Book Open Access

Theoretical study of anticancer activity of glycoside amides

Tsanov; Tsanov

This book is a long-term study and analysis presented in a more scientifically popular form. The matter is presented in a freer way in order to explain the matter.

GOALS AND OBJECTIVES OF THE STUDY

 

First goal: A study of what exactly is the reason for the long-term use of toxic amygdalin in the social group

Annotation to the realization of the objective: By making a precise socio-anthropological analysis of the life of the ancient people of Botra (Hunza people, Burusho / Brusho people), we come to the hypothesis, which is confirmed by two proofs, through a number of modern quantum-mechanical, molecular-topological and bio-analytical checks. A convenient, harmless, form of amygdalin derivative is available that has the same biological and chemical activity and could be used in conservative clinical oncology. The article also presents a theoretical comparative analysis of biochemical reactivity in in vivo and in vitro media, by which we also determine the recommended dosage for patient administration. Based on a comparative analysis of the data, obtained in published clinical studies of amygdalin, is presented and summarized a scheme of the anti-tumor activity

Presentation and scientific popularization of the results: some of the conducted researches are published in the format of an article - Theoretical Analysis for the Safe Form and Dosage of Amygdalin Product https://doi.org/10.2174/1871520620666200313163801.

 

Second goal: Analysis of molecules forming activity in the environment around the cancer cell and their ability to cross the cell membrane

Annotation to the realization of the objective: This scientific analysis is a continuation of the first goal (§I.1.). The hypothesis that hydrolyzed to amine/carboxylic acid cyano/nitrile glycosides are a potential anticancer drug has been proposed and theoretically confirmed there. Their biological activity remains unchanged directly from the natural compounds of this group, but their toxicity is many times lower than unmodified native molecules. After defining the chemical formula and determining the pharmaceutical form and dosage, most active groups are also identified, which directly determines their biological activity.

Presentation and scientific popularization of the results some of the conducted researches are published in the format of an article - Theoretical Study of the Process of Passage of Glycoside Amides through the Cell Membrane of Cancer Cell https://doi.org/10.2174/1871520620999201103201008 .

 

Third goal: Analysis of models for evaluation of the offered pharmaceutical forms

Annotation to the realization of the objective: The pharmaceutical form allows deviation from the chemically pure substance. This is a convenient and at the same time affordable (from a financial and / or technological point of view) form of admission by patients. It is not necessary to use an "ideal" pure active substance (including a specific isomeric form). Due to the wide variety of natural glucosamide nitriles (starting material for the production of amide / carboxylic acid), modern pharmacology allows their combined use by chemical nature and concentration of the active form passing through the cell membrane.

Methodology: A comparative analysis is performed based on stoichiometric calculations for the concentration of the active form and the prediction of bioactivity. For this purpose, the following methodology is used: Analysis of data on the active molecular form of anticancer cells and determination of the drug dose. 

Presentation and scientific popularization of the results: some of the conducted researches are published in the format of an article - Theoretical analysis of anticancer cellular effects of glycoside amides

https://doi.org/10.2174/1871520621666210903122831 .

 

Fourth goal: Interpretable prediction for anticancer sensitivity of glycoside amides

 

Annotation to the realization of the objective: This goal is a natural continuation of the hypothesis that the bioactive form of natural nitrile glycosides is due to a hydrolyzed to amide molecule. As a secondary hydrolysis, one proceeds to the carboxylic acid, which was subsequently specified to be necessary for subsequent biochemical processes. Her didactic proof defines, etc. active anti-cancer molecular forms. Subsequent calculations illustrate biochemically the passage of these active forms across the cell membrane of a cancer cell. For the transition from chemical to pharmaceutical form, dozens of indicators characterizing per oral drugs were analyzed.

The main research challenge is to create a sufficiently adapted methodological scheme and at the same time to maintain the general conservatism of good oncological medical practices.

Methodology: The current methodological program relies on a comparative analysis of non-identical variables. In one case it values the IC50, and in the other pharmacokinetic and druglikeness indicators of potential oral dosage forms.

In order to minimize the dualism in the interpretation, conditionally postulate some of the allowable values that would be reflected in the processing of a sample of data from the general population.

 

AUTHOR'S NOTES

With the present scientific work we have tried to present in a more generalized form our long-term theoretical research. We tried to draw every value, every dependence and every conclusion precisely, in a form that is not subject to any personal view and/or to be enslaved to a generally "accepted" opinion.

Natural nitrile glycosides would not cross the tumor cell membrane. They decompose to HCN-acid, phenyl methanol and carbohydrate. They do NOT have antitumor activity due to their inability to reach the target unchanged. These compounds, in their natural form, are extremely toxic to the human body. Applying them is not a cure, even at higher concentrations they do more harm than good. Theoretically, we have derived dozens of their modified forms, but their amides and carboxylic acids are the most promising for their introduction in conservative oncology. The fact is that the tumor cell itself is trying to counteract in a way that is quite safe for it.

