scholarly journals QSAR Modeling and Molecular Docking Analysis of Some Active Compounds against Mycobacterium tuberculosis Receptor (Mtb CYP121)

2018 ◽  
Vol 2018 ◽  
pp. 1-24 ◽  
Author(s):  
Shola Elijah Adeniji ◽  
Sani Uba ◽  
Adamu Uzairu
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Molecular Docking ◽  
Correlation Coefficient ◽  
Density Functional ◽  
Biological Activities ◽  
External Validation ◽  
Structural Features ◽  
Qsar Modeling ◽  
Qsar Study ◽  
Docking Analysis

A quantitative structure-activity relationship (QSAR) study was performed to develop a model that relates the structures of 50 compounds to their activities against M. tuberculosis. The compounds were optimized by employing density functional theory (DFT) with B3LYP/6-31G⁎. The Genetic Function Algorithm (GFA) was used to select the descriptors and to generate the correlation model that relates the structural features of the compounds to their biological activities. The optimum model has squared correlation coefficient (R2) of 0.9202, adjusted squared correlation coefficient (Radj) of 0.91012, and leave-one-out (LOO) cross-validation coefficient (Qcv2) value of 0.8954. The external validation test used for confirming the predictive power of the built model has R2pred value of 0.8842. These parameters confirm the stability and robustness of the model. Docking analysis showed the best compound with high docking affinity of −14.6 kcal/mol which formed hydrophobic interaction and hydrogen bond with amino acid residues of M. tuberculosis cytochromes (Mtb CYP121). QSAR and molecular docking studies provide valuable approach for pharmaceutical and medicinal chemists to design and synthesize new anti-Mycobacterium tuberculosis compounds.

scholarly journals Theoretical investigation of a few selected compounds as potent anti-tubercular agents and molecular docking evaluation: A multi-linear regression approach

2020 ◽  
Vol 11 (1) ◽  
pp. 60-67
Author(s):  
Shola Elijah Adeniji ◽  
Abdulwahab Isiaka ◽  
Kalen Ephraim Audu ◽  
Olajumoke Bosede Adalumo
Keyword(s):  
Molecular Docking ◽  
Correlation Coefficient ◽  
Drug Targets ◽  
Biological Activities ◽  
External Validation ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Multi Drug Resistance ◽  
Validation Test

Emergence of multi-drug resistant strains of Mycobacterium tuberculosis to the available drugs has demanded for the development of more potent anti-tubercular agents with efficient pharmacological activities. Time consumed and expenses in discovering and synthesizing new drug targets with improved biological activity have been a major challenge toward the treatment of multi-drug resistance strain M. tuberculosis. To solve the above problem, Quantitative Structure Activity Relationship (QSAR) is a recent approach developed to discover a novel drug with a better biological against M. Tuberculosis. A validated QSAR model developed in this study to predict the biological activities of some anti-tubercular compounds and to design new hypothetical drugs is influenced with the molecular descriptors; AATS7s, VR1-Dzi, VR1-Dzs, SpMin7-Bhe and RDF110i. The internal validation test for the derived model was found to have correlation coefficient (R2) of 0.8875, adjusted correlation coefficient (R2adj) value of 0.8234 and leave one out cross validation coefficient (Qcv2) value of 0.8012 while the external validation test was found to have (R2test) of 0.7961 and Y-randomization Coefficient (cRp2) of 0.6832. Molecular docking shows that ligand 13 of 2,4-disubstituted quinoline derivatives have promising higher binding score of -18.8 kcal/mol compared to the recommended drugs; isoniazid -14.6 kcal/mol. The proposed QSAR model and molecular docking studies will provides valuable approach for the modification of the lead compound, designing and synthesis more potent anti-tubercular agents.

scholarly journals QSAR and docking studies of 3, 5-dimethylpyrazole as potent inhibitors of Phosphodiesterase-4

