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Antimicrobial peptide (AMP) is the polypeptide, which protects the organism avoiding attack from pathogenic bacteria. Studies have shown that there were some antimicrobial peptides with molecular action mechanism involved in crossing the cell membrane without inducing severe membrane collapse, then interacting with cytoplasmic target-nucleic acid, and exerting antibacterial activity by interfacing the transmission of genetic information of pathogenic microorganisms. However, the relationship between the antibacterial activities and peptide structures was still unclear. Therefore, in the present work, a series of AMPs with a sequence of 20 amino acids was extracted from DBAASP database, then, quantitative structure–activity relationship (QSAR) methods were conducted on these peptides. In addition, novel antimicrobial peptides with stronger antimicrobial activities were designed according to the information originated from the constructed models. Hence, the outcome of this study would lay a solid foundation for the in-silico design and exploration of novel antibacterial peptides with improved activity activities. [ABSTRACT FROM AUTHOR]

In this paper, 3D-QSAR models were constructed to conduct a preliminary study on the structure–activity relationship of chrysin. The three-dimensional structures of the selected 54 chrysin derivatives were constructed by SYBYL-X 2.0 software, molecular mechanics procedures for conformational optimization, and molecular alignment. The 3D-QSAR model of these compounds was constructed by comparative molecular force field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA), and the structure–activity relationships of chrysin compounds was preliminarily discussed. CoMFA and CoMSIA models are all constructed reasonably and reliably (CoMFA: q2 = 0.703, r2 = 0.886, SEE = 0.217, F = 113.572; CoMSIA: q2 = 0.647, r2 = 0.841, SEE = 0.255, F = 111.740), a series of three-dimensional contour maps were obtained to visualize the influence of various fields around the compound molecules on the drug activity. Groups with more hydrogen bonding acceptors attached to the end of the 7-O-alkane chain of chrysin are favorable for the molecular activity, such as amino acids. However, excessively long 7-O-alkane chains or the introduction of bulky hydrophobic groups on the 7-O-alkane chain will reduce the activity of the molecule. In contrast, the introduction of bulky hydrophobic groups on the side chains of amino acids will enhance the molecular activity. [ABSTRACT FROM AUTHOR]

Piperidine and piperazine derivatives exhibit a diverse range of biological applications, including antipsychotic activity. In this study, a dataset of molecules containing piperidine, piperazine moieties that possess serotonin 5-HT2A and dopamine D2 inhibitory activity have been chosen for Pharmacophore modeling, Quantitative Structure–Activity (3D-QSAR) Relationship, Molecular docking, and ADME studies. The pharmacophoric hypothesis was found to be AAHPRRR_1 having seven features as one H-bond acceptor (A), one hydrophobic (H), one positive ion acceptor (P), and three aromatic rings (R), with survival score = 6.465 and AUC = 0.92. Based on the best hypothesis, the ZINC-Data base was virtually screened to find out the lead molecules. 3D-QSAR model, including internal and external validation showed comparative molecular field analysis (CoMFA) against 5HT2A (q2 = 0.552, R2 = 0.889, and r2 poured. = 0.653 and number of component 5) and comparative molecular similarity indices analysis (CoMSIA) (q2 = 0.599, R2 = 0.893, and r2 pred. = 0.617), for D2 (CoMFA, q2 = 0.577, R2 = 0.863, and r2 pred. = 0.598) (CoMSIA, q2 = 0.532, R2 = 0.82) all results exhibited better productivity and significant statistical reliability of the model. The docking study was carried out on the crystal structure of 5-HT2A having PDB ID; 6A93 and D2 receptor having PDB ID; 6CM4. The screened compound ZINC74289318 possess a higher docking score − 10.744 and − 11.388 than co-crystallized ligand docking score − 8.840 and − 10.06 against 5-HT2A and D2 receptor respectively. Further, ZINC74289318 was screened for all drug-likeness parameters and no showed violation of the Lipinski rule of five. Also, it was found to possess good bioavailability of 0.55 with synthetic accessibility of 4.42 which is greater than risperidone. [ABSTRACT FROM AUTHOR]

The emergence of multidrug resistance bacteria poses a great health theat. Therefore, it is a crucial demand to obtain new antibacterial drugs. Antimicrobial peptides (AMPs) have the characteristics of wide antimicrobial spectrum and lower drug resistance, hence, it is hopeful to substitute for classical antibiotics. In this study, two classic methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA), were used to analyze the structural feature of AMPs against Staphylococcus aureus or Escherichia coli, respectively. Subsequently, the models established by three-dimensional quantitative structure–activity relationships (3D-QSAR) (for S. aureus, CoMFA: Q2 = 0.512, R2 = 0.943, F = 59.916; CoMSIA: Q2 = 0.645, R2 = 0.993, F = 339.242; for E. Coli, CoMFA: Q2 = 0.507, R2 = 0.913, F = 66.862; CoMSIA: Q2 = 0.573, R2 = 0.966, F = 96.84) have good predictability and stability was constructed. Seven novel small AMPs were designed and synthesized based on the theoretical model. The novel AMPs showed potent antibacterial activity against S. aureus and E. coli while causing low host toxicity. This study provides a potential therapeutic option using 3D-QSAR models guiding the design and modification of novel AMPs, to address the prevalent infections caused by MDR bacterial. [ABSTRACT FROM AUTHOR]

Rising mortality due to cancer has led to the development and identification of newer targets and molecules to cure the disease. Telomerase is one of the attractive targets for design of many chemotherapeutic drugs. This research highlights the designing of novel telomerase inhibitors using ligand-based (3D-QSAR) and structure-based (molecular docking and molecular dynamics simulation) approaches. For the development of the 3D-QSAR model, 37 synthetic molecules reported earlier as telomerase inhibitors were selected from diversified literature. Three different alignment methods were explored; among them, distill alignment was found to be the best method with good statistical results and was used for the generation of QSAR model. Statistically significant CoMSIA model with a correlation coefficient (r2ncv) value of 0.974, leave one out (q2) value of 0.662 and predicted correlation coefficient (r2pred) value of 0.560 was used for the analysis of QSAR. For the MDS study, A-chain of telomerase was stabilised for 50 ns with respect to 1-atm pressure, with an average temperature of 299.98 k and with potential energy of 1,145,336 kJ/m converged in 997 steps. Furthermore, the behaviour study of variants towards the target revealed that active variable gave better affinity without affecting amino acid sequences and dimensions of protein which was accomplished through RMSD, RMSF and Rg analysis. Results of molecular docking study supported the outcomes of QSAR contour maps as ligand showed similar interactions with surrounded amino acids which were identified in contour map analysis. The results of the comprehensive study might be proved valuable for the development of potent telomerase inhibitors. [ABSTRACT FROM AUTHOR]