The knowledge that humanity has gained from the millennial battle between it and tumors, combined with the development of mathematics, statistical and quantum molecular thermodynamics, molecular topology and geometry, clinical oncology, pathophysiology, etc., with the unequivocal contribution of thousands of scientists, we tried to we present this thesis as a sentence and the most modest way to try to confirm and prove it.

 

The proposed methodological program for conservative treatment of oncological diseases does not contradict the good medical practices for chemotherapy. In order to improve the general condition of patients, chemoprevention and/or homeopathy could be applied, but not at the expense of a varied diet, incl. table salt, water, culinary acidifiers and fats. Alternative medicine should only be used to treat individual symptoms, not syndromes. The studied molecular forms activity is significant and many times exceeds a number of approved products for treatment. Anti-cancer agents could best be administered orally. Their toxicity is many times less than that of most references accepted in clinical chemotherapy. Personalized therapy - in a small number of cases, it is necessary to act individually according to the patient's current history. For this purpose, after the application of the general therapy and / or in combination with it, the specific agent for the respective cell lines must be taken. The ratio of amide to carboxylic acid should again be 4.87:1.

  • ACS (Ed.). (1991). Unproven methods of cancer management: Laetrile. CA: A Cancer Journal for Clinicians, 41(3), 187-92. doi:10.3322/canjclin.41.3.187

  • Ahmed, M. (2016). Ethnicity, Identity and Group Vitality: A study of Burushos of Srinagar. Journal of Ethnic and Cultural Studies, 3(1), 1-10. doi:10.29333/ejecs/51

  • Airley, R. (2009). Cancer Chemotherapy: Basic Science to the Clinic. Wiley

  • Allinger, N. L. (1977). Conformational analysis. 130. MM2. A hydrocarbon force field utilizing V1 and V2 torsional terms. J. Am. Chem. Soc., 99(25), 8127–8134. doi:10.1021/ja00467a001

  • Allinger, N. L. (1977). Conformational analysis. 130. MM2. A hydrocarbon force field utilizing V1 and V2 torsional terms. Journal of the American Chemical Society, 99(25), 8127-34. doi:10.1021/ja00467a001

  • Ames, B. N., Durston, W. E., Yamasaki, E., & Lee, F. D. (1973). Carcinogens are Mutagens: A Simple Test System Combining Liver Homogenates for Activation and Bacteria for Detection. Proceedings of the National Academy of Sciences of the United States of America, 70(8), 2281-5. doi:10.1073/pnas.70.8.2281

  • Ani, R., Anand, P. S., Sreenath, B., & Deepa, O. S. (2020). In Silico Prediction Tool for Drug-likeness of Compounds based on Ligand Based Screening. International Journal of Research in Pharmaceutical Sciences, 11(4), 6273-81. doi:10.26452/ijrps.v11i4.3310

  • Aoyagi, T., shizuka, M., Takeuchi, T., & Umezawa, H. (1977). Enzyme inhibitors in relation to cancer therapy. Japanese journal of antibiotics, 30, 121-32

  • Azad, I., Nasibullah, M., Khan, T., Hassan, F., & Akhter, Y. (2018). Exploring the novel heterocyclic derivatives as lead molecules for design and development of potent anticancer agents. Journal of Molecular Graphics and Modelling, 81, 211-28. doi:10.1016/j.jmgm.2018.02.013

  • Babić, D., Klein, D. J., Lukovits, I., Nikolić, S., & Trinajstić, N. (2001). Resistance‐distance matrix: A computational algorithm and its application. Int. Journal of Quantum Chemistry, 90(1), 166-76. doi:10.1002/qua.10057

  • Baderna, D., & Benfenati, E. (2019). In vitro - Micronucleus activity (IRFMN/VERMEER) - v.1.0.0. (A. Manganaro, Ed.) Retrieved from https://www.vegahub.eu/vegahub-dwn/qmrf/QMRF_MNVITRO_VERMEER.pdf

  • Balaban, A. T. (1982). Distance Connectivity Index. Chemical Physics Letters, 89, 399-404

  • Barceloux, D. (2008). Medical toxicology of natural substances: foods, fungi, medicinal herbs, plants, and venomous animals. John Wiley & Sons

  • Baroni, A., Paoletti, I., Greco, R., Satriano, R. A., Ruocco, E., Tufano, M. A., & Perez, J. J. (2005). Immunomodulatory effects of a set of amygdalin analogues on human keratinocyte cells. Experimental Dermatology, 14(11), 854-9. doi:10.1111/j.1600-0625.2005.00368.x

  • Barwina, M., Wiergowski , M., & Anand, J. S. (2013). Accidental poisoning with peach seeds used as anticancer therapy--report of two cases. Przeglad lekarski, 70(8), 687-9

  • Batista, J., Tan, L., & Bajorath, J. (2010). Atom-Centered Interacting Fragments and Similarity Search Applications. Journal of Chemical Information and Modeling, 50(1), 79-86. doi:10.1021/ci9004223

