Molecular Docking and Three‐Dimensional Quantitative Structure–Activity Relationships for Antitubercular Pyrimidine Derivatives
| Autor: | A. Shyam Kumar, Sruthi Turaga, Tejraj M. Aminabhavi, Vinod Shaiva, Shilomboleni Prodensia T, Gurubasavaraj V. Pujar, Pohamba Johanna K, Praveen M. Parkali, Sheshagiri R. Dixit, Shrinivas D. Joshi |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
chemistry.chemical_classification
Fatty acid biosynthesis Polymers and Plastics biology Pyrimidine 010405 organic chemistry Chemistry Organic Chemistry Quantitative structure Reductase 010402 general chemistry 01 natural sciences 0104 chemical sciences Acyl carrier protein chemistry.chemical_compound Enzyme Biochemistry Materials Chemistry biology.protein lipids (amino acids peptides and proteins) |
| Zdroj: | Polycyclic Aromatic Compounds. 42:4132-4145 |
| ISSN: | 1563-5333 1040-6638 |
| Popis: | Enoyl Acyl Carrier Protein (ACP) Reductase, a key enzyme, which catalyzes the last reductive step of fatty acid biosynthesis and it, is one of the key enzymes for the development of antitubercular agents. In this pursuit, molecular docking and 3D-QSAR studies (CoMFA and CoMSIA) have been performed on a series of pyrimidine derivatives (29 compounds) to understand the binding sites, interactions to improve over the existing leads in terms of improved biological and physico-chemical properties. Molecular docking was performed on a protein InhA (T2A mutant) (PDB ID: 5OIR) using the Surflex-Dock suite available in SYBYL-X 2.1.1 (Tripose Inc., USA). In addition, 3D-QSAR studies have been performed to validate the models using the data set, which was segregated into training and test set by using the Diversity and Dissimilarity method. Structural features required for the prediction of better inhibitory potency was generated in the form of contour maps from the CoMFA and CoMSIA models (Steric, Electrostatic, Hydrophobicity, H-bond donor and acceptor maps) and predicted values for r2 = 0.966, q2 = 0.22 for the CoMFA model and r2 = 0.925, q2 = 0.576 for the CoMSIA model. From this study, it is observed that interaction with amino acid residues TYR158, MET199, MET161, GLY96, and PHE97 are important for the activity that helped to predict SARs by providing important structural features. Both the models were good in understanding the specific activity of some of the compounds that will facilitate to develop new types of Enoyl ACP reductase inhibitors. |
| Databáze: | OpenAIRE |
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