Genetic mutations in APC or CNTBB1 gene with aberrant canonical Wnt/β-catenin pathway are responsible for more than 90% of colorectal carcinogenesis. Tankyrases (TNKS) are known to downregulate Wnt signaling by stabilizing AXIN protein through poly(ADP ribose)polymerization or PARSylation process and subsequently, promoting degradation of intracellular β-catenin. Tankyrase enzymes are modulated by a range of known inhibitors that bind individually to any of the nicotinamide or induced adenosine pockets or as dual binding antagonists. Hence, for designing dual tankyrase inhibitors as Wnt signaling antagonist; we carried out 3D-QSAR studies using a data set of 51 molecules of reported 3,4,5-trisubstituted 4H-1,2,4-triazole derivatives. These reported 51 molecules were divided into a training set (39 molecules) and test set (12 molecules), aligned and subjected to generate CoMFA, CoMSIA, and HQSAR models. CoMFA analysis showed q2 value of 0.694, r2ncv value of 0.991 and r2pred value of 0.641. Optimized CoMSIA analysis (SEHA) showed q2 value of 0.624, r2ncv value of 0.909 and r2pred value of 0.850. Both internal and external validations were performed for generated models of CoMFA and CoMSIA (SEHA) and satisfactory results were obtained. HQSAR analysis showed q2, r2, and r2pred values of 0.781, 0.901, and 0.811, respectively. Applicability domain was also found to be satisfactory with all compounds falling within the range and no outlier was observed. Contour maps from all studies provided significant results with identification of desired spatial arrangement of different atoms or functional groups in a molecule. Triazole ring system-based molecules were reported as potent tankyrase inhibitors. These noteworthy results were employed for the design of different triazole derivatives as potent tankyrase inhibitors, wherein a series of 20 different molecules were designed for evaluation of their potentials as novel tankyrase inhibitors. [ABSTRACT FROM AUTHOR]

The angiotensin I-converting enzyme (ACE) has been found to exhibit inhibitory capability against blood pressure. Recently, several ACE inhibitors with different structures have been reported. In the present work, molecular modeling studies using quantitative structure–activity relationship (QSAR) and molecular docking simulations were carried out. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were firstly used to generate 3D-QSAR models. The results indicate that the best CoMFA model has R cv 2 = 0.504, R pred 2 = 0.5896, and the best CoMSIA model has R cv 2 = 0.525, R pred 2 = 0.5666. Furthermore, 2D-QSAR models developed by multiple linear regression/MLR, partial least squares regression/PLSR, and support vector machine regression/SVR methods provide highly significant squared correlation coefficient Rtr2 values of 0.8380, 0.8650, and 0.8230, external validated correlation coefficient Qte2 of 0.8279, 0.8223, and 0.7255, respectively. The statistical results show satisfactory goodness-of-fit, robustness, and perfect external predictive performance. Moreover, molecular docking studies were employed to predict the binding mode between dipeptides and ACE receptor. The combination of QSAR studies and molecular docking indicates the requirement of certain physicochemical parameters for better ACE inhibitors. [ABSTRACT FROM AUTHOR]

In the present work, three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed in an attempt to predict the key features of bitter-tasting tripeptides. The 3D-QSAR models were carried out by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods and the corresponding statistical correlation coefficients R2cv for the training set are 0.534 and 0.547, respectively, the predicted correlation coefficients R2pred for the test set are found to be 0.7162 and 0.5792, respectively. The information obtained from the QSAR contour maps enables the interpretation of the structure-activity relationship. In addition, molecular docking was also employed to investigate the interaction between bitter-tasting peptides and related receptor hTAS2R1, results indicate that the Lys76, Pro188 and His243 were significant for binding to the peptides, and some essential features were identified to deduce some interesting structure-activity relationships. The present QSAR models along with information contour maps and molecular docking study may be used for designing and predicting novel bitter-tasting peptides. [ABSTRACT FROM AUTHOR]

A 3D QSAR study was performed on 1,2,4-oxadiazole derivatives using the [(SW) kNN MFA], CoMFA, and CoMSIA techniques. On the basis of 3D QSAR outcomes, new molecules were designed by substituting different substituents. These designed compounds were synthesized and confirmed their synthesis by spectroscopic techniques. The synthesized compounds were screened for their anticancer activity against different cancer cell lines. Compound 2-[3-(pyridine-4-yl)-1,2,4-oxadiazol-5-yl]benzo[d]thiazole showed equipotent (IC50 = 4.96 μM) as 5-fluorouracil (IC50 = 3.2 μM) against colon (CaCo-2) cancer cell line, and compound [2-[3-(pyridin-4-yl)-1,2,4-oxadiazol-5-yl]benzo[d]thiazol-4-yl]methanol showed equipotent activity (IC50 = 0.35 μM) as compared to 5-fluorouracil (IC50 = 0.23 μM) against colorectal (DLD1) cancer cell line. Compound 2-[3-(3,4-dimethoxyphenyl)-1,2,4-oxadiazol-5-yl]benzo[d]thiazole was found to be 4–5 less potent (IC50 = 19.40 μM) as paclitaxel (IC50 = 4.10 μM) against breast (T47D) cancer cell line, and compound 4-[5-(benzo[d]thiazol-2-yl)-1,2,4-oxadiazol-3-yl]benzene-1,2-diol was found about 10 times less potent (IC50 = 15.7 μM) than mitomycin (IC50 = 1.50 μM) against prostate (PC-3) cancer cell line. These results disclose the discovery of new 1,2,4-oxadiazole-based anticancer drugs. [ABSTRACT FROM AUTHOR]

Aminopeptidase M1 (PfAM1) is one of the key enzymes involved in the development of new antimalarials. To accelerate the discovery of inhibitors with selective activity against PfAM1 and microsomal neutral aminopeptidase (pAPN), in the present work, the optimum comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were built based on PfAM1 and pAPN inhibitors. The results of the developed 3D-QSAR models were as follows: PfAM1/CoMFA: R cv 2 = 0.740, R pred 2 = 0.7781; PfAM1/CoMSIA: R cv 2 = 0.740, R pred 2 = 0.7354; pAPN/CoMFA: R cv 2 = 0.612, R pred 2 = 0.7318; pAPN/CoMSIA: R cv 2 = 0.609, R pred 2 = 0.7480, and the models derived from MLR, PLSR and SVR methods provided high R2 values of 0.6960, 0.6965, 0.7971 for PfAM1, 0.7700, 0.7697, 0.8228 for pAPN and Q2 of 0.7004, 0.7004, 0.5632 for PfAM1, 0.7551, 0.7566 and 0.8394 for pAPN, respectively, indicating that the developed 3D-QSAR and 2D-QSAR models possess good ability for prediction of the relative compound activities. Furthermore, all inhibitors were docked into the active site of the PfAM1 and pAPN receptors, the hydrogen-bond interactions between the compound 33 with Glu497, Glu463 and Arg489 of the PfAM1, and the compound 4 with Ala348, Glu384 and Phe467 of the receptor pAPN are able to help to stabilize the conformation. The above results would provide helpful clues to predicting the binding activity of novel inhibitors and the foundation for understanding the interaction mechanism between the inhibitors and the receptors. [ABSTRACT FROM AUTHOR]

