'Strain effect' descriptors for ATP and ADP derivatives with modified phosphate groups

Semiempirical AM1 calculations were carried out for quantum chemically optimized conformations of ATP and ADP and their modified phosphate derivatives with the oxygen atoms intervening between phosphorus atoms substituted by imido or methylene groups or the double-bonded oxygen atoms substituted by sulfur. In addition to the calculation of conventional geometric and energetic parameters, the effect of these substitutions was quantified in terms of conformational 'strain energy'. The latter has been defined as the energy of transformation of the parent nucleotide (ATP or ADP) from the optimum conformation to the conformation optimized for its phosphate-modified analog. The results of calculations revealed that conformational 'strain' of phosphate-modified nucleotides depends not only on the nature of the substituent but also on its position. The respective effect had the largest magnitude when the substitution was made between two terminal phosphorus atoms. Given that the 'strain energy' characterizes the geometrical aspects of the interaction of nucleotide molecules with receptors and enzymes, an attempt was made to correlate it with the corresponding biological activities. Such correlation was significant in the case of highly specific binding sites for universal ligands like ATP.     

Multiple target screening method for robust and accurate in silico ligand screening

We developed a new in silico multiple target screening (MTS) method, based on a multi-receptor versus multi-ligand docking affinity matrixes, and examined its robustness against changes in the scoring system. According to this method, compounds in a database are docked to multiple proteins. The compounds among these proteins that are likely bind to the target protein are selected as the members of the candidate-hit compound group. Then, the compounds in the group are sorted into descending order using the docking score: the first (n-th) compound is expected to be the most (n-th) probable hit compound. This method was applied to the analysis of a set of 142 receptors and 142 compounds using a receptor-ligand docking program, Sievgene [Y. Fukunishi, Y. Mikami, H. Nakamura, Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening, J. Mol. Graphics Modelling, 24 (2005) 34-45], and the results demonstrated that this method achieves a high hit ratio compared to uniform sampling. We prepared two new scores: the DeltaG score, designed to reproduce the protein-ligand binding free energy, and the hit-optimized score, designed to maximize the hit ratio of in silico screening. Using the Sievgene docking score, DeltaG score and hit-optimized score, the MTS method is more robust than the multiple active-site correction scoring method [G.P.A. Vigers, J.P. Rizzi, Multiple active site corrections for docking and virtual screening, J. Med. Chem., 47 (2004) 80-89].     

In silico identification and computational analysis of the nucleotide binding site in the C-terminal domain of Hsp90

Hsp90 contains two distinct Nucleotide Binding Sites (NBS), in its N-terminal domain (NTD) and C-terminal domain (CTD), respectively. The NTD site belongs to the GHKL super-family of ATPases and has been the subject of extensive characterization. However, a structure of the nucleotide-bound form of CTD is still unavailable. In this study molecular modeling was employed to incorporate experimental data using partial constructs of the CTD, from work published by many research groups, onto existing structural models of its apo- form. Our attempts to locate potential nucleotide ligand-binding sites or cavities yielded one major candidate—a structurally unconventional site—exhibiting the requisite shape and volume for accommodation of tri-phosphate nucleotides. Its structure was refined by molecular dynamics (MD)-based techniques. We reproducibly docked the Mg²⁺ complexed form of ATP, GTP, CTP, TTP and UTP to this putative NBS. These docking simulations and calculated ligand-binding scores are in general agreement with published data about experimentally measured binding to the CTD. The overall pattern of interactions between residues lining the site and docked nucleotides is conserved and broadly similar to that of other nucleotide-binding sites. Our docking simulations suggest that nucleotide binding stabilizes the only structurally labile region, thereby providing a rationale for the increased resistance to thermal denaturation and proteolysis. The docked nucleotides do not intrude onto the surface of residues involved in dimerization or chaperoning. Our molecular modeling permitted recognition of larger structural changes in the nucleotide-bound CTD dimer, including stabilization of helix-2 in both chains and intra- and inter- chain interactions between three residues (I613, Q617, R620).     