2021 ◽  
Vol 11 (1-s) ◽  
pp. 86-93
Author(s):  
Hiba Hashim Mahgoub Mohamed ◽  
Amna Bint Wahab Elrashid Mohammed Hussien ◽  
Ahmed Elsadig Mohammed Saeed
Keyword(s):  
Molecular Docking ◽  
Correlation Coefficient ◽  
External Validation ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Pyrazole Derivatives ◽  
Qsar Study ◽  
Furan Moiety ◽  
The Stability ◽  
Leave One Out

A quantitative structure-activity relationship (QSAR) study was performed to develop a model on a series of 3, 5-dimethylpyrazole containing furan moiety derivatives which exhibited considerable inhibitory activity against PDE4B. The obtained model has correlation coefficient (r) of 0.934, squared correlation coefficient (r2) of 0.872, and leave-one-out (LOO) cross-validation coefficient (Q2) value of 0.733. The predictive power of the developed model was confirmed by the external validation which has (r2) value of 0.812. These parameters confirm the stability and robustness of the model to predict the activity of a new designed set of 3,5-dimethyl-pyrazole derivatives (I-XV), results indicated that the compound III, V, XIII, and XV showed the strongest inhibition activity (IC50 = 0.2813, 0.5814, 0.6929, 0.6125μM, respectively) against PDE4B compared to the reference rolipram with (IC50=1.9μM). Molecular docking was performed on a new designed compound with PDE4B protein (3o0j). Docking results showed that compounds (X and IX) have high docking affinity of -36.2037 and -33.2888 kcal/mol respectively. Keywords: QSAR, molecular docking, pyrazole derivatives, PDE4 inhibitors, anti-inflammatory.

Action of Thioglycosides of 1,2,4-Triazoles and Imidazoles on the Oxidative Stress and Glycosidases in Mice with Molecular Docking

2019 ◽  
Vol 16 (6) ◽  
pp. 696-710
Author(s):  
Mahmoud Balbaa ◽  
Doaa Awad ◽  
Ahmad Abd Elaal ◽  
Shimaa Mahsoub ◽  
Mayssaa Moharram ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Molecular Docking ◽  
Active Sites ◽  
Biological Activities ◽  
Imidazole Ring ◽  
Quantitative Structure Activity Relationship ◽  
Binding Interaction ◽  
Qsar Study

Background: ,2,3-Triazoles and imidazoles are important five-membered heterocyclic scaffolds due to their extensive biological activities. These products have been an area of growing interest to many researchers around the world because of their enormous pharmaceutical scope. Methods: The in vivo and in vitro enzyme inhibition of some thioglycosides encompassing 1,2,4- triazole N1, N2, and N3 and/or imidazole moieties N4, N5, and N6. The effect on the antioxidant enzymes (superoxide dismutase, glutathione S-transferase, glutathione peroxidase and catalase) was investigated as well as their effect on α-glucosidase and β-glucuronidase. Molecular docking studies were carried out to investigate the mode of the binding interaction of the compounds with α- glucosidase and β -glucuronidase. In addition, quantitative structure-activity relationship (QSAR) investigation was applied to find out the correlation between toxicity and physicochemical properties. Results: The decrease of the antioxidant status was revealed by the in vivo effect of the tested compounds. Furthermore, the in vivo and in vitro inhibitory effects of the tested compounds were clearly pronounced on α-glucosidase, but not β-glucuronidase. The IC50 and Ki values revealed that the thioglycoside - based 1,2,4-triazole N3 possesses a high inhibitory action. In addition, the in vitro studies demonstrated that the whole tested 1,2,4-triazole are potent inhibitors with a Ki magnitude of 10-6 and exhibited a competitive type inhibition. On the other hand, the thioglycosides - based imidazole ring showed an antioxidant activity and exerted a slight in vivo stimulation of α-glucosidase and β- glucuronidase. Molecular docking proved that the compounds exhibited binding affinity with the active sites of α -glucosidase and β-glucuronidase (docking score ranged from -2.320 to -4.370 kcal/mol). Furthermore, QSAR study revealed that the HBD and RB were found to have an overall significant correlation with the toxicity. Conclusion: These data suggest that the inhibition of α-glucosidase is accompanied by an oxidative stress action.

