Novel peptide-specific quantitative structure-activity relationship (QSAR) analysis applied to collagen IV peptides with antiangiogenic activity

Angiogenesis is the growth of new blood vessels from existing vasculature. Excessive vascularization is associated with a number of diseases including cancer. Antiangiogenic therapies have the potential to stunt cancer progression. Peptides derived from type IV collagen are potent inhibitors of angiogenesis. We wanted to gain a better understanding of collagen IV structure-activity relationships using a ligand-based approach. We developed novel peptide-specific QSAR models to study the activity of the peptides in endothelial cell proliferation, migration, and adhesion inhibition assays. We found that the models produced quantitatively accurate predictions of activity and provided insight into collagen IV derived peptide structure-activity relationships.     

Three-dimensional quantitative structure-activity relationship analysis of human CYP51 inhibitors.

CYP51 fulfills an essential requirement for all cells, by catalyzing three sequential mono-oxidations within the cholesterol biosynthesis cascade. Inhibition of fungal CYP51 is used as a therapy for treating fungal infections, whereas inhibition of human CYP51 has been considered as a pharmacological approach to treat dyslipidemia and some forms of cancer. To predict the interaction of inhibitors with the active site of human CYP51, a three-dimensional quantitative structure-activity relationship model was constructed. This pharmacophore model of the common structural features of CYP51 inhibitors was built using the program Catalyst from multiple inhibitors (n = 26) of recombinant human CYP51-mediated lanosterol 14alpha-demethylation. The pharmacophore, which consisted of one hydrophobe, one hydrogen bond acceptor, and two ring aromatic features, demonstrated a high correlation between observed and predicted IC(50) values (r = 0.92). Validation of this pharmacophore was performed by predicting the IC(50) of a test set of commercially available (n = 19) and CP-320626-related (n = 48) CYP51 inhibitors. Using predictions below 10 microM as a cutoff indicative of active inhibitors, 16 of 19 commercially available inhibitors (84%) and 38 of 48 CP-320626-related inhibitors (79.2%) were predicted correctly. To better understand how inhibitors fit into the enzyme, potent CYP51 inhibitors were used to build a Cerius(2) receptor surface model representing the volume of the active site. This study has demonstrated the potential for ligand-based computational pharmacophore modeling of human CYP51 and enables a high-throughput screening system for drug discovery and data base mining.     

Three-dimensional quantitative structure-activity relationship modeling of gamma-secretase inhibitors using molecular field analysis

Three-dimensional quantitative structure-activity relationship analysis of a set of 79 analogs of gamma-secretase inhibitors was performed by molecular field analysis with genetic partial least squares method to investigate the substitutional requirements to derive a predictive model and for the favorable receptor-drug interaction that may be used for the designing of a novel gamma-secretase inhibitors. The developed molecular field analysis model has a good fit, with r2 value of 0.952 and cross-validated coefficient, r2(cv), value of 0.931. Predictive ability of the developed model was further assessed using test set of 19 compounds and r2(pred) was found to be 0.665.     

A quantitative structure-activity relationship approach to the minimization of albumin binding

The binding of 2,6-disubstituted xanthones to human serum albumin (HSA) has been investigated using an ultrafiltration technique. A set of 26 compounds was chosen for study using a selection procedure aimed at minimizing the interparameter correlations, while ensuring that the physicochemical properties covered the maximum possible range of values. The magnitude of binding has been expressed as the compound concentration required to produce a specified bound concentration, in preference to equilibrium constants and number of albumin binding sites. Albumin binding was found to have a nonlinear dependence on the octanol-water partition coefficient (log P) and has been rationalized in terms of a simple binding model.     

Advances in quantitative structure-activity relationship models of antimalarials

Importance of the field: Malaria still remains one of the deadliest infectious diseases having a tremendous morbidity and mortality impact in the developing world. Computational tools such as quantitative structure-activity relationship (QSAR) studies help medicinal chemists to understand the consistent relationship between antimalarial activity and molecular properties, and design new potent and selective ligands that may act on different classes of antimalarial drug targets so that these compounds may eventually be synthesized and assayed. Area covered in this review: In the present review, we focus on the current knowledge of QSARs and pharmacophore models of different classes of antimalarial drugs. In this context, we also review the reported docking studies of antimalarial compounds acting on different targets to explore the interaction pattern at the molecular level. What the reader will gain: The reader will gain an overview of advances of QSAR and related theoretical models of antimalarial drug compounds. Take home message: This review infers that most of the reported QSAR models are analog based QSARs with a limited applicability domain, but QSAR models based on diverse chemical structures acting on a particular target have been reported in very few cases.     

Three-dimensional quantitative structure-activity relationship analysis of ligand binding to human sequence antidigoxin monoclonal antibodies using comparative molecular field analysis

The present study indicates that the newly generated human sequence antidigoxin monoclonal antibody (mAb), 1B3, binds digoxin with a different fine specificity binding than our previously obtained human sequence monoclonal antibodies (mAbs) (Ball, W. J.; et al. J. Immunol. 1999, 163, 2291-2298). Uniquely, 1B3 has a higher affinity for digitoxin than digoxin, the immunizing hapten, and a strong requirement for at least one sugar residue linked to the aglycone (-genin). By means of comparative molecular field analysis (CoMFA), the results of competition binding studies for 56 cardiotonic and hormonal steroids were employed to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) models for ligand binding to 1B3 and to three additional human sequence mAbs, as well as the murine antidigoxin mAb 40-50 (Mudgett-Hunter, M.; et al. Mol. Immunol. 1985, 22, 447-488). All five 3D-QSAR models yielded cross-validated q(2) values greater than 0.5, which indicates that they have significant predictive ability. The CoMFA StDevCoeff contour plots, as well as the competition results, indicate that 1B3 binds ligands in a manner distinct from the other four mAbs. The CoMFA contour plots for 40-50 were also compared with the known X-ray crystallographic structure of the 40-50-ouabain complex (Jeffrey, P. D.; et al. J. Mol. Biol. 1995, 248, 344-360) in order to identify correlations between residues in the mAb binding site and specific contour plot regions. These 3D-QSAR models and their respective contour plots should be useful tools to further understand the molecular nature of antibody-antigen interactions and to aid in the redesign or enhancement of therapeutic antibodies.     

