Discovery of novel antimalarial drugs based on thiosemicarbazone derivatives: An in silico approach

2021 ◽  
Vol 16 ◽  
Author(s):  
Arjun Anant ◽  
Kamalpreet Kaur ◽  
Vivek Asati
Keyword(s):  
Amino Acids ◽  
Plasmodium Falciparum ◽  
Virtual Screening ◽  
Trichomonas Vaginalis ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Docking Studies ◽  
Qsar Study ◽  
Zinc Compounds ◽  
Qsar Analysis

Background: Thiosemicarbazones belongs to the group of semicarbazides which contains sulfur atom instead of the oxygen atom. Several studies have shown that they are effective against extracellular protozoans like Trichomonas vaginalis, Plasmodium falciparum, Trypanosoma cruzi and other parasites. Objective: The current research involves pharmacophore model design, 3-D-QSAR, virtual screening, and docking studies, all of which are evaluated using various parameters. Methods: The present study was performed by Schrodinger software. A total of 40 ligands were selected for the development of 3D QSAR models. To predict the pIC50 values in 3D-QSAR analysis, the entire dataset was divided into two sets, training and test sets, in a 7:3 ratio. The selected pharmacophore hypothesis has been selected for the virtual screening study. Results: DHHRR_1 emerged as the best pharmacophore model with a survival score of 5.80. The 3D QSAR study showed a significant model with R2 =0.91 and. Q2 = 0.73. The series top-scoring compound 7e had a docking score of -10.44 and showed interactions with the amino acids ARG-265, PHE-227, and LEU-531 required for activity. The developed pharmacophore model has been used for screening of ZINC compounds where ZINC26244107, ZINC13469100, ZINC01290725and ZINC01350173 showed thebest XP docking scores (-11.60, -11.27, -11.35, -10.52, consecutively) with binding important amino acids ARG265, HIE185 and LEU 531 against plasmodium falciparum, PDB ID: 5TBO. These results wereevaluated with thestandard antimalarial drug chloroquine. ADME analysis showed the drug-likeness properties of the compounds. Conclusion: The results of the present study may be helpful for the future development of antimalarial compounds against Plasmodium falciparum.

3D QSAR Based Virtual Screening of Pyrido[1,2-a] Benzimidazoles as Potent Antimalarial Agents

2019 ◽  
Vol 16 (3) ◽  
pp. 301-312
Author(s):  
Kalicharan Sharma ◽  
Apeksha Srivastava ◽  
Pooja Tiwari ◽  
Shweta Sharma ◽  
Mohammad Shaquiquzzaman ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Antimalarial Activity ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Activity Data ◽  
Qsar Studies ◽  
Antimalarial Agents ◽  
Fisher Ratio

Background: Development of novel antimalarial agents has been one of the sought areas in medicinal chemistry. In this study the same was done by virtual screening of in-house database on developed QSAR model. </P><P> Methods: A six point pharmacophore model was generated (AADHRR.56) from 41 compounds using PHASE module of Schrodinger software and used for pharmacophore based search. Docking studies of the obtained hits were performed using GLIDE. Most promising hit was synthesized & biologically evaluated for antimalarial activity. </P><P> Result: The best generated model was found to be statistically significant as it had a high correlation coefficient r2= 0.989 and q2 =0.76 at 3 component PLS factor. The significance of hypothesis was also confirmed by high Fisher ratio (F = 675.1) and RMSE of 0.2745. The model developed had good predicted coefficient (Pearson R = 0.8826). The virtual screening on this model resulted in six hits, which were docked against FP-2 enzyme. The synthesized compound displayed IC50 value of 0.27&#181;g/ml against CQS (3D7) and 0.57μg/ml against CQR (RKL9). </P><P> Conclusion: 3D QSAR studies reviled that hydrophobic groups are important for anti-malarial activity while H-donor is less desirable for the same. Electron withdrawing groups at R1 position favours the activity. The biological activity data of the synthesized hit proved that the pharmacophore hypothesis developed could be utilized for developing novel anti-malarial drugs.

Pharmacophore Based 3D-QSAR, Virtual Screening and Docking Studies on Novel Series of HDAC Inhibitors with Thiophen Linker as Anticancer Agents

2016 ◽  
Vol 19 (9) ◽  
pp. 735-751 ◽  
Author(s):  
Preeti Patel ◽  
Avineesh Singh ◽  
Vijay Patel ◽  
Deepak Jain ◽  
Ravichandran Veerasamy ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Anticancer Agents ◽  
Hdac Inhibitors ◽  
3D Qsar ◽  
Docking Studies

Design of Dual COX-2 and 5-LOX Inhibitors with Iron-Chelating Properties Using Structure-Based and Ligand-Based Methods

2021 ◽  
Vol 18 ◽  
Author(s):  
Jelena Bošković ◽  
Dušan Ružić ◽  
Olivera Čudina ◽  
Katarina Nikolic ◽  
Vladimir Dobričić
Keyword(s):  
Molecular Docking ◽  
External Validation ◽  
Three Dimensional ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Qsar Analysis ◽  
In Silico Admet ◽  
Cox 2 ◽  
Lox Inhibitors

Background: Inflammation is common pathogenesis of many diseases progression, such as malignancy, cardiovascular and rheumatic diseases. The inhibition of the synthesis of inflammatory mediators by modulation of cyclooxygenase (COX) and lipoxygenase (LOX) pathways provides a challenging strategy for the development of more effective drugs. Objective: The aim of this study was to design dual COX-2 and 5-LOX inhibitors with iron-chelating properties using a combination of ligand-based (three-dimensional quantitative structure-activity relationship (3D-QSAR)) and structure-based (molecular docking) methods. Methods: The 3D-QSAR analysis was applied on a literature dataset consisting of 28 dual COX-2 and 5-LOX inhibitors in Pentacle software. The quality of developed COX-2 and 5-LOX 3D-QSAR models were evaluated by internal and external validation methods. The molecular docking analysis was performed in GOLD software, while selected ADMET properties were predicted in ADMET predictor software. Results: According to the molecular docking studies, the class of sulfohydroxamic acid analogues, previously designed by 3D-QSAR, was clustered as potential dual COX-2 and 5-LOX inhibitors with iron-chelating properties. Based on the 3D-QSAR and molecular docking, 1j, 1g, and 1l were selected as the most promising dual COX-2 and 5-LOX inhibitors. According to the in silico ADMET predictions, all compounds had an ADMET_Risk score less than 7 and a CYP_Risk score lower than 2.5. Designed compounds were not estimated as hERG inhibitors, and 1j had improved intrinsic solubility (8.704) in comparison to the dataset compounds (0.411-7.946). Conclusion: By combining 3D-QSAR and molecular docking, three compounds (1j, 1g, and 1l) are selected as the most promising designed dual COX-2 and 5-LOX inhibitors, for which good activity, as well as favourable ADMET properties and toxicity, are expected.

scholarly journals COMBINATORIAL PHARMACOPHORE MODELING AND ATOM BASED 3D QSAR STUDIES OF BENZOTHIADIAZINES AS HCV-NS5B INHIBITORS

2018 ◽  
Vol 10 (3) ◽  
pp. 43
Author(s):  
Prasanthi Polamreddy ◽  
Vinita Vishwakarma ◽  
Manoj Kumar Mahto
Keyword(s):  
Virtual Screening ◽  
Correlation Coefficient ◽  
Current Model ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Qsar Model ◽  
Pharmacophore Modeling ◽  
Structural Protein ◽  
Pearson's R ◽  
Pearson’S R

Objective: The objective of the current study was to elucidate the 3D pharmacophoric features of benzothiadiazine derivatives that are crucial for inhibiting Hepatitis C virus (HCV) Non-structural protein 5B (NS5B) and quantifying the features by building an atom based 3D quantitative structure-activity relationship (3D QSAR) model.Methods: Generation of QSAR model was carried out using PHASE 3.3.Results: A five-point pharmacophore model with two hydrogen bond acceptors, one negative ionization potential and two aromatic rings (AANRR) was found to be common among a maximum number of benzothiadiazine based NS5B inhibitors. A statistically significant 3D QSAR model was obtained from AANRR.6 which had correlation-coefficient (R2) value of 0.924, cross-validated correlation-coefficient (Q2) of 0.774, high Fisher ratio of 138 and low root mean square standard error (RMSE=0.29). There is another parameter, Pearson’s R, its value emphasizes correlation between predicted and observed activities of the test set. For the current model, Pearson’s R-value is 0.90, hence underlining the good quality of the model. The present study suggests that nitrogen atom of benzothiadiazine sulfamide ring, oxyacetamide group attached to C7 carbon of benzothiadiazine and sulfonamide oxygens are crucial for NS5B inhibitory activity. Prediction of activities of hit drugs generated in earlier research suggests that Aprepitant (Phase predicted activity: 6.9) could be a potential NS5B inhibitor.Conclusion: This 3D QSAR model developed was statistically good and can be used to predict the activities of newly designed NS5B inhibitors and virtual screening as well. Predict the activities of newly designed NS5B inhibitors and virtual screening as well.

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