scholarly journals In silico studies on smoothened human receptor and its antagonists in search of anticancer effects

2020 ◽  
Vol 85 (3) ◽  
pp. 335-346
Author(s):  
Ana Borota ◽  
Sorin Avram ◽  
Ramona Curpan ◽  
Alina Bora ◽  
Daniela Varga ◽  
...  
Keyword(s):  
Acquired Resistance ◽  
Area Under The Curve ◽  
Weighted Average ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Receptor Inhibition ◽  
In Silico Studies ◽  
Qsar Models ◽  
Pharmacophore Hypothesis

Lately, the cancers related with abnormal hedgehog (Hh) signalling pathway are targeted by smoothened (SMO) receptor inhibitors that are rapidly developing. Still, the problems of known inhibitors such as severe side effects, weak potency against solid tumors or even the acquired resistance need to be overcome by developing new suitable inhibitors. To explore the structural requirements of antagonists needed for SMO receptor inhibition, pharmacophore mapping, 3D-QSAR models, database screening and docking studies were performed. The best selected pharmacophore hypothesis based on which statistically significant atom-based 3D-QSAR model was developed (R2 = = 0.856, Q2 = 0.611 and Pearson-R = 0.817), was further subjected to dataset screening in order to evaluate its ability to prioritize active compounds over decoys. The efficiency of one four-points pharmacophore hypothesis (AAHR.524) was observed based on good evaluation metrics such as the area under the curve (0.795), and weighted average precision (0.835), suggesting that the model is trustworthy in predicting novel inhibitors against SMO receptor.

scholarly journals Pharmacophore Modeling and Docking Studies on Some Nonpeptide-Based Caspase-3 Inhibitors

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Simant Sharma ◽  
Arijit Basu ◽  
R. K. Agrawal
Keyword(s):  
Neurodegenerative Disorders ◽  
Caspase 3 ◽  
3D Qsar ◽  
Qsar Model ◽  
Pharmacophore Modeling ◽  
Docking Studies ◽  
Aromatic Rings ◽  
Query Tool ◽  
Pharmacophore Hypothesis ◽  
Synthetic Derivatives

Neurodegenerative disorders are major consequences of excessive apoptosis caused by a proteolytic enzyme known as caspase-3. Therefore, caspase-3 inhibition has become a validated therapeutic approach for neurodegenerative disorders. We performed pharmacophore modeling on some synthetic derivatives of caspase-3 inhibitors (pyrrolo[3,4-c]quinoline-1,3-diones) using PHASE 3.0. This resulted in the common pharmacophore hypothesis AAHRR.6 which might be responsible for the biological activity: two aromatic rings (R) mainly in the quinoline nucleus, one hydrophobic (H) group (CH3), and two acceptor (A) groups (–C=O). After identifying a valid hypothesis, we also developed an atom-based 3D-QSAR model applying the PLS algorithm. The developed model was statistically robust (q2=0.53; pred_r2=0.80). Additionally, we have performed molecular docking studies, cross-validated our results, and gained a deeper insight into its molecular recognition process. Our developed model may serve as a query tool for future virtual screening and drug designing for this particular target.

QSAR and Docking Studies on Piperidyl-cyclohexylurea Derivatives for Prediction of Selective and Potent Inhibitor of Matriptase

2019 ◽  
Vol 15 (2) ◽  
pp. 167-181 ◽  
Author(s):  
Agha Zeeshan Mirza ◽  
Hina Shamshad
Keyword(s):  
Active Compound ◽  
Potent Inhibitor ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Lack Of Fit ◽  
Hydrogen Donors ◽  
Qsar Models ◽  
Test Sets ◽  
New Compounds

Background: QSAR models as PLS, GFA, and 3D were developed for a series of matriptase inhibitors using 35 piperidyl-cyclohexylurea compounds. The training and test sets were divided into a set of 28 and 8 compounds, respectively and the pki values of each compound were used in the analysis. Methods: Docking and alignment methodologies were used to develop models in 3D QSAR. The best models among all were selected on the basis of regression statistics as r2, predictive r2 and Friedman Lack of fit measure. Hydrogen donors and rotatable bonds were found to be positively correlated properties for this target. The models were validated and used for the prediction of new compounds. Based on the predictions of 3D-QSAR model, 17 new compounds were prepared and their activities were predicted and compared with the active compound. Prediction of activities was performed for these 18 compounds using consensus results of all models. ADMET was also performed for the best-chosen compound and compared with the known active. Results and Conclusion: The developed model was able to validate the obtained results and can be successfully used to predict new potential and active compounds.

