Design and synthesis of N-terminal cyclic motilin partial peptides: a novel pure motilin antagonist

Motilin antagonist was designed and synthesized on the basis of the structure-activity relationship analysis of porcine motilin that we reported recently. The drug design was performed on a specific concept to reduce a flexibility of peptide conformation of porcine motilin partial peptide by its cyclization. The cyclic peptide was synthesized using Boc (tert-butyloxycarbonyl) solid phase methodology, followed by cyclization using the azide procedure, and tested for the binding activity to motilin receptor and smooth muscle contractile activity. The cyclic peptides 3, 4, and 5 showed antagonistic property on contraction assay (pA2 [the negative logarithm of molar concentration of antagonist causing a 2-hold shift to the right of the concentration-response curve for motilin]: 4.5, 4.34, and 4.04, respectively, in rabbit duodenum) and no contractile activity even at high concentration.     

Assessing how well a modeling protocol captures a structure-activity landscape

We introduce the notion of structure-activity landscape index (SALI) curves as a way to assess a model and a modeling protocol, applied to structure-activity relationships. We start from our earlier work [ J. Chem. Inf. Model., 2008, 48, 646-658], where we show how to study a structure-activity relationship pairwise, based on the notion of "activity cliffs"-pairs of molecules that are structurally similar but have large differences in activity. There, we also introduced the SALI parameter, which allows one to identify cliffs easily, and which allows one to represent a structure-activity relationship as a graph. This graph orders every pair of molecules by their activity. Here, we introduce the new idea of a SALI curve, which tallies how many of these orderings a model is able to predict. Empirically, testing these SALI curves against a variety of models, ranging over two-dimensional quantitative structure-activity relationship (2D-QSAR), three-dimensional quantitative structure-activity relationship (3D-QSAR), and structure-based design models, the utility of a model seems to correspond to characteristics of these curves. In particular, the integral of these curves, denoted as SCI and being a number ranging from -1.0 to 1.0, approaches a value of 1.0 for two literature models, which are both known to be prospectively useful.     

Structure-activity relationship of Ca2+ channel blockers: A study using conformational analysis and chemometric methods

Summary A structure-activity relationship study has been done on 8 compounds with the activity known as Ca²⁺ channel blockers. Conformational analysis was carried out using a molecular mechanics method. The 3D-QSAR approach was used and the most polar functional groups present in all the molecules were considered. Eight interatomic distances are necessary to define the relative spatial disposition of these relevant molecular fragments. The structure-activity relationship between interatomic distances and biological activity was performed using statistic and chemometric methods. In particular, with Principal Component Analysis, it was possible to reduce the number of interatomic distances: only six of the eight distances are sufficient to describe the system in a useful way. A classification method was iteratively used to select the most probable conformations linked to the biological activity and to build a model able to classify conformations according to their biological behaviour. Cluster analysis on the active selected conformations subsequently allowed the identification of two different geometrical patterns for the active compounds. Finally the validity of the model was verified by correctly predicting the activity of other molecules not used in the construction of the model but possessing known activity.     

A 3D QSAR approach to the search for geometrical similarity in a series of nonpeptide angiotensin II receptor antagonists

Summary A 3D QSAR methodology based on the combined use of conformational analysis and chemometrics was applied to perform a comparative analysis of the 3D conformational features of 13 nonpeptide angiotensin II receptor antagonists showing different levels of binding affinity. Conformational analysis by using a molecular mechanics MM2 method was carried out for each of these structures to obtain conformational minima. These minima were described by ten interatomic distances which define the relative spatial disposition of five significant atoms belonging to relevant functional groups present in all the 13 molecules. The structure-activity relationship between the interatomic distances and the biological activity was then assessed by using chemometric methods (cluster analysis, principal component analysis, classification methods). With our indirect approach based on the search for geometrical similarity it was possible, even though structural information on the receptor active site was lacking, to identify the 3D geometrical requirements for the binding affinity of nonpeptide angiotensin II receptor inhibitors.     

Studies on a Series of Coumarin Derivatives for Anticancer Activity against Breast Carcinoma Cell Line MCF-7 and Their Molecular Design

Breast cancer is one of the most common malignant tumors in women, and is also the focus of researchers. In this article, 3D-QSAR(three-dimensional quantitative structure-activity relationship) was performed on 24 molecules which are a series of coumarin derivatives for their anticancer activity. Our team divided these compounds randomly into the training and test sets to build the CoMFA(comparative molecular field analysis) and CoMSIA(comparative molecular similarity index analysis) models. The coefficients of cross-validation Q~2 and non cross-validation R~2 for CoMFA model were 0.684 and 0.949, and 0.579 and 0.930 for the CoMSIA model, respectively. The result demonstrates that the model has strong stability and satisfactory predictability. 3D contour maps suggest that the electrostatic factor has the greatest impact on activity followed by the H-bonding acceptor and hydrophilic factors. Taking the above results into account, we designed several molecules with high anticancer activity against breast carcinoma cell line MCF-7.     

Spectroscopic QSAR methods and self-organizing molecular field analysis for relating molecular structure and estrogenic activity

The performance of three "spectroscopic" quantitative structure-activity relationship (QSAR) methods (eigenvalue (EVA), electronic eigenvalue (EEVA), and comparative spectra analysis (CoSA)) for relating molecular structure and estrogenic activity are critically evaluated. The methods were tested with respect to the relative binding affinities (RBA) of a diverse set of 36 estrogens previously examined in detail by the comparative molecular field analysis method. The CoSA method with (13)C chemical shifts appears to provide a predictive QSAR model for this data set. EEVA (i.e., molecular orbital energy in this context) is a borderline case, whereas the performances of EVA (i.e., vibrational normal mode) and CoSA with (1)H shifts are substandard and only semiquantitative. The CoSA method with (13)C chemical shifts provides an alternative and supplement to conventional 3D QSAR methods for rationalizing and predicting the estrogenic activity of molecules. If CoSA is to be applied to large data sets, however, it is desirable that the chemical shifts are available from common databases or, alternatively, that they can be estimated with sufficient accuracy using fast prediction schemes. Calculations of NMR chemical shifts by quantum mechanical methods, as in this case study, seem to be too time-consuming at this moment, but the situation is changing rapidly. An inherent shortcoming common to all spectroscopic QSAR methods is that they cannot take the chirality of molecules into account, at least as formulated at present. Moreover, the symmetry of molecules may cause additional problems. There are three pairs of enantiomers and nine symmetric (C(2) or C(2)(v)) molecules present in the data set, so that the predictive ability of full 3D QSAR methods is expected to be better than that of spectroscopic methods. This is demonstrated with SOMFA (self-organizing molecular field analysis). In general, the use of external test sets with randomized data is encouraged as a validation tool in QSAR studies.     

Design,synthesis and bioactivity of novel herbicides targeted ALS (VII): Quantitative structure-activity relationships of herbicidal sulfonylureas

The quantitative relationship between the structures of 20 sulfonylureas and their herbicidal activities against rape was analyzed using physicochemical parameters and regression analysis. The results showed that the electronic properties of the molecules are the dominant factor to the activity and there is apparently an optimum electronic property (Σs? or pK_a) for the molecules to fit the receptor. Combined with the preview QSAR results for herbicidal triazolopyrimidine-2-sulfonamides, we can conclude that the structure-activity relationships of these two sets of compounds are identical, which suggested that these two sets of compounds acted on the same target site.     

维生素E类化合物抗氧化活性的理论分析

用半径验方法AM1,对12种维生素E类化合物及2种单酚与羟基自由基反应的活化能、氧氢键离解能D进行了计算。发现Ea、D越低,其抗氧化活性愈高;Ea、D与化合物分子中芳环上烷基取代基的数目、种类及位置有关;14个化合物的反应活化能均小于56kJ·mol-1;从反应物到过渡态氧原子上的净电荷减少。     

一类新型N型钙通道阻滞剂的比较定量构效关系研究

使用结构和量子化学参数对一系列N取代N-甲基二肽衍生物的N型钙通道阻滞活性进行了定量构效关系研究, 并使用SOMFA方法建立了三维定量构效关系模型. 结果表明分子的范德华体积和最低未占据轨道能量是影响化合物生物活性的主要因素. N原子上取代基的溶剂可及面积也对化合物的钙通道阻滞活性有重要影响. 三维定量构效关系模型进一步支持了以上结果. 这些研究结果可为设计更高活性的N型钙通道阻滞剂提供有价值的参考信息.     

Structure-activity study of intact porcine motilin

Biologically important sites on intact porcine motilin (pMTL) were explored using its partial peptides. The partial peptides were synthesized using Fmoc (9-fluorenylmethyloxycarbonyl) solid phase methodology, and tested for the binding activity to motilin receptor and the smooth muscle contractile activity. The results were as follows: important residues for the contractile activity were found to be Phe1, Ile4, and Tyr7, and an open space existed beyond the N-terminus between motilin and its receptor. On the model of interaction between motilin and motilin receptor evolved from these results, the three points of interaction, due to Phe1, Ile4, and Tyr7, and the presence of an open space were expected. The motilin agonist and antagonist, designed on this model, will help the inquiry into motilin associated diseases.     

Development of a quantitative structure-activity relationship model for inhibition of gram-positive bacterial cell growth by biarylamides

A set of compounds consisting of a new and diverse collection of biarylamides was examined using quantitative structure-activity relationship techniques for the purpose of developing a model to describe inhibition of gram-positive bacterial growth (minimum inhibition concentration). The model was sought in order to obtain insight for designing new molecules. A detailed analysis of the underlying structure-activity relationship helped provide insight concerning which structural features of the molecules modulated the activity of the compounds against gram-positive organisms.     

Molecular Property eXplorer: a novel approach to visualizing SAR using tree-maps and heatmaps

The tremendous increase in chemical structure and biological activity data brought about through combinatorial chemistry and high-throughput screening technologies has created the need for sophisticated graphical tools for visualizing and exploring structure-activity data. Visualization plays an important role in exploring and understanding relationships within such multidimensional data sets. Many chemoinformatics software applications apply standard clustering techniques to organize structure-activity data, but they differ significantly in their approaches to visualizing clustered data. Molecular Property eXplorer (MPX) is unique in its presentation of clustered data in the form of heatmaps and tree-maps. MPX employs agglomerative hierarchical clustering to organize data on the basis of the similarity between 2D chemical structures or similarity across a predefined profile of biological assay values. Visualization of hierarchical clusters as tree-maps and heatmaps provides simultaneous representation of cluster members along with their associated assay values. Tree-maps convey both the spatial relationship among cluster members and the value of a single property (activity) associated with each member. Heatmaps provide visualization of the cluster members across an activity profile. Unlike a tree-map, however, a heatmap does not convey the spatial relationship between cluster members. MPX seamlessly integrates tree-maps and heatmaps to represent multidimensional structure-activity data in a visually intuitive manner. In addition, MPX provides tools for clustering data on the basis of chemical structure or activity profile, displaying 2D chemical structures, and querying the data based over a specified activity range, or set of chemical structure criteria (e.g., Tanimoto similarity, substructure match, and "R-group" analysis).     