磺酰胺嘧啶类化合物的定量构效关系研究

目的研究磺酰胺嘧啶类化合物的定量构效关系(QSAR)。方法应用量子化学方法计算了48个磺酰胺嘧啶类化合物的结构参数,并用神经网络方法讨论了此类化合物分子结构与内皮素(ETs)受体拮抗活性之间的QSAR。结果获得了一个预测能力较好的QSAR神经网络模型。结论磺酰胺嘧啶类化合物与ETs受体之间存在直接的电荷迁移作用,前线轨道能、电子结构、空间因素是影响此类化合物对ETs活性的主要因素。将量子化学和神经网络相结合的方法可以成为QSAR研究的有效工具。     

Synthesis and quantitative structure-activity relationship analysis of N-triiodoallyl- and N-iodopropargylazoles. New antifungal agents

New series of N-(2,3,3-triiodoallyl) and N-(3-iodopropargyl) azole derivatives (100 compounds) involving pyrrole, pyrazole, imidazole, triazole, and tetrazole nuclei were synthesized successively with the aid of quantitative structure-activity relationship (QSAR) analysis to obtain potent antifungal agents. Starting from the derivatives of nitropyrrole-containing antibiotics, the QSAR analysis of the pyrrole derivatives against Candida albicans and Trichophyton mentagrophytes strains indicated the positive contribution of the nitro group and negative effect of the size of molecule. Further application of the QSAR analysis on the multi-azole derivatives revealed the importance of hydrophobicity and electronegativity as well as steric effect to the activities and led to the synthesis of one of the most potent iodo compounds, 2-(2,3,3-triiodoallyl)tetrazole (67, ME1401).     

黄烷醇类化合物抗氧化性的构效关系

目的　采用分子力学和量子化学从头计算的方法 ,研究黄烷醇类化合物抗氧化性的构效关系。方法　系统地计算了阿福豆素、儿茶素和培儿茶素等 3种黄烷醇类化合物的能量与电子结构 ,还计算了黄烷醇类化合物在脱氢氧化反应过程中生成自由基和类醌化合物的能量变化和电子羟基键级及电荷差。结果　黄烷醇类化合物抗氧化能力的顺序为培儿茶素 >儿茶素 >阿福豆素。结论　根据计算结果 ,黄烷醇类化合物抗氧化的能力与酚羟基的脱氢活性有关 ,并从能量和电子结构的角度给予了理论解释     

In silico human and rat Vss quantitative structure-activity relationship models

We present herein a QSAR tool enabling an entirely in silico prediction of human and rat steady-state volume of distribution (Vss), to be made prior to chemical synthesis, preceding detailed allometric or mechanistic assessment of Vss. Three different statistical methodologies, Bayesian neural networks (BNN), classification and regression trees (CART), and partial least squares (PLS) were employed to model human (N=199) and rat (N=2086) data sets. The results in prediction of an independent test set show the human model has an r2 of 0.60 and an rms error in prediction of 0.48. The corresponding rat model has an r2 of 0.53 and an rms error in prediction of 0.37, indicating both models could be very useful in the early stages of the drug discovery process. This is the first reported entirely in silico approach to the prediction of rat and human steady-state volume of distribution.     

Conformational and quantitative structure-activity relationship study of cytotoxic 2-arylidenebenzocycloalkanones

Various 2-arylideneindanones 1, 2-arylidenetetralones 2, and 2-arylidenebenzosuberones 3 were synthesized with the aim of determining the relative orientations of the two aryl rings which favored cytotoxicity. Molecular modeling of the unsubstituted compound in each series revealed differences in the spatial arrangements of the two aryl rings, and evaluation of these compounds against P388, L1210, Molt 4/C8, and CEM cells as well as a panel of human tumor cell lines indicated that in general the order of cytotoxicity was 3 > 2 > 1. In particular 2-(4-methoxyphenylmethylene)-1-benzosuberone (3k) had the greatest cytotoxicity, possessing 11 times the potency of the reference drug melphalan when all five screens were considered. Series 3 was considered in further detail. First, excision of the aryl ring fused to the cycloheptanone moiety in series 3 led to some 2-arylidene-1-cycloheptanones 4 which had approximately one-third of the bioactivity of the analogues 3. Second, in some screens cytotoxicity was correlated negatively with the sigma values and positively with the MR constants of the substituents in the arylidene aryl ring of 3. Third, X-ray crystallography of five representative compounds (3i,k-n) revealed differences in the locations of the aryl rings which may have contributed to the variations in cytotoxicity. Finally three members of series 3 inhibited RNA and protein syntheses and induced apoptosis in human Jurkat T cells. This study has revealed that 2-arylidene-1-benzosuberones are a group of useful cytotoxic agents, and in particular 3k serves as a prototypic molecule for subsequent structural modifications.