A theory of mode of action of azolylalkylquinolines as DNA binding agents using automated flexible ligand docking

Azolylalkylquinolines (AAQs) are a family of quinolines with varying degrees of cytotoxic activity (comparable or moderately superior to adriamycin in some cases) developed in the past decade in our group where their exact mode of action is still unclear. In this study the most probable DNA binding mode of AAQs was investigated employing a novel flexible ligand docking approach by using AutoDock 3.0. Forty-nine AAQs with known experimental inhibitory activity were docked onto d(CGCAAATTTGCG)(2), d(CGATCG)(2) and d(CGCG)(2) oligonucleotides retrieved from the Protein Data Bank (PDB IDs: 102D, 1D12 and 1D32, respectively) as the representatives of the three plausible models of interactions between chemotherapeutic agents and DNA (groove binding, groove binding plus intercalation and bisintercalation, respectively). Good correlation (r(2)=0.64) between calculated binding energies and experimental inhibitory activities was obtained using groove binding plus intercalation model for phenyl-azolylalkylquinoline (PAAQ) series. Our findings show that the most probable mode of action of PAAQs as DNA binding agents is via intercalation of quinolinic moiety between CG base pairs with linker chain and azole moiety binding to the minor groove.     

11种结合自由能评价函数对中草药中法尼酯受体的配体预测比较

以蛋白质晶体结构数据库PDB中FX-fexaramine复合物(PDB代码:1OSH)三维结构为研究对象,采用Ligandfit作为采样工具,筛选到中草药中12个可能与FXR相互作用强的的配体。并比较了11种结合自由能评价函数(Ligscorel、Lig- score2、D-Score、-PLP1、-PLP2、Jain、-PMF、Ludil、Ludi2、Ludi3,以及共同评价函数)在该研究体系中的预测能力。结果表明将评价函数中的-PLP1和-PLP1这2种评价函数的预测能力最好。     

Can human allergy drug fexofenadine,an antagonist of histamine (H1) receptor,be used to treat dog and cat? Homology modeling,docking and molecular dynamic Simulation of three H1 receptors in complex with fexofenadine

Fexofenadine, a potent antagonist to human histamine 1 (H₁) receptor, is a non-sedative third generation antihistamine that is widely used to treat various human allergic conditions such as allergic rhinitis, conjunctivitis and atopic dermatitis. Encouragingly, it’s been successfully used to treat canine atopic dermatitis, this supports the notion that it might have a great potential for treating other canine allergic conditions and other mammal pets such as dog. Regrettably, while there is a myriad of studies conducted on the interactions of antihistamines with human H₁ receptor, the similar studies on non-human pet H₁ are considerably scarce. The published studies using the first and second generation antihistamines drugs have shown that the antihistamine response is varied and unpredictable. Thus, to probe its efficacy on pet, the homology models of dog and cat H₁ receptors were built based on the crystal structure of human H₁ receptor bound to antagonist doxepin (PDB 3RZE) and fexofenadine was subsequently docked to human, dog and cat H₁ receptors. The docked complexes are then subjected to 1000 ns molecular dynamics (MD) simulations with explicit membrane. Our calculated MM/GBSA binding energies indicated that fexofenadine binds comparably to the three receptors; and our MD data also showed the binding poses, structural and dynamic features among three receptors are very similar. Therefore, our data supported the application of fexofenadine to the H₁ related allergic conditions of dog and cat. Nonetheless, subtle systemic differences among human, dog and cat H₁ receptors were also identified. Clearly, there is still a space to develop a more selective, potent and safe antihistamine alternatives such as Fexofenadine for dog or cat based on these differences. Our computation approach might provide a fast and economic way to predict if human antihistamine drugs can also be safely and efficaciously administered to animals.     

Combining docking, scoring and molecular field analyses to probe influenza neuraminidase-ligand interactions

In this project, several docking conditions, scoring functions and corresponding protein-aligned molecular field analysis (CoMFA) models were evaluated for a diverse set of neuraminidase (NA) inhibitors. To this end, a group of inhibitors were docked into the active site of NA. The docked structures were utilized to construct a corresponding protein-aligned CoMFA models by employing probe-based (H+, OH, CH3) energy grids and genetic partial least squares (G/PLS) statistical analysis. A total of 16 different docking configurations were evaluated, of which some succeeded in producing self-consistent and predictive CoMFA models. However, the best model coincided with docking the ionized ligands into the hydrated form of the binding site via PLP1 scoring function (r2LOO=0.735, r2PRESS against 24 test compounds=0.828). The highest-ranking CoMFA models were employed to probe NA-ligand interactions. Further validation by comparison with a co-crystallized ligand-NA crystallographic structure was performed. This combination of docking/scoring/CoMFA modeling provided interesting insights into the binding of different NA inhibitors.     

