Furanone derivatives as new inhibitors of CDC7 kinase: development of structure activity relationship model using 3D QSAR,molecular docking,and in silico ADMET

Cell division cycle 7 (CDC7) is a serine/threonine kinase, which plays a vital role in the replication initiation of DNA synthesis. Overexpression of the CDC7 in various tumor growths and in cell proliferation makes it a promising target for treatment of cancers. To investigate the binding between the CDC7 and furanone inhibitors, and in order to design highly potent inhibitors, a three-dimensional quantitative structure activity relationship (3D-QSAR) with molecular docking was performed. The optimum CoMSIA model showed significant statistical quality on all validation methods with a determination coefficient (R²?=?0.945), bootstrapping R² mean (BS-R²?=?0.960), and leave-one-out cross-validation (Q²) coefficient of 0.545. The predictability of this model was evaluated by external validation using a test set of nine compounds with a predicted determination coefficient R²_test of 0.96, besides the mean absolute error (MAE) of the test set was 0.258 log units. The extracted contour maps were used to identify the important regions, where the modification was necessary to design a new molecule with improved activity. Furthermore, a good consistency between the molecular docking and contour maps strongly demonstrates that the molecular modeling is reliable. Based on those obtained results, we designed several new potent CDC7 inhibitors, and their inhibitory activities were validated by the molecular models. Additionally, those newly designed inhibitors showed promising results in the preliminary in silico ADMET evaluations.     

3D QSAR Studies on Benzyl Phenyl Ether Diamidine Derivatives with Antiprotozoal Activities

Human African trypanosomiasis (HAT) is a neglected tropical disease, and some drugs treating HAT have been used for even more than 60 years. Currently, a series of benzyl phenyl ether diamidine derivatives are discovered, which exhibit high antiprotozoal activities and low cytotoxicity, leading to good development prospects. The comparative molecular field analysis (CoMFA) and the comparative molecular similarity indices analysis (CoMSIA) are used to study the relationship between the structure and antiprotozoal activities. The established 3D QSAR model shows not only significant statistical quality, but also satisfies predictive ability: the best CoMFA model had r² = 0.958 and q² = 0.766, the best CoMSIA model had r² = 0.957 and q² = 0.812, the predictive ability of CoMFA and CoMSIA model were further confirmed by a test set which had 11 compounds, giving the correlation coefficient Q_ext² of 0.792, 0.873, respectively. The contour maps and contribution maps show important features that can improve the antiprotozoal activity: position 3 from substituent R4 should be a low electronegativity group, position 4 from substituent R₄ should have higher electronegativity, substituent R₂ should be selected to a low electronegativity and small bulk group. Together these results may offer some useful theoretical information in designing potential inhibitors.     

Structural basis of pyrazolopyrimidine derivatives as CAMKIIδ kinase inhibitors: insights from 3D QSAR,docking studies and in silico ADMET evaluation

Ca²⁺/calmodulin-dependent protein kinase II (CAMKIIδ) belongs to the serine/threonine kinase family, which is involved in a broad range of cellular events in cell survival and proliferation as well as a number of other signal transduction pathways. Thus, it is regarded a promising target for treatment of cancers. In the present paper, a three-dimensional quantitative structure–activity relationship and molecular docking were applied to investigate a series of new CAMKIIδ inhibitors of pyrazolopyrimidine derivatives. The determination coefficient (R²) and leave-one-out cross-validation coefficient (Q²) of CoMSIA model are 0.676 and 0.956, respectively. The predictive ability of this model was evaluated by the external validation using a test set of eight compounds with a predicted determination coefficient \(R^{ 2}_{\text{test}}\) of 0.80, besides the mean absolute error of the test set was 0.328 log units. Docking results are in concordance with CoMSIA contour maps, gave the information for interactive mode exploration. Based on those satisfactory results, newly designed molecules were predicted with highly potent CAMKIIδ inhibitory activity, additionally, they have showed promising results in the preliminary in silico ADMET evaluations. This study could expand our understanding of pyrazolopyrimidine derivatives as inhibitors of CAMKIIδ and would be of great help in lead optimization for early drug discovery of highly potent CAMKIIδ inhibitors.     

3D QSAR Modeling and Molecular Docking Studies on a Series of Triazole Analogues as Antibacterial Agents

The 3D QSAR analysis using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques is performed on novel nalidixic acid based 1,2,4-triazole derivatives suggested earlier as antibacterial agents. The CoMFA and CoMSIA models employed for a training set of 28 compounds gives reliable values of Q² (0.53 and 0.52, respectively) and R² (0.79 and 0.85, respectively). The contour maps produced by the CoMFA and CoMSIA models are used to determine a three-dimensional quantitative structure-activity relationship. Based on the 3D QSAR contours new molecules with high predicted activities are designed. In addition, surflex-docking is performed to confirm the stability of predicted molecules in the receptor.     

