Literature DB >> 30607318

Computer aided drug design based on 3D-QSAR and molecular docking studies of 5-(1H-indol-5-yl)-1,3,4-thiadiazol-2-amine derivatives as PIM2 inhibitors: a proposal to chemists.

Adnane Aouidate1, Adib Ghaleb1, Mounir Ghamali1, Samir Chtita1, Abdellah Ousaa1, M'barek Choukrad1, Abdelouahid Sbai1, Mohammed Bouachrine2, Tahar Lakhlifi1.   

Abstract

PIM2 kinase plays a crucial role in the cell cycle events including survival, proliferation, and differentiation in normal and neoplastic neuronal cells. Thus, it is regarded as an essential target for cancer pharmaceutical. Design of novel 5-(1H-indol-5-yl)-1,3,4-thiadiazol-2-amine derivatives with enhanced PIM2 inhibitory activity. A series of twenty-five PIM2 inhibitors reported in the literature containing 5-(1H-indol-5-yl)-1,3,4-thiadiazol-2-amines scaffold was studied by using two computational techniques, namely, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indexes analysis (CoMSIA) studies were developed using nineteen molecules having pIC50 ranging from 8.222 to 4.157. The best generated CoMFA and CoMSIA models exhibit conventional determination coefficients R2 of 0.91 and 0.90 as well as the Leave One Out cross-validation determination coefficients Q2 of 0.68 and 0.62, respectively. Moreover, the predictive ability of those models was evaluated by the external validation using a test set of six compounds with predicted determination coefficients Rtest 2 of 0.96 and 0.96, respectively. Besides, y-randomization test was also performed to validate our 3D-QSAR models. The most and the least active compounds were docked into the active site of the protein (PDB ID: 4 × 7q) to confirm those obtained results from 3D-QSAR models and elucidate the binding mode between this kind of compounds and the PIM2 enzyme. These satisfactory results are not offered help only to understand the binding mode of 5-(1H-indol-5-yl)-1,3,4-thiadiazol series compounds into this kind of targets, but provide information to design new potent PIM2 inhibitors.

Entities:  

Keywords:  5-(1H-indol-5-yl)-1,3,4-thiadiazol; CoMFA; CoMSIA; Drug design; Molecular docking; PIM2

Year:  2018        PMID: 30607318      PMCID: PMC6314742          DOI: 10.1007/s40203-018-0043-7

Source DB:  PubMed          Journal:  In Silico Pharmacol        ISSN: 2193-9616


  4 in total

1.  Identification of a novel dual-target scaffold for 3CLpro and RdRp proteins of SARS-CoV-2 using 3D-similarity search, molecular docking, molecular dynamics and ADMET evaluation.

Authors:  Adnane Aouidate; Adib Ghaleb; Samir Chtita; Mohammed Aarjane; Abdellah Ousaa; Hamid Maghat; Abdelouahid Sbai; M'barek Choukrad; Mohammed Bouachrine; Tahar Lakhlifi
Journal:  J Biomol Struct Dyn       Date:  2020-06-18

2.  Discovery of novel natural products as dual MNK/PIM inhibitors for acute myeloid leukemia treatment: Pharmacophore modeling, molecular docking, and molecular dynamics studies.

Authors:  Linda M Mohamed; Maha M Eltigani; Marwa H Abdallah; Hiba Ghaboosh; Yousef A Bin Jardan; Osman Yusuf; Tilal Elsaman; Magdi A Mohamed; Abdulrahim A Alzain
Journal:  Front Chem       Date:  2022-07-22       Impact factor: 5.545

3.  In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.

Authors:  Mustapha Abdullahi; Adamu Uzairu; Gideon Adamu Shallangwa; Paul Andrew Mamza; Muhammad Tukur Ibrahim
Journal:  Heliyon       Date:  2022-08-08

4.  Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.

Authors:  Mustapha Abdullahi; Adamu Uzairu; Gideon Adamu Shallangwa; Paul Andrew Mamza; Muhammad Tukur Ibrahim
Journal:  Beni Suef Univ J Basic Appl Sci       Date:  2022-08-19
  4 in total

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