In Silico Drug Design Studies of Bioactive Cannabinoid and [60]Fullerene Derivatives

In Silico Drug Design Studies of Bioactive Cannabinoid and [60]Fullerene Derivatives Inaugural-Dissertation to obtain the academic degree Doctor rerum naturalium (Dr. rer. nat.) submitted to the Department of Biology, Chemistry and Pharmacy of Freie Universität Berlin by SERDAR DURDAGI from Tuzluca, Turkey January, 2009 The work presented in this thesis is financially supported by the European Union within the 6th Framework Programme-Marie Curie Actions (Project: EURODESY- MEST-CT-2005-020575). 1st Reviewer: Prof. Hartmut Oschkinat 2nd Reviewer: Prof. Thomas Mavromoustakos Date of defence: 04 May 2009 2 Abstract The relationship between conformations of bioactive molecules with their pharmacol- ogical profiles has been well established. Only the unique biologically active conformation of a drug molecule can bind to the active site of the receptor. In this thesis, conformational analysis of bioactive compounds at various environments will be dis- cussed. Two categories of molecules were investigated; cannabinoid (CB) analogues and [60]fullerene derivatives. The major structural characteristics of these molecules are: (i) amphiphilicity and (ii) existence of flexible and rigid pharmacophoric segments. Their flexible segments constitute a challenging field for conformational analysis exploring of putative bioactive conformations. In case of CBs, a set of novel Δ8-tetrahydrocannabinol (Δ8-THC) and cannabidiol (CBD) analogues were subjected to three-dimensional quantitative structure-activity relationships (3D-QSAR) studies using comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) method- ologies. The high active compound C-1'-dithiolane Δ8-THC analogue AMG3 at the data base was selected as template molecule. Using molecular modeling techniques such as Monte Carlo (MC), molecular dynamics (MD) and grid scan analysis, the putative bioactive conformation of AMG3 in solution was determined. This conformer was used as a template, and CB1 and CB2 pharmacophore models were developed. The availability of homology models of CB1 and CB2 receptors based on rhodopsin has allowed the conformational analysis studies of AMG3 at the binding site of the receptor. Derived low energy conformers of AMG3 at the receptor site have been compared with its in solution conformations. The steroelectronic properties of binding cavities of a receptor model are directly related to the performed molecular model co- ordinates. In the presented thesis, a homology modeling study based on β2-adrenergic receptor for both CB1 and CB2 receptors was also performed and results were compared with rhodopsin based homology models. Similar binding sites of CB1 and CB2 receptors using rhodopsin based models have been generated using the β2-adrenergic based receptors. The QSAR models were re-generated using putative bioactive conformers of AMG3 at the binding site of the CB1 and CB2 receptors. Relative contri- 3 butions of steric/electrostatic fields of the 3D QSAR/CoMFA and CoMSIA pharmacophore models have shown that steric effects govern the bioactivity of the compounds, but electrostatic interactions also play an important role. The comparison of derived QSAR models has shown that increasing the complexity level of calculations (mimicking more accurately the biological conditions) was positively affected the obtained statistical result. The optimal QSAR partial least square (PLS) analysis was used as an input in the de novo drug design studies and these simulations provided novel CB analogues with enhanced predicted binding affinities. In case of fullerene derivatives, a series of experimentally reported as well as compu- tationally designed monoadducts and bisadducts of [60]fullerene analogues have been used in order to analyze the binding interactions between fullerene based inhibitors and human immunodeficiency virus type I aspartic protease (HIV-1 PR), employing docking studies. MD simulations of ligand-free and the inhibitor-bound HIV-1 PR systems complemented the above studies and provided proper input structure of HIV- 1 PR in docking simulations. The obtained results revealed a different orientation of the β-hairpin flaps at these two systems. In inhibitor bound system, the flaps of the enzyme are pulled in toward the bottom of the active site (the closed form) while, in ligand-free system flaps shifted away from the dual Asp25 catalytic site and this system adopts a semi-open form. The structural analysis of these systems at catalytic and flexible flap regions of the HIV-1 PR through the simulations, assisted in understand- ing the structural preferences of these regions, as well as, the adopted orientations of fullerene derivatives within the active site of the enzyme. The reported most active fullerene analogue in the data base has been used as template and 3D QSAR models were derived. Based on obtained contour plots and derived PLS analysis, de novo drug design studies were performed in order to propose novel analogues with enhanced binding affinities. Such structures may trigger the interest of medicinal chem- ists for synthesizing novel HIV-1 PR inhibitors possessing higher bioactivity, consid- ering the urgent need for new anti-HIV drugs. 4 Contents Chapter 1. Introduction…………………………………………………………...…9 1.1 Motivation……………………………………………………………………......10 1.2 Investigated Systems…………………………………………..…………………13 1.2.1 CBs…………………………………………………………………...…….13 1.2.2 [60]Fullerene Derivatives……………………………………………...…..15 1.3 The Aim of the Study……………………………………………………….……17 1.4 The Outline of the Thesis Structure……………………………………...………17 Chapter 2. Theoretical Background……………………………….………………18 2.1 Some Useful Definitions for Many-body Systems………………………………19 2.1.1 QM Calculations……………………………………………………….19 2.1.2 Semi-empirical Calculations………………………………….……..…20 2.1.3 MM Calculations: Empirical Force Field Models…………….……….21 2.2 Continuum Representation of the Solvent………………………………….……22 2.2.1 Solvation Free Energy………………………………………………….22 2.2.2 Electrostatic Contributions to the Free Energy of Solvation……..……23 2.3 Computer Simulations Methods…………………………………………………23 2.3.1 Energy Minimization Method………………………………………….23 2.3.2 Molecular Dynamics Method…………………………………….……24 2.3.3 Monte Carlo (MC) Method…………………………………………….25 2.4 Methods for Exploring Conformational Space…………...………….…………..26 2.4.1 Grid Search……………………………………………………………..26 2.4.2 Random Search Methods…………………………………...………….27 2.4.3 Distance Geometry in NMR………………………………..………….28 2.4.4 Exploring Conformational Space by Simulation Methods…………….28 2.4.5 Cluster Algorithms…………………………………………….……….29 2.5 The Use of Molecular Modeling and Cheminformatics Methods in the Design of New Molecules……………………………………………………………….………29 2.5.1 Molecular Docking…………………………………………..…………29 5 2.5.2 Scoring Functions for Molecular Docking…………….….……………30 2.5.3 3D QSAR Studies………………………………………..…..…………32 2.5.3.1 Structure-activity Relationships (SAR)………...…………….32 2.5.3.2 QSAR……………………………………………………..….32 2.5.3.2.1 Partition Coefficients (P)………………...…………33 2.5.3.2.2 Electronic Parameters………………….….………..34 2.5.3.2.3 Steric Parameters……………………….….……….36 2.5.3.2.4 Deriving a QSAR Equation……………..….………37 2.5.3.2.5 Cross-validation…………………………..….…….40 2.5.3.2.6 Principle Components Regression (PCR)………….41 2.5.3.2.7 Partial Least Squares (PLS)…………………….…..43 2.5.3.3 3D QSAR………………………………………………….…44 2.5.3.1 CoMFA……………………………………………....44 2.5.3.2 CoMSIA………………………………………….…..45 2.5.4 De Novo Drug Design………………………………………………….47 Chapter 3. Computational Details…………………………………………..……..48 3.1 Minimization Methods………………………………………………….….…….49 3.1.1 Geometry Optimizations of Investigated Systems…………………….50 3.2 MC Simulations………………………………………………………………….50 3.3 3D QSAR/CoMFA and CoMSIA Settings…………………………………..…..50 3.4 Molecular Docking…………………………………………………………..…..51 3.5 MD Simulations………………………………………………………….………54 3.5.1 Details of the Performed Simulations………………………………….56 3.5.1.1 MD Simulations of CBs…………………………..………….56 3.5.1.2 MD Simulations of HIV-1 PR and Fullerene analogues….….57 3.6 De Novo Drug Design……………………………………………………….…...57 Chapter 4. Strategies in Computational Drug Design……………………………60 6 Chapter 5. Conformational Analysis, 3D QSAR, Homology Modeling, Molecular Docking and MD Simulations of CBs………………..………...……........………..67 5.1 Introduction……………………………………………….……………….……..68 5.2 Results and Discussion………………………………….………………………..77 5.2.1 Conformational Analysis of AMG3 in Vacuum and in Lipid Bilayer En- vironments (without Receptor)…………..……………………….........……………..77 5.2.1.1 Selection of Low Energy Conformers of AMG3 Using MC Studies………………………………………………………………..77 5.2.1.2 Geometry Optimization Calculations……………………...…77 5.2.1.3 Rotational Energy Barrier Calculations…………………..….79 5.2.1.4 MD Simulations of Conformers in Lipid Bilayer.……..….....79 5.2.1.5 3D QSAR/CoMFA Results……………………………….….84 5.2.1.6 3D QSAR/CoMSIA Results………………………………….88 5.2.1.7 Discussion……………………………………………………90 5.2.2 Conformational Analysis of AMG3 at the Binding Site of the Recep- tor…………………………………………………………………………...103 5.2.2.1 Molecular Docking Studies…………………………………103 5.2.2.2 Molecular Specificity for the S1 and S2 Binding Pockets at the CB1 Receptor………………………………………………….……107 5.2.2.3 Second Generation of 3D QSAR Models Based on in silico Docking Results………………………………………………...…..111 5.2.2.4 MD Simulations of AMG3 at the Active Site of the Membrane- associated CB1 and CB2 Receptors…………………….………..…119 5.2.2.5 Third Generation of 3D QSAR Models Based on Conforma- tional Analysis Results of

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