scholarly journals Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2322 ◽  
Author(s):  
Saw Simeon ◽  
Nuttapat Anuwongcharoen ◽  
Watshara Shoombuatong ◽  
Aijaz Ahmad Malik ◽  
Virapong Prachayasittikul ◽  
...  
Keyword(s):  
Hydrogen Bonding ◽  
Molecular Docking ◽  
Binding Pocket ◽  
Binding Energies ◽  
Acetylcholinesterase Inhibition ◽  
Qsar Modeling ◽  
Qsar Study ◽  
Data Set ◽  
Ache Inhibitors ◽  
Redundant Data

Alzheimer’s disease (AD) is a chronic neurodegenerative disease which leads to the gradual loss of neuronal cells. Several hypotheses for AD exists (e.g., cholinergic, amyloid, tau hypotheses, etc.). As per the cholinergic hypothesis, the deficiency of choline is responsible for AD; therefore, the inhibition of AChE is a lucrative therapeutic strategy for the treatment of AD. Acetylcholinesterase (AChE) is an enzyme that catalyzes the breakdown of the neurotransmitter acetylcholine that is essential for cognition and memory. A large non-redundant data set of 2,570 compounds with reported IC50values against AChE was obtained from ChEMBL and employed in quantitative structure-activity relationship (QSAR) study so as to gain insights on their origin of bioactivity. AChE inhibitors were described by a set of 12 fingerprint descriptors and predictive models were constructed from 100 different data splits using random forest. Generated models affordedR2, ${Q}_{\mathrm{CV }}^{2}$ and ${Q}_{\mathrm{Ext}}^{2}$ values in ranges of 0.66–0.93, 0.55–0.79 and 0.56–0.81 for the training set, 10-fold cross-validated set and external set, respectively. The best model built using the substructure count was selected according to the OECD guidelines and it affordedR2, ${Q}_{\mathrm{CV }}^{2}$ and ${Q}_{\mathrm{Ext}}^{2}$ values of 0.92 ± 0.01, 0.78 ± 0.06 and 0.78 ± 0.05, respectively. Furthermore, Y-scrambling was applied to evaluate the possibility of chance correlation of the predictive model. Subsequently, a thorough analysis of the substructure fingerprint count was conducted to provide informative insights on the inhibitory activity of AChE inhibitors. Moreover, Kennard–Stone sampling of the actives were applied to select 30 diverse compounds for further molecular docking studies in order to gain structural insights on the origin of AChE inhibition. Site-moiety mapping of compounds from the diversity set revealed three binding anchors encompassing both hydrogen bonding and van der Waals interaction. Molecular docking revealed that compounds13,5and28exhibited the lowest binding energies of −12.2, −12.0 and −12.0 kcal/mol, respectively, against human AChE, which is modulated by hydrogen bonding,π–πstacking and hydrophobic interaction inside the binding pocket. These information may be used as guidelines for the design of novel and robust AChE inhibitors.

Vibrational spectral, density functional theory and molecular docking analysis on 4-nitrobenzohydrazide

2021 ◽  
Vol 1223 ◽  
pp. 128948
Author(s):  
H. Marshan Robert ◽  
D Usha ◽  
M. Amalanathan ◽  
R. Racil Jeya Geetha ◽  
M. Sony Michael Mary
Keyword(s):  
Density Functional Theory ◽  
Molecular Docking ◽  
Spectral Density ◽  
Density Functional ◽  
Functional Theory ◽  
Docking Analysis ◽  
Molecular Docking Analysis

scholarly journals Fragmentation Study, Dual Anti-Bactericidal and Anti-Viral Effects and Molecular Docking of Cobalt(III) Complexes

2020 ◽  
Vol 21 (21) ◽  
pp. 8355
Author(s):  
Laísa de P. Fernandes ◽  
Júlia M. B. Silva ◽  
Daniel O. S. Martins ◽  
Mariana B. Santiago ◽  
Carlos H. G. Martins ◽  
...  
Keyword(s):  
Molecular Docking ◽  
High Resolution Mass Spectrometry ◽  
Biological Activities ◽  
Therapeutic Application ◽  
Chikv Infection ◽  
Docking Analysis ◽  
Future Studies ◽  
Relative Binding ◽  
Good Potential

Considering our previous findings on the remarkable activity exhibited by cobalt(III) with 2-acetylpyridine-N(4)-R-thiosemicarbazone (Hatc-R) compounds against Mycobacterium tuberculosis, the present study aimed to explored new structure features of the complexes of the type [Co(atc--R)2]Cl, where R = methyl (Me, 1) or phenyl (Ph, 2) (13C NMR, high-resolution mass spectrometry, LC–MS/MS, fragmentation study) together with its antibacterial and antiviral biological activities. The minimal inhibitory and minimal bactericidal concentrations (MIC and MBC) were determined, as well as the antiviral potential of the complexes on chikungunya virus (CHIKV) infection in vitro and cell viability. [Co(atc-Ph)2]Cl revealed promising MIC and MBC values which ranged from 0.39 to 0.78 µg/mL in two strains tested and presented high potential against CHIKV by reducing viral replication by up to 80%. The results showed that the biological activity is strongly influenced by the peripheral substituent groups at the N(4) position of the atc-R1− ligands. In addition, molecular docking analysis was performed. The relative binding energy of the docked compound with five bacteria strains was found in the range of −3.45 and −9.55 kcal/mol. Thus, this work highlights the good potential of cobalt(III) complexes and provide support for future studies on this molecule aiming at its antibacterial and antiviral therapeutic application.

scholarly journals QSAR modeling of antibacterial activity of some benzimidazole derivatives

2011 ◽  
Vol 17 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Sanja Podunavac-Kuzmanovic ◽  
Dragoljub Cvetkovic
Keyword(s):  
Antibacterial Activity ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structural Features ◽  
Benzimidazole Derivatives ◽  
Qsar Modeling ◽  
Qsar Study ◽  
Validation Procedure ◽  
Leave One Out

A quantitative structure-activity relationship (QSAR) study has been carried out for training set of 12 benzimidazole derivatives to correlate and predict the antibacterial activity of studied compounds against Gram-negative bacteria Pseudomonas aeruginosa. Multiple linear regression was used to select the descriptors and to generate the best prediction model that relates the structural features to inhibitory activity. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based on the following descriptors: parameter of lipophilicity (logP) and hydration energy (HE). Good agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the generated QSAR model.

QSAR study of 2,4-disubstituted phenoxyacetic acid derivatives as a CRTh2 receptor antagonists

2009 ◽  
Vol 63 (4) ◽  
Author(s):  
Abhishek Jain ◽  
Veerasamy Ravichandran ◽  
Rajesh Singh ◽  
Vishnukanth Mourya ◽  
Ram Agrawal
Keyword(s):  
Receptor Antagonist ◽  
Correlation Coefficient ◽  
Statistical Significance ◽  
Linear Regression Analysis ◽  
External Validation ◽  
Qsar Model ◽  
Multiple Linear Regression Analysis ◽  
Phenoxyacetic Acid ◽  
Qsar Study ◽  
Qsar Studies

AbstractIn pursuit of better CRTh2 receptor antagonist agents, QSAR studies were performed on a series of 2,4-disubstituted phenoxyacetic acid derivatives. Stepwise multiple linear regression analysis was performed to derive QSAR models which were further evaluated for statistical significance and predictive power by internal and external validation. The best QSAR model was selected; having the correlation coefficient R = 0.904, standard error of estimation SEE = 0.456 and the cross validated squared correlation coefficient Q 2 = 0.739. Predictive ability of the selected model was also confirmed by the leave one out cross validation method and by leave 33 % out Q 2 = 0.688. The QSAR model indicates that the descriptors (logP, SI3, LM, and DVZ) play an important role in the CRTh2 receptor antagonist activities. Results of the present study may be useful in the designing of more potent 2,4-disubstituted phenoxyacetic acid derivatives as CRTh2 receptor antagonist agents.

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