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Hydroxylated polychlorinated biphenyls (HO-PCBs), as the major metabolites of PCBs, have been reported to act as estrogen receptor β (ERβ) agonists. However, the chemical-biological interactions governing their activities toward ERβ have not been elucidated. Therefore, three dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations, to the best of our knowledge, for the first time were performed to explore the correlation between the structures and activities. The best 3D-QSAR model presented higher predictive ability ( R 2 cv =0.543, R =0.6795) based on comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA), respectively. At the same time, the derived contour maps indicated the important structural features required for improving the activity. Furthermore, molecular docking studies and MD simulations predicted the binding mode and the interactions between the ligand and the receptor. All the results would lead to a better understanding of the specific mechanism of HO-PCBs on estrogen receptor β (ERβ).Communicated by Ramaswamy H. Sarma.2 pred =0.5793/ R 2 cv =0.543, R 2 pred =0.6795) based on comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA), respectively. At the same time, the derived contour maps indicated the important structural features required for improving the activity. Furthermore, molecular docking studies and MD simulations predicted the binding mode and the interactions between the ligand and the receptor. All the results would lead to a better understanding of the specific mechanism of HO-PCBs on estrogen receptor β (ERβ).Communicated by Ramaswamy H. Sarma.

Background: JAK2 inhibitors have been proposed as a new therapeutic option for thalassemia therapy. The objective of this study was to discover the key structural features for improving 2-aminopyrimidine derivatives as potential JAK2 inhibitors. Materials & methods: Quantitative structure-activity relationship (QSAR) approaches (hologram QSAR and comparative molecular similarity indices analysis), molecular dynamics simulations, binding energy calculations and pharmacokinetic predictions were employed. Results: Reliable QSAR models, binding mode and binding interactions of JAK2 inhibitors were obtained and these obtained results were used as the key information for rational design of highly potent JAK2 inhibitors. Conclusion: The concept of new potential JAK2 inhibitors integrated from the obtained results was proved, producing two newly designed compounds, D01 and D02, with potential for use as JAK2 inhibitors.

• Constructed a reliable 3D-QSAR model of Thiazole derivatives. • Design of five thiazole compounds as new inhibitors of PIN1 with high predicted activities. • Molecular docking, molecular dynamics and MM/GBSA calculations were used for studying the interactions. For three systems, the most active compound, the control compound, and a newly designed compound. • ADMET study indicated that these compounds had a good predictive activity. Due to the role of enzyme PIN1 in cancer cells, PIN1 is a promising therapeutic target. The study of the mechanism between PIN1 and thiazole inhibitors was carried out operating 3D-QSAR modeling, molecular docking, molecular dynamics simulations, in order to design high activity inhibitors. The optimal CoMSIA / SH model showed good reliability and satisfactory predictability Q2 = 0.717, R2 = 0.961, R2 pred = 0.740. The predictability and precision of the generated model were assessed by the criteria of Golbraikh and Tropsha. The CoMSIA model with a contribution from steric and hydrophobic fields (CoMSIA/SH) passes all these validation protocols successfully, therefore the established model is reliable. The analysis of Contour map analysis may provide structural information to improve inhibitory function. Furthermore, molecular docking and MD simulations show stability and provide information on ligand-receptor interactions. The results served as the basis for developing new compounds and their expected inhibitory activities. The result of the physicochemical and ADMET / pharmacokinetic properties showed that these five proposed molecules are bioavailable by the oral route, high gastrointestinal absorption, good permeability and therefore do not inhibit CYP3A4 and CYP2D6. In addition, nontoxic to the Ames test and therefore these results would provide the necessary physicochemical and pharmacokinetic properties and relevant information in the analysis drug discovery [ABSTRACT FROM AUTHOR]

• 3D-QSAR studies on 37 reported 2-phenylquinazolin-4-one derivatives was performed. • CoMFA, CoMSIA, topomer CoMFA and HQSAR techniques were used to generate the QSAR models. • Statistical results and contour maps of each QSAR model were analyzed and interpreted. • Critical ligand substitutions required for the design of novel potent tankyrase inhibitors were summarized. Tankyrase is an emerging target of 17 membered poly(ADP-ribose)polymerase enzyme family for the treatment of Wnt driven cancers. TNKS are associated with many cellular functions; Wnt–β-catenin signaling, telomere homeostasis, mitotic spindle formation etc. The inhibition of cell growth could be achieved by the inhibition of TNKS through Wnt-signaling mechanism. To develop novel lead molecules as tankyrase inhibitors, we performed 3D-QSAR studies on 37 reported 2-phenylquinazolin-4-one derivatives. Training set contained 29 while test set contained 8 molecules. Four different techniques, CoMFA, CoMSIA, Topomer CoMFA and HQSAR were used to generate the QSAR models. Distill alignment based CoMFA analysis showed q2 value of 0.605, r2 ncv value of 0.958 and r2 pred value of 0.553. Optimized CoMSIA analysis (SEHD) showed q2 value of 0.580, r2 ncv value of 0.953 and r2 pred value of 0.723. Topomer CoMFA analysis showed q2 value of 0.684, r2 (conventional correlation coefficient) value of 0.955 and r2 pred value of 0.721. HQSAR analysis showed q2, r2 and r2 pred values of 0.833, 0.951 and 0.753, respectively. Combined results of all studies provided significant output in terms of substitutions required for activity and can be used for the design of novel quinazolinone derivatives as potent tankyrase inhibitors. [Display omitted] [ABSTRACT FROM AUTHOR]