  • Baue, C. A., Schneider, G., & Göller, A. H. (2019). Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies. Journal of Cheminformatics, 11, 59. doi:10.1186/s13321-019-0381-4

  • Benfenati, E. (2020, 10). Adipose tissue:blood model (INERIS) - v. 1.0.0. (A. Manganaro, Ed.) Retrieved from https://www.vegahub.eu/vegahub-dwn/qmrf/QMRF_ADIPOSE_BLOOD_IRMFN.pdf

  • Benfenati, E., & Marzo, M. (2020, March). QMRF Title:Developmental/Reproductive Toxicity library (PG) (version 1.1.0). Retrieved from https://www.vegahub.eu/vegahub-dwn/qmrf/QMRF_DEVTOX_PG.pdf

  • Benfenati, E., Benigni, R., Demarini, D. M., Helma, C., Kirkland, D., Martin, T. M., . . . Yang, C. (2009). Predictive Models for Carcinogenicity and Mutagenicity: Frameworks, State-of-the-Art, and Perspectives. Journal of Environmental Science and Health, 27(2), 57-90. doi:10.1080/10590500902885593

  • Benfenati, Е., Roncaglioni, А., Lombardo, А., & Manganaro, А. (2019). Integrating QSAR, Read-Across, andScreening Tools: The VEGAHUB Platform as an Example. In H. Hong (Ed.). Springer. doi:10.1007/978-3-030-16443-0

  • Benigni, R., & Bossa, C. (2011). Mechanisms of chemical carcinogenicity and mutagenicity: a review with implications for. Chemical Reviews, 111(4), 2507-36. doi:10.1021/cr100222q

  • Benigni, R., Bossa, C., & Tcheremenskaia, O. (2013). In vitro cell transformation assays for an integrated, alternative assessment of carcinogenicity: a databased. Mutagenesis, 28(1), 101-16. doi:10.1093/mutage/ges059

  • Benigni, R., Bossa, C., & Tcheremenskaia, O. (2013). Nongenotoxic carcinogenicity of chemicals: mechanisms of action and early recognition through a new set of structural alerts. Chemical Reviews, 113(5), 2940-57. doi:10.1021/cr300206t

  • Benigni, R., Bossa, C., Jeliazkova, N. G., Netzeva, T. I., & Worth, A. P. (2008). The Benigni/Bossa rulebase for mutagenicity and carcinogenicity - a module of toxtree. Technical Report EUR 23241 EN, European Commission, Joint Research Centre. Retrieved from https://publications.jrc.ec.europa.eu/repository/handle/JRC43157

  • Bernard, H. R. (1998). Handbook of Methods in Cultural Anthropology.

  • BHAGAVAN, N. V. (2002). CHAPTER 1 - Water, Acids, Bases, and Buffers. In Medical Biochemistry (pp. 1-16). Academci press. doi:10.1016/B978-012095440-7/50003-2

  • Bhullar, K. S., Lagarón, N. O., McGowan, E. M., Parmar, I., Jha, A., Hubbard, B. P., & Rupasinghe, H. V. (2018). Kinase-targeted cancer therapies: progress, challenges and future directions. Molecular Cancer, 17(48). doi:10.1186/s12943-018-0804-2

  • Biaglow, J. E., & Durand, R. E. (1978). The enhanced radiation response of an in vitro tumour model by cyanide released from hydrolysed amygdalin. International Journal of Radiation Biology and Related Studies in Physics, Chemistry, and Medicine, 33(4), 397-401. doi:10.1080/09553007814550311

  • Bickerton, G. R., Paolini, G. V., Besnard, J., Muresan, S., & Hopkins, A. L. (2012). Quantifying the chemical beauty of drugs. Nature Chemistry, 4(2), 90-8. doi:10.1038/nchem.1243

  • Bitting, T. H. (1978). Drugs--Federal Drug Administration ban on Laetrile treatments for terminally ill cancer patients is arbitrary and capricious. Tulsa Law Review (former: TL Journal), 14, 222-5.

  • Böcker, A., Derksen, S., Schmidt, E., Teckentrup, A., & Schneider, G. (2005). A hierarchical clustering approach for large compound libraries. Journal of Chemical Information and Modeling, 45(4), 807-15. doi:10.1021/ci0500029

  • Bodor, N., Buchwald, P., & Huang, M. J. (1999). The Role of Computational Techniques in Retrometabolic Drug Design Strategies. Theoretical and Computational Chemistry, 8, 569-618.

  • Bolarinwa, I. F., Orfila, C., & Morgan, M. R. (2014). Amygdalin content of seeds, kernels and food products commercially-available in the UK. Food Chemistry, 152(1), 133-9. doi:10.1016/j.foodchem.2013.11.002

  • Born, M., & Wolf, E. (1999). Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (Vol. section 2.3.3). Cambridge University Press.

