CoMFA modeling of enzyme kinetics: K(m) values for sulfation of diverse phenolic substrates by human catecholamine sulfotransferase SULT1A3

Three-dimensional QSAR models were developed for predicting kinetic Michaelis constant (K(m)) values for phenolic substrates of human catecholamine sulfating sulfotransferase (SULT1A3). The K(m) values were correlated to the steric and electronic molecular fields of the substrates utilizing Comparative Molecular Field Analysis (CoMFA). The evaluated SULT1A3 substrate data set consisted of 95 different substituted phenols, catechols, catecholamines, steroids, and related structures for which the K(m) values were available. The data set was divided in three different subgroups in the initial analysis: (1). for the first CoMFA model substrates with only one reacting hydroxyl group were selected (n = 51), (2).the second model was build with structurally rigid substrates (n = 59), and (3). finally all substrates of the data set were included in the analysis (n = 95). Substrate molecules were aligned using the aromatic ring and the reacting hydroxyl group as a template. After the initial analysis different substrate alignment rules based on the existing knowledge of the SULT1A3 active site structure were evaluated. After this optimization a final CoMFA model was built including all 95 substrates of the data set. Cross-validated q(2) values (leave-one-out and leave-n-out) and coefficient contour maps were calculated for all derived CoMFA models. All four CoMFA models were statistically significant with q(2) values up to 0.624. These predictive QSAR models will provide us information about the factors that affect substrate binding at the active site of human catecholamine sulfotransferase SULT1A3.     

酪氨酸蛋白磷酸酯酶1B抑制剂的分子对接和三维定量构效关系研究

用一种柔性分子对接方法(FlexX)将12个2-草酰胺苯甲酸类抑制剂和酪氨酸蛋白磷酸酯酶(PTP1B)活性口袋进行分子对接,对接程序预测的抑制剂和酶之间的相互作用能与抑制活性之间有很好的相关性(非线性相关系数R²达0.859),这说明对接结果可以比较准确地预测抑制剂和PTP1B之间的结合模式.然后,将33个同类抑制剂的骨架叠合在分子对接预测的结合构象上,用比较分子力场分析方法(CoMFA)对其进行三维定量活性构效关系研究,得到的CoMFA模型具有很好的统计相关性(交互验证回归系数q²为0.650),并可以准确地预测测试集6个化合物的活性(平均标准偏差为0.177).同时,由CoMFA模型得出的抑制剂改造信息与用FlexX预测的结合模式是一致的,进一步证明我们预测的结合模式是正确的.为研究这类抑制剂和PTP1B的结合模式及对抑制剂进行结构改造提供了信息.     

基于QSAR/QSSR的苯并三唑化合物选择性抑制PTP-1B的研究

蛋白酪氨酸磷酸酶1B (PTP-1B)特异性抑制剂是近年来治疗II型糖尿病药物研发的热点. PTP-1B与T细胞蛋白酪氨酸磷酸酶(TCPTP)同源性很高, 为了避免在使用PTP-1B抑制剂过程中对TCPTP产生交叉抑制, 则需要设计开发对PTP-1B具有高活性和高特异选择性的小分子化合物. 苯并三唑类化合物对PTP-1B的抑制活性很高, 并且其中一些化合物对PTP-1B表现出了较好的特异选择性, 具有良好的药用开发前景. 通过CoMFA和CoMSIA两种方法分别对该类化合物进行了三维定量结构-活性关系(3D-QSAR)和三维定量结构-选择性关系(3D-QSSR)研究, 并建立了相关的预测模型. 计算结果表明PTP-1B中的Arg24与化合物的氢键相互作用是提高选择性的重要因素, 并且在R2位引入氢键供体且体积较大的强供电子基团, 将有利于化合物抑制活性的提高, 而在R2位取代基的末端引入氢键受体且体积较大的强吸电子基团, 将有利于化合物选择性的提高.     

3D QSAR and molecular docking studies of benzimidazole derivatives as hepatitis C virus NS5B polymerase inhibitors