Molecular description of pyrimidine-based inhibitors with activity against FAK combining 3D-QSAR analysis,molecular docking and molecular dynamics

Focal adhesion kinase (FAK) is a promising target for developing more effective anticancer drugs. To better understand the structure-activity relationships and mechanism of actions of FAK inhibitors, a molecular modeling study using 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy analysis were conducted. Two types of satisfactory 3D-QSAR models were generated, comprising the CoMFA model (R²_cv = 0.528, R²_pred = 0.7557) and CoMSIA model (R²_cv = 0.757, R²_pred = 0.8362), for predicting the inhibitory activities of novel inhibitors. The derived contour maps indicate structural characteristics for substituents on the template. Molecular docking, molecular dynamic simulations and binding free energy calculations further reveal that the binding of inhibitors to FAK is mainly contributed from hydrophobic, electrostatic and hydrogen bonding interactions. In addition, some key residues (Arg14, Glu88, Cys90, Arg138, Asn139, Leu141, and Leu155) responsible for ligand-receptor binding are highlighted. All structural information obtained from 3D-QSAR models and molecular dynamics is consist with the available experimental activities. All the results will facilitate the optimization of this series of FAK inhibitors with higher inhibitory activities.     

Combining ligand-based and structure-based drug design approaches to study the structure-activity relationships of a β-carboline derivative series

In this study, we investigated the structure-activity relationships of a series of β-carboline alkaloid derivatives using the 2D-QSAR and molecular docking, in order to identify the mode of interaction between β-carboline derivatives and the PLK1 kinase, and determine their key substituents responsible for the cytotoxic activity. The obtained QSAR models using multiple linear regression (MLR) and partial least squares (PLS) methods showed a high correlation between the experimental activity and the predicted one by PLS (R²_PLS?=?0.82, q²?=?0.72) and MLR (R²_MLR?=?0.82, q²?=?0.72). An external dataset was used to test the extrapolation power of the models which resulted in an R²_PLS (EV)?=?0.76; RMSE?=?0.39. The 2D-QSAR analysis reveals that lipophilicity plays an important role in the cytotoxic activity of this group of β-carboline derivatives. Indeed, the molecular docking study into the active site of the polo-like kinase (PLK1) revealed that the most active ligand 57 shows higher binding energy and interacts, especially by H-bonds and hydrophobic interactions, with the active site of the PLK1 kinase. Consequently, the results obtained from the 2D-QSAR and docking studies provided a useful tool to design new and potent β-carboline derivatives as cytotoxic agents.     

Insight into the structural requirements of benzimidazole derivatives as interleukin‐2 inducible t‐cell kinase inhibitors by computational explorations

In the present work, a set of ligand‐ and receptor‐based 3D‐QSAR models were developed to explore the structure–activity relationship of 109 benzimidazole‐based interleukin‐2‐inducible T‐cell kinase (ITK) inhibitors. In order to reveal the requisite 3D structural features impacting the biological activities, a variety of in silico modeling approaches including the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), docking, and molecular dynamics were applied. The results showed that the ligand‐based CoMFA model (Q² = 0.552, R²_ncv = 0.908, R²_pred = 0.787, SEE = 0.252, SEP = 0.558) and CoMSIA model (Q² = 0.579, R²_ncv = 0.914, R²_pred = 0.893, SEE = 0.240, SEP = 0.538) were superior to other models with greater predictive power. In addition, a combined analysis between the 3D contour maps and docking results showed that: (1) Compounds with bulky or hydrophobic substituents near ring D and electropositive or hydrogen acceptor groups around rings C and D could increase the activity. (2) The key amino acids impacting the receptor–ligand interactions in the binding pocket are Met438, Asp500, Lys391, and Glu439. The results obtained from this work may provide helpful guidelines in design of novel benzimidazole analogs as inhibitors of ITK. © 2013 Wiley Periodicals, Inc.     

Studies on molecular mechanism between SHP2 and pyridine derivatives by 3D-QSAR,molecular docking and MD simulations

BackgroundSrc homology 2 (SH2)-containing protein tyrosine phosphatase 2 (SHP2) as a major phosphatase would affect the development of tumors by regulating several cellular processes, and is a significant potential target for cancer treatment.MethodsIn the present work, a series of pyridine derivatives possessing a wide range of inhibitory activity was employed to investigate the structural requirements by developing three dimensional quantitative structure–activity relationship (3D-QSAR) models using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The results show that CoMFA (R²_cv = 0.646, R²_pred = 0.5587) and CoMSIA (R²_cv = 0.777, R²_pred = 0.7131) have excellent stability and predictability. The relationship between the inhibitory activity and structure of the inhibitors was analyzed by the derived contour maps. Furthermore, the QSAR models were validated by molecular docking and molecular dynamics simulations, which were also applied to reveal the potential molecular mechanism of these inhibitors.FindingsIt was found that Arg110, Asn216, Thr218, Thr252 and Pro490 play a crucial role in stabilizing the inhibitors. Additionally, MM/PBSA calculations provided the binding free energy were also conducted to explain the discrepancy of binding activities. Overall, the outcomes of this work could provide useful information and theoretical guidance for the development of novel and potent SHP2 inhibitors.     

Computational explorations to gain insight into the structural features of TNF-α receptor I inhibitors

TNF-α is a crucial cytokine in the process of inflammatory diseases. The adverse effect of TNF-α is mostly mediated by interaction of TNF-α with TNF-α receptor type I (TNFR1); therefore, discovery of molecules which can bind to TNFR1 preventing TNF-α-receptor complex formation would be of great interest. In the current study, using GRID/GOLPE program, a 3D-QSAR study was conducted on a series of synthetic TNFR1 binders, which resulted in a 3D-QSAR model with appropriate power of predictivity in internal (r²?=?0.94 and q²_LOO?=?0.74) and external (r²?=?0.66 and SDEP?=?0.42) validations. The structural features of TNFR1 inhibitors essential for exerting activity were explored by analyzing the contour maps of the 3D-QSAR model showing that steric interactions and hydrogen bonds are responsible for exerting TNFR1 inhibitory activity. To propose potential chemical entities for TNFR1 inhibition, PubChem database was searched and the selected compounds were virtually tested for anti-TNFR1 activity using the generated model, resulting in two potential anti-TNFR1 compounds. Finally, the possible interactions of the compounds with TNFR1 were investigated using docking studies. The findings in the current work can pave the way for designing more potent anti-TNFR1 inhibitors.     

Strategies to design pyrazolyl urea derivatives for p38 kinase inhibition: a molecular modeling study

The p38 protein kinase is a serine–threonine mitogen activated protein kinase, which plays an important role in inflammation and arthritis. A combined study of 3D-QSAR and molecular docking has been undertaken to explore the structural insights of pyrazolyl urea p38 kinase inhibitors. The 3D-QSAR studies involved comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA). The best CoMFA model was derived from the atom fit alignment with a cross-validated r ² (q ²) value of 0.516 and conventional r ² of 0.950, while the best CoMSIA model yielded a q ² of 0.455 and r ² of 0.979 (39 molecules in training set, 9 molecules in test set). The CoMFA and CoMSIA contour maps generated from these models provided inklings about the influence of interactive molecular fields in the space on the activity. GOLD, Sybyl (FlexX) and AutoDock docking protocols were exercised to explore the protein–inhibitor interactions. The integration of 3D-QSAR and molecular docking has proffered essential structural features of pyrazolyl urea inhibitors and also strategies to design new potent analogues with enhanced activity.     

3D-QSAR and Docking Studies of Pyrido[2,3-d]pyrimidine Derivatives as Wee1 Inhibitors

In order to investigate the inhibiting mechanism and obtain some helpful information for de-signing functional inhibitors against Wee1, three-dimensional quantitative structure-activity relationship (3D-QSAR) and docking studies have been performed on 45 pyrido[2,3-d] pyrim-idine derivatives acting as Wee1 inhibitors. Two optimal 3D-QSAR models with significant statistical quality and satisfactory predictive ability were established, including the CoMFA model (q²=0.707, R²=0.964) and CoMSIA model (q²=0.645, R²=0.972). The external val-idation indicated that both CoMFA and CoMSIA models were quite robust and had high predictive power with the predictive correlation coefficient values of 0.707 and 0.794, essen-tial parameter r²_m values of 0.792 and 0.826, the leave-one-out r²_m(LOO) values of 0.781 and 0.809, r²_m(overall) values of 0.787 and 0.810, respectively. Moreover, the appropriate binding orientations and conformations of these compounds interacting with Wee1 were revealed by the docking studies. Based on the CoMFA and CoMSIA contour maps and docking analyses, several key structural requirements of these compounds responsible for inhibitory activity were identified as follows: simultaneously introducing high electropositive groups to the sub-stituents R1 and R5 may increase the activity, the substituent R2 should be smaller bulky and higher electronegative, moderate-size and strong electron-withdrawing groups for the substituent R3 is advantageous to the activity, but the substituent X should be medium-size and hydrophilic. These theoretical results help to understand the action mechanism and design novel potential Wee1 inhibitors.     

