In Silico Insights on GD2 : A Potential Target for Pediatric Neuroblastoma

Author(s): Akanksha Limaye, Jajoriya Sweta, Maddala Madhavi, Urvy Mudgal, Sourav Mukherjee, Shreshtha Sharma, Tajamul Hussain, Anuraj Nayarisseri*, Sanjeev Kumar Singh*

Journal Name: Current Topics in Medicinal Chemistry

Volume 19 , Issue 30 , 2019


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Graphical Abstract:


Abstract:

Background: Originating from the abnormal growth of neuroblasts, pediatric neuroblastoma affects the age group below 15 years. It is an aggressive heterogenous cancer with a high morbidity rate. Biological marker GD2 synthesised by the GD2 gene acts as a powerful predictor of neuroblastoma cells. GD2 gangliosides are sialic acid-containing glycosphingolipids. Differential expression during brain development governs the function of the GD2. The present study explains the interaction of the GD2 with its established inhibitors and discovers the compound having a high binding affinity against the target protein. Technically, during the development of new compounds through docking studies, the best drug among all pre-exist inhibitors was filtered. Hence in reference to the best docked compound, the study proceeded further.

Methodology: The In silico approach provides a platform to determine and establish potential inhibitor against GD2 in Pediatric neuroblastoma. The 3D structure of GD2 protein was modelled by homology base fold methods using Smith-Watermans’ Local alignment. A total of 18 established potent compounds were subjected to molecular docking and Etoposide (CID: 36462) manifested the highest affinity. The similarity search presented 336 compounds similar to Etoposide.

Results: Through virtual screening, the compound having PubChem ID 10254934 showed a better affinity towards GD2 than the established inhibitor. The comparative profiling of the two compounds based on various interactions such as H-bond interaction, aromatic interactions, electrostatic interactions and ADMET profiling and toxicity studies were performed using various computational tools.

Conclusion: The docking separated the virtual screened drug (PubChemID: 10254934) from the established inhibitor with a better re-rank score of -136.33. The toxicity profile of the virtual screened drug was also lesser (less lethal) than the established drug. The virtual screened drug was observed to be bioavailable as it does not cross the blood-brain barrier. Conclusively, the virtual screened compound obtained in the present investigation is better than the established inhibitor and can be further augmented by In vitro analysis, pharmacodynamics and pharmacokinetic studies.

Keywords: GD2, GD2 inhibitors, Pediatric neuroblastoma, Molecular docking, Virtual screening, Tumour.

[1]
Brodeur, G.M. Neuroblastoma: biological insights into a clinical enigma. Nat. Rev. Cancer, 2003, 3(3), 203-216.
[http://dx.doi.org/10.1038/nrc1014] [PMID: 12612655]
[2]
Brodeur, G.M.; Pritchard, J.; Berthold, F.; Carlsen, N.L.; Castel, V.; Castelberry, R.P.; De Bernardi, B.; Evans, A.E.; Favrot, M.; Hedborg, F. Revisions of the international criteria for neuroblastoma diagnosis, staging, and response to treatment. J. Clin. Oncol., 1993, 11(8), 1466-1477.
[http://dx.doi.org/10.1200/JCO.1993.11.8.1466] [PMID: 8336186]
[3]
Davidoff, A.M.; Kimbrough, S.A.; Ng, C.Y.; Shochat, S.J.; Vanin, E.F. Neuroblastoma regression and immunity induced by transgenic expression of interleukin-12. J. Pediatr. Surg., 1999, 34(5), 902-906.
[http://dx.doi.org/10.1016/S0022-3468(99)90395-0] [PMID: 10359203]
[4]
Park, J.R.; Bagatell, R.; London, W.B.; Maris, J.M.; Cohn, S.L.; Mattay, K.K.; Hogarty, M. Children’s Oncology Group’s 2013 blueprint for research: neuroblastoma. Pediatr. Blood Cancer, 2013, 60(6), 985-993.
[http://dx.doi.org/10.1002/pbc.24433] [PMID: 23255319]
[5]
Mueller, W.P.; Coppenrath, E.; Pfluger, T. Nuclear medicine and multimodality imaging of pediatric neuroblastoma. Pediatr. Radiol., 2013, 43(4), 418-427.
[http://dx.doi.org/10.1007/s00247-012-2512-1] [PMID: 23151727]
[6]
Furukawa, K.; Soejima, H.; Niikawa, N.; Shiku, H. Genomic organization and chromosomal assignment of the human beta1, 4-N-acetylgalactosaminyltransferase gene. Identification of multiple transcription units. J. Biol. Chem., 1996, 271(34), 20836-20844.
[http://dx.doi.org/10.1074/jbc.271.34.20836] [PMID: 8702839]
[7]
Nagata, Y.; Yamashiro, S.; Yodoi, J.; Lloyd, K.O.; Shiku, H.; Furukawa, K. Expression cloning of beta 1,4 N-acetylgalactosaminyltransferase cDNAs that determine the expression of GM2 and GD2 gangliosides. J. Biol. Chem., 1992, 267(17), 12082-12089.
[PMID: 1601877]
[8]
Lo Piccolo, M.S.; Cheung, N.K.V.; Cheung, I.Y. GD2 synthase: a new molecular marker for detecting neuroblastoma. Cancer, 2001, 92(4), 924-931.
[http://dx.doi.org/10.1002/1097-0142(20010815)92:4<924:AID-CNCR1402>3.0.CO;2-O] [PMID: 11550167]
[9]
Sariola, H.; Terävä, H.; Rapola, J.; Saarinen, U.M. Cell-surface ganglioside GD2 in the immunohistochemical detection and differential diagnosis of neuroblastoma. Am. J. Clin. Pathol., 1991, 96(2), 248-252.
[http://dx.doi.org/10.1093/ajcp/96.2.248] [PMID: 1713742]
[10]
Ladisch, S.; Wu, Z.L.; Feig, S.; Ulsh, L.; Schwartz, E.; Floutsis, G.; Wiley, F.; Lenarsky, C.; Seeger, R. Shedding of GD2 ganglioside by human neuroblastoma. Int. J. Cancer, 1987, 39(1), 73-76.
[http://dx.doi.org/10.1002/ijc.2910390113] [PMID: 3539825]
[11]
Vuree, S.; Dunna, N.R.; Khan, I.A.; Alharbi, K.K.; Vishnupriya, S.; Soni, D.; Shah, P.; Chandok, H.; Yadav, M.; Nayarisseri, A. Pharmacogenomics of drug resistance in Breast Cancer Resistance Protein (BCRP) and its mutated variants. J. Pharm. Res., 2013, 6(7), 791-798.
[http://dx.doi.org/10.1016/j.jopr.2013.06.020]
[12]
Sinha, K.; Majhi, M.; Thakur, G.; Patidar, K.; Sweta, J.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Computer aided Drug Designing for the identification of high affinity small molecule targeting CD20 for the clinical treatment of Chronic Lymphocytic Leukemia (CLL). Curr. Top. Med. Chem., 2018, 18(29), 2527-2542.
[http://dx.doi.org/10.2174/1568026619666181210150044] [PMID: 30526461]
[13]
Yu, A.L.; Gilman, A.L.; Ozkaynak, M.F.; London, W.B.; Kreissman, S.G.; Chen, H.X.; Smith, M.; Anderson, B.; Villablanca, J.G.; Matthay, K.K.; Shimada, H.; Grupp, S.A.; Seeger, R.; Reynolds, C.P.; Buxton, A.; Reisfeld, R.A.; Gillies, S.D.; Cohn, S.L.; Maris, J.M.; Sondel, P.M. Anti-GD2 antibody with GM-CSF, interleukin-2, and isotretinoin for neuroblastoma. N. Engl. J. Med., 2010, 363(14), 1324-1334.
[http://dx.doi.org/10.1056/NEJMoa0911123] [PMID: 20879881]
[14]
Suzuki, M.; Cheung, N-K.V. Disialoganglioside GD2 as a therapeutic target for human diseases. Expert Opin. Ther. Targets, 2015, 19(3), 349-362.
