Identification of potential CRAC channel inhibitors: Pharmacophore mapping, 3D-QSAR modelling,and molecular docking approach

Upregulation of store-operated Ca²⁺ influx via ORAI1, an integral component of the CRAC channel, is responsible for abnormal cytokine release in active rheumatoid arthritis, and therefore ORAI1 has been proposed as an attractive molecular target. In this study, we attempted to predict the mechanical insights of ORAI1 inhibitors through pharmacophore modelling, 3D-QSAR, molecular docking and free energy analysis. Various hypotheses of pharmacophores were generated and from that, a pharmacophore hypothesis with two hydrogen bond acceptors, one hydrogen bond donor and two aromatic rings (AADRR) resulted in a statistically significant 3D-QSAR model (r² = 0.84 and q² = 0.74). We believe that the obtained statistical model is a reliable QSAR model for the diverse dataset of inhibitors against the IL-2 production assay. The visualization of contours in active and inactive compounds generated from the 3D-QSAR models and molecular docking studies revealed major interaction with GLN108, HIS113 and ASP114, and interestingly, these residues are located near the Ca²⁺ selectivity filter region. Free energy binding analysis revealed that Coulomb energy, van der Waals energy and non-polar solvation terms are more favourable for ligand binding. Thus, the present study provides the physical and chemical requirements for the development of novel ORAI1 inhibitors with improved biological activity.     

3D-QSAR,docking, molecular dynamics simulation and free energy calculation studies of some pyrimidine derivatives as novel JAK3 inhibitors

Janus kinase 3 (JAK3) is a promising drug target for the treatment of inflammatory diseases, autoimmune disorders, organ transplant rejection and various cancers. In the present study, 3D-QSAR, docking, MD simulation and MM/PBSA studies were performed on a series of pyrimidine-based JAK3 inhibitors. A reliable COMSIA (q² = 0.717 and r² = 0.986) model was developed and validated using external validation test set, bootstrapping, progressive scrambling and r_m² metrics analyses. Structural requirements identified through contour maps of the model were strategically utilized to computationally design 170 novel JAK3 inhibitors with improved potency. Docking studies were performed on the selected data set and newly designed compounds to show their binding mode and to identify important interacting residues inside the active site of JAK3. In addition, docking results of the selected designed compounds inside the active sites of JAK1, JAK2 and TYK2 indicated their JAK3 selectivity. MD simulation (100 ns) on the docked complex of compound 28 (one of highly active compounds of the data set) assisted in the further exploration of the binding interactions. Some crucial residues like Lys830 (glycine-rich loop), Val836, Ala853, Leu905 (hinge region), Cys909, Asn954, Leu956 and Ala966 were identified. Hydrogen bond interactions with hinge residue Leu905 were critical for the binding of JAK3 inhibitors. Additionally, MM/PBSA calculation provided the binding free energy of the compound 28. Newly designed molecules showed promising results in the preliminary in silico ADMET evaluations. Outcomes of the study can further be exploited to develop potent JAK3 inhibitors.     

Pharmacophore modeling,atom based 3D-QSAR,molecular docking and molecular dynamics studies on Escherichia coli ParE inhibitors

ATP dependent ParE enzyme is as an attractive target for the development of antibacterial agents. Atom based 3D-QSAR model AADHR.187 was developed based on the thirty eight Escherichia coli ParE inhibitors. The generated model showed statistically significant coefficient of determinations for the training (R² = 0.985) and test (R² = 0.86) sets. The cross-validated correlation coefficient (q2) was 0.976. The utility of the generated model was validated by the enrichment study. The model was also validated with structurally diverse external test set of ten compounds. Contour plot analysis of the generated model unveiled the chemical features necessary for the E. coli ParE enzyme inhibition. Extra-precision docking result revealed that hydrogen bonding and ionic interactions play a major role in ParE protein-ligand binding. Binding free energy was computed for the data set inhibitors to validate the binding affinity. A 30-ns molecular dynamics simulation showed high stability and effective binding of inhibitor 34 within the active site of ParE enzyme. Using the best fitted model AADHR.187, pharmacophore-based high-throughput virtual screening was performed to identify virtual hits. Based on the above studies three new molecules are proposed as E. coli ParE inhibitors with high binding affinity and favourable ADME properties.     

