Integrated machine learning, molecular docking and 3D-QSAR based approach for identification of potential inhibitors of trypanosomal N-myristoyltransferase

2016 ◽  
Vol 12 (12) ◽  
pp. 3711-3723 ◽  
Author(s):  
Nidhi Singh ◽  
Priyanka Shah ◽  
Hemlata Dwivedi ◽  
Shikha Mishra ◽  
Renu Tripathi ◽  
...  

Integrated in silico approaches for the identification of antitrypanosomal inhibitors.

Author(s):  
Rania Kasmi ◽  
Larbi Elmchichi ◽  
Abdellah El Aissouq ◽  
Mohammed Bouachrine ◽  
Abdelkrim Ouammou

Backgroud: Kinases are proteins that control many biological functions. They are involved in cellular regulation, and many of them are deregulated in cancer proliferation. The evidence of this deregulation in many pathologies served as the origin of kinases as a therapeutic class and constitutes the motive that leads numerous teams to search for inhibitors of these targets. Objective: Based on 3D-QSAR studies and the molecular docking approach, we have developed new potential inhibitors that could be optimized and transformed into colon cancer drugs. Objective: Based on 3D-QSAR studies and the molecular docking approach, we have developed new potential inhibitors that could be optimized and transformed into colon cancer drugs. Method: To design new bioactive molecules and study their interactions with the cyclin-depend kinase type 2 (CDK2) enzyme, we used two virtual screening methods: 3D-QSAR modeling and molecular docking on a series of 28 pyrimidine-based benzothiazole derivatives. Results: To develop models (3D QSAR) we used CoMFA and CoMSIA techniques using SYBYL-X2.0 molecular modeling software. The statistical parameters reveal that the good CoMFA model displays (Q²= 0.587; R²= 0.895) and that of CoMSIA displays (Q²= 0.552; R²= 0.768) which are considered to be very good internal prediction values, while an external validation of a test series of 5 compounds not included in the model development series gives R²test values of 0.56 for CoMFA and R²test values of 0.51 for CoMSIA. The molecular docking approach with AutoDockTools-1.5.6 is introduced in this work to enrich the interpretations extracted from the CoMFA and CoMSIA contour maps, and to provide an in silico research method for the most favorable mode of interaction of an inhibitor within its receptor (CDK2). Conclusion: We have constructed and validated a quantitative 3D model of structure-activity relation-ships of pyrimidine-based benzothiazole derivatives as CDK2 inhibitors. This model allows us to identify the nature and position of the groups that enhance the activity, giving us directions to discover new, more powerful molecules in a limited time.


Author(s):  
Milan Jovanović ◽  
Nemanja Turković ◽  
Branka Ivković ◽  
Zorica Vujić ◽  
Katarina Nikolić ◽  
...  

Heliyon ◽  
2021 ◽  
pp. e06603
Author(s):  
Ayoub Khaldan ◽  
Soukaina Bouamrane ◽  
Fatima En-Nahli ◽  
Reda El-mernissi ◽  
Khalil El khatabi ◽  
...  

Author(s):  
Suraj N. Mali ◽  
Anima Pandey

Malarial parasites have been reported for moderate-high resistance towards classical antimalarial agents and henceforth development of newer novel chemical entities targeting multiple targets rather than targeting single target will be a highly promising strategy in antimalarial drug discovery. Herein, we carried out molecular modeling studies on 2,4-disubstituted imidazopyridines as anti-hemozoin formation inhibitors by using Schrödinger’s molecular modeling package (2020_4). We have developed statistically robust atom-based 3D-QSAR model (training set, [Formula: see text]; test set, [Formula: see text]; [Formula: see text] [Formula: see text]; root-mean-square error, [Formula: see text]; standard deviation, [Formula: see text]). Our molecular docking, in-silico ADMET analysis showed that dataset molecule 37, has highly promising results. Our ligand-based virtual screening resulted in top five ZINC hits, among them ZINC73737443 hit was observed with lesser energy gap, i.e. 7.85[Formula: see text]eV, higher softness value (0.127[Formula: see text]eV), and comparatively good docking score of [Formula: see text]10.2[Formula: see text]kcal/mol. Our in-silico analysis for a proposed hit, ZINC73737443 showed that this molecule has good ADMET, in-silico nonames toxic as well as noncarcinogenic profile. We believe that further experimental as well as the in-vitro investigation will throw more lights on the identification of ZINC73737443 as a potential antimalarial agent.


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