JAK2 plays a critical role in JAK/STAT signaling pathway and in patho-mechanism of myeloproliferative disorders and autoimmune diseases. Thus, effective JAK2 inhibitors provide a promising opportunity for the pharmaceutical intervention of many diseases. In this work, 3D-QSAR study was performed on a series of 1-amino-5H-pyrido-indole-4-carboxamide derivatives as JAK2 inhibitors to obtain reliable comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) models with three different alignment methods. Among the different alignment methods, ligand-based (CoMFA: q2 = 0.676, r2 = 0.979; CoMSIA: q2 = 0.700, r2 = 0.953) and pharmacophore-based alignment (CoMFA: q2 = 0.710, r2 = 0.982; CoMSIA: q2 = 0.686, r2 = 0.960) has produced better statistical results when compared to receptor-based alignment (CoMFA: q2 = 0.507, r2 = 0.979; CoMSIA: q2 = 0.544, r2 = 0.917). Statistical parameters indicated that data are well fitted and have high predictive ability. The presence of electrostatic and hydrophobic field is highly desirable for potent inhibitory activity, and the steric field plays a minor role in modulating the activity. The contour analysis indicates ARG980, ASN981, ASP939 and LEU937 have more possibility of interacting with bulky, hydrophobic groups in pyrido and positive and negative groups in pyrazole ring. Based on our findings, we have designed sixteen molecules and predicted its activity and drug-like properties. Subsequently, molecular docking, molecular dynamics and DFT calculations were performed to evaluate its potency. [ABSTRACT FROM AUTHOR]

Macrocyclic ring structures could have drug-like properties such as membrane permeability, metabolic stability, binding affinity, selectivity, and high-biological activities. Synthesized macrocyclic inhibitors have been studied and the effect of ring size has gained attention from drug design community. Marsault et al. showed a positive correlation between ring size and inhibitory activity against rennin. On the other hand, De Clercq et al. suggested that there would be some optimum ring size for histone deacetylase inhibitory activity. Therefore, macrocyclic effects appear elusive while intriguing. In this study, we have selected a large set of macrocyclic inhibitors (14–20-membered rings) to study macrocyclic effect on MerTK using molecular modeling techniques. We carefully positioned all the cyclic inhibitors into the binding pocket utilizing available information obtained from both experimental and theoretical means. Then, from the resultant binding poses, the ligand–receptor interactions were analyzed. Unlike previous reports, we could not observe any relevance between ring size and inhibitory activity. However, there is a correlation between the number of hydrogen bonds and inhibitory activity. Among these hydrogen-bonding interactions, active site residues Arg727, and Asn728 as well as two signature interactions at the hinge region were found to be crucial for MerTK inhibition. Furthermore, the importance of number of hydrogen bonding was further validated statistically by means of 3D-QSAR techniques such as CoMFA and CoMSIA. The involvement of Arg727 and Asn728 was checked graphically by CoMSIA hydrogen-bonding donor map. This outcome could be helpful for more potent MerTK inhibitor design. In addition, more detailed studies on ring size effect would be desirable to understand macrocyclic effects. [ABSTRACT FROM AUTHOR]

Estrogen receptors (ERs) are significant protein targets that can alter normal homeostatic transcription and signaling pathways. And the development of selective ER ligands is involved in the pharmacology of anticancer drugs, leading to the synthesis of numerous ER selective ligands. In the present work, three dimensional quantitative structure–activity relationship (3D-QSAR) models, including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) in combination with molecular docking were performed on a series of ER ligands to investigate the potential relationship between the structural features of the compounds and its activity and selectivity. Good statistical significance was achieved for the CoMFA (ERα: R2cv = 0.676, R2pred = 0.631. ERβ: R2cv = 0.578, R2pred = 0.5341) and CoMISA (ERα: R2cv = 0.693, R2pred = 0.5758. ERβ: R2cv = 0.653, R2pred = 0.615) models. In addition, molecular docking results confirmed that the substituents at ring A, ring D and ring E were crucial for interacting with receptors ERα and ERβ, respectively, which were in agreement with the QSAR results. The substituents in ring A and ring F for ERα and residues Thr347/Ala302, Met388/Leu343, Leu391/Arg346, Met421/Ile376, Gly521/Leu476 for ERα and ERβ, respectively, contribute the most to the subtype selectivity. These results obtained from this work provide valuable information for the design of novel selective ER ligands with enhanced activity. [ABSTRACT FROM AUTHOR]

ERRγinverse agonist is a powerful therapeutic target for the treatment of cancers and certain metabolic disorders. Until now, only GSK5814 was reported as selective ERRγinverse agonist. So 60 newly hydroxytamoxifen analogues were selected to perform molecular docking and 3D-QSAR study to design more selective inverse agonist of ERRγ. Both established CoMFA and CoMSIA models obtained high predictive and satisfactory value, demonstrated that bulky, hydrophobic and negative electrostatic substitutions are preferred at R2 position, and introducing hydrophilic and H-bond donor and acceptor groups at R1 and R4 positions is greatly important for improving binding activities. The obtained information will be useful to provide clues for rationally designing novel and high potency ERRγinverse agonists. [ABSTRACT FROM AUTHOR]

Phosphodiesterase-5 (PDE5) inhibitors can be used as clinical agents for the treatment of erectile dysfunction and pulmonary hypertension. A series of aryl-chromeno-pyrrol derivatives were previously identified as PDE5 inhibitors in our lab. Herein, these molecules were subjected to 3D-QSAR analysis with CoMFA and CoMSIA methods to gain deeper insight into the structural requirements for their bioactivities. Receptor- and ligand-based alignment were used and compared to find the alignment-related factors that affect the accuracy of QSAR models. The receptor-based CoMFA and CoMSIA models, which were generated by superimposing the docking conformations directly in the protein binding site, gave more significant results for 38 training set compounds and 5 test set molecules. Comparison of the two alignments revealed that spatial arrangement of the ligands is the principal factor in determining the reliability of the 3D-QSAR models. Detailed analysis of the receptor-based CoMSIA-SE contour maps provided much helpful information to improve the bioactivities of aryl-chromeno-pyrrol analogs as PDE5 inhibitors. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The N-methyl-D-aspartate (NMDA) is the family of glutamate receptor, which is involved in controlling synaptic plasticity and memory function; but overactivation of this receptor results to excess intracellular calcium formation, triggers neuronal injury and also involves in several pathologies. Both ligand- and structure-based quantitative structure-activity relationship (QSAR), pharmacophore, docking and simulation studies have been performed on a set of structurally diverse inhibitors to explore prime molecular structural features involve for specific binding to NMDA, and vis-à-vis inhibiting enzyme activity. 3D QSAR studies, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models showed the importance of steric, electrostatic and hydrophobic features; while hydrogen bond acceptor and hydrophobic features are depicted as important pharmacophore features of the molecule. Molecular docking and simulation studies corroborated the consequence of the features obtained from ligand-based Bayesian model (AUROCcv = 0.878); 3D QSAR CoMFA (R2 = 0.895, se = 0.513, Q2 = 0.602, R2pred = 0.673); CoMSIA (R2 = 0.877, se = 0.555, Q2 = 0.615, R2pred = 0.727); hologram QSAR (Q2 = 0.812, R2 = 0.941, R2pred = 0.772), and pharmacophore models (Q2 = 0.926, R2 = 0.927, R2pred = 0.621). Presence of aromatic ring, hetero and halogen atoms along with alkyl group of molecular scaffold shows their importance for binding affinity to NMDA receptor. Stability of the complex is adjudged by both docking and simulation studies. [ABSTRACT FROM AUTHOR]