Design of 5H-pyrrolo[2,3-b]pyrazine-2-phenyl Ether Derivatives as Potential JAK3 Inhibitor Based on Surflex Docking,3D-QSAR Modeling and Reverse Docking

Tyrosine protein kinase JAK3 has a very important significance on organ transplantation and the treatment of autoimmune diseases, which has been a potential therapeutic target. In recent years, a large number of JAK3 inhibitors have been reported. However, the poor selectivity and side effects have limited their widespread use in clinical practice. In order to solve this problem, 52 potential small-molecule inhibitors were combined with JAK1, JAK2 and JAK3 respectively to obtain the optimal conformation of small molecules. On the basis of that we established 3D quantitative structure-activity relationships(3D-QSAR) model. Comparative molecular field analysis(Co MFA) and molecular similarity analysis(Co MSIA) were used to evaluate the model. We took advantage of reverse docking to explore the underlying toxicity and side effects. Combining 3D quantitative structure-activity relationships, surflex-dock and reverse docking results, ten 5 H-pyrrolo[2,3-b]pyrazine-2-phenyl ether derivatives based on the most optimal selectivity and activity compound 39 were designed. It can be seen from Co MFA and Co MSIA predicted active values of designed molecules that the selectivity of designed small molecules was improved obviously. Among them, compounds 61 and 62 could become the potential small molecule compounds.     

Soft agonist receptor interactions: Theoretical and experimental simulation of the active site of the receptor of sweet molecules

The structure-activity relationship of sweet molecules is chosen as an example to illustrate a mechanistic approach of soft agonist-receptor interactions. It is shown that an essentially geometric model of the receptor site can explain the activity of most sweet molecules, both rigid and flexible. The relevant conformations of flexible molecules in solution are extracted from a combination of NMR data and of energy calculations. A possible experimental simulation of the receptor environment in solution is illustrated by the complex of a dipeptide sweetener with a crown-ether.     

Molecular field analysis and 3D-quantitative structure-activity relationship study (MFA 3D-QSAR) unveil novel features of bile acid recognition at TGR5

Bile acids regulate nongenomic actions through the activation of TGR5, a membrane receptor that is G protein-coupled to the induction of adenylate cyclase. In this work, a training set of 43 bile acid derivatives is used to develop a molecular interaction field analysis (MFA) and a 3D-quantitative structure-activity relationship study (3D-QSAR) of TGR5 agonists. The predictive ability of the resulting model is evaluated using an external set of compounds with known TGR5 activity, and six bile acid derivatives whose unknown TGR5 activity is herein assessed with in vitro luciferase assay of cAMP formation. The results show a good predictive model and indicate a statistically relevant degree of correlation between the TGR5 activity and the molecular interaction fields produced by discrete positions of the bile acid scaffold. This information is instrumental to extend on a quantitative basis the current structure-activity relationships of bile acids as TGR5 modulators and will be fruitful to design new potent and selective agonists of the receptor.     

Significance analysis and multiple pharmacophore models for differentiating P-glycoprotein substrates

P-glycoprotein (Pgp) mediated drug efflux affects the absorption, distribution, and clearance of a broad structural variety of drugs. Early assessment of the potential of compounds to interact with Pgp can aid in the selection and optimization of drug candidates. To differentiate nonsubstrates from substrates of Pgp, a robust predictive pharmacophore model was targeted in a supervised analysis of three-dimensional (3D) pharmacophores from 163 published compounds. A comprehensive set of pharmacophores has been generated from conformers of whole molecules of both substrates and nonsubstrates of P-glycoprotein. Four-point 3D pharmacophores were employed to increase the amount of shape information and resolution, including the ability to distinguish chirality. A novel algorithm of the pharmacophore-specific t-statistic was applied to the actual structure-activity data and 400 sets of artificial data (sampled by decorrelating the structure and Pgp efflux activity). The optimal size of the significant pharmacophore set was determined through this analysis. A simple classification tree using nine distinct pharmacophores was constructed to distinguish nonsubstrates from substrates of Pgp. An overall accuracy of 87.7% was achieved for the training set and 87.6% for the external independent test set. Furthermore, each of nine pharmacophores can be independently utilized as an accurate marker for potential Pgp substrates.