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Anti Cancer Activity of Some Novel Quinazoline Derivatives

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Published: Wed, 16 May 2018

Abstract

At present, the criteria used to select finest novel anticancer drug candidates include inhibitors of cell proliferation, necessary reaction and pathways in cancerous cells. In silico advance resulting in the identification of essential reactions and pathways spreads across several parts of metabolism. The aim of our study is to study the interaction of quinazoline derivatives with 8 selected anticancer drug target enzymes in Silico molecular docking approach. Results of our study suggested that molecular docking approach could be a potential tool to identify the hydrogen bond interactions and the molecular mechanisms of diseases. It was concluded that quinazoline derivative would be of potent drug targets to treat various cancers based on the docking approach.

Keywords: Cancer, Quinazoline, Hydrogen Bond

INTRODUCTION

Biomedical research has complete spectacular strides during the long-ago century. The efforts of researchers in both the public and private sectors have helped to build up new drugs to treat diseases that had stuck apprehension and dread into the lives of people. This biomedical research can be divided into two components, i.e. drug discovery and drug development [1]. In the field of molecular modeling, docking is a method which predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex. Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using for example scoring functions [2].

The plan of this study was to identify a lead molecule that could be used to further evaluate as targets for cancer chemotherapy and tuberculosis to provide a starting point for lead optimization and preclinical drug development. Using molecular modeling and fragment-based design, de novo design strategies as well as known pharmacophores, which have shown promise against other kinase targets. To further validate the lead compound, it was subjected to several cell-based assays in which it exhibited activity in the mid to high micromolar range. These results suggest that the lead compound has effectively hit the intended cellular targets; however, that lead optimization will be required to produce a more drug like inhibitor, which possesses biological activity at clinically relevant concentrations. Therefore, our approach has successfully generated a potent compound from which a larger drug discovery effort can be implemented.

Neuronal acetylcholine receptor subunit alpha-3is aproteinthat in humans is encoded by theCHRNA3gene. This locus encodes a member of the nicotinic acetylcholine receptor family of proteins. Members of this family of proteins form pentameric complexes comprised of both alpha and beta subunits. This locus encodes an alpha-type subunit, as it contains characteristic adjacent cysteine residues. The encoded protein is a ligand-gated ion channel that likely plays a role in neurotransmission. Polymorphisms in this gene have been associated with an increased risk of smoking initiation and an increased susceptibility to lung cancer [3].

Basic fibroblast growth factor, also known asbFGF,FGF2orFGF-β is a member of thefibroblast growth factorfamily. The protein encoded by this gene is a member of the fibroblast growth factor (FGF) family. FGF family members bind heparin and possess broad mitogenic and angiogenic activities. This protein has been implicated in diverse biological processes, such as limb and nervous system development, wound healing, and tumor growth. The mRNA for this gene contains multiple polyadenylation sites, and is alternatively translated from non-AUG (CUG) and AUG initiation codons, resulting in five different isoforms with distinct properties. The CUG-initiated isoforms are localized in the nucleus and are responsible for the intracrine effect, whereas, the AUG-initiated form is mostly cytosolic and is responsible for the paracrine and autocrine effects of this FGF [4].

Telomerase reverse transcriptase(abbreviated toTERT, orhTERTin humans) is a catalytic subunit of theenzymetelomerase, which, together with thetelomerase RNA component(TERC), comprises the most important unit of the telomerase complex. Telomerases are part of a distinct subgroup of RNA-dependent polymerases. Telomerase lengthens telomeres inDNAstrands, thereby allowing senescentcellsthat would otherwise become postmitotic and undergoapoptosisto exceed theHayflick limitand become potentially immortal, as is often the case with cancerous cells. To be specific, TERT is responsible for catalyzing the addition ofnucleotidesin a TTAGGG sequence to the ends of achromosome’stelomeres.This addition of repetitiveDNA sequences prevents degradation of the chromosomal ends following multiple rounds of replication. hTERT absence (usually as a result of achromosomalmutation) is associated with the disorderCri du chat [5].

Fibroblast growth factor 4is aproteinthat in humans is encoded by theFGF4gene.The protein encoded by this gene is a member of thefibroblast growth factor(FGF) family. FGF family members possess broadmitogenicand cell survival activities and are involved in a variety of biological processes including embryonic development, cell growth,morphogenesis, tissue repair, tumor growth and invasion. This gene was identified by its oncogenic transforming activity. This gene andFGF3, another oncogenic growth factor, are located closely on chromosome 11. Co-amplification of both genes was found in various kinds of human tumors. Studies on the mouse homolog suggested a function in bone morphogenesis and limb expansion through the sonic hedgehog (SHH) signaling pathway [6].

MATERIALS AND METHODS

TOOLS AND DATABASE ARE USED

LITERATURE COLLECTION

  • NCBI -PMC, Pubmed, and OMIM

PROTEIN SEQUENCE RETRIEVAL SYSTEM

  • NCBI and Microbial Genome Database

PROTEIN MODELING

  • CPH 3.0 model server

MOLECUALR VISUALIZATION TOOLS

  • Discovery Studio Software
  • Molsoft Software

CHEMINFORMATICS

  • Online smiles translator

MOLECULAR DRUG DOKING

  • Patchdock

METHODS

Literature Collection

The molecular details (literature) of Akpkuptonuria were collected using online digital libraries and literature databases like OMIM, NCBI – PUBMED and PUBMED Central database.

Sequence Retrieval System

The protein sequence of CHRNA3 (Cholinergic receptor nicotinic alpha 3), FGF2 (Fibroblast growth factor 2), TERT (Tolomerase reverse transcriptase) and FGF4 (Fibroblast growth factor 4) were retrieved from the NCBI and MBGDB in order to perform protein sequence analysis and modeling.

Cheminformatics

Chemical compound identification

The potential chemical inhibitors of Anti cancer were selected using NCBI –Pubchem compound chemical database and 2D converted into 3D using ONLINE SMILES TRANSLATOR tool.

Drug designing and Docking

The synthesized chemical molecules are combined with the potential agents (CHRNA3, FGF2, TERT and FGF4) using an automated molecular docking server patch dock.

EXPERIMENTAL WORK

Quinazolines and their derivatives are building block for approximately 150 naturally occurring alkaloids isolated from a number of families of the plant kingdom, from microorganisms and animals and are now known for a wide range of biological properties1-8including anti-inflammatory, anti-tumoral anticonvulsant, hypnotic, sedative, antibacterial, antidiabetic, and several other useful and interesting properties. Quinazolines are one of the most active classes of compounds possessing a wide spectrum of biological activity. They are widely used in pharmaceuticals and agrochemicals [7-12]. The quinazoline antibacterials have emerged as an area of immense interest because of their broad spectrum of in vitro activity and there in vivo chemotherapeutic efficiency.

The rapid rise in bacterial resistance to the traditional antibiotics such as Penicillins and tetracyclines has encouraged a continuing search for new classes of compounds with novel modes of antibacterial activity. Further derivatives of quinazolines are of considerable interest because of their pharmacological properties such as protein tyrosine kinase inhibitor, cholecystokinin inhibitor etc.

TABLE 1. LIST OF COMPOUNDS TO BE DOCKED

RESULT AND DISCUSSION

TABLE 2. MOLECULAR DRUG DOCKING STUDIES – PACTHDOCK RESULTS

S.No

Types of Cancer

Q1

Q2

Q3

Q4

Q5

Q6

Standard

1

Lung cancer

-135.55

-449.89

-496.48

-398.67

-467.16

-427.28

-251.53

2

Breast cancer

-115.64

-284.41

-282.13

-253.39

-300.24

-278.11

-343.23

3

Blood cancer

-90.10

-294.23

-335.83

-325.74

-266.59

-237.78

-284.26

4

Stomach cancer

-93.99

-150.29

-160.32

-149.52

-168.35

-178.05

-116.04

 

SUMMARY AND CONCLUSION

The present study was carried out with the aim of in-silico studies of anti cancer activity of some novel Quinazoline derivatives.

Lung Cancer (Cholinergic receptor nicotinic alpha 3)

The compounds were screened using High throughput screening, and further subjected to Induced Fit Docking studies. The ligands with good ligand scores of -496.48 Aáµ’. The binding mode of the title compounds with the Cholinergic receptor nicotinic alpha 3 (CHRNA3) inhibitor was clarified by flexible docking method. Thus based on ligand score, glide energy and interaction with residues in the active site of the CHRNA3, compound Q3, Q5, Q2, Q6 and Q4 was found to be more potent inhibitor as they exhibit drug like activity. The entire test Compounds which have highest ligand energy compared to the Standard compounds (Afatinib, -251.53 Aáµ’). All the test compounds are more potent than Standard compounds.

Breast Cancer (Fibroblast Growth Factor 2)

The compounds were screened using High throughput screening, and further subjected to Induced Fit Docking studies. The ligands with good ligand scores of -300.24 Aáµ’. The binding mode of the title compounds with the (Fibroblast Growth Factor 2) (FGF2) inhibitor was clarified by flexible docking method. Thus based on ligand score, glide energy and interaction with residues in the active site of the FGF2, all compound was found to be less potent inhibitor as they exhibit drug like activity. The entire test Compounds which have lowest ligand energy compared to the Standard compounds (Afatinib, -343.23 Aáµ’). All the test compounds are less potent than Standard compounds.

Blood Cancer (Telomerase reverse transcriptase)

The compounds were screened using High throughput screening, and further subjected to Induced Fit Docking studies. The ligands with good ligand scores of -335.83 Aáµ’. The binding mode of the title compounds with the Telomerase reverse transcriptase (TERT) inhibitor was clarified by flexible docking method. Thus based on ligand score, glide energy and interaction with residues in the active site of the TERT, compound Q3, Q4 and Q2 was found to be more potent inhibitor as they exhibit drug like activity. The entire test Compounds which have highest ligand energy compared to the Standard compounds (Barasertib, -284.26 Aáµ’). All the test compounds are more potent than Standard compounds.

Stomach Cancer (Fibroblast Growth Factor 4)

The compounds were screened using High throughput screening, and further subjected to Induced Fit Docking studies. The ligands with good ligand scores of -178.05 Aáµ’. The binding mode of the title compounds with the Fibroblast Growth Factor 4 (FGF4) inhibitor was clarified by flexible docking method. Thus based on ligand score, glide energy and interaction with residues in the active site of the FGF4, compound Q6, Q5, Q3, Q2 and Q4 was found to be more potent inhibitor as they exhibit drug like activity. The entire test Compounds which have highest ligand energy compared to the Standard compounds (Verubulin, -116.04 Aáµ’). All the test compounds are more potent than Standard compounds.

It may conclude that further beneficial pharmacophore modifications in the design of novel quinazoline derivatives may be synthesize by designing novel ligands for therapeutic targets by substituting different functional group and also examine with the help of NMR, MASS and X-ray which provide three dimensional frame works which can analyze structure activity data, can guide the design and synthesis of future potential therapeutic towards other chronic disorder along with in vivo and in vitro model.


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