Glycogen synthase kinase-3 inhibition by 3-anilino-4-phenylmaleimides: insights from 3D-QSAR and docking

Glycogen synthase kinase-3, a serine/threonine kinase, has been implicated in a wide variety of pathological conditions such as diabetes, Alzheimer’s disease, stroke, bipolar disorder, malaria and cancer. Herein we report 3D-QSAR analyses using CoMFA and CoMSIA and molecular docking studies on 3-anilino-4-phenylmaleimides as GSK-3α inhibitors, in order to better understand the mechanism of action and structure-activity relationship of these compounds. Comparison of the active site residues of GSK-3α and GSK-3β isoforms shows that all the key amino acids involved in polar interactions with the maleimides for the β isoform are the same in the α isoform, except that Asp133 in the β isoform is replaced by Glu196 in the α isoform. We prepared a homology model for GSK-3α, and showed that the change from Asp to Glu should not affect maleimide binding significantly. Docking studies revealed the binding poses of three subclasses of these ligands, namely anilino, N-methylanilino and indoline derivatives, within the active site of the β isoform, and helped to explain the difference in their inhibitory activity.     

雌激素β受体喹啉类配体的分子对接及3D-QSAR研究

对33个喹啉衍生物的雌激素β受体活性进行了分子对接以及比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA). 对接结果显示氢键和疏水作用是配体与受体结合的主要因素,同时结果亦显示对接结合能与观测值pIC50具有极显著的线性相关性. 根据对接后各优势构象将33个样本进行叠合并进行CoMFA与CoMSIA研究,均得到了较优的结果,其中以选用立体场、静电场和疏水场建立的CoMSIA模型结果最优,其主成分数,r2,q2（LOO）和r2pred分别为2, 0.894, 0.708和0.802. 构效关系模型分析显示基团的空间位阻、电性及疏水作用是影响活性的主要因素     

Pose prediction accuracy in docking studies and enrichment of actives in the active site of GSK-3beta

We present molecular docking studies on the inhibitors of GSK-3beta kinase in the enzyme binding sites of the X-ray complexes (1H8F, 1PYX, 1O9U, 1Q4L, 1Q5K, and 1UV5) using the Schr?dinger docking tool Glide. Cognate and cross-docking studies using standard precision (SP) and extraprecision (XP) algorithms have been carried out. Cognate docking studies demonstrate that docked poses similar to X-ray poses (root-mean-square deviations of less than 2 A) are found within the top four ranks of the GlideScore and E-model scores. However, cross-docking studies typically produce poses that are significantly deviated from X-ray poses in all but a couple of cases, implying potential for induced fit effects in ligand binding. In this light, we have also carried out induced fit docking studies in the active sites of 1O9U, 1Q4L, and 1Q5K. Specifically, conformational changes have been effected in the active sites of these three protein structures to dock noncognate ligands. Thus, for example, the active site of 1O9U has been induced to fit the ligands of 1Q4L, 1Q5K, and 1UV5. These studies produce ligand docked poses which have significantly lower root-mean-square deviations relative to their X-ray crystallographic poses, when compared to the corresponding values from the cross-docking studies. Furthermore, we have used an ensemble of the induced fit models and X-ray structures to enhance the retrieval of active GSK-3beta inhibitors seeded in a decoy database, normally used in Glide validation studies. Thus, our studies provide valuable insights into computational strategies useful for the identification of potential GSK-3beta inhibitors.     

Docking and 3D-QSAR Analysis on a Series of Pyridone-based EZH2 Inhibitors

Enhancer of Zeste homolog 2(EZH2) is closely correlated with malignant tumor and regarded as a promising target to treat B-cell lymphoma. In our research, the molecular docking and three-dimensional quantitative structure-activity relationships(3D-QSAR) studies were performed on a series of pyridone-based EZH2 compounds. Molecular docking allowed us to study the critical interactions at the binding site of EZH2 protein with inhibitors and identify the practical conformations of ligands in binding pocket. Moreover, the docking-based alignment was applied to derive the reliable 3D-QSAR models. Comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA) provided available ability of visualization. All the derived 3D-QSAR models were considered to be statistically significant with respect to the internal and external validation parameters. For the CoMFA model, q~2 = 0.649, r~2 = 0.961 and r~2 pred = 0.877. For the CoMSIA model, q~2 = 0.733, r~2 = 0.980 and r~2 pred = 0.848. With the above arguments, we extracted the correlation between the biological activity and structure. Based on the binding interaction and 3D contour maps, several new potential inhibitors with higher biological activity predicted were designed, which still awaited experimental validation. These theoretical conclusions could be helpful for further research and exploring potential EZH2 inhibitors.     

