Molecular Modeling Studies of 4,5-Dihydro-1H-pyrazolo[4,3-h] quinazoline Derivatives as Potent CDK2/Cyclin A Inhibitors Using 3D-QSAR and Docking

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r(2) (cv) values of 0.747 and 0.518 and r(2) values of 0.970 and 0.934, respectively. 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 from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.     

Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) Studies on α(1A)-Adrenergic Receptor Antagonists Based on Pharmacophore Molecular Alignment

The α(1A)-adrenergic receptor (α(1A)-AR) antagonist is useful in treating benign prostatic hyperplasia, lower urinary tract symptoms, and cardiac arrhythmia. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a set of α(1A)-AR antagonists of N-aryl and N-nitrogen class. Statistically significant models constructed from comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were established based on a training set of 32 ligands using pharmacophore-based molecular alignment. The leave-oneout cross-validation correlation coefficients were q(2) (CoMFA) = 0.840 and q(2) (CoMSIA) = 0.840. The high correlation between the cross-validated/predicted and experimental activities of a test set of 12 ligands revealed that the CoMFA and CoMSIA models were robust (r(2) (pred) (/CoMFA) = 0.694; r(2) (pred) (/CoMSIA) = 0.671). The generated models suggested that electrostatic, hydrophobic, and hydrogen bonding interactions play important roles between ligands and receptors in the active site. Our study serves as a guide for further experimental investigations on the synthesis of new compounds. Structural modifications based on the present 3D-QSAR results may lead to the discovery of other α(1A)-AR antagonists.     

Combined pharmacophore modeling, docking, and 3D-QSAR studies of PLK1 inhibitors

Polo-like kinase 1, an important enzyme with diverse biological actions in cell mitosis, is a promising target for developing novel anticancer drugs. A combined molecular docking, structure-based pharmacophore modeling and three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on a set of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as PLK1 inhibitors. The common substructure, molecular docking and pharmacophore-based alignment were used to develop different 3D-QSAR models. The comparative molecular field analysis (CoMFA) and comparative molecule similarity indices analysis (CoMSIA) models gave statistically significant results. These models showed good q(2) and r(2) (pred) values and revealed a good response to test set validation. All of the structural insights obtained from the 3D-QSAR contour maps are consistent with the available crystal structure of PLK1. The contour maps obtained from the 3D-QSAR models in combination with the structure based pharmacophore model help to better interpret the structure-activity relationship. These satisfactory results may aid the design of novel PLK1 inhibitors. This is the first report on 3D-QSAR study of PLK1 inhibitors.     

3D-QSAR and Molecular Docking Studies on Fused Pyrazoles as p38α Mitogen-Activated Protein Kinase Inhibitors

The p38α mitogen-activated protein kinase (MAPK) has become an attractive target for the treatment of many diseases such as rheumatoid arthritis, inflammatory bowel disease and Crohn's disease. In this paper, 3D-QSAR and molecular docking studies were performed on 59 p38α MAPK inhibitors. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to determine the structural requirements for potency in inhibiting p38α MAPK. The resulting model of CoMFA and CoMSIA exhibited good r(2) (cv) values of 0.725 and 0.609, and r(2) values of 0.961 and 0.905, respectively. Molecular docking was used to explore the binding mode between the inhibitors and p38α MAPK. We have accordingly designed a series of novel p38α MAPK inhibitors by utilizing the structure-activity relationship (SAR) results revealed in the present study, which were predicted with excellent potencies in the developed models. The results provided a useful guide to design new compounds for p38α MAPK inhibitors.     

Inhibitory mode of N-phenyl-4-pyrazolo[1,5-b] pyridazin-3-ylpyrimidin-2-amine series derivatives against GSK-3: molecular docking and 3D-QSAR analyses

Glycogen synthase kinase 3 (GSK-3) inhibition is an important research topic because of its wide range of associated health implications. The interaction mode of a series of N-phenyl-4-pyrazolo[1,5-b]pyridazin-3-ylpyrimidin-2-amine compounds with human GSK-3 has been studied using molecular docking and 3D-QSAR approaches. In the 3D-QSAR studies, the molecular alignment and conformation determination are so important that they affect the success of a model. Flexible docking (AutoDock3.0.5) was used for the determination of 'active' conformation and molecular alignment. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to develop 3D-QSAR models of 80 N-phenyl-4-pyrazolo[1,5-b]pyridazin-3-ylpyrimidin-2-amine compounds. The r(2) values were 0.870 and 0.861 for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by 10 compounds of the test set. Mapping these models back to the topology of the active site of GSK-3 led to a better understanding of the vital N-phenyl-4-pyrazolo[1,5-b]pyridazin-3-ylpyrimidin-2-amines-GSK-3 interactions. The results demonstrate that combination of ligand-based and receptor-based modeling is a powerful approach to build 3D-QSAR models. The interaction mode from this study may be helpful for the design of a novel inhibitor and guide the selection of candidate sites for further experimental studies on site-directed mutagenesis.     

Investigation of Antigen-Antibody Interactions of Sulfonamides with a Monoclonal Antibody in a Fluorescence Polarization Immunoassay Using 3D-QSAR Models

A three-dimensional quantitative structure-activity relationship (3D-QSAR) model of sulfonamide analogs binding a monoclonal antibody (MAb(SMR)) produced against sulfamerazine was carried out by Distance Comparison (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA). The affinities of the MAb(SMR), expressed as Log(10)IC(50), for 17 sulfonamide analogs were determined by competitive fluorescence polarization immunoassay (FPIA). The results demonstrated that the proposed pharmacophore model containing two hydrogen-bond acceptors, two hydrogen-bond donors and two hydrophobic centers characterized the structural features of the sulfonamides necessary for MAb(SMR) binding. Removal of two outliers from the initial set of 17 sulfonamide analogs improved the predictability of the models. The 3D-QSAR models of 15 sulfonamides based on CoMFA and CoMSIA resulted in q(2) (cv) values of 0.600 and 0.523, and r(2) values of 0.995 and 0.994, respectively, which indicates that both methods have significant predictive capability. Connolly surface analysis, which mainly focused on steric force fields, was performed to complement the results from CoMFA and CoMSIA. This novel study combining FPIA with pharmacophore modeling demonstrates that multidisciplinary research is useful for investigating antigen-antibody interactions and also may provide information required for the design of new haptens.     

3D-QSAR and Molecular Docking Studies on Derivatives of MK-0457, GSK1070916 and SNS-314 as Inhibitors against Aurora B Kinase

Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q(2) = 0.605, r(2) (pred) = 0.826), (q(2) = 0.52, r(2) (pred) = 0.798) and (q(2) = 0.582, r(2) (pred) = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors.     

Pharmacophore and Molecular Docking Guided 3D-QSAR Study of Bacterial Enoyl-ACP Reductase (FabI) Inhibitors

Enoyl acyl carrier protein (ACP) reductase (FabI) is a potential target for the development of antibacterial agents. Three-dimensional quantitative structure-activity relationships (3D-QSAR) for substituted formamides series of FabI inhibitors were investigated using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Pharmacophore and molecular docking methods were used for construction of the molecular alignments. A training set of 36 compounds was performed to create the 3D-QSAR models and their external predictivity was proven using a test set of 11 compounds. Graphical interpretation of the results revealed important structural features of the formamides related to the active site of FabI. The results may be exploited for further optimization of the design of new potent FabI inhibitors.     

Structural Determination of Three Different Series of Compounds as Hsp90 Inhibitors Using 3D-QSAR Modeling, Molecular Docking and Molecular Dynamics Methods

Hsp90 is involved in correcting, folding, maturation and activation of a diverse array of client proteins; it has also been implicated in the treatment of cancer in recent years. In this work, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), molecular docking and molecular dynamics were performed on three different series of Hsp90 inhibitors to build 3D-QSAR models, which were based on the ligand-based or receptor-based methods. The optimum 3D-QSAR models exhibited reasonable statistical characteristics with averaging internal q(2) > 0.60 and external r(2) (pred) > 0.66 for Benzamide tetrahydro-4H-carbazol-4-one analogs (BT), AT13387 derivatives (AT) and Dihydroxylphenyl amides (DA). The results revealed that steric effects contributed the most to the BT model, whereas H-bonding was more important to AT, and electrostatic, hydrophobic, H-bond donor almost contributed equally to the DA model. The docking analysis showed that Asp93, Tyr139 and Thr184 in Hsp90 are important for the three series of inhibitors. Molecular dynamics simulation (MD) further indicated that the conformation derived from docking is basically consistent with the average structure extracted from MD simulation. These results not only lead to a better understanding of interactions between these inhibitors and Hsp90 receptor but also provide useful information for the design of new inhibitors with a specific activity.     

Pyrrolo[3,2-d]pyrimidine Derivatives as Type II Kinase Insert Domain Receptor (KDR) Inhibitors: CoMFA and CoMSIA Studies

Kinase insert domain receptor (KDR) inhibitors have been proved to be very effective anticancer agents. Molecular docking, 3D-QSAR methods, CoMFA and CoMSIA were performed on pyrrolo[3,2-d]pyrimidine derivatives as non-ATP competitive KDR inhibitors (type II). The bioactive conformation was explored by docking one potent compound 20 into the active site of KDR in its DFG-out inactive conformation. The constructed CoMFA and CoMSIA models produced statistically significant results with the cross-validated correlation coefficients q(2) of 0.542 and 0.552, non-cross-validated correlation coefficients r(2) of 0.912 and 0.955, and predicted correction coefficients r(2) (pred) of 0.913 and 0.897, respectively. These results ensure the CoMFA and CoMSIA models as a tool to guide the design of a series of new potent KDR inhibitors.     

Studies on [5,6]-Fused Bicyclic Scaffolds Derivatives as Potent Dual B-RafV600E/KDR Inhibitors Using Docking and 3D-QSAR Approaches

Research and development of multi-target inhibitors has attracted increasing attention as anticancer therapeutics. B-Raf^V600E synergistically works with vascular endothelial growth factor receptor 2 (KDR) to promote the occurrence and progression of cancers, and the development of dual-target drugs simultaneously against these two kinds of kinase may offer a better treatment advantage. In this paper, docking and three-dimensional quantitative structure activity relationship (3D-QSAR) studies were performed on a series of dual B-Raf/KDR inhibitors with a novel hinge-binding group, [5,6]-fused bicyclic scaffold. Docking studies revealed optimal binding conformations of these compounds interacting with both B-Raf and KDR. Based on these conformations, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) 3D-QSAR models were constructed, and the best CoMFA (q² = 0.542, r² = 0.989 for B-Raf; q² = 0.768, r² = 0.991 for KDR) and CoMSIA models (q² = 0.519, r² = 0.992 for B-Raf; q² = 0.849, r² = 0.993 for KDR) were generated. Further external validations confirmed their predictability, yielding satisfactory correlation coefficients (r²_pred = 0.764 (CoMFA), r²_pred = 0.841 (CoMSIA) for B-Raf, r²_pred = 0.912 (CoMFA), r²_pred = 0.846 (CoMSIA) for KDR, respectively). Through graphical analysis and comparison on docking results and 3D-QSAR contour maps, key amino acids that affect the ligand-receptor interactions were identified and structural features influencing the activities were discussed. New potent derivatives were designed, and subjected to preliminary pharmacological evaluation. The study may offer useful references for the modification and development of novel dual B-Raf/KDR inhibitors.     

Structural Determinants of CX-4945 Derivatives as Protein Kinase CK2 Inhibitors: A Computational Study

Protein kinase CK2, also known as casein kinase-2, is involved in a broad range of physiological events including cell growth, proliferation and suppression of apoptosis which are related to human cancers. A series of compounds were identified as CK2 inhibitors and their inhibitory activities varied depending on their structures. In order to explore the structure-activity correlation of CX-4945 derivatives as inhibitors of CK2, in the present study, a set of ligand- and receptor-based 3D-QSAR models were developed employing Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA). The optimum CoMFA (R(cv) (2) = 0.618, R(pred) (2) = 0.892) and CoMSIA (R(cv) (2) = 0.681, R(pred) (2) = 0.843) models exhibited reasonable statistical characteristics for CX-4945 derivatives. The results indicated that electrostatic effects contributed the most to both CoMFA and CoMSIA models. The combination of docking analysis and molecular dynamics (MD) simulation showed that Leu45, Lys68, Glu81, Val116, Asp175 and Trp176 of CK2 which formed several direct or water-bridged H-bonds with CX-4945 are crucial for CX-4945 derivatives recognition to CK2. These results can offer useful theoretical references for designing more potent CK2 inhibitors.     

Docking-Based 3D-QSAR Studies for 1,3,4-oxadiazol-2-one Derivatives as FAAH Inhibitors

This work aimed to construct 3D-QSAR CoMFA and CoMSIA models for a series of 31 FAAH inhibitors, containing the 1,3,4-oxadiazol-2-one moiety. The obtained models were characterized by good statistical parameters: CoMFA Q² = 0.61, R² = 0.98; CoMSIA Q² = 0.64, R² = 0.93. The CoMFA model field contributions were 54.1% and 45.9% for steric and electrostatic fields, respectively. In the CoMSIA model, electrostatic, steric, hydrogen bond donor, and hydrogen acceptor properties were equal to 34.6%, 23.9%, 23.4%, and 18.0%, respectively. These models were validated by applying the leave-one-out technique, the seven-element test set (CoMFA r²_test-set = 0.91; CoMSIA r²_test-set = 0.91), a progressive scrambling test, and external validation criteria developed by Golbraikh and Tropsha (CoMFA r²₀ = 0.98, k = 0.95; CoMSIA r²₀ = 0.98, k = 0.89). As the statistical significance of the obtained model was confirmed, the results of the CoMFA and CoMSIA field calculation were mapped onto the enzyme binding site. It gave us the opportunity to discuss the structure–activity relationship based on the ligand–enzyme interactions. In particular, examination of the electrostatic properties of the established CoMFA model revealed fields that correspond to the regions where electropositive substituents are not desired, e.g., in the neighborhood of the 1,3,4-oxadiazol-2-one moiety. This highlights the importance of heterocycle, a highly electronegative moiety in this area of each ligand. Examination of hydrogen bond donor and acceptor properties contour maps revealed several spots where the implementation of another hydrogen-bond-donating moiety will positively impact molecules’ binding affinity, e.g., in the neighborhood of the 1,3,4-oxadiazol-2-one ring. On the other hand, there is a large isopleth that refers to the favorable H-bond properties close to the terminal phenoxy group of a ligand, which means that, generally speaking, H-bond acceptors are desired in this area.     

Combined 3D-QSAR and Docking Modelling Study on Indolocarbazole Series Compounds as Tie-2 Inhibitors

Tie-2, a kind of endothelial cell tyrosine kinase receptor, is required for embryonic blood vessel development and tumor angiogenesis. Several compounds that showed potent activity toward this attractive anticancer drug target in the assay have been reported. In order to investigate the structure-activity correlation of indolocarbazole series compounds and modify them to improve their selectivity and activity, 3D-QSAR models were built using CoMFA and CoMSIA methods and molecular docking was used to check the results. Based on the common sketch align, two good QSAR models with high predictabilities (CoMFA model: q(2) = 0.823, r(2) = 0.979; CoMSIA model: q(2) = 0.804, r(2) = 0.967) were obtained and the contour maps obtained from both models were applied to identify the influence on the biological activity. Molecular docking was then used to confirm the results. Combined with the molecular docking results, the detail binding mode between the ligands and Tie-2 was elucidated, which enabled us to interpret the structure-activity relationship. These satisf actory results not only offered help to comprehend the action mechanism of indolocarbazole series compounds, but also provide new information for the design of new potent inhibitors.     

The Three Dimensional Quantitative Structure Activity Relationships (3D-QSAR) and Docking Studies of Curcumin Derivatives as Androgen Receptor Antagonists

Androgen receptor antagonists have been proved to be effective anti-prostate cancer agents. 3D-QSAR and Molecular docking methods were performed on curcumin derivatives as androgen receptor antagonists. The bioactive conformation was explored by docking the potent compound 29 into the binding site of AR. The constructed Comparative Molecular Field Analysis (CoMFA) and Comparative Similarity Indices Analysis (CoMSIA) models produced statistically significant results with the cross-validated correlation coefficients q(2) of 0.658 and 0.567, non-cross-validated correlation coefficients r(2) of 0.988 and 0.978, and predicted correction coefficients r(2) (pred) of 0.715 and 0.793, respectively. These results ensure the CoMFA and CoMSIA models as a tool to guide the design of novel potent AR antagonists. A set of 30 new analogs were proposed by utilizing the results revealed in the present study, and were predicted with potential activities in the developed models.     

Probing Structural Features and Binding Mode of 3-Arylpyrimidin-2,4-diones within Housefly γ-Aminobutyric Acid (GABA) Receptor

In order to obtain structural features of 3-arylpyrimidin-2,4-diones emerged as promising inhibitors of insect γ-aminobutyric acid (GABA) receptor, a set of ligand-/receptor-based 3D-QSAR models for 60 derivatives are generated using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA). The statistically optimal CoMSIA model is produced with highest q(2) of 0.62, r(2) (ncv) of 0.97, and r(2) (pred) of 0.95. A minor/bulky electronegative hydrophilic polar substituent at the 1-/6-postion of the uracil ring, and bulky substituents at the 3'-, 4'- and 5'-positions of the benzene ring are beneficial for the enhanced potency of the inhibitors as revealed by the obtained 3D-contour maps. Furthermore, homology modeling, molecular dynamics (MD) simulation and molecular docking are also carried out to gain a better understanding of the probable binding modes of these inhibitors, and the results show that residues Ala-183(C), Thr-187(B), Thr-187(D) and Thr-187(E) in the second transmembrane domains of GABA receptor are responsible for the H-bonding interactions with the inhibitor. The good correlation between docking observations and 3D-QSAR analyses further proves the model reasonability in probing the structural features and the binding mode of 3-arylpyrimidin-2,4-dione derivatives within the housefly GABA receptor.     

Investigation of the Structure Requirement for 5-HT(6) Binding Affinity of Arylsulfonyl Derivatives: A Computational Study

5-HT(6) receptor has been implicated in a series of diseases including anxiety, depression, schizophrenia and cognitive dysfunctions. 5-HT(6) ligands have been reported to play a significant role in the treatment for central nervous system (CNS) diseases. Presently, a large series of 223 5-HT(6) ligands were studied using a combinational method by 3D-QSAR, molecular docking and molecular dynamics calculations for further improvement of potency. The optimal 3D models exhibit satisfying statistical results with r(2) (ncv), q(2) values of 0.85 and 0.50 for CoMFA, 0.81 and 0.53 for CoMSIA, respectively. Their predictive powers were validated by external test set, showing r(2) (pred) of 0.71 and 0.76. The contour maps also provide a visual representation of contributions of steric, electrostatic, hydrophobic and hydrogen bond fields as well as the prospective binding models. In addition, the agreement between 3D-QSAR, molecular docking and molecular dynamics simulation proves the rationality of the developed models. These results, we hope, may be helpful in designing novel and potential 5-HT(6) ligands.     

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q² (cross-validated correlation coefficient) = 0.557, R²_ncv (non-cross-validated correlation coefficient) = 0.740, R²_pre (predicted correlation coefficient) = 0.749 and Q² = 0.598, R²_ncv = 0.767, R²_pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors.