Molecular modelling and insilico drug docking studies on breast cancer target protein (TNRC9) using cheminformatics software and tools

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1 Available online at ISSN: INTERNATIONAL JOURNAL OF NOVEL TRENDS IN PHARMACEUTICAL SCIENCES Molecular modelling and insilico drug docking studies on breast cancer target protein (TNRC9) using cheminformatics software and tools RESEARCH ARTICLE Hemalatha.V 1, Sakila.L 2 and Balaji.M 3 1 Post Graduate and Research Department of Zoology, Ethiraj College for Women, Chennai, Tamilnadu, ndia. 2 Associate professor, Post Graduate and Research Department of Zoology, Ethiraj College for Women, Chennai, Tamilnadu, India. 3 Senior Bioinformatician- Akshaya Computational Medicine Pvt, Ltd., Chennai, Tamilnadu, India. Abstract In the world, breast cancer is the fifth most common cause of cancer death. In 2005, breast cancer caused 502,000 deaths (7% of cancer deaths; almost 1% of all deaths) in the world. Among all women in the world, breast cancer is the most common cancer. In this project we model the protein target for breast cancer and design the de novo drug which can be subjected to testing protocols by Clinical Pharmacology departments which would be of immense benefit in the treatment of cancer. Hence by way of our project we model the protein target and the designed drugs act as potential therapeutic agents for Clinical Oncological and Pharmacoinformatics studies. Key words: Protein modelling, drug designing and docking. INTRODUCTION Bioinformatics is the application of computer technology to the management of biological information. Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied to genebased drug discovery and development. The need for Bioinformatics capabilities has been precipitated by the explosion of publicly available genomic information resulting from the Human Genome Project. Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning DNA and protein sequences to compare them, and creating and viewing 3-D models of protein structures. Worldwide, breast cancer is the most common invasive cancer in women. (The most common form of cancer is non-invasivenon-melanoma skin cancer; non-invasive cancers are generally easily cured, cause very few deaths, and are routinely excluded from cancer statistics.) Breast cancer comprises 22.9% of invasive cancers in women [1] and 16% of all female cancers [2]. In 2012, it comprised 25.2% of cancers diagnosed in women, making it the most common female cancer [3]. In 2008, breast cancer caused 458,503 deaths worldwide (13.7% of cancer deaths in women and 6.0% of all cancer deaths for men and women together). Lung cancer, the second most common cause of cancer-related death in women, caused 12.8% of cancer deaths in women (18.2% of all cancer deaths for men and women together). The number of cases worldwide has significantly increased since the 1970s, a phenomenon partly attributed to the modern lifestyles. Breast cancer is strongly related to age with only 5% of all breast cancers occurring in women under 40 years old [4]. There were more than 41,000 newly diagnosed cases of breast cancer registered in England in 2011, around 80% of these cases were in women age 50 or older [5]. To whom correspondence should be addressed: Hemalatha V hemavenu1993@gmail.com VOLUME 5 NUMBER 3 JUN

METHODOLOGY Literature studies First, we collect molecular genetic information related to Human Breast cancer using PUBMED, PUBMED CENTRAL and OMIM.

2 METHODOLOGY Literature studies First, we collect molecular genetic information related to Human Breast cancer using PUBMED, PUBMED CENTRAL and OMIM. Gene Identification Next, based on literature, we identify the potential mutation gene named TNRC9 (TRINUCLEOTIDE REPEAT CONTAINING 9). Sequence retrieval system To retrieve the protein sequence of TNRC9 (TRINUCLEOTIDE REPEAT CONTAINING 9) gene using ENSEMBL GENOME BROWSER in order to perform the protein modelling studies. Protein modelling In protein modelling studies, we use CPH 3.0 Model server and view the structure with the help of molecular visualization tools such as DISCOVERY STUDIO SOFTWARE. Drug selection The literature studies on cancer drugs were done using NCBI PUBCHEM Compound database. Drug designing and validation Using Molinspiration Cheminformatics software, we design the drug candidates and validate those using Cheminformatics protocols. Drug Docking The drug and protein will be docked with the help of advanced and automated molecular drug docking server called PATCHDOCK in order to perform the complete binding affinities between the modelled protein and the De Novo drug. Protein drug binding sites prediction Finally, we evaluate the docking results using molecular tools such as DISCOVERY STUDIO SOFTWARE. RESULTS Table 1. Gene Summary S.No Gene name CHR LOC OMIM PDB Gene ID 1. TNRC9 (TRINUCLEOTIDE REPEAT CONTAINING 9) No Protein sequence MDVRFYPAAAGDPASLDFAQCLGYYGYSKFGNNNNYMNMAEANNAFFAASEQTFHTPSLGDEEFEIPPIT PPPESDPALGMPDVLLPFQALSDPLPSQGSEFTPQFPPQSLDLPSITISRNLVEQDGVLHSSGLHMDQSH TQVSQYRQDPSLIMRSIVHMTDAARSGVMPPAQLTTINQSQLSAQLGLNLGGASMPHTSPSPPASKSATP SPSSSINEEDADEANRAIGEKRAAPDSGKKPKTPKKKKKKDPNEPQKPVSAYALFFRDTQAAIKGQNPNA TFGEVSKIVASMWDSLGEEQKQVYKRKTEAAKKEYLKALAAYRASLVSKAAAESAEAQTIRSVQQTLAST NLTSSLLLNTPLSQHGTVSASPQTLQQSLPRSIAPKPLTMRLPMNQIVTSVTIAANMPSNIGAPLISSMG TTMVGSAPSTQVSPSVQTQQHQMQLQQQQQQQQQQMQQMQQQQLQQHQMHQQIQQQMQQQHFQHHMQQHL QQQQQHLQQQINQQQLQQQLQQRLQLQQLQHMQHQSQPSPRQHSPVASQITSPIPAIGSPQPASQQHQSQ IQSQTQTQVLSQVSIF Fig 1. Protein 3Dimnensional structure prediction (TOX3) ASP,GLU bright red CYS,MET yellow LYS,ARG blue SER,THR orange PHE,TYR mid blue ASN,GLN cyan GLY light grey LEU,VAL,ILE green ALA dark grey TRP pink HIS pale blue PRO flesh Discovery studio software cartoon model view and amino acids residues color. VOLUME 5 NUMBER 3 JUN

labels The above picture represents the red colour indicates helix,green indicates the sheets,and

Protein 3Dimnensional structure prediction (TOX3) Discovery studio software cartoon model

3 Fig 2. Protein 3Dimnensional structure prediction (TOX3) Discovery stuidio software solid ribbon model with labels The above picture represents the red colour indicates helix,green indicates the sheets,and blue indicates the turn and white indicates the coils regions in the TNRC9 protein. Fig 3. Protein 3Dimnensional structure prediction (TOX3) Discovery studio software cartoon model (Hydrobhocity) Fig 4. Protein 3Dimnensional structure prediction (TOX3) Discovery studio software CPK model : Red colour indicates Oxygen,Grey indicates carbon,and Blue indicates Nitrogen. VOLUME 5 NUMBER 3 JUN

Table 2. Drug summary S. NO DRUG NAME CID NO MOL W IUPAC NAME SMILES MOL. FORMULA 1. Melatonin 896 232.

4 Table 2. Drug summary S. NO DRUG NAME CID NO MOL W IUPAC NAME SMILES MOL. FORMULA 1. Melatonin g/mol N-[2-(5-methoxy-1H-indol- 3-yl)ethyl] acetamide COC1=CC2=C(NC=C 2CCNC(C)=O)C=C1 C 13 H 16 N 2 O 2 2. Tramadol HCl g/mol 3. De Novo g/mol Fig 5. Drug designing and validation (1R,2R)-2-[(dimethylamino) methyl]-1-(3-methoxy phenyl)cyclohexan-1- ol;hydrochloride CN(C)CC1CCCCC1(C2 =CC(=CC=C2)OC)O. Cl COC1=CC2=C(NC=C 2CCNC(C)=O)C=C1C N(C)CC1CCCCC1(C2= CC(=CC=C2)OC)O.Cl C 16 H 26 ClNO 2 C 29 H 40 N 3 O 4 Cl 2D structure of (MELATONIN+TRAMADOL) Molecular drug properties score: molinspiration software: (melatonin and tramadol hydrochloride) Fig 6. 3D structure prediction (MELATONIN) Discovery studio software Stick model (Red Oxygen, Grey- Carbon and Blue- Nitrogen.) (melatonin) VOLUME 5 NUMBER 3 JUN

5 Fig 7. Protein 3Dimnensional structure prediction (TRAMADOL) Discovery studio software Ball and stick model Red indicates Oxygen; Grey indicates Carbon, Green indicates Chlorine and Blue Nitrogen. Fig 8. Protein 3Dimnensional structure prediction (DENOVA) Discovery studio software stick model Red indicates Oxygen,Grey indicates Carbon,Green Chlorine and Blue indicates Nitrogen. Table 3. Drug Docking Protein Target Melatonin Tramadol hydrochloride De Novo TOX Table : Drug binding values : (MELATONIN+TRAMADOL) is Fig 9.1. Molecular drug docking Patch Dock results : 1 The above picture represents the drug docking score of (TOX3+TRAMADOL) VOLUME 5 NUMBER 3 JUN

Molecular drug docking Patch Dock results: 3 The above picture represents the

6 Fig 9.2. Molecular drug docking Patch Dock results 2 The above picture represents the drug docking score of (TOX3+MELATONIN) Fig 9.3. Molecular drug docking Patch Dock results: 3 The above picture represents the drug docking score of (TOX3+DENOVA) Fig 12. Molecular Protein-Drug Docking (Discovery studio software) Protein drug complex: yellow stick model view shows (de novo) and cartoon model view shows protein (TOX3+DENOVA). VOLUME 5 NUMBER 3 JUN

protein : wire frame model view and ligand green color.

Molecular Protein-Drug Docking (Molegro Molecular viewer software) Protein (TOX3) shows

7 Fig 12. Molecular Protein-Drug Docking (Discovery studio software) Discovery studio software protein : wire frame model view and ligand green color. Fig 12. Molecular Protein-Drug Docking (Discovery studio software) Discovery studio software protein(tox3) : surface model view and ligand (MELATONIN+TRAMADOL)green color. Fig 13. Molecular Protein-Drug Docking (Molegro Molecular viewer software) Protein (TOX3) shows secondary structure model and drug (MELATONIN+TRAMADOL) shows spacefill model.(protein drug interaction) VOLUME 5 NUMBER 3 JUN

8 DISCUSSION From the protein modelling studies of the present research investigation we retrieved the amino acid sequence of TNRC9 (TRINUCLEOTIDE REPEAT CONTAINING 9) Fig.(1,2,3&4) protein using human genome browser. The total number of amino acids of TNRC9 (TRINUCLEOTIDE REPEAT CONTAINING 9) protein is (576 a a). In protein modelling studies, we used an automated protein modelling server named CPH 3.0 model server. According to Nielsen M et al., 2010, CPH models-3.0 is a web-server predicting protein 3D-structure by use of single template homology modelling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homologymodelling algorithm. A query sequence is first attempted modelled using the fast CPH models-2.0 profile scoring function suitable for close homology modelling. We have used this CPH models-2.0 to convert the TNRC9 amino acids into a 3Dimensional structure. The predicted three dimensional structures is a foundation for structure based drug designing. After modelled the protein we view the detailed 3 dimensional structure using an advanced molecular visualization tool called Discovery studio software Fig (1,2, 3&4). These structures explain the structural and functional regions such as alpha helix, beta sheets, turns and coils (Antigen binding sites) of the TNRC9 protein. This information is very important before docking studies to identify the protein binding sites present in the target protein. Molinspiration is used for complete drug designing and drug validation. In these studies we combine (Tramadol Hydrochloride + Melatonin=denova) in order to inhibit the TNRC9 protein structure in Insilco methods. Fig (6,7and8) represents drug designing and validation. The molecular properties of the de novo drug show that (Mw: and Log p: 4.014). Based on the complete drug likeness score the designed de novo drug obeys the basic rules of drug designing. Molinspiration is developed based on the drug likeness score. Hence the designed de novo drug clear represents that there are no errors present. We try to dock the chemical candidates with the modelled TNRC9 target protein. In Drug docking studies, we use patch dock server in order to bind the modelled protein and the designed drug. The results show a binding value of ( ) of the Target protein with melatonin. Whereas, Melatonin combined with Tramadol hydrochloride shows a binding value of ( ). The results elucidated in Fig (12), show that the designed denovo drug shows a higher binding affinity when compared with melatonin. This findings of the new combination of drug will help the patient to have a quality life for their survival. In this research investigation, we focus on delivering the drug candidate for breast cancer patients both before and after surgery. The designed De Novo drug shows a higher binding affinity when compared with Melatonin. The nature of the designed chemical compound is that it has both anti-oxidant and anti-inflammatory properties. The anti-oxidant property of the drug can be used to reduce the effect of breast cancer in the early stages. Similarly, the anti-inflammatory property of the drug will subside the pain after surgery of patients who have undergone treatment by chemotherapy for breast cancer. Hence, the novel drug has both anti-cancerous and antiinflammatory properties. SUMMARY The principle objective of the present investigation is to find out the highly expressed gene involved in breast cancer. Our aim is to decrease the pain in breast cancer as well as to reduce the growth rate of breast cancer. The genes associated with breast cancer are identified by data mining using various literature databases like PubMed centre &online mendelian inheritance in man(omim). In this project, we found out that genecoded-protein (TNRC9)are the best candidates for drug docking. Drug chemical structure that obey the drug likeness score were produced like melatonin &tramadol hydrochloride. The best drug candidates melatonin& tramadol hydrochloride for the TNRC9was found out using bioinformatics software and tools. We suggest that the designed drug combination melatonin and tramadol hydrochloride for TNRC9 are best candidates for reducing the growth of breast cancer as well as pain based on our binding affinity values. Based on the docking results we find out that the designed chemical structure act as VOLUME 5 NUMBER 3 JUN

9 a potential therapeutic agents of breast cancer. SUGGESTION FOR FUTURE WORK The designed de novo drug can be subjected to testing protocols by Clinical Pharmacology departments which would be REFERENCES 1. World Cancer Report. International Agency for Research on Cancer Breast cance: prevention and control". World Health Organization. 3. World Cancer Report International Agency for Research on Cancer, World Health Organization of immense benefit in the treatment of cancer. So, we finally conclude that the modelled protein target and the designed drugs are potential therapeutic agents for Clinical Oncological and Pharmacoinformatics studies. 4. Breast Cancer: Breast Cancer in Young Women WebMD Nearly 85% of women diagnosed with breast cancer now survive for 5 year or more Office for National Statistics, VOLUME 5 NUMBER 3 JUN

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