Homology models of the mutated EGFR and their response towards quinazoline analogues

One of the most intensely studied tyrosine kinases is the epidermal growth factor receptor (EGFR). The tyrosine kinase receptors are known to be over expressed in some solid tumors and non-small cell lung cancers, causing differential susceptibility to the quinazoline inhibitors. In this study we have taken SYK tyrosine kinase coordinates from PDB database to model two new EGFR receptors with these mutations G695S and L834R and conducted all the docking studies of the inhibitors, also evaluated these two models for quality of structure using PROCHECK. Seven quinazoline analogues (gefitinib, erlotinib, CI-1033, and EKB-569 and other analogues) were selected for comparisons among the two new models. This study determined the receptor/inhibitor interactions, at that active domain binding sites consisting of 15 amino acids. We were able to calculate the energy data for each of the seven inhibitors. This data has been important in interpreting the affinity between the inhibitors evaluated against the three models of EGFR (wild-type and two mutated types). "Affinity"-based studies have indicated the order of response based on docking energy levels (Van der Waals and electrostatic interactions). The active ATP binding sites consisting of 15 amino acid residues were identified and the total energy (E(total)) which showed the affinity between the inhibitor molecules and the receptor (Van der Waals and electrostatic interactions). The selection of the quinazoline analogues was purely on their emergence as possible candidates in the drug discovery areas. This study describes the successful application of these models that we constructed for molecular docking studies to rationally design compounds predicted to bind favorably to the modeled EGFR catalytic sites.     

P1 and P1′ para-fluoro phenyl groups show enhanced binding and favorable predicted pharmacological properties: Structure-based virtual screening of extended lopinavir analogs against multi-drug resistant HIV-1 protease

Crystal structure of multidrug-resistant (MDR) clinical isolate 769, human immunodeficiency virus type-1 (HIV-1) protease in complex with lopinavir (LPV) (PDB ID: 1RV7) showed altered binding orientation of LPV in the expanded active site cavity, causing loss of contacts and decrease in potency. In the current study, with a goal to restore the lost contacts, three libraries of LPV analogs containing extended P1 and/or P1′ phenyl groups were designed and docked into the expanded active site cavity of the MDR769 HIV-1 protease. The compounds were then ranked based on three criteria: binding affinity, overall binding profile and predicted pharmacological properties. Among the twelve proposed extensions in different combinations, compound 14 (consists of para-fluoro phenyl group as both P1 and P1′ moieties) was identified as a lead with improved binding profile, binding affinity against the MDR protease and favorable predicted pharmacological properties comparable to those of LPV. The binding affinity of 14 against wild type (NL4-3) HIV-1 protease was comparable to that of LPV and was better than LPV against an ensemble of MDR HIV-1 protease variants. Thus, 14 shows enhanced binding affinity by restoring lost contacts in the expanded active site cavity of MDR769 HIV-1 protease variants suggesting that it may have higher potency compared to that of LPV and hence should be further synthesized and evaluated against NL4-3 as well as MDR variants of HIV-1.     

Molecular recognition in the sphingosine 1-phosphate receptor family

Computational modeling and its application in ligand screening and ligand receptor interaction studies play important roles in structure-based drug design. A series of sphingosine 1-phosphate (S1P) receptor ligands with varying potencies and receptor selectivities were docked into homology models of the S1P(1-5) receptors. These studies provided molecular insights into pharmacological trends both across the receptor family as well as at single receptors. This study identifies ligand recognition features that generalize across the S1P receptor family, features unique to the S1P(4) and S1P(5) receptors, and suggests significant structural differences of the S1P(2) receptor. Docking results reveal a previously unknown sulfur-aromatic interaction between the S1P(4) C5.44 sulfur atom and the phenyl ring of benzimidazole as well as pi-pi interaction between F3.33 of S1P(1,4,5) and aromatic ligands. The findings not only confirm the importance of a cation-pi interaction between W4.64 and the ammonium of S1P at S1P(4) but also predict the same interaction at S1P(5). S1P receptor models are validated for pharmacophore development including database mining and new ligand discovery and serve as tools for ligand optimization to improve potency and selectivity.     

