Modeling the binding modes of Kv1.5 potassium channel and blockers

The ultra-rapid delayed rectifier potassium current (I(Kur)), encoded by Kv1.5 gene, is the critical determinant of Phase I repolarization of action potential duration (APD). The evidences that Kv1.5 gene expresses more extensively in human atrial myocytes than in ventricle and the I(Kur) currents has not been recorded in the human ventricle, suggest Kv1.5 potassium channel as a selective target for the treatment of atrial fibrillation (AF). Recent mutagenesis studies have provided us some evidences that are useful in designing Kv1.5 blockers. In order to further evaluate these molecular biological information, the homology model of Kv1.5 potassium channel was established based on the Kv1.2 crystal structure (PDB entry: 2A79) using MODELLER 9v2 program. After the molecular dynamics refinement, the optimized homology model was assessed as a reliable structure by PROCHECK, ERRAT, WHAT-IF, PROSA2003 and DOPE graph. The results of molecular docking studies on different Kv1.5 inhibitors are in agreement with the published mutagenesis data. Based on the docking conformations, a pharmacophore model was developed by HipHop algorithm in order to probe the common features of blockers. By analyzing the results, active site architecture, certain key residues and pharmacophore common-features that are responsible for substrate specificity were identified on the Kv1.5 potassium channel, which would be very helpful in understanding the blockade mechanism of Kv1.5 potassium channel and providing insights into rational design of novel Kv1.5 blockers.     

用分子对接方法研究肝素与孕激素受体相互结合模式(英文)

用分子对接模拟软件研究了肝素与孕激素受体的相互作用。以肝素中的一糖单位作为探针对孕激素受体蛋白进行搜索,获得肝素组成单位与孕激素受体的特异性结合模式。结果发现,2-O-硫酸-α-L 艾杜糖醛酸(2-O-sulfated iduronic acid,IdoA(2S))作为肝素的核心组成单糖之一,与孕激素受体的结合能力最好。分子对接结果显示 IdoA(2S)深入到孕激素受体的 helix2 和 helix 11 所包围的结合口袋,与孕激素受体结合结构域关键残基 Asn 719 形成稳固的氢键;并与孕激素受体结合结构域的关键残基 Met 909 残基侧链近距离接触,揭示了 IdoA(2S)可能具有的孕激素受体拮抗效应的分子作用机制。本模拟实验所建立的模型能够部分解释肝素抑制孕激素依赖性乳腺癌的现象,同时推测了其相应机理。     

Development of CoMFA models of affinity and selectivity to angiotensin II type-1 and type-2 receptors

The renin-angiotensin system (RAS) is of major importance in cardiovascular and renal regulation and has been an attractive target in drug discovery for a long time. The main receptors involved in the RAS are the Angiotensin type-1 (AT(1)) and type-2 (AT(2)) receptors, which are both activated by the endogenous octapeptide angiotensin II (AngII). This study describes the development of 3D-QSAR models for AT(1) and AT(2) receptor affinity and AT(1)/AT(2) receptor selectivity using CoMFA. A data set of 244 compounds, based on the triazolinone and quinazolinone structural classes was compiled from the literature. Before CoMFA could be performed, an alignment rule for the two structural classes was defined using the pharmacophore-searching program DISCOtech. Models were validated using a test set obtained by dividing the data set into a training set and test set using hierarchical clustering, based on the CoMFA fields, AT(1)-, AT(2)-receptor affinities, and AT(1)/AT(2) selectivity values. Predictive models with good statistics could be developed both for AT(1) and AT(2) receptor affinity as well as selectivity towards these receptors.     

Computer aided comparative analysis of the binding modes of the adenosine receptor agonists for all known subtypes of adenosine receptors

Molecular models of all known subtypes (A1, A2A, A2B, and A3) of the human adenosine receptors were built in homology with bovine rhodopsin. These models include the transmembrane domain as well as all extracellular and intracellular hydrophilic loops and terminal domains. The molecular docking of adenosine and 46 selected derivatives was performed for each receptor subtype. A binding mode common for all studied agonists was proposed, and possible explanations for differences in the ligand activities were suggested.     

Modeling of self-oscillating modes of formation of oil- and gas-fields

This paper presents the results of the computational analysis of complex self-oscillating modes of motion of fluids during the formation of hydrocarbon deposits, held for a number of regions, and determination of their characteristic properties made on this basis.     

