Homology modeling, binding site identification and docking in flavone hydroxylase CYP105P2 in Streptomyces peucetius ATCC 27952

Homology models of cytochrome P450 105P2 (CYP105P2) were constructed using four P450 structures, CYP105A1, CYP105, CYP165B3 and CYP107L1, as templates for the model building. Using Accelrys Discovery Studio 2.1 software, the lowest energy CYP105P2 model was then assessed for stereochemical quality and side-chain environment. Further active site optimization of the CYP105P2 model built using these templates was performed by molecular dynamics to generate the final CYP105P2 model. The substrates, flavone, flavanone, quercetin and naringenin, were docked into the model. The model-flavone complex was used to validate the active site architecture, and structurally and functionally important residues were identified by subsequent characterization of the secondary structure.     

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

The growing number of protein–ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein–ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein–ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein–ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein–ligand complex structures available to improve predictions on binding.     

Synthesis,structure and electrochemical properties of a polyoxometalate-templated compound with 2D twofold interpenetrating network

A new Keggin-type polyoxometalate-based compound {[Cu₂(L)₄(H₂O)₄](PW₁₁^VIW^VO₄₀)}·16H₂O (1) constructed from PW₁₁^VIW^VO₄₀ ⁴⁻, N,N′-bis(4-pyridylformyl) piperazine (L) and Cu(II) has been hydrothermally synthesized and structurally characterized by elemental analyses, IR and single-crystal X-ray diffraction analysis. Single-crystal X-ray diffraction analysis reveals that the semi-rigid piperazine-based ligands L coordinate to the Cu(II) atoms to constitute a two dimensional coordination network. The 2D (4, 4) cationic layers are stacked together in a perpendicular mode, resulting in the formation of twofold interpenetrating frameworks with large cavities. The PW₁₂ anions reside in the large cubic-like cavities, serving as non-coordinating templates. The compound 1 displays good electrocatalytic activity toward the reduction of nitrite in 1 M H₂SO₄ aqueous solution.     

细胞色素P450 2f1(CYP2f1)的三维结构模建和与维甲酸的对接研究

利用同源模建和分子动力学模拟方法，模建了细胞色素P450 2f1(CYP2f1)的三维结构．在此基础上，分析了活性位点的组成和结构，并进行了与小分子(维甲酸)的对接研究．研究结果表明，His328，Ser397和Arg417对复合物的结合起重要作用．     

Constituents of Zingiber aromaticum and their CYP3A4 and CYP2D6 inhibitory activity

A new sesquiterpene 2,9-humuladien-6-ol-8-one (1) was isolated from methanol extract of Zingiber aromaticum, along with 15 known compounds. The structures of the isolated compounds were elucidated on the basis of spectroscopic analyses. The isolated compounds were tested for their inhibitory activity on the metabolism mediated by cytochrome P450 3A4 (CYP3A4) and CYP2D6.     

Investigation of binding features: Effects on the interaction between CYP2A6 and inhibitors

A computational investigation has been carried out on CYP2A6 and its naphthalene inhibitors to explore the crucial molecular features contributing to binding specificity. The molecular bioactive orientations were obtained by docking (FlexX) these compounds into the active site of the enzyme. And the density functional theory method was further used to optimize the molecular structures with the subsequent analysis of molecular lipophilic potential (MLP) and molecular electrostatic potential (MEP). The minimal MLPs, minimal MEPs, and the band gap energies (the energy difference between the highest occupied molecular orbital and lowest unoccupied molecular orbital) showed high correlations with the inhibition activities (pIC₅₀s), illustrating their significant roles in driving the inhibitor to adopt an appropriate bioactive conformation oriented in the active site of CYP2A6 enzyme. The differences in MLPs, MEPs, and the orbital energies have been identified as key features in determining the binding specificity of this series of compounds to CYP2A6 and the consequent inhibitory effects. In addition, the combinational use of the docking, MLP and MEP analysis is also demonstrated as a good attempt to gain an insight into the interaction between CYP2A6 and its inhibitors. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Molecular characterization,modeling and docking of CYP107CB2 from Bacillus lehensis G1, an alkaliphile

Cytochrome P450s are a superfamily of heme monooxygenases which catalyze a wide range of biochemical reactions. The reactions involve the introduction of an oxygen atom into an inactivated carbon of a compound which is essential to produce an intermediate of a hydroxylated product. The diversity of chemical reactions catalyzed by cytochrome P450s has led to their increased demand in numerous industrial and biotechnology applications. A recent study showed that a gene sequence encoding a CYP was found in the genome of Bacillus lehensis G1, and this gene shared structural similarity with the bacterial vitamin D hydroxylase (Vdh) from Pseudonocardia autotrophica. The objectives of present study was to mine, for a novel CYP from a new isolate B. lehensis G1 alkaliphile and determine the biological properties and functionalities of CYP in this bacterium. Our study employed the usage of computational methods to search for the novel CYP from CYP structural databases to identify the conserved pattern, functional domain and sequence properties of the uncharacterized CYP from B. lehensis G1. A computational homology model of the protein’s structure was generated and a docking analysis was performed to provide useful structural knowledge on the enzyme’s possible substrate and their interaction. Sequence analysis indicated that the newly identified CYP, termed CYP107CB2, contained the fingerprint heme binding sequence motif FxxGxxxCxG at position 336-345 as well as other highly conserved motifs characteristic of cytochrome P450 proteins. Using docking studies, we identified Ser-79, Leu-81, Val-231, Val-279, Val-383, Ala-232, Thr-236 and Thr-283 as important active site residues capable of stabilizing interactions with several potential substrates, including vitamin D₃, 25-hydroxyvitamin D₃ and 1α-hydroxyvitamin D₃, in which all substrates docked proximally to the enzyme’s heme center. Biochemical analysis indicated that CYP107CB2 is a biologically active protein to produce 1α,25-dihydroxyvitamin D₃ from 1α-hydroxyvitamin D₃. Based on these results, we conclude that the novel CYP107CB2 identified from B. lehensis G1 is a putative vitamin D hydroxylase which is possibly capable of catalyzing the bioconversion of parental vitamin D₃ to calcitriol, or related metabolic products.     

Comparison of metabolic soft spot predictions of CYP3A4, CYP2C9 and CYP2D6 substrates using MetaSite and StarDrop

Metabolite identification study plays an important role in determining the sites of metabolic liability of new chemical entities (NCEs) in drug discovery for lead optimization. Here we compare the two predictive software, MetaSite and StarDrop, available for this purpose. They work very differently but are used to predict the site of oxidation by major human cytochrome P450 (CYP) isoforms. Neither software can predict non-CYP catalyzed metabolism nor the rates of metabolism. For the purpose of comparing the two software packages, we tested known probe substrate for these enzymes, which included 12 substrates of CYP3A4 and 18 substrates of CYP2C9 and CYP2D6 were analyzed by each software and the results were compared. It is possible that these known substrates were part of the training set but we are not aware of it. To assess the performance of each software we assigned a point system for each correct prediction. The total points assigned for each CYP isoform experimentally were compared as a percentage of the total points assigned theoretically for the first choice prediction for all substrates for each isoform. Our results show that MetaSite and StarDrop are similar in predicting the correct site of metabolism by CYP3A4 (78% vs 83%, respectively). StarDrop appears to do slightly better in predicting the correct site of metabolism by CYP2C9 and CYP2D6 metabolism (89% and 93%, respectively) compared to MetaSite (63% and 70%, respectively). The sites of metabolism (SOM) from 34 in-house NCEs incubated in human liver microsomes or human hepatocytes were also evaluated using two prediction software packages and the results showed comparable SOM predictions. What makes this comparison challenging is that the contribution of each isoform to the intrinsic clearance (Clint) is not known. Overall the software were comparable except for MetaSite performing better for CYP2D6 and that MetaSite has a liver model that is absent in StarDrop that predicted with 82% accuracy.     

Rapid genotyping of CYP2D6, CYP2C19 and TPMT polymorphisms by primer extension reaction in a dipstick format

In recent years an increasing amount of interest has been directed at the study and routine testing of polymorphisms responsible for variations in drug metabolism. Most of the current methods involve either time-consuming electrophoresis steps or specialized and expensive equipment. In this context, we have developed a rapid, simple and robust method for genotyping of CYP2D6*3, CYP2D6*4, CYP2C19*2, CYP2C19*3 and TPMT*2 single nucleotide polymorphisms (SNP). Genomic DNA is isolated from whole blood and the segments that span the SNP of interest are amplified by PCR. The products are subjected directly (without purification) to two primer extension (PEXT) reactions (three cycles each) using normal and mutant primers in the presence of biotin-dUTP. The PEXT primers contain a (dA)₃₀ segment at the 5′ end. The PEXT products are detected visually by a dry-reagent dipstick-type assay in which the biotinylated extension products are captured from immobilized streptavidin on the test zone of the strip and detected by hybridization with oligo(dT)-functionalized gold nanoparticles. Patient samples (76 variants in total) were genotyped and the results were fully concordant with those obtained by direct DNA sequencing.     

Exploration of 3D activity cliffs on the basis of compound binding modes and comparison of 2D and 3D cliffs

Activity cliffs are formed by pairs or groups of structurally similar compounds having large differences in potency and are focal points of structure-activity relationship (SAR) analysis. The choice of molecular representations is a critically important aspect of activity cliffs analysis. Thus far, activity cliffs have predominantly been defined on the basis of molecular graph or fingerprint representations. Herein we introduce 3D activity cliffs derived from comparisons of experimentally determined compound binding modes. The analysis of 3D activity cliffs is generally applicable to target proteins for which structures of multiple ligand complexes are available. For two popular targets, β-secretase 1 (BACE1) and factor Xa (FXa), public domain X-ray structures with bound inhibitors were collected. Crystallographic binding modes of inhibitors were systematically compared using a 3D similarity method taking conformational, positional, and atomic property differences into account. In addition, standard 2D similarity relationships were also determined. SAR information associated with individual compounds substantially changed when either bioactive conformations or 2D molecular graphs were used for similarity evaluation. 3D activity cliffs were identified for BACE1 and FXa inhibitor sets and systematically compared to 2D cliffs. It was found that less than 40% of 3D activity cliffs were conserved when 2D similarity was applied. The limited conservation of 3D and 2D cliffs provides further evidence for the strong molecule representation dependence of activity cliffs. Moreover, 3D cliffs represent a new class of activity cliffs that convey SAR information in ways that differ from graph-based similarity measures. In cases where sufficient structural information is available, the comparison of 3D and 2D cliffs is expected to aid in SAR analysis and mapping of critical binding determinants.     

Molecular modeling of sigma receptor ligands: A model of binding based on conformational and electrostatic considerations

We have performed molecular modeling studies on four representative sigma receptor specific ligands, (+)haloperidol, (+)3-PPP, (+)pentazocine and progesterone, to develop a model for sigma receptor-ligand binding. The modeling studies have investigated the conformational and electrostatic properties of the ligands. Based on the complementarity of the conformational and electrostatic properties of the ligands, a model of binding has been proposed which shows that the four ligands can fit a common receptor sit. Unlike the binding model for haloperidol that was previously proposed by Manallack and Andrews, our model binds haloperidol in the gauche conformation. The first site binds the fluorophenyl group and the second site the lone pair of the piperidine nitrogen. This pharmacophore can be presented by (+)3-PPP and (+)pentazocine, but for progesterone the binding model requires the ring junction of the cyclohexenyl ring A and ring B to fit the fluorophenyl region, while the lone pair of the acetylcarbonyl oxygen at ring D emulates the nitrogen lone pair of the piperidine ring. Calculations were performed using RCG5 for generating conformations, molecular mechanics for calculating steric energies, quantum mechanical methods for generating charges, and ARCHEM for calculating electrostatic potentials on the Van der Waals surface.     

