IN-SILICO IDENTIFICATION OF NEWER POTENTIAL LEMUR TYROSINE KINASE 3 INHIBITORS FOR THE TREATMENT OF BREAST CANCER

IN-SILICO IDENTIFICATION OF NEWER POTENTIAL LEMUR TYROSINE KINASE 3 INHIBITORS FOR THE TREATMENT OF BREAST CANCER

R. Priyadarsini *, M. Ashokan, N. Bright Lemuel John, R. Harshita, P. Kokila and P. Madhumitha

Department of Pharmaceutical Chemistry, College of Pharmacy, Madras Medical College, Chennai, Tamil Nadu, India.

ABSTRACT: Breast cancer refers to cancer emerging from breast tissue, commonly from the lobules that supply the ducts with milk or from the inner linings of milk ducts. Due to the mutation of DNA or RNA from the normal cells and abnormal genes when inherited, cancer cells are evolved. LMTK3 (lemur tyrosine kinase 3) has emerged as an important player in breast cancer, contributing to the advancement of disease and the acquisition of resistance to therapy through a strikingly complex set of mechanisms. This prompted us to design newer LMTK3 inhibitors as efficient therapeutic drugs for the treatment of Breast cancer. Based on the common pharmacophoric features for the inhibition of LMTK3, a series of leads were designed using computational methods. A virtual library consisting of newly designed 100 molecules as LMTK3 inhibitors was constructed. Based on these facts, a scaffold library has been created with 100 newly designed ligands containing aromatic rings, Imidazole, pyrrole, indole, benzimidazole, morpholine, benzothiazole, pyrazine, quinoxaline, pyridine, indolinone, oxazole, quinolizine as LMTK3 inhibitors. The binding mechanism of newly designed ligands with target enzymes LMTK3 inhibitors was studied using a Autodock tools 1.5.6. The designed compounds were further subjected to optimization by drug likeliness properties and filtered by applying ADMET properties. The newly designed ligands BCI08, BCI19, BCI40, BCI42, BCI44, BCI49, BC150, BCI53, BCI73, BCI88 were found to be highly active hits. These compounds bioactive potential and prospective drug-likeness profile make them promising leads for further experimental research.

Keywords: Breast cancer, LMTK3, ADMET properties, Docking studies

INTRODUCTION: Cancer is one of the major causes of death globally, more than 10 million people die each year. The survival rates depend upon the severity of cancer, and it also plays an immense role in lowering the quality of life. 80% of patients who are suffering from BC are above the age of fifty ^{1, 2}. BC is a prevalent malignancy and has become the second leading cause of cancer death among women globally.

Breast cancer refers to cancer emerging from breast tissue, commonly from the lobules that supply the ducts with milk or from the inner linings of milk ducts. Due to the modification/ mutation of DNA or RNA from the normal cells, cancer cells are evolved.

Moreover, it develops if the immune system is not functioning properly, or the number of cells generated is disproportionate for the immune system to eliminate. Abnormal genes like BRCA1 and BRCA2 when inherited, increases the risk of BC, especially in women who have the gene BRCA, tend to develop BC at early age ³. Furthermore, family history also plays a significant role in the patients with BC (they may have increased possibility of developing BC) ⁴. LMTK3 also contributes to the advancement of breast cancer and the acquisition of resistance to therapy through a strikingly complex set of mechanisms.

This led us to the objective of designing newer LMTK3 inhibitors as efficient therapeutic drugs for the treatment of Breast cancer based on the common pharmacophoric features for inhibition of LMTK3 and thus a series of leads were designed using computational methods. A virtual library consisting of newly designed 100 molecules as LMTK3 inhibitors was constructed and further optimised for ADMET properties.

MATERIALS AND METHODS:

Selection of Target: Protein Data Bank (PDB) is a crystallographic database for three-dimensional structural data of large biological molecules, such as proteins, nucleic acid and complex assemblies. The targets creating the greatest enthusiasm at this time for the treatment of Breast cancer include, LMTK3 inhibitors, HER-2 inhibitors, VEGF Receptor inhibitors, Aromatase inhibitors, GnRH agonist, Selection estrogen receptor modulator and down regulators. While carrying out the literature ^5-11 review, it was found that LMTK3 (PDB ID: 6 SEQ) is emerging as one of the most prominent drug targets in the treatment of breast cancer, thus it was chosen as the target of our study.

LMTK3 (lemur tyrosine kinase 3) has emerged as an important player in breast cancer, contributing to the advancement of disease and the acquisition of resistance to therapy through a strikingly complex set of mechanisms. Although the knowledge of its physiological function is largely limited to receptor trafficking in neurons, there is mounting evidence that LMTK3 promotes oncogenesis in a wide variety of cancers. LMTK3 comes under the Classification: TRANSFERASE and is present in the Organism(s): Homo sapiens.

It has a Resolution of 2.10 Å and RCSB PDB CODE: 6SEQ. While high LMTK3 mRNA expression has been reported to be an independent poor prognostic factor in patients with ERα+BC, immunohistochemistry (IHC) analysis has further revealed that tumours overexpressing human epidermal growth factor receptor 2 (HER2) are more likely to be LMTK3 positive, while triple negative BC (TNBC) tumours have high cytoplasmic expression of LMTK3. LMTK3 is a heat shock protein 90 (HSP90) client protein, requiring HSP90 for folding and stability, LMTK3 inhibitors promotes proteasome-mediated degradation of LMTK3.

Pharmacologic inhibition of LMTK3 decreases proliferation of cancer cell lines in the NCI-60 panel, with a concomitant increase in apoptosis in breast cancer cells, recapitulating effects of LMTK3 gene silencing. Furthermore, LMTK3 inhibition reduces growth of xenograft and transgenic breast cancer mouse models without displaying systemic toxicity at effective doses ¹².

Pharmacophoric Identification: A Pharma-cophore is defined as a set of structural features in a molecule that is recognized at a receptor site and is responsible for that molecule’s biological activity. Hence all these essential chemical features were used as 3D structural query to screen the chemical database for retrieving new potent LMTK3 inhibitors.

Database Screening: Scaffold hopping or chemo type switching is a technology that modifies the chemical scaffold of a bioactive compound retaining the activity and key interaction points, or the interacting molecular fragments of the parent compound.

Virtual Library: When the literature in Scientific journals and research articles were reviewed, compounds containing chemical features involved in hydrogen bond formation such as hydrogen bond acceptor (HBA), hydrogen bond donor (HBD) and hydrophobic interactions such as aromatic ring features were found to be effective agents as LMTK3 inhibitor ^13-22.

It was observed that in docked complex was shown to form a direct hydrogen bond and hydrophobic interactions with the residue of LMTK3. Hence all these chemical features were used as 3D structural query to screen the chemical databases for retrieving and designing novel potent LMTK3 inhibitor. The analogue library was generated by modifying the respective functional groups with sterically and conformation ally allowed substituents.

Lead Optimisation:

Drug Likeliness Screening: Drug likeliness is qualitative concept used in drug design for how drug-like substances is to be an effective drug likeliness property was performed for all the newly designed LMTK3 inhibitors by using different online software like Lipinski's rule of five, Osiris online software, Mol inspiration software and the results were tabulated.

Docking Studies: All the designed ligands were subjected to docking studies using Autodock tools 1.5.6 software and the results were discussed below. Autodock tools 1.5.6 is a molecular modelling simulation, especially effective for protein ligand docking.

RESULTS AND DISCUSSION: In the search of new and potent LMTK3 inhibitors as anti-breast cancer agents, a virtual scaffold library of 100 molecules was constructed using chemsketch and based on the chemical features like hydrogen bond acceptor (HBA), hydrogen bond donor (HBD), hydrophobic (HYP) features which were observed from reviewing literature.

TABLE 1: PHARMACOPHORIC FEATURES USED IN CONSTRUCTION OF LIBRARY OF LMTK3 INHIBITORS

Virtual Library of LMTK3 Inhibitors:

Docking Results:

Docking Studies: Autodock tools1.5.6 is a molecular modelling simulation, especially effective for protein ligand docking. Docking scores of all the newly designed ligands are given in the Table 1.

TABLE 1: LIST OF DOCKING SCORE FOR DESIGNED LMTK3 INHIBITORS (AUTODOCK 1.5.6)

Based on the docking scores of all the 100 newly designed ligands, they are categorized and given below in Table 2. Compounds that are highly active (>-7.5 kcal/mol), moderately active (-6.0 to -7.49 kcal/mol) and Low active (below -6 kcal/mol) are characterized below.

TABLE 2: DOCKING RESULTS OF LMTK3 INHIBITORS USING AUTODOCK TOOLS 1.5.6

Molecular Docking: On the basis of performed docking studies, designed ligands were considered as best hit molecules and their docking interaction snapshots are highlighted below.

FIG. 1: DOCKING STUDIES OF NEWLY DESIGNED LMTK-3 INHIBITORS USING AUTODOCK 1.5.6

Drug Likeliness Screening: The newly designed ligands were subjected to molecular docking, ADMET properties, Lipinski’s rule of five, toxicity prediction. Through this, the newly generated ligands are filtered and refined that constitutes optimization of leads.

