock more than one ligand molecule to the receptor. We ran two test examples, docking N,N-dimethylformamide into alpha-cyclodextrin and R-phenoxypropionic acid into beta-cyclodextrin. The test examples showed that the SCD approach is able to overcome high-energy barriers and to cover the entire box within which the search is performed. The limitations of molecular dynamics docking in comparison with our approach also are discussed. The philosophy of the newly developed approach is not only to find the best dock for the receptor-ligand(s) system, but also to describe all the important binding modes and provide a good starting point for studying the dynamics within the cavity during the docking process.     

Catalytic mechanism of l,l-diaminopimelic acid with diaminopimelate epimerase by molecular docking simulations

Peptidoglycan, a key constituent of bacterial cell walls, is currently the target of broad spectrum antibiotics and a new research field involves both design and synthesis of inhibitors of its biosynthesis. Most bacteria require either lysine, or its biosynthetic precursor, diaminopimelate (meso-DAP), as a component of the peptidoglycan layer of the cell wall. In this paper, molecular modelling studies were undertaken in order to shed light on the molecular basis of interaction between (2S,6S)-diaminopimelic acid (l,l-DAP) (1) with its target enzyme DAP-epimerase, since this is a key step in the lysine biosynthetic path leading to (2R,6S)-diaminopimelic acid (meso-DAP) (2). In particular, the docking of the ligand-enzyme complex was studied by means of MD simulations and DFT computations in order to ascertain the optimal structural requirements for the epimerization reaction. Molecular dynamics simulations clearly showed that the configuration of the distal carbon C6 of l,l-DAP is critical for complex formation since both amino and carboxylate groups are involved in Hbonding interactions with the active site residues. Furthermore, the interactions occurring between the functional groups bonded to the C2 and some residues of the binding cavity immobilize the ligand in a position appropriate for the epimerization reaction, i.e., exactly in the middle of the two catalytic residues Cys73 and Cys217 as confirmed by DFT quantum mechanical computation of the Michaelis complex. All this mechanistic information could be useful for the rational design of new potential antibiotic drugs effective as inhibitors of peptidoglycan biosynthesis.     

基于联合建模的中小型航天器对接杆缓冲性能分析

基于中小型航天器对接过程可以考虑在对接杆部分实现缓冲的思想,改变对接杆构型,采用变形能力大的对接杆提高对接冲击的缓冲性能,通过Pro/ENGINEER与MSC Patran和MSC Dytran的配合使用,对普通圆柱直杆、弓形杆和球形杆等3种构型的对接杆进行建模,仿真分析其在正碰和斜碰情形下的缓冲性能,并通过改变碰撞初...     

Human type 10 17 beta-hydroxysteroid dehydrogenase: molecular modelling and substrate docking

17 beta-hydroxysteroid dehydrogenases catalyze the oxidoreduction of hydroxy/oxo groups at position C17 of steroid hormones, thereby constituting a prereceptor control mechanism of hormone action. At present, 11 different mammalian 17 beta-hydroxysteroid dehydrogenases have been identified, catalyzing the cell- and steroid-specific activation and inactivation of estrogens and androgens. The human type 10 17 beta-hydroxysteroid dehydrogenase (17 beta-HSD-10) is a multifunctional mitochondrial enzyme that efficiently catalyzes the oxidative inactivation at C17 of androgens and estrogens. However, it also mediates oxidation of 3 alpha-hydroxy groups of androgens, thereby reactivating androgen metabolites. Finally, it is involved in beta-oxidation of fatty acids by catalyzing the L-hydroxyacyl CoA dehydrogenase reaction of the beta-oxidation cycle. These features and expression profiles suggest a critical role of 17 beta-HSD-10 in neurodegenerative and steroid-dependent cancer forms. Since no three-dimensional structure of 17 beta-HSD-10 is available, homology modelling was carried out to understand the molecular basis of these substrate specificities. The structure obtained displays the properties of a one-domain, alpha/beta fold enzyme of the SDR family. The active site is located within a large, hydrophobic cleft, which forms optimal contacts with the different steroid surfaces. The data provide explanations for the substrate specificities toward the various classes of sex steroid hormones. The model is suitable to explore substrate and inhibitor characteristics that may be used in the development of novel strategies in the treatment of degenerative or malignant diseases.     

Bio-inspired optimization for the molecular docking problem: State of the art,recent results and perspectives

Molecular docking is a Bioinformatics method based on predicting the position and orientation of a small molecule or ligand when it is bound to a target macromolecule. This method can be modeled as an optimization problem where one or more objectives can be defined, typically around an energy scoring function. This paper reviews developments in the field of single- and multi-objective meta-heuristics for efficiently addressing molecular docking optimization problems. We comprehensively analyze both problem formulations and applied techniques from Evolutionary Computation and Swarm Intelligence, jointly referred to as Bio-inspired Optimization. Our prospective analysis is supported by an experimental study dealing with a molecular docking problem driven by three conflicting objectives, which is tackled by using different multi-objective heuristics. We conclude that genetic algorithms are the most widely used techniques by far, with a noted increasing prevalence of particle swarm optimization in the last years, being these last techniques particularly adequate when dealing with multi-objective formulations of molecular docking problems. We end this experimental survey by outlining future research paths that should be under target in this vibrant area.     

Homology modeling and molecular docking studies of Drosophila and Aedes sex peptide receptors

The Drosophila melanogaster sex peptide receptor (DrmSPR), which is a G protein-coupled receptor (GPCR), is known as the specific receptor for sex peptide (SP). It is responsible for the reproductive behavior in the Drosophila model system; in particular, it is involved in the post-mating responses such as the increase in egg-laying ability and decrease in receptivity in females. In a previous study, we discovered a small molecule agonist of DrmSPR for the first time, which could not, however, activate Aedes aegypti SPR (AedesSPR). To investigate the binding mechanism of the small molecule agonist of DrmSPR, the ensemble structures of low-lying packing structures of DrmSPR and AedesSPR were assembled using the GEnSeMBLE (GPCR Ensemble of Structures in Membrane BiLayer Environment) method. The generated homology models exhibited the typical pattern of inter-helical interactions of the class A GPCRs. The docking experiments of the small molecule agonist suggest that Tyr^5.35 and Phe^2.67 residues may be involved in a hydrophobic interaction and that Ser^3.25 forms a hydrogen bond with the agonist. Additionally, we found that the docking results were consistent with the experimental data of the reference compounds with variable agonistic activities. Moreover, a potential distinction of the putative binding sites in two GPCR models of DrmSPR and AedesSPR, which was determined in this study, can explain the selective action of the agonist for DrmSPR but not for AedesSPR.     

Arylhydrazone derivatives of naproxen as new analgesic and anti-inflammatory agents: Design,synthesis and molecular docking studies

A series of new arylidenehydrazone derivatives of naproxen were synthesized and evaluated for their analgesic and anti-inflammatory activities. Some of the synthesized analogues showed comparable activities when compared against naproxen for their analgesic and anti-inflammatory properties. 2-(6-methoxy-2-naphthyl)-N′-[(pyridine-4-yl)methylene]propanoic acid hydrazide 4j was found to be the most active analgesic agent. 2-(6-methoxy-2-naphthyl)-N′-[4-nitrobenzylidene]propanoic acid hydrazide 4g showed highest anti-inflammatory activity in comparison to the naproxen. Molecular modeling study of the synthesized compounds suggested that the designed molecules were well located and bound to the COX-1 and COX-2 active sites. Compound 4g showed the highest selectivity for COX-2 (R_{COX-2/COX-1 =} 1.94) and higher affinity rather than naproxen in COX-2 active site (R_{COX-2/naproxen =} 1.28). Moreover, the structural analyses confirmed that the E-ap rotamer is the preferred structure for the arylidenehydrazone derivatives.     

Long-range interactions and parallel scalability in molecular simulations

Typical biomolecular systems such as cellular membranes, DNA, and protein complexes are highly charged. Thus, efficient and accurate treatment of electrostatic interactions is of great importance in computational modeling of such systems. We have employed the GROMACS simulation package to perform extensive benchmarking of different commonly used electrostatic schemes on a range of computer architectures (Pentium-4, IBM Power 4, and Apple/IBM G5) for single processor and parallel performance up to 8 nodes—we have also tested the scalability on four different networks, namely Infiniband, GigaBit Ethernet, Fast Ethernet, and nearly uniform memory architecture, i.e. communication between CPUs is possible by directly reading from or writing to other CPUs' local memory. It turns out that the particle-mesh Ewald method (PME) performs surprisingly well and offers competitive performance unless parallel runs on PC hardware with older network infrastructure are needed. Lipid bilayers of sizes 128, 512 and 2048 lipid molecules were used as the test systems representing typical cases encountered in biomolecular simulations. Our results enable an accurate prediction of computational speed on most current computing systems, both for serial and parallel runs. These results should be helpful in, for example, choosing the most suitable configuration for a small departmental computer cluster.