| Titre : | Multi-combined Drug-likeness, 3D-QSAR Modeling, Molecular docking and Molecular Dynamics Analysis of several series of pharmaceutical |
| Auteurs : | Maroua Fattouche, Auteur ; Salah Belaidi, Directeur de thèse |
| Type de document : | Thése doctorat |
| Editeur : | Biskra [Algérie] : Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie, Université Mohamed Khider, 2024 |
| Format : | 1 vol. (97 p.) / ill., couv. ill. en coul / 30 cm |
| Langues: | Anglais |
| Langues originales: | Anglais |
| Résumé : |
Neuropathic pain syndrome has a profoundly negative and agonizing impact on the lives of the individuals it afflicts. In order to find an effective treatment for this condition, extensive and thorough scientific studies have demonstrated that the σ1 receptor serves as an exceptional target for therapeutic compounds. The 3D-QSAR studies were constructed using the technique of comparative molecular similarity indice analysis (CoMSIA). The outcomes of these studies demonstrated the reliability of CoMSIA model (with R2 train value of 0.96 and Q2 value of 0.54) in accurately predicting the activity of various compounds. By assimilating the valuable insights gathered from the field contributors of the 3D-QSAR models and conducting molecular docking studies on the highly potent compound C48, a total of sixteen new compounds were successfully designed to exhibit enhanced efficacy against neuropathic pain. In addition to the comprehensive 3D-QSAR analysis, the newly synthesized compounds were subjected to an absorption, distribution, metabolism, excretion, and toxicity evaluation. This evaluation aimed to assess the pharmacokinetic and toxicological properties of the compounds, providing valuable insight for future in vitro investigations. Calculations DFT of the new compounds Mol2, Mol3, and Mol4, including the analysis of their molecular properties, geometric optimization, frontier molecular orbital (FMOs), density states (DOS), and energy evaluation, In order to compare these compounds with the reference ligand 61w, their respective properties were thoroughly investigated. The most stable orientations for the compounds Mol2, Mol4, and Mol3 were determined to be the ones that yielded the highest stability and efficiency. The significant advancements made in this study, should serve as a strong motivation for future in vitro investigations on these compounds. |
| Sommaire : |
Contents Abstract………………………………………………………………………………………..I Contents…………………………………………………………………………………...…III List of works……………………………………………………………………………….VIII List of abbreviations……………………………………………………………....................X List of figures…………………………………………………………………………...….XIV List of tables……………………………………………………………………...………XVII General Introduction………………………………………………………………………....2 CHAPTER I The pyrimidine and inhibition of human σ1 receptor for neuropathic pain syndrome treatment 1. The pyrimidine………………………………………………………………………...…….8 1.1 Introduction…………………………………………………………………………...……8 1.2 Pyrimidine ring structure……………………………………………………………..……9 1.3 Medicinal Properties of Pyrimidines………………………………………………...……10 2. Pain: A simplified model………………………………………………………………..…11 2.1 Nociceptive input…………………………………………………………………………12 2.2 Modulatory output……………………………………………………………………..….13 2.3 Local control……………………………………………………………………………...14 2.4 Neuropathic pain………………………………………………………………….………16 3. The sigma-1 receptor………………………………………………………………………16 3.1 History and discovery of Sigma-1 Receptor……………………………………..……….16 3.2 The pharmacology of Sigma-1 Receptor…………………………………………………18IV References………………………………………………………………………………….…20 CHAPTER II Overview on Computational methods in drug discovery 1. Introduction……………………………………………………………………..………….25 2. Computer-aided drug design…………………………………………………….…………25 2.1 CADD applications in drug discovery and development…………………………………26 2.2 Classification of CADD……………………………………………………………..