Modeling of the cage induction motor for symmetrical and asymmetrical modes of operation

This paper presents a numerical model of the three-phase, cage induction motor. This model has been represented as a system of differential equations for flux linkages and angular velocity determination. The differential equations for the flux linkages of the stator windings have been expressed in phase coordinates, while the differential equations for the flux linkages of the rotor circuits have been expressed in orthogonal coordinates, which are fixed in respect with the stator of the motor. The skin effect in the rotor deep bars has been taken in account by representing the rotor as two parallel-connected resistive–inductive circuits. Using the developed model the starting, restarting, running-down modes and three-phase, line-to-line, line-to-ground short-circuits as well as the steady-state conditions can be analyzed. The modes of sudden three-phase short-circuit at the motor terminals, sudden single line-to-ground fault at the high-voltage side of the power supply system and the motor starting process followed by steady-state conditions have been computed.     

Studying the catechol binding cavity in comparative models of human dopamine D2 receptor

Obtaining more structural information of human dopamine D(2) receptor may help in the design of better therapeutic agents against diseases such as Parkinson. In this study attempts have been made to develop a functional model for the catechol binding site of the human dopamine D(2) receptor, with two primary models being postulated based on the presence of a disulfide bridge in the second extracellular loop. The models have been subjected to subsequent molecular dynamics simulation and receptor based virtual screening of catechol structures. During steady state of the simulations, representative models with the reduced disulfide bridge were more capable of discriminating between active and inactive catechol structures. It is postulated that similar conformational changes of the second extracellular loop observed in 5-HT4 and β-adrenergic receptors, might also take place in the human D(2) receptor during its interaction with agonist ligands.     

Comparison and analysis of the structures and binding modes of antifungal SE and CYP51 inhibitors

With the abuse of clinical broad-spectrum antimicrobial agents, immunosuppressive agents, chemotherapy drugs, the emergence of pathogenic fungi resistance is more and more frequent. However, there is still no effective treatment for the fungal resistance. Squalenee epoxidase (SE) and 14 α-demethylase (CYP51) are important antifungal drug targets. In order to achieve a deeper insight into the structural characteristics and the action modes of SE and CYP51inhibitors, the homology model of SE (Candida albicans) was constructed using monooxygenase of Pseudomonas aeruginosa as template, and the reliability of model was confirmed by Ramachandran plots and Verify 3D. Subsequently, the molecular superimposition and molecular docking were performed, and the pharmacophore model based on the CYP51 receptor structure was constructed. The results indicate that SE and CYP51 inhibitors have common structural feature with two parts of essential fragments, which are mainly composed of aromatic groups. In addition, the fragment structures of inhibitors are combined in the similar hydrophobic pockets through the hydrophobic forces. The present study provides a deeper perspective to understand the characteristics and docking modes of SE and CYP51 inhibitors. It can be used to guide the optimization and design of SE and CYP51 inhibitors. In addition, it also provides the oretical support for the development of dual target antifungal inhibitors (SE and CYP51), which can help us solve the problem of fungi resistance.     

Analysis and control of the jump modes behavior of 2-D singular systems—Part II: Regular observer and compensator design

This paper considers the problems of regular observer and compensator design for 2-D acceptable singular systems. First, the notions of jump mode reconstructability and jump mode reachability for 2-D acceptable singular systems are proposed. Necessary and sufficient conditions are presented for the jump mode reconstructability and reachability, respectively. Then, we show that there exists a reduced order regular observer for a 2-D acceptable singular system if the system is detectable and jump mode reconstructable, while there exists a reduced order regular compensator for a 2-D acceptable singular system if the system is stabilizable and jump mode reachable.     

