Exploring molecular shape analysis of styrylquinoline derivatives as HIV-1 integrase inhibitors

Conversion of 2-methyl-4-styrylquinolines into 2,4-distyrylquinolines: synthesis, and spectroscopic and structural characterization of five examples

Four new 2,4-distyrylquinolines and one 2-styryl-4-[2-(thiophen-2-yl)vinyl]quinoline have been synthesized using indium trichloride condensation reactions between aromatic aldehydes and the corresponding 2-methylquinolines, which were themselves prepared using Friedländer annulation reactions between mono- or diketones and (2-aminophenyl)chalcones: the products have all been fully characterized by spectroscopic and crystallographic methods. 2,4-Bis[(E)-styryl]quinoline, C25H19N, (IIa), and its dichloro analogue, 2-[(E)-2,4-dichlorostyryl]-4-[(E)-styryl]quinoline, C25H17Cl2N, (IIb), exhibit different orientations of the 2-styryl unit relative to the quinoline nucleus. In each of the 3-benzoyl analogues {2-[(E)-4-bromostyryl]-4-[(E)-styryl]quinolin-3-yl}(phenyl)methanone, C32H22BrNO, (IIc), {2-[(E)-4-bromostyryl]-4-[(E)-4-chlorostyryl]quinolin-3-yl}(phenyl)methanone, C32H21BrClNO, (IId), and {2-[(E)-4-bromostyryl]-4-[(E)-2-(thiophen-2-yl)vinyl]quinolin-3-yl}(phenyl)methanone, C30H20BrNOS, (IIe), the orientation of the 2-styryl unit is similar to that in (IIa), but the orientation of the 4-arylvinyl units show considerable variation. The thiophene unit in (IIe) is disordered over two sets of atomic sites having occupancies of 0.926 (3) and 0.074 (3). There are no hydrogen bonds of any kind in the structure of (IIa), but in (IId), a single C-H...O hydrogen bond links the molecules into cyclic centrosymmetric R22(20) dimers. A combination of C-H...N and C-H...π hydrogen bonds links the molecules of (IIb) into a three-dimensional framework structure. A combination of three C-H...π hydrogen bonds links the molecules of (IIc) into sheets, and a combination of C-H...O and C-H...π hydrogen bonds forms sheets in (IIe). Comparisons are made with the structures of some related compounds.

Synthesis and spectroscopic and structural characterization of three new 2-methyl-4-styrylquinolines formed using Friedländer reactions between (2-aminophenyl)chalcones and acetone

Three new 2-methyl-4-styrylquinoline derivatives have been synthesized in high yields using Friedländer reactions between chalcones [1-(2-aminophenyl)-3-arylprop-2-en-1-ones] and acetone, and characterized using IR, 1H and 13C NMR spectroscopy, and mass spectrometry, and by crystal structure analysis. In (E)-4-(4-fluorostyryl)-2-methylquinoline, C18H14FN, (I), the molecules are joined into cyclic centrosymmetric dimers by C-H...N hydrogen bonds and these dimers are linked into sheets by π-π stacking interactions. The molecules of (E)-2-methyl-4-[4-(trifluoromethyl)styryl]quinoline, C19H14F3N, (II), are linked into cyclic centrosymmetric dimers by C-H...π hydrogen bonds and these dimers are linked into chains by a single π-π stacking interaction. There are no significant hydrogen bonds in the structure of (E)-4-(2,6-dichlorostyryl)-2-methylquinoline, C18H13Cl2N, (III), but molecules related by translation along [010] form stacks with an intermolecular spacing of only 3.8628 (2) Å. Comparisons are made with the structures of some related compounds.

Discovery of novel indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors by virtual screening

In this study, a combination of virtual screening methods were utilized to identify novel potential indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors. A series of IDO1 potential inhibitors were identified by a combination of following steps: Lipinski's Rule of Five, Veber rules filter, molecular docking, HipHop pharmacophores, 3D-Quantitative structure activity relationship (3D-QSAR) studies and Pan-assay Interference Compounds (PAINS) filter. Three known categories of IDO1 inhibitors were used to constructed pharmacophores and 3D-QSAR models. Four point pharmacophores (RHDA) of IDO1 inhibitors were generated from the training set. The 3D-QSAR models were obtained using partial least squares (PLS) analyze based on the docking conformation alignment from the training set. The leave-one-out correlation (q²) and non-cross-validated correlation coefficient (r²_pred) of the best CoMFA model were 0.601 and 0.546, and the ones from the best CoMSIA model were 0.506 and 0.541, respectively. Six hits from Specs database were identified and analyzed to confirm their binding modes and key interactions to the amino acid residues in the protein. This work may provide novel backbones for new generation of inhibitors of IDO1.