马来酰胺类糖原合成酶激酶-3β抑制剂的分子对接和三维定量构效关系

通过分子对接和三维定量构效关系(3D-QSAR)两种方法来确定两类马来酰胺类的糖原合成酶激酶-3β(GSK-3β)抑制剂的结合方式. 首先, 用分子对接确定抑制剂与GSK-3β结合模式及其相互作用; 然后用比较分子力场分析法(CoMFA)与比较分子相似性指数分析法(CoMSIA)对48个化合物做三维定量构效关系的分析. 两种方法得出的交互验证回归系数分别为0.669(CoMFA)和0.683(CoMSIA), 证明该模型具有很好的统计相关性, 同时也说明该模型具有较高的预测能力.根据该模型提供的信息, 设计出9个预测活性较好的分子.     

In silico design novel (5-imidazol-2-yl-4-phenylpyrimidin-2-yl)[2-(2-pyridylamino)ethyl]amine derivatives as inhibitors for glycogen synthase kinase 3 based on 3D-QSAR,molecular docking and molecular dynamics simulation

Glycogen Synthase Kinase 3 (GSK-3) is a member of cellular kinase with various functions, such as glucose regulation, cellular differentiation, neuronal function and cell apoptosis. It has been proved as an important therapeutic target in type 2 diabetes mellitus and Alzheimer's disease. To better understand their structure–activity relationships and mechanism of action, an integrated computational study, including three dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, and molecular dynamics (MD), was performed on 79 (5-Imidazol-2-yl-4-phenylpyrimidin-2-yl)[2-(2-pyridylamino)ethyl]amine GSK-3 inhibitors. In this paper, we constructed 3D-QSAR using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) method. The results showed that the CoMFA model (q ² = 0.743, r² = 0.980) and the CoMSIA model (q² = 0.813, r² = 0.976) had stable and reliable predictive ability. The electrostatic and H-bond donor fields play important roles in the models. The contour maps of the model visually showed the relationship between the activity of compounds and their three-dimensional structure. Molecular docking was used to identify the key amino acid residues at the active site of GSK-3 and explore its binding mode with ligands. Based on 3D-QSAR models, contour maps and the binding feature between GSK-3 and inhibitor, we designed 10 novel compounds with good potential activity and ADME/T profile. Molecular dynamics simulation results validated that Ile62, Val70 and Lys85 located in the active site play a key role for GSK-3 complexed with inhibitors. These results might provide important information for designing GSK-3 inhibitors with high activity.     

马来酰胺类糖原合成酶激酶-3β抑制剂的分子对接和三维定量构效关系

通过分子对接和三维定量构效关系(3D-QSAR)两种方法来确定两类马来酰胺类的糖原合成酶激酶-3β(GSK-3β)抑制剂的结合方式.首先,用分子对接确定抑制剂与GSK-3β的结合模式及其相互作用;然后用比较分子力场分析法(CoMFA)与比较分子相似性指数分析法(CoMSIA)对48个化合物做三维定量构效关系的分析.两种方法得出的交互验证回归系数分别为0.669(CoMFA)和0.683(CoMSIA),证明该模型具有很好的统计相关性,同时也说明该模型具有较高的预测能力.根据该模型提供的信息,设计出9个预测性较好的分子.     

Pharmacophore interactions analysis and prediction of inhibitory activity of 1,7-diazacarbazoles as checkpoint kinase 1 inhibitors: application of molecular docking, 3D-QSAR and RBF neural network

