Design of novel quinazolinone derivatives as inhibitors for 5HT7 receptor

To study the pharmacophore properties of quinazolinone derivatives as 5HT₇ inhibitors, 3D QSAR methodologies, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied, partial least square (PLS) analysis was performed and QSAR models were generated. The derived model showed good statistical reliability in terms of predicting the 5HT₇ inhibitory activity of the quinazolione derivative, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like q² (cross validated correlation coefficient) of 0.642, 0.602 and r² (conventional correlation coefficient) of 0.937, 0.908 for CoMFA and CoMSIA respectively. The predictive ability of the models to determine 5HT₇ antagonistic activity is validated using a test set of 26 molecules that were not included in the training set and the predictive r² obtained for the test set was 0.512 & 0.541. Further, the results of the derived model are illustrated by means of contour maps, which give an insight into the interaction of the drug with the receptor. The molecular fields so obtained served as the basis for the design of twenty new ligands. In addition, ADME (Adsorption, Distribution, Metabolism and Elimination) have been calculated in order to predict the relevant pharmaceutical properties, and the results are in conformity with required drug like properties.     

3D-QSAR and molecular docking studies of 2-pyrimidinecarbonitrile derivatives as inhibitors against falcipain-3

The three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of falcipain-3 inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. A training set containing 42 molecules served to establish the QSAR models. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients r(cv)(2) (q(2)) of 0.549 and 0.608, and conventional correlation coefficients (r(2)) of 0.976 and 0.932, respectively. An independent test set of 12 molecules validated the external predictive power of both models with predicted correlation coefficients (r(pred)(2)) for CoMFA and CoMSIA as 0.697 and 0.509, respectively. The docking of inhibitors into falcipain-3 active site using GOLD software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of falcipain-3 active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved falcipain-3 inhibitors.     

Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis – a case study on HIV-1 protease inhibitors

Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r_loo² values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r² values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r_pred²) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r_pred² of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.     

Binding conformations and QSAR of CA-4 analogs as tubulin inhibitors

A theoretical study on the binding conformations and the quantitative structure–activity relationship (QSAR) of combretastatin A4 (CA-4) analogs as inhibitors toward tubulin has been carried out using docking analysis and comparative molecular field analysis (CoMFA). The appropriate binding orientations and conformations of these compounds interacting with tubulin were revealed by the docking study; and a 3D-QSAR model showing significant statistical quality and satisfactory predictive ability was established, in which the correlation coefficient (R²) and cross-validation coefficient (q²) were 0.955 and 0.66, respectively. The same model was further applied to predict the pIC₅₀ values for 16 congeneric compounds as external test set, and the predictive correlation coefficient R²_pred reached 0.883. Other tests on additional validations further confirmed the satisfactory predictive power of the model. In this work, it was very interesting to find that the 3D topology structure of the active site of tubulin from the docking analysis was in good agreement with the 3D-QSAR model from CoMFA for this series of compounds. Some key structural factors of the compounds responsible for cytotoxicity were reasonably presented. These theoretical results can offer useful references for understanding the action mechanism and directing the molecular design of this kind of inhibitor with improved activity.     

Comparative molecular field analysis (CoMFA) of phthalazine derivatives as phosphodiesterase IV inhibitors

A comparative molecular field analysis (CoMFA) of phthalazine class of phosphodiesterase IV (PDE IV) inhibitors has been performed to correlate their chemical structures with their observed biological activity. A statistically valid model with good correlative and predictive power is reported. The leave one out cross-validation study gave cross-validation r(2)(cv) of value 0.507 at six optimum components and conventional r(2) of value 0.98. The predictive ability of the model was tested by predicting the seven molecules belonging to the test set giving predictive correlation coefficient of 0.59. This model is potentially helpful in the design of novel and more potent PDE IV inhibitors.     

Insights on inhibition of Plasmodium falciparum plasmepsin I by novel epoxyazadiradione derivatives – molecular docking and comparative molecular field analysis

In the present study, we have explored the anti-malarial potential of epoxyazadiradione, the natural entity extracted from the neem seed oil and its chemical derivatives, against Plasmodium falciparum. The Surflex dock analysis of 41 compounds against an indispensable target, plasmepsin I (PM-I) revealed that around 70% of the compounds are found to have good binding capacity with the consensus score (C-score) of 5 to 4 with few hydrogen bonds. To elucidate the major structural requirements, vital for binding with the plasmepsin enzyme and to develop the predictive models, three-dimentional quantitative structural activity relationship (3D-QSAR) – comparative molecular field analysis (CoMFA) was carried out using Sybyl X.0. Robust and predictive models were obtained with cross-validated correlation coefficient (q²) value of 0.967 and the non-cross-validated correlation coefficient (r²) value of 0.825, which were validated by an external test set with the predictive correlation coefficient r²_(pred) values of 0.773. Three zones were identified for substitution with bulky groups and one zone for substitution with non-bulky groups. Three positions favouring the electronegative group substitution and one for the electropositive group substitution were identified. The physicochemical properties of ligands with the highest C-score were studied.

