Docking Study, ADMET Profiling of the Designed  

3-Chlorobenzo[b]thiophene-2-Carbonyl Chloride Derivatives:

Promising Anti-Breast Cancer Activity

 

Mohammed F. Al-Owaidi, Monther F. Al Ameri

Department of Pharmaceutical Chemistry, College of Pharmacy,

Mustansiriyah University, 10002, Baghdad, Iraq.

 

ABSTRACT:

Globally, breast cancer accounted for approximately 700٫000 deaths in 2020. Estrogen receptor alpha (ERα) is the primary pathway for breast cancer treatment. Tamoxifen (TAM) is the most extensively used drug for estrogen receptor (+) breast cancer. However, it is implicated in endometrial carcinoma, pulmonary thrombus, stroke, and breast cancer resistance. This research aims to overcome these issues in selectivity and side effects. The study was conducted in a new drug design using Structure Based Drug Design (SBDD) approach, molecular docking with ERα and then predicting their ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) profile. GOLD (Genetic Optimization for Ligand Docking, v.5.7.1), SwissADME and BIOVIA Discovery Studio Visualizer 2020 applications used for the predicting and analyzing of the results. It has shown that all of our compounds (MFA1-8) where a higher PLP (the Piecewise Linear Potential) fitness scores with a range (66.21-77.20) than (60.96) for TAM with different molecular interactions such as H- bondings and non-covalent hydrophobic interactions with the pose. They were all exhibited better conformation to prevent helix-12 (H-12) from repositioning over the opening of the binding pocket. This work generated fresh insight into the significant hydrophobic bonding with LEU428. MFA1-8 showed better pharmacokinetics, drug-likeness, and toxicity profiles than TAM. These findings suggest that these novel 3-chlorobenzo[b]thiophene-2-carbonyl chloride derivatives could serve as the lead compounds to fight breast cancer by inhibiting the ERα pathway.

 

 

 

1. INTRODUCTION: 

1.1. Overview:

Cancer is one of the most critical threats to human health in the world, and the clinical prognosis remains relatively poor. According to WHO, cancer is the second biggest cause of death worldwide, accounting for 10 million fatalities in 2020.^1,2  Breast cancer was affected 2.3 million women globally in 2020, with 685,000 fatalities.²

 

Breast cancer is classified into three significant subclasses based on the availability or lack of molecular markers for estrogen or progesterone receptors and human epidermal growth factor 2 (ERBB2; Erb-B2 Receptor Tyrosine Kinase 2): hormone receptor-positive/ERBB2 negative (70% of patients), ERBB2 positive (15%-20%), and triple-negative breast cancer (TNBC) (tumors lacking all three typical molecular markers; 15%), despite the fact that there is no effective, safe treatment for TNBC.^3,4 Tamoxifen, a selective estrogen receptor modulator, is the most extensively used anti-estrogen adjunct medication for ER-positive women with breast cancer.^5,6 Tamoxifen, a selective estrogen receptor modulator (SERM), was licensed in the 1970s.⁷ It has evident that tamoxifen works as a partial agonist, which increases its affinity to cause endometrial cancer, pulmonary thrombosis, stroke, and its implication in the development of breast cancer resistance.^5,8-10 However, ER remains a therapeutic target in endocrine-resistant breast cancer, as evidenced by the clinical success of fulvestrant, a selective estrogen receptor degrader (SERD) that has been recommended as first-line therapy for metastatic ER+ breast cancer.^11-13

 

With millions of new patients every year, medical research is focused on developing appropriate chemotherapeutic drugs. Nowadays, there is no absolute effective treatment for cancer patients in clinical practice, but chemotherapy is still the most widely used form of treatment for cancer.^9,14 However, most cancers are either resistant to chemotherapy or acquire resistance during treatment. Conceptually, existing chemotherapeutic medicines cannot distinguish cancer cells from normal cells, resulting in therapies that are nearly as dangerous as the disease itself.¹⁵ As a result, designing and discovering new, safe and efficient chemical classes of agents aiming at the treatment and prevention of cancer are the prime targets for contemporary medicinal chemistry researchers.¹⁶

 

1.2. Estrogen receptor and its binding pocket:

The estrogen receptor (ER) is a steroid hormone receptor that contains an N-terminal activation function, DNA-binding and C-terminal ligand-binding domains.¹⁷ In fact, there are three types of estrogen receptors such as ERα, ERβ (similar to ERα in about 95% of DNA-binding domain and 55% in the ligand-binding domain,) and GPER1 (G protein-coupled estrogen receptor 1). ERα has a total length of 595 amino acids and a molecular weight of 67kDa. ERβ is composed of 530 amino acids long and weighs 59 kDa.^18-20 The presence of a positive estrogen receptor (ER) is a common predictor of treatment to endocrine therapy in breast cancer and has been widely employed in the selection of appropriate medication for patients with metastatic disease for the past 20 years.²¹

 

As established, the pocket volume of ER ligand-binding is 450 Å and appropriate for ligands 250 Å-380 Å. Furthermore, the diversity of ER ligand scaffolds reflects the plasticity of ER-LBD and lends itself to the discovery of novel pharmacological modulators. Four cysteines amino acids (381, 417, 447, and 530) in LBD were found to be covalent targets of ERa.^(9,22) The ligand-binding domain (LBD) of the ER is primarily a non-polar cavity made up of helices (H) 3, 6-8, 11, besides 12 residues. The ER helix-12 (H-12) (residues 536–544) is crucial in determining whether a ligand is an agonist or antagonist. The ER agonist, like estradiol forms hydrogen bonds with His524, Glu353, and Arg394, which leads to stabilization of the active position of H-12. H-12 lies over the orifice of the binding pocket that is composed of H-3, H-5/6 and H-11.^5,17,23 On the other hand, when the antagonist 4- hydroxyl tamoxifen [An active metabolite of TAM, 4-OHTAM] binds to the ER LBD, this would inevitably obstruct the co-activator recognition region, producing antagonist action.^5,24 Once 4-OHTAM is bound, there is no hydrogen bonding with His524 of H-12. This could be explained by the steric feature of TAM that precludes the ligand from its cognate receptor and, hence prevents H-12 from repositioning to adopt an agonist-like shape.^5,17 It could argue that the protruding of the steric ligand from its binding pocket between H-3 and H-11 is the general stigma to the anti-estrogenic effect of steroidal and non-steroidal compounds.²⁵ According to the interactions inferred from the X-ray structure, it has been shown that 4-OHTAM can make hydrophobic connections with the butenyl group and aromatic rings, positive ionizable interaction with the 3̊ amine nitrogen, and H- bond interactions with the phenoxy and hydroxyl oxygens.⁵ (Figure. 1)

 

 

Figure 1: X-ray derived structure (PDB code: 3ERT) of 4-OHTAM showing pharmacophoric-molecular modelling with ERα. Hydrophobic (depicted in red), ionizable (encircled with yellow), hydrogen bond donor and acceptor interactions (blue and green arrows).⁵

 

2. METHODOLOGY:

2.1. Computer system and software:

The attributes of a computer system (HP) that used for docking research are Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz, 1.80 GHz, 8.00 GB RAM, running on Windows 10 Pro operating system. CCDC GOLD (v.5.7.1) is wholly licensed and installed. This process used 3D conformations, which achieved by the ChemDraw-16 program of the Chem Office software package (Chem Office, 2016). Chemical Book software used for preliminary docking study. Discovery Studio Visualizer (DSV) 2020 software used to analyze the results. SwissADME online software used to predict the ADMET profile of the investigated compounds.

 

 

2.2. Pharmacokinetics, drug-likeness and toxicity study:

All investigated eight molecules submitted to Swiss ADME assay (www.swissadme.ch) via converting their drawing chemical structures, drawn by chemAxonʼs Marvin JS, to the corresponding Smile format to assess the potential pharmacokinetic properties, drug-likeness and toxicity profile.

 

2.3. Ligand/receptor preparation and molecular docking protocol:

In terms of ligands preparations, the chemical structure of the compounds correctly sketched using Chem3D Pro 12.0 software. Subsequently, the energy calculated and minimized using MM2 minimize and MM2 dynamic options, respectively. Furthermore, regarding the receptor refinement, the crystal structures of Human Estrogen Receptor (ER) Protein (PDB code: 1ERE, resolution: 3.10 Å, R-Value Free: 0.251, R-Value Work: 0.218) with suitable experimental parameters obtained from the protein data bank (PDB) website (https://www.rcsb.org/), ²⁵ which transferred to the Hermes module of GOLD (v.5.7.1) (Genetic Optimization for Ligand Docking). The receptors compiled before the docking process by adding polar hydrogen atoms to achieve specific ionization and tautomeric positions of amino acid residues. After that, crystallographic water molecules that are not implicated in the binding of the ligand to the active site were expelled. Finally, extracting the original ligands from the receptor active sites accomplished.

 

Concerning the molecular docking protocol, the CCDC GOLD suite's Hermes visualizer program is used to set up the receptors in the docking process. The active sites determined using the interaction locations of the original ligands. All of the protein residue characterize within the (10 A°) of the typical ligands for the docking process. The ligands uploaded to Herms using mol format. The number of positions was ten, with the top-ranked solution being the default and the early termination option disabled. As a configuration template, chemscore kinase employed. The piecewise linear potential (PLP) function is used in the scoring function. Finally, the results saved as mol.2 files. The PLP scoring system gives information about the most effective binding method, the binding free energy and docked postures. DSV software used for the interpretation of the results. Consequently, PLP outcomes meticulously examined to determine our proposed ligand affinity and interaction with the ER's amino acid residues.

 

3. RESULT AND DISCUSSION:

3.1 Structure Design:

All eight candidates were designed using a Chemical Book website. The preliminary structures of Chemical book software were manipulating depending on the GOLD software using our knowledge in the structure of the receptor (ER-α) and the most recent researches.^26-29 From the above, we concluded that the best spacer is ethylene diamine to accommodate the better direction to the warhead group inside the binding pocket. The warhead group was either 2-Azetidinone or thiazolidinone to provide hydrophilic and hydrophobic interaction with the pose. Finally, the para substituted phenyl ring was added to the structure to keep the polyaromatic nature of the designed compounds as the established drugs SERM (raloxifene and Arzoxifene) (Fig. 2).

 

 

Fig. 2. Structure Based drug design (SDBB) of the target compounds

 

3.2. Retrosynthetic analysis:

To achieve the recognizable starting materials, the retrosynthetic pathway of compounds MFA1-8 explored. In step I, there was disconnecting amide, sulfide and carbon-carbon bonds, which ended with two commercially available compounds; ethyl thioglycolate and acetyl chloride.³⁰ By continuing the disconnecting approach, in step 2, another amide bond cleaved to yield a commercially available 3-chlorobenzo[b]thiophene-2-carbonyl chloride. In the final step, i.e. step 3, imine disconnected to primary amine and aldehyde derivatives. Both ethylenediamine and benzaldehyde derivatives are cheap and often available in the market (Scheme 1).

 

Scheme 1: Retrosynthetic analysis of compounds MFA1-8.

3.3 Chemical synthesis:

It has shown that our compounds (MFA1-8) can be synthesized starting with recognizable and cheap starting materials. The reaction can be started between ethylenediamine and benzaldehyde derivatives to form the Schiff base. Then, the Schiff base products can be hybridized with 3-chlorobenzo[b]thiophene-2-carbonyl chloride scaffold through a nucleophilic attack to create amide derivatives. After that, these hybrid molecules can be cyclized through a cycloaddition reaction with either ethyl thioglycolate or acetyl chloride to form thiazolidinone derivatives (MFA1-4) and 2-azetidinone derivatives (MFA5-8), respectively (Table 1).

 

 

Table 1: Chemical structures and their molecular weight of MFA 1-8

Codes	Thiazolidinone based cpds.		Codes	2-Azetidinone based cpds.
	Structures	m.wt (g/mol)		Structures	m.wt (g/mol)
MFA1		446.97	MFA5		414.91
MFA2		451.39	MFA6		419.32
MFA3		430.97	MFA7		398.91
MFA4		461.94	MFA8		429.88
cpds: compounds; m.wt: molecular weight

 

3.4 Molecular docking and virtual screening:

There is much information that can conclude from GOLD (v.5.7.1) docking software. It provides information such as the hydrogen bonding and the distance between the pose and ligand, the short contact interaction, binding energy, selectivity to the specific protein (PDB code: 1ERE); as well as, the inhibitory activity of ligands through the PLP fitness score. This means the higher the PLP fitness score, the more selective ligand with a higher inhibiting activity compared to the reference compound TAM. Two main factors determine the effectiveness of a ligand to inhibit the ERα, such as fitted to the pharmacophore and the size of the ligands.

 

 

In terms of pharmacophore fitness of ligands, the current study found that all of our compounds, MFA1-8, show a better pharmacophore fit score than the reference TAM. This could explain by that our compounds have higher affinity to bind with the receptor via accommodating their structures perfectly inside the receptor. The PLP fitness scores are ranging from 66.21 to 77.20 compared to 60.96 for the TAM, with a distance almost equal to 3 Å. MFA1 and MFA5 show H- bonding with THR347. By contrast, MFA2 and MFA3 make H- bonding with MET343, which is in agreement with the previous docking studies with oxadiazole derivatives.³¹ In addition, our finding shows that MFA4 can form an H-bond interaction with ILE424. On the other hand, our ligands perform numerous hydrophobic contacts with different amino acids in coincidence with another finding of the ability of these amino acids to form hydrophobic interactions with ligands as shown in Table 2.^32,33 The most important thing is that all our ligands do not make H- bonding with His-525 of H-12, which could argue that our ligands accommodated perfectly to antagonize the ERα via preventing H-12 from making a lid over the opening of the binding pocket.²⁵ Additionally, one unanticipated finding was that there was no binding between vital ERα activation residue Lys-362 and our ligands, which could explain the higher inhibitory docking score compared to the reference.³⁴ In terms of ligands MFA6-8, there were only hydrophobic bondings with LEU428, LEU384 and MET421. This result may be explained by the fact that the lipophilic nature of ERα and unexpectedly the essential binding with LEU428 for the inferior antagonism feature for the MFA6 and, in particular, MFA7.

 

Table 2: PLP fitness score and their interactions with amino acids in the pose for new 3-chlorobenzo[b] thiophene-2-carbonyl chloride derivatives (MFA1-8) docked with 1ERE using GOLD and DSV.

Compounds	PLP fitness score	Amino acids incorporated with H- bonding	Amino acids incorporated with Short contact interactions
MFA1	69.17	THR347	LEU384, PHE404, GLU353, LEU387, LEU346, MET343
MFA2	69.20	MET343	ILE424, LEU428, MET421, ILE424, MET343, LEU346, HIS524, PHE404, LEU387
MFA3	72.06	MET343	LEU428, PHE425, ILE424, MET421, LEU387, LEU346, PHE404, MET343
MFA4	66.21	ILE424	GLU353, MET421, GLY521, MET388, PHE404, LEU387, MET343, LEU346, LEU525
MFA5	70.41	THR347	LEU428, MET343, LEU387, LEU346, PHE404, MET421, PHE425, ILE424
MFA6	74.70	Note available	LEU428, LEU384, PHE404, GLU353, LEU378, LEU428, ILE424, LEU346, PHE425, MET421, MET343
MFA7	77.20	Note available	LEU428, PHE404, LEU387, PHE425, ILE424, MET421, MET343, LEU346
MFA8	71.30	Note available	MET421, LEU525, GLY521, LEU346, LEU387, PHE404
TAM	60.96	GLU353	ILE424, MET424, LEU525, MET343, LEU346, LEU387, PHE404, MET388, MET421, ILE424

In the case of the size of ligands, it is generally acknowledged that the large size of ERα gives flexibility in designing new antagonizing ligands. It has shown in the figures below (Figures 3 and 4) compared to the reference (Figure 5) that our compounds (selected data) are large enough to accommodate their cognate receptor. However, they are sterically large to prevent helix-12 from repositioning over the opening of the binding pocket.³⁵ It could argue that our ligands pendant from the receptor could occur only through the displacement of H-12 and hence protruding them from the binding cavity between H-3 and H-11.

 

 

Figure 3: 3D structure of MFA1 and its receptor showing the helices H-3 and H-11 that composed the binding pocket with its displaced H-12, using BIOVIA Discovery Studio Visualizer 2020 for this analysis.

 

 

Figure 4: 3D structure of MFA7 and its receptor showing the helices H-3 and H-11 that composed the binding pocket with its displaced H-12, using BIOVIA Discovery Studio Visualizer 2020 for this analysis.

 

 

Figure 5: 3D structure of TAM and its receptor showing the helices H-3 and H-11 that composed the binding pocket with its displaced H-12, using BIOVIA Discovery Studio Visualizer 2020 for this analysis.

3.5. In‑silico pharmacokinetics, drug-likeness and toxicity profile:

It has demonstrated that the antagonistic response of an inhibitor to an enzyme or a protein receptor does not guarantee its usefulness as a potential drug.³⁶ As a result, pharmacokinetics, drug-likeness and toxicity profile are critical in drug discovery and development, as they aid in making a sensible prediction on whether or not inhibitors can be delivered to a biological system.³⁷ What stands out on the table is that most of the compounds are absorbed orally, and at the same time, their lipophilicity is enough to prevent them from crossing the blood-brain barrier; hence it would expect that all the compounds exert no effect on the brain. Furthermore, the interesting about the data in this table is that all the compounds obey Goes, Veber, similarly, the Lipinski rule of five, which states: a molecule or inhibitor can be orally absorbed/active if (2) or more of the following thresholds are met: (Mw) <500, LOGP ≤ 5, number of hydrogen bond acceptors (nHBA) ≤10, number of hydrogen bond donors (nHBD)≤ 5, and topological polar surface area (TPSA) ≤ 40 A.^31,38 According to the aforementioned, all compounds met all the criteria of Lipinski and other related rules (Goes & Veber) which could give these compounds a step forward to be a suitable drug candidate.

 

What is more, both PAINS and BRENK filtered used to assess the selectivity and the toxicity issues. In fact, PAINS- Pan-Assay Interference Compounds- is a filter to eliminate the false positive drug candidate that works not selectively on their biological target.³⁹ Whereas, BRENK filters out unnecessary functionality due to possible toxicity or poor pharmacokinetics.(40) It has shown the designed compound MFA1-8 were almost met PAINS and BRENK filters with the exception of MFA4 and MFA8 because they have N-O single bond in their structures. (Table 3)

 

To sum up, in comparison to the reference (TAM), our compounds are inferior in pharmacokinetics, drug-likeness and medicinal chemistry properties.

 

Table 3. Pharmacokinetics, Drug likeness and medicinal chemistry Profile of the investigated compounds and the reference TAM.

Codes	Pharmacokinetics			Drug likeness                                                       Medicinal Chemistry
	GI absorption	BBB permeant	nHBA:nHBD	Lipinski	Goes	Veber	%F	PAINS	Brenk
MFA1	High	No	3:1	Yes	Yes	Yes	0.55	0	0
MFA2	High	No	2:1	Yes	Yes	Yes	0.55	0	0
MFA3	High	No	2:1	Yes	Yes	Yes	0.55	0	0
MFA4	Low	No	4:2	Yes	Yes	No (1)a	0.55	0	(1)b
MFA5	High	No	3:1	Yes	Yes	Yes	0.55	0	0
MFA6	High	No	2:1	Yes	Yes	Yes	0.55	0	0
MFA7	High	No	2:1	Yes	Yes	Yes	0.55	0	0
MFA8	High	No	4:2	Yes	Yes	Yes	0.55	0	(1)b
TAM	Low	No	2:0	Yes (1)c	No (1)d	Yes	0.55	0	(1)e

Note: the number between two-bracket ( ) refers to the number of violations.

^a: TPSA>140;^b: Oxygen- nitrogen single bond;^c: mLog P> 5; ^d: WLogP> 5;^e: Stilbene like structure

Abbreviation:

GI: Gastro-Intestinal; BBB: Blood-Brain Barrier; n: Number; HBA: Hydrogen Bond Acceptor; HBD: Hydrogen Bond Donor; PAINS: Pan-Assay Interference Compounds, TAM: Tamoxifen.

 

4. CONCLUSION:

This study has set out to design, molecular modelling and ADMET profile for the new 3-chlorobenzo[b]thiophene-2-carbonyl chloride derivatives. All eight design candidates identified using GOLD molecular modeling and ADMET profiling. The investigations have shown that our compounds have either hydrogen bonding and/or hydrophobic non-covalent interactions with their pose. They have a higher PLP fitness score and better ADMET profile than tamoxifen. It has been argued that these compounds offer a better mechanical blocking to the binding pocket with better H-12 displacement. Furthermore, it has shown that the methyl substitution compounds (namely, MFA3 and MFA7) have a higher fitness score with better conformation. These compounds are selected for chemical synthesis and biological evaluation and perhaps for the targeted hits optimization for future development of 3-chlorobenzo[b]thiophene-2-carbonyl chloride derivatives as a potential anti-breast cancer activity with superior ADMET profile and lowest side effect.

 

5. CONFLICTS OF INTEREST:

The authors declare no conflict of interest.

 

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Accepted on 19.08.2022        © RJPT All right reserved

Research J. Pharm. and Tech 2023; 16(2):901-907.