Microsoft Word - ETASR_V11_N4_pp7336-7342 Engineering, Technology & Applied Science Research Vol. 11, No. 4, 2021, 7336-7342 7336 www.etasr.com Zaher et al.: In-silico Study of the Developed Hydroxychloroquine-based ACE2 Inhibitor Molecules … In-silico Study of the Developed Hydroxychloroquine-based ACE2 Inhibitor Molecules Against COVID-19: Molecular Modeling and Docking K. Zaher Laboratory of Preparation Modification and Application of Multiphase Polymeric Materials (LMPMP) University Ferhat Abbas Setif-1 Setif, Algeria zaherkarma@gmail.com N. E. Masango Laboratory of Preparation Modification and Application of Multiphase Polymeric Materials (LMPMP) University Ferhat Abbas Setif-1 Setif, Algeria nyarieellen@gmail.com W. Sobhi Laboratory of Applied Biochemistry Faculty of Nature and Life Sciences University Ferhat Abbas Setif-1 and Research Center of Biotechnology Constantine, Algeria sobhiwidad@gmail.com K. E. Kanouni Laboratory of Preparation Modification and Application of Multiphase Polymeric Materials (LMPMP) University Ferhat Abbas Setif-1 Setif, Algeria khalilkanouni@hotmail.com A. Semmeq National Center for Scientific Research and Laboratory of Theoretical Physics and Chemistry University of Lorraine Nancy, France abderrahmane.semmeq@univ-lorraine.fr Y. Benguerba Laboratory of Preparation Modification and Application of Multiphase Polymeric Materials (LMPMP) University Ferhat Abbas Setif-1 Algeria benguerbayacine@yahoo.fr Abstract-In the present study, we will verify the action of hydroxychloroquine-based derivatives on ACE2 which is considered to be the main portal of entry of the SARS-CoV-2 virus and constitutes an exciting target given its relative genetic stability compared to viral proteins. Thus, 81 molecules derived from hydroxychloroquine by substitutions at 4 different positions were generated in-silico and then studied for their affinity for ACE2 by molecular docking. Only 4 molecules were retained because of their affinity and bioavailability demonstrated by molecular dynamics and molecular docking calculations using COSMOtherm and Materials Studio software. Keywords-hydroxychloroquine; molecular modeling; Covid-19; ACE2; affinity I. INTRODUCTION Covid-19 is caused by SARS-CoV-2 [1] which is one of the emerging respiratory viruses, including MERS (Middle East Respiratory Syndrome) and SARS-CoV (Severe Acute Respiratory Syndrome), which all belong to the same family of coronaviridae [2]. The most common symptoms include fever, dry cough, muscle fatigue, headache, and diarrhea in some cases. Discovered in Wuhan in China in December 2019, this disease quickly spread throughout the world [3]. A few months after the start of the pandemic, more than 2,500,000 people have already died, and more than 100 million have been infected. To date, there is no effective cure against Covid-19 [4] and it is necessary to wait several months before the use of vaccines reaches a satisfactory level. During this time, the treatment of the disease relies on drugs to relieve the severe symptoms of the disease. To this end, more than 200 drugs have already been the subject of clinical trials, including hydroxychloroquine [5]. By targeting the SARS-CoV2 virus, it has been shown that chloroquine and several of its derivatives can bind to several viral proteins [6, 7]. Besides, chloroquine and its derivatives can also bind to ACE2 [8, 9]. The choice of this target is based on two main facts: the first is that ACE2 is the main entry point for the virus and the second is because of its genetic stability Corresponding author: K. E. Kanouni Engineering, Technology & Applied Science Research Vol. 11, No. 4, 2021, 7336-7342 7337 www.etasr.com Zaher et al.: In-silico Study of the Developed Hydroxychloroquine-based ACE2 Inhibitor Molecules … [10, 11]. Chloroquine and hydroxychloroquine have been the subjects of several studies to explain their effect on the SARS- CoV2 virus proteins [12, 13] such as NSP3, main protease, RNA dependent polymerase, spike glycoprotein, ADP-ribose-1 monophosphatase, and NSP9 replicase protein [6] These interactions, determined in silico, mean that chloroquine and its derivatives are potential active molecules against SARS-Cov2 [14, 15]. It appears -in many studies- that hydroxychloroquine interacts with ACE2 (PBD code: 6M18) [8]. We performed the present work to study, in silico, the effect of a series of hydroxychloroquine-derived molecules on ACE2. Thus, 81 molecules were obtained by substitution of hydroxychloroquine on 4 different positions. The study aims to estimate the affinity of the selected molecules for ACE2, the prediction of their bioactivity, molecular docking, and their electronic properties by COSMO-RS using COSMOtherm software (version 15.0). The second part of this work is focused on the selection of the preferred molecules according to their physicochemical properties calculated by molecular modeling and molecular docking method using Materials Studio software (version 17.1). II. MATERIALS AND METHODS The chemical properties of hydroxychloroquine were calculated using SwissADME (Table I). Four positions, 4, 11, 12, and 13, were chosen to undergo modifications by substituting the original chemical groups with others (Table II). TABLE I. HYDROXYCHLOROQUINE PROPERTIES CALCULATED BY SWISSADME Properties Values Molecular weight 335.9g/mol XLogP 3.6 Hydrogen acceptors 4 Hydrogen donors 2 Rotative bonds 9 Exact mass 335.17644g/mol Mono-isotopic mass 335.17644g/mol TPSA (Topological polar surface area) 48.4A2 Heavy atoms 23 TABLE II. CHEMICAL GROUPS SELECTED TO CREATE NEW MOLECULES. Position Original First modification Second modification 4 – R1 H CH3 F 11 – R2 CH3 CH2OH CHO (aldehyde) 12 – R3 CH2 CH-NH2 CH-CH3 13 – R4 CH2 -O- CH2OH It should be noted that only these 4 positions leave the interaction between the candidate molecules with the receptor site relatively stable. These substitutions made it possible to generate 81 new molecules, which were subjected to the study of their affinity for ACE2 by examining two essential parameters: Ligand Efficiency (LE) and Lipophilic Ligand Efficiency (LLE). Molinspiration Chemoinformatics software carried out the prediction of the bioactivity of the selected molecules. This step allows classifying the molecules according to their capacity to bind to the protein. The study on the protein ACE2-ligand complexes was investigated using SeeSAR software. In the last step, we studied the electronic properties of these molecules by COSMO-RS software. III. RESULTS AND DISCUSSION A. Construction of a Series of Inhibitor Molecules from Hydroxychloroquine After having done the modifications mentioned above, we managed to formulate 81 different molecules from Hydroxychloroquine with the help of the SeeSAR [16]. The main objective was to obtain a candidate molecule closer to Hydroxychloroquine but increase the receptor ACE2 (Table III). TABLE III. RESULTS EXPLAINING THE FIXATION PROBABILITY OF EACH MOLECULE WITH THE RECEPTOR Molecule R1 R2 R3 R4 Fixation probability to the receptor site Molecule_01 H CH3 CH2 CH2 YES Molecule_02 H CH3 CH2 O YES Molecule_03 H CH3 CH2 CH-OH YES Molecule_04 H CH3 CH-NH2 CH2 YES Molecule_05 H CH3 CH-NH2 O YES Molecule_06 H CH3 CH-NH2 CH-OH YES Molecule_07 H CH3 CH-CH3 CH2 YES Molecule-08 H CH3 CH-CH3 O YES Molecule_09 H CH3 CH-CH3 CH-OH YES Molecule_10 H CH2-OH CH2 CH2 YES Molecule_11 H CH2-OH CH2 O NO Molecule_12 H CH2-OH CH2 CH-OH NO Molecule_13 H CH2-OH CH-NH2 CH2 YES Molecule_14 H CH2-OH CH-NH2 O YES Molecule_15 H CH2-OH CH-NH2 CH-OH NO Molecule_16 H CH2-OH CH-CH3 CH2 YES Molecule_17 H CH2-OH CH-CH3 O YES Molecule_18 H CH2-OH CH-CH3 CH-OH YES Molecule_19 H CHO CH2 CH2 NO Molecule_20 H CHO CH2 O NO Molecule_21 H CHO CH2 CH-OH NO Molecule_22 H CHO CH-NH2 CH2 NO Molecule_23 H CHO CH-NH2 O NO Molecule_24 H CHO CH-NH2 CH-OH NO Molecule_25 H CHO CH-CH3 CH2 NO Molecule_26 H CHO CH-CH3 O NO Molecule_27 H CHO CH-CH3 CH-OH NO Molecule_28 CH3 CH3 CH2 CH2 NO Molecule_29 CH3 CH3 CH2 O NO Molecule_30 CH3 CH3 CH2 CH-OH NO Molecule_31 CH3 CH3 CH-NH2 CH2 NO Molecule_32 CH3 CH3 CH-NH2 O NO Molecule_33 CH3 CH3 CH-NH2 CH-OH NO Engineering, Technology & Applied Science Research Vol. 11, No. 4, 2021, 7336-7342 7338 www.etasr.com Zaher et al.: In-silico Study of the Developed Hydroxychloroquine-based ACE2 Inhibitor Molecules … Molecule_34 CH3 CH3 CH-CH3 CH2 NO Molecule_35 CH3 CH3 CH-CH3 O NO Molecule_36 CH3 CH3 CH-CH3 CH-OH NO Molecule_37 CH3 CH2-OH CH2 CH2 NO Molecule_38 CH3 CH2-OH CH2 O NO Molecule_39 CH3 CH2-OH CH2 CH-OH NO Molecule_40 CH3 CH2-OH CH-NH2 CH2 YES Molecule_41 CH3 CH2-OH CH-NH2 O NO Molecule_42 CH3 CH2-OH CH-NH2 CH-OH NO Molecule_43 CH3 CH2-OH CH-CH3 CH2 NO Molecule_44 CH3 CH2-OH CH-CH3 O NO Molecule_45 CH3 CH2-OH CH-CH3 CH-OH NO Molecule_46 CH3 CHO CH2 CH2 NO Molecule_47 CH3 CHO CH2 O NO Molecule_48 CH3 CHO CH2 CH-OH NO Molecule_49 CH3 CHO CH-NH2 CH2 NO Molecule_50 CH3 CHO CH-NH2 O NO Molecule_51 CH3 CHO CH-NH2 CH-OH NO Molecule_52 CH3 CHO CH-CH3 CH2 NO Molecule_53 CH3 CHO CH-CH3 O NO Molecule_54 CH3 CHO CH-CH3 CH-OH NO Molecule_55 F CH3 CH2 CH2 NO Molecule_56 F CH3 CH2 O NO Molecule_57 F CH3 CH2 CH-OH NO Molecule_58 F CH3 CH-NH2 CH2 NO Molecule_59 F CH3 CH-NH2 O NO Molecule_60 F CH3 CH-NH2 CH-OH NO Molecule_61 F CH3 CH-CH3 CH2 NO Molecule_62 F CH3 CH-CH3 O NO Molecule_63 F CH3 CH-CH3 CH-OH NO Molecule_64 F CH2-OH CH2 CH2 NO Molecule_65 F CH2-OH CH2 O NO Molecule_66 F CH2-OH CH2 CH-OH NO Molecule_67 F CH2-OH CH-NH2 CH2 NO Molecule_68 F CH2-OH CH-NH2 O YES Molecule_69 F CH2-OH CH-NH2 CH-OH NO Molecule_70 F CH2-OH CH-CH3 CH2 NO Molecule_71 F CH2-OH CH-CH3 O NO Molecule_72 F CH2-OH CH-CH3 CH-OH NO Molecule_73 F CHO CH2 CH2 YES Molecule_74 F CHO CH2 O NO Molecule_75 F CHO CH2 CH-OH NO Molecule_76 F CHO CH-NH2 CH2 NO Molecule_77 F CHO CH-NH2 O YES Molecule_78 F CHO CH-NH2 CH-OH NO Molecule_79 F CHO CH-CH3 CH2 NO Molecule_80 F CHO CH-CH3 O NO Molecule_81 F CHO CH-CH3 CH-OH NO B. Affinity Study Parameters that explain in detail the affinity of each molecule for the receptor site include: LE: Refers to each atom's bond energy in a molecule toward the receptor. In other words, it refers to the ratio between ∆G (Gibbs energy) and the number of atoms other than hydrogen in a molecule. If the LE value is greater than 0.3, the molecule in question will have a greater probability of fixing itself to the receptor [17]. The corresponding mathematical equation is given by: LE = (1.37×plC50)/HA (1) plC50 corresponds to the Ligand concentration occupying 50% of the receptor, and HA represents the number of atoms other than hydrogen (heavy atoms). LLE: Refers to a parameter used in the conception of drugs that permits evaluating the potential energy of a chemical bond and its lipophilicity to deduce its drug-likeness [18]. For the Ligand-receptor interaction to be favorable, the LLE value should be greater than or equal to 5 [19]. The corresponding mathematical equation is given by: LLE = plC50 – Log (P) (2) Every molecule was docked with the receptor ACE2 model to show the possibility of forming a stable complex. From 81 molecules, it was found that only 19 were proved to interact with the specified target favorably. A drug's capacity to interact with a receptor is directly linked to its affinity for the receptor [20]. The estimated affinity for the 19 candidate molecules was calculated, and the results are shown in Table IV. The results show that only 8 molecules are having a good affinity when compared with molecule_01 (Hydroxychloroquine). TABLE IV. ESTIMATED AFFINITY VALUES FOR THE CANDIDATE MOLECULES Molecules Estimated affinity (nm) Molecules Estimated affinity (nm) Molecule_01 6202803 Molecule_13 48012075 Molecule_02 10178356 Molecule_14 238783948 Molecule_03 21861750 Molecule_16 4668615 Molecule_04 47841687 Molecule_17 3998199 Molecule_05 61083910 Molecule_18 645211 Molecule_06 7882945 Molecule_40 454448307 Molecule_07 4408448 Molecule_68 477694848 Molecule_08 4351693 Molecule_73 5716436 Molecule_09 720512 Molecule_77 1016590889 Molecule_10 2407812 C. Bioactivity Prediction The selected 8 molecules were examined in Molinspiration Chemoinformatics software to know the preferred binding protein of each molecule [21]. The results of the bioactivity prediction are summarized in Table V. The symbol "XXXX" means that the molecule can interact with 4 types of protein, one of them being an enzyme inhibitor, the symbol "XXXXX" means that the molecule can interact with 5 types of protein, one of them being an enzyme inhibitor, and symbol "0" means that there is no particular interaction with any protein. Only 4 molecules can have the same activity as Hydroxychloroquine. TABLE V. BIOACTIVITY PREDICTION OF THE CANDIDATE MOLECULES Molecules Predicted bioactivity Molecule _01 0 Molecule _07 XXXX Molecule _08 0 Molecule _09 XXXXX Molecule _10 0 Molecule _16 0 Molecule _17 0 Molecule _18 XXXXX Molecule _73 XXXXX D. Study on the Protein-Ligand Complexes Following the analysis of the candidate molecules by Molinspiration, bioactivity results and the molecules' properties proved that only 4 of the 19 molecules had the desired Engineering, Technology & Applied Science Research Vol. 11, No. 4, 2021, 7336-7342 7339 www.etasr.com Zaher et al.: In-silico Study of the Developed Hydroxychloroquine-based ACE2 Inhibitor Molecules … properties (had the estimated affinity closer to that of Hydroxychloroquine). These are Molecule_07, Molecule_09, Molecule_18, and Molecule_73. Figure 1 shows the candidate molecules in interaction with the receptor ACE2 and energy values in kJ/mol calculated from desolvation and interaction energies. SeeSAR was used to study these complexes. Each sphere represents atoms in the molecule, and each atom interacts differently with the atoms of the receptor (Figure 1). (a) (b) (c) (d) (e) Fig. 1. Interaction of the 4 potential candidate molecules with the protein ACE2. Each sphere represents an atom, and the greater the sphere's size, the greater the interaction with the receptor site. When the sphere is colored green, this signifies that the contribution of this atom is favorable. On the contrary, the sphere colored in red characterizes the unfavorable atom's interaction contribution. If the sphere is not colored, the value of ∆G is null or close to zero. Therefore, the contribution of the corresponding atom is negligible. Blue color represents polar regions, while yellow color represents hydrophobic regions [22]. The following points describe the interpretation of the results obtained in Figure 1. • Molecule 01: The Hydroxychloroquine molecule shows a low affinity with its receptor site. Most of its atoms colored with green have a low ∆G values, and it has an unfavorable contribution formed by the N17 (2.7kJ/mol) and C2 (2.3kJ/mol). • Molecule 07: atoms N17 and N3 are colored in red, with ∆G values of 9.3 and 1.6 kJ/mol, respectively. Therefore, the interaction with the receptor site is unfavorable. However, most of the atoms have negative ∆G values C19 (-5.7kJ/mol), O46 (-5.2kJ/mol), C18 (-3.7kJ/mol), C41 (-3.1kJ/mol), C10 (-2.9kJ/mol), and Cl6 (-1.9kJ/mol), signifying that their interaction with the receptor site is favorable. • Molecule 09: C21 is the only atom colored in red (∆G = 6.4kJ/mol), corresponding to unfavorable interaction. Atoms C47 (-3.7kJ/mol), C2 (-3.6kJ/mol), C19 (- Engineering, Technology & Applied Science Research Vol. 11, No. 4, 2021, 7336-7342 7340 www.etasr.com Zaher et al.: In-silico Study of the Developed Hydroxychloroquine-based ACE2 Inhibitor Molecules … 3.4kJ/mol), and O44 (-3.1kJ/mol), have negative ∆G values corresponding to favorable interactions with the ACE2 protein model. • Molecule 18: Likewise, O37 has a positive ∆G value (2.3kJ/mol), so as a result, its interaction with the receptor site is unfavorable. For the atoms C2 (-4.2kJ/mol), C9 (-2.3kJ/mol), C11 (-2.0kJ/mol), Cl6 (-1.8kJ/mol), C19 (-1.6kJ/mol), and C18 (-1.2kJ/mol) the interaction with the receptor site is favorable. • Molecule 73: For this molecule, N3 (7.0kJ/mol) and C14 (5.8kJ/mol) corresponding to unfavorable interaction. Atoms C35 (-4.1kJ/mol), C19 (-3.3kJ/mol), C16 (-3.2kJ/mol), C2 (-2.5kJ/mol), C1 (-2.3kJ/mol), and N12 (-2.3kJ/mol) have favorable interactions with ACE2. After this analysis, we can conclude that Molecules 09 and 18 have the most significant probability to form a sufficiently stable complex with the receptor compared to the other molecules. However, for the other two molecules, the number of atoms with a favorable interaction with the receptor is very high compared to those having a non-favorable contribution, meaning that they also have sufficient capacity to interact with the receptor site. The second step of docking is performed using SeeSAR software to determine the distances between the atoms of each candidate molecule with the amino acids of the protein receptor site (6M18). All the data are resumed in Table VI. TABLE VI. DISTANCES BETWEEN ATOMS OF CANDIDATE MOLECULES WITH AMINO ACIDS OF THE RECEPTOR SITE (6M18) Molecules Atoms Amino acids Distances (A°) Molecule-01 H48 Glu300 1.84 O47 Trp530 2.01 Molecule-07 H47 Ser307 1.93 Molecule-09 H45 Glu300 1.94 H53 2.05 O44 Asn527 1.96 O51 Trp530 1.88 Molecule-18 O37 Trp530 2.01 H47 Glu300 2.25 Molecule-73 H33 Glu300 1.95 • Molecule 1 (Hydroxychloroquine) forms 2 hydrogen bonds with the receptor site, the first is between H48 and Glu300 with a short distance and the second is between O47 and Trp530 with a moderate distance. • Molecule 7 forms a single hydrogen bond with the receptor site, between H47 and Ser307 with a moderate distance. • Molecule 9 forms 2 hydrogen bonds with Glu300, the first with H45 (short) and the second with H53 (moderate), ASN-527 forms another hydrogen bond (moderate) with O44. The littlest interaction was created between O51 and Trp530. • Molecule 73 forms a single hydrogen bond with the receptor site between H33 and Glu300 with a moderate distance. From these results, it can be concluded that Molecule 9 will have the best interaction with the receptor site. E. Prediction of Electronic Properties by COSMO-RS Conductor-like Screening Model for Real Solvents (COSMO-RS) is a quantum chemistry method based on thermodynamics, which helps to determine chemical potentials for solutions [23]. This method can predict sigma charge densities as well as chemical potentials for each species in the solution. The calculation is done in two main steps: Firstly, geometrical optimization on the molecule was done with the module Dmol3 [24] of the software BIOVIA Material Studio 2017 [25]. Secondly, the obtained cosmo-files were used to calculate sigma profiles and sigma potentials with the COSMOtherm software [26]. The sigma profile is divided into 3 distinct regions: • HBD Region: Hydrogen bond donor region: the sigma values are less than -0.01eÅ-2. The negative sigma values mean positive polarities [27]. • Non-Polar Region: σ values are given in the interval -0.01eÅ-2 to +0.01eÅ-2 [28]. • HBA Region: Hydrogen bond acceptor region: the σ values are greater than 0.01eÅ-2. Positive sigma values represent negative polarities [29]. Figure 2 shows that the highest picks for all the selected molecules are found in the non-polar region. They are showing the tremendous non-polar character of the molecule surfaces. That said, the 5 molecules have net peaks in the HBD and HBA regions, making hydrogen bonds as acceptors and donors with the ACE2. The selected molecules meet the criteria that a candidate-molecule must possess to interact with the protein target: HBA, HBD, and hydrophobic sites [30]. Fig. 2. Electronic charge densities of the candidate molecules. Molecule 01 (Hydroxychloroquine) possesses a small HBD and HBA region. Molecule 07 shows a small HBD region and also some HBA regions. In Molecule 09, there are 3 regions capable of accepting hydrogen atoms and a small hydrogen donor region. Molecule 18 possesses a large enough hydrogen donor region as well as a hydrogen bond acceptor region. A tiny region in Molecule 73, almost negligible, can donate a hydrogen atom (colored in blue) while a more significant part, Engineering, Technology & Applied Science Research Vol. 11, No. 4, 2021, 7336-7342 7341 www.etasr.com Zaher et al.: In-silico Study of the Developed Hydroxychloroquine-based ACE2 Inhibitor Molecules … colored in red, represents the hydrogen acceptor region; The most prominent picks in the range -0.01eÅ-2<σ<+0.01eÅ-2 are due to the non-polar chemical groups such as CH3, CH2, CH, which are more abundant in the molecules. Negatively charged atoms such as O- constitute hydrogen acceptors (region HBA) [31]. The positively charged atoms or atoms with lone pairs of electrons are responsible for the picks in the region HBD (NH, NH2, and NH3). Figure 3 proves the results obtained from the sigma profiles and the energies of desolvation and interaction. All candidate molecules have strong affinities HBD and HBA well balanced. This demonstrates that they have sufficient solubility in water and blood after administration [28]. Fig. 3. Sigma potentials of the four candidate molecules. IV. CONCLUSION Taking hydroxychloroquine as the primary molecule, we built 81 new derivative molecules, of which only 4 molecules had improved affinity for ACE2. The modifications of the hydroxychloroquine structure at critical positions enhance properties such as affinity for the receptor site, solubility, and permeability and allow reconsidering the hydroxychloroquine derivative molecules for therapeutic use as a ligand for ACE2. 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