……28 2.2.1 Ligand-based drug design (LBDD)………………………………………………..……28 2.2.2 Structure-based drug discovery (SBDD)………………………………………….……28 2.3 Molecular mechanics………………………………………………………………..……29 3. Quantitative structure–activity relationship………………………………..………………30 3.1 3D-QSAR…………………………………………………………………………………31 3.1.1 The CoMFA method………………………………………………………...………….32 3.1.2 The CoMSIA method………………………………………………………...…………32 3.1.3 Alignment of the structures…………………………………………………..…………32 3.1.4 Calculation of molecular interaction fields……………………………………..………33 3.1.5 Interpretation and validation of a QSAR model………………………………..………34 3.1.5.1 Internal validation……………………………………………………….……………34 3.1.5.2 Standard statistical tests and coefficients……………………………..………………35 3.1.5.3 External validation……………………………………………………………………36V 3.1.6 Applications of the QSAR study ……………………………………….………………37 3.2 Structure-based virtual screening…………………………………………………………39 4. Molecular docking………………………………………………………………………….39 4.1 General protocol……………………………………………………………..……………40 4.1.1 Ligand preparation………………………………………………………...……………41 4.1.2 Target preparation………………………………………………………………………41 4.1.3 Binding site detection……………………………………………………..…………….42 4.1.4 Docking validation…………………………………………………………..………….42 4.2 Types of molecular docking………………………………………………………………43 4.2.1 Rigid docking………………………………………………………...…………………43 4.2.2 Semi-flexible docking……………………………………………..……………………43 4.2.3 Flexible-flexible docking…………………………………………….…………………43 4.3 Scoring Functions (SFs)……………………………………………………..……………45 4.3.1 Physics-based SFs………………………………………………………………………45 4.3.2 Empirical SFs………………………………………………………………...…………46 4.3.3 Knowledge-based SFs……………………………………………………..……………47 4.3.4 Consensus scoring………………………………………………………………………48 4.3.5 Machine-learning-based SFs……………………………………………………………49 5. Pharmacokinetics Properties and Computational tools employed in ADMET………...….50 6. Quantum mechanics…………………………………………..……………………………51VI 7. Density Functional Theory (DFT)…………………………………….……………...……51 7.1 Conceptual Density Functional Theory (DFT)……………………………………...……51 7.1.1 Fundamental and Computational Aspects of DFT……………………………...………52 References……………………………………………………………………………….……54 CHAPTER III Materials and methods 1. Introduction………………………………………………………………………...………62 2. Computational methods…………………………………………………………….………62 3. Data sets…………………………………………………………………………………….65 4. Equilibrium structure optimizations…………………………………………………..……66 5. Generation of 3D-QSAR studies and CoMSIA analysis……………………………………66 6. Molecular docking……………………………………………………………………….…67 6.1. Preparation of the membrane protein 5HK1………………………………………………67 6.2. Docking of the proposed molecules into the 5HK1 binding site………………………..…67 7. Prediction of synthetic accessibility and ADMET characteristics……………………..……67 8. DFT calculations……………………………………………………………………………68 References………………………………………………………………………………….…70 CHAPTER IV Results and discussion 1. Introduction…………………………………………………………75 2. Optimized geometries of the compounds of the series………………………...……………75 3. CoMSIA results………………………………………………………………….…………75 3.1. CoMSIA model………………………………………………………………...…………75 3.2. CoMSIA graphical interpretation and contour analysis………………………..…………76 4. Design and selection of new human σ1 receptor inhibitors……………………………….…78 5. Docking results and analysis…………………………………………………………..……79 6. ADMET prediction and synthetic accessibility……………………………………….……84 7. DFT calculations…………………………………………………………………….….…..88VII 7.1. The trend of reactivity and FMO study……………………………………………….….88 7.2. Density of states (DOS)………………………………………………………………… 90 References.......92 General conclusion....95 Appendices..97 |
| Type de document : | Thése doctorat |
| En ligne : | http://thesis.univ-biskra.dz/id/eprint/6575 |
Disponibilité (1)
| Cote | Support | Localisation | Statut |
|---|---|---|---|
| TCH/118 | Théses de doctorat | bibliothèque sciences exactes | Consultable |
