3D-QSAR and docking studies on pyridopyrazinones as BRAF inhibitors

BRAF has become an important and exciting therapeutic target toward human cancer. 3D-QSAR and docking studies were performed to explore the interaction of the BRAF with a series of pyridopyrazinones. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were carried out in terms of their potential for predictability. The CoMFA and CoMSIA models using 71 compounds in the training set gave r _cv² values of 0.567 and 0.662, r ² values of 0.900 and 0.907, respectively. The 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained by 3D-QSAR models may be useful to design novel potential BRAF inhibitors.     

Molecular docking and 3D-QSAR studies on the MAPKAP-K2 inhibitors

Mitogen-activated protein kinase-activated protein kinase 2 (MAPKAP-K2) has been identified as a drug target for the treatment of inflammatory diseases. Therefore, there is an urgent need to develop new classes of MAPKAP-K2 inhibitors. To understand the structure activity correlation of MAPKAP-K2 inhibitors, we have carried out a molecular docking study and three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling. Both comparative molecular field analysis ( $r_{\text{cv}}^{2}$  = 0.602, $r_{\text{ncv}}^{2}$  = 0.955) and comparative molecular similarity indices analysis ( $r_{\text{cv}}^{2}$  = 0.546, $r_{\text{ncv}}^{2}$  = 0.891) models were generated using the training set on the basis of the common substructure-based alignment and gave reasonable results. The structural insights obtained from both the 3D-QSAR contour maps and molecular docking help to better interpret the structure activity relationship. The results obtained from this study will be useful in the design of potent MAPKAP-K2 inhibitors.     

Molecular docking and 3D-QSAR studies on checkpoint kinase 1 inhibitors

Checkpoint kinase 1(Chk1) is a promising target for cancer treatment. Here three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on 174 1,4-dihydroindeno[1,2-c]pyrazole inhibitors of Chk1 using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Two satisfactory ligand-based QSAR models were built (CoMFA model: q ² = 0.541, r ² = 0.880, CoMSIA model: q ² = 0.590, r ² = 0.902). The docking-based studies presented a detailed understanding of interaction between the inhibitors and Chk1. The obtained QSAR models are highly predictable (CoMFA model: q ² = 0.567, r ² = 0.891, CoMSIA model: q ² = 0.596, r ² = 0.917). The models were further validated by an external testing set obtaining $ r_{\text{pred}}^{2} $ r pred 2 values 0.896 and 0.923 for CoMFA and CoMSIA, respectively. So our models might be helpful for further modification of 1,4-dihydroindeno[1,2-c]pyrazole derivatives.     

3D-QSAR and docking studies of piperidine carboxamide derivatives as ALK inhibitors

Anaplastic lymphoma kinase (ALK) is an important and attractive target for the design of new anticancer drugs. In the present study, quantitative structure–activity relationship (QSAR) models of piperidine carboxamide derivatives against ALK were developed by CoMFA and CoMSIA approaches. Both the CoMFA and CoMSIA models yielded significant statistical results. The results of the QSAR model indicated the importance of steric, electrostatic, and hydrophobic properties in the potent ALK inhibitors. Furthermore, molecular docking of the most active compound 25 with the active site of ALK was also investigated. The outcomes of this study may result in a better understanding of the inhibition mechanism of ALK and aided in the development of new and more potent anticancer drugs.     

3D-QSAR and molecular docking studies of hydroxamic acids as peptide deformylase inhibitors

Comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and molecular docking study were conducted on hydroxamic acids as potent peptide deformylase (PDF) inhibitors. The optimal CoMFA model gave statistically significant results with q ² and r ² values of 0.568 and 0.956, respectively. The optimal CoMSIA model with combination of steric, hydrophobic and H-bond donor fields resulted in the best results with q ² and r ² values of 0.722 and 0.958, respectively. These two models were validated by an external test set of eight compounds with satisfactory predictive r ² values of 0.810 and 0.820, respectively. The contour plots of molecular fields indicated that electrostatic and bulky groups substituted at the R₁ position, and electropositive and small substituted at R₂ position were favorable for the inhibitory activity. In addition, FlexX docking was employed to investigate the binding mode between PDF and its inhibitors. It was found that hydrogen bond interactions might be an important factor for binding affinity of inhibitors in the hydrophobic cavity. Based on the optimal CoMSIA model and FlexX docking, a series of PDF inhibitors with high predictive activities have been designed. This work might provide valuable information in designing more promising PDF inhibitors.     