  • Box, G., & Wilson, K. (1951). On the Experimental Attainment of Optimum Conditions. Journal of the Royal Statistical Society, 12.

  • Brenk, R., Schipani, A., James, D., Krasowski, A., Gilbert, I. H., Frearson, J., & Wyatt, P. G. (2008). Lessons Learnt from Assembling Screening Libraries for Drug Discovery for Neglected Diseases. ChemMedChem, 3(3), 435-44. doi:10.1002/cmdc.200700139

  • Brown, I. D. (2009). Topology and Chemistry. Structural Chemistry, 13, 339-55. doi:10.1023/A:1015872125545

  • Busby, S. A., & Burris, T. P. (2012). Retinoic Acid Receptors (RARA, RARB, and RARC). In S. Choi (Ed.), Encyclopedia of Signaling Molecules. New York: Springer. doi:10.1007/978-1-4419-0461-4_385

  • Cadow, J., Born, J., Manica, M., Oskooei, A., & Martínez, M. R. (2020). PaccMann: a web service for interpretable anticancer compound sensitivity prediction. Nucleic Acids Research, 48(W1), W502-8. doi:10.1093/nar/gkaa327

  • Cappelli, C. I., Manganelli, S., Toma, C., Benfenati, E., & Mombelli, E. (2021). Prediction of the Partition Coefficient between Adipose Tissue and Blood for Environmental Chemicals: From Single QSAR Models to an Integrated Approach. Molecular Informatics, 40(3). doi:10.1002/minf.202000072

  • Carter, J. H., McLafferty, M. A., & Goldman, P. (1980). Role of the gastrointestinal microflora in amygdalin (laetrile)-induced cyanide toxicity. Biochemical Pharmacology, 29(3), 301-4. doi:10.1016/0006-2952(80)90504-3

  • Cassano, A., Manganaro, A., Martin, T., Young, D., Piclin, N., Pintore, M., . . . Benfenati, E. (2010). The CAESAR models for developmental toxicity. Chemistry Central Journal, 4(1). doi:10.1186/1752-153X-4-S1-S4

  • Chabner, B. A., & Longo, D. L. (2018). Cancer Chemotherapy, Immunotherapy and Biotherapy: Principles and Practice (6th Ed. ed.). Lippincott Williams & Wilkins (LWW).

  • Chang, H. K., Shin, M. S., Yang, H. Y., Lee, J. W., Kim, Y. S., Lee, M. H., . . . Kim, C. J. (2006). Amygdalin induces apoptosis through regulation of Bax and Bcl-2 expressions in human DU145 and LNCaP prostate cancer cells. Biological and Pharmaceutical Bulletin, 29(8), 1597-602. doi:10.1248/bpb.29.1597

  • Chang, L., Zhu, H., Li, W., Liu, H., Zhang, Q., & Chen, H. (2005). Protective effects of amygdalin on hyperoxia-exposed type II alveolar epithelial cells isolated from premature rat lungs in vitro. Zhonghua er ke za zhi. Chinese journal of pediatrics, 43(2), 118-23.

  • Chen, Y., Ma, J., Wang, F., Hu, J., Cui, A., Wei, C., . . . Li, F. (2013). Amygdalin induces apoptosis in human cervical cancer cell line HeLa cells. Immunopharmacology and Immunotoxicology, 35(1), 43-51. doi:10.3109/08923973.2012.738688

  • Christopher, A. (2017). Drawing conclusions from data: descriptive statistics, inferential statistics, and hypothesis testing, In Interpreting and using statistics in psychological research. SAGE Publications Inc. doi:10.4135/9781506304144

  • Chye, F. Y., & Sim, K. Y. (2009). Antioxidative and Antibacterial Activities of Pangium edule Seed Extracts. International Journal of Pharmacology, 5, 285-97. doi:10.3923/ijp.2009.285.297

  • Clayden, J. (2001). Chapter 48. In Organometallic Chemistry (pp. 1311–1314). Oxford University Press.

  • Cömert, S., Akin, Y., Vitrinel, A., Telatar, B., Ağikuru, T., Gözü, H., . . . Turan, S. (2010). A mutation in thyroid hormone receptor beta causing "resistance to thyroid hormone" in a neonate. Minerva Pediatrics, 62(4), 419-22.

  • Curran, W. J. (1980). Law-medicine notes. Laetrile for the terminally ill: Supreme Court stops the nonsense. The New England Journal of Medicine, 302(11), 619-21. doi:10.1056/NEJM198003133021108

  • Daina, A., Michielin, O., & Zoete, V. (2014). iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach. Journal of Chemical Information and Modeling, 54(12), 3284-301. doi:10.1021/ci500467k

  • Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7(42717). doi:10.1038/srep42717

  • Damian, V., Sandu, A., Damian, M., Potra, F., & Carmichael, G. R. (2002). The Kinetic PreProcessor KPP -- A Software Environment for Solving Chemical Kinetics. Computers and Chemical Engineering, 26(11), 1567-79.