The urgent need for novel HCV antiviral agents has provided an impetus for understanding the structural requisites of NS5B polymerase inhibitors at the molecular level. Toward this objective, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of 67 HCV NS5B polymerase inhibitors were performed using two methods. First, ligand-based 3D QSAR studies were performed based on the lowest energy conformations employing the atom fit alignment method. Second, receptor-based 3D QSAR models were derived from the predicted binding conformations obtained by docking all NS5B inhibitors at the allosteric binding site of NS5B (PDB ID: 2dxs). Results generated from the ligand-based model were found superior (r2cv values of 0.630 for CoMFA and 0.668 for CoMSIA) to those obtained by the receptor-based model (r2cv values of 0.536 and 0.561 for CoMFA and CoMSIA, respectively). The predictive ability of the models was validated using a structurally diversified test set of 22 compounds that had not been included in a preliminary training set of 45 compounds. The predictive r2 values for the ligand-based CoMFA and CoMSIA models were 0.734 and 0.800, respectively, while the corresponding predictive r2 values for the receptor-based CoMFA and CoMSIA models were 0.538 and 0.639, respectively. The greater potency of the tryptophan derivatives over that of the tyrosine derivatives was interpreted based on CoMFA steric and electrostatic contour maps. The CoMSIA results revealed that for a NS5B inhibitor to have appreciable inhibitory activity it requires hydrogen bond donor and acceptor groups at the 5-position of the indole ring and an R substituent at the chiral carbon, respectively. Interpretation of the CoMFA and CoMSIA contour maps in context of the topology of the allosteric binding site of NS5B provided insight into NS5B-inhibitor interactions. Taken together, the present 3D QSAR models were found to accurately predict the HCV NS5B polymerase inhibitory activity of structurally diverse test set compounds and to yield reliable clues for further optimization of the benzimidazole derivatives in the data set.     

Homology model directed alignment selection for comparative molecular field analysis: Application to photosystem II inhibitors

The use of a computational docking protocol in conjunction with a protein homology model to derive molecular alignments for Comparative Molecular Field Analysis (CoMFA) was examined. In particular, the DOCK program and a model of the herbicidal target site, photosystem II (PSII), was used to derive alignments for two PSII inhibitor training sets, a set of benzo- and napthoquinones and a set of butenanilides. The protein design software in the QUANTA molecular modeling package was used to develop a homology model of spinach PSII based on the reported amino acid sequence and the X-ray crystal structure of the purple bacterium reaction center. The model is very similar to other reported PSII protein homology models. DOCK was then used to derive alignments for CoMFA modeling by docking the inhibitors in the PSII binding pocket. The molecular alignments produced from docking yielded highly predictive CoMFA models. As a comparison, the more traditional atom-atom alignments of the same two training sets failed to produce predictive CoMFA models. The general utilities of this application for homology model refinement and as an alternative scoring method are discussed.     

Negative regulation of a protein tyrosine phosphatase by tyrosine phosphorylation

The low molecular weight protein tyrosine phosphatase (LMW-PTP) is a ubiquitously expressed enzyme with several proposed roles in cell signaling. Previously, two tyrosine phosphorylation modifications of LMW-PTP at sites Tyr-131 and Tyr-132 in response to growth factor stimulation have been mapped and suggested to stimulate LMW-PTP phosphatase activity. Biochemical analysis of tyrosine phosphorylation of a tyrosine phosphatase is challenging because of the intrinsic instability of these modifications. Here we used expressed protein ligation to site-specifically incorporate a phosphotyrosine mimic (phosphonomethylenephenylalanine, Pmp) at the Tyr-131 and Tyr-132 positions and measured the catalytic activity of these semisynthetic LMW-PTPs. The phosphonate-modified LMW-PTPs were 10- to 23-fold less active in dephosphorylating phosphotyrosine peptides derived from the PDGF receptor and p190RhoGap, two putative cellular substrates. These findings suggest the first example of a tyrosine phosphatase that is inhibited by tyrosine phosphorylation and provide a new model for the regulation of LMW-PTP and its role in cell adhesion.     

Mapping the binding site of a large set of quinazoline type EGF-R inhibitors using molecular field analyses and molecular docking studies