Modeling of high-affinity binding of the novel atrial anti-arrhythmic agent, vernakalant, to Kv1.5 channels

Vernakalant (RSD1235) is an investigational drug that converts atrial fibrillation rapidly and safely in patients intravenously [Roy et al., J. Am. Coll. Cardiol. 44 (2004) 2355–2361; Roy et al., Circulation 117 (2008) 1518–1525] and maintains sinus rhythm when given orally [Savelieva et al., Europace 10 (2008) 647–665]. Here, modeling using AutoDock4 allowed exploration of potential binding modes of vernakalant to the open-state of the Kv1.5 channel structure. Point mutations were made in the channel model based on earlier patch-clamp studies [Eldstrom et al., Mol. Pharmacol. 72 (2007) 1522–1534] and the docking simulations re-run to evaluate the ability of the docking software to predict changes in drug–channel interactions. Each AutoDock run predicted a binding conformation with an associated value for free energy of binding (FEB) in kcal/mol and an estimated inhibitory concentration (K_i). The most favored conformation had a FEB of −7.12 kcal/mol and a predicted K_i of 6.08 μM (the IC50 for vernakalant is 13.8 μM; [Eldstrom et al., Mol. Pharmacol. 72 (2007) 1522–1534]). This conformation makes contact with all four T480 residues and appears to be clearly positioned to block the channel pore.     

Shape-From-Silhouette Across Time Part II: Applications to Human Modeling and Markerless Motion Tracking

In Part I of this paper we developed the theory and algorithms for performing Shape-From-Silhouette (SFS) across time. In this second part, we show how our temporal SFS algorithms can be used in the applications of human modeling and markerless motion tracking. First we build a system to acquire human kinematic models consisting of precise shape (constructed using the temporal SFS algorithm for rigid objects), joint locations, and body part segmentation (estimated using the temporal SFS algorithm for articulated objects). Once the kinematic models have been built, we show how they can be used to track the motion of the person in new video sequences. This marker-less tracking algorithm is based on the Visual Hull alignment algorithm used in both temporal SFS algorithms and utilizes both geometric (silhouette) and photometric (color) information.Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

Modeling of flux,binding and substitution of urea molecules in the urea transporter dvUT

Urea transporters (UTs) are transmembrane proteins that transport urea molecules across cell membranes and play a crucial role in urea excretion and water balance. Modeling the functional characteristics of UTs helps us understand how their structures accomplish the functions at the atomic level, and facilitates future therapeutic design targeting the UTs. This study was based on the crystal structure of Desulfovibrio vulgaris urea transporter (dvUT). To model the binding behavior of urea molecules in dvUT, we constructed a cooperative binding model. To model the substitution of urea by the urea analogue N,N′-dimethylurea (DMU) in dvUT, we calculated the occupation probability of DMU along the urea pore and the ratio of the occupation probabilities of DMU at the external (S_ext) and internal (S_int) binding sites, and we established the mutual substitution rule for binding and substitution of urea and DMU. Based on these calculations and modelings, together with the use of the Monte Carlo (MC) method, we further modeled the urea flux in dvUT, equilibrium urea binding to dvUT, and the substitution of urea by DMU in the dvUT. Our modeling results are in good agreement with the existing experimental functional data. Furthermore, the modelings have discovered the microscopic process and mechanisms of those functional characteristics. The methods and the results would help our future understanding of the underlying mechanisms of the diseases associated with impaired UT functions and rational drug design for the treatment of these diseases.     

雄激素受体干扰物的活性预测模型的研究

目的在于定量预测雄激素受体干扰物活性,并确定最佳建模方法。选择150个分子作为数据集,随机选38个分子作为检验集,其它分子为训练集。每个化合物分子计算了193个分子参数。通过采用多元线性回归和主成分回归等方法,建立数学模型,并用验证集检验了所建模型的预测能力。结果发现逐步筛选法和主成分分析方法所建模型都表现出较强的预测能力(应用于检验集的相关系数分别为R=0.61,R=0.52)。以上研究将有助于新药雄激素受体抑制剂的筛选和开发。     

Prediction of the receptor conformation for iGluR2 agonist binding: QM/MM docking to an extensive conformational ensemble generated using normal mode analysis

Highly flexible proteins constitute a significant challenge in molecular docking within the field of drug design. Depending on the efficacy of the bound ligand, the ligand-binding domain (LBD) of the ionotropic glutamate receptor iGluR2 adopts markedly different degrees of domain closure due to large-scale domain movements. With the purpose of predicting the induced domain closure of five known iGluR2 partial to full agonists we performed a validation study in which normal mode analysis (NMA) was employed to generate a 25-membered ensemble of iGluR2 LBD structures with gradually changing domain closures, followed by accurate QM/MM docking to the ensemble. Based on the docking scores we were able to predict the correct optimal degree of closure for each ligand within 1–3° deviation from the experimental structures. We demonstrate that NMA is a useful tool for reliable ensemble generation and that we are able to predict the ligand induced conformational change of the receptor through docking to such an ensemble. The described protocol expands and improves the information that can be obtained from computational docking when dealing with a flexible receptor.     