In the present study, we mainly focused on new synthesized 1,7-diazacarbazole derivatives (44 active molecules) as Chk1 inhibitors to build 3D-QSAR model. Comparative molecular field analysis (CoMFA) model with three principal components was developed. The relative contributions in building of CoMFA model were 64.41 % for steric field and 35.59 % for electrostatic field. R ² values for training and test sets of CoMFA model were 0.8724 and 0.7818, respectively, and squared correlation coefficient for leave-one-out cross-validation test (q ²) was 0.6753. To improve the predictive power, a new 3D-QSAR model was developed by using radial basis function network (RBFN) and score of CoMFA interactions energy values as input variables. Scores 1, 2 and 3 were used as input variables, and a RBFN model with seven centers and spread value equal to 95 was developed to create a nonlinear 3D-QSAR model. R ² values for training and test sets were 0.9613 and 0.8564, and q ² for leave-one-out cross-validation test was 0.9258. Docking of all molecules to 3DX ligand binding site of Chk1 receptor indicated six interactions as pharmacological interactions between compounds and binding site of receptors. These pharmacological interactions were hydrogen bonding with LEU-15 and GLU-85 in main chain and four van der Waals interactions with LEU-15, VAL-23, TYR-86 and LEU-137 in side chain. CoMFA contour plots were used to design new inhibitors, and inhibitory activity of each compound was predicted by using CoMFA and RBFN models.     

GSK-3-selective inhibitors derived from Tyrian purple indirubins

Gastropod mollusks have been used for over 2500 years to produce the "Tyrian purple" dye made famous by the Phoenicians. This dye is constituted of mixed bromine-substituted indigo and indirubin isomers. Among these, the new natural product 6-bromoindirubin and its synthetic, cell-permeable derivative, 6-bromoindirubin-3'-oxime (BIO), display remarkable selective inhibition of glycogen synthase kinase-3 (GSK-3). Cocrystal structure of GSK-3beta/BIO and CDK5/p25/indirubin-3'-oxime were resolved, providing a detailed view of indirubins' interactions within the ATP binding pocket of these kinases. BIO but not 1-methyl-BIO, its kinase inactive analog, also inhibited the phosphorylation on Tyr276/216, a GSK-3alpha/beta activation site. BIO but not 1-methyl-BIO reduced beta-catenin phosphorylation on a GSK-3-specific site in cellular models. BIO but not 1-methyl-BIO closely mimicked Wnt signaling in Xenopus embryos. 6-bromoindirubins thus provide a new scaffold for the development of selective and potent pharmacological inhibitors of GSK-3.     

Receptor-based modeling and 3D-QSAR for a quantitative production of the butyrylcholinesterase inhibitors based on genetic algorithm

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of structurally related steroidal alkaloids as butyrylcholinesterase (BuChE) inhibitors. Docking studies were employed to position the inhibitors into the BuChE active site to determine the most probable binding mode. The strategy was to explore multiple inhibitor conformations in producing a more reliable 3D-QSAR model. These multiple conformations were derived using the FlexS program. The conformation selection step for CoMFA was done by genetic algorithm. The genetic algorithm based CoMFA approach was found to be the best. Both CoMFA and CoMSIA yielded significant cross-validated q(2) values of 0.701 and 0.627 and the r(2) values of 0.979 and 0.982, respectively. These statistically significant models were validated by a test set of five compounds. Comparison of CoMFA and CoMSIA contour maps helped to identify structural requirements for the inhibitors and serves as a basis for the design of the next generation of the inhibitor analogues. The results demonstrate that the combination of ligand-based and receptor-based modeling with use of a genetic algorithm is a powerful approach to build 3D-QSAR models. These data can be used for the lead optimization process with respect to inhibition enhancement which is important for the drug discovery and development for Alzheimer's disease.     

CoMFA and CoMSIA 3D-quantitative structure-activity relationship model on benzodiazepine derivatives, inhibitors of phosphodiesterase IV

Recently, we reported structurally novel PDE4 inhibitors based on 1,4-benzodiazepine derivatives. The main interest in developing bezodiazepine-based PDE4 inhibitors is in their lack of adverse effects of emesis with respect to rolipram-like compounds. A large effort has thus been made toward the structural optimization of this series. In the absence of structural information on the inhibitor binding mode into the PDE4 active site, 2D-QSAR (H-QSAR) and two 3D-QSAR (CoMFA and CoMSIA) methods were applied to improve our understanding of the molecular mechanism controlling the PDE4 affinity of the benzodiazepine derivatives. As expected, the CoMSIA 3D contour maps have provided more information on the benzodiazepine interaction mode with the PDE4 active site whereas CoMFA has built the best tool for activity prediction. The 2D pharmacophoric model derived from CoMSIA fields is consistent with the crystal structure of the PDE4 active site reported recently. The combination of the 2D and 3D-QSAR models was used not only to predict new compounds from the structural optimization process, but also to screen a large library of bezodiazepine derivatives.     

Structure-based QSAR analysis of a set of 4-hydroxy-5,6-dihydropyrones as inhibitors of HIV-1 protease: an application of the receptor-dependent (RD) 4D-QSAR formalism

Receptor-dependent (RD) 4D-QSAR models were constructed for a set of 39 4-hydroxy-5,6-dihydropyrone analogue HIV-1 protease inhibitors. The receptor model used in this QSAR analysis was derived from the HIV-1 protease (PDB ID ) crystal structure. The bound ligand in the active site of the enzyme, also a 4-hydroxy-5,6-dihydropyrone analogue, was used as the reference ligand for docking the data set compounds. The optimized RD 4D-QSAR models are not only statistically significant (r(2) = 0.86, q(2) = 0.80 for four- and greater-term models) but also possess reasonable predictivity based on test set predictions. The proposed "active" conformations of the docked analogues in the active site of the enzyme are consistent in overall molecular shape with those suggested from crystallographic studies. Moreover, the RD 4D-QSAR models also "capture" the existence of specific induced-fit interactions between the enzyme active site and each specific inhibitor. Hydrophobic interactions, steric shape requirements, and hydrogen bonding of the 4-hydroxy-5,6-dihydropyrone analogues with the HIV-1 protease binding site model dominate the RD 4D-QSAR models in a manner again consistent with experimental conclusions. Some possible hypotheses for the development of new lead HIV-1 protease inhibitors can be inferred from the RD 4D-QSAR models.     

STAT3环烷烃并噻吩类衍生物抑制剂的三维定量构效关系研究

本文对STAT3抑制剂的化学结构与生物活性之间的关系进行研究。采用三维定量构效关系(3D-QSAR)中的比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)方法针对52个STAT3抑制剂建立3D-QSAR模型,阐明了抑制剂化学结构与其生物活性之间的关系。所构建的CoMFA模型交叉验证系数为0.548,非交叉验证系数为0.754,标准偏差为0.278,显著系数为58.297;所构建的CoMSIA模型交叉验证系数为0.892,非交叉验证系数为0.597,标准偏差为0.192,显著系数为57.794。结果显示CoMFA和CoMSIA模型具有良好的稳定性和预测能力。3D-QSAR模型等势图提供的相关场信息对新型STAT3抑制剂的设计具有指导意义。     

Structure-based design leads to the identification of lithium mimetics that block mania-like effects in rodents. possible new GSK-3beta therapies for bipolar disorders

More than two million American adults, or approximately one percent of the population 18 years or older, suffer from bipolar disorder. Current treatments include the so-called "mood stabilizers," lithium and valproic acid. Both are relatively dated drugs that are only partially effective and produce various undesirable side effects including weight gain. Based upon continued efforts to understand the molecular target for lithium, it now appears that specific inhibitors of the enzyme glycogen synthase kinase-3beta (GSK-3beta) may mimic the therapeutic action of mood stabilizers and might therefore allow for the design of improved drugs for treating patients with bipolar disorder as well as certain neurodegenerative disorders. Furthermore, the pro-apoptotic properties of the GSK-3 enzyme suggest the possible use of such inhibitors as neuroprotective agents. In fact, neuroprotection may contribute to the treatment of mood disorders. The present chemistry, modeling, and biology efforts have identified 3-benzofuranyl-4-indolylmaleimides as potent and relatively selective GSK-3beta inhibitors. The best ligand in this series (having a Ki value of 4.6 nM against GSK-3beta) was studied in a novel mouse model of mania that has recently been validated with several clinically effective mood stabilizers. This study presents the first demonstration of the efficacy of a GSK-3beta inhibitor in this mouse model of mania. Selective brain penetrable GSK-3 ligands like those described herein become valuable research tools in better defining the role of this multifaceted kinase in both physiological and pathophysiological events.     