With the increasing patients suffered from AIDS, highly active antiretroviral therapy is considered as the most effective way to control this disease, leading to an urgent need for new potent drug discovery. Recently, a series of NNRTIs belonging to DAPY and DANA family was reported as promising anti-HIV agents. The CoMFA and CoMSIA analysis were conducted to build up 3D-QSAR models with satisfactory statistical parameters (q 2 = 0.887 and R 2 = 0.988 for CoMFA model, q 2 = 0.901 and R 2 = 0.990 for the optimal CoMSIA model). In order to perform further validation of the 3D-QSAR models, a SMILES-based software CORAL was applied to build up the 2D-QSAR model, which also provided essential structural information for further modifications. All three models showed excellent predictability. Combination of analysis of 3D contour maps derived from CoMFA and CoMSIA models and analysis of 2D molecular fragments derived from CORAL software gave insights into the design of novel anti-HIV agents. [ABSTRACT FROM AUTHOR]

Highlights: [•] Ligand based pharmacophore model was developed and validated for LRH-1 agonists. [•] Three different databases were screened by means of validated pharmacophore model. [•] CoMFA and CoMSIA models were developed and validated. [•] Docking analysis shows that His390 and Arg393 plays important role in binding of agonists. [ABSTRACT FROM AUTHOR]

Matrix metalloproteinase (MMPs) are a family of calcium-dependent zinc-containing endopeptidases which are responsible for the tissue remodeling and degradation of the extracellular matrix (ECM), including collagens, elastins, gelatin, matrix glycoproteins, and proteo- glycan. In this study, by using molecular docking and 3D-QSAR analysis we get new insights into the relationship between experimental IC50 values and their descriptors obtained from CoMSIA and CoMFA programs. Obtained information on molecular structural of a series of β-N-biaryl ether sulfonamide hydroxamates as potential MMP inhibitors, that can be used to understand the drug receptor interactions of these kind of molecules. [ABSTRACT FROM AUTHOR]

Cholesteryl ester transfer protein (CETP) converts high density lipoprotein cholesterol to low density lipoproteins. It is a promising target for treatment of coronary heart disease. Two dimensional quantitative structure activity relationship (2D-QSAR), hologram QSAR (HQSAR) studies and comparative molecular field analysis (CoMFA) as well as comparative molecular similarity analysis (CoMSIA) were performed on 104 CETP inhibitors. The statistical qualities of generated models were justified by internal and external validation, i.e., q² and Rpred² respectively. The best 2D-QSAR model was obtained with q² and Rpred² values of 0.794 and 0.796 respectively. The 2D-QSAR study suggests that unsaturation, branching and van der Waals volumes may play important roles. The HQSAR model showed q² and Rpred² values of 0.628 and 0.550 respectively. Similarly, CoMFA model showed q² and Rpred² values of 0.707 and 0.755 respectively whereas CoMSIA model was obtained with q² and Rpred² values of 0.696 and 0.703 respectively. CoMFA and CoMSIA studies indicate that steric factors are important at substituted phenoxy and tetrafluoroethoxy groups whereas electropositive factors play important role at difluoromethyl group. The results of 3D-QSAR studies validate those of 2D-QSAR and HQSAR studies as well as the earlier observed SAR data. Current work may help to develop better CETP inhibitors. [ABSTRACT FROM AUTHOR]

Abstract: The octanol/air partition coefficient (K OA) is a key physicochemical parameter for describing the partition of organic pollutants between air and environment organic phase. The development of appropriate method to estimate K OA is of great importance. In the present study, the steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor descriptors were computed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). On the basis of these parameters, the statistically quantitative structure–property relationship (QSPR) models for logK OA of hydroxylated polybrominated diphenyl ethers (OH-PBDEs) and methoxylated polybrominated diphenyl ethers (MeO-PBDEs) congeners were developed using partial least-squares (PLS) analysis, of which the R 2 is about 0.980, 0.952 respectively. The electrostatic field was found to be main factors governing the logK OA. The results of validation indicate the models of this study exhibit optimum stability, and thus it is feasible to predict logK OA. [Copyright &y& Elsevier]

Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed based on a series of azaindole carboxylic acid derivatives that had previously been reported as promising HIV-1 integrase inhibitors. Docking studies to explore the binding mode were performed based on the highly active molecule 36. The best docked conformation of molecule 36 was used as template for alignment. The comparative molecular field analysis (CoMFA) model (including steric and electrostatic fields) yielded the cross validation q² = 0.655, non-cross validation r²= 0.989 and predictive rprcd² = 0.979. The best comparative molecular similarity indices analysis (CoMSIA) model (including steric, electrostatic, hydrophobic and hydrogen-bond acceptor fields) yielded the cross validation q² = 0.719, non-cross validation r² = 0.992 and predictive rprcd² = 0.953. A series of new azaindole carboxylic acid derivatives were designed and the HIV-1 integrase inhibitory activi-ties of these designed compounds were predicted based on the CoMFA and CoMSIA models. [ABSTRACT FROM AUTHOR]

Cyclin-dependent kinase 2 (CDK.2) has been identified as an important target for developing novel anticancer agents. Molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) and pharmacophore modelling were combined with the ultimate goal of studying the structure-activity relationship of CDK.2 inhibitors. The comparative molecular similarity indices analysis (CoMSIA) model constructed based on a set of 3-amino-pyraxole derivatives as CDK2 inhibitors gave statistically significant results (q² = 0.700; r² = 0.982). A HypoGen pharmacophore model, constructed using diverse CDK2 inhibitors, also showed significant statistics (ΔCost = 61.483; RMSD = 0.53; Correlation coefficient = 0.98). The small residues and error values between the estimated and experimental activities of the training and test set compounds proved their strong capability of activity prediction. The structural insights obtained from these two models were consistent with each other. The pharmacophore model summarized the important pharmacophoric features required for protein-ligand binding. The 3D contour maps in combination with the comprehensive pharmacophore features helped to better interpret the structure-activity relationship. The results will be beneficial for the discovery and design of novel CDK.2 inhibitors. The simplicity of this approach provides expansion to its applicability in optimizing other classes of small molecular CDK2 inhibitors. [ABSTRACT FROM AUTHOR]