Homology modeling, agonist binding site identification, and docking in octopamine receptor of Periplaneta americana

AY333178 (from Periplaneta americana, 628 AAs) was selected as a target octopamine receptor (OAR) class OAR2 for this study using Discovery Studio (DS Modeling1.1/1.2, Accelrys Inc.). Blast similarity search was performed and identified that AY333178 contains N-terminal domain of GPCR. Based upon Blast and Pfam results, Rhodopsin 1U19 (protein data bank) was considered as an ideal homologue and used as a template for homology modeling due to its higher X-ray resolution at 2.2A. Sequence alignment between AY333178 and 1U19 was done using Align123 followed by a manual modification. The final alignment was carefully evaluated and evidenced to be matching the conserved residue data for class A GPCR fairly well. The 3D model of AY333178 was generated with MODELER, and further refined using CHARMm. Superimposition of the model was done over the template 1U19. Two fairly consistent profiles were observed demonstrating AY333178 model was reasonable and could be employed for the further docking study. Agonist docking into OAR2 model was done using LigandFit. The superimposition of two top poses of representative agonists was performed with a soft surface generated. Those models are considered to be used in designing new leads for hopefully more active compounds. Further research on the comparison of models for the agonists may elucidate the mechanisms of OAR2-ligand interactions.     

Structural,magnetic and transport properties of S doping in Sr2FeMoO6 compound

The polycrystalline Sr₂FeMoO_6-xS_x (0.0 ≤ x ≤ 0.4) series were synthesized. The structure of Sr₂FeMoO_6-xS_x is assigned to tetragonal system with space group I4/mmm. The cell volume decreases with x from 0.0 to 0.3, then, increases with x from 0.3 to 0.4. S doping leads the oxygen/sulfur at 4e and 8h positions to movement away from Fe and to displacement toward Mo, respectively. The M_S at room temperature increases with degree of order of Fe and Mo ions. The electrical resistivity for studied samples exhibits a semiconductor-like behavior. The resistivity decreases with S doping. The electrical transport behavior is mainly dominated by electron-electron interactions except x = 0.4 in 0.0 magnetic field.     

On the use of neural network ensembles in QSAR and QSPR

Despite their growing popularity among neural network practitioners, ensemble methods have not been widely adopted in structure-activity and structure-property correlation. Neural networks are inherently unstable, in that small changes in the training set and/or training parameters can lead to large changes in their generalization performance. Recent research has shown that by capitalizing on the diversity of the individual models, ensemble techniques can minimize uncertainty and produce more stable and accurate predictors. In this work, we present a critical assessment of the most common ensemble technique known as bootstrap aggregation, or bagging, as applied to QSAR and QSPR. Although aggregation does offer definitive advantages, we demonstrate that bagging may not be the best possible choice and that simpler techniques such as retraining with the full sample can often produce superior results. These findings are rationalized using Krogh and Vedelsby's decomposition of the generalization error into a term that measures the average generalization performance of the individual networks and a term that measures the diversity among them. For networks that are designed to resist over-fitting, the benefits of aggregation are clear but not overwhelming.     

A novel layered supramolecular compound containing 2D network of eight-member water clusters and terephthalato extended-bridged

A novel layered supramolecular compound [Ni(L)(TPHA)]·8H₂O, containing two-dimensional (2D) water clusters and terephthalato-bridged ligand, where L = 1,3,6,9,11,14-hexaazatricyclo[12.2.1.1^6,9] octadecane, TPHA = terephthalate dianion, has been synthesized and structurally characterized by spectroscopy and X-ray crystallography. The complex is neutral, in which the nickel(II) ions are bridged by the TPHA to form a one-dimensional (1D) infinite chain structure, and containing the eight-member water cluster. The presence of octameric water clusters have effectively increased the 1D coordination polymer to a three-dimensional layered structure. Every water cluster is connected strongly by a O–H···O hydrogen bond (range of the bonds between 2.724 and 3.056 Å). The complex crystallizes in monoclinic, space group P21/c with a = 9.788(3), b = 13.030(4), c = 11.646(4) Å, and β = 104.551(5)°.