  • Davey, R. A., & Grossmann, M. (2016). Androgen Receptor Structure, Function and Biology: From Bench to Bedside. The Clinical biochemist, 37(1), 3-15.

  • Davignon, J. P., Trissel, L. A., & Kleinman, L. M. (1978). Pharmaceutical assessment of amygdalin (Laetrile) products. Cancer Treatment Reviews, 62(1), 99-104.

  • De Berardinis , R. J., Lum, J. J., Hatzivassiliou, G., & Thompson, C. B. (2008). The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metabolism, 7(1), 11-20. doi:10.1016/j.cmet.2007.10.002

  • Desegaulx, M., Sirdaarta, J., Rayan, P., Cock, I. E., & McDonnell, P. A. (2015). An examination of the anti-bacterial, anti-fungal and anti-Giardial properties of macadamia nut. Acta Horticulturae, 1106, 239-46. doi:10.17660/ActaHortic.2015.1106.36

  • Devillers, J., & Balaban, A. T. (1999). Topological Indices and Related Descriptors in QSAR and QSPR. Amsterdam, Netherlands: Gordon and Breach.

  • Devore, J. L. (2011). Probability and Statistics for Engineering and the Sciences (8th ed.). Boston, MA, US: Cengage Learning.

  • Di, L., & Kerns, E. (2008). Drug-like Properties: Concepts, Structure Design and Methods. Academic Press.

  • Dimitrov, S. D., Diderich, R., Sobanski, T., Pavlov, T. S., Chankov, G., Chapkanov, A., . . . Mekenyan, O. (2016). QSAR Toolbox – workflow and major functionalities. SAR and QSAR in Environmental Research, 27(3), 203-19. doi:10.1080/1062936X.2015.1136680

  • Do , J., Hwang, J., Seo, S., Woo, W., & Nam, S. (2008). Antiasthmatic activity and selective inhibition of type 2 helper T cell response by aqueous extract of semen armeniacae amarum. Immunopharmacology and Immunotoxicology, 28(2), 213-225. doi:10.1080/08923970600815253

  • Doak, B. C., Over, B., Giordanetto, F., & Kihlberg, J. (2014). Oral druggable space beyond the rule of 5: insights from drugs and clinical candidates. Chemistry & Biology, 21(9), 1115-42. doi:10.1016/j.chembiol.2014.08.013

  • Doan, T. B., Cheung, V., Clyne, C. D., Hilton, H. N., Eriksson, N., Young, M. J., . . . Graham, J. D. (2020). A tumour suppressive relationship between mineralocorticoid and retinoic acid receptors activates a transcriptional program consistent with a reverse Warburg effect in breast cancer. Breast Cancer Research volume, 22, 122. doi:10.1186/s13058-020-01355-x

  • Dral, P. O., Wu, X., Spörkel, L., Koslowski, A., & Thiel, W. (2016). Semiempirical Quantum-Chemical Orthogonalization-Corrected Methods: Benchmarks for Ground-State Properties. Journal of Chemical Theory and Computation, 12(3), 1097-120. doi:10.1021/acs.jctc.5b01047

  • DruLiTo, D. L. (2020, 12 23). Drug-likeness rules. Retrieved from http://www.niper.gov.in/pi_dev_tools/DruLiToWeb/DruLiTo_index.html

  • Durak, Z. E., Büber, S., Devrim, E., Kocaoğlu, H., & Durak, I. (2014). Aqueous extract from taxus baccata inhibits adenosine deaminase activity significantly in cancerous and noncancerous human gastric and colon tissues. Pharmacognosy magazine, 10(2), 214-16. doi:10.4103/0973-1296.133232

  • Eatemadi, A., Aiyelabegan, H. T., Negahdari, B., Mazlomi, M. A., Daraee, H., Daraee, N., . . . Sadroddiny, E. (2017). Role of protease and protease inhibitors in cancer pathogenesis and treatment. Biomedicine & Pharmacotherapy, 86, 221-31. doi:10.1016/j.biopha.2016.12.021

  • Ellison, N. M., Byar, D. P., & Newell, G. R. (1978). Special report on Laetrile: the NCI Laetrile Review. Results of the National Cancer Institute's retrospective Laetrile analysis. The New England Journal of Medicine, 299(10), 549-52. doi:10.1056/NEJM197809072991013

  • EPA, U. (2020, 10 15). Toxicity Estimation Software Tool /TEST/. Retrieved from https://www.epa.gov/chemical-research/toxicity-estimation-software-tool-test

  • Ertl, P., Rohde, B., & Selzer, P. (2000). Fast Calculation of Molecular Polar Surface Area as a Sum of Fragment-Based Contributions and Its Application to the Prediction of Drug Transport Properties. Journal of Medicinal Chemistry, 43(20), 3714-7. doi:10.1021/jm000942e

  • Evans, R. M., & Mangelsdorf, D. J. (2014). Nuclear Receptors, RXR, and the Big Bang. Cell, 157(1), 255-66. doi:10.1016/j.cell.2014.03.012

  • Femenia, A., Rossello, C., Mulet, A., & Canellas, J. (1995). Chemical Composition of Bitter and Sweet Apricot Kernels. Journal of Agricultural and Food Chemistry, 43(2), 356-61. doi:10.1021/jf00050a018

  • Fenselau, C., Pallante, S., Batzinger, R. P., Benson, W. R., Barron, R. P., Sheinin, E. B., & Maienthal, M. (1977). Mandelonitrile beta-glucuronide: synthesis and characterization. Science, 198(4317), 625-7. doi:10.1126/science.335509

  • Ferrari, T., & Gini, G. (2010). An open source multistep model to predict mutagenicity from statistical analysis and relevant structural alerts. Chemistry Central Journal, 4(1), 52. doi:10.1186/1752-153X-4-S1-S2

  • Ferrari, T., Cattaneo, G., Gini, N., Golbamaki Bakhtyari, N., Manganaro, A., & Benfenati, E. (2013). Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction. SAR and QSAR in Environmental, 24(5), 365-83. doi:10.1080/1062936X.2013.773376

  • Fifen, J. J., Nsangou, M., Dhaouadi, Z., Motapon, O., & Jaidane, N. (2011). Solvent effects on the antioxidant activity of 3,4-dihydroxyphenylpyruvic acid : DFT and TD-DFT studies. Computational and Theoretical Chemistry, 966(1-3), 232-43. doi:10.1016/j.comptc.2011.03.006

  • Fjodorova, N., & Novič, M. (2014). Comparison of criteria used to access carcinogenicity in CPANN QSAR models versus the knowledge-based expert system Toxtree . SAR and QSAR in Environmental Research, 25(6). doi:10.1080/1062936X.2014.898687

  • Fjodorova, N., Vračko, M., Novič, M., Roncaglioni, A., & Benfenati, E. (2010). New public QSAR model for carcinogenicity. Chemistry Central Journal, 4(1). doi:10.1186/1752-153X-4-S1-S3

  • FoodData. (1984/2004). FDC ID: 168462. NDB Number: 11457.

  • Foote, J., & Raman, A. (2000). A relation between the principal axes of inertia and ligand binding. National Academy of Sciences, 97(3), 978-83. doi:10.1073/pnas.97.3.978

  • Fukuda, T., Ito, H., Mukainaka, T., Tokuda, H., Nishino, H., & Yoshida, T. (2003). Anti-tumor promoting effect of glycosides from Prunus persica seeds. Biological and Pharmaceutical Bulletin, 26(2), 271-3. doi:10.1248/bpb.26.271

  • Gary, W. C., Zhengyin, Y., Wensheng, L., & Masucci, A. (2012). The IC50 Concept Revisited. Current Topics in Medicinal Chemistry, 12(11). doi:10.2174/156802612800672844

  • Ghandi, M., Huang, F. W., & Jané-Valbuena, J. (2019). Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature, 569, 503-8. doi:10.1038/s41586-019-1186-3

  • Ghose, A. K., Viswanadhan, V. N., & Wendoloski, J. J. (1999). A Knowledge-Based Approach in Designing Combinatorial or Medicinal Chemistry Libraries for Drug Discovery. 1. A Qualitative and Quantitative Characterization of Known Drug Databases. Journal of combinatorial chemistry, 1(1), 55-68. doi:10.1021/cc9800071

  • Gidopoulos, N. I., & Wilson, S. (2003). The Fundamentals of Electron Density, Density Matrix and Density Functional Theory in Atoms, Molecules and the Solid State. Springer Netherlands. doi:10.1007/978-94-017-0409-0

  • Gomez-Sanchez, E., & Gomez-Sanchez, C. E. (2014). The multifaceted mineralocorticoid receptor. Comprehensive Physiology, 4(3), 965-994. doi:10.1002/cphy.c130044

  • Gordon, M. S., & Schmidt, M. W. (2005). Advances in Electronic Structure Theory: GAMESS a Decade Later. In C. E. Dykstra, G. Frenking, K. S. Kim, & G. E. Scuseria, Theory and Applications of Computational Chemistry (pp. 1167-89). Amsterdam: Elsevier. doi:10.1016/b978-044451719-7/50084-6

  • Graham, D. Y. (1977). Enzyme replacement therapy of exocrine pancreatic insufficiency in man. The New England Journal of Medicine, 296, 1314-7. doi:10.1056/NEJM197706092962303

  • Greenberg, D. M. (1980). The case against laetrile: the fraudulent cancer remedy. Cancer, 45(4), 799-807. doi:10.1002/1097-0142(19800215)45:4<799::aid-cncr2820450432>3.0.co;2-6