[http://dx.doi.org/10.1517/14728222.2014.986459] [PMID: 25604432]
[15]
Slominski, A.; Zbytek, B.; Slominski, R. Inhibitors of melanogenesis increase toxicity of cyclophosphamide and lymphocytes against melanoma cells. Int. J. Cancer, 2009, 124(6), 1470-1477.
[http://dx.doi.org/10.1002/ijc.24005] [PMID: 19085934]
[16]
Matthay, K.K.; George, R.E.; Alice, L.Y. Promising therapeutic targets in neuroblastoma. Clin. Cancer Res., 2012, 18(10), 2740-2753.
[http://dx.doi.org/10.1158/1078-0432.CCR-11-1939]
[17]
Brignole, C.; Marimpietri, D.; Gambini, C.; Allen, T.M.; Ponzoni, M.; Pastorino, F. Development of Fab’ fragments of anti-GD(2) immunoliposomes entrapping doxorubicin for experimental therapy of human neuroblastoma. Cancer Lett., 2003, 197(1-2), 199-204.
[http://dx.doi.org/10.1016/S0304-3835(03)00099-5] [PMID: 12880982]
[18]
Simon, T.; Längler, A.; Harnischmacher, U.; Frühwald, M.C.; Jorch, N.; Claviez, A.; Berthold, F.; Hero, B. Topotecan, cyclophosphamide, and etoposide (TCE) in the treatment of high-risk neuroblastoma. Results of a phase-II trial. J. Cancer Res. Clin. Oncol., 2007, 133(9), 653-661.
[http://dx.doi.org/10.1007/s00432-007-0216-y] [PMID: 17479288]
[19]
Mody, R.; Naranjo, A.; Van Ryn, C.; Yu, A.L.; London, W.B.; Shulkin, B.L.; Parisi, M.T.; Servaes, S.E.; Diccianni, M.B.; Sondel, P.M.; Bender, J.G.; Maris, J.M.; Park, J.R.; Bagatell, R. Irinotecan-temozolomide with temsirolimus or dinutuximab in children with refractory or relapsed neuroblastoma (COG ANBL1221): an open-label, randomised, phase 2 trial. Lancet Oncol., 2017, 18(7), 946-957.
[http://dx.doi.org/10.1016/S1470-2045(17)30355-8] [PMID: 28549783]
[20]
Kowalczyk, A.; Gil, M.; Horwacik, I.; Odrowaz, Z.; Kozbor, D.; Rokita, H. The GD2-specific 14G2a monoclonal antibody induces apoptosis and enhances cytotoxicity of chemotherapeutic drugs in IMR-32 human neuroblastoma cells. Cancer Lett., 2009, 281(2), 171-182.
[http://dx.doi.org/10.1016/j.canlet.2009.02.040] [PMID: 19339105]
[21]
Cheung, N-K.V.; Dyer, M.A. Neuroblastoma: developmental biology, cancer genomics and immunotherapy. Nat. Rev. Cancer, 2013, 13(6), 397-411.
[http://dx.doi.org/10.1038/nrc3526] [PMID: 23702928]
[22]
Li, Z. Combination of an allosteric Akt inhibitor MK-2206 with etoposide or rapamycin enhances the anti-tumor growth effect in Neuroblastoma. Clin. Cancer Res., 2012, 3321.
[23]
Gholizadeh, S.; Dolman, E.M.; Wieriks, R.; Sparidans, R.W.; Hennink, W.E.; Kok, R.J. Anti-GD2 Immunoliposomes for targeted delivery of the survivin inhibitor sepantronium bromide (YM155) to neuroblastoma tumor cells. Pharm. Res., 2018, 35(4), 85.
[http://dx.doi.org/10.1007/s11095-018-2373-x] [PMID: 29516187]
[24]
George, R.E.; Diller, L.; Bernstein, M.L. Pharmacotherapy of neuroblastoma. Expert Opin. Pharmacother., 2010, 11(9), 1467-1478.
[http://dx.doi.org/10.1517/14656566.2010.482100] [PMID: 20408767]
[25]
Bandaru, S.; Sumithnath, T.G.; Sharda, S.; Lakhotia, S.; Sharma, A.; Jain, A.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Helix-coil transition signatures B-RAF V600E mutation and virtual screening for inhibitors directed against Mutant B-Raf. Curr. Drug Metab., 2017, 18(6), 527-534.