Scalability of parallel spatial direct numerical simulations on intel hypercube and IBM SP1 and SP2

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube and IBM SP1 and SP2 parallel computers is documented. Spatially evolving disturbances associated with laminar-to-turbulent transition in boundary-layer flows are computed with the PSDNS code. The feasibility of using the PSDNS to perform transition studies on these computers is examined. The results indicate that PSDNS approach can effectively be parallelized on a distributed-memory parallel machine by remapping the distributed data structure during the course of the calculation. Scalability information is provided to estimate computational costs to match the actual costs relative to changes in the number of grid points. By increasing the number of processors, slower than linear speedups are achieved with optimized (machine-dependent library) routines. This slower than linear speedup results because the computational cost is dominated by FFT routine, which yields less than ideal speedups. By using appropriate compile options and optimized library routines on the SP1, the serial code achieves 52–56 Mflops on a single node of the SP1 (45 percent of theoretical peak performance). The actual performance of the PSDNS code on the SP1 is evaluated with a real world simulation that consists of 1.7 million grid points. One time step of this simulation is calculated on eight nodes of the SP1 in the same time as required by a Cray Y/MP supercomputer. For the same simulation, 32-nodes of the SP1 and SP2 are required to reach the performance of a Cray C-90. A 32 node SP1 (SP2) configuration is 2.9 (4.6) times faster than a Cray Y/MP for this simulation, while the hypercube is roughly 2 times slower than the Y/MP for this application.     

整合药效团的分子对接方法研究

通过对计算机药物虚拟筛选技术、Dock评分函数体系和PocketV.2评分方法的分析,研究Dock评分函数体系及其源代码、PocketV.2评分方法及其源代码,提出基于药效团的计算机药物虚拟筛选方法。利用模拟配体与受体真实相互作用的分子间距离及性质的点模式匹配算法,实现了基于药效团的计算机药物虚拟筛选。在超性能计算集群环境下运行,并对该算法进行了测试,结果表明具有较强的可靠性和较高的准确性。     

Analysis of CYP2D6 substrate interactions by computational methods

Cytochrome P450 CYP2D6 is involved in the oxidation of well over 150 drugs and, in general, those which contain a basic nitrogen atom in the molecule. To clarify how the residues of CYP2D6 are utilized for orientating a wide range of its specific substrates and distinguishing them from a variety of other organic compounds, docking studies by AutoDock and molecular dynamics (MD) simulations were conducted. Specific ligands were docked to both the homology model and crystal structures optimally to estimate the site of reaction on the ligand molecule and the binding energy for the complex, which were generally in good agreement with the experimental data. MD simulation for the CYP2D6-propranolol complex was then carried out to reveal the amino acid residues interacting with the substrate at the active site. Phe-120, Glu-216, Asp-301, and Phe-483 are identified as the substrate-binding residues in agreement with previously reported site-directed mutagenesis data and the crystal structure reported recently (PDB code: 2F9Q). As well as these residues, our theoretical prediction suggests that Phe-219 and Glu-222 are also important residues for mediating oxidation of substrates, especially propranolol.     

Smoother and Bayesian filter based semi-codeless tracking of dual-frequency GPS signals

The orbit of the Shenzhou IV unmanned spacecraft has been observed four times by jointly using single-frequency GPS receiver, SLR and USB since its successful launch on Dec. 30, 2002. The radial accuracy of orbit determination was better than 2 m[1]. We t…     

Exploring putative inhibitors of Death Associated Protein Kinase 1 (DAPK1) via targeting Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN) substrate recognition motifs