  • Guo, J., Wu, W., Shen, M., Yang, S., & Tan, J. (2013). Amygdalin inhibits renal fibrosis in chronic kidney disease. Mol Med Rep, 7(5), 1453-7. doi:10.3892/mmr.2013.1391

  • Halgren, T. A. (1996). Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry, 17(5-6), 490-519. doi:10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P

  • Halgren, Т. А. (1996). Merck molecular force field. III. Molecular geometries and vibrational frequencies for MMFF94. Journal of Computational Chemistry, 17(5-6), 553-86. doi:10.1002/(SICI)1096-987X(199604)17:5/6%3C553::AID-JCC3%3E3.0.CO;2-T

  • Hall, J. M., & Greco, C. W. (2019). Perturbation of Nuclear Hormone Receptors by Endocrine Disrupting Chemicals: Mechanisms and Pathological Consequences of Exposure. Cells, 9(1), 13. doi:10.3390/cells9010013

  • Hansen, K., Mika, S., Schroeter, T., Sutter, A., Laak, A., Steger-Hartmann, T., . . . Müller, K. R. (2009). Benchmark data set for in silico prediction of Amesmutagenicity. Journal of Chemical Information and Modeling, 49(9), 2077-81. doi:10.1021/ci900161g

  • Harutyunyan, G. (2014). ARMANU - PRUNUS ARMENIACA: ORIGINATED IN ARMENIA. (A. Danielyan, Ed.) 21st Century, 2(16), 79-94. Retrieved from historical background of the native land of apricot versus modern information challenges: http://www.fundamentalarmenology.am/datas/pdfs/113.pdf

  • Heikkila, R. E., & Cabbat, F. S. (1980). The prevention of alloxan-induced diabetes by amygdalin. Life Sciences, 27(8), 659-62. doi:10.1016/0024-3205(80)90006-5

  • Herbert, V. (1979). Laetrile: the cult of cyanide. Promoting poison for profit. The American Journal of Clinical Nutrition, 32(5), 1121–58. doi:10.1093/ajcn/32.5.1121

  • Holland, J. C. (1982). Why patients seek unproven cancer remedies: a psychological perspective. CA Cancer J Clin, 32(1), 10-4. doi:10.3322/canjclin.32.1.10

  • Howard-Ruben, J., & Miller, N. J. (1984). Unproven methods of cancer management. Part II: Current trends and implications for patient care. Oncology Nursing Forum, 11(1), 67-73.

  • Hu, S., Xu, Y., Meng, L., Huang, L., & Sun, H. (2018). Curcumin inhibits proliferation and promotes apoptosis of breast cancer cells. Experimental and Therapeutic Medicine, 16(2), 1266-72. doi:10.3892/etm.2018.6345

  • Hubert, M., & Vandervieren, E. (2008). An adjusted boxplot for skewed distributions. Computational Statistics & Data Analysis, 52(12), 5186-201. doi:10.1016/j.csda.2007.11.008

  • Hughes, I., & Hase, T. (2010). Measurements and their Uncertainties: A practical guide to modern error analysis. Oxford University Press.

  • Hwang, H. J., Kim, P., Kim, C. J., Lee, H. J., Shim, I., Yin, C. S., . . . Hahm, D. H. (2008). Antinociceptive effect of amygdalin isolated from Prunus armeniaca on formalin-induced pain in rats. Biological and Pharmaceutical Bulletin, 31(8), 1559-1564. doi:10.1248/bpb.31.1559

  • Hwang, H. J., Lee, H. J., Kim, C. J., Shim, I., & Hahm, D. H. (2008). Inhibitory effect of amygdalin on lipopolysaccharide-inducible TNF-alpha and IL-1beta mRNA expression and carrageenan-induced rat arthritis. J Microbiol Biotechnol, 18(10), 1641-7.

  • Jablonsky, J., Haz, H., Burcova, Z., Kreps, F., & Jablonsky, J. (2019). Pharmacokinetic properties of biomass-extracted substances isolated by green solvents. Bioresources, 14(3), 6294-303. doi:10.15376/biores.14.3.6294-6303

  • Jacobsen, B. M., & Horwitz, K. B. (2012). Progesterone receptors, their isoforms and progesterone regulated transcription. Molecular and cellular endocrinology, 357(1-2), 18-29. doi:10.1016/j.mce.2011.09.016

  • Janiszewska, M., Primi, M. C., & Izard , T. (2020). Cell adhesion in cancer: Beyond the migration of single cells. Journal of Biological Chemistry, 295(8), 2495-505. doi:10.1074/jbc.REV119.007759

  • Jeliazkova, N., & Benfenati, E. (2020, 10). VEGA implementation of Cramer classification - v. 1.0.0. Retrieved from https://www.vegahub.eu/vegahub-dwn/qmrf/QMRF_CRAMER_TOXTREE.pdf