Communicated by Ramaswamy H. Sarma     

3D QSAR studies on T-type calcium channel blockers using CoMFA and CoMSIA

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of isoxazolyl compounds as a potent T-type calcium channel blockers. A set of 24 structurally similar compounds served to establish the model. Four different conformations of the most active compound were used as template structures for the alignment, three of which were obtained from Catalyst pharmacophore modeling and one by using SYBYL random search option. All CoMFA and CoMSIA models gave cross-validated r(2) (q(2)) value of more than 0.5 and conventional r(2) value of more than 0.85. The predictive ability of the models was validated by an external test set of 10 compounds, which gave satisfactory pred r(2) values ranging from 0.577 to 0.866 for all models. Best predictions were obtained with CoMFA std model of Conformer no: 3 alignment (q(2)=0.756, r(2)=0.963), giving predictive r(2) value of 0.866 for the test set. CoMFA and CoMSIA contour maps were used to analyze the structural features of the ligands accounting for the activity in terms of positively contributing physicochemical properties: steric, electrostatic, hydrophobic and hydrogen bonding fields.     

A novel seven-lncRNA signature for prognosis prediction in hepatocellular carcinoma

Liver cancer is still one of the leading causes of cancer-related death worldwide. This study is dedicated to developing a multi–long noncoding RNA (lncRNA) model for risk stratification and prognosis prediction on patients with hepatocellular carcinoma (HCC). We first downloaded lncRNA expression profiles and corresponding clinical information of patients with liver cancer from The Cancer Genome Atlas database. Differentially expressed (DE) lncRNAs between HCC samples and normal samples were identified. In total, 308 patients with HCC were randomly divided into a training group (n = 154) and a testing group (n = 154). Univariate Cox regression and least absolute shrinkage and selection operator Cox regression analyses were performed to select the best survival-related candidates from these DE lncRNAs in the training set. Seven lncRNAs (AC009005.2, RP11-363N22.3, RP11-932O9.10, RP11-572O6.1, RP11-190C22.8, RP11-388C12.8, and ZFPM2-AS1) were finally identified and used to construct a seven-lncRNA signature. The signature could classify patients into high-risk and low-risk groups with significantly different overall survival. The area under the curve of receiver operating characteristic curve for the signature to predict 5-year survival reached more than 0.75. Besides, the prognostic value of the seven-lncRNA signature was independent of conventional clinical factors. The predictive performance of the signature was further validated in the testing set and the whole set. Functional enrichment analysis indicated that the seven prognostic lncRNAs may be involved in several essential biological processes and pathways. The current study demonstrated the potential clinical implications of the seven-lncRNA signature for survival prediction of patients with HCC.     

Sperm survival and heterogeneity are correlated with fertility after intrauterine insemination in superovulated ewes

Efficient animal production involves accurate estimations of fertilizing ability. One key factor is the plasma membrane of the sperm cell, which is actively involved in the cascade of events before oocyte fusion. Many methods are used to analyze the characteristics of this membrane, including partition in aqueous two-phase systems which is an efficient method to analyze sperm surface changes accounting for loss of viability and different functional states. Centrifugal countercurrent distribution (CCCD) analysis can also be used in an aqueous two-phase system to determine the relationship between sperm parameters and in vivo fertility in ewes. In a previous work, we found a significant correlation between two post-CCCD parameters (heterogeneity and recovered viability) and field fertility when the same sample was used after cervical AI. The present study was intended to find out whether the control of several external factors that affect reproductive efficiency is able to increase the correlation coefficient between post-CCCD parameters and fertility. Thus, 90 Rasa aragonesa ewes were controlled on the same farm and received intrauterine inseminations using the same technical equipment. The fertilizing ability of the raw semen and sperm samples selected by a dextran/swim-up process was compared using a low number of spermatozoa per insemination (7 x 10(7)) to enhance possible fertility differences. A new post-CCCD parameter was considered; the loss of viability (LV) occurred during the CCCD process. This variable denotes the sperm surviving ability and corresponds to the difference between the total number of viable cells loaded and recovered after the CCCD run. The mean fertility of eight sperm control samples was 60% (range: 25-76%), and there was no significant correlation between standard parameters and in vivo fertility. LV ranged from 2 to 69% (average 27%) and was negatively correlated with fertility (r = -0.914, P < 0.01). Ejaculate heterogeneity (H) ranged from 20 to 47% and was positively, but not significantly, correlated with fertility (r = 0.391). A predictive equation for fertility was deduced by multiple analysis with a very high correlation coefficient (r = 0.967), and level of significance (P < 0.005): predictive fertility PF = 52.546 - 0.594 LV + 0.665 H. The mean fertility of 13 swim-up selected samples was 63% (range: 25-86%). Again, only parameters derived from the CCCD analysis were highly correlated with fertility, especially LV and H (P < 0.05).     