蛋白酪氨酸磷酸酶1B抑制剂的分子对接及三维定量构效关系研究

目的对文献报道的一系列芳环取代噻唑类蛋白酪氨酸磷酸酶1B(PTP1B)抑制剂进行分子对接及三维定量构效关系(3D-QSAR)研究。方法应用Surflex-Dock进行分子对接结合模式研究,并用比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)方法进行三维定量构效关系研究,建立具有良好预测能力的3D-QSAR模型。结果对接结果表明,该类结构可以很好地占据PTP1B的3个关键结合位点,大大提高了抑制剂与酶的亲和力。所建立的CoMFA模型交叉验证系数q~2为0.644,CoMSIA模型交叉验证系数q~2为0.719。结论获得的CoMFA和CoMSIA模型具有可靠的预测能力,可应用于指导该类化合物的设计。     

3D-QSAR and docking studies of HIV-1 protease inhibitors using R-group search and Surflex-dock

In this paper, a three-dimensional quantitative structure–activity relationships study for 38 HIV-1 protease inhibitors was established using Topomer CoMFA. The multiple correlation coefficients of fitting, cross-validation, and external validation were 0.959, 0.867, and 0.964, respectively. The results indicated that the model obtained has both favorable estimation stability and good prediction capability. Topomer Search was used to search R-group from ZINC database. As the result, a series of R-groups with relatively high activity contribution was obtained. By No. 32 molecule filtering, 10 Ra and 6 Rb groups were selected. We employed the 10 Ra and 6 Rb groups to alternately substitutes for the Ra and Rb of sample 32. Finally, we designed 60 new compounds with higher activity than that of the template molecule. The results suggested the Topomer Search technology could be effectively used to screen and design new HIV-1 protease inhibitors and has good predictive capability to guide the design of new HIV/AIDS drugs. As the ligands, the training molecules and new designed compounds were used for molecular docking to study the interaction mode with the protein receptor. As the results, we found that the ligands would form the hydrogen-bonding interactions with Asp25, Asp29, Asp30, Gly48, and Ile50 of the protein receptor generally.     

Molecular docking and 3D-QSAR studies of 2-substituted 1-indanone derivatives as acetylcholinesterase inhibitors

Aim： To explore the binding mode of 2-substituted 1-indanone derivatives with acetylcholinesterase （ACHE） and provide hints for the future design of new de- rivatives with higher potency and specificity. Methods： The GOLD-docking con- formations of the compounds in the active site of the enzyme were used in subse- quent studies. The highly reliable and predictive three-dimensional quantitative structure-activity relationship （3D-QSAR） models were achieved by comparative molecular field analysis （CoMFA） and comparative molecular similarity analysis （CoMSIA） methods. The predictive capabilities of the models were validated by an external test set. Moreover, the stabilities of the 3D-QSAR models were veri- fied by the leave-4-out cross-validation method. Results： The CoMFA and CoMSIA models were constructed successfully with a good cross-validated coef- ficient （q2） and a non-cross-validated coefficient （r2）. The q2 and r2 obtained from the leave- 1-out cross validation method were 0.784 and 0.974 in the CoMFA model and 0.736 and 0.947 in the CoMSIA model, respectively. The coefficient isocontour maps obtained from these models were compatible with the geometrical and physi- cochemical properties of ACHE. Conclusion： The contour map demonstrated that the binding affinity could be enhanced when the small protonated nitrogen moi- ety was replaced by a more hydrophobic and bulky group with a highly partial positive charge. The present study provides a better understanding of the inter- action between the inhibitors and ACHE, which is helpful for the discovery of new compounds with more potency and selective activity.     