[http://dx.doi.org/10.2174/1389200218666170503114611] [PMID: 28472910]
[26]
Nasr, A.B.; Ponnala, D.; Sagurthi, S.R.; Kattamuri, R.K.; Marri, V.K.; Gudala, S.; Lakkaraju, C.; Bandaru, S.; Nayarisseri, A. Molecular Docking studies of FKBP12-mTOR inhibitors using binding predictions. Bioinformation, 2015, 11(6), 307-315.
[http://dx.doi.org/10.6026/97320630011307] [PMID: 26229292]
[27]
Cheng, F.; Li, W.; Zhou, Y.; Shen, J.; Wu, Z.; Liu, G.; Lee, P.W.; Tang, Y. admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties. J. Chem. Inf. Model., 2012, 52(11), 3099-3105.
[28]
Dunna, N.R.; Kandula, V.; Girdhar, A.; Pudutha, A.; Hussain, T.; Bandaru, S.; Nayarisseri, A. High affinity pharmacological profiling of dual inhibitors targeting RET and VEGFR2 in inhibition of kinase and angiogeneis events in medullary thyroid carcinoma. Asian Pac. J. Cancer Prev., 2015, 16(16), 7089-7095.
[http://dx.doi.org/10.7314/APJCP.2015.16.16.7089] [PMID: 26514495]
[29]
Sinha, C.; Nischal, A.; Bandaru, S.; Kasera, P.; Rajput, A.; Nayarisseri, A.; Khattri, S. An in silico approach for identification of novel inhibitors as a potential therapeutics targeting HIV-1 viral infectivity factor. Curr. Top. Med. Chem., 2015, 15(1), 65-72.
[http://dx.doi.org/10.2174/1568026615666150112114337] [PMID: 25579575]
[30]
Sinha, C.; Nischal, A.; Pant, K.K.; Bandaru, S.; Nayarisseri, A.; Khattri, S. Molecular docking analysis of RN18 and VEC5 in A3G-Vif inhibition. Bioinformation, 2014, 10(10), 611-616.
[http://dx.doi.org/10.6026/97320630010611] [PMID: 25489169]
[31]
Bandaru, S.; Marri, V.K.; Kasera, P.; Kovuri, P.; Girdhar, A.; Mittal, D.R.; Ikram, S.; Gv, R.; Nayarisseri, A. Structure based virtual screening of ligands to identify cysteinyl leukotriene receptor 1 antagonist. Bioinformation, 2014, 10(10), 652-657.
[http://dx.doi.org/10.6026/97320630010652] [PMID: 25489175]
[32]
Dunna, N.R.; Bandaru, S.; Akare, U.R.; Rajadhyax, S.; Gutlapalli, V.R.; Yadav, M.; Nayarisseri, A. Multiclass comparative virtual screening to identify novel Hsp90 inhibitors: a therapeutic breast cancer drug target. Curr. Top. Med. Chem., 2015, 15(1), 57-64.
[http://dx.doi.org/10.2174/1568026615666150112113627] [PMID: 25579569]
[33]
Bandaru, S.; Ponnala, D.; Lakkaraju, C.; Bhukya, C.K.; Shaheen, U.; Nayarisseri, A. Identification of high affinity non-peptidic small molecule inhibitors of MDM2-p53 interactions through structure-based virtual screening strategies. Asian Pac. J. Cancer Prev., 2015, 16(9), 3759-3765.
[http://dx.doi.org/10.7314/APJCP.2015.16.9.3759] [PMID: 25987034]
[34]
Akare, U.R.; Bandaru, S.; Shaheen, U.; Singh, P.K.; Tiwari, G.; Singare, P.; Nayarisseri, A.; Banerjee, T. Molecular docking approaches in identification of high affinity inhibitors of Human SMO receptor. Bioinformation, 2014, 10(12), 737-742.