β-Amyloid precursor protein cleavage enzyme (BACE) has been shown to be an attractive therapeutic target to control Alzheimer's disease (AD). Inhibition of β-secretase enzyme can prevent the deposition of Aβ (β-amyloid) peptides, which is thought to be the major cause of AD. The present study has been considered to explore 3D-QSAR, HQSAR, and pharmacophore mapping studies of BACE inhibitors. Contour maps of 3D-QSAR studies (CoMFA: R = 0.998, se = 0.067, Q = 0.765, R = 0.772, r = 0.739; CoMSIA: R = 0.992, se = 0.125, Q = 0.730, R = 0.713, r = 0.687) explain the importance of steric and electrostatic, along with hydrogen-bond (HB) acceptor and donor for binding affinity to BACE. HQSAR study ( R = 0.941, se = 0.326, Q = 0.792, R = 0.713, r = 0.709) indicates the important fragments of the molecular fingerprints that might be crucial for binding affinity. Pharmacophore space modeling ( R = 0.937, rmsd = 0.937, Q = 0.935, R = 0.709, r = 0.837) describes that HB acceptor, donor, hydrophobic, and steric are the important features for interaction with receptor cavity. Finally, the models are adjudged through the docking study elucidating the interactions between the receptor and the ligand, indicating the structural requirements of potent BACE inhibitors. [ABSTRACT FROM AUTHOR]

3D-QSAR CoMFA, CoMSIA and docking studies were performed on a set of 4-azasteroidal human steroid 5α-reductase inhibitors. The models developed using maximal common substructure-based alignment was found to be reliable and significant with good predictive r value. CoMSIA model developed using combination of steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor features has shown r = 0.564 with six optimum components, r = 0.945, F value = 101.196, r = 0.693 and SEE = 0.209. The contour plots obtained has shown a favourable effect of bulkier groups at C-17 position. Docking studies indicates the importance of bulkier groups at C-17 position for favourable activity. The study further helps in design of potent inhibitors of the enzyme. [ABSTRACT FROM AUTHOR]

Checkpoint kinase 1(Chk1) is a promising target for cancer treatment. Here three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on 174 1,4-dihydroindeno[1,2-c]pyrazole inhibitors of Chk1 using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Two satisfactory ligand-based QSAR models were built (CoMFA model: q = 0.541, r = 0.880, CoMSIA model: q = 0.590, r = 0.902). The docking-based studies presented a detailed understanding of interaction between the inhibitors and Chk1. The obtained QSAR models are highly predictable (CoMFA model: q = 0.567, r = 0.891, CoMSIA model: q = 0.596, r = 0.917). The models were further validated by an external testing set obtaining $$ r_{\text{pred}}^{2} $$ values 0.896 and 0.923 for CoMFA and CoMSIA, respectively. So our models might be helpful for further modification of 1,4-dihydroindeno[1,2-c]pyrazole derivatives. [ABSTRACT FROM AUTHOR]

Human telomeres are repetitive guanine rich sequences found at the ends of chromosomes that form special secondary structures known as G-quadruplexes. In majority of cancer cells, the telomerase enzyme has been found to maintain the length of telomeres, conferring cell immortality and prevention of cell senescence. Small molecules that bind and stabilize the G-quadruplex have proved to be potential telomerase inhibitors. The quantitative structure-activity relationships of triazine derivatives as G-quadruplex mediating telomerase inhibitors remain unclear. The objective of the study is to uncover structural requirements for triazine derivatives as G-quadruplex binders, which would eventually assist and complement the rational drug-design attempts for successful development of telomerase inhibitors as anticancer drugs. The model has been established by using a training set of compounds with cross-validated q 0.593, non-cross-validated r 0.976, standard error of estimate 0.167, and F test 115.130 for the best CoMSIA model. The predictive ability of the models was validated with the correlation coefficient r 0.738 for the best CoMSIA model. The highly predictive 3D-model resulting from this study discovers the roles played by molecular features, mainly steric, hydrogen bond donor and hydrophobic properties. [ABSTRACT FROM AUTHOR]

Obesity and the metabolic syndrome are pandemic diseases with high morbidity and mortality. With the aim of discovering novel therapies for those diseases, the cannabinoid receptor 1 (CB1), which has been validated as a target for treating appetitive disorders, is now considered a novel target for the design of anti-obesity compounds. Our main goal was to determine the activity landscape of pyrazole derivatives and to develop reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) models. Structure-activity similarity (SAS) maps of pyrazole analogs acting as antagonists of CB1 were constructed in order to identify activity cliffs, compounds that have high structural similarity with the rest of the compound set, but low activity similarity. According to the SAS maps, one molecule was identified as an outlier and before comparative molecular field analysis (COMFA) and comparative molecular similarity analysis (CoMSIA) 3D-QSAR models were derived. The best models resulted in an r value of 0.992 and a q of 0.766 for CoMFA and an r of 0.983 and a q of 0.681 for CoMSIA. Contour plots identified that the R position at the pyrazole moiety is an important feature for the optimization of the binding affinity to the CB1 receptor. According to our results, these models can be a useful tool for the design and prediction of novel CB1 antagonists. [ABSTRACT FROM AUTHOR]

Abstract: As a development strategy for backups of Fimasartan (1), a comparative molecular similarity indices analysis (CoMSIA) of a set of sixty-five 5-(biphenyl-2-yl)-1H-tetrazole derivatives has been performed to find out the pharmacophore elements for angiotensin II receptor type 1 (AT1) blockade. The most potent compound containing pyrimidin-4(3H)-one ring, Fimasartan (1) was used to align the molecules. As a result, we obtained 3D-QSAR model which provided good predictivity for both the training set (q 2 =0.846, r 2 =0.975) and the external test set . This model would guide the design of backups for Fimasartan (1), a launched oral antihypertensive agent. [Copyright &y& Elsevier]

Highlights: [•] We developed QSAR models for a series of 41 azacycles CCR5 antagonists using CoMFA, CoMSIA and Topomer CoMFA methods. [•] Molecular docking method was used to analyses possible interactions between CCR5 and azacycles derivatives. [•] The results of molecular docking and 3D-QSAR studies supported one another. [•] A set of novel derivatives with predicted activities were designed. [ABSTRACT FROM AUTHOR]

Highlights: [•] 3-Dimensional QSAR, CoMFA and CoMSIA studies of radical scavenging activity of novel chromone series have been performed. [•] The best CoMFA and CoMSIA models gave good statistical outcomes. [•] The contour maps provided structural features of new compounds with improved activity. [Copyright &y& Elsevier]

SGLT2 has become a target of therapeutic interest in diabetes research. CoMFA and CoMSIA studies were performed onC-aryl glucoside SGLT2 inhibitors (180 analogues) as potential anti-diabetic agents. Three different alignment strategies were used for the compounds. The best CoMFA and CoMSIA models were obtained by means of Distill rigid body alignment of training and test sets, and found statistically significant with cross-validated coefficients (q2) of 0.602 and 0.618, respectively, and conventional coefficients (r2) of 0.905 and 0.902, respectively. Both models were validated by a test set of 36 compounds giving satisfactory predicted correlation coefficients (r2pred) of 0.622 and 0.584 for CoMFA and CoMSIA models, respectively. A comparison was made with earlier 3D QSAR study on SGLT2 inhibitors, which shows that our 3D QSAR models are better than earlier models to predict good inhibitory activity. CoMFA and CoMSIA models generated in this work can provide useful information to design new compounds and helped in prediction of activity prior to synthesis. [ABSTRACT FROM AUTHOR]

CoMFA and CoMSIA based 3D-QSAR of HIV-1 RT wild and mutant (K103, Y181C, and Y188L) inhibitory activities of 4-benzyl/benzoyl pyridin-2-ones followed by protein informatics of corresponding non-nucleoside inhibitors' binding pockets from pdbs 2BAN, 3MED, 1JKH, and 2YNF were analysed to discover consensus features of the compounds for broad-spectrum activity. The CoMFA/CoMSIA models indicated that compounds with groups which lend steric-cum-electropositive fields in the vicinity of C5, hydrophobic field in the vicinity of C3 of pyridone region and steric field in aryl region produce broad-spectrum anti-HIV-1 RT activity. Also, a linker rendering electronegative field between pyridone and aryl moieties is common requirement for the activities. The protein informatics showed considerable alteration in residues 181 and 188 characteristics on mutation. Also, mutants' isoelectric points shifted in acidic direction. The study offered fresh avenues for broad-spectrum anti-HIV-1 agents through designing new molecules seeded with groups satisfying common molecular fields and concerns of mutating residues. [ABSTRACT FROM AUTHOR]

Highlights: [•] Robust and predictive models were built by using MLR, CoMFA and CoMSIA methods. [•] Position R1: A small hydrophobic electro-donating group benefits the bioactivity. [•] Position R2: A hydrophobic and electronegative atom is expected, especially halogen. [•] Position R4: Important to the solubility, an electro-withdrawing group is expected. [•] Position R5: A bulky connected with benzene by an electro-donating atom is preferred. [Copyright &y& Elsevier]

Conformational alignment is the most important step in 3D-QSAR methodology. There are various methods available to create an alignment hypothesis for the compounds being studied in 3D-QSAR. Most famous alignment methods include: alignment on a suitable template conformation, field fit alignment, database alignment, pharmacophore-based alignment, atom fit, and docking based alignment. All of the above-mentioned methods were explored previously to sample the conformational space in 3D-QSAR. Current study is dealing with the situation where most of the alignment methods were failed to produce a statistically robust 3D-QSAR model. Therefore, a relatively new alignment scheme was employed using ROCS (Rapid Overlay of Chemical Structures) method from OpenEyes. In the present study, Combretastatin A-4 based Tubulin inhibitors were used as case study. Co-crystal ligand conformation (i.e., Colchicine) in the Tubulin complex structure (PDB ID: 1SA0) was utilized as a template molecule. To date, very few applications of ROCS-based alignments in 3D-QSAR are reported in literature. Therefore, current study will serve as an addition to the existing status of using ROCS in 3D-QSAR. Genetic algorithm was utilized to build final 3D-QSAR model. Correlation obtained from final model suggesting that robust 3D-QSAR model was constructed. [ABSTRACT FROM AUTHOR]

Highlights: [•] Surflex-dock poses show greater observed propensity of hydrogen bonding with NH of Ile 150 compared to Glide poses. [•] The docking scores of Surflex-dock poses correlate better with experimental binding affinities than Glide docked poses. [•] Pose prediction accuracy is improved when urea core constraints are imposed during the docking of the THP ligands. [•] 3-D QSAR CoMFA and CoMSIA models developed using Surflex-SIM (Sybyl-X) and Phase_Shape (Maestro) alignments have similar predictive powers. [ABSTRACT FROM AUTHOR]

Janus kinase 2 (JAK2) is an intracellular nonreceptor tyrosine kinase that belongs to the JAK family of kinases, which play an important role in survival, proliferation, and differentiation of a variety of cells. JAK2 inhibitors are potential drugs for the treatment of myeloproliferative neoplasms. The three dimensional quantitative structure-activity relationships have been studied on a series of JAK2 inhibitors by comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA). The CoMFA model had a cross-validated coefficient q2 of 0.633, and the relation non-cross-validated coefficient r2 of 0.976. The F value is 225.030. The contributions of steric and electrostatic fields to the activity are 55.2% and 44.8%, respectively. For the CoMSIA study, the q2, r2, and F values of the model are 0.614, 0.929, and 88.771, respectively. The contributions of steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond donor fields to the activity are 27.3%, 23.9%, 16.4%, 21.7%, and 10.7%, respectively. The CoMFA and CoMSIA models showed strong predictive ability, and the 3D contour plots give the basis on the structure modification of JAK2 inhibitors. [ABSTRACT FROM AUTHOR]

Background: Tremendous research from last twenty years has been pursued to cure human life against HIV virus. A large number of HIV protease inhibitors are in clinical trials but still it is an interesting target for researchers due to the viral ability to get mutated. Mutated viral strains led the drug ineffective but still used to increase the life span of HIV patients. Results: In the present work, 3D-QSAR and docking studies were performed on a series of Danuravir derivatives, the most potent HIV- protease inhibitor known so far. Combined study of 3D-QSAR was applied for Danuravir derivatives using ligand-based and receptor-based protocols and generated models were compared. The results were in good agreement with the experimental results. Additionally, docking analysis of most active 32 and least active 46 compounds into wild type and mutated protein structures further verified our results. The 3D-QSAR and docking results revealed that compound 32 bind efficiently to the wild and mutated protein whereas, sufficient interactions were lost in compound 46. Conclusion: The combination of two computational techniques would helped to make a clear decision that compound 32 with well inhibitory activity bind more efficiently within the binding pocket even in case of mutant virus whereas compound 46 lost its interactions on mutation and marked as least active compound of the series. This is all due to the presence or absence of substituents on core structure, evaluated by 3D-QSAR studies. This set of information could be used to design highly potent drug candidates for both wild and mutated form of viruses. [ABSTRACT FROM AUTHOR]

A three-dimensional quantitative structure-activity relationship of 66 structurally and functionally diverse series of 1-substituted imidazoles with antifungal activity was studied using the CoMSIA method. The compounds were divided into a training set of 56 molecules and a test set of 10 molecules. The optimum CoMSIA model obtained for the training set were all statistically significant with cross-validated coefficients ( q) of 0.725 and conventional coefficients ( r) of 0.998. The predictive ability of CoMSIA was determined using a test set of ten imidazole derivatives. CoMSIA model (Model 1) obtained from steric, electrostatic, and H-bond acceptor fields were found to have best predictivity with a predictive correlation coefficient ( r) of 0.60. Based upon the information derived from CoMSIA, it is evident that steric, electrostatic, and hydrogen bond acceptor groups may be important for the design of more potent imidazole analogs as potent Candida P450DM inhibitors. [ABSTRACT FROM AUTHOR]

Comparative molecular field analysis (CoMFA), comparative molecular field analysis region focusing (CoMFA-RF) for optimizing the region for the final partial least square analysis, and comparative molecular similarity indices analysis (CoMSIA) methods were employed to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) models of 1H NMR chemical shift of NH proton of diaryl triazene derivatives. The best orientation was searched by all-orientation search (AOS) strategy to minimize the effect of the initial orientation of the structures. The predictive abilities of CoMFA-RF and CoMSIA models were determined using a test set of ten compounds affording predictive correlation coefficients of 0.721 and 0.754, respectively, indicating good predictive power. For further model validation, cross validation (leave one out), progressive scrambling, and bootstrapping were also applied. The accuracy and speed of obtained 3D-QSAR models for the prediction of 1H NMR chemical shifts of NH group of diaryl triazene derivatives were greater compared to some computational well-known procedures. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Multidrug resistance (MDR) plays a crucial role in the failure of cancer treatment with chemotherapeutic agents. In order to overcome the MDR, we have developed both 2D and 3D-QSAR models to enhance the structural requirement for P-gp inhibitors. In this work, hologram quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of arylmethylamine-phenyl derivatives of P-gp inhibitors. The best predictions were obtained for HQSAR model ( q = 0.645, r = 0.772), CoMFA model ( q = 0.577, r = 0.917), and CoMSIA model (electrostatic, and H-bond donor) ( q = 0.610, r = 0.923). Statistical parameters from the generated QSAR models indicated that the data is well fitted and have high predictive ability. HQSAR result showed that donor and acceptor descriptors play an important role in P-gp activity, and methoxy group on the A-ring at R position is necessary for increasing activity. The CoMFA and CoMSIA models predicted that steric, electrostatic, and H-bond donor parameters are important for activity toward P-gp. Our theoretical results could be useful to design novel and more potent P-gp derivatives. [ABSTRACT FROM AUTHOR]

Malaria is currently one of the world's most severe endemic diseases, responsible for majority of morbidity and mortality. A large number of drugs are available for its treatment; however, the development of resistance has become more widespread with most of the frontline drug therapies. Inhibitors of PfDHODH have proven efficacy for the treatment of malaria. 3D QSAR studies on some 5-(2-methylbenzimidazol-1-yl)- N-alkylthiophene-2-carboxamide derivatives as PfDHODH inhibitors were performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods to rationalize the structural requirements responsible for the inhibitory activity of these compounds. The alignment strategy was used for these compounds by means of Distill function defined in SYBYL x 1.2. The best CoMFA and CoMSIA models obtained for the training set were statistically significant with q of 0.669 and 0.727, cross-validated coefficient ( r) of 0.603 and 0.698, and conventional coefficients ( r) of 0.971 and 0.966, respectively. Both the models were validated by an external test set of five compounds giving satisfactory prediction ( r) of 0.799 and 0.815 for CoMFA and CoMSIA models, respectively. Further the robustness of the model was verified by bootstrapping analysis. Generated CoMFA and CoMSIA models provide useful information for the design of novel inhibitors with better PfDHODH inhibitory activity. [ABSTRACT FROM AUTHOR]

3D-QSAR methods, CoMFA region focusing (CoMFA-RF) and CoMSIA along with docking studies carried out for investigating 32 carbonic anhydrase I inhibitors. These inhibitors have been studied for the development of antiglaucoma, antitumor, antiobesity or anticonvulsant drugs. Docking analysis by GOLD provide conformations which have been realigned in CoMFA and CoMSIA models. Training set for the CoMFA–RF and CoMSIA models using 24 docked conformations gives q2Loo values of 0.615 and 0.637 and r2nv values of 0.701 and 0.713, respectively. The results of CoMFA-RF and CoMSIA with and without docked conformations were compared. The ability of prediction and robustness of the models were evaluated by test set, cross validation (leave-one-out and leave-ten-out), bootstrapping, and progressive scrambling approaches. The all-orientation search (AOS) was used to achieve the best orientation to minimize the effect of initial orientation of the structures. The docking results confirmed CoMFA and CoMSIA contour maps. [ABSTRACT FROM AUTHOR]

"cytochrome P450" family of enzymes are present in every cell and are responsible for biotransformation of drugs from active to inactive metabolites that are readily excreted by the body., the rapid metabolism of certain drugs by the CYP450 enzyme system can markedly alter their pharmacokinetic (PK) profile and can result in sub-therapeutic plasma levels of those drugs over time. To understand the ligand structural requirements and to enhance inhibitory potency for new ligands against CYP-450 enzyme system, 3D- QSAR comparative molecular field analysis (CoMFA) study was carried out on a series of 2-[3-(4-fluorobenzyl)-5-pyridin-4-yl-1H-pyrazol-1-yl] derivatives, as selective CYP- 450 enzyme system inhibitors. Comparative molecular field analysis (CoMFA) QSAR models were computed with Sybyl 6.7v. The developed model gave leave-one-out (LOO) cross-validated correlation coefficient q2 value of 0.844, non-cross-validated correlation coefficient r2 value of 0.992, and the predicted correlation coefficient r2pred was found to be 0.781. The QSAR model gave satisfactory statistical results in terms of q2 and r2 values. The CoMFA model provided the most significant correlation of steric and electrostatic fields with biological activities. The information derived from this study provides a tool for guiding further structural modification to obtain selective inhibitors of CYP450. [ABSTRACT FROM AUTHOR]

As a fundamental factor in acquired immunodeficiency syndrome (AIDS) therapy, it has been shown that HIV-1 protease inhibitors to be an important in restraining HIV-1. In the present study, the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling was conducted on a series of phenyloxazolidinone derivatives. The comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), performed on the training set of 51 compounds, and the optimum PLS model on CoMFA/CoMSIA descriptors showed 'leave-one-out' cross-validation correlation coefficients ( Q) of 0.772 and 0.720 as well as the non-cross-validated correlation coefficients ( R) of 0.966 and 0.963, respectively. Furthermore, the satisfactory results, based on the bootstrapping analysis and tenfold cross-validation, suggest the highly statistical significance of the optimal model. The statistical parameters from the models indicate that the data are well fitted and have high predictive ability. Moreover, the resulting 3D CoMFA/CoMSIA contour maps provide useful guidance for designing highly active inhibitors. The external predictive capability of the established model was evaluated by an external test set of 16 compounds, resulting in the predicted correlation coefficients ( R) of 0.9848 and 0.9291, respectively. It is recommended that the bulky electron-donating substituents at the regions A and D can increase the biological activities of the inhibitors. It is expected that the developed model could provide some useful information for the future synthesis of highly potent HIV-1 protease inhibitors. [ABSTRACT FROM AUTHOR]

p38 kinase plays a vital role in inflammation mediated by tumor necrosis factor-α and interleukin-1β pathways. Inhibition of p38 kinase provides an effective way to treat inflammatory diseases. 3D-QSAR study was performed to obtain reliable comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for a series of p38 inhibitors with three different alignment methods (Receptor based, atom by atom matching, and pharmacophore based). Among the different alignment methods, better statistics were obtained with receptor-based alignment (CoMFA: q = 0.777, r = 0.958; CoMSIA: q = 0.782, r = 0.927). Superposing CoMFA/CoMSIA contour maps on the p38 active site gave a valuable insight to understand physical factors which are important for binding. In addition, this pharmacophore model was used as a 3D query for virtual screening against NCI database. The hit compounds were further filtered by docking and scoring, and their biological activities were predicted by CoMFA and CoMSIA models. [ABSTRACT FROM AUTHOR]

While some synthetic chemicals have been demonstrated to disrupt normal endocrine function by binding to the androgen receptor (AR), the mechanism by which ligands bind to the ligand binding domain (LBD) remained unclear. In this study, docking and comparative molecular similarity index analysis (CoMSIA) were performed to study the AR ligand binding mechanism of steroids and non-steroidal chemicals. The obtained docking conformations and predictive CoMSIA models (values as 0.842 and 0.554) indicated the primary interaction site and key residues in the binding process. The major factors influence the binding affinity of steroids and non-steroidal chemicals were electrostatic and hydrophobic interactions, respectively. The results indicated that besides amino-acid residues Gln711, Arg752 and Thr877 which have previously been reported to be important in binding ligands, Leu701 and Leu704 are also important. Residues Val746, Met749 and Phe764 are crucial only for steroids, while Met742 and Met787 are important only for non-steroidal chemicals. This knowledge of key interactions and important amino-acid residues governing ligands to the AR allow better prediction of potency of AR agonists so that their potential to disrupt AR-mediated pathways and to design less potent alternatives. [Copyright &y& Elsevier]

This study reports the utilization of three approaches – pharmacophore, CoMFA/CoMSIA and HQSAR studies – to identify the essential structural requirements in 3D chemical space for the modulation of the antimalarial activity of substituted 1,2,4-trioxanes. The superiority of quantitative pharmacophore-based alignment (QuantitativePBA) over global minima energy conformer-based alignment (GMCBA) has been reported in CoMFA and CoMSIA studies. The developed models showed good statistical significance in internal validation (q2, group cross-validation and bootstrapping) and performed very well in predicting the antimalarial activity of test set compounds. Structural features in terms of their steric, electrostatic and hydrophobic interactions in 3D space have been found to be important for the antimalarial activity of substituted 1,2,4-trioxanes. Further, the HQSAR studies based on the same training and test set acted as an additional tool to find the sub-structural fingerprints of substituted 1,2,4-trioxanes for their antimalarial activity. Together, these studies may facilitate the design and discovery of new substituted 1,2,4-trioxanes with potent antimalarial activity. [ABSTRACT FROM AUTHOR]

Polybrominated diphenyl ethers (PBDEs) have become ubiquitous contaminations due to their use as flame retardants. The structural similarity of PBDE to some dioxin-like compounds suggested that they may share similar toxicological effects: they might activate the aryl hydrocarbon receptor (AhR) signal transduction pathway and thus might have adverse effects on wildlife and humans. In this study, in silico computational workflow combining molecular docking and three-dimensional quantitative structure–activity relationship (3D-QSAR) was performed to investigate the binding interactions between PBDEs and AhR and the structural features affecting the AhR binding affinity of PBDE. The molecular docking showed that hydrogen-bond and hydrophobic interactions were the major driving forces for the binding of ligands to AhR, and several key amino acid residues were also identified. The CoMSIA model was developed from the conformations obtained from molecular docking and exhibited satisfactory results as q 2 of 0.605 and r 2 of 0.996. Furthermore, the derived model had good robustness and statistical significance in both internal and external validations. The 3D contour maps generated from CoMSIA provided important structural features influence the binding affinity. The obtained results were beneficial to better understand the toxicological mechanism of PBDEs. [ABSTRACT FROM AUTHOR]

Chemokine receptor 5 (CCR5) is an important receptor used by human immunodeficiency virus type 1 (HIV-1) to gain viral entry into host cell. In this study, we used a combined approach of comparative modeling, molecular docking, and three dimensional quantitative structure activity relationship (3D-QSAR) analyses to elucidate detailed interaction of CCR5 with their inhibitors. Docking study of the most potent inhibitor from a series of compounds was done to derive the bioactive conformation. Parameters such as random selection, rational selection, different charges and grid spacing were utilized in the model development to check their performance on the model predictivity. Final comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were chosen based on the rational selection method, Gasteiger-Hückel charges and a grid spacing of 0.5 Å. Rational model for CoMFA ( q = 0.722, r = 0.884, Q = 0.669) and CoMSIA ( q = 0.712, r = 0.825, Q = 0.522) was obtained with good statistics. Mapping of contour maps onto CCR5 interface led us to better understand of the ligand-protein interaction. Docking analysis revealed that the Glu283 is crucial for interaction. Two new amino acid residues, Tyr89 and Thr167 were identified as important in ligand-protein interaction. No site directed mutagenesis studies on these residues have been reported. [ABSTRACT FROM AUTHOR]

The peroxisome proliferator-activated receptors (PPARs) have increasingly become attractive targets for developing novel therapeutics for Type 2 Diabetes. Three dimensional-quantitative structure-activity relationship approach has been applied to a series of α-substituted 3-phenylpropanoic acid and tyrosine derivatives, reported as PPARα/γ dual agonists. Comparative molecular similarity indices analysis has been employed in correlating pharmacological data available for single enantiomer at individual receptor subtype. Three models: PPARα, PPARγ and PPARdual-model, using sum of individual activities as dependent parameter, are developed with statistically significant r > 0.5 and r > 0.9 and lower values of standard error of estimation. This information can be used to design and prediction of enantioselective novel PPAR agonists. Activities of two sets of designed new molecules have also been predicted using generated models. [ABSTRACT FROM AUTHOR]

As a basis for predicting structural features that may lead to the design of more potent and selective inhibitors of urease, the three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out on a series of 30 bis-coumerine analogs, which are known urease inhibitors. Five different properties: steric, electrostatic, hydrophobic, H-bond donor, and H-bond acceptor, assumed to cover the major contributions to ligand binding, were used to generate the 3D-QSAR model. A significant cross-validated correlation coefficient q2 (0.51), r (0.962) for CoMSIA were obtained, indicating the statistical significance of this class of compounds. Actual urease inhibitory activities of this class, and the predicted values were in good agreement with the experimental results. This model offer insight into the structural requirements for activity of bis-coumerine analogues as urease inhibitors, since there is only speculative knowledge of their target in protein. [ABSTRACT FROM AUTHOR]

Amebiasis is a major threat to the public health that causes tens of thousands of deaths per year. In order to better rationalize the discovery of more potent anti-amebic agents, three-dimensional quantitative structure-activity relationship studies were conducted on a large number (six sets) of anti-amebic thiosemicarbazones and thiocarbamoylpyrazolines using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis and the topomer CoMFA methods, in addition to the 3D-dependent Eigen value analysis method. The generated models were subject to internal, external, and cross validation statistical tests to judge their respective qualities. Herein, the best alignment approach was described and the models' profiles were analyzed to give a structural insight of more potent antiamebics. [ABSTRACT FROM AUTHOR]

Abstract: We report a series of new glitazones incorporated with phenylalanine and tyrosine. All the compounds were tested for their in vitro glucose uptake activity using rat-hemidiaphragm, both in presence and absence of insulin. Six of the most active compounds from the in vitro screening were taken forward for their in vivo triglyceride and glucose lowering activity against dexamethazone induced hyperlipidemia and insulin resistance in Wistar rats. The liver samples of rats that received the most active compounds, 23 and 24, in the in vivo studies, were subjected to histopathological examination to assess their short term hepatotoxicity. The investigations on the in vitro glucose uptake, in vivo triglyceride and glucose lowering activity are described here along with the quantitative structure–activity relationships. [Copyright &y& Elsevier]

Phenolic acids are potent antioxidants, yet the quantitative structure-activity relationships of phenolic acids remain unclear. The purpose of this study was to establish 3D-QSAR models able to predict phenolic acids with high DPPH• scavenging activity and understand their structure-activity relationships. The model has been established by using a training set of compounds with cross-validated q2 = 0.638/0.855, non-cross-validated r2 = 0.984/0.986, standard error of estimate = 0.236/0.216, and F = 139.126/208.320 for the best CoMFA/CoMSIA models. The predictive ability of the models was validated with the correlation coefficient r2 pred = 0.971/0.996 (>0.6) for each model. Additionally, the contour map results suggested that structural characteristics of phenolics acids favorable for the high DPPH• scavenging activity might include: (1) bulky and/or electron-donating substituent groups on the phenol ring; (2) electron-donating groups at the meta-position and/or hydrophobic groups at the meta-/ortho-position; (3) hydrogen-bond donor/electron-donating groups at the ortho-position. The results have been confirmed based on structural analyses of phenolic acids and their DPPH• scavenging data from eight recent publications. The findings may provide deeper insight into the antioxidant mechanisms and provide useful information for selecting phenolic acids for free radical scavenging properties. [ABSTRACT FROM AUTHOR]

Human histamine H1 receptor (HHR1) is one of the receptors through which histamine exerts its allergic reactions, and inhibition of this receptor is an important strategy in treatment of inflammatory diseases. In this study, classical and 3D quantitative structure–activity relationship (QSAR) studies were carried out using 36 inverse agonists of which 27 diverse compounds were used in training set. The MOE® and SYSTAT® programs were used in descriptor calculation and step-wise multiple regression analysis. A predictive and statistically significant QSAR model based on four descriptors was developed and cross-validated with the leave-one-out (LOO) method. The statistical data of this model were r = 0.908, F = 25.703, s = 0.445, . Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were carried out using the same training set compounds. Pharmacophore-based molecular alignment was used to develop models using different fields. The best CoMFA model was the one developed using the CoMFA indicator fields (r 2 = 0.998, ), and the best CoMSIA model was the one with CoMSIA steric fields (r 2 = 0.862, ). As the models explain well the observed variance in HHR1 binding affinities in both the training and the test set, they can be used in designing future antihistamines. [ABSTRACT FROM AUTHOR]

Abstract: A series of 2-hydrazinyl-4-morpholinothieno[3,2-d]pyrimidine derivatives were synthesized and evaluated for their cytotoxic activities against five cancer cell lines. Most of them exhibited moderate to significant cytotoxic activities and high-selectivity against one or more cell lines, and nearly all of them had higher potency than positive controls against MDA-MB-231 cell line. The most promising compound 15f showed strong cytotoxic activities against H460, HT-29 and MDA-MB-231 cell lines, which were 1.7- to 66.5-folds more active than 2-(1H-Indazol-4-yl)-6-((4-(methylsulfonyl)-1-piperazinyl)methyl)-4-(4-morpholinyl)thieno[3,2-d]pyrimidine(GDC-0941). To investigate the SARs of thieno[3,2-d]pyrimidine derivatives in more details, CoMFA (q 2 = 0.436, r 2 = 0.937) and CoMSIA (q 2 = 0.706, r 2 = 0.947) models on H460 cell line were established. The generated 3D-QSAR models can be used for further rational design of novel thienopyrimidines as highly potent and selective cytotoxic agents. [Copyright &y& Elsevier]

B-RAF is a member of the RAF protein kinase family involved in the regulation of cell growth, differentiation, and proliferation. It forms a part of conserved apoptosis signals through the RAS-RAF-MAPK pathway. B-RAF protein has much potential for scientific research as therapeutic target due to its involvement in human melanoma cancer. In this work, a molecular modeling study was carried out for the first time with 3D-QSAR studies by following the docking protocol on three different data sets of B-RAF inhibitors. Based on the co-crystallized compound (PDB ID: 1UWJ), a receptor-guided alignment method was utilized to derive reliable CoMFA and CoMSIA models. The selected CoMFA model gives the best statistical values ( q = 0.753, r = 0.962). With the same alignment protocol, a statistically reliable CoMSIA model out of fourteen different combinations was also derived ( q = 0.807, r = 0.961). The actual predictive powers of both models were rigorously validated with an external test set, which gave satisfactory predictive r values for CoMFA and CoMSIA models, 0.89 and 0.88, respectively. In addition, y-randomization test was also performed to validate our 3D-QSAR models. Contour maps from CoMFA and CoMSIA models supported statistical results, revealed important structural features responsible for biological activity within the active site and explained the correlation between biological activity and receptor-ligand interactions. Based on the developed models few new structures were designed. The newly predicted structure ( IIIa) showed higher inhibitory potency (pIC 6.826) than that of the most active compound of the series. [ABSTRACT FROM AUTHOR]