HQSAR Studies Research Articles

Structural insights on 2-phenylquinazolin-4-one derivatives as tankyrase inhibitors through CoMFA, CoMSIA, topomer CoMFA and HQSAR studies

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, r2ncv value of 0.958 and r2pred value of 0.553. Optimized CoMSIA analysis (SEHD) showed q2 value of 0.580, r2ncv value of 0.953 and r2pred value of 0.723. Topomer CoMFA analysis showed q2 value of 0.684, r2 (conventional correlation coefficient) value of 0.955 and r2pred value of 0.721. HQSAR analysis showed q2, r2 and r2pred 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.

Structural exploration of arylsulfonamide-based ADAM17 inhibitors through validated comparative multi-QSAR modelling studies

Zinc-dependent ADAM17 takes part in a number of life-threatening conditions such as inflammatory diseases, cancer, Alzheimer's disease and rheumatoid arthritis. Therefore, ADAM17 may be a valuable target to design specific inhibitors for combating these diseases. In this scenario, it is a challenging task to design specific ADAM17 inhibitors as none of the earlier investigated compounds has come into the market as a potential drug candidate. Here, molecular modelling including 2D-QSAR, HQSAR, Bayesian classification, pharmacophore mapping and molecular docking studies of arylsulfonamides were performed to explore the structural and pharmacophoric requirements for exerting higher ADAM17 inhibitory activity. All these molecular modelling approaches were validated individually and these were statistically significant and reliable. The bulky steric and hydrophobic P1′ substituents at the para position of the arylsulfonamido moiety favoured ADAM17 inhibition that supported and validated by molecular docking study. These crucial observations of arylsulfonamides may be considered for designing higher effective ADAM17 inhibitors in future.

Design of novel amyloid β aggregation inhibitors using QSAR, pharmacophore modeling, molecular docking and ADME prediction.

The inhibition of abnormal amyloid β (Aβ) aggregation has been regarded as a good target to control Alzheimer's disease. The present study adopted 2D-QSAR, HQSAR and 3D QSAR (CoMFA & CoMSIA) modeling approaches to identify the structural and physicochemical requirements for the potential Aβ aggregation inhibition. A structure-based molecular docking technique is utilized to approve the features that are obtained from the ligand-based techniques on 30 curcumin derivatives. The combined outputs were then used to screen the modified 10 compounds. The 2D QSAR model on curcumin derivatives gave statistical values R2 = 0.9086 and SEE = 0.1837. The model was further confirmed by Y-randomization test and Applicability domain analysis by the standardization approach. The HQSAR study (Q2 = 0.615, Rncv 2 = 0.931, Rpred 2 = 0.956) illustrated the important molecular fingerprints for inhibition. Contour maps of 3D QSAR models, CoMFA (Q2 = 0.687, Rncv 2 = 0.787, Rpred 2 = 0.731) and CoMSIA (Q2 = 0.743, Rncv 2 = 0.972, Rpred 2 = 0.713), depict that the models are robust and provide explanation of the important features, like steric, electrostatic and hydrogen bond acceptor, which play important role for interaction with the receptor site cavity. The molecular docking study of the curcumin derivatives elucidates the important interactions between the amino acid residues at the catalytic site of the receptor and the ligands, indicating the structural requirements of the inhibitors. The ligand-receptor interactions of top hits were analyzed to explore the pharmacophore features of Aβ aggregation inhibition. The Aβ aggregation inhibitory activities of novel chemical entities were then obtained through inverse QSAR. The newly designed molecules were further screened through machine learning, prediction of toxicity and nature of metabolism to get the proposed six lead compounds.

In silico screening for identification of pyrrolidine derivatives dipeptidyl peptidase-IV inhibitors using COMFA, CoMSIA, HQSAR and docking studies

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 (q2) value of 0.727, 0.870 and 0.939 and r2 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.

Design of 2-Nitroimidazooxazine Derivatives as Deazaflavin-Dependent Nitroreductase (Ddn) Activators as Anti-Mycobacterial Agents Based on 3D QSAR, HQSAR, and Docking Study with In Silico Prediction of Activity and Toxicity.