Human immunodeficiency virus type-1 reverse transcriptase (HIV-1 RT) plays a key in the life cycle of HIV-1. It is considered to be one of the promising targets for treating HIV/AIDS which contains two drug binding sites, a substrate binding site, and an allosteric site. Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are a class of RT inhibitors that bind to allosteric sites on HIV-1 RT in a non-competitive manner and thereby disrupting the conformation of RT. Hence, they can act as potent inhibitors against HIV-1 RT. In present study, the key structural requirements for enhancing HIV-1 RT inhibitory activity were explored from combined docking and three-dimensional quantitative structure activity relationship (3D QSAR) protocols. Initially, multiple-receptor conformation docking (MRCD) was performed using a series of diaryl pyridine and pyrimidine derivatives into the active site of ten X-ray crystal structures and one NMR-resolved conformation of HIV-1 RT. Later, the dock poses obtained from docking were clustered and 3D QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods. Finally, a robust model was established using cross-validation techniques and the robustness of the model was confirmed through high accuracy of q2loo of 0.843 and 0.682, r2ncv of 0.977 and 0.949, and r2pred of 0.702 and 0.690, respectively, for CoMFA and CoMSIA. Based on the outcome of the results, new pyrimidine derivatives having potential inhibitory against HIV-1 RT were designed. [ABSTRACT FROM AUTHOR]

Resveratrol (3,4′,5-trihydroxystilbene) has been reported to promote degradation of intracellular amyloid-beta (Aβ) aggregates in Alzheimer’s disease (AD). In the present paper, we report comparative molecular field analysis (CoMFA)-based and comparative molecular similarity indices analysis (CoMSIA)-based three-dimensional quantitative structure-activity relationship (3D-QSAR) study of 30 resveratrol derivatives. The best predictive CoMFA model with correlation coefficients (r2) of 0.905 and 0.908 for training and test sets, respectively, and cross-validated correlation coefficient (q2) of 0.713 was obtained using training and test set of 20 and 10 compounds, respectively. Using the same sets of compounds, the best CoMSIA model exhibiting steric, electrostatic, and hydrophobic fields revealed r2 values of 0.938 and 0.966 for training and test sets, respectively, and q2 value of 0.726. The features obtained from contour maps of both CoMFA and CoMSIA models were used to design a library of hybrid resveratrol derivatives based on a set of six potent Aβ aggregation inhibitors. The inhibitory potential of the most active compound of this library was found to be close to that of the most active compound of the data set. The results obtained from the present study makes a foundation for the development of effective drugs against Aβ aggregation. [ABSTRACT FROM AUTHOR]

Matrix metalloproteinase-2 (MMP-2) is established as one of the most important metalloenzymes for targeting cancer. However, homologous MMP-9 of the gelatinase family is implicated as an antitarget of cancer. Therefore, it is an important and challenging task to achieve MMP-2 selectivity over MMP-9. In this article, robust validated chemico-biological quantitative approaches were conducted on a series of in house glutamate-based selective MMP-2 inhibitors over MMP-9 for further refinement of our MMP-2 inhibitor designing approach. The two-dimensional quantitative structure-activity relationship (2D-QSAR) study suggested that arylsulfonamide moiety was better than arylcarboxamide function, which in turn, supported by the hologram QSAR (HQSAR), 3D-QSAR comparative molecular field analysis (CoMFA), and comparative molecular similarity analysis (CoMSIA) studies. Regarding the MMP-2 selectivity, glutamines were better than isoglutamines as evidenced by the quantitative activity-activity relationship (QAAR) and molecular docking studies. Favorable hydrophobic and steric features of aryl function directed towards the S1′ pocket were also well attributed. Naphthyl and p-bromophenoxyphenyl moieties in place of biphenyl function were found to be unfavorable for MMP-2 inhibition and selectivity over MMP-9. Linear or cyclic aliphatic group directed towards the S2′ pocket was favorable, whereas branching was unfavorable for MMP-2 inhibition and selectivity. The importance of biphenyl and 3,5-bistrifluoromethylbenzyl functions directed towards the S1′ and S2′ pockets, respectively, was well attributed for potent MMP-2 inhibition and selectivity over MMP-9. [ABSTRACT FROM AUTHOR]

Influenza endonuclease plays important role in the viral transcription and translation processes. Inhibition of endonuclease enzyme may be an interesting choice to restrict influenza infection. This current study deals with validated multi-chemometric modelling approaches namely regression-based and classification-based quantitative structure-activity relationships (QSARs), hologram QSAR, comparative molecular similarity analysis (CoMSIA), Open3DQSAR study and pharmacophore mapping to identify the structural and physicochemical requirements along with the chemico-biological interactions of pyridinones and pyranones for anti-endonuclease activity. The results suggest that the pyridinone scaffold is more preferable than the pyranone ring. The keto function at 4th position and aryl tetrazole substitution at 1st position of the parent moiety may be important for endonuclease inhibition. Hydroxyl group at 5th position of the parent ring may act as hydrogen bond acceptor feature. The steric substituent is suitable at 2nd position whereas hydrophobic substitution is found to be unfavourable at this position. Bulky hydrophobic substituents are not preferred at the 3rd position of the parent moiety. The information revealed from these integrated ligand-based modelling methods may provide useful informations for designing newer potential anti-influenza agents in future. [ABSTRACT FROM AUTHOR]

Rearranged during transfection is a transmembrane receptor tyrosine kinase. It is involved in medullary thyroid cancer and lung adenocarcinoma in humans. In this work, molecular docking and three-dimensional quantitative structure-activity relationship studies were performed on recently reported series of two-substituted phenol quinazoline derivatives as rearranged during transfection inhibitors. Docking study identified key active site residues such as Ala807, Lys758, Leu802, Leu730, Tyr806, Ala756, Val804, Asp892, and Glu775 that participate in the inhibition of rearranged during transfection. A reasonable comparative molecular field analysis ( q = 0.592, optimal number of components = 4, r = 0.921) and comparative molecular similarity indices analysis ( q = 0.580, optimal number of components = 6, r = 0.963) models were generated in three-dimensional quantitative structure-activity relationship study. Various validation techniques such as external test set validation, bootstrapping analysis, and progressive scrambling were carried out to check the predictive ability of the obtained models. The validated models resulted in acceptable statistical values and proved to be predictive and robust. comparative molecular similarity indices analysis model was selected as the final model based on the reasonable statistical values of q , r , standard error of estimate, and r . The contour maps analysis of comparative molecular similarity indices analysis model revealed the favorable regions to enhance the inhibitory activity of compounds. R and R positions were favorable for bulky substitution. Hydrophilic and negative substitutions at R position were favorable. Thus results of our study can provide insights in the designing potent and selective rearranged during transfection kinase inhibitors. [ABSTRACT FROM AUTHOR]

The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four QSAR models were successfully established by CoMSIA, CoMFA, topomer CoMFA and HQSAR approaches with respective characteristic values q = 0.567, R = 0.968, ONC = 5; q = 0.547, R = 0.980, ONC = 7; q = 0.559, R = 0.921, ONC = 7 and q = 0.527, R = 0.921, ONC = 6. The predictive ability of CoMSIA with r = 0.991 is the best one compared with the other three approaches, such as CoMFA (r = 0.787), topomer CoMFA (r = 0.819) and HQSAR (r = 0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities. [ABSTRACT FROM AUTHOR]

To explore the relationship between the structures of substituted pyrrolidine derivatives and their inhibition of dipeptidyl peptidase IV inhibitors. The QSAR, including CoMFA, CoMSIA and HQSAR, were applied to identify the key structures impacting their inhibitory potencies. The CoMFA, CoMSIA and HQSAR with cross-validated correlation coefficient (q) value of 0.727, 0.870 and 0.939 and r value of 0.973, 0.981 and 0.949. Based on the structure-activity relationship revealed by the present study, we have designed a set of novel dipeptidyl peptidase IV inhibitors that showed excellent potencies in the developed models. Thus, our results allowed us to design new derivatives with desired activities. [ABSTRACT FROM AUTHOR]