A facile synthesis of (E)-2-(aryl/hetaryl)vinyl-4-phenylquinoline-3-carboxylic acids

New synthetic approach to (

Hyaluronidase Inhibitory Activity of Pentacylic Triterpenoids from Prismatomeris tetrandra (Roxb.) K. Schum: Isolation, Synthesis and QSAR Study

The mammalian hyaluronidase degrades hyaluronic acid by the cleavage of the β-1,4-glycosidic bond furnishing a tetrasaccharide molecule as the main product which is a highly angiogenic and potent inducer of inflammatory cytokines. Ursolic acid 1, isolated from Prismatomeris tetrandra, was identified as having the potential to develop inhibitors of hyaluronidase. A series of ursolic acid analogues were either synthesized via structure modification of ursolic acid 1 or commercially obtained. The evaluation of the inhibitory activity of these compounds on the hyaluronidase enzyme was conducted. Several structural, topological and quantum chemical descriptors for these compounds were calculated using semi empirical quantum chemical methods. A quantitative structure activity relationship study (QSAR) was performed to correlate these descriptors with the hyaluronidase inhibitory activity. The statistical characteristics provided by the best multi linear model (BML) (R² = 0.9717, R²cv = 0.9506) indicated satisfactory stability and predictive ability of the developed model. The in silico molecular docking study which was used to determine the binding interactions revealed that the ursolic acid analog 22 had a strong affinity towards human hyaluronidase.

Development of QSAR models for predicting anti-HIV-1 activity using the Monte Carlo method

Abstract The CORAL software (http://www.insilico.eu/coral/) has been examined as a tool for modeling anti-HIV-1 activity by quantitative structure — activity relationships (QSAR) for three different sets: (i) TIBO derivatives (n=82) (ii) anti-HIV-1 activity of 2-amino-6-arylsulfonylbenzonitriles and their congeners (n=64), and (iii) the measured binding affinity for fullerene-based HIV-1 PR inhibitors (n=48). A new global invariant ATOMPAIR of the molecular structure which can be calculated with the simplified molecular input line entry system (SMILES) was studied. The ATOMPAIR is an indicator of the joint presence of pairs of chemical elements (F, Cl, Br, N, O, S, and P) and three types of bonds (double covalent bond, triple covalent bond, and stereo chemical bond). Six random splits into sub-training, calibration, and test set were examined for each set. For the three aforementioned sets, the use of ATOMPAIR in the modeling process improves the predictive potential of the models for six random splits. Graphical abstract

3D-QSAR studies of quinoline ring derivatives as HIV-1 integrase inhibitors

In the process of HIV-1 virus replication, integrase plays a quite important role. Integrase inhibitors of quinoline ring derivatives were analysed by the Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Induces Analysis (CoMSIA) and Topomer CoMFA methods. Firstly, 77 compounds were selected to form the training and test sets. Secondly, predictive models were constructed with the CoMFA, CoMSIA and Topomer CoMFA methods. The CoMFA model yielded the best model with q (2) of 0.76 and [Formula: see text] of 0.99, the CoMSIA model has q (2 )= 0.70 and [Formula: see text] of 0.99, while the Topomer CoMFA model has q (2) of 0.66 and [Formula: see text] of 0.97. These results provide a helpful contribution to the design of novel highly active HIV-1 integrase inhibitors.

Pharmacological descriptors related to the binding of Gp120 to CD4 corresponding to 60 representative HIV-1 strains

The standardization of HIV-1 strains for vaccine tests include the use of viral reference panels. We determined a series of pharmacological descriptors (molecular surfaces, volumes, electrostatic energies, solvation energies, number of atoms, number of hydrogen donors or acceptors and number of rigid bonds) for the gp120 CD4-binding sites structures in the unliganded state from a reference panel of 60 diverse strains of HIV-1. We identified the descriptors that varied significantly between the strains, the outliner strains for each descriptor set and the possible correlations between the descriptors. Our results improve the knowledge about gp120, its molecular and possible neutralization properties.

Descriptor analysis of estrogen receptor β-selective ligands using 2-phenylquinoline, tetrahydrofluorenone and 3-hydroxy 6H-benzo[c]chromen-6-one scaffolds

Estrogen receptor beta (ERβ) selective ligands have attracted much attention recently in the design of anti-cancer drugs that are devoid of the common side effects of estrogen. Structural studies of estrogen receptor alpha (ERα) and β revealed that there were considerable differences in their ligand-binding cavity and in their volume. Hence, the present study has hypothesized that size and shape descriptors can influence the affinity/selectivity of the ligands towards ERβ. To prove the same, quantitative structure-activity relationship (QSAR) analyses were carried out using multiple regression analysis on 2-phenylquinoline, tetrahydrofluorenone and 3-hydroxy-6H-benzo[c]chromen-6-one series. Results indicate that increased lipophilicity, decrease in ellipsoidal volume and width of substituents, presence of halogen atoms was essential for the ligands to have high affinity/selectivity towards ERβ. QSAR models obtained were both internally and externally validated. The study delineates that the size and shape descriptors are best modulators of ERβ affinity/selectivity. Docking studies were performed to support our QSAR results.

Simplified molecular input-line entry system and International Chemical Identifier in the QSAR analysis of styrylquinoline derivatives as HIV-1 integrase inhibitors

The simplified molecular input-line entry system (SMILES) and IUPAC International Chemical Identifier (InChI) were examined as representations of the molecular structure for quantitative structure-activity relationships (QSAR), which can be used to predict the inhibitory activity of styrylquinoline derivatives against the human immunodeficiency virus type 1 (HIV-1). Optimal SMILES-based descriptors give a best model with n = 26, r(2) = 0.6330, q(2) = 0.5812, s = 0.502, F = 41 for the training set and n = 10, r(2) = 0.7493, r(pred)(2) = 0.6235, R(m)(2) = 0.537, s = 0.541, F = 24 for the validation set. Optimal InChI-based descriptors give a best model with n = 26, r(2) = 0.8673, q(2) = 0.8456, s = 0.302, F = 157 for the training set and n = 10, r(2) = 0.8562, r(pred)(2) = 0.7715, R(m)(2) = 0.819, s = 0.329, F = 48 for the validation set. Thus, the InChI-based model is preferable. The described SMILES-based and InChI-based approaches have been checked with five random splits into the training and test sets.

Computer tools in the discovery of HIV-1 integrase inhibitors

Computer-aided drug design (CADD) methodologies have made great advances and contributed significantly to the discovery and/or optimization of many clinically used drugs in recent years. CADD tools have likewise been applied to the discovery of inhibitors of HIV-1 integrase, a difficult and worthwhile target for the development of efficient anti-HIV drugs. This article reviews the application of CADD tools, including pharmacophore search, quantitative structure-activity relationships, model building of integrase complexed with viral DNA and quantum-chemical studies in the discovery of HIV-1 integrase inhibitors. Different structurally diverse integrase inhibitors have been identified by, or with significant help from, various CADD tools.

Quantitative structure-property relationship studies on amino acid conjugates of jasmonic acid as defense signaling molecules

Jasmonates and related compounds, including amino acid conjugates of jasmonic acid, have regulatory functions in the signaling pathway for plant developmental processes and responses to the complex equilibrium of biotic and abiotic stress. But the molecular details of the signaling mechanism are still poorly understood. Statistically significant quantitative structure-property relationship models (r(2) > 0.990) constructed by genetic function approximation and molecular field analysis were generated for the purpose of deriving structural requirements for lipophilicity of amino acid conjugates of jasmonic acid. The best models derived in the present study provide some valuable academic information in terms of the 2/3D-descriptors influencing the lipophilicity, which may contribute to further understanding the mechanism of exogenous application of jasmonates in their signaling pathway and designing novel analogs of jasmonic acid as ecological pesticides.

Current mathematical methods used in QSAR/QSPR studies

This paper gives an overview of the mathematical methods currently used in quantitative structure-activity/property relationship (QASR/QSPR) studies. Recently, the mathematical methods applied to the regression of QASR/QSPR models are developing very fast, and new methods, such as Gene Expression Programming (GEP), Project Pursuit Regression (PPR) and Local Lazy Regression (LLR) have appeared on the QASR/QSPR stage. At the same time, the earlier methods, including Multiple Linear Regression (MLR), Partial Least Squares (PLS), Neural Networks (NN), Support Vector Machine (SVM) and so on, are being upgraded to improve their performance in QASR/QSPR studies. These new and upgraded methods and algorithms are described in detail, and their advantages and disadvantages are evaluated and discussed, to show their application potential in QASR/QSPR studies in the future.

Quantitative structure-activity relationship studies on 1-aryl-tetrahydroisoquinoline analogs as active anti-HIV agents

Predictive quantitative structure-activity relationship analysis was developed for a diverse series of recently synthesized 1-aryl-tetrahydroisoquinoline analogs with anti-HIV activities in this study. The conventional 2D-QSAR models were developed by genetic function approximation (GFA) and stepwise multiple linear regression (MLR) with acceptable explanation of 94.9% and 95.5% and good predicted power of 91.7% and 91.7%, respectively. The results of the 2D-QSAR models were further compared with 3D-QSAR model generated by molecular field analysis (MFA), investigating the substitutional requirements for the favorable receptor-drug interaction and quantitatively indicating the important regions of molecules for their activities. The results obtained by combining these methodologies give insights into the key features for designing more potent analogs against HIV.