[http://dx.doi.org/10.6026/97320630010737] [PMID: 25670876]
[35]
Bandaru, S.; Alvala, M.; Akka, J.; Sagurthi, S.R.; Nayarisseri, A.; Singh, S.K.; Mundluru, H.P. Identification of small molecule as a high affinity β2 agonist promiscuously targeting wild and mutated (Thr164Ile) β 2 adrenergic receptor in the treatment of bronchial asthma. Curr. Pharm. Des., 2016, 22(34), 5221-5233.
[http://dx.doi.org/10.2174/1381612822666160513145721] [PMID: 27174812]
[36]
Ali, M.A.; Vuree, S.; Goud, H.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Identification of high-affinity small molecules targeting gamma secretase for the treatment of Alzheimer’s disease. Curr. Top. Med. Chem., 2019, 19(13), 1173-1187.
[http://dx.doi.org/10.2174/1568026619666190617155326] [PMID: 31244427]
[37]
Bandaru, S.; Prasad, M.H.; Jyothy, A.; Nayarisseri, A.; Yadav, M. Binding modes and pharmacophoric features of muscarinic antagonism and β2 agonism (MABA) conjugates. Curr. Top. Med. Chem., 2013, 13(14), 1650-1655.
[http://dx.doi.org/10.2174/15680266113139990115] [PMID: 23889054]
[38]
Nayarisseri, A.; Moghni, S.M.; Yadav, M.; Kharate, J.; Sharma, P.; Chandok, K.H.; Shah, K.P. In silico investigations on HSP90 and its inhibition for the therapeutic prevention of breast cancer. J. Pharm. Res., 2013, 7(2), 150-156.
[http://dx.doi.org/10.1016/j.jopr.2013.02.020]
[39]
Shaheen, U.; Akka, J.; Hinore, J.S.; Girdhar, A.; Bandaru, S.; Sumithnath, T.G.; Nayarisseri, A.; Munshi, A. Computer aided identification of sodium channel blockers in the clinical treatment of epilepsy using molecular docking tools. Bioinformation, 2015, 11(3), 131-137.
[http://dx.doi.org/10.6026/97320630011131] [PMID: 25914447]
[40]
Gudala, S.; Khan, U.; Kanungo, N.; Bandaru, S.; Hussain, T.; Parihar, M.; Nayarisseri, A.; Mundluru, H.P. Identification and pharmacological analysis of high efficacy small molecule inhibitors of EGF-EGFR interactions in clinical treatment of non-small cell lung carcinoma: A computational approach. Asian Pac. J. Cancer Prev., 2015, 16(18), 8191-8196.
[http://dx.doi.org/10.7314/APJCP.2015.16.18.8191] [PMID: 26745059]
[41]
Babitha, P.P.; Sahila, M.M.; Bandaru, S.; Nayarisseri, A.; Sureshkumar, S. Molecular docking and pharmacological investigations of rivastigmine-fluoxetine and coumarin-tacrine hybrids against acetyl choline esterase. Bioinformation, 2015, 11(8), 378-386.
[http://dx.doi.org/10.6026/97320630011378] [PMID: 26420918]
[42]
Natchimuthu, V.; Bandaru, S.; Nayarisseri, A.; Ravi, S. Design, synthesis and computational evaluation of a novel intermediate salt of N-cyclohexyl-N-(cyclohexylcarbamoyl)-4-(trifluoromethyl) benzamide as potential potassium channel blocker in epileptic paroxysmal seizures. Comput. Biol. Chem., 2016, 64, 64-73.
[http://dx.doi.org/10.1016/j.compbiolchem.2016.05.003] [PMID: 27266485]
[43]
Patidar, K.; Deshmukh, A.; Bandaru, S.; Lakkaraju, C.; Girdhar, A.; Vr, G.; Banerjee, T.; Nayarisseri, A.; Singh, S.K. Virtual screening approaches in identification of bioactive compounds akin to delphinidin as potential HER2 inhibitors for the treatment of breast cancer. Asian Pac. J. Cancer Prev., 2016, 17(4), 2291-2295.