Deazaflavin-dependent nitroreductase (Ddn) is an emerging target in the field of anti-tuberculosis agents. In the present study, 2-nitroimidazooxazine derivatives as Ddn activators were aligned for CoMFA, CoMSIA and HQSAR analysis. The best CoMFA and CoMSIA model were generated with leave-one-out correlation coefficients (q2) of 0.585 and 0.571, respectively. Both the CoMFA and CoMSIA models were also validated by a test set of 11 compounds with satisfactory [Formula: see text] value of 0.701 and 0.667, respectively. Results of 3D QSAR and HQSAR study were used for the designing of novel and potent nitroimidazooxazine derivatives as Ddn activators. 21 novel compounds were designed, and docked into the Ddn enzyme. In docking study compound ng11 showed interaction with key amino acid residues such as Tyr65 and Tyr133, and also showed better ADMET compatibility. The ADMET prediction, docking study and the predicted activity of novel designed compounds revealed that compound ng11 showed good potential as Ddn activators for the treatment of tuberculosis.

Exploring molecular structural requirement for AChE inhibition through multi-chemometric and dynamics simulation analyses

The acetylcholinesterase enzyme (AChE) plays an important role in central and peripheral nervous systems. Acetylcholine (ACh) acts through the regulation of AChE activity, which can play a key role in accelerating senile amyloid β-peptide (Aβ) plaque deposition. Therefore, inhibition of the AChE enzyme can be used as a key principle to prevent ACh depletion. The present study has been emphasized to explore both ligand- and structure-based 3D QSAR, HQSAR, pharmacophore, molecular docking and simulation studies on a set of structurally diverse inhibitors to optimize prime structural features responsible for selective binding to AChE, and vis-à-vis inhibiting enzyme activity. The pharmacophore model showed the importance of HB acceptor and donor, positive ionization and hydrophobic features of the molecule for effective binding. Structure-based docking and simulation studies adjudged the significance of features obtained from ligand-based 3D QSAR, CoMFA (Q2 = .608, = .700), CoMSIA (Q2 = .632, = .734), HQSAR (Q2 = .850, = .693) and pharmacophore (Q2 = .839, ROCscore = .769) models. The aim of the present study is to identify the essential structural and physicochemical profiles of molecules that can provide therapeutic benefits with less toxicity. Structurally diverse compounds have been used for the study, and the generated models showed the large applicability domain.

HQSAR study and molecular design of benzimidazole 5-carboxylic derivatives of hepatitis C virus NS5B polymerase

HQSAR study and molecular design of benzimidazole 5-carboxylic derivatives of hepatitis C virus NS5B polymerase

Computational strategies to explore antimalarial thiazine alkaloid lead compounds based on an Australian marine sponge Plakortis Lita

In this work, an attempt was made to propose new leads based on the natural scaffold Thiaplakortone-A active against malaria. The 2D QSAR studies suggested that three descriptors correlate with the anti-malarial activity with an R2 value of 0.814. Robustness, reliability, and predictive power of the model were tested by internal validation, external validation, Y-scrambling, and applicability domain analysis. HQSAR studies were carried out as an additional tool to find the sub-structural fingerprints. The CoMFA and CoMSIA models gave Q2 values of 0.813 and 0.647, and values of 0.994 and 0.984, respectively. Using the 2D-QSAR equation, the activity values of the seven modified compounds were calculated and it was found that three molecules showed good anti-malarial activity. Molecular docking of the 42 Thiaplakortone-A derivatives with Plasmodium falciparum calcium-dependent protein kinase 1 (PfCDPK1) was carried out to find out protein-ligand interactions. Data mining of the bioassay data-set AID: 504850 using the classifier based on Random Forest of Weka suggested that all of the eight molecules selected and three out of the seven virtual molecules were anti-malarial active. Both the virtual molecules and drug molecules were docked with CYP3A4, indicating that the virtual molecules could metabolize easily. Toxicity studies using Osiris shows that three molecules showed no toxic characters.

Exploring Structural and Physicochemical Profiles of Potential GSK-3β Inhibitors Using Structure- and Ligand-Based Modeling Studies.