3D-QSAR analysis of sialyltransferase inhibitors

A predictive 3D-QSAR model that correlates the biological activities with the chemical structures of a series of sialyltransferase inhibitors, exemplified by the sugar:nucleotide derivatives, was developed by means of comparative molecular field analysis (CoMFA). The resulting cross-validated value (q(2)=0.629), non-cross-validated value (r(2)=0.965) and standard error of estimate (SEE=0.288) indicate that the obtained pharmacophore model indeed mimics the steric and electrostatic environment where inhibitors bind to the enzyme. The developed model also possesses promising predictive ability as discerned by the testing on the external test set, and should be useful to further understand the molecular nature of inhibitor-enzyme interactions and to aid in the design of more potent sialyltransferase inhibitors.     

Distinct second extracellular loop structures of the brain cannabinoid CB(1) receptor: implication in ligand binding and receptor function

The G-protein-coupled receptor (GPCR) second extracellular loop (E2) is known to play an important role in receptor structure and function. The brain cannabinoid (CB(1)) receptor is unique in that it lacks the interloop E2 disulfide linkage to the transmembrane (TM) helical bundle, a characteristic of many GPCRs. Recent mutation studies of the CB(1) receptor, however, suggest the presence of an alternative intraloop disulfide bond between two E2 Cys residues. Considering the oxidation state of these Cys residues, we determine the molecular structures of the 17-residue E2 in the dithiol form (E2(dithiol)) and in the disulfide form (E2(disulfide)) of the CB(1) receptor in a fully hydrated 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine bilayer, using a combination of simulated annealing and molecular dynamics simulation approaches. We characterize the CB(1) receptor models with these two E2 forms, CB(1)(E2(dithiol)) and CB(1)(E2(disulfide)), by analyzing interaction energy, contact number, core crevice, and cross correlation. The results show that the distinct E2 structures interact differently with the TM helical bundle and uniquely modify the TM helical topology, suggesting that E2 of the CB(1) receptor plays a critical role in stabilizing receptor structure, regulating ligand binding, and ultimately modulating receptor activation. Further studies on the role of E2 of the CB(1) receptor are warranted, particularly comparisons of the ligand-bound form with the present ligand-free form.     

Molecular simulation of a series of benzothiazole PI3Kα inhibitors: probing the relationship between structural features, anti-tumor potency and selectivity

The phosphatidylinositol 3-kinase α (PI3Kα) was genetically validated as a promising therapeutic target for developing novel anticancer drugs. In order to explore the structure-activity correlation of benzothiazole series as inhibitors of PI3Kα, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) were performed on 61 promising molecules to build 3D-QSAR models based on both the ligand- and receptor-based methods. The best CoMFA and CoMSIA models had a cross-validated coefficient r(cv)(2) of 0.618 and 0.621, predicted correlation coefficient r(pred) (2) of 0.812 and 0.83, respectively, proving their high correlative and predictive abilities on both the training and test sets. In addition, docking analysis and molecular dynamics simulation (MD) were also applied to elucidate the probable binding modes of these inhibitors at the ATP binding pocket. Based on the contour maps and MD results, some key structural factors responsible for the activity of this series of compounds were revealed as follows: (1) Ring-A has a strong preference for bulky hydrophobic or aromatic groups; (2) Electron-withdrawing groups at the para position of ring-B and hydrophilic substituents in ring-B region may benefit the potency; (3) A polar substituent like -NHSO(2)- between ring-A and ring-B can enhance the activity of the drug by providing hydrogen bonding interaction with the protein target. The satisfactory results obtained from this work strongly suggest that the developed 3D-QSAR models and the obtained PI3Kα inhibitor binding structures are reasonable for the prediction of the activity of new inhibitors and be helpful in future PI3Kα inhibitor design.     

Design of novel quinazolinone derivatives as inhibitors for 5HT7 receptor

To study the pharmacophore properties of quinazolinone derivatives as 5HT(7) inhibitors, 3D QSAR methodologies, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied, partial least square (PLS) analysis was performed and QSAR models were generated. The derived model showed good statistical reliability in terms of predicting the 5HT(7) inhibitory activity of the quinazolione derivative, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like q(2) (cross validated correlation coefficient) of 0.642, 0.602 and r(2) (conventional correlation coefficient) of 0.937, 0.908 for CoMFA and CoMSIA respectively. The predictive ability of the models to determine 5HT(7) antagonistic activity is validated using a test set of 26 molecules that were not included in the training set and the predictive r(2) obtained for the test set was 0.512 & 0.541. Further, the results of the derived model are illustrated by means of contour maps, which give an insight into the interaction of the drug with the receptor. The molecular fields so obtained served as the basis for the design of twenty new ligands. In addition, ADME (Adsorption, Distribution, Metabolism and Elimination) have been calculated in order to predict the relevant pharmaceutical properties, and the results are in conformity with required drug like properties.