  • Jiagang, D., Li, C., Wang, H., Hao, E., Du, Z., Bao, C., . . . Wang, Y. (2011). Amygdalin mediates relieved atherosclerosis in apolipoprotein E deficient mice through the induction of regulatory T cells. Biochemical and Biophysical Research Communications, 411(3), 523-529. doi:10.1016/j.bbrc.2011.06.162

  • Juengel, E., Thomas, A., Rutz, J., Makarevic, J., Tsaur, I., Nelson, K., . . . Blaheta, R. A. (2016). Amygdalin inhibits the growth of renal cell carcinoma cells in vitro. International Journal of Molecular Medicine, 37(2), 526-32. doi:10.3892/ijmm.2015.2439

  • Kaczorowski, G. J., McManus, O. B., Priest, B. T., & Garcia, M. L. (2008). Ion channels as drug targets: the next GPCRs. Journal of general physiology, 131(5), 399-405. doi:10.1085/jgp.200709946

  • Kadam, R. U., & Roy, N. (2007). Recent trends in drug-likeness prediction: A comprehensive review of In silico methods. Indian Journal of Pharmaceutical Sciences, 69(5), 609-15. doi:10.4103/0250-474X.38464

  • Kalita, B. C., Das, A. K., Gupta, D. D., Hui, P. K., Gogoi, B. J., & Tag, H. (2018). GC-MS analysis of phytocomponents in the methanolic extract of Gynocardia odorataR.Br.-A poisonous plant from Arunachal Himalayan Region. Journal of Pharmacognosyand Phytochemistry, 7(1), 2458-63.

  • Karabulutlu, E. Y. (2014). Coping with stress of family caregivers of cancer patients in Turkey. Asia-Pacific Journal of Oncology Nursing, 1(1), 55-60. doi:10.4103/2347-5625.135822

  • Karakas, N., Okur, M. E., Ozturk, I., Ayla, S., Karadag, A. E., & Polat, D. Ç. (2019). Antioxidant Activity of Blackthorn (Prunus spinosa L.) Fruit Extract and Cytotoxic Effects on Various Cancer Cell Lines. Medeniyet medical journal, 34(3), 297-304. doi:10.5222/MMJ.2019.87864

  • Kato, S. (2000). The function of vitamin D receptor in vitamin D action. Journal of Biochemistry, 127(5), 717-22. doi:10.1093/oxfordjournals.jbchem.a022662

  • Keijzer, R., Blommaart, P. J., Labruyère, W. T., Vermeulen, J. L., Doulabi, B. Z., Bakker, O., . . . Lamers, W. H. (2007). Expression of thyroid hormone receptors A and B in developing rat tissues; evidence for extensive posttranscriptional regulation. Journal of Molecular Endocrinology, 38(5), 523-35. doi:10.1677/jme.1.02125

  • Khanna, V., & Ranganathan, S. (2009). Physiochemical property space distribution among human metabolites, drugs and toxins. BMC bioinformatics, 15. doi:10.1186/1471-2105-10-S15-S10

  • Kier, L. B., & Hall, L. H. (2002). The Meaning of Molecular Connectivity: A Bimolecular Accessibility Model. Croatica Chemica Acta, 75, 371-82. doi:10.1021/ci990135s

  • Klamt. (2005). COSMO-RS: From Quantum Chemistry to Fluid Phase Thermodynamics and Drug Design. Elsevier Science.

  • Klamt, A. (2018). The COSMO and COSMO‐RS solvation models. WIREs Computational Molecular Science, 8(1). doi:10.1002/wcms.1338

  • Kousparou, C. A., Epenetos, A. A., & Deonarain, M. P. (2002). Antibody-guided enzyme therapy of cancer producing cyanide results in necrosis of targeted cells. International Journal of Cancer, 99(1), 138-48. doi:10.1002/ijc.10266

  • Krakhmal, N. V., Zavyalova, M. V., Denisov, E. V., Vtorushin, S. V., & Perelmuter, V. M. (2015). Cancer Invasion: Patterns and Mechanisms. Acta Naturae, 7(2), 17-28.

  • Kristiansen, K. (2004). Molecular mechanisms of ligand binding, signaling, and regulation within the superfamily of G-protein-coupled receptors: molecular modeling and mutagenesis approaches to receptor structure and function. Pharmacology & Therapeutics, 103(1), 21-80. doi:10.1016/j.pharmthera.2004.05.002

  • Kříž, K., & Řezáč, J. (2019). Reparametrization of the COSMO Solvent Model for Semiempirical Methods PM6 and PM7. Journal of Chemical Information and Modeling, 01.

  • Kühne, R., Eber, R., & Schürmann, G. (2009). Chemical domain of QSAR models from atom-centered fragments. Journal of Chemical Information and Modeling, 49(12), 2660-9. doi:10.1021/ci900313u

  • Kwon, H. Y., Hong, S. P., Hahn, D. H., & Kim, J. H. (2003). Apoptosis induction of Persicae Semen extract in human promyelocytic leukemia (HL-60) cells. Archives of Pharