key: cord-0895023-kogpwwlj
authors: Hariyono, Pandu; Dwiastuti, Rini; Yusuf, Muhammad; Salin, Nurul H.; Hariono, Maywan
title: 2-Phenoxyacetamide Derivatives as SARS-CoV-2 Main Protease Inhibitor: In Silico Studies
date: 2021-12-12
journal: Results Chem
DOI: 10.1016/j.rechem.2021.100263
sha: d817fdadf534466eaa80a9629631129acdbc1966
doc_id: 895023
cord_uid: kogpwwlj

2-Phenoxyacetamide group has been identified as one of markers in the discovery and development of SARS-CoV-2 antiviral agent through its main protease (M(pro)) inhibition pathway. This study aims to study a series of 2-phenoxyacetamide derivatives using in silico method toward SARS-CoV-2 M(pro) as the protein target. The study was initiated by employing structure-based pharmacophore to virtually screen and to select the ligands, which have the best fit score (hits) along with the common pharmacophore features being matched. The result shows that from the 11 ligands designed, four ligands are selected as the hits by demonstrating fit score in the range of 56.20 to 65.53 to the pharmacophore model, employing hydrogen bond acceptor (HBA) and hydrophobic (H) as the common features. The hits were then docked into the binding site of the M(pro) to see the binding mode of the corresponding hits as well as its affinity. The docking results free energy of binding (ΔG(bind)) of the hits are in agreement with the pharmacophore fit score, in the range of -6.83 to -7.20 kcal/ mol. To gain the information of the hits as a potential drug to be developed, the in silico study was further proceed by predicting the mutagenic potency, toxicity and pharmacokinetic profiles. Based on the efficiency percentage, all hits meet the criteria as drug candidates by showing 84-88% leading to a conclusion that 2-phenoxyacetamide derivatives are beneficial to be marked as the lead compound for SARS-CoV-2 M(pro) inhibitor.

Regarding with COVID-19 pandemic, up to September 2021, WHO has been reporting 225,680,357 confirmed cases and 4,644,740 deaths since it was outbreak in early 2020 1. The spread chain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is rapidly circulated inter-human through mouth droplets and also suspectedly by airborne, while no specific antiviral drug has been found to combat the viral replication 2. On the other hand, although vaccination has reached about 40% of the world population, however to date, the herd immunity seems like still a long way to go, especially to the third-fourth world countries 3.

The repurposed drug such as hydroxy-chloroquine, oseltamivir, lopinavir and ivermectin could be lifesaving, however, it is not applicable in some cases having the drug contraindications 4.

Therefore, a specific drug is indispensable to minimize adverse drug reaction as well as to maximize the drug effectiveness.

To tail with the drug specificity, the finding of a new drug has been well-known to do by identifying the molecular targets at the initial step in which protein/ enzyme is one of the targets 5, 6. SARS-CoV-2 is composed by structural proteins (spike, membrane, envelope, capsid, ssRNA) and the non-structural proteins (nsp1-nsp16) with their integrated function to maintain the virus life cycle 7. Main protease (M pro ) is the nsp5 having a function in the polypeptide1a and polypeptide1ab proteolysis to yield various small protein fragments to further be constructed and packed in new virions 8. Therefore, by inhibiting this enzyme, the new virion formation would be canceled leading to a stopped viral replication 9.

During this one year, although it is still less, a series or individual peptidomimetic as well as small organic compounds have been evaluated for their inhibition against SARS-CoV-2 M pro 10. Initial study by Stoermer oxopyrrolidin-3-yl]methyl}but-2-enyl)-l-leucinamide or briefly named as N 3 as a potential SARS-CoV-2 M pro , gave an immense value in the drug design of COVID-19 antiviral agent 12. N 3 is a Michael acceptor peptidomimetic compound, mimicking lopinavir suggested to bind to the M pro active site by interacting with the amino acid residues surround the sub-site11', 1, 2, and 4 (See Figure 1) . The subsite 1 (S1) is surrounded by PRO166, GLU189, THR190, and ALA191, while subsite 2 (S2) is flanked by the catalytic residue HIS41 and CYS145. Subsite 4 (S4) is indicated by SER46, whereas the subsite 1' (S1') is circumscribed by LEU141, ASN142, and GLU166. The most common interactions are hydrogen bond with GLU166, CYS145 and HIS163, supported by an extra-large hydrophobic interaction 13. However, the character of peptidomimetic, which has a high flexibility, could cause its instability during pharmacokinetic steps as well as its pharmacodynamic behavior 14, 15. Therefore, a structural modification could be one of alternatives to improve the drug-like structure properties of this interesting ligand. Figure 1 . The surface binding pocket of SARS-CoV-2 M pro with four subsites (S1', S1, S2 and S4) with their surrounding residues. The pink area is the catalytic dyad, whereas the green areas are the residues that flank the catalytic cavity. Inset is the solid ribbon in combined with CPK model of the M pro protein.

Interestingly, lopinavir is the protease inhibitor of Human Immunodeficiency Virus (HIV) currently repurposed for the treatment of COVID-19 patient 16. This HIV antiviral agent bears 2-phenoxyacetamide group, which is similar to the benzyl acetyl group in N 3 , has been identified as one of the important parts in binding the protease (see Figure 2 ). This scaffold is feasible to be either synthesized or simply purchased from the supplier (Sigma Aldrich) 17-

In this present study, we investigate a series of 2-phenoxyacetamide derivatives using in silico methods toward SARS-CoV-2 M pro as the protein target. The in silico study was initiated by employing structure-based pharmacophore to virtually screen and to select the ligands, which have the best fit score (hits) along with its common pharmacophore features. To avoid the hits potentially to be pan-assay interference compounds (PAINS) compounds, the online filter was conducted. The hits were then docked into the binding pocket of the M pro , to see the binding mode of the corresponding hits as well as its affinity. To gain the information of the hits as a potential drug to be developed, the in silico study was further proceed by predicting their mutagenic potency, toxicity and pharmacokinetic profiles. phenoxyacetamide group, whereas the red dashed circle is benzyl acetyl, which mimics to 2phenoxyacetamide group. 

The PAINS filter was carried out by inputting the SMILES string in the searching machine (https://www.cbligand.org/PAINS/). The prediction was done by clicking the searching machine and the result was obtained by showing whether it passed the PAINS filter 23.

The drug-like structure profile were individually predicted by inputting its SMILES string, which is automatically done by the server. The value of molecular weight (MW), partition coefficient (log P), the number of hydrogen bond donors (HBD), the number of hydrogen bond acceptors (HBA), the number of rotatable bonds and the surface area, were observed and then tabulated 24.

Using the same protocol in Section 2.5, the mutagenic potency of the ligands was represented by the AMES test result. Instead, other parameters such as maximum tolerated dose (human) (hMTD), human Ether-à-go-go-Related Gene (hERG) I inhibitor, hERG II inhibitor, oral rat acute toxicity (log LD 50 ), oral rat chronic toxicity (log LOAEL), hepatotoxicity, skin sensitization, T. pyriformis toxicity, and minnow toxicity represented the toxicity properties of the ligands 24.

Using the same protocol in 2.5, the ADME (absorption, distribution, metabolism, and excretion) profiles of the ligands were predicted. Subsequently, the absorption is influenced by water solubility, Caco2 permeability, skin permeability, P-glycoprotein substrate, Pglycoprotein I inhibitor, and P-glycoprotein II inhibitor, instead of human gastrointestinal absorption. The distribution is represented by VDss (human), fraction unbound (human), blood-brain barrier (BBB) permeability, and central nervous system (CNS) permeability. The metabolism is represented by the CYP2D6 substrate, CYP3A4 substrate, CYP1A2 inhibitor, CYP2C19 inhibitor, CYP2C9 inhibitor, CYP2D6 inhibitor, and CYP3A4 inhibitor. Lastly, the excretion is represented by total clearance and renal OCT2 substrate. The drug-like structure, mutagenic potency, toxicity and pharmacokinetic predictions were carried using pkCSM online tool (http://biosig.unimelb.edu.au/pkcsm/prediction) 24.

As previously published, the pharmacophore model has a pentagon shape which is composed Table 1 whereas the phenoxy phenyl rings are oriented to S1' and S1 for ligand 1 and ligand 6, respectively. In contrast, the S4 is shared by the phenoxy phenyl ring of Ligand 2 dan 3,

whereas the arylamide phenyl rings are oriented to the S1' and S1 for ligand 3 and ligand 2,

respectively. Overall, according to the phenyl ring occupations, the pose of ligand 2 and ligand 6 is similar (oriented to the S4 and S1) instead of the type of phenyl ring is different. The same behavior is also occurred in ligand 1 dan ligand 3, wherein the S4 and S1' are occupied by phenyl ring with a different type of linker.

The lowest G bind (-7.20 kcal/ mol; see Table 2 ) goes to ligand 6, which is contributed by Other docking profiles can be seen in Table 2 , whereas the non-bonding interactions for Ligand 1, 2, and 3 can be seen in Table 3 . Working with enzymatic system, a false-positive result often raises due to some factors. These are covalent modifications, redox effects, chelation, autofluorescence, or degradation, which could be a signal of the false-positive results under in vitro assay condition, which is then called as pan-assay interference compounds (PAINS) 25. Here, the hits were filtered to predict whether they have a potential PAINS property, thus, they should be put beside from the next process. The result shows that no hit is predicted to have this PAINS property, therefore, all hits pass to the next step of the drug-like structure characterization.

Lipinski Rule limits an ideal drug-like structure should have less than 500 Da in molecular weight (MW), partition coefficient (log P) < 5, the number of hydrogen bond donor (HBD) ≤ 5, the number of hydrogen bond acceptor (HBA) ≤ 10, rotatable bonds ≤ 10, and surface area ≤ 140Å [26, 27] . In general, the result shows that all ligands passed the MW, the number of HBD, HBA rotatable bonds, and surface area limitations. Table 3 presents the chalcones with their Lipinski Rule profiles. In general, a chemical's mutagenic properties are usually evaluated using the AMES test [28, 29] . Furthermore, the toxicity to human can be measured using human maximum tolerated dose (hMTD), human Ether-à-go-go-Related Gene (hERG) effect, oral rat acute toxicity (log LD 50 ), oral rat chronic toxicity (log LOAEL), hepatotoxicity, skin sensitization, T. pyriformis toxicity, and minnow toxicity [30] [31] [32] . This hMTD is accepted when the estimated toxic dose threshold in humans is greater than 0.477. hERG I and II represent the potassium channels that mediate the cardiac repolarization in humans. Thus, inhibiting these genes would cause a long QT syndrome development that might lead to a fatal arrhythmia. The in vivo toxicity is frequently expressed by LD 50 value, which can be defined as the lowest dose given to cause 50% death of a group of animals in testing a compound acute toxicity, represented by ORAT (log LD 50 value)

prediction. The safety of drugs to the environment is nowadays a concern. Low environmental damage is demonstrated by the values of T. pyriformis and minnow toxicity to be respectively higher than 0.5 and -0.3

The AMES test indicates that no ligand shows mutagenic effect. Most of the hits have a low maximum dose which is weakly tolerated in humans, except for ligand 3. No hits inhibit the both hERG, except for ligand 6, which inhibits hERG II. Interestingly, all hits exhibit no skin sensitization as well as their hepatotoxicity. The oral rat acute toxicity LD 50 can be grouped as very toxic (≤ 5mg/kg), toxic or moderately toxic (> 5 to < 500 mg/kg), harmful or slightly toxic (>500 to < 2000 mg/kg), and non-toxic (> 2000 mg/kg) [29] . After converting the log ORAT into its antilog, the ORAT value of ligand 1, 2, 3 and 6 are 132, 101, 34 and 478 mg/ kg, respectively. Therefore, ligand 3 show a potential toxic property, whereas ligand 1, 2 and 6

show a potential moderate toxicity. In the chronic toxicities (ORCT), all hits could be categorized as a potential toxic to moderate toxic category. Except for ligand 3, all hits do not demonstrate T. pyriformis toxicity potency, whereas, ligand 2 and ligand 3 show minnow toxicity. Table 5 presents the AMES test result of the hits for mutagenicity prediction along with other toxicity profiles. Table 6 demonstrates that almost all hits are well absorbed through the human intestine with nearer values to 100% into the blood system, except for ligand 3, which only shows 58.026% human intestinal absorption. The water solubility of all hits in general are most likely accepted as their log S value are higher than -4, indicating that it may dissolve readily during the dissolution step. Furthermore, the Caco2 cell model for oral absorption prediction requires value greater than 0.90 [33] . Therefore, except ligand 3, all hits show good human gastrointestinal absorption. The skin permeability of all hits is most likely suitable for the transdermal route because the values are approximately -2.5. A protein transport namely Pglycoprotein (P-gp) is vital during the pharmacokinetics steps, although this could have either benefited and unbenefited therapeutic effect [34] . A drug is supposed to not inhibit P-gp, either P-gp I or P-gp II and in the normal situation, it should not be acting as P-gp substrate either.

According to the prediction, ligand 2 is predicted to act the P-gp substrate, whereas no hits inhibit both P-gp I and P-gp II. Volume of distribution at steady state (VDss) is a parameter in distribution directly proportional with the amount of drug distributed into tissue; the more VD indicates the more amount of tissue distribution, which should be ≥ -0.15. Among the hits, there only ligand 3 do not meet these criteria. The fraction unbound (fu) for all hits are predicted to be < 0.15 except for ligand 2, indicated that there is an interference from the plasma protein on the way of drug to the receptor. The drug distribution is also parameterized for their ability to cross the brain membrane which is important as the compounds may affect the central nervous system (CNS) [35] . The blood-brain barrier (BBB) and CNS permeability are poor when the value < -1 and < -3, respectively. This means that the compound is poorly distributed to the brain and unable to penetrate CNS. From the results, all hits should be carefully managed as there is potential to enter the CNS especially for ligand 1, which can also penetrate BBB. Table 7 presented the distribution profiles of the hits as predicted by software. Biotransformation or metabolisms are also important to indicate good drug-like properties.

Subfamilies of cytochrome P450 namely CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 have been studied playing essential roles in drug biotransformation [36] . Brain and intestines are the most organ, wherein respectively CYP2D6 and CYP3A4 are deposited. They most likely responsible to metabolize the drug in their surrounding areas. Furthermore, when a drug has first-pass metabolism, CYP3A4 is the main metabolizer. In this prediction, neither hits act as the substrate nor inhibitor for CYP2D6. However, ligand 1 and 6 act as CYP3A4 substrates and CYP2C19 inhibitors. Furthermore, except for ligand 3, all hits are likely to inhibit CYP1A2, which should be of concern, when the compound is consumed with other drugs. Interestingly, no hit acts as inhibitor for CYP2C9 and CYP3A4 as presented in Table 8 . Upon metabolism, a drug is removed from the body, which can be indicated from its total clearance associated with the drug elimination rate [37] . On the other hand, OCT2 transporter works by renal up taking the drug from the blood. Most likely, the drug having cationic characters as well as endogenous compound will be prioritized to be removed and cleared from the body [38] . Cimetidine, H2 antagonist, had been studied to inhibit OCT2, thus, it elevates OCT2-dependent renal clearance drugs, which alters the pharmacokinetics and pharmacodynamics profiles. Ligand 3 is predicted to be the fastest compound excreted from the body due to its highest total clearance. In contrast, ligand 2 is the slowest compound to be removed from the body due to its lowest total clearance. However, all hits have low total clearance (log Cl < 0.763), yet, it is generally desirable to develop a drug for oral administration without a high dosage regimen [39] . Interestingly, there is no ligand predicted to act as renal OCT2 substrate, that might be less to undesirable side effects. Table 9 presents the total clearance of all hits that reflects their speed to be eliminated from the body system. 

Structural modification of an existing compound has been applied since long time ago with various reasons [40] . These could be either enhancing the drug activity or reducing the toxicity.

Other reasons could be improving the drug pharmacokinetic profiles or its physical-chemical stability. The chemical structure could be simplified to reduce the cost and time being consumed in the drug synthesis or production. However, this simplification should not extremely change the drug activity, thus, in silico study could be a good starting point to design a drug, which is feasible to be synthesized, while maintaining its pharmacophore features.

In this study, a series of 2-phenoxyacetamide derivatives has been designed as SARS-CoV-2 M pro inhibitor by considering its synthetic feasibility as well as the pharmacophore features as generated from baicalein, a SARS-CoV-2 M pro inhibitor. 2-phenoxyacetamide could be simply synthesized under acetylation between 2-phenoxyacetyl chloride and aromatic amine [41] or under alkylation of phenol using bromopropionyl chloride [42] . There are 11 2- phenoxyacetamide derivatives designed with mostly having modification at the arylamide phenyl ring. These modifications are carried out by attaching electron withdrawing groups (EWGs) such as Cl, COOH, NO 2 and phenyl in different positions [43] . On the other hand, some electron donating groups (EDGs) such as OH, C 2 H 4 OH and methyl are also implemented [43] . A combination between EWG and EDG, i.e. COCH 3 is also applied. Interestingly, all 11

ligands performed a considerably fit score toward the pharmacophore model with almost no significant difference, except for ligand 1, 2, 3 and 6. The common pharmacophore features are also consistent for all ligands covering 4HBA and 1H features, except for ligand 6 with an extra 1H feature. However, the selected hits are most likely having EWG character than the EDG. Interestingly, the highest fit score goes to the ligand having a combination between EWG and EDG modification at the para position of the arylamide phenyl ring. This group is able to locate the position of both phenyl rings (arylamide and phenoxy) fit to the hydrophobic features, while other hits are only able to fit one hydrophobic feature. Thereby, it increases the fit score. This COCH 3 is also able to maintain the fitting with HBA features as others done.

The docking poses are dealt with the pharmacophore results. The phenyl rings could be a head and tail to nicely sit in the hydrophobic sub-pockets, while either the HBA or HBD interacts with the surrounding residues via H-Bond interactions. A more attention is drawn for ligand 6, in which the COCH 3 at the para position could locate the NH-amide to interact with SER144 at a considerably close distance (2.44 Å). This phenomenon reminds us to the chymotrypsin protease character, in which serine is one of the catalytic triad next to histidine and aspartate, located at the catalytic domain [44] . In the ligand 6's pose, GLU166 could hold the O-amide to let the water attacks the amide bond leading to hydrolysis. This could be the mode of action on how ligand 6 distracts the interaction of M pro with its substrate, thus it acts as a competitive inhibitor. However, an experimental kinetic study should be performed to confirm this.

In the real experiment (in vitro), a drug candidate should be confirmed their true-positive activity by adding detergent (0.01−0.05% Tween-20) [45] . This detergent is purposed to avoid aggregate interference, that sometime/ frequently happen during in vitro enzymatic assay, which could lead to the false-positive result. This positive result could not be due to the enzyme-tested compound chemical interaction, but rather to compound's aggregation, that buries the enzyme's binding pocket leading to a false-positive result. A number of compounds have been identified to be a potential PAINS compounds such as toxoflavine, isothiazolone, curcumin, hydroxyphenyl hydrazone, ene-rhodanine, and phenol-sulphonamide [25] . This work surely increases the time and cost of experiment because the tested samples could be thousands or even more. Therefore, the development of PAINS filter using online tool is a great innovation to reduce time and cost of research.

The efficiency of hit to be developed as drug candidates are measured by calculating the efficiency in each parameter, employing drug-like structure, toxicity, absorption, distribution, metabolism and excretion. These are calculated by dividing the number of permitted criteria over the total number of criteria, and then multiplied by 100 to obtain an efficiency percentage.

For example, the toxicity in Table 5 , ligand 1 showed seven of 10 criteria, which passed the mutagenicity and toxicity requirement, therefore, it is calculated as 70, etc. The efficiency percentages are presented in Table 10 . In the drug-like structure properties, all hits meet 100% of the criteria including MW, log P, HBD, HBA, rotatable bonds and surface area. The mutagenicity and toxicity profiles show 60-70% agreement of all hits with the requirements, whereas the percentages are quite high to meet the absorption criteria. As such, the distribution criteria are 75-100% passed by all hits. Ligand 1 and 6 are taken into account, as these hits could be 43% potentially interfering the CYP activities in drug metabolisms. Interestingly, all hits are fully meeting the excretion criteria. The average of all properties is drawn resulting the efficiency of all hits by 84 to 88% as drug candidates. 1  100  70  100  100  57  100  88  2  100  60  86  75  86  100  85  3  100  60  71  75  100  100  84  6  100  70  100  100  57  100  88 This study is limited by no dynamics behaviour investigated and performed to confirm the stability of the ligand while interacting with the M pro . The post-MD binding energy should be calculated using methods such as Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) or Molecular Mechanics Generalised Born Surface Area (MMGBSA), which is closer to the real condition than the docking energy calculation only. However, due to our limitation, we plan to perform this MD after synthesizing and experimentally testing the potential compound from this study.

A series of 2-phenoxyacetamide derivatives have been designed as SARS-CoV-2 M pro inhibitor by approaching a deal of a feasible synthesis dan a selective pharmacophore. The initial in silico screening selects four hit compounds with four highest fit score with the common pharmacophore features being HBA and H. These hits were further studied for their binding affinity as well as chemical interactions with the M pro binding pocket. The docking result shows an agreement with the pharmacophore study, in which ligand with COCH 3 at para position toward the arylamide phenyl ring, possessing the strongest binding with the M pro as well as with the pharmacophore of such enzyme's inhibitor. The PAINS filter suggests, that all hits do not have a potential aggregation during in vitro assay. The potency as a drug candidate was further evaluated based on drug-like structure, mutagenic potency and toxicity, and ADMET

showing that all hits considerably meet the criteria as a drug candidate, by showing 84-88% efficiency. In conclusion, 2-phenoxyacetamide derivatives are potential to be processed as lead compound for SARS-CoV-2 M pro .

Conceptualization, review and editing, MH; RD; Investigation, PH, NHS, MY; Writing, PH, MH.

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We greatly acknowledge the Scripps Research Institute, PubChem, ACD/Labs, and Dassault Systems for freely providing AutoDock, 3D structure, ACD/ Chemsketch, and Biovia Discovery Studio softwares.

This work was financially supported by Internal Grant with the scheme of Doctoral-Master 

The data soft files are available in this below link, https://drive.google.com/drive/folders/1m6oTtl_kXfyjz4IGt3rypNXO_o8rxl5Y?usp=sharing