Prediction of the receptor conformation for iGluR2 agonist binding: QM/MM docking to an extensive conformational ensemble generated using normal mode analysis

Highly flexible proteins constitute a significant challenge in molecular docking within the field of drug design. Depending on the efficacy of the bound ligand, the ligand-binding domain (LBD) of the ionotropic glutamate receptor iGluR2 adopts markedly different degrees of domain closure due to large-scale domain movements. With the purpose of predicting the induced domain closure of five known iGluR2 partial to full agonists we performed a validation study in which normal mode analysis (NMA) was employed to generate a 25-membered ensemble of iGluR2 LBD structures with gradually changing domain closures, followed by accurate QM/MM docking to the ensemble. Based on the docking scores we were able to predict the correct optimal degree of closure for each ligand within 1–3° deviation from the experimental structures. We demonstrate that NMA is a useful tool for reliable ensemble generation and that we are able to predict the ligand induced conformational change of the receptor through docking to such an ensemble. The described protocol expands and improves the information that can be obtained from computational docking when dealing with a flexible receptor.     

Modeling and optimization method featuring multiple operating modes for improving carbon efficiency of iron ore sintering process

Iron ore sintering is one of the most energy-consuming processes in steelmaking. Since its main source of energy is the combustion of carbon, it is important to improve the carbon efficiency to save energy and to reduce undesired emissions. A modeling and optimization method based on the characteristics of the sintering process has been developed to do that. It features multiple operating modes and employs the comprehensive carbon ratio (CCR) as a measure of carbon efficiency. The method has two parts. The first part is the modeling of multiple operating modes of the sintering process. K-means clustering is used to identify the operating modes; and for each mode, a predictive model is built that contains two submodels, one for predicting the state parameters and one for predicting the CCR. The submodels are built using back-propagation neural networks (BPNNs). An analysis of material and energy flow, and correlation analyses of process data and the CCR, are used to determine the most appropriate inputs for the submodels. The second part of the method is optimization based on a determination of the optimal operating mode. The problem of how to reduce the CCR is formulated as a two-step optimization problem, and particle swarm optimization is used to solve it. Finally, verification of the modeling and optimization method based on actual process data shows that it improves the carbon efficiency of iron ore sintering.     

New insights into the stereochemical requirements of the bradykinin B1 receptor antagonists binding

Bradykinin (BK) is a nonapeptide involved in several pathophysiological conditions including among others, septic and haemorrhagic shock, anaphylaxis, arthritis, rhinitis, asthma, inflammatory bowel disease. Accordingly, BK antagonists have long been sought after for therapeutic intervention. Action of BK is mediated through two different G-protein coupled receptors known as B1 and B2. Although there are several B1 antagonists reported in literature, their pharmacological profile is not yet optimal so that new molecules need to be discovered. In the present work we have constructed an atomistic model of the B1 receptor and docked diverse available non-peptide antagonists in order to get a deeper insight into the structure-activity relationships involving binding to this receptor. The model was constructed by homology modeling using the chemokine CXC4 and bovine rhodopsin receptors as template. The model was further refined using molecular dynamics for 600 ns with the protein embedded in a POPC bilayer. From the refinement process we obtained an average structure that was used for docking studies using the Glide software. Antagonists selected for the docking studies include Compound 11, Compound 12, Chroman28, SSR240612, NPV-SAA164 and PS020990. The results of the docking study underline the role of specific receptor residues in ligand binding. The results of this study permitted to define a pharmacophore that describes the stereochemical requirements of antagonist binding, and can be used for the discovery of new compounds.     

对等网络蠕虫建模与分析

对等网络蠕虫是威胁对等网络乃至Internet安全的一个重要问题。针对蠕虫扩散过程和对等网络拓扑的特点,构造了对等网络蠕虫传播模型;以Gnutella网络为研究实例,获取其拓扑快照数据,用以模拟蠕虫在Gnutella网络中的传播过程,从而验证模型的有效性,衡量对等网络蠕虫对P2P网络的危害。