IN-SILICO STUDIES OF ANTI-PROLIFERATIVE CURCUMIN ANALOGS

2021 ◽  
pp. 24-26
Author(s):  
Monu Kumar Shukla
Keyword(s):  
In Silico ◽  
3D Qsar ◽  
Qsar Model ◽  
Physicochemical Characteristics ◽  
Docking Studies ◽  
Biological Evaluation ◽  
Qsar Studies ◽  
Anticancer Properties ◽  
Curcumin Analogues ◽  
In Silico Studies

Prostate cancer affects males more than women. Curcumin, a bioactive component of turmeric, reported to have anticancer properties on several cancer cell lines. Researchers utilised molecular docking to generate new curcumin analogues, quantify their characteristics, and anticipate its mode of action. In this research article QSAR studies were performed on 40 curcumin analogues using V-life MDS 3.5 software. The physicochemical characteristics were computed using Molinspiration Cheminformatics software. The best QSAR model for 2D and 3D QSAR was selected. Then ten compounds were designed and improved based on model results directly linked to activity. The in-silico approach predicted the good biological activity of compounds. Docking studies were performed using Akt1 as a probable target. Among the developed compounds, MKS50 has the best docking score (-7.175 kcal/mol). This study will provide a new path for the design, synthesis, and biological evaluation of novel curcumin analogues.

Insilico studies, synthesis and antitubercular activity of some novel quinoline – azitidinone derivatives

2020 ◽  
Vol 16 ◽  
Author(s):  
Trupti. S. Chitre ◽  
Kalyani. D. Asgaonkar ◽  
Amrut B. Vikhe ◽  
Shital M Patil ◽  
Dinesh. R. Garud ◽  
...  
Keyword(s):  
Combinatorial Library ◽  
3D Qsar ◽  
Antitubercular Activity ◽  
Structural Features ◽  
Docking Studies ◽  
Quinoline Derivatives ◽  
Qsar Models ◽  
Molecular Modeling Studies ◽  
Lead Generation ◽  
Mcf 7

Background: Diarylquinolines like Bedaquiline have shown promising antitubercular activity by their action of Mycobacterial ATPase. Objective: The structural features necessary for good antitubercular activity for a series of quinoline derivatives were explored through computational chemistry tools like QSAR and combinatorial library generation. In the current study, 3-Chloro-4-(2-mercaptoquinoline-3-yl)-1-substitutedphenylazitidin-2-one derivatives have been designed and synthesized based on molecular modeling studies as anti-tubercular agents. Method: 2D and 3DQSAR analysis was used to designed compounds having quinoline scaffold. The synthesized compounds were evaluated against active and dormant strains of Mycobacterium tuberculosis (MTB) H37 Ra and Mycobacterium bovis BCG. The compounds were also tested for cytotoxicity against MCF-7, A549 and Panc-1 cell lines using MTT assay. Binding affinity of designed compounds was gauged by molecular docking studies. Results: Statistically significant QSAR models generated by SA-MLR method for 2D QSAR exhibited r2 = 0.852, q2 = 0.811and whereas 3D QSAR with SA-kNN showed q2 = 0.77. The synthesized compounds exhibited MIC in the range of 1.38-14.59(µg/ml) .These compounds showed some crucial interaction with MTB Atpase. Conclusion: The present study has shown some promising results which can be further explored for lead generation.

scholarly journals STRUCTURAL EXPLORATION AND PHARMACOPHORIC INVESTIGATION OF PYRAZOLE BASED ANALOGS AS NOVEL HISTONE DEACETYLASE 1 INHIBITOR USING COMBINATORIAL STUDIES