Molecular Docking and 3D QSAR Research of Indolocarbazole Series as Cyclin-Dependent Kinase Inhibitors

Fifty indolocarbazole series as cyclin-dependent kinase inhibitors (CDKs) are used to establish a threedimensional quantitative structure-activity relationship (3D QSAR) model based on docking conformations resulting from the Topomer comparative molecular field analysis (Topomer CoMFA). The statistic parameters show that the cross-validation (q²), the multiple correlation coefficient of fitting (r²), and external validation statistic (Q_ext²) are 0.953, 0.968, and 0.954, respectively. It is demonstrated that this Topomer CoMFA model has good stability and prediction ability. The methodology of the fragment-based drug design (FBDD) was also used to virtually screen new CDKs by the Topomer Search technology. Four similar substitutional groups selected from the ZINC database were added to the basic scaffold. As a result, 18 new CDKs with high activities were obtained. The template molecule and new designed compounds are used to study the binding relationship between the ligands and the receptor protein with Surflex-Dock. The docking results suggest good binding interactions of the designed compounds with protein. There are several hydrogen bondings between CDKs with amino acid residues of LYS33, LYS89, ASP86, LEU83, GLU81.     

Influence of the Molecular Mass of Poly(<Emphasis Type="Italic">N</Emphasis>-vinylpyrrolidone) on Formation of Cu<Subscript>2</Subscript>O Nanoparticles During Reduction of Divalent Copper Ions with <Emphasis Type="Italic">tert</Emphasis>-Butylamine Borane in Polymer Solution

The process of reduction of divalent copper ions with tert-butylamine borane in dilute aqueous solutions of poly(N-vinylpyrrolidone) is investigated. The influence of polymer molecular mass on properties of the resultant Cu₂O sols is studied. It is shown that Cu₂O nanoparticles with an average diameter of 6–8 nm independent of polymer molecular mass and a relatively narrow size distribution of particles are formed in the systems under study. The contour length of macromolecules and the hydrodynamic diameter of a poly(N-vinylpyrrolidone) macromolecular coil are compared with the diameter of Cu₂O particles. Poly(N-vinylpyrrolidone) with M ≥ 1 × 10⁴ can be used to produce Cu₂O nanoparticles. Poly(N-vinylpyrrolidone) with M > 4 × 10⁴ should be used for the formation of long-living Cu₂O sols.     

Molecular modelling studies on cinnoline-based BTK inhibitors using docking and structure-based 3D-QSAR

ABSTRACT

BTK inhibitors have been proved as an effective target for B-cell malignancies. Ibrutinib is the most advanced irreversible BTK inhibitor for treating mantle cell lymphoma/chronic lymphocytic leukaemia but with existing drug resistance and adverse effects. To design novel effective and safety reversible BTK inhibitors, 115 newly cinnoline analogues were selected to perform molecular docking and 3D-QSAR study because of the main scaffold similarity to Ibrutinib. Both established CoMFA and CoMSIA models obtained high predictive and satisfactory value. CoMFA/CoMSIA contour maps demonstrated that bulky substitutions are preferred at R₁ and R₃ positions, and introducing hydrophilic and negative electrostatic substitutions at R₁ positions is important for improving BTK inhibitory activities. These results will be useful to provide clues for rationally designing novel and high potency BTK inhibitors.     

Quantum-chemical study of lutetium,ytterbium, and gadolinium phthalocyaninates PcLnCl

Structural parameters and IR spectra of the (¹A₁//C_4v)-PcLuCl, (²B₂//C_4v)-PcYbCl, and (⁸A₂//C_4v)-PcGdCl molecules, (²A₂//C_4v)-Pc⁺LuCl, (3B₁//C_4v)-Pc⁺YbCl, and (⁹A₁//C_4v)-Pc⁺GdCl cations, (¹A_g//D_2h)-PcLuCl₂LuPc dimer, and PcLuCl···PcLuCl coaxial molecular pair have been simulated using the DFT (U) PBE0/SDD method. The PcLnCl (Ln = Lu, Yb, Gd) molecules have exhibited the equilibrium Ln–N bond length of 222, 223, and 230 pm, the Ln–Cl bond length of 245, 246, and 253 pm, the dipole moment of 4.73, 4.57, and 4.84 D directed from Cl to Ln, and ionization potential of 6.6 eV. β-Decay (¹A₁//C_4v)-Pc¹⁷⁷LuCl → (¹A₁//C_4v)-(Pc^177mHfCl)⁺ occurs with no significant change of the charge on the metal atom.     

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.

     

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.