Microfluidic bolus induced gradient generator for live cell signalling

Major events in cell biology are initiated by the binding of ligands to cell surface receptors and/or their transport into cells. We present a study of a simple microchannel system that integrates a bolus generator and surface-adhered cell culture domains. Our system allows the delivery of small packets or boluses of biomolecules to a cell population. Owing to pressure driven microfluidic flow of the bolus, a gradient of cell surface bound ligands is established along the length of the microchannel. Experimental data for the epidermal growth factor (EGF) binding to its receptor on A431 cells are presented. We highlight the effect of changing Peclet number (or flowrate), bolus shape, bolus volume and ligand concentration on the gradient formed longitudinally in the microchannel. A mathematical model describing the transient convection, diffusion, dispersion and binding of ligands to cell surface receptors is developed. The model provides essential design guidelines for our system with good qualitative agreement with experimental data. The results suggest ways to modulate the amount of bound ligand and the gradient independently. This simple microsystem is suitable for generating longer range gradients involving larger cell populations as compared to existing microfluidic systems.     

Interactive Exploration of Protein Cavities

We present a novel application for the interactive exploration of cavities within proteins in dynamic data sets. Inside a protein, cavities can often be found close to the active center. Therefore, when analyzing a molecular dynamics simulation trajectory it is of great interest to find these cavities and determine if such a cavity opens up to the environment, making the binding site accessible to the surrounding substrate. Our user‐driven approach enables expert users to select a certain cavity and track its evolution over time. The user is supported by different visualizations of the extracted cavity to facilitate the analysis. The boundary of the protein and its cavities is obtained by means of volume ray casting, where the volume is computed in real‐time for each frame, therefore allowing the examination of time‐dependent data sets. A fast, partial segmentation of the volume is applied to obtain the selected cavity and trace it over time. Domain experts found our method useful when they applied it exemplarily on two trajectories of lipases from Rhizomucor miehei and Candida antarctica. In both data sets cavities near the active center were easily identified and tracked over time until they reached the surface and formed an open substrate channel.     

TSS BVHs: Tetrahedron Swept Sphere BVHs for Ray Tracing Subdivision Surfaces

We present a novel, compact bounding volume hierarchy, TSS BVH, for ray tracing subdivision surfaces computed by the Catmull‐Clark scheme. We use Tetrahedron Swept Sphere (TSS) as a bounding volume to tightly bound limit surfaces of such subdivision surfaces given a user tolerance. Geometric coordinates defining our TSS bounding volumes are implicitly computed from the subdivided mesh via a simple vertex ordering method, and each level of our TSS BVH is associated with a single distance bound, utilizing the Catmull‐Clark scheme. These features result in a linear space complexity as a function of the tree depth, while many prior BVHs have exponential space complexity. We have tested our method against different benchmarks with path tracing and photon mapping. We found that our method achieves up to two orders of magnitude of memory reduction with a high culling ratio over the prior AABB BVH methods, when we represent models with two to four subdivision levels. Overall, our method achieves three times performance improvement thanks to these results. These results are acquired by our theorem that rigorously computes our TSS bounding volumes.     

Interaction between peroxisome proliferator-activated receptor γ and its agonists: docking study of oximes having 5-benzyl-2,4-thiazolidinedione

The molecular modelling of oximes having 5-benzyl-2,4-thiazolidinedione moieties, agonists of the peroxisome proliferator-activated receptor γ (PPARγ), was performed with respect to their structures complexed with the ligand binding domain of PPARγ. For each ligand molecule, the 5-benzyl-2,4-thiazolidinedione head group was used as an anchor and the conformation of the rest of the molecule was searched for the most energetically favorable interaction with the receptor by systematic conformation search and manual modelling. Although both tail-up and tail-down configurations, which have been observed in the crystal structure of eicosapentaenoic acid when complexed with PPARδ, appeared among the lowest energy structures for most of the compounds, potent agonists were found to adopt a configuration similar to that of rosiglitazone when bound to PPARγ, according to the crystal structure. The structure–activity relationships were analyzed based on the receptor–ligand interaction. The alkyl group and the aromatic ring of the tail group of the ligands had hydrophobic interactions with the receptor, and these interactions were found to be essential for the strong activity.     

Interaction between peroxisome proliferator-activated receptor gamma and its agonists: docking study of oximes having 5-benzyl-2,4-thiazolidinedione

The molecular modelling of oximes having 5-benzyl-2,4-thiazolidinedione moieties, agonists of the peroxisome proliferator-activated receptor gamma (PPAR gamma), was performed with respect to their structures complexed with the ligand binding domain of PPAR gamma. For each ligand molecule, the 5-benzyl-2,4-thiazolidinedione head group was used as an anchor and the conformation of the rest of the molecule was searched for the most energetically favorable interaction with the receptor by systematic conformation search and manual modelling. Although both tail-up and tail-down configurations, which have been observed in the crystal structure of eicosapentaenoic acid when complexed with PPAR delta, appeared among the lowest energy structures for most of the compounds, potent agonists were found to adopt a configuration similar to that of rosiglitazone when bound to PPAR gamma, according to the crystal structure. The structure-activity relationships were analyzed based on the receptor-ligand interaction. The alkyl group and the aromatic ring of the tail group of the ligands had hydrophobic interactions with the receptor, and these interactions were found to be essential for the strong activity.     

The interpretation of ligand displacement experiments: calculations for multisite acceptors

A method is described for calculating the degree of competition for binding between two ligands which are bound at any number of site classes on a binding protein from a generalization of the equilibrium competitive binding equations, the protein's binding parameters for each of the ligands, and the total protein and ligand concentrations. Theoretical displacement curves thus obtained for each of the possible competitive binding models with a multisite protein can then be compared with experimentally determined ligand displacements in order to find which model is most realistic or if measured displacements are due rather to negative cooperativity effects. The binding parameters used for the calculations have a statistical error attached to them, since they have been obtained experimentally, so here we also propose a method for calculating the standard deviations of the theoretical displacement curves deriving from these errors. This permits the use of statistical hypothesis testing in the comparison of theoretical and experimental results. An example is shown in which this method permits the verification that two drugs (phenylbutazone and azapropazone) are both bound by the same high- and low-affinity sites of a protein (alpha-fetoprotein).     

Design and computational support for the binding stability of a new CCR5/CXCR4 dual tropic inhibitor: Computational design of a CCR5/CXCR4 drug

The human immunodeficiency virus (HIV) infects healthy human cells by binding to the glycoprotein cluster of differentiation 4 receptors on the surface of helper T-cells, along with either of two chemokine receptors, CC chemokine receptor type 5 (CCR5) or C-X-C chemokine receptor type 4 (CXCR4). Recently, a pyrazolo-piperdine ligand was synthesized and the corresponding biological data showed good binding to both chemokine receptors, effectively blocking HIV-1 entry. Here, we exhaustively assess the atomistic binding interactions of this compound with both CCR5 and CXCR4, and we find that binding is driven by π-stacking interactions between aromatic rings on the ligand and receptor residues, as well as electrostatic interactions involving the protonated piperidine nitrogen. However, these favorable binding interactions were partially offset by unfavorable desolvation of active site glutamates and aspartates, prompting our proposal of a new, synthetically-accessible derivative designed to increase the electrostatic interactions without compromising the π-stacking features.     

Sphingosine 1-phosphate pKa and binding constants: intramolecular and intermolecular influences

The dissociation constant for an ionizable ligand binding to a receptor is dependent on its charge and therefore on its environmentally-influenced pKa value. The pKa values of sphingosine 1-phosphate (S1P) were studied computationally in the context of the wild type S1P1 receptor and the following mutants: E3.29Q, E3.29A, and K5.38A. Calculated pKa values indicate that S1P binds to S1P1 and its site mutants with a total charge of -1, including a +1 charge on the ammonium group and a -2 charge on the phosphate group. The dissociation constant of S1P binding to these receptors was studied as well. The models of wild type and mutant proteins originated from an active receptor model that was developed previously. We used ab initio RHF/6-31+G(d) to optimize our models in aqueous solution, where the solvation energy derivatives are represented by conductor-like polarizable continuum model (C-PCM) and integral equation formalism polarizable continuum model (IEF-PCM). Calculation of the dissociation constant for each mutant was determined by reference to the experimental dissociation constant of the wild type receptor. The computed dissociation constants of the E3.29Q and E3.29A mutants are three to five orders of magnitude higher than those for the wild type receptor and K5.38A mutant, indicating vital contacts between the S1P phosphate group and the carboxylate group of E3.29. Computational dissociation constants for K5.38A, E3.29A, and E3.29Q mutants were compared with experimentally determined binding and activation data. No measurable binding of S1P to the E3.29A and E3.29Q mutants was observed, supporting the critical contacts observed computationally. These results validate the quantitative accuracy of the model.     

Classification and comparison of ligand-binding sites derived from grid-mapped knowledge-based potentials

We describe the application of knowledge-based potentials implemented in the MOE program to compare the ligand-binding sites of several proteins. The binding probabilities for a polar and a hydrophobic probe are calculated on a grid to allow easy comparison of binding sites of superimposed related proteins. The method is fast and simple enough to simultaneously use structural information of multiple proteins of a target family. The method can be used to rapidly cluster proteins into subfamilies according to the similarity of hydrophobic and polar fields of their ligand-binding sites. Regions of the binding site which are common within a protein family can be identified and analysed for the design of family-targeted libraries or those which differ for improvement of ligand selectivity. The field-based hierarchical clustering is demonstrated for three protein families: the ligand-binding domains of nuclear receptors, the ATP-binding sites of protein kinases and the substrate binding sites of proteases. More detailed comparisons are presented for serine proteases of the chymotrypsin family, for the peroxisome proliferator-activated receptor subfamily of nuclear receptors and for progesterone and androgen receptor. The results are in good accordance with structure-based analysis and highlight important differences of the binding sites, which have been also described in the literature.     

Induced-fit docking of mometasone furoate and further evidence for glucocorticoid receptor 17alpha pocket flexibility

An induced-fit docking method was used to characterize the interactions of the glucocorticoid receptor binding-site with mometasone furoate, a glucocorticoid with a lipophilic ester at the C17alpha position. Two validation studies demonstrated that the protocol can reproduce crystal structures of nuclear receptors, and is appropriate for modeling ligand binding to the glucocorticoid receptor. Key hydrogen bonding interactions between mometasone furoate and the glucocorticoid receptor, as well as favorable hydrophobic interactions between the furoate group and the 17alpha pocket, contribute to high affinity and specificity of this ligand for the receptor. Using the glucocorticoid des-ciclesonide, which has an even larger moiety at the 16,17alpha position, induced-fit docking demonstrates the ability of the 17alpha pocket of the receptor to expand even further to accommodate the ligand.     

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.     

小分子配体模仿结合位点水分子: 相同配体与不同蛋白靶点之间作用模式的计算研究

在计算化学和药物设计领域中,精确预测小分子配体的蛋白质靶标是一件极具挑战性工作,特别是那些与相同小分子配体相互作用,但蛋白间并不具有显著序列或结构相似性的靶标蛋白。为了研究相同小分子配体与不相关的蛋白质靶标之间的结合特性,我们使用蛋白水合效应分析 (SPA) 程序研究了 33 对药物靶蛋白结合位点水分子的结构特性。每个蛋白对中的两个蛋白质,均由可与相同配体小分子相结合的两个不相关的蛋白质组成。通过计算两蛋白质间的水化位点替代重叠率,我们发现共有高达 73% 的蛋白对中有着显著的水分子替代重叠率值。特别是我们发现相同小分子与不同蛋白相互作用时,或许存在一种特别的“识别代码”,即小分子配体的功能基团与结合位点的水分子之间存在着较好的几何构型相似性。在无法确定小分子与蛋白相互作用模式时,可以依靠活性结合腔穴中水分子的结合构型特征,进行粗略估算与预测,对蛋白-配体相互作用模式研究有重要的实用价值。     

表面等离子体共振(SPR)生物传感器技术的进展--BIACORE J的应用

SPR 生物传感器技术正在持续发展着。瑞典 BIACORE 公司新近推出了用于生物分子间相互作用日常分析的新型号仪器,BIACORE J。应用抗体/蛋白质 A 及配位基/受体等体系进行了 BIACORE J 用于活性浓度和键合亲和力测定的考核。结果表明了仪器的高灵敏度和键合响应的重现性。该型号仪器易于操作,并可用于多种领域,SPR 技术也因而成为被广泛采用的研究工具。     

InCa-SiteFinder: A method for structure-based prediction of inositol and carbohydrate binding sites on proteins

Carbohydrate binding sites are considered important for cellular recognition and adhesion and are important targets for drug design. In this paper we present a new method called InCa-SiteFinder for predicting non-covalent inositol and carbohydrate binding sites on the surface of protein structures. It uses the van der Waals energy of a protein–probe interaction and amino acid propensities to locate and predict carbohydrate binding sites. The protein surface is searched for continuous volume envelopes that correspond to a favorable protein–probe interaction. These volumes are subsequently analyzed to demarcate regions of high cumulative propensity for binding a carbohydrate moiety based on calculated amino acid propensity scores.InCa-SiteFinder¹ was tested on an independent test set of 80 protein–ligand complexes. It efficiently identifies carbohydrate binding sites with high specificity and sensitivity. It was also tested on a second test set of 80 protein–ligand complexes containing 40 known carbohydrate binders (having 40 carbohydrate binding sites) and 40 known drug-like compound binders (having 58 known drug-like compound binding sites) for the prediction of the location of the carbohydrate binding sites and to distinguish these from the drug-like compound binding sites. At 73% sensitivity the method showed 98% specificity. Almost all of the carbohydrate and drug-like compound binding sites were correctly identified with an overall error rate of 12%.     

Die ReiheIndices Verborum zum Altdeutschen Schrifttum: Ein Forschungsbericht

TheIndices Verborum zum altdeutschen Schrifttum is a series of word indices, rhyme concordances and retrograde word lists of German medieval texts. In providing basic reference tools for these documents, the series will make much of the material written in the high and late middle Ages more readily accessible to scholars. The Indices Verborum are divided into groups of five volumes, each group supplemented by a reference volume, in which all of the word forms appearing in the preceding five volumes are listed (in both alphabetical and retrograde order) with appropriate references. Most of the work on the first group of five volumes has been completed and the first three volumes of this group have been published.      

On the structure, interactions, and dynamics of bound VEGF

The vascular endothelial growth factor (VEGF) is believed to be the most important protein in the regulation of the angiogenic cascade. Thus, exploring the structure and dynamical properties of this growth factor and the influence of receptor and inhibitor binding to these properties may reveal new insights on VEGF's biological process and inhibition opportunities. Here we describe an analysis of molecular dynamics simulations of VEGF bound to the Flt-1 receptor, VEGF bound to the v107 peptide inhibitor, and also VEGF bound to a mutant v107. We analyze the effects of binding to VEGF regarding three aspects: structure, interactions, and dynamics. We found that the structure of VEGF is not significantly perturbed upon binding. We analyze the individual contribution of the VEGF residues to the total interaction energy of binding to Flt-1 and v107. We also compare dynamical variables such as thermal fluctuations and correlations with those of the unbound form. We found that receptor binding is able to promote stronger perturbations on the VEGF dynamical behavior than VEGF inhibitor binding. VEGF motions in the receptor bound complex are shown to be less correlated than motions of unbound VEGF. The work addresses the changes on conformational flexibility of the isolated VEGF upon binding, as well as changes in structure and side-chain rearrangements.     

Molecular modeling of sigma 1 receptor ligands: a model of binding conformational and electrostatic considerations

We have performed molecular modeling studies on several sigma 1 specific ligands, including PD144418, spipethiane, haloperidol, pentazocine, and others to develop a pharmacophore for sigma 1 receptor-ligand binding, under the assumption that all the compounds interact at the same receptor binding site. The modeling studies have investigated the conformational and electrostatic properties of the ligands. Superposition of active molecules gave the coordinates of the hypothetical 5-point sigma 1 pharmacophore, as follows: R1 (0.85, 7.26, 0.30); R2 (5.47, 2.40, -1.51); R3 (-2.57, 4.82, -7.10); N (-0.71, 3.29, -6.40); carbon centroid (3.16, 4.83, -0.60), where R1, R2 were constructed onto the aromatic ring of each compound to represent hydrophobic interactions with the receptor; and R3 represents a hydrogen bond between the nitrogen atom and the receptor. Additional analyses were used to describe secondary binding sites to electronegative groups such as oxygen or sulfur atom. Those coordinates are (2.34, 5.08, -4.18). The model was verified by fitting other sigma 1 receptor ligands. This model may be used to search conformational databases for other possibly active ligands. In conjunction with rational drug design techniques the model may be useful in design and synthesis of novel sigma 1 ligands of high selectivity and potency. Calculations were performed using Sybyl 6.5.     

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.     

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.