[http://dx.doi.org/10.7314/APJCP.2016.17.4.2291] [PMID: 27221932]
[44]
Sahila, M.M.; Babitha, P.P.; Bandaru, S.; Nayarisseri, A.; Doss, V.A. Molecular docking based screening of GABA (A) receptor inhibitors from plant derivatives. Bioinformation, 2015, 11(6), 280-289.
[http://dx.doi.org/10.6026/97320630011280] [PMID: 26229288]
[45]
Bandaru, S.; Tarigopula, P.; Akka, J.; Marri, V.K.; Kattamuri, R.K.; Nayarisseri, A.; Mangalarapu, M.; Vinukonda, S.; Mundluru, H.P.; Sagurthi, S.R. Association of Beta 2 adrenergic receptor (Thr164Ile) polymorphism with Salbutamol refractoriness in severe asthmatics from Indian population. Gene, 2016, 592(1), 15-22.
[http://dx.doi.org/10.1016/j.gene.2016.07.043] [PMID: 27450915]
[46]
Khandekar, N.; Singh, S.; Shukla, R.; Tirumalaraju, S.; Bandaru, S.; Banerjee, T.; Nayarisseri, A. Structural basis for the in vitro known acyl-depsipeptide 2 (ADEP2) inhibition to Clp 2 protease from Mycobacterium tuberculosis. Bioinformation, 2016, 12(3), 92-97.
[http://dx.doi.org/10.6026/97320630012092] [PMID: 28149041]
[47]
Bandaru, S.; Alvala, M.; Nayarisseri, A.; Sharda, S.; Goud, H.; Mundluru, H.P.; Singh, S.K. Molecular dynamic simulations reveal suboptimal binding of salbutamol in T164I variant of β2 adrenergic receptor. PLoS One, 2017, 12(10) e0186666
[http://dx.doi.org/10.1371/journal.pone.0186666] [PMID: 29053759]
[48]
Sharda, S.; Sarmandal, P.; Cherukommu, S.; Dindhoria, K.; Yadav, M.; Bandaru, S.; Sharma, A.; Sakhi, A.; Vyas, T.; Hussain, T.; Nayarisseri, A.; Singh, S.K. A virtual screening approach for the identification of high affinity small molecules targeting BCR-ABL1 inhibitors for the treatment of chronic myeloid leukemia. Curr. Top. Med. Chem., 2017, 17(26), 2989-2996.
[http://dx.doi.org/10.2174/1568026617666170821124512] [PMID: 28828991]
[49]
Jain, D.; Udhwani, T.; Sharma, S.; Gandhe, A.; Reddy, P.B.; Nayarisseri, A.; Singh, S.K. Design of novel JAK3 Inhibitors towards Rheumatoid Arthritis using molecular docking analysis. Bioinformation, 2019, 15(2), 68-78.
[http://dx.doi.org/10.6026/97320630015068] [PMID: 31435152]
[50]
Mendonça-Junior, F.J.B.; Scotti, M.T.; Nayarisseri, A.; Zondegoumba, E.N.T.; Scotti, L. Natural bioactive products with antioxidant properties useful in neurodegenerative diseases. Oxid. Med. Cell. Longev., 2019. 20197151780
[http://dx.doi.org/10.1155/2019/7151780] [PMID: 31210847]
[51]
Nayarisseri, A.; Hood, E.A. Advancement in microbial cheminformatics. Curr. Top. Med. Chem., 2018, 18(29), 2459-2461.
[http://dx.doi.org/10.2174/1568026619666181120121528] [PMID: 30457050]
[52]
Gokhale, P.; Chauhan, A.P.S.; Arora, A.; Khandekar, N.; Nayarisseri, A.; Singh, S.K. FLT3 inhibitor design using molecular docking based virtual screening for acute myeloid leukemia. Bioinformation, 2019, 15(2), 104-115.
[http://dx.doi.org/10.6026/97320630015104] [PMID: 31435156]
[53]
Shukla, P.; Khandelwal, R.; Sharma, D.; Dhar, A.; Nayarisseri, A.; Singh, S.K. Virtual screening of IL-6 inhibitors for idiopathic arthritis. Bioinformation, 2019, 15(2), 121-130.