A series of sulfonylnitrophenylthiazoles derivatives were identified as effective targeting agents that block the interaction of the thyroid hormone receptor with its coactivators. In this work, in order to analyze the structure-activity relationship of these inhibitors and investigate the structural requirements for thyroid hormone receptor inhibitory activity, new statistically validated in silico models adopting different molecular descriptors were established. The two-dimensional quantitative structure-activity relationship models were developed using multiple linear regression method, which show both significant statistical quality and predictive ability ( R = 0.939, Q = 0.622 for thyroid hormone receptor β; R = 0.862, Q = 0.763 for thyroid hormone receptor α), and different molecular descriptors were included, namely R2, H5, EEigo4r and Ram for thyroid hormone receptor β, MATS1, IC and R5e+ for thyroid hormone receptor α. The optimum comparative molecular field analysis models were established using the template ligand-based alignment, which show satisfactory linear correlations (thyroid hormone receptor β: R = 0.577, R = 0.8013; thyroid hormone receptor α: R = 0.549, R = 0.8639). In addition, the R of 0.543, R of 0.8523 for thyroid hormone receptor β and R of 0.560, R of 0.8695 for thyroid hormone receptor α have been observed when comparative molecular similarity analysis fields were applied. All the developed statistical models give satisfactory results with accurate fitting and strong predictive abilities. Moreover, the contour maps provide an intuitive understanding of the structural requirements for the inhibitors. In conclusion, these data can provide some meaningful theoretical references to understand the factors influencing the inhibitory activity and direct the molecular design of novel inhibitors with increased activity. [ABSTRACT FROM AUTHOR]

Acetyl-CoA carboxylases (ACC) have long been recognized as an attractive target for metabolic syndrome because of its indispensable role in the regulation of fatty acid metabolism in most living organisms. Based on the lead compound CP-640186, a series of spiro-compounds of benzothiazole derivatives have been identified as ACC inhibitors, which displayed high ACC inhibitor activities and good metabolic stability. Nevertheless, no quantitative structure-activity relationship study has been developed for this kind of ACC inhibitors. In order to evaluate the correlation between changes on structures and variation on biological activity, three-dimensional quantitative structure-activity relationship analysis was employed. Satisfactory results were obtained after performing a leave-one-out cross-validation study with q and r values of 0.625 and 0.927 by the comparative molecular field analysis model, 0.779 and 0.937 by the comparative molecular similarity indices analysis model, respectively. The predictive ability of the models was validated using external validation test set. The contour map analysis of comparative molecular field analysis and comparative molecular similarity indices analysis models indicated that electropositive and bulky groups substituted at the R position of carbamido group, and hydrophilic groups substituted at the phenyl ring were favorable for the inhibitory activity. Furthermore, FlexX docking was employed to investigate the binding mode between human ACC1 and its inhibitors and to validate the three-dimensional quantitative structure-activity relationship models. As a result, based on the results of three-dimensional quantitative structure-activity relationship and FlexX docking, a series of ACC inhibitors with higher predictive activities have been designed. This work might provide valuable information in further optimization of human ACC inhibitors. [ABSTRACT FROM AUTHOR]

Aurora A kinase is involved in the inactivation of apoptosis leading to ovarian, breast, colon, and pancreatic cancers. Inhibitors of Aurora A kinase promote aberrant mitosis resulting in arrest at a pseudo G1 state to induce mitotic catastrophe, ultimately leading to apoptosis. In this study, ligand-based and docking-based three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses of imidazole and thiazolidine derivatives as potential Aurora A kinase inhibitors were performed. The results provided highly reliable and predictive 3D-QSAR comparative molecular similarity index analysis (CoMSIA) models with a cross-validated q value of 0.768, non-cross-validated r value of 0.983, and predictive coefficient $${\text{r}}_{\text{pred}}^{2}$$ value of 0.978. CoMSIA contour maps suggested that the NH and benzyl hydroxy groups in R, and the CO group in the thiazolidine ring and pyridine ring were important components for biological activity. The maps also suggest that the introduction of hydroxy groups at C of the imino-phenyl ring, C in the pyridine ring, or the substitution of the imino-phenyl ring for the imino-2-pyridine ring could be applied to enhance biological activity. [ABSTRACT FROM AUTHOR]

Mer kinase is implicated as therapeutic target for the prevention and treatment of thrombosis. A molecular modeling study was performed on a series of pyrimidine-based inhibitors of Mer specific tyrosine kinase. The relationship between the structure and the activity of these inhibitors was studied using three-dimensional quantitative structure-activity relationship, molecular docking and molecular dynamics simulations. A reliable comparative molecular similarity indices analysis model with a cross-validated correlation coefficient ( q ) of 0.637 and a conventional correlation coefficient ( r ) of 0.955 was obtained from the combination of steric and hydrogen bond donor fields. Model showed acceptable predictive capability with predicted correlation coefficient ( r ) of 0.614. Satisfactory performance in several validation procedures indicated the reliability and robustness of the model. Docking study was performed to determine the binding mode of these inhibitors inside the active site of Mer kinase. Molecular dynamics simulation was performed on the docked structure to explore the thorough binding process. Docking and molecular dynamics simulation identified some crucial binding residues such Leu593, Pro672, Phe673, Met674, Gly677, Asp678, Thr681, Tyr685, and Met730. This study provides useful information for the design of novel and more potent antithrombotic agents. [ABSTRACT FROM AUTHOR]

Lots of unexpected disinfection by-products were formed during the chlorination disinfection of contaminated water bodies, leading to a potential threat to human health and ecological safety. In this study, SOS/umu assay was used to trace the genotoxicity variation of 20 quinolone compounds during the chlorination disinfection. Furthermore, two- and three-dimensional quantitative structure-activity relationship models were developed based on the electronic and hydrophobic properties of the quinolones, which were used to quantify the impact of the different structural features of the compounds on their genotoxicity variation. The results revealed that quinolones bearing hydrophilic substituents with less H-bond donors and negative charge at the 1-position of the quinolone ring exhibited a positive correlation with genotoxicity elevation. More notably, the chlorination of quinolones in both ultrapure water and secondary effluent matrices provided comparable levels of genotoxicity, indicating that our research could potentially be used to evaluate the environmental risk of quinolone antibiotics in chlorination disinfection treatment. [ABSTRACT FROM AUTHOR]

The p38 mitogen-activated protein kinases belong to the mitogen-activated protein kinase superfamily. They are strongly activated by different stress signals and inflammatory cytokines. p38α mitogen-activated protein kinase is broadly expressed in most cell types and plays an important role in the coordination of the cellular responses such as proliferation, differentiation & survival. The role of p38α in various cancers and cellular functions makes it an interesting kinase drug target. In the present study, a series of recently published disubstituted dibenzosuberones derivatives were taken as p38α inhibitors and three-dimensional quantitative structure-activity relationship study was performed. A reasonable Comparative Molecular Field Analysis ( q = 0.689, NOC = 6, r = 0.942) and Comparative Molecular Similarity Indices Analysis ( q = 0.645, NOC = 6, r = 0.921) models were developed. All the developed models were validated using external test set, bootstrapping, progressive sampling and rm metric calculations. The validation of models showed acceptable statistical values and proved to be predictive and robust. The contour map analysis revealed the important insight on favorable substituents to increase the potency of the compounds. Negative substitution near the oxygen atom of R position and hydrophobic & hydrogen bond acceptor groups near the phenyl ring of R position could enhance the activity. Likewise, positive hydrophobic substitution near the phenyl ring at R position favors the increase in the inhibitory activity. Our finding could be helpful to design a more potent derivative of p38α kinase inhibitors in future. [ABSTRACT FROM AUTHOR]