3D-QSAR study,docking molecular and simulation dynamic on series of benzimidazole derivatives as anti-cancer agents

Benzimidazole is an important heterocyclic organic compound which has a structural analogy to nucleotides found in human body and hence is an important pharmacophore in medicinal chemistry. The anti-cancer activities for a diverse set of benzimidazole as anti-cancer agents against breast cancer cell line (MCF7) assay have been subjected to 3D-QSAR (3-Dimensional Quantitative Structural-Activity Relationship) studies. Both CoMFA and CoMSIA models exhibit significant results in terms of statistical parameters as determination coefficients R² > 0.9 and Leave One Out cross-validation determination coefficients Q²> 6. The predictive quality of both 3D QSAR models have been assessed by external validation and Y-randomization test. Five new compounds have been designed and predicted by in silico ADMET method. In the second part, we have used the docking molecular and simulation dynamics (MD) to investigate the bonding interactions and stability of the designed compounds into the Pin1. Then, we have compared them to Trastuzumab and Tamoxifen as a standard inhibitors drug of breast cancer. The designed compounds form stable hydrogen and hydrophobic bonding interactions with the residues Lys63, Gln131, Ser154, Arg 68 and Arg69 of Pin1 receptor during 100 ns as a time of the simulation. The obtained results showed that the new benzimidazole are useful as a template for future design of more potent inhibitors against breast cancer cell lines (MCF7).     

Combined 2D and 3D-QSAR,molecular modelling and docking studies of pyrazolodiazepinones as novel phosphodiesterase 2 inhibitors

Selective inhibition of phosphodiesterase 2 (PDE2) in cells where it is located elevates cyclic guanosine monophosphate (cGMP) and acts as novel analgesic with antinociceptive activity. Three-dimensional quantitative structure–activity relationship (QSAR) studies for pyrazolodiazepinone inhibitors exhibiting PDE2 inhibition were performed using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and Topomer CoMFA, and two-dimensional QSAR study was performed using a Hologram QSAR (HQSAR) method. QSAR models were generated using training set of 23 compounds and were validated using test set of nine compounds. The optimum partial least squares (PLS) for CoMFA-Focusing, CoMSIA-SDH, Topomer CoMFA and HQSAR models exhibited good ‘leave-one-out’ cross validated correlation coefficient (q²) of 0.790, 0.769, 0.840 and 0.787, coefficient of determination (r²) of 0.999, 0.964, 0.979 and 0.980, and high predictive power (r²_pred) of 0.796, 0.833, 0.820 and 0.803 respectively. Docking studies revealed that those inhibitors able to bind to amino acid Gln859 by cGMP binding orientation called ‘glutamine-switch’, and also bind to the hydrophobic clamp of PDE2 isoform, could possess high selectivity for PDE2. From the results of all the studies, structure–activity relationships and structural requirements for binding to active site of PDE2 were established which provide useful guidance for the design and future synthesis of potent PDE2 inhibitors.     

6-氮杂吲唑类Pim-1激酶抑制剂的3D-QSAR、药效团模型研究和分子设计

Pim-1激酶通过作用于多种信号通路或靶点影响肿瘤的发生发展,近年来被认为是肿瘤治疗的良好靶标。本文采用SYBYL-X2.1.1软件中的Topomer CoMFA、GALAHAD模块建立计算机模型,研究39个基于6-氮杂吲唑环的Pim-1激酶抑制剂的三维定量构效关系及药效团特征元素。结果显示,Topomer CoMFA建模所得交叉验证系数(q²)和相关系数(r²)分别为0.756和0.951,结合外部验证表明此3D-QSAR模型具有较高预测能力及较好的统计学稳定性,同时,用等势图描述了R1、R2基团处立体场、静电场对活性的具体影响。药效团研究结果表明,含氢键受体的芳香杂环母核结构,以及侧链取代基中含有芳香杂环结构对化合物的活性贡献较大。最后根据上述模型信息新设计了15个Pim-1激酶抑制剂分子并完成活性预测及分子对接模式研究,其中4个分子的预测pIC₅₀高于建模分子中活性最好的化合物17,Surflex-Dock分析显示新设计分子均与Pim-1激酶形成较强氢键相互作用。基于6-氮杂吲唑环的Pim-1激酶抑制剂的3D-QS...     