Design of inhibitors of the MurF enzyme of Streptococcus pneumoniae using docking, 3D-QSAR, and de Novo design

The biosynthetic pathway for formation of the bacterial cell wall (peptidoglycan) presents an attractive target for intervention. This is exploited by many of the clinically useful antibiotics, which inhibit enzymes involved in the later stages of peptidoglycan synthesis. MurF is one of the four amide bond-forming enzymes (d-alanyl-d-alanine ligating enzyme) that catalyzes the ATP-dependent formation of UDP-MurNAc-tripeptide. In the present study, several MurF inhibitors were docked into the active site of MurF to explore their binding modes and also to gain an insight into the crucial ligand-receptor interactions at the molecular level. The final selection of the "bioactive" conformation of every ligand was influenced by consensus scoring in which various independent scoring functions such as GoldScore, ChemScore, HINT score and X-CScore were employed. Subsequently, 3D-QSAR studies using comparative molecular field analysis (CoMFA) and the new approach comparative residue interaction analysis (CoRIA) have been carried out on the enzyme-inhibitor complexes obtained by docking and postscoring analysis. Finally, new inhibitors have been designed using the de novo approach of Ludi, and the activities of the most promising hits have been predicted with the CoMFA and CoRIA models.     

Molecular docking and 3D-QSAR study of pyranmycin derivatives against 16S rRNA A site

To understand pharmacophore properties of pyranmycin derivatives and to design novel inhibitors of 16S rRNA A site, comparative molecular field analysis (CoMFA) approach was applied to analyze three-dimensional quantitative structure–activity relationship (3D-QSAR) of 17 compounds. AutoDock 3.0.5 program was employed to locate the orientations and conformations of the inhibitors interacting with 16S rRNA A site. The interaction mode was demonstrated in the aspects of inhibitor conformation, hydrogen bonding and electrostatic interaction. Similar binding conformations of these inhibitors and good correlations between the calculated binding free energies and experimental biological activities suggest that the binding conformations of these inhibitors derived from docking procedure were reasonable. Robust and predictive 3D-QSAR model was obtained by CoMFA with q² values of 0.723 and 0.993 for cross-validated and non-cross-validated, respectively. The 3D-QSAR model built here will provide clear guidelines for novel inhibitors design based on the Pyranmycin derivatives against 16S rRNA A site.     

CoMFA 3D-QSAR analysis of HIV-1 RT nonnucleoside inhibitors, TIBO derivatives based on docking conformation and alignment

HIV-1 RT is one of the key enzymes in the duplication of HIV-1. Inhibitors of HIV-1 RT are classified as nonnucleoside RT inhibitors (NNRTIs) and nucleoside analogues. NNRTIs bind in a region not associated with the active site of the enzyme. Within the NNRTI category, there is a set of inhibitors commonly referred to as TIBO inhibitors. Fifty TIBO inhibitors were used in the work to build 3-D QSAR models. The two known crystal structures of complexes are used to investigate and validate the docking protocol. The results show that the docking simulations reproduce the crystal complexes very well with RMSDs of approximately 1 A and approximately 0.6 A for 1REV and 1COU, respectively. The alignment of molecules and "active" conformation selection are the key to a successful 3D-QSAR model by CoMFA. The flexible docking (Autodock3) was used on determination of "active" conformation and molecular alignment, and CoMFA and CoMSIA were used to develop 3D-QSAR models of 50 TIBOs in the work. The 3D-QSAR models demonstrate a good ability to predict the activity of studied compounds (r2 = 0.972, 0.944, q2 = 0.704, 0.776). It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the binding structure of the complex. The results demonstrate that the combination of ligand-based and receptor-based modeling is a powerful approach to build 3D-QSAR models.     

3D-QSAR studies of dihydropyrazole and dihydropyrrole derivatives as inhibitors of human mitotic kinesin Eg5 based on molecular docking

Human mitotic kinesin Eg5 plays an essential role in mitoses and is an interesting drug target against cancer. To find the correlation between Eg5 and its inhibitors, structure-based 3D-quantitative structure-activity relationship (QSAR) studies were performed on a series of dihydropyrazole and dihydropyrrole derivatives using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Based on the LigandFit docking results, predictive 3D-QSAR models were established, with cross-validated coefficient values (q2) up to 0.798 for CoMFA and 0.848 for CoMSIA, respectively. Furthermore, the CoMFA and CoMSIA models were mapped back to the binding sites of Eg5, which could provide a better understanding of vital interactions between the inhibitors and the kinase. Ligands binding in hydrophobic part of the inhibitor-binding pocket were found to be crucial for potent ligand binding and kinases selectivity. The analyses may be used to design more potent EG5 inhibitors and predict their activities prior to synthesis.