Lipid peroxidation has been implicated in disease states such as atherosclerosis, asthma, neurodegenerative disorders, Parkinson's disease, cancer, etc. In this study, the anti-lipid peroxidation activity for a series of chromone compounds, evaluated in vitro by ferric thiocyanate and thiobarbituric acid assays, were subjected to three-dimensional quantitative structure-activity relationship studies using comparative molecular field analysis and comparative molecular similarity indices analysis. From ferric thiocyanate assay, the best comparative molecular field analysis and comparative molecular similarity indices analysis models gave cross-validated r ( q ) = 0.563 and 0.593 and non cross-validated r = 0.974 and 0.929, respectively. The best comparative molecular field analysis and comparative molecular similarity indices analysis models derived from thiobarbituric acid assay gave q = 0.558 and 0.612, and non cross-validated r = 0.959 and 0.919, respectively. The generated hydrogen donor contour maps support the previously reported structure-activity relationship that the presence of a catechol moiety in ring A is essential for high potency. [ABSTRACT FROM AUTHOR]

The chronic toxicity of anthropogenic molecules such as substituted benzenes to Daphnia magna is a basic eco-toxicity parameter employed to assess their environmental risk. As the experimental methods are laborious, costly, and time-consuming, development in silico models for predicting the chronic toxicity is vitally important. In this study, on the basis of five molecular descriptors and 48 compounds, a quantitative structure-property relationship model that can predict the chronic toxicity of substituted benzenes were developed by employing multiple linear regressions. The correlation coefficient ( R) and root-mean square error (RMSE) for the training set were 0.836 and 0.390, respectively. The developed model was validated by employing 10 compounds tested in our lab. The R and RMSE for the validation set were 0.736 and 0.490, respectively. To further characterizing the toxicity mechanism of anthropogenic molecules to Daphnia, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed. [ABSTRACT FROM AUTHOR]

Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer's disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r = 0.988, q = 0.757, ONC = 6; r = 0.966, q = 0.645, ONC = 5; and r = 0.957, q = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors. [ABSTRACT FROM AUTHOR]

Bruton tyrosine kinase (Btk) is a non-receptor tyrosine kinase. It is a crucial component in BCR pathway and expressed only in hematopoietic cells except T cells and Natural killer cells. BTK is a promising target because of its involvement in signaling pathways and B cell diseases such as autoimmune disorders and lymphoma. In this work, a combined molecular modeling study of molecular docking, 3D-QSAR and molecular dynamic (MD) simulation were performed on a series of 2,5-diaminopyrimidine compounds as inhibitors targeting Btk kinase to understand the interaction and key residues involved in the inhibition. A structure based CoMFA ( q = 0.675, NOC = 5, r = 0.961) and COMSIA ( q = 0.704, NOC = 6, r = 0.962) models were developed from the conformation obtained by docking. The developed models were subjected to various validation techniques such as leave-five-out, external test set, bootstrapping, progressive sampling and rm metrics and found to have a good predictive ability in both internal and external validation. Our docking results showed the important residues that interacts in the active site residues in inhibition of Btk kinase. Furthermore, molecular dynamics simulation was employed to study the stability of the docked conformation and to investigate the binding interactions in detail. The MD simulation analyses identified several important hydrogen bonds with Btk, including the gatekeeper residue Thr474 and Met477 at the hinge region. Hydrogen bond with active site residues Leu408 and Arg525 were also recognized. A good correlation between the MD results, docking studies and the contour map analysis are observed. This indicates that the developed models are reliable. Our results from this study can provide insights in the designing and development of more potent Btk kinase inhibitors. [ABSTRACT FROM AUTHOR]

c-Met kinase is a recognized target for the development of small-molecule inhibitors for the treatment of cancer. In this study, a diverse set of 74 c-Met kinase inhibitors consisted of 6,7-disubstituted-4-phenoxyquinoline derivatives were used for CoMFA and CoMSIA (3D QSAR). 3D QSAR models were obtained using rigid body (Distill) alignment of training and test set molecules. CoMFA and CoMSIA models were found statistically significant with leave-one-out correlation coefficients ( q) of 0.626 and 0.556, respectively, cross-validated coefficients ( r) of 0.532 and 0.501, respectively, and conventional coefficients ( r) of 0.907 and 0.940, respectively. QSAR models were validated by a test set of 23 compounds giving satisfactory predicted correlation coefficients ( r) of 0.456 and 0.701 for CoMFA and CoMSIA models, respectively. This study will provide clues to design new compounds as c-Met kinase inhibitors. [ABSTRACT FROM AUTHOR]

Mer kinase is a novel cancer therapeutic target. Abnormal activation or overexpression of Mer kinase has been implicated in several human cancers. Three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking studies were performed on a series of pyridinepyrimidine derivatives to understand the structural basis for Mer kinase inhibitory activity. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were used to derive 3D-QSAR models. The CoMFA model produced statistically significant results with a cross-validated correlation coefficient ( q) of 0.634 and a non-cross-validated correlation coefficient ( r) of 0.968. The reliable CoMSIA model with q of 0.665 and r of 0.991 was obtained from the combination of steric, electrostatic, hydrophobic, hydrogen bond acceptor and hydrogen bond donor fields. The CoMFA and CoMSIA models showed reasonable predictive abilities with predicted correlation coefficient ( r) of 0.629 and 0.811, respectively. The models were further evaluated by leave-five-out cross-validation and bootstrapping analyses. Docking studies were carried out to deduce probable binding conformations of this series of inhibitors inside the active site of Mer kinase. Docking studies also contributed to the identification of some crucial binding residues in the active site. The correlation of 3D-QSAR and docking results indicated the robustness of the QSAR models. Overall, a combined application of docking and 3D-QSAR results could provide a better understanding of the interactions between the inhibitors and protein. This study could assist in the design of novel compounds with enhanced Mer kinase inhibitory activity. [ABSTRACT FROM AUTHOR]

Vascular endothelial growth factor-2 receptor (VEGFR-2) kinase is a promising target for the development of novel anticancer drugs. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on a series of tetrahydro-3 H-imidazo[4,5- c]pyridine derivatives to understand the structural basis for VEGFR-2 inhibitory activity. Several 3D-QSAR models were developed using various partial atomic charge schemes. Comparative molecular field analysis (CoMFA) and Comparative molecular similarity indices analysis (CoMSIA) methods were employed to derive these models. The CoMFA models performed better than the CoMSIA models. The reliable CoMFA model was obtained with the Gasteiger-Marsili charge scheme. The model produced statistically significant results with a cross-validated correlation coefficient (q) of 0.635 and a coefficient of determination (r) of 0.930. The model showed reasonable predictive power with predictive correlation coefficient ( $${\text{r}}_{\text{pred}}^{2}$$ ) of 0.582. Robustness of the model was further checked by leave-five-out cross-validation, bootstrapping and progressive scrambling analysis. The model was found to be statistically robust and expected to assist in the design of novel compounds with enhanced VEGFR-2 inhibitory activity. [ABSTRACT FROM AUTHOR]

