Microsoft Word - 8. muliadi good.docx Indonesian Journal of Chemical Research http://ojs3.unpatti.ac.id/index.php/ijcr Indo. J. Chem. Res., 9(1), 49-56, 2021 DOI: 10.30598//ijcr.2021.9-mul 49 Density Functional Theory for QSAR Antioxidant Compound Myristicin Derivatives Muliadi*, Mudzuna Quraisyah Basimin, Ahmad Muchsin Jayali. Chemistry Education Department, Khairun University, Jl. Bandara Babullah, Ternate 97728 Indonesia *Corresponding author: muliadi@unkhair.ac.id Received: April 2021 Received in revised: April 2021 Accepted: May 2021 Available online: May 2021 Abstract This research was conducted to determine the molecular structure modeling and the quantitative relationship of the activity structure (QSAR) of substituted myristicin derivatives with electron donor groups such as -C6H5 (M1), -NH2 (M2), -Cl (M3), -F (M4), and -H (M5). The results of geometry optimization with the DFT (Density Fractal Theory) method or density functional calculations calculated with the density level of B3LYP/6-31G each obtained the total energy of each compound M1- M5: M1: 175.49 kcal/mol M2: 132.707 kcal/mol, M3: 115.701 kcal/mol, M4: 116.048 kcal/mol, M5: 121.377 kcal/mol. Determining the relationship between descriptors and the antioxidant activity (IC50) for basic structure myristicin compounds and five derivatives was carried out using SPSS 21. The results of the correlation analysis showed that there was a relationship between the descriptors and antioxidant activity. Determining the best QSAR equation model is done by analyzing multiple linear and multilinear regression using IBM SPSS 21. The results of multiple linear regression analysis or multilinear regression obtained for the best QSAR equation model are: Log P = -2.600 + (0.006) IW- (1.558) qC8 - (6.532) EHOMO + (0.014) PSA + (0.133) MD with n = 6, R = 1.000, R2 = 0.926, SE = 0. Keywords: Myristicin, geometry optimization, DFT Method, QSAR Method INTRODUCTION Over time, the human lifestyle has undergone many changes, such as eating habits that preferfast food (Ginting et al., 2017). The fast-food with high heating and burning triggers the formation of free radical compounds.When human consumed this food too much, can cause cancer, stroke, diabetes mellitus, atherosclerosis, cataracts, and coronary heart disease (Rohmatussolihat, 2015). Within a decade, the results of research on free radicals have been intensively reported to trigger various diseases. Free radicals can oxidize nucleic acids, proteins, fats, and even cell DNA and initiate degenerative diseases (Rifai, Kasmui, & Hadisaputro, 2014). One of the compounds that are believed and widely consumed to prevent dangerous diseases is a compound that has antioxidant properties. A report from (Hasanan, 2015), claims that the ability of antioxidant compounds to prevent free radicals is 50% greater than vitamin C (Fadillah, Rahmadani, & Rijai, 2017). Compounds that have antioxidant properties can naturally be obtained from plants (Damayanti & Ervilita, 2017). Several plants produce antioxidants, including rukam fruit extract and kesuma keling seed extract (Fadiyah, Lestari, & Mahardika, 2020; Souhoka, Hattu, & Huliselan, 2019). In addition, bay leaves, kenitu leaves and bark, strawberry leaves, katuk leaves, and nutmeg have also been reported as antioxidants (Widyastuti, Kusuma, Nurlaili, & Sukmawati, 2016). Indonesia is the largest nutmeg producing country globally, with about 70-75% of the total nutmeg production. One of the largest centers of nutmeg production in Indonesia is North Maluku. Nutmeg is a native Indonesian spice plant that has only been used for food and domestic food industry purposes in the form of jam, syrup, and sweets (Dungir, Katja, & Kamu, 2012). In addition, all parts of the nutmeg can be processed into nutmeg oil, such as seeds, pulp and mace (Ayunani, Hastuti, Ansory, & Nilawati, 2018). According to research results from (Wibowo, Febriana, Riasari, & Auilifa, 2018) and (Ismiyarto, Ngadiwiyana, & Mustika, 2009). The main compound contained in the nutmeg plant is myristicin. Myristicin compounds also have antioxidant properties. Isnaeni et al., (2016) studied 13 analogue compounds of chalcone using steric, hydrophobic, and electronic descriptors computationally calculated using the DFT method, using the Gaussian 09 MarvinBeans-6.0.0 programs (Isnaeni et al., 2016). The results showed that Kalkon compound can increase antioxidant activity. Muliadi, et al. Indo. J. Chem. Res., 9(1), 49-56, 2021 DOI: 10.30598//ijcr.2021.9-mul 50 The QSAR (Quantitative Structure-Activity Relationship) method has been widely used to design new drugs and computationally study the relationship between the activity and structure (Tahir, Wijaya, Purwono, & Widianingsih, 2010). Using the QSAR method begins with structural modeling or geometry optimization using the GaussView 6,016 program package to obtain electronic descriptors and the Marvin Sketch 64 program package to obtain hydrophobic and steric descriptors. This biological activity can be predicted through computational computation of molecular descriptors. The QSAR method focuses on correlating activities experimentally with descriptors computationally. Kilo, Aman, Sabihi, & Kilo, (2019) reported using the QSAR method to determine the potency of pyrazoline as an anti-amoeba . The DFT (Density Finctional Theory) method has proven to be very good for the optimization of molecular structures because DFT is a method that iscurrently developing rapidly. This method is very effective and efficient because it can result in close to experimental results and requiringa short time (Chandra, Asmuruf, & Siallagan, 2020). Based on the above background, this study aims to determine the molecular structure model and the quantitative relationship of the activity structure (QSAR) of myristicin derivatives with the DFT method. METHODOLOGY Biological Data The descriptor of biological activity and compounds studied in this research is the antioxidant activity of modified myristicin derivative compounds whose electron donor substitution groups consist of -C6H5, -NH2, -Cl, -F, and -H. The value of Half Maximal Inhibitory Concentration (IC50) of antioxidants is known based on experimental research carried out (Wibowo et al., 2018). Modeling and Geometry Optimization of Myristicin Derivatives Myristicin derivative compounds are modeled in a simulation form based on 3D visualization. Their geometric shapes are optimized using the DFT (Density Functional Theory) method with the combined functional parameters of the three Becke and Lee-Yang-Parr (B3LYP) parameters. All calculations using the Bassist 6-31G set (Male, Wayan Sutapa, & Merion Ranglalin, 2015). Optimization of molecular geometry is carried out to obtain a stable molecular structure (Janssens et al., 1990). Determination of Descriptors Determination of electronic descriptors is done using the DFT (Density Functional Theory) method.The computational calculations using the GaussView 6.016 and Marvin Sketch 64 programs in the form of dipole moment (MD), HOMO energy, LUMO energy, Gap energy (ΔEG), and atomic net charge (qC1, qC2, qC3, qC4, qC5, qC6, qC8, and, qC14). Calculations performed using QSAR, including Log P, Polar Surface Area (PSA), Polarizability, Harary Index, Randic Index, and Wiener Index, were analyzed using computational chemistry calculations (Velkov, 2009). Multilinear Regression Analysis Multilinear regression analysis was performed using the IBM SPSS 21 statistical program based on the Backward method to produce an equation model. Furthermore, the validation of the QSAR equation model was analyzed using data from the consideration of R, R2, and SE (Armunanto & Sudiono, 2010). The accepted equation must have the following criteria: 1) The value of R, R2 is close to 1, and The SE value is small. A small SE indicates that the error rate between the data and the model is relatively small (Tahir, Wijaya, et al., 2010). RESULTS AND DISCUSSION Optimization of Myristicin Derivative Compounds Molecular Geometry The molecular structure modeling of myristicin derivative compounds using the DFT method. Six different electron donor groups in the basicform of myristicin compounds (Figure 1). The compounds used in this study consist of five derivatives compounds and one of myristicin's basic structure. All the compounds had an IC50 tested experimentally (Table 1). An evaluation of the characteristics of the antioxidants present in the nutmeg plant examined by Jukic et al. showed that nutmeg essential oil has strong antioxidants (Agaus & Agaus, 2019). Figure 1.The basic Structure of 6-allyl-4- methoxybenzo[d][1,3]dioxole (M0) O CH3 O O CH2 Muliadi, et al. Indo. J. Chem. Res., 9(1), 49-56, 2021 DOI: 10.30598//ijcr.2021.9-mul 51 Table 1. Data Set of Five Myristicin Derivative Compounds Compound code Donor substituent Log P M1. C6H5 3.97 M2. NH2 1.69 M3. Cl 1.53 M4. F 1.53 M5. H 1.53 In this study, the myristicin derivative compounds use an electron donor substitution group, namely - C6H5, -NH2, -Cl, -F, -H. The antioxidant test showed that the nutmeg had the highest component containing myristicin at 22.22%, and the IC50 data was converted into Log IC50is 1.34. The actual properties (descriptors) of a compound can be predicted if the molecular structure is optimized to obtain a stable structure (Maahury, Male, & Martoprawiro, 2020). 6-allyl-4-phenoxybenzo[d][1,3]dioxole (M1) O-(6-allylbenzo[d][1,3]dioxol-4-yl)hydroxylamine (M2) 6-allylbenzo[d][1,3]dioxol-4-yl hypochlorite (M3) 6-allylbenzo[d][1,3]dioxol-4-yl hypofluorite(M4) 6-allylbenzo[d][1,3]dioxol-4-ol (M5) Figure 2. The 3D structure based on the numberingfor compound M1, M2, M3, M4, M5 using DFT Method; M=Miristisin Author, et al. Indo. J. Chem. Res., 9(1), 40-48, 2021 DOI: 10.30598//ijcr.2021.9-mul 52 Tabel 2.Atomic Charge of Myristicin Derivative Compounds Using DFT Method Atomic Charge (eV) M0 M1 M2 M3 M4 M5 qC1 0.09 0.09 0.09 0.09 0.09 -0.35 qC2 0.11 0.11 0.11 0.11 0.11 0.15 qC3 0.09 0.09 0.11 0.08 0.08 -0.35 qC4 -0.02 -0.02 -0.02 -0.02 -0.02 -0.07 qC5 -0.04 -0.04 -0.04 -0.04 -0.04 -0.35 qC6 -0.02 0.06 -0.02 -0.02 -0.02 0.15 qC8 0.15 0.09 0.15 0.15 0.15 -0.07 qC14 -0.07 0.06 -0.07 -0.07 -0.07 0.15 Table 3.Total Energy Data, Heat of Formation, Electronic Descriptors, Hydrophobic Descriptors and Steric Descriptors of Myristicin Derivatives Using the DFT Method Compound code Total Energy (kcal/mol) Heat of Formation (kcal/mol- kelvin) HOMO Energy (eV) LUMO Energy (eV) ΔEG(eV) Dipole Moment(D) Log P Polariz- ability (Å3) Polar Surface Area (Å2) Indeks Harary Indeks Randic Indeks Wiener M0 140.372 48.588 -0.27799 -0.15618 0.12181 1.6482113 1.34 21.62 27.69 39.21 11.58 292 M1 175.49 61.811 -0.28348 -0.16958 0.1139 1.2891821 3.97 30.09 27.69 61.45 15.02 706 M2 132.707 48.628 -0.27678 -0.15715 0.11963 1.6507633 1.69 21.32 53.71 39.21 11.29 292 M3 115.701 47.18 -0.28240 -0.20193 0.08047 4.6800676 1.53 19.72 38.69 35.19 9.90 238 M4 116.048 46.536 -0.28663 -0.20637 0.08026 4.4347508 1.53 19.72 38.69 35.19 9.90 238 M5 121.377 43.962 -0.28022 -0.15718 0.12304 1.7627658 1.53 19.72 38.69 35.19 10.441 238 Author, et al. Indo. J. Chem. Res., 9(1), 40-48, 2021 DOI: 10.30598//ijcr.2021.9-mul 53 Geometry optimization of the five myristicin derivative compounds was carried out to produce the best and stable structure. The molecular structure model of five myristicin derivative compounds is indicated by atomic number, atomic symbol, numbering, and charge. This is done to distinguish the atoms bound in the molecule. The results of modeling five myristicin derivative compounds can be seen in Figure 2. The bonds between each atom in myristicin derivative molecules are caused by interaction between the valence electrons in each atom. This interaction will affect the strength of the bonds in the molecule. The factorsinfluencing the interactions between atoms in a molecule are electronegativity and electron affinity (Tahir, Wijaya, & Bambang, 2003). By using DFT (density functional theory), the optimization of the geometric structure of the five myristicin derivative compounds is determined through computational simulations. Compared with other myristicin derivative compounds, the M3 compound has the best structure, with total energy is 115.701 (kcal/mol), as shown in (Table 2). The total energy and heat of formation are the most important parameters in determining how much energy is needed in determining the most optimal structure with the smallest or close to zero energy (Ismiyarto et al., 2009). Quantitative Relationship Study of Activity Structure Through the quantitative relationship of activity structure (QSAR) study, the antioxidant biological activity of myristicin derivatives was determined by computational simulations. The study of the structure of antioxidant activity can be described quantitatively by calculating the structure of the compound under investigation. Descriptors were selected to produce myristicin derivative compounds' physical and chemical properties (Adhikari, Halder, Mondal, & Jha, 2013). Electronic descriptor calculations can be done using the DFT method. The computationally calculated electronic descriptor produces data in HOMO energy, LUMO energy, dipole moment (Table 3), and net atomic charge (Table 4). The dipole moment is related to the polarity of the myristicin derivative molecule, where the highest polarity is in the M3 compound, about 4.6800676 D. The orbitals for electronic excitation, involve the HOMO and LUMO. Electron excitation from HOMO to LUMO has a certain distance and requires energy, which can be measured from the energy difference between the HOMO and the LUMO. Table 4.Results of Determination of the Equation Model Compound Code Log P Log Ppredictions M1 3.97 0.5473343 M2 1.69 -1.4581628 M3 1.53 -1.6915776 M4 1.53 -1.7468346 M5 1.53 -2.3486929 This energy is called the Gap Energy (ΔEG), and the unit is eV. Gap energy is related to the stability and reactivity of the molecule, stability and reactivity can be seen through the energy difference (Špirtović- Halilović et al., 2014). produce data in the form of HOMO energy, LUMO energy, dipole moment. The less stable and more reactive Myristicin derivatives compound in this research is M4.The M4 has ΔEG of about 0.08026 eV. This result is because the molecules with a small ΔEG value are reactive and less stable. After all, they require less energy when an exciting electron from HOMO to LUMO. Meanwhile, the derivative compound that more stable and less reactive is M5. M5 hasthe largest ΔEG, about 0.12304 eV. The compound has the highest ΔEG, the more stable and less reactive. This condition because it requires a large amount of energy to exciting electron from HOMO to LUMO. The electronic descriptors of the atomic charge are essential in determining the electronic interactions between atoms in molecules that are bonded to one another. This interaction will involve the electrons in the atom joining each other, thus affecting the charge value of each atom. The difference in charge values is influenced by the transfer of electrons to each atom attached to the molecule, the atomic charge can be seen in (Table 3). The log P value is related to the compound's polarity (water solubility), which indicates the distribution of antioxidant compounds in the human body after consumption. The good biological activity log P, is solubility in water and difficult to penetrate the lipid membrane at0