Glycogen synthase kinase-3β (GSK-3β) is a promising target for therapeutic invasion of Alzheimer's disease (AD). The kinase enzyme plays major role in pathological process for the formation of β-amyloid plaques and neurofibrillary tangles in AD. In the present study, structure-based pharmacophore and ligand-based 3D QSAR, HQSAR and pharmacophore mapping studies have been emphasized to explore the possible structural requirement of this potential kinase inhibitors using a structurally diverse set of compounds. The developed models were validated with the interaction study at the catalytic cleft. The 3D QSAR studies yield robust models of CoMFA R(2) = 0.965, se = 0.212, Q(2) = 0.525, R(2)pred = 0.709, r(2)m = 0.579 and CoMSIA: R(2) = 0.935, se = 0.289, Q(2) = 0.581, R(2)pred = 0.723, r(2)m = 0.935, that explain the importance of steric, electrostatic, hydrogen bond (HB) acceptor of the molecule for inhibition of GSK-3β. The HQSAR study (R(2) = 0.871, se = 0.400, Q(2) = 0.639, R(2)pred = 0.721, r(2)m = 0.664) indicated the fragments of the molecular fingerprints that might be important for inhibition. Both structure- and ligand-based pharmacophore mapping proposed that acceptor and donor features of the molecule are essential for receptor-ligand interactions. Molecular diversity provides an opportunity on wide range of applicability for the GSK-3β inhibitors, and depicts information on the structural and properties requirement for effective binding at the active site selectivity that minimize the side effects with therapeutic benefits.

Design, synthesis and QSAR studies on a series of 2, 5-disubstituted- 1,3,4-oxadiazole derivatives of diclofenac and naproxen for analgesic and anti-inflammatory activity.

A series of twenty molecules belonging to 2,5-disubstituted-1,3,4-oxadiazole derivatives of Diclofenac and Naproxen were designed, synthesized and their structures were confirmed by spectroscopy. The target compounds were evaluated for anti-inflammatory and analgesic activity. The result indicates that the compounds 12, 4, 6, 7 and 15 were found to have good analgesic and anti-inflammatory activities, while the compounds 12 and 14 were found to have good analgesic and the compound 22 were found to have good anti-inflammatory activities. HQSAR and Topomer QSAR studies were performed to get insights in the structures contributing for biological activity. The compounds bearing mono-substitution such as Cl, OCH3 and NO2 in the phenyl ring were found to have maximum analgesic and anti-inflammatory activities.

Chemometric design to explore pharmacophore features of BACE inhibitors for controlling Alzheimer's disease.

The β-amyloid precursor protein cleavage enzyme (BACE) has been conceived to be an attractive therapeutic target to control Alzheimer's disease (AD). Validated ligand-based pharmacophore mapping was combined with 3D QSAR modeling approaches that include CoMFA, CoMSIA and HQSAR techniques to identify structural and physico-chemical requirements for a potential BACE inhibitor using a database containing 980 structurally diverse compounds, assembled from different reports. A structure-based docking technique was also used to validate the features obtained from the ligand-based models, which were further used to screen the database of compounds designed by a de novo approach. Contour maps of 3D QSAR models, CoMFA (R(2) = 0.880, se = 0.402, Q(2) = 0.596, Rpred(2) = 0.713,) and CoMSIA (R(2) = 0.903, se = 0.362, Q(2) = 0.578, Rpred(2) = 0.715), and a pharmacophore space model (R(2) = 0.833, rmsd = 1.578, Q(2) = 0.845, Rpred(2) = 0. 764) depict that the models are robust and provide an explanation of the important features such as steric, electrostatic, hydrophobic, positive ionization, hydrogen bond acceptor and donor properties, which play important roles for interaction with the receptor site cavity. The HQSAR study (R(2) = 0.823, se = 0.488, Q(2) = 0.823, Rpred(2) = 0.768) and de novo design, which generate new fragments, illustrated the important molecular fingerprints for inhibition. The docking study elucidated the important interactions between the amino acid residues (Gly11, Thr72, Asp228, Gly230, Thr231, Arg235) at the catalytic site of the receptor and the ligand, indicating the structural requirements of the inhibitors. The de novo designed molecules were further screened for ADMET properties, and ligand-receptor interactions of the top hits were analysed by molecular docking to explore pharmacophore features of BACE inhibitors.

Structural findings of quinolone carboxylic acids in cytotoxic, antiviral, and anti-HIV-1 integrase activity through validated comparative molecular modeling studies

Validated comparative 2D- and 3D-QSAR modeling and docking studies were performed for forty-five quinolone carboxylic acids having cytotoxic, antiviral, and anti-HIV-1 IN activity. Statistically significant 2D-QSAR model was developed through MLR and PLS analyses on unsplitted as well as splitted dataset and validated. The models were validated on external set compounds. Chemical potential, Mulliken charge at C8, and ETSA index at C3 are important for cytotoxicity. Global hardness, electrophilic frontier electron density at C10, ETSA index at O21, and C13 play pivotal role for antiviral activity. Mulliken charge at C5, ETSA index at C14, RTSA index at C8, and C13 and LUMO density on C7 are important for anti-HIV-1 IN activity. HQSAR study suggested that maximum contributing fragments include C2 and C14 and substitutions at C13 and C14 for anti-HIV-1 IN activity and antiviral activity, respectively. The positively contributing fragments include C8, C9, C10, C11, and C16 are beneficial for cytotoxicity. CoMFA study suggested that favorable steric region located near C14 is important for anti-HIV-1 IN activity, steric factor at C8 substitution is important for antiviral and cytotoxicity activities. CoMSIA study correlates the steric region found in CoMFA study; hydrophobic favorable regions are located around C8 and near C13. For antiviral activity, unfavorable hydrogen bond acceptor region is observed near C8 substitution, favorable hydrogen bond acceptor region is observed at N1 substitution. For cytotoxic activity, favorable electrostatic region is located around quinolone and benzene ring. Docking study suggested that Glu152, Gln148, and Asn155 residues of the HIV-1 integrase enzyme bind with the molecule.

Predictive 3D-QSAR and HQSAR model generation of isocitrate lyase (ICL) inhibitors by various alignment methods combined with docking study

Isocitrate lyase (ICL) is one of the most important targets in the treatment of Mycobacterium tuberculosis. In this study a diverse set of 2-benzanilide derivatives were aligned by two different methods for CoMFA, CoMSIA, and HQSAR analysis. The best CoMFA model was obtained with the internal validation value (q2) of 0.730 and conventional coefficient (r2) of 0.944. Various CoMSIA models were generated and cross-validated. The best cross-validation coefficient (q2) value was found to be statistically satisfactory (0.688). Both the models were validated by test set of 10 compounds with satisfactory prediction value of (r2pred) 0.725 and 0.631 for CoMFA and CoMSIA, respectively. Cross-validation coefficient value (q2) of 0.694 and r2 of 0.856 were obtained for HQSAR study. The docking study reveals that large hydrophobic pockets occupy R substitutions of these compounds. An electronically negative surface is observed near R1 substitution. The results of the 3D-QSAR analysis corroborate with the molecular docking results, and our findings will serve as a basis for further development of better allosteric inhibitors of ICL inhibitors against M. tuberculosis.

Two- and three-dimensional QSAR studies on a set of antimycobacterial pyrroles: CoMFA, Topomer CoMFA, and HQSAR

Designing compounds having good anti-tubercular activity is gaining much importance in the area of tuberculosis research due to the reemergence of antibiotic resistance strains. In this study, quantitative structure activity relationship (QSAR) of a group of 55 anti-tubercular agents with varying structures and potencies, CoMFA, Topomer CoMFA, and HQSAR studies have been performed on a series of antimycobacterial pyrroles. A training set containing 46 compounds served to establish the model and CoMFA was assessed by r 2 value of 0.852 and cross-validated the q 2 value of 0.614. In the Topomer CoMFA, r 2 was 0.805, whole cross-validated q 2 was 0.535. The predictive ability of CoMFA and Topomer CoMFA models was determined using a test set of 9 compounds, which gave the predictive correlation coefficients (r pred 2 ) of 0.623 and 0.458, respectively. HQSAR was also carried out as a complementary study, and the best HQSAR model was generated using atoms, bond, connectivity, and hydrogen atoms as fragment distinction, 7–10 as fragment size and three components showing the cross-validated q 2 value of 0.710 and conventional r 2 value of 0.795. CoMFA, Topomer CoMFA steric, electrostatic, and HQSAR atomic contribution maps were generated to analyze the structural features of the datasets on that govern their inhibitory potency. 3D and 2D-QSAR studies (CoMFA, Topomer CoMFA, HQSAR) of antimycobacterial pyrroles are described.

Exploring structural requirement and binding interactions of β-amyloid cleavage enzyme inhibitors using molecular modeling techniques

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: R2 = 0.998, se = 0.067, Q2 = 0.765, Rpred2 = 0.772, rm2 = 0.739; CoMSIA: R2 = 0.992, se = 0.125, Q2 = 0.730, Rpred2 = 0.713, rm2 = 0.687) explain the importance of steric and electrostatic, along with hydrogen-bond (HB) acceptor and donor for binding affinity to BACE. HQSAR study (R2 = 0.941, se = 0.326, Q2 = 0.792, Rpred2 = 0.713, rm2 = 0.709) indicates the important fragments of the molecular fingerprints that might be crucial for binding affinity. Pharmacophore space modeling (R2 = 0.937, rmsd = 0.937, Q2 = 0.935, Rpred2 = 0.709, rm2 = 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.

Triple-layered QSAR studies on substituted 1,2,4-trioxanes as potential antimalarial agents: superiority of the quantitative pharmacophore-based alignment over common substructure-based alignment

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 (q 2, 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.

Insights into the Structural Requirements of PKCβII Inhibitors Based on HQSAR and CoMSIA Analyses

Diabetic cardiomyopathy is a clinical condition diagnosed when ventricular dysfunction develops in patients with diabetes devoid of coronary atherosclerosis and hypertension. The selective inhibition of PKCβII represents an effective approach for treating microvascular complications. HQSAR and CoMSIA studies were performed on a data set of 43 maleimide-based molecules acting as potent inhibitors of PKCβII. HQSAR model yielded an of 0.98 and a cross-validated of 0.85, while CoMSIA modeling of these same data generated an of 0.98 and a cross-validated of 0.85. Both the models show good predictive power having for HQSAR and CoMSIA as 0.63 and 0.75, respectively, indicating the reliability of models. The analysis shows that the terminal substitution with electronegative atom at indole or azaindole ring is essential for PKCβII inhibition, while substitution of bulkier group in linker connecting two heteroaryl rings diminishes the activity. This study is presumably helpful in designing new potent molecules as PKCβII inhibitors in fighting against various diseases related to PKCβII.

2D and 3D QSAR analyses to predict favorable substitution sites in anilino-monoindolylmaleimides acting as PKCβII selective inhibitors

Diabetic cardiomyopathy (DCM) is a clinical condition, diagnosed when ventricular dysfunction develops in diabetic patients without coronary atherosclerosis and hypertension. Intensive studies on pathogenesis of DCM show PKCβII as one of the mediators, responsible for developing DCM. 2D-QSAR (HQSAR) and 3D-QSAR (CoMSIA) studies were performed on a dataset of 42 anilino-monoindolylmaleimides acting as PKCβII selective inhibitors. Among the different alignment strategies used for CoMSIA study FlexS was found to be the best alignment method. Conformational search was performed for a few molecules to obtain the best model. CoMSIA analysis gave information about sites of favorable substitutions and steered us to assume that alkyl amine substitution on the pharmacophore would be a favorable substituent for improving the biological activity. From HQSAR studies we could extrapolate the presence of tertiary acceptor group may probably be responsible for increase in the activity whereas occurrence of cyclic ring structures would lead to decrease in the activity.

3D QSAR studies of 1,3,4-benzotriazepine derivatives as CCK 2 receptor antagonists

A number of CCK 2 antagonists have been reported to play an important role in controlling gastric acid-related conditions, nervous system related disorders and certain types of cancer. To obtain the helpful information for designing potent antagonists with novel structures and to investigate the quantitative structure–activity relationship of a group of 62 different CCK 2 receptor antagonists with varying structures and potencies, CoMFA, CoMSIA, and HQSAR studies were carried out on a series of 1,3,4-benzotriazepine-based CCK 2 receptor antagonists. QSAR models were derived from a training set of 49 compounds. By applying leave-one-out (LOO) cross-validation study, cross-validated ( r cv 2 ) values of 0.673 and 0.608 and non-cross-validated ( r ncv 2 ) values of 0.966 and 0.969 were obtained for the CoMFA and CoMSIA models, respectively. The predictive ability of the CoMFA and CoMSIA models was determined using a test set of 13 compounds, which gave predictive correlation coefficients ( r pred 2 ) of 0.793 and 0.786, respectively. HQSAR was also carried out as a complementary study, and the best HQSAR model was generated using atoms, bonds, hydrogen atoms, and chirality as fragment distinction with fragment size (2–5) and six components showing r cv 2 and r ncv 2 values of 0.744 and 0.918, respectively. CoMFA steric and electrostatic, CoMSIA hydrophobic and hydrogen bond acceptor fields, and HQSAR atomic contribution maps were used to analyze the structural features of the datasets that govern their antagonistic potency.