In the current work, three-dimensional QSAR studies for one large set of quinazoline type epidermal growth factor receptor (EGF-R) inhibitors were conducted using two types of molecular field analysis techniques: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). These compounds belonging to six different structural classes were randomly divided into a training set of 122 compounds and a test set of 13 compounds. The statistical results showed that the 3D-QSAR models derived from CoMFA were superior to those generated from CoMSIA. The most optimal CoMFA model after region focusing bears significant cross-validated r(2)(cv) of 0.60 and conventional r(2) of 0.92. The predictive power of the best CoMFA model was further validated by the accurate estimation to these compounds in the external test set, and the mean agreement of experimental and predicted log(IC(50)) values of the inhibitors is 0.6 log unit. Separate CoMFA models were conducted to evaluate the influence of different partial charges (Gasteiger-Marsili, Gasteiger-Hückel, MMFF94, ESP-AM1, and MPA-AM1) on the statistical quality of the models. The resulting CoMFA field map provides information on the geometry of the binding site cavity and the relative weights of various properties in different site pockets for each of the substrates considered. Moreover, in the current work, we applied MD simulations combined with MM/PBSA (Molecular mechanics/Possion-Boltzmann Surface Area) to determine the correct binding mode of the best inhibitor for which no ligand-protein crystal structure was present. To proceed, we define the following procedure: three hundred picosecond molecular dynamics simulations were first performed for the four binding modes suggested by DOCK 4.0 and manual docking, and then MM/PBSA was carried out for the collected snapshots. The most favorable binding mode identified by MM/PBSA has a binding free energy about 10 kcal/mol more favorable than the second best one. The most favorable binding mode identified by MM/PBSA can give satisfactory explanation of the SAR data of the studied molecules and is in good agreement with the contour maps of CoMFA. The most favorable binding mode suggests that with the quinazoline-based inhibitor, the N3 atom is hydrogen-bonded to a water molecule which, in turn, interacts with Thr 766, not Thr 830 as proposed by Wissner et al. (J. Med. Chem. 2000, 43, 3244). The predicted complex structure of quinazoline type inhibitor with EGF-R as well as the pharmacophore mapping from CoMFA can interpret the structure activities of the inhibitors well and afford us important information for structure-based drug design.     

酪氨酸激酶抑制剂的比较分子场分析

采用比较分子场分析(CoMFA)方法研究了一组嘧啶类衍生物酪氨酸激酶抑制剂活性与结构的关系.所得模型不仅能够很好地预报训练集中的化合物的活性,而且还可以准确地预报预报集中的化合物活性.通过分析分子场等值面图在空间的分布,可以观察到叠加分子周围的立体和静电特征对化合物活性的影响.     

苯并呋喃／噻吩联二苯类PTP1B抑制剂三维构效关系研究

主要采用比较分子力场分析方法（CoMFA）对苯并呋喃／噻吩联二苯类PTP1B (protein tyrosine phosphatase 1B)抑制剂进行了三维构效关系的研究，考察了 静电场、立体场和氢键场对构效关系的影响，交叉系数q^2的值达到0．58，表明 CoMFA得到的构效关系模型比较理想，同时test set中分子的预测活性也表明，模 型具有较好的预测能力，研究还表明，氢键场的加入不一定有利于模型的改善，通 过对分子场等值面图的分析，可以观察到叠合分子周围立体场和静电场对化合物活 性的影响，为改进原有化合物的结构，提高它们的活性提供了指导，还尝试采用比 较分子相似性指数分析方法（CoMFA）对这一系列化合物作了研究，结果表明虽然 CoMFA中加入了疏水场，但是对于研究的体系，CoMFA的模型质量并没有显著提高。     

Effects of variable selection on CoMFA coefficient contour maps in a set of triazines inhibiting DHFR

Summary An example of a CoMFA study is described with the aim to discuss one of the major problems of this 3D QSAR method: lack of variable selection. It is shown that the use of nonrelevant energy parameters might produce CoMFA contour maps which poorly reflect the actual nature of the binding site and are in part statistical artefacts. The data set employed in our analysis comparises triazine inhibitors of dihydrofolate reductase (DHFR), isolated from chicken liver, which have already been the object of a QSAR study by other authors. Since three-dimensional structures of triazine-DHFR complexes are known, it was possible not only to reduce ambiguities in the superimposition of the ligands, but also to compare the resulting CoMFA contour maps with the enzyme active site.Supplementary material available: The Cartesian coordinates and the atomic charges of the PM3-optimized structures used in the CoMFA study are available as MOL2 files upon request.To whose memory this paper is dedicated.     

3D QSAR studies on protein tyrosine phosphatase 1B inhibitors: comparison of the quality and predictivity among 3D QSAR models obtained from different conformer-based alignments

A set of 65 flexible peptidomimetic competitive inhibitors (52 in the training set and 13 in the test set) of protein tyrosine phosphatase 1B (PTP1B) has been used to compare the quality and predictive power of 3D quantitative structure-activity relationship (QSAR) comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the three most commonly used conformer-based alignments, namely, cocrystallized conformer-based alignment (CCBA), docked conformer-based alignment (DCBA), and global minima energy conformer-based alignment (GMCBA). These three conformers of 5-[(2S)-2-({(2S)-2-[(tert-butoxycarbonyl)amino]-3-phenylpropanoyl}amino)3-oxo-3-pentylamino)propyl]-2-(carboxymethoxy)benzoic acid (compound number 66) were obtained from the X-ray structure of its cocrystallized complex with PTP1B (PDB ID: 1JF7), its docking studies, and its global minima by simulated annealing. Among the 3D QSAR models developed using the above three alignments, the CCBA provided the optimal predictive CoMFA model for the training set with cross-validated r2 (q2)=0.708, non-cross-validated r2=0.902, standard error of estimate (s)=0.165, and F=202.553 and the optimal CoMSIA model with q2=0.440, r2=0.799, s=0.192, and F=117.782. These models also showed the best test set prediction for the 13 compounds with predictive r2 values of 0.706 and 0.683, respectively. Though the QSAR models derived using the other two alignments also produced statistically acceptable models in the order DCBA>GMCBA in terms of the values of q2, r2, and predictive r2, they were inferior to the corresponding models derived using CCBA. Thus, the order of preference for the alignment selection for 3D QSAR model development may be CCBA>DCBA>GMCBA, and the information obtained from the CoMFA and CoMSIA contour maps may be useful in designing specific PTP1B inhibitors.     

Antibody-free lanthanide-based fluorescent probe for determination of protein tyrosine kinase and phosphatase activities

A single-labeled peptide probe for measuring peptide phosphorylation status was developed by using a phosphate sensitive terbium chelate. The activity of Abl protein tyrosine kinase and T-cell protein Tyrosine phosphatase (TC PTP) was monitored in real time. To study the probe design in detail, variable substrate peptide sequences, where the enzyme target site was located from two to five amino acids apart from the nearest tyrosine residue, were synthesized. The maximum change observed in fluorescence intensity after phosphorylation was up to 320%, when the phosphorylated tyrosine was located two amino acids from the lysine coupled to the phosphate sensitive terbium chelate, demonstrating an excellent performance for a homogeneous assay. Also the longer distance of five amino acids between the phosphorylated tyrosine residue and terbium chelate resulted up to 260% change in fluorescence intensity.

A Formylglycine-Peptide for the Site-Directed Identification of Phosphotyrosine-Mimetic Fragments**

Discovery of protein-binding fragments for precisely defined binding sites is an unmet challenge to date. Herein, formylglycine is investigated as a molecular probe for the sensitive detection of fragments binding to a spatially defined protein site . Formylglycine peptide 3 was derived from a phosphotyrosine-containing peptide substrate of protein tyrosine phosphatase PTP1B by replacing the phosphorylated amino acid with the reactive electrophile. Fragment ligation with formylglycine occurred in situ in aqueous physiological buffer. Structures and kinetics were validated by NMR spectroscopy. Screening and hit validation revealed fluorinated and non-fluorinated hit fragments being able to replace the native phosphotyrosine residue. The formylglycine probe identified low-affinity fragments with high spatial resolution as substantiated by molecular modelling. The best fragment hit, 4-amino-phenyl-acetic acid, was converted into a cellularly active, nanomolar inhibitor of the protein tyrosine phosphatase SHP2.     

Bioassay‐guided isolation of an active compound with protein tyrosine phosphatase 1B inhibitory activity from Sargassum fusiforme by high‐speed counter‐current chromatography

A rapid and efficient method using high‐speed counter‐current chromatography was established for the bioassay‐guided separation of an active compound with protein tyrosine phosphatase 1B inhibitory activity from Sargassum fusiforme. Under the bioassay guidance, the ethyl acetate extract with the best IC₅₀ value of 0.37 ± 0.07 μg/mL exhibited a potential protein tyrosine phosphatase 1B inhibitory activity, which was further separated by high‐speed counter‐current chromatography. The separation was performed with a two‐phase solvent system composed of n‐hexane/methanol/water (5:4:1, v/v). As a result, dibutyl phthalate (19.7 mg) with the purity of 95.3% was obtained from 200 mg of the ethyl acetate extract. Its IC₅₀ was 14.05 ± 0.06 μM, which was further explained by molecular docking. The result of molecular docking showed that dibutyl phthalate enfolded in the catalytic site of protein tyrosine phosphatase 1B. The main force between dibutyl phthalate and protein tyrosine phosphatase 1B was the hydrogen bond interaction with Gln266. In addition, hydrogen bond, van der Waals force and hydrophobic interaction with the amino acids (Ala217, Ile219, and Gly220) were also responsible for the stable protein‐ligand complex.     

Discovery of a potent,selective protein tyrosine phosphatase 1B inhibitor using a linked-fragment strategy

Protein tyrosine phosphatase 1B (PTP1B) is an enzyme that downregulates the insulin receptor. Inhibition of PTP1B is expected to improve insulin action, and the design of small molecule PTP1B inhibitors to treat type II diabetes has received considerable attention. In this work, NMR-based screening identified a nonselective competitive inhibitor of PTP1B. A second site ligand was also identified by NMR-based screening and then linked to the catalytic site ligand by rational design. X-ray data confirmed that the inhibitor bound with the catalytic site in the native, "open" conformation. The final compound displayed excellent potency and good selectivity over many other phosphatases. The modular approach to drug design described in this work should be applicable for the design of potent and selective inhibitors of other therapeutically relevant protein tyrosine phosphatases.     

Enhancement of ordinal CoMFA by ridge logistic partial least squares

Conventional comparative molecular field analysis (CoMFA) requires at least 3 orders of experimental data, such as IC 50 and K i, to obtain a good model, although practically there are many screening assays where biological activity is measured only by rating scale. To improve three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis, we developed in this study a modified ordinal classification-oriented CoMFA using partial-least-squares generalized linear regression and ridge estimation. The modified Logistic CoMFA was validated using a corticosteroid binding globulin receptor binding data set, a benchmark for 3D-QSAR, and an acetylcholine esterase inhibitor data set. Our results show that modification of Logistic CoMFA enhanced both prediction accuracy and 3D graphical analysis. In addition, the 3D graphical analysis of the modified Logistic CoMFA was much improved. This improvement resulted in more accurate information on the binding mode between proteins and ligands than in the case of conventional CoMFA.     

A ligand-based comparative molecular field analysis (CoMFA) and homology model based molecular docking studies on 3′, 4′-dihydroxyflavones as rat 5-lipoxygenase inhibitors: Design of new inhibitors

In this study, ligand based comparative molecular field analysis (CoMFA) with five principal components was performed on class of 3′, 4′-dihydroxyflavone derivatives for potent rat 5-LOX inhibitors. The percentage contributions in building of CoMFA model were 91.36% for steric field and 8.6% for electrostatic field. R² values for training and test sets were found to be 0.9320 and 0.8259, respectively. In case of LOO, LTO and LMO cross validation test, q² values were 0.6587, 0.6479 and 0.5547, respectively. These results indicate that the model has high statistical reliability and good predictive power. The extracted contour maps were used to identify the important regions where the modification was necessary to design a new molecule with improved activity. The study has developed a homology model for rat 5-LOX and recognized the key residues at the binding site. Docking of most active molecule to the binding site of 5-LOX confirmed the stability and rationality of CoMFA model. Based on molecular docking results and CoMFA contour plots, new inhibitors with higher activity with respect to the most active compound in data set were designed.     

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.     

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of thiazolone derivatives as hepatitis C virus NS5B polymerase allosteric inhibitors

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models for a series of thiazolone derivatives as novel inhibitors bound to the allosteric site of hepatitis C virus (HCV) NS5B polymerase were developed based on CoMFA and CoMSIA analyses. Two different conformations of the template molecule and the combinations of different CoMSIA field/fields were considered to build predictive CoMFA and CoMSIA models. The CoMFA and CoMSIA models with best predictive ability were obtained by the use of the template conformation from X-ray crystal structures. The best CoMFA and CoMSIA models gave q (2) values of 0.621 and 0.685, and r (2) values of 0.950 and 0.940, respectively for the 51 compounds in the training set. The predictive ability of the two models was also validated by using a test set of 16 compounds which gave r (pred) (2) values of 0.685 and 0.822, respectively. The information obtained from the CoMFA and CoMSIA 3D contour maps enables the interpretation of their structure-activity relationship and was also used to the design of several new inhibitors with improved activity.     

1,2-萘醌类化合物抑制PTP1B的三维定量构效关系研究

蛋白酪氨酸磷酸酶1B (protein tyrosine phosphatase 1B, PTP-1B)是近年来发现的治疗II型糖尿病的新靶点, 1,2-萘醌类化合物对PTP-1B有较好的抑制活性, 具有良好的药用前景. 为了设计出本类化合物抑制效果更好的分子构型, 用比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)对该类化合物进行了三维定量构效关系(3D-QSAR)的研究, 并建立了相关的预测模型. 其中, CoMFA模型的交叉验证相关系数(q²)为0.555, 非交叉验证相关系数(r²)为0.991, 标准偏差(SEE)为0.049, F值为564.910. CoMSIA模型的q²为0.558, r²为0.991, SEE为0.050, F值为542.773. 计算结果表明, 获得的CoMFA和CoMSIA模型具有良好的预测能力, 可以应用于指导该类化合物的设计.