The novel 4-hydroxyphenylpyruvate dioxygenase inhibitors in vivo and in silico approach: 3D-QSAR analysis,molecular docking,bioassay and molecular dynamics

4-Hydroxyphenylpyruvate dioxygenase (HPPD) is not only an important target enzyme for the treatment of type I tyrosinemia, but also a new target for design bleaching herbicides, and it plays key role in the biosynthesis of tocopherol and plastoquinone. Thirty-six known active pyridine derivatives were collected, and comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models based on common skeleton were constructed to obtain novel HPPD herbicides with higher activity. Two new HPPD inhibitors were rationally designed and synthesized according to the CoMFA and CoMSIA models and verified by enzyme activity, biological assays, and molecular docking. The promising compound W1 ((E)-5-(3-(4-bromophenyl)acryloyl)-6-hydroxy-2,3-dihydropyridin-4(1H)-one) showed better AtHPPD inhibitory activity, and the bioassay results revealed that some weeds showed bleaching symptoms. The good binding stability of W1 and protein was confirmed by molecular dynamics simulation in 100 ns. These results would be highly useful in the progress of new HPPD inhibitors discovery.     

Pharmacophore modeling, 3D-QSAR,docking, and molecular dynamics simulation on topoisomerase IV inhibitors of wild type Staphylococcus aureus

Staphylococcus aureus is a gram-positive bacterium. It is a foremost cause of skin and respiratory infections, endocarditis, osteomyelitis, Ritter’s disease, and bacteraemia. Topoisomerase enzyme is involved in preventing or correcting topological problems of overwinding or underwinding occurring in DNA before replication process. An exhaustive molecular modeling studies that includes pharmacophore modeling, ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, molecular dynamics simulation, and ADME calculations were performed on isothiazoloquinolones derivatives which are reported as effective inhibitors against topoisomerase IV of wild type S. aureus. In pharmacophore modeling by using pharmacophore alignment and scoring engine (PHASE) a five-point model (AHHRR.3) was generated with existing compounds having statistical significant as correlation coefficient (R ² = 0.954), cross-validation coefficient (Q ² = 0.650), and F value of 130.5. Ligand-based 3D-QSAR study was applied using comparative molecular field analysis (CoMFA) with Q ² = 0.616, R ² = 0.989, and comparative molecular similarity indices analysis (CoMSIA) with Q ² = 0.510, R ² = 0.995. The predictive ability of this model was determined using a test set of molecules that gave acceptable predictive correlation (R ² Pred) values 0.55 and 0.56 for CoMFA and CoMSIA, respectively. Docking and molecular dynamic simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed pharmacophore models and docking methods provide guidance to design enhanced activity molecules.

     

Pharmacophore modelling,atom-based 3D-QSAR generation and virtual screening of molecules projected for mPGES-1 inhibitory activity

COX-2 inhibitors exhibit anticancer effects in various cancer models but due to the adverse side effects associated with these inhibitors, targeting molecules downstream of COX-2 (such as mPGES-1) has been suggested. Even after calls for mPGES-1 inhibitor design, to date there are only a few published inhibitors targeting the enzyme and displaying anticancer activity. In the present study, we have deployed both ligand and structure-based drug design approaches to hunt novel drug-like candidates as mPGES-1 inhibitors. Fifty-four compounds with tested mPGES-1 inhibitory value were used to develop a model with four pharmacophoric features. 3D-QSAR studies were undertaken to check the robustness of the model. Statistical parameters such as r² = 0.9924, q² = 0.5761 and F test = 1139.7 indicated significant predictive ability of the proposed model. Our QSAR model exhibits sites where a hydrogen bond donor, hydrophobic group and the aromatic ring can be substituted so as to enhance the efficacy of the inhibitor. Furthermore, we used our validated pharmacophore model as a three-dimensional query to screen the FDA-approved Lopac database. Finally, five compounds were selected as potent mPGES-1 inhibitors on the basis of their docking energy and pharmacokinetic properties such as ADME and Lipinski rule of five.     

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.     

3D-QSAR and molecular docking study of LRRK2 kinase inhibitors by CoMFA and CoMSIA methods

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modelling was conducted on a series of leucine-rich repeat kinase 2 (LRRK2) antagonists using CoMFA and CoMSIA methods. The data set, which consisted of 37 molecules, was divided into training and test subsets by using a hierarchical clustering method. Both CoMFA and CoMSIA models were derived using a training set on the basis of the common substructure-based alignment. The optimum PLS model built by CoMFA and CoMSIA provided satisfactory statistical results (q² = 0.589 and r² = 0.927 and q² = 0.473 and r² = 0.802, respectively). The external predictive ability of the models was evaluated by using seven compounds. Moreover, an external evaluation set with known experimental data was used to evaluate the external predictive ability of the porposed models. The statistical parameters indicated that CoMFA (after region focusing) has high predictive ability in comparison with standard CoMFA and CoMSIA models. Molecular docking was also performed on the most active compound to investigate the existence of interactions between the most active inhibitor and the LRRK2 receptor. Based on the obtained results and CoMFA contour maps, some features were introduced to provide useful insights for designing novel and potent LRRK2 inhibitors.     

Pharmacophore Modeling and 3D-QSAR Study of Indole and Isatin Derivatives as Antiamyloidogenic Agents Targeting Alzheimer’s Disease

Thirty-six novel indole-containing compounds, mainly 3-(2-phenylhydrazono) isatins and structurally related 1H-indole-3-carbaldehyde derivatives, were synthesized and assayed as inhibitors of beta amyloid (Aβ) aggregation, a hallmark of pathophysiology of Alzheimer’s disease. The newly synthesized molecules spanned their IC₅₀ values from sub- to two-digit micromolar range, bearing further information into structure-activity relationships. Some of the new compounds showed interesting multitarget activity, by inhibiting monoamine oxidases A and B. A cell-based assay in tau overexpressing bacterial cells disclosed a promising additional activity of some derivatives against tau aggregation. The accumulated data of either about ninety published and thirty-six newly synthesized molecules were used to generate a pharmacophore hypothesis of antiamyloidogenic activity exerted in a wide range of potencies, satisfactorily discriminating the ‘active’ compounds from the ‘inactive’ (poorly active) ones. An atom-based 3D-QSAR model was also derived for about 80% of ‘active’ compounds, i.e., those achieving finite IC₅₀ values lower than 100 μM. The 3D-QSAR model (encompassing 4 PLS factors), featuring acceptable predictive statistics either in the training set (n = 45, q² = 0.596) and in the external test set (n = 14, r²_ext = 0.695), usefully complemented the pharmacophore model by identifying the physicochemical features mainly correlated with the Aβ anti-aggregating potency of the indole and isatin derivatives studied herein.     

Design,synthesis, cytotoxicity and 3D-QSAR analysis of new 3,6-disubstituted-1,2,4,5-tetrazine derivatives as potential antitumor agents

We synthesized two new series of 3-substituted-6-(2,5-dimethylpyrazol-1-yl)-1,2,4,5-tetrazines and analysed them for a potential role as antitumor agents. Twenty-two compounds were obtained, and four molecular structures were determined by X-ray diffraction analysis. Using flow cytometry and MTT assay, potential action on cell toxicity was determined for each of the compounds for four cancer cell lines. The potency and selectivity demonstrated by these compounds are dependent on the cancer cell line, where the following compounds were found the most promising agents against certain cell lines: compounds 1i and 1j for HL-60 cells, 1a and 1b on HCT116 cells, 1f on Hela cells and 2h on H1975 cells. The action exerted by these compounds is comparable to the well-known cancer treatment drug etoposide and higher than vatalanib. To arrive at the structural requirements for activity on each cell line, a SAR and 3D-QSAR analysis was carried out. From the 3D-QSAR models, steric and electronic features were identified in the aromatic centres, and were key components for cytotoxic activity on HL-60 cell lines. The cytometry results suggest that some tetrazine derivatives induce apoptosis on HCT116 cells.     

Studies of febuxostat analogues as xanthine oxidase inhibitors through 3D-QSAR,Topomer CoMFA and molecular modeling

Xanthine oxidase, a complex molybdoflavoprotein, catalyzes the hydroxylation of xanthine to uric acid, which has emerged as an important target for gout and hyperuricemia. In this work, a combination of molecular modeling methods was performed on a series of febuxostat analogues as xanthine oxidase inhibitors to establish molecular models for new drug design, including three-dimensional quantitative structure–activity relationship, topomer comparative molecular field analysis (CoMFA), molecular docking and molecular dynamic simulations. The optimal CoMFA model yielded a leave-one-out correlation coefficient (q²) of 0.841 and a non-validated correlation coefficient (r²) of 0.985. The respective q² and r² of the best comparative molecular similarity indices analysis (CoMSIA) model were 0.794 and 0.972, respectively. The Topomer CoMFA model provided a q² of 0.915 and an r² of 0.977. 3D contour maps generated from CoMFA and CoMSIA have identified several key features responsible for the inhibition activity. Molecular modeling was taken to further elucidate the proposed binding conformations of the inhibitors to the protein. The obtained results can be served as a useful guideline for designing novel febuxostat derivatives with improved activity against xanthine oxidase.

     

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。     

3D-QSAR,molecular docking and ADMET studies of thioquinazolinone derivatives against breast cancer

Breast cancer is a deadly disease and the second largest cause of mortality on a worldwide platform. Despite the availability of several cancer treatments, life expectancies stay relatively poor. Consequently, the medicinal chemistry community prioritizes the quick discovery of novel anticancer drugs. In recent years, computational approaches have been widely used to accelerate the drug development process. In light of this, in the current work, we performed three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking analyses on thioquinazolinone derivatives with aromatase enzyme (PDB: 3S7S). External validation was used to validate the prediction capabilities of the generated model. The best CoMSIA (comparative molecular similarity indices analysis) model exhibited the significant values of $Q^2$, $R^{2}and$ $R_{pred}^2$. These findings suggested that the electrostatic, hydrophobic and hydrogen bond donor and acceptor fields have a significant effect on inhibition of breast cancer. Thus, a number of innovative potent aromatase inhibitors were designed and their biological activities were predicted based on the best model. Furthermore, molecular docking studies were carried out for the designed compounds against breast cancer. Additionally, ADMET proprieties were used to evaluate drug-likeness of these novel drug candidates. The most active compounds found by these computational studies could be helpful for synthesis and testing as prospective future anti-cancer treatments.     

靛玉红类CDK1抑制剂的同源模建、分子对接及3D-QSAR研究

细胞周期蛋白依赖性激酶1的异常表达会导致G2期的停滞及多种肿瘤的发生,故CDK1近年来已成为一个理想的治疗靶点. 本文以细胞分裂调控蛋白2的同源体为模板,同源模建了CDK1的结构,并与靛玉红类小分子抑制剂进行分子对接. 分别运用三种叠合方法进行分子叠合,并在此基础上采用Sybyl 7.1中的比较分子场分析(CoMFA)模块及Discovery Studio 3.0中的三维定量构效关系(3D-QSAR)模块(以下简称为DS)分别建立了3D-QSAR模型. 其中,将分子对接叠合与公共骨架叠合联合运用的叠合方法所得3D-QSAR模型的评价参数是最佳的(CoMFA：q²=0.681,r²=0.909,r_pred.²=0.836; DS：q²=0.579,r²=0.971,r_pred.²=0.795,其中q²为交叉验证系数,r²为非交叉验证系数). 本文的研究结果在对靛玉红类小分子进行结构修饰设计出新的CDK1抑制剂方面,可提供重要的理论基础.