2018 ◽  
Vol 10 (3) ◽  
pp. 90
Author(s):  
Avineesh Singh ◽  
Harish Rajak
Keyword(s):  
Molecular Docking ◽  
Histone Deacetylase ◽  
Histone Deacetylase Inhibitors ◽  
Research Work ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Inhibition Activity ◽  
Design Strategies ◽  
Histone Deacetylase 1

Objective: Histone deacetylase inhibitors (HDACi) have four essential pharmacophores as cap group, connecting unit, a linker moiety and zinc binding group for their anticancer and histone deacetylase (HDAC) inhibition activity. On the basis of this fact, the objective of this research was to evaluate the exact role of pyrazole nucleus as connecting unit and its role in the development of newer HDACi.Methods: Ligand and structure-based computer-aided drug design strategies such as pharmacophore and atom based 3D QSAR modelling, molecular docking and energetic based pharmacophore mapping have been frequently applied to design newer analogs in a precise manner. Herein, we have applied these combinatorial approaches to develop the structure-activity correlation among novel pyrazole-based derivatives.Results: the Pharmacophore-based 3D-QSAR model was developed employing Phase module and e-pharmacophore on compound 1. This 3D-QSAR model provides fruitful information regarding favourable and unfavourable substitution on pyrazole-based analogs for HDAC1 inhibition activity. Molecular docking studies indicated that all the pyrazole derivatives bind with HDAC1 proteins and showed critical hydrophobic interaction with 5ICN and 4BKX HDAC1 proteins.Conclusion: The outcome of the present research work clearly indicated that pyrazole nucleus added an essential hydrophobic feature in cap group and could be employed to design the ligand molecules more accurately.

scholarly journals 2D AND 3D-QSAR ANALYSIS OF AMINO (3-((3, 5-DIFLUORO-4-METHYL-6-PHENOXYPYRIDINE-2-YL) OXY) PHENYL) METHANIMINIUM DERIVATIVES AS FACTOR XA INHIBITOR

2019 ◽  
pp. 104-114
Author(s):  
Smita Suhane ◽  
A. G. Nerkar ◽  
Kumud Modi ◽  
Sanjay D. Sawant
Keyword(s):  
Factor Xa ◽  
3D Qsar ◽  
Qsar Model ◽  
Regression Method ◽  
Field Analysis ◽  
Factor Xa Inhibitors ◽  
Nearest Neighbour ◽  
Qsar Analysis ◽  
Qsar Models ◽  
2D And 3D

Objective: The main objective of the present study was to evolve a novel pharmacophore of methaniminium derivatives as factor Xa inhibitors by developing best 2D and 3D QSAR models. The models were developed for amino (3-((3, 5-difluoro-4-methyl-6-phenoxypyridine-2-yl) oxy) phenyl) methaniminium derivatives as factor Xa inhibitors. Methods: With the help of Marvin application, 2D structures of thirty compounds of methaniminium derivatives were drawn and consequently converted to 3D structures. 2D QSAR using multiple linear regression (MLR) analysis and PLS regression method was performed with the help of molecular design suite VLife MDS 4.3.3. 3D QSAR analysis was carried out using k-Nearest Neighbour Molecular Field Analysis (k-NN-MFA). Results: The most significant 2D models of methaniminium derivatives calculated squared correlation coefficient value 0.8002 using multiple linear regression (MLR) analysis. Partial Least Square (PLS) regression method was also employed. The results of both the methods were compared. In 2D QSAR model, T_C_O_5, T_2_O_2, s log p, T_2_O_1 and T_2_O_6 descriptors were found significant. The best 3D QSAR model with k-Nearest Neighbour Molecular Field Analysis have predicted q2 value 0.8790, q2_se value 0.0794, pred r2 value 0.9340 and pred_r2 se value 0.0540. The stepwise regression method was employed for anticipating the inhibitory activity of this class of compound. The 3D model demonstrated that hydrophobic, electrostatic and steric descriptors exhibit a crucial role in determining the inhibitory activity of this class of compounds. Conclusion: The developed 2D and 3D QSAR models have shown good r2 and q2 values of 0.8002 and 0.8790 respectively. There is high agreement in inhibitory properties of experimental and predicted values, which suggests that derived QSAR models have good predicting properties. The contour plots of 3D QSAR (k-NN-MFA) method furnish additional information on the relationship between the structure of the compound and their inhibitory activities which can be employed to construct newer potent factor Xa inhibitors.

Identification of new checkpoint kinase-1 (Chk1) inhibitors by docking, 3D-QSAR, and pharmacophore-modeling methods

2012 ◽  
Vol 90 (8) ◽  
pp. 675-692 ◽  
Author(s):  
Premlata K. Ambre ◽  
Raghuvir R. S. Pissurlenkar ◽  
Evans C. Coutinho ◽  
Radhakrishnan P. Iyer
Keyword(s):  
Hydrogen Bond ◽  
3D Qsar ◽  
Pharmacophore Modeling ◽  
Docking Studies ◽  
Hydrogen Bond Donor ◽  
Hydrogen Bond Acceptor ◽  
Checkpoint Kinase ◽  
Checkpoint Kinase 1 ◽  
Qsar Models ◽  
Potential Inhibitors

Inhibition of checkpoint kinase-1 (Chk1) by small molecules is of great therapeutic interest in the field of oncology and for understanding cell-cycle regulations. This paper presents a model with elements from docking, pharmacophore mapping, the 3D-QSAR approaches CoMFA, CoMSIA and CoRIA, and virtual screening to identify novel hits against Chk1. Docking, 3D-QSAR (CoRIA, CoMFA and CoMSIA), and pharmacophore studies delineate crucial site points on the Chk1 inhibitors, which can be modified to improve activity. The docking analysis showed residues in the proximity of the ligands that are involved in ligand–receptor interactions, whereas CoRIA models were able to derive the magnitude of these interactions that impact the activity. The ligand-based 3D-QSAR methods (CoMFA and CoMSIA) highlight key areas on the molecules that are beneficial and (or) detrimental for activity. The docking studies and 3D-QSAR models are in excellent agreement in terms of binding-site interactions. The pharmacophore hypotheses validated using sensitivity, selectivity, and specificity parameters is a four-point model, characterized by a hydrogen-bond acceptor (A), hydrogen-bond donor (D), and two hydrophobes (H). This map was used to screen a database of 2.7 million druglike compounds, which were pruned to a small set of potential inhibitors by CoRIA, CoMFA, and CoMSIA models with predicted activity in the range of 8.5–10.5 log units.

scholarly journals Integrated Ligand and Structure-Based Investigation of Structural Requirements for Silent Information Regulator 1 (SIRT1) Activation

2019 ◽  
Vol 18 (27) ◽  
pp. 2313-2324
Author(s):  
Amit K. Gupta ◽  
Sun Choi
Keyword(s):  
3D Model ◽  
Therapeutic Agent ◽  
Statistical Significance ◽  
3D Qsar ◽  
Qsar Model ◽  
Hydrogen Bond Acceptor ◽  
High Statistical Significance ◽  
Qsar Models ◽  
Silent Information Regulator 1 ◽  
2D And 3D

A series of imidazothiazole and oxazolopyridine derivatives as human Silent Information Regulator 1 (SIRT1) activators were subjected to the integrated 2D and 3D QSAR approaches. The derived 3D QSAR models yielded high cross-validated q2 values of 0.682 and 0.628 for CoMFA and CoMSIA, respectively. The non-cross validated values of r2 training = 0.89; predictive r2 test = 0.69 for CoMFA and r2=0.87; predictive r2 test =0.67 for CoMSIA reflected the statistical significance of the developed model. The steric, electrostatic, hydrophobic and hydrogen bond acceptor interactions have been found important in describing the variation in human SIRT1 activation. Further, 2D QSAR model for the same dataset yielded high statistical significance and derived 2D model’s parameters corroborated with the 3D model in terms of features. Derived model was also validated by the crystal structure of active conformation of SIRT1. Developed models may be useful for the identification of potential novel human SIRT1 activators as a therapeutic agent.

scholarly journals The Integration of Pharmacophore-Based 3D QSAR Modeling and Virtual Screening in Identification of Natural Product Inhibitors against SARS-CoV-2

2020 ◽  
Author(s):  
Samira Norouzi ◽  
Maryam Farahani ◽  
Samad Nejad Ebrahimi
Keyword(s):  
Virtual Screening ◽  
3D Structure ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Molecular Characteristics ◽  
Qsar Modeling ◽  
Data Set ◽  
Public Health Emergencies ◽  
Current Outbreak

Background: The current outbreak of Coronavirus Disease 2019 (SARS-CoV-2) led to public health emergencies all over the world and made it a global concern. Also, the lack of an effective treatment to combat this virus is another concern that has appeared. Today, increasing knowledge of biological structures like increasing computer power brings about a chance to use computational methods efficiently in different phases of the drug discovery and development for helping solve this new global problem. Methods: In this study, 3D pharmacophores were generated based on thirty-one structures with functional affinity inhibition (antiviral drugs used for SARS and MERS) with IC50<250 µM from the literature data. A 3D-QSAR model has been developed and validated to be utilized in virtual screening. Results: The best pharmacophore models have been utilized as 3D queries for virtual screening to gain promising inhibitors from a data set of thousands of natural compounds retrieved from PubChem. The hit compounds were subsequently used for molecular docking studies to investigate their affinity to the 3D structure of the SARS-CoV-2 receptors. The ADMET properties calculate for the hits with high binding affinity. Conclusion: The study outcomes can help understand the molecular characteristics and mechanisms of the binding of hit compounds to SARS-CoV-2 receptors and promising identification inhibitors that are likely to be evolved into drugs.

In Vitro and In Silico Studies of Glycyrrhetinic Acid Derivatives as Anti- Filarial Agents

2019 ◽  
Vol 19 (14) ◽  
pp. 1191-1200 ◽  
Author(s):  
Rekha Tyagi ◽  
Surjeet Verma ◽  
Shikha Mishra ◽  
Mrigank Srivastava ◽  
Sarfaraz Alam ◽  
...  
Keyword(s):  
Linear Chain ◽  
Qsar Model ◽  
Docking Studies ◽  
Glycyrrhetinic Acid ◽  
Standard Drug ◽  
Amide Derivatives ◽  
In Silico Studies ◽  
Parasite Motility ◽  
The Tropics

Background: Lymphatic filariasis is one of the chronic diseases in many parts of the tropics and sub-tropics of the world despite the use of standard drugs diethylcarbamazine and ivermectin because they kill microfilaries and not the adult parasites. Therefore, new leads with activity on adult parasites are highly desirable. Objective: Anti-filarial lead optimization by semi-synthetic modification of glycyrrhetinic acid (GA). Methods: The GA was first converted into 3-O-acyl derivative, which was further converted into 12 amide derivatives. All these derivatives were assessed for their antifilarial potential by parasite motility assay. The binding affinity of active GA derivatives on trehalose-6-phosphate phosphatase (Bm-TPP) was assessed by molecular docking studies. Results: Among 15 GA derivatives, GAD-2, GAD-3, and GAD-4 were found more potent than the GA and standard drug DEC. These derivatives reduced the motility of Brugia malayi adult worms by up to 74% while the GA and DEC reduced only up to 49%. Further, GA and most of its derivatives exhibited two times more reduction in MTT assay when compared to the standard drug DEC. These derivatives also showed 100% reduction of microfilariae and good interactions with Bm-TPP protein. Conclusion: The present study suggests that 3-O-acyl and linear chain amide derivatives of glycyrrhetinic acid may be potent leads against B. malayi microfilariae and adult worms. These results might be helpful in developing QSAR model for optimizing a new class of antifilarial lead from a very common, inexpensive, and non toxic natural product.

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