Molecular docking and 3D-QSAR studies on gag peptide analogue inhibitors interacting with human cyclophilin A

The interaction of a series gag peptide analogues with human cyclophilin A (hCypA) have been studied employing molecular docking and 3D-QSAR approaches. The Lamarckian Genetic Algorithm (LGA) and divide-and-conquer methods were applied to locate the binding orientations and conformations of the inhibitors interacting with hCypA. Good correlations between the calculated interaction free energies and experimental inhibitory activities suggest that the binding conformations of these inhibitors are reasonable. A novel interaction model was identified for inhibitors 11, 15, and 17 whose N-termini were modified by addition of the deaminovaline (Dav) group and the C-termini of 15 and 17 were modified by addition of a benzyl group. Accordingly, two new binding sites (sites A and D in Figure 1) were revealed, which show a strong correlation with inhibitor potency and thus can be used as a starting point for new inhibitor design. In addition, two predictive 3D-QSAR models were obtained by CoMFA and CoMSIA analyses based on the binding conformations derived from the molecular docking calculations. The reasonable r(cross)(2) (cross-validated) values 0.738 and 0.762 were obtained for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by four peptide analogues test set. The CoMFA and CoMSIA field distributions are in general agreement with the structural characteristics of the binding groove of hCypA. This indicates the reasonableness of the binding model of the inhibitors with hCypA. Considering all these results together with the valuable clues of binding from references published recently, reasonable pharmacophore elements have been suggested, demonstrating that the 3D-QSAR models about peptide analogue inhibitors are expected to be further employed in predicting activities of the novel compounds for inhibiting hCypA.     

Molecular modeling studies on 3,4-dihydroquinazolines as trypanothione reductase inhibitors using 3D-QSAR and docking approaches

The trypanothione reductase (TryR) has been used as a key validated target to guide drug discovery for human African trypanosomiasis (HAT). 3D-QSAR and docking studies were performed on a series of 3,4-dihydroquinazolines as TryR inhibitors to establish a molecular model for new drug design. The CoMFA and CoMSIA models resulted from 53 molecules gave r _cv ² values of 0.591 and 0.574, r ² values of 0.968 and 0.943, respectively. The external validation indicated that CoMSIA model with a valid r _m ² value of 0.864 exhibited better predictive power than CoMFA model. 3D contour maps generated from CoMFA and CoMSIA along with the docking analyses have identified several key features responsible for the activity. A set of analogs were proposed by utilizing the results revealed in the present study, and were predicted with significantly improved potencies in the developed models. The results can be served as a useful guideline for designing novel 3,4-dihydroquinazoline derivatives with improved activity against human African trypanosomes.     

3D-QSAR and molecular docking studies on substituted isothiazole analogs as inhibitors against MEK-1 kinase

MEK-1 and MEK-2 are dual-specificity kinases and important components in the mitogen-activated protein kinase pathway. These enzymes are crucial for normal cell survival and are also expressed in several types of cancers, making them important targets for drug design. We have applied an integrated in silico approach that combines comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular docking to study the structural determinants for the recognition of substituted isothiazole analogs as allosteric inhibitors against MEK-1 kinase. The best 3D-QSAR models for comparative molecular field analysis and comparative molecular similarity indices analysis were selected based on statistical parameters. 3D contour maps suggested that bulky or long-chain substitutions at the X position on the core part decrease the inhibitory activity, and the presence of a hydrogen bond donor substitution enhances the activity. The bulky and electronegative substitutions at the Y position on the core part enhance the activity of the inhibitors. Molecular docking studies reveal a large and hydrophobic pocket that accommodates the Y substitution and a polar pocket that accommodates substitutions on the X position and forms hydrogen bonding interactions with MEK-1 kinase. The results of the 3D-QSAR analysis corroborate with the molecular docking results, and our findings will serve as a basis for further development of better allosteric inhibitors of MEK-1 kinase against several cancers.     

Design of novel focal adhesion kinase inhibitors using 3D-QSAR and molecular docking

Focal adhesion kinase (FAK) plays a primary role in regulating the activity of many signaling molecules. Increased FAK expression has been implicated in a series of cellular processes, including cell migration and survival. Inhibiting the activity of FAK for cancer therapy is currently under investigation. Hence, FAK and its inhibitors have been the subject of intensive research. To understand the structural factors affecting inhibitory potency, molecular docking and 3D-QSAR modeling were studied in this project. CoMFA and CoMSIA methods were used for deriving 3D-QSAR models, which were trained with 78 compounds and then were evaluated for predictive ability with additional 19 compounds. Two substructure-based 3D-QSAR models, including CoMFA model (r ² = 0.930; q ² = 0.629) and CoMSIA model (r ² = 0.952; q ² = 0.586), had a good quality to predict the biological activities of new compounds. Meanwhile, using the flexible docking strategy, two docking-based 3D-QSAR models (CoMFA with r ² = 0.914; q ² = 0.594; CoMSIA with r ² = 0.914; q ² = 0.524) were also constructed. The structure–activity relationship has been illustrated clearly by the contour maps gained from the 3D-QSAR models in combination with the docked binding structures. All the results indicated that it might be useful in the rational design of novel FAK inhibitors.     

Azetidine-based inhibitors of dipeptidyl peptidase IV (DPP IV)

The structure-activity relationships of azetidine-based DPP IV inhibitors will be discussed in detail in the following review. The azetidine-based DPP IV inhibitors can be divided into three main subtypes, the 2-cyanoazetidines, 3-fluoroazetidines and 2-ketoazetidines. These subtypes have been explored and structure-activity relationships have been established by several groups. Several compounds within each of these subtypes display sub micromolar potency against DPP IV. The most potent cyanoazetidines and ketoazetidines have large, hydrophobic amino acid groups bound to the azetidine nitrogen and display activities below 100 nM. DPP IV inhibition is not sensitive to stereochemistry at the 2-position as both 2-(R)- and 2-(S)-cyano and -keto azetidines display similar inhibitory potencies. While these "warhead"-based cyano- and ketoazetidines have the potential for covalent, bond-forming inhibition, they can also react to internally cyclize into inactive ketopiperazines and dihydroketopyrazine. Thus, chemical instability was also explored for compounds in these two subtypes and certain members of the cyanoazetidine series display aqueous stability comparable to the closely related cyanopyrrolidines. Select 3-fluoroazetidines also display inhibitory potencies below 1 microM without the propensity for cyclization and chemical instability associated with the other subseries.     

Molecular docking, 3D-QSAR studies, and in silico ADME prediction of p-aminosalicylic acid derivatives as neuraminidase inhibitors

Neuraminidase (NA) is a major glycoprotein of influenza virus which is essential for viral infection. It offers a potential target for antiviral drug design and discovery. To develop novel potent neuraminidase inhibitors (NAI), Surflex-Dock was employed to dock 40 hydrophobic p-aminosalicylic acid derivatives into the active site of NA. The 3D-quantitative structure-activity relationship studies involving comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were carried out on 40 molecules. Both CoMFA (q(2) = 0.628, r(2) = 0.697) and CoMSIA (q(2) = 0.746, r(2) = 0.816) gave reasonable results. A preliminary pharmacokinetic profile of these NAI was also performed on the basis of Volsurf predictions. The results obtained from this study will be useful in the design of novel potent NAI.     

The unique properties of dipeptidyl-peptidase IV (DPP IV / CD26) and the therapeutic potential of DPP IV inhibitors

This review deals with the properties and functions of dipeptidyl peptidase IV (DPP IV, EC 3.4.14.5). This membrane anchored ecto-protease has been identified as the leukocyte antigen CD26. The following aspects of DPP IV/CD26 will be discussed : the structure of DPP IV and the new family of serine proteases to which it belongs, the substrate specificity, the distribution in the human body, specific DPP IV inhibitors and the role of CD26 in the intestinal and renal handling of proline containing peptides, in cell adhesion, in peptide metabolism, in the immune system and in HIV infection. Especially the latest developments in the search for new inhibitors will be reported as well as the discovery of new natural substrates for DPP IV such as the glucagon-like peptides and the chemokines. Finally the therapeutical perspectives for DPP IV inhibitors will be discussed.