Recently, a new signaling complex Death Associated Protein Kinase 1 (DAPK1) ̶ N-methyl-D-aspartate receptor subtype 2B (NMDAR2B or NR2B) engaged in the neuronal death cascade was identified and it was found that after stroke injury, N-methyl-D-aspartate glutamate (NMDA) receptors interact with DAPK1 through NR2B subunit and lead to excitotoxicity via over-activation of NMDA receptors. An acute brain injury, such as stroke, is a serious life-threatening medical condition which occurs due to poor blood supply to the brain and further leads to neuronal cell death. During a stroke, activated DAPK1 migrates towards the extra-synaptic site and binds to NR2B subunit of NMDA receptor. It is this DAPK1-NR2B interaction that arbitrates the pathological processes like apoptosis, necrosis, and autophagy of neuronal cells observed in stroke injury, hence we aimed to inhibit this vital interaction to prevent neuronal damage. In the present study, using PubChem database, we applied an integrative approach of virtual screening and molecular dynamic simulations and identified a potential lead compound 11 that interrupts DAPK1-NR2B interaction by competing with both ATP and substrate for their binding sites on DAPK1. This inhibitor was found potent and considerably selective to DAPK1 as it made direct contact with the ATP binding sites as well as substrate recognition motifs: Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN). Further in vitro and in vivo experiments are demanded to validate the efficacy of compound 11 nevertheless, it can be considered as suitable starting point for designing DAPK1 inhibitors.     

Molecular recognition in the sphingosine 1-phosphate receptor family

Computational modeling and its application in ligand screening and ligand receptor interaction studies play important roles in structure-based drug design. A series of sphingosine 1-phosphate (S1P) receptor ligands with varying potencies and receptor selectivities were docked into homology models of the S1P_1–5 receptors. These studies provided molecular insights into pharmacological trends both across the receptor family as well as at single receptors. This study identifies ligand recognition features that generalize across the S1P receptor family, features unique to the S1P₄ and S1P₅ receptors, and suggests significant structural differences of the S1P₂ receptor. Docking results reveal a previously unknown sulfur–aromatic interaction between the S1P₄ C5.44 sulfur atom and the phenyl ring of benzimidazole as well as π–π interaction between F3.33 of S1P_1,4,5 and aromatic ligands. The findings not only confirm the importance of a cation–π interaction between W4.64 and the ammonium of S1P at S1P₄ but also predict the same interaction at S1P₅. S1P receptor models are validated for pharmacophore development including database mining and new ligand discovery and serve as tools for ligand optimization to improve potency and selectivity.     

Ambiguities in Incremental Line Rastering

In implmenting rater grahic algorithms, it is impotant to toroughly understand behavior and implicit defaults inherent in each algorithm. Design choices must balance performance with respect to drawing speed, circult count, code space, picture fidelity, system complexity, and system consistency. For example, "close" may sound appealing when describing the match of the rastered representation to a geometirc line. An implementation, however, must quantily an error metric?such as minimum normal distance between candidate raster grid points and the geometric line?and resolve "ties" in which two candidate grid points have an equal error metric. Equal error metric ambiguity can permit algorithimic selection of raster points for a line from (X0, Y0) to (X1, Y1) to differ from points selected rastering the same line back from (X1, Y1) to (X0, Y0). Modilying a rastering algorithm to provide an exactly reversibie path, though, will cause problems when lines are rastered in a context of approximating a circle with a polygon. Only by fully understanding any algorithm can designers determine whether such pel-level anomalies are worth the code space or circuit count necessary to provide explicit user resolution, or whether a fixed default must suffice. This article discusses implementation considerations relevant to selecting and customizing incremental line-drawing algorithms to cope with such anomalies as equal error metric instances, perturbation effects of clipping, interesections in raster space, EXOR interpretations for polylines, reversibility, and fractional endpoint rounding.     

Structural determinants of the alpha2 adrenoceptor subtype selectivity

Alpha2-adrenergic receptor (α2-AR) subtypes, acting mainly on the central nervous and cardiovascular systems, represent important targets for drug design, confirmed by the high number of studies published so far. Presently, only a few α2-AR subtype selective compounds are known. Using homology modeling and ligand docking, the present study analyzes the similarities and differences between binding sites, and between extracellular loops of the three subtypes of α2-ARs. Several α2-AR subtype selective ligands were docked into the active sites of the three α2-AR subtypes, key interactions between ligands and receptors were mapped, and the predicted results were compared with the available experimental data. Binding site analysis reveals a strong identity between important amino acid residues in each receptor, the very few differences being the key toward modulating selectivity of α2-AR ligands. The observed differences between binding site residues provide an excellent starting point for virtual screening of chemical databases, in order to identify potentially selective ligands for α2-ARs.