Physiochemical Properties: The Lipinski’s rule of five was performed by using Lipinski’s rule of five molecular properties calculator online software i.e., Molinspiration online database. All the newly designed ligands were found to pass the Lipinski’s rule of five and the results were tabulated below.

TABLE 3: LIPINSKI’S RULE OF FIVE FOR THE LMTK3 INHIBITORS

All the newly designed ligands were found to pass the Lipinski’s rule of five and snapshots for the LMTK3 inhibitors are given below,

FIG. 2: PHYSIOCHEMICAL PROPERTIES OF NEWLY DESIGNED LMTK3 INHIBITORS

ADMET Properties: The ADMET results of the selected ligands like BCI08, BCI19, BCI40, BCI42, BCI44, BCI49, BC150, BCI53, BCI73, BCI88 were depicted in the following images.

FIG. 3: BIOLOGICAL PROPERTIES OF NEWLY DESIGNED LMTK3 INHIBITORS

Toxicity Profile: The toxicity profile results of the selected ligands like BCI08, BCI19, BCI40, BCI42, BCI44, BCI49, BC150, BCI53, BCI73, BCI88 were depicted in the following images.

FIG. 4: TOXICITY PROFILE OF NEWLY DESIGNED LMTK3 INHIBITORS

Thus, all newly designed ligands (100 LMTK3 inhibitors) have satisfied all the above filtering method of good predictive activity with good docking scores and also drug likeliness properties confirming that these molecules are accepted to be orally bioavailable.

CONCLUSION: In-silico identification approach has revealed newly designed novel LMTK3 (PDB ID: 6SEQ) inhibitors that can be used in the treatment of breast cancer. Based on the review of literature6-24, the important chemical features required for the inhibition of action of LMTK3 were identified and the 3D structural query of novel 100 heterocyclic ligands were screened to retrieve new potent LMTK3 inhibitors. Drug likeliness of the newly designed compounds was studied with the help of Lipinski’s rule of five and ADMET properties, which assisted us in screening of the non-drug like compounds. Later, the screened drug-like compounds were identified and further subjected to molecular docking study using Autodock1.5.6 software creating a library of novel inhibitors of LMTK3. Hence, we propose that the final hit compounds like BCI08, BCI19, BCI40, BCI42, BCI44, BCI49, BC150, BCI53, BCI73, BCI88 as possible virtual leads and are finally selected for synthesis. Out of 100 newly designed ligands, certain leads containing heterocyclic nucleus such as 4-(phenyl acetamido) substituted imidazole and 5-substitued Indoles can be synthesized and further evaluated for in-vitro and in-vivo anti-breast cancer activity in future.

ACKNOWLEDGEMENTS: We consider this, as an opportunity to express our sincere thanks to The Dean, Our Principal and Our Guide, College of Pharmacy, Madras Medical College, Chennai-03.

Author Contribution Statement: Dr. R. Priyadarsini supervised the project, designed the framework for the entire research work and analysed the data produced throughout the research work.

Mr M. Ashokan, Mr. N. Bright Lemuel John, Ms. R. Harshita, Ms. P. Kokila, Ms P. Madhumitha performed the computations and carried out the research methodology. All authors discussed the results and contributed to the final manuscript.

CONFLICTS OF INTEREST: Conflict of interest declared none.

REFERENCES:

1. Baillache DJ and Unciti-Broceta A: Recent developments in anticancer kinase inhibitors based on the pyrazolo[3,4-d] pyrimidine scaffold. RSC Medicinal Chemistry 2020; 11(10): 1112–35.
2. Łukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. Breast cancer epidemiology, risk factors, classification, prognostic markers, and current treatment strategies an updated review. Cancers 2021; 13(17): 4287.
3. Sharma GN, Dave R, Sanadya J, Sharma P and Sharma KK: Various types and management of breast cancer: an overview. J Adv Pharm Technol Res 2010; 1(2): 109-26.
4. Hartmann LC, Sellers TA, Frost MH, Lingle WL, Degnim AC and Ghosh K: Benign breast disease and the risk of breast cancer. New England Journal of Medicine 2005; 353(3): 229–37.
5. Cilibrasi C, Ditsiou A, Papakyriakou A, Mavridis G, Eravci M and Stebbing J: LMTK3 inhibition affects microtubule stability. Molecular Cancer 2021; 20(1).
6. Vella V and Giamas G: Diving into the Dark Kinome: Lessons learned from LMTK3. Cancer Gene Therapy 2021; 29(8-9): 1077–9.
7. Jiang T, Lu X, Yang F, Wang M, Yang H and Xing N: LMTK3 promotes tumorigenesis in bladder cancer via the ERK/MAPK pathway. FEBS Open Bio 2020; 10(10): 2107
8. Cairns J, Ingle JN, Kalari KR, Shepherd LE, Kubo M and Goetz MP: The lncRNA MIR2052HG regulates ERΑ levels and aromatase inhibitor resistance through LMTK3 by recruiting EGR1. Breast Cancer Research 2019; 21(1).
9. Quereda V, Bayle S, Vena F, Frydman SM, Monastyrskyi A and Roush WR: Therapeutic targeting of Cdk12/CDK13 in triple-negative breast cancer. Cancer Cell 2019; 36(5).
10. Stebbing J, Shah K, Lit LC, Gagliano T, Ditsiou A and Wang T: LMTK3 confers chemo-resistance in breast cancer. Oncogene 2018; 37(23): 3113–30.
11. Krishnan A, Dhamodharan D, Sundaram T, Sundaram V and Byun HS: Computational discovery of novel human LMTK3 inhibitors by high throughput virtual screening using NCI Database. Korean Journal of Chemical Engineering 2022; 39(6): 1368–74.
12. Ditsiou A, Cilibrasi C, Simigdala N, Papakyriakou A, Milton-Harris L and Vella V: The structure-function relationship of oncogenic LMTK3. Science Advances 2020; 6(46).
13. Ortiz MA, Michaels H, Molina B, Toenjes S, Davis J and Marconi GD: Discovery of cyclic guanidine-linked sulfonamides as inhibitors of LMTK3 kinase. Bioorganic & Medicinal Chemistry Letters 2020; 30(9): 127108.
14. Sarma H and Mattaparthi VS: Structure-based virtual screening of high-affinity ATP competitive inhibitors against human lemur tyrosine kinase-3 (LMTK3) domain: A novel therapeutic target for breast cancer. Interdisciplinary Sciences: Computational Life Sciences 2018; 11(3): 527–41.
15. Allam L, Fatima G, Wiame L, Amri HE and Ibrahimi A: Molecular screening and docking analysis of LMTK3 and AKT1 combined inhibitors. Bioinfor 2018; 14(9): 499-03.
16. Anbarasu K and Jayanthi S: Identification of curcumin derivatives as human LMTK3 inhibitors for breast cancer: A docking, dynamics, and MM/PBSA approach. 3 Biotech 2018; 8(5).
17. Sarma H and Kumar Mattaparthi VS: Salient structural features of human lemur tyrosine kinase 3 (LMTK3) domain from molecular dynamics simulation study. Current Biotechnology 2018; 7(4): 309–16.
18. Allam L, Lakhlili W, Tarhda Z, Akachar J, Ghrifi F and Amri HE: Three dimensional structure prediction of the human LMTK3 catalytic domain in DYG-in conformation. Journal of Biomolecular Research & Therapeutics 2017; 06(01).
19. Kumar Mattaparthi VS and Sarma H: Unveiling the transient protein-protein interactions that modulate the activity of estrogen receptor(er)-α by human lemur tyrosine kinase3 (LMTK3) domain: An in-silico study. Current Proteomics 2017; 14(2): 157–64.
20. Anbarasu K and Jayanthi S: Designing and optimization of novel human LMTK3 inhibitors against breast cancer – a computational approach. Journal of Receptors and Signal Transduction 2016; 37(1): 51–9.
21. Jacob J, Favicchio R, Karimian N, Mehrabi M, Harding V and Castellano L: LMTK3 escapes tumour suppressor mirnas via sequestration of DDX5. Cancer Letters 2016; 372(1): 137–46.
22. Xu Y, Zhang H, Nguyen VTM, Angelopoulos N, Nunes J and Reid A: LMTK3 represses tumor suppressor-like genes through chromatin remodeling in breast cancer. Cell Reports 2015; 12(5): 837–49.
23. Xu Y, Zhang H, Lit LC, Grothey A, Athanasiadou M and Kiritsi M: The kinase LMTK3 promotes invasion in breast cancer through grb2-mediated induction of integrin β 1. Science Signaling 2014; 7(330).
24. Asano T, Sato S, Yoshimoto N, Endo Y, Hato Y and Dong Y: High expression of LMTK3 is an independent factor indicating a poor prognosis in estrogen receptor αpositive breast cancer patients. Japanese Journal of Clinical Oncology 2014; 44(10): 889–97.
    

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    How to cite this article:

    Priyadarsini R, Ashokan M, John NBL, Harshita R, Kokila P and Madhumitha P: In-silico identification of newer potential lemur tyrosine kinase 3 inhibitors for the treatment of breast cancer. Int J Pharm Sci & Res 2023; 14(12): 5861-79. doi: 10.13040/IJPSR.0975-8232.14(12).5861-79.

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