In this paper, 65 small molecules of HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) were aligned by two different alignment methods (substructure-based and docking-based alignment) for the construction of three-dimensional quantitative structure-activity relationship models. And the molecular descriptors were calculated by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Statistical parameters derived from the models using the above two different alignment methods showed that the docking-based CoMFA and CoMSIA models were better than the substructure-based models with both higher internal consistencies ( q of 0.727 and 0.698, respectively) and external predictive powers ( $$r_{\text{pred}}^{2}$$ of 0.906 and 0.940, respectively). According to the generated contour maps, several key structural features required for increasing the biological activity of compounds were achieved. Additionally, a docking study was also performed to explore the binding mechanisms of this series of compounds, and the obtained binding interactions are in agreement with the results of the contour maps. These structural-based and ligand-based computational studies can offer useful references for the further rational design of HIV-1 NNRTIs. [ABSTRACT FROM AUTHOR]

TAK1 is a member of the MAPKKK family, and it is one of the key molecules in inflammatory signaling pathways. It is an interesting drug target recently because of its role in many signaling pathways and various cellular processes. In the present study, a series of recently published 7-aminofuro [2,3-c] pyridine derivatives were taken as TAK1 antagonists, and 3D QSAR study was performed. A reasonable CoMFA ( q = 0.690 NOC = 6, r = 0.946) and COMSIA ( q = 0.676, NOC = 5, r = 0.904) models were developed. All the developed models were validated using external validation test set, leave five out, bootstrapping, progressive samplings, and rm metrics. Both the models exhibited acceptable values on all validation techniques and, hence, was considered to be robust and predictive. Furthermore, the contour map analysis of CoMFA and COMSIA models exposed important understandings in the substituents to increase the potency of the compounds. Small negative substitutions at R position of five-membered ring found to increase the activity. Similarly, hydrophobic substitution and hydrogen bond acceptor group at the R position of the five-membered ring could increase the activity. Avoiding bulky substitution and hydrogen bond acceptor group near the phenyl ring at R position and R would help in increasing the potency of the compounds. Our finding could be used to design a more potent derivative of TAK1 inhibitors. Graphical abstract: [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Aromatase inhibitors are the most important targets in treatment of estrogen-dependent cancers. In order to search for potent non-steroidal aromatase inhibitors (NSAIs) with lower side effects and overcome cellular resistance, Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database was used to derive 3D pharmacophore models. The obtained best pharmacophore model contains one acceptor atom, one donor atom, and two hydrophobes, which was used in effective alignment of dataset. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 84 structurally diverse NSAIs to build 3D-QSAR models based on both pharmacophore and docking alignments. The CoMFA and CoMSIA models based on the pharmacophore alignment show better statistical results (CoMFA: q = 0.634, r = 0.986, r = 0.737; CoMSIA: q = 0.668, r = 0.926, r = 0.708). This 3D-QSAR approach provides significant insights that can be used to develop novel and potent NSAIs. In addition, the best pharmacophore model was used as a 3D query for virtual screening against NCI2000 database. The hit compounds were further filtered by docking, and their biological activities were predicted by the CoMFA and CoMSIA models, and six structurally diverse compounds with good predicted pIC values were obtained, which are expected to design novel NSAIs with new skeletons. [ABSTRACT FROM AUTHOR]

GPR35, an orphan G protein-coupled receptor, has attracted much attention as a novel therapeutic target for the treatment of diabetes, hypertension, etc. Recently, 8-substituted chromen-4-one-2-carboxylic acid derivatives were identified as potent and selective agonists for human GPR35. In the present study, the three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for a series of 8-substituted chromen-4-one-2-carboxylic acid derivatives using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and Topomer CoMFA techniques implemented in the SYBYL software packages. The statistically significant models were obtained with 30 compounds in training set by ligand-based atom-by-atom matching alignment, which were further validated by a test set of eight compounds. The CoMFA model resulted in cross-validated coefficient ( q) value of 0.610 using 4 components, non-cross-validated coefficient ( r) value of 0.918 with estimated F value of 69.917, and standard error of estimate (SEE) of 0.352. While the CoMSIA model combined with steric, electrostatic and hydrophobic fields were finally selected ( q = 0.646, r = 0.800, F = 53.852, SEE = 0.489, N = 2). For the Topomer CoMFA model, the better statistics were obtained based on fragment units ( q = 0.746, r = 0.979, F = 146.294, SEE = 0.175, N = 7). Furthermore, the contour maps obtained from 3D-QSAR studies were appraised for activity trends for the compounds analyzed. The results indicate that steric, electrostatic, and hydrophobic substituents play a significant role in the agonist activity. The data generated from the present study will further help design novel, potent, and selective agonists for GPR35. [ABSTRACT FROM AUTHOR]

Limited oral bioavailability has hindered the widespread use of flavonoids as bioactive substances. Several studies have been performed to evaluate the transport characteristics of flavonoids in the intestines using cell models, such as Caco-2 cells, but information regarding the key structural features of flavonoids that influence intestinal uptake is still limited to date. In this study, quantitative structure-permeability relationship (QSPR) models were developed to study the permeability of 36 flavonoids through Caco-2 cells using both 2D and 3D approaches. For the 2D model, stepwise multiple linear regression (SMLR) and partial least squares regression (PLSR) resulted in good internal ( R = 0.8, R = 0.93) and external ( R = 0.93, R = 0.90) predictability using a set of 409 molecular descriptors. The high cross-validated (leave-one-out) R values ( Q) for both 2D models ( Q = 0.77, Q = 0.67) suggest that the models are robust and predictive. A pharmacophore (GALAHAD)-based COMSIA analysis was used to generate the 3D QSPR model, which yielded a predictive and robust model ( R = 0.96, R = 0.95, Q = 0.625) composed of hydrogen bond acceptor and donor fields. According to the contour plots, the locations of hydrogen bond acceptors and donors play a crucial role in determining Caco-2 permeability of flavonoids. The models provide deeper insight into the QSPR of flavonoids on intestinal absorption using Caco-2 cell models and could be useful for the high-throughput screening of flavonoids and/or flavonoid-like drugs with health-promoting activities. Graphical Abstract: [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

The present study is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSARs) modeling of 3-benzimidazol-2-ylhydroquinolin-2-one derivatives inhibiting vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase. The 3D-QSARs were established for 36 3-benzimidazol-2-ylhydroquinolin-2-one derivatives as VEGFR-2 tyrosine kinase inhibitors using comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) techniques. The negative logarithm of IC (pIC) was used as the biological activity in the 3D-QSAR study. With the CoMFA model, the cross-validated value ( q) was 0.516, the non-cross-validated value ( R) was 0.927, and the external cross-validated value (Q) was 0.855; with the CoMSIA model, the corresponding q, R, and Q values were 0.538, 0.980, and 0.809, respectively. The CoMFA and CoMSIA models were validated by a structurally diversified test set of nine compounds. Then, molecular docking was carried out to better understand of the interactions between VEGFR-2 tyrosine kinase target and inhibitors. Finally, based on results of the structure-activity relationship and of the molecular docking, seven VEGFR-2 tyrosine kinase inhibitors that showed excellent potencies have been constructed. [ABSTRACT FROM AUTHOR]

Growth suppression of many non-COX-2 expressing tumor cells can be exhibited by COX-2 inhibitors, where supplementation of cells with exogenous prostaglandins fails to rescue the cells from growth inhibition. It can, therefore, be speculated that anti-cancer properties of some COX-2 inhibitors may be contributed by the COX-2-independent effects also. Some of the derivatives obtained from certain COX-2 inhibitors which show non-COX-2 inhibitory mechanism have revealed some significant anti-cancer activities. From a COX-2 selective inhibitor nimesulide, an analog JCC76 is derived which is a non-COX-2 active compound and shows inhibition of SKBR-3 breast cancer cell growth. Other JCC76 derived inhibitors also played significant role in SKBR-3 cell inhibition. An analog-based study was done using pharmacophore modeling and 3D-QSAR to provide clues for potential lead compound designing. A five point pharmacophore ADHRR was generated using 39 JCC76-derived SKBR-3 inhibitors. The validated pharmacophore alignment was used for further 3D-QSAR analysis, which presented a good R value of 0.562, 0.982, and 0.848 for atom-based QSAR, CoMFA, and CoMSIA model, respectively. All the QSAR models presented good statistical significance and predictivity. The corresponding Q values for each model are 0.513, 0.649, and 0.518, respectively. Both the pharmacophore and CoMSIA results displayed that the H-bond donor and acceptor sites are the key structural feature for JCC76-derived non-COX-2-dependent inhibitors with high activity. [ABSTRACT FROM AUTHOR]

Dipeptidyl peptidase-4 (DPP-4) is one of the most attractive targets in the area of type 2 diabetes treatment. Till date, many structurally diverse DPP-4 inhibitors have been explored and published. To identify essential structural features of these diverse DPP-4 inhibitors responsible for antidiabetic activity, three-dimensional quantitative structure-activity relationship analyses were carried out on 36 reported quinoline and isoquinoline derivatives. The studies include comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) using three different alignment methods. The distill rigid body alignment-based CoMFA and CoMSIA models gave best significant results for 27 training set molecules, with cross-validated coefficients ( q) of 0.803 and 0.826, respectively, and conventional coefficients ( r) of 0.991 and 0.983, respectively. Validation by test set of nine molecules gave excellent predicted correlation coefficients ( r) of 0.874 and 0.847 for CoMFA and CoMSIA models, respectively. Detailed analysis of CoMFA and CoMSIA contour maps revealed many helpful structural insights to improve the activity of newly designed quinoline and isoquinoline derivatives as DPP-4 inhibitors for the treatment of type-2 diabetes. [ABSTRACT FROM AUTHOR]

Mer kinase is a novel therapeutic target for many cancers, and overexpression of Mer receptor tyrosine kinase has been observed in several kinds of tumors. To deeply understand the structure-activity correlation of a series of pyridine/pyrimidine analogs as potent Mer inhibitors, a combined molecular docking and three-dimensional quantitative structure-activity relationship modeling was carried out. A comparative molecular similarity indices analysis model was developed based on the maximum common substructure alignment. The optimum model exhibited statistically significant results: the cross-validated correlation coefficient $$q^{2}$$ was 0.599, and non-cross-validated $$r^{2}$$ value was 0.984. Furthermore, the results of internal validation such as bootstrapping, Y-randomization as well as external validation (the external predictive correlation coefficient $$r_\mathrm{ext}^2 =0.728)$$ confirmed the rationality and good predictive ability of the model. Using the crystal structure of Mer kinase, the selected pyridine/pyrimidine compounds were docked into the enzyme active site. Some key amino acid residues were determined, and hydrogen bonding and hydrophobic interactions between Mer kinase and inhibitors were identified. The satisfactory results from this study may aid in the research and development of novel potent Mer kinase inhibitors. [ABSTRACT FROM AUTHOR]

3D QSAR models using 3D pharmacophore, CoMFA, and CoMSIA approaches were developed for a series of quinoline derivatives as PDE4 receptor antagonists. Hypogen method was used to engender the 3D pharmacophore model. The top scoring four feature pharmacophore models, Hypo1 contains one hydrogen-bond acceptor, two hydrogen-bond donors, and a hydrophobic feature. Hypo1 was validated using test set, Fischer's randomization test, and screening of decoy set. CoMFA and CoMSIA models were developed using the alignment obtained by pharmacophore (Hypo1), substructure alignment, and by application of region focusing. Substructure alignment followed by region focusing provided the best CoMFA and CoMSIA models. Based on the results of 3D QSAR studies, some new molecules were designed and evaluated by Docking and Lipinski filters. The designed molecules were synthesized and two top scoring molecules were subjected to preliminary evaluation of their efficacy in treatment of asthma and COPD. The molecules demonstrated efficacy comparable to standard drugs in treatment of asthma and COPD. [ABSTRACT FROM AUTHOR]

Human breast cancer resistance protein (BCRP) belongs to the G subfamily of ATP-binding cassette transporter. Over-expression of BCRP in cancer cells limits the efficacy of many chemotherapeutic agents, resulting in multiple drug resistance. A clear understanding of inhibitor-binding mode will be useful in the design of BCRP-selective inhibitor. To gain structural insights into the active site of BCRP, three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for two different chemical series (flavonoids and chalcones derivatives) of BCRP inhibitors. Stable and statistically reliable predictive CoMFA and CoMSIA models have shown significant $$r_{\rm cv}^{2} > 0.7,\;r_{\rm ncv}^{2} > 0.9,\;r_{\rm bs}^{2} > 0.9,\;r_{\rm pred}^{2} > 0.6$$ and a small standard deviation <0.2, indicating a better statistical relationship between the activity and descriptors. 3D contour maps generated from these models were analyzed individually, which provided the regions in space where interactive fields may influence the inhibitory activity of BCRP inhibitors. The similarity search between site points, generated from contour maps, and binding pockets identified using different pocket search tools, provided essential clues for characterization of the binding site. Molecular docking analysis reveals that Asp643, Asp650, and Val651 of the nucleotide-binding domain play an important role in binding of flavonoids and chalcones. The structural insights obtained from 3D-QSAR and molecular docking studies will serve as a guideline for designing and predicting novel BCRP inhibitors. [ABSTRACT FROM AUTHOR]

Docking experiments on the published crystal structure of enoyl-ACP reductase (1C14.PDB) with potent phenoxy triazoles, phenoxy oxadiazoles, and fused phenoxy triazole compounds have been described to indicate that {2-[(4-amino-5-thioxo-4,5-dihydro-1 H-1,2,4-triazol-3-yl)methoxy]-4-bromophenyl}(phenyl)methanone (compound 2) binds to the enzyme active site. The methoxy and methyl groups seem to play a key role in the binding as well as its biological activity as shown by the structure-activity relationship studies reported for analogs of phenoxy triazole. Furthermore, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed based on the binding conformation predicted by molecular docking. The predicted CoMFA/CoMSIA models showed the satisfactory statistical significance with a good predicted power. The information gained from molecular docking and 3D-QSAR studies gives us a valuable clue for optimizing the lead molecules. Graphical Abstract: [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]