[http://dx.doi.org/10.6026/97320630015121] [PMID: 31435158]
[54]
Udhwani, T.; Mukherjee, S.; Sharma, K.; Sweta, J.; Khandekar, N.; Nayarisseri, A.; Singh, S.K. Design of PD-L1 inhibitors for lung cancer. Bioinformation, 2019, 15(2), 139-150.
[http://dx.doi.org/10.6026/97320630015139] [PMID: 31435160]
[55]
Rao, D.M.; Nayarisseri, A.; Yadav, M.; Patel, D. Comparative modeling of methylentetrahydrofolate reductase (MTHFR) enzyme and its mutational assessment: in silico approach. Int. J. Bioinform. Res., 2010, 2(1), 5-9.
[http://dx.doi.org/10.9735/0975-3087.2.1.5-9]
[56]
Kelotra, S.; Jain, M.; Kelotra, A.; Jain, I.; Bandaru, S.; Nayarisseri, A.; Bidwai, A. An in silico appraisal to identify high affinity anti-apoptotic synthetic tetrapeptide inhibitors targeting the mammalian caspase 3 enzyme. Asian Pac. J. Cancer Prev., 2014, 15(23), 10137-10142.
[http://dx.doi.org/10.7314/APJCP.2014.15.23.10137] [PMID: 25556438]
[57]
Sweta, J.; Khandelwal, R.; Srinitha, S.; Pancholi, R.; Adhikary, R.; Ali, M.A.; Nayarisseri, A.; Vuree, S.; Singh, S.K. Identification of high-affinity small molecule targeting IDH2 for the clinical treatment of acute myeloid leukemia. Asian Pac. J. Cancer Prev., 2019, 20(8), 2287-2297.
[http://dx.doi.org/10.31557/APJCP.2019.20.8.2287] [PMID: 31450897]
[58]
Gutlapalli, V.R.; Sykam, A.; Nayarisseri, A.; Suneetha, S.; Suneetha, L.M. Insights from the predicted epitope similarity between Mycobacterium tuberculosis virulent factors and its human homologs. Bioinformation, 2015, 11(12), 517-524.
[http://dx.doi.org/10.6026/97320630011517] [PMID: 26770024]
[59]
Nayarisseri, A.; Yadav, M.; Wishard, R. Computational evaluation of new homologous down regulators of Translationally Controlled Tumor Protein (TCTP) targeted for tumor reversion. Interdiscip. Sci., 2013, 5(4), 274-279.
[http://dx.doi.org/10.1007/s12539-013-0183-8] [PMID: 24402820]
[60]
Praseetha, S.; Bandaru, S.; Nayarisseri, A.; Sureshkumar, S. Pharmacological analysis of vorinostat analogues as potential anti-tumor agents targeting human histone deacetylases: an epigenetic treatment stratagem for cancers. Asian Pac. J. Cancer Prev., 2016, 17(3), 1571-1576.
[http://dx.doi.org/10.7314/APJCP.2016.17.3.1571] [PMID: 27039807]
[61]
Majhi, M.; Ali, M.A.; Limaye, A.; Sinha, K.; Bairagi, P.; Chouksey, M.; Shukla, R.; Kanwar, N.; Hussain, T.; Nayarisseri, A.; Singh, S.K. An in silico investigation of potential egfr inhibitors for the clinical treatment of colorectal cancer. Curr. Top. Med. Chem., 2018, 18(27), 2355-2366.
[http://dx.doi.org/10.2174/1568026619666181129144107] [PMID: 30499396]
[62]
Sharma, K.; Patidar, K.; Ali, M.A.; Patil, P.; Goud, H.; Hussain, T.; Nayarisseri, A.; Singh, S.K. Structure-based virtual screening for the identification of high affinity compounds as potent vegfr2 inhibitors for the treatment of renal cell carcinoma. Curr. Top. Med. Chem., 2018, 18(25), 2174-2185.
[http://dx.doi.org/10.2174/1568026619666181130142237] [PMID: 30499413]
[63]
Shameer, K.; Nayarisseri, A.; Romero Duran, F.X.; González-Díaz, H. Improving neuropharmacology using big data, machine learning and computational algorithms. Curr. Neuropharmacol., 2017, 15(8), 1058-1061.
[http://dx.doi.org/10.2174/1570159X1508171114113425] [PMID: 29199918]
[64]
Basak, S.C.; Nayarisseri, A.; González-Díaz, H.; Bonchev, D. Editorial (Thematic Issue: Chemoinformatics models for pharmaceutical design, part 2). Curr. Pharm. Des., 2016, 22(34), 5177-5178.
[http://dx.doi.org/10.2174/138161282234161110222751] [PMID: 27852211]
[65]
Basak, S.C.; Nayarisseri, A.; González-Díaz, H.; Bonchev, D. Editorial (Thematic Issue: Chemoinformatics models for pharmaceutical design, Part 1). Curr. Pharm. Des., 2016, 22(33), 5041-5042.
[http://dx.doi.org/10.2174/138161282233161109224932] [PMID: 27852204]
[66]
Kelotra, A.; Gokhale, S.M.; Kelotra, S.; Mukadam, V.; Nagwanshi, K.; Bandaru, S.; Nayarisseri, A.; Bidwai, A. Alkyloxy carbonyl modified hexapeptides as a high affinity compounds for Wnt5A protein in the treatment of psoriasis. Bioinformation, 2014, 10(12), 743-749.
[http://dx.doi.org/10.6026/97320630010743] [PMID: 25670877]
[67]
Chandrakar, B.; Jain, A.; Roy, S.; Gutlapalli, V.R.; Saraf, S.; Suppahia, A.; Verma, A.; Tiwari, A.; Yadav, M.; Nayarisseri, A. Molecular modeling of Acetyl-CoA carboxylase (ACC) from Jatropha curcas and virtual screening for identification of inhibitors. journal of pharmacy research, 2013, 6(9), 913-918.
[68]
Khandelwal, R.; Chauhan, A.P.S.; Bilawat, S.; Gandhe, A.; Hussain, T.; Hood, E.A.; Nayarisseri, A.; Singh, S.K. Structure-based virtual screening for the identification of high affinity small molecule towards STAT3 for the clinical treatment of Osteosarcoma. Curr. Top. Med. Chem., 2018, 18(29), 2511-2526.
[http://dx.doi.org/10.2174/1568026618666181115092001] [PMID: 30430945]
[69]
Nayarisseri, A.; Singh, S.K. Functional inhibition of VEGF and EGFR suppressors in cancer treatment. Curr. Top. Med. Chem., 2019, 19(3), 178-179.
[http://dx.doi.org/10.2174/156802661903190328155731] [PMID: 30950335]
[70]
Monteiro, A.F.M.; Viana, J.O.; Nayarisseri, A.; Zondegoumba, E.N.; Mendonça Junior, F.J.B.; Scotti, M.T.; Scotti, L. Computational studies applied to flavonoids against alzheimer’s and parkinson’s diseases. Oxid. Med. Cell. Longev., 2018, 20187912765
[http://dx.doi.org/10.1155/2018/7912765] [PMID: 30693065]
[71]
Patidar, K.; Panwar, U.; Vuree, S.; Sweta, J.; Sandhu, M.K.; Nayarisseri, A.; Singh, S.K. An In silico approach to identify high affinity small molecule targeting m-TOR inhibitors for the clinical treatment of breast cancer. Asian Pac. J. Cancer Prev., 2019, 20(4), 1229-1241.
[http://dx.doi.org/10.31557/APJCP.2019.20.4.1229] [PMID: 31030499]
[72]
Sharda, S.; Khandelwal, R.; Adhikary, R.; Sharma, D.; Majhi, M.; Hussain, T. A computer-aided drug designing for pharmacological inhibition of ALK inhibitors induces apoptosis and differentiation in Non-small cell lung cancer. Curr. Top. Med. Chem., 2019, 19(13), 1129-1144.
[http://dx.doi.org/10.2174/1568026619666190521084941] [PMID: 31109278]


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Article Details

VOLUME: 19
ISSUE: 30
Year: 2019
Published on: 11 November, 2019
Page: [2766 - 2781]
Pages: 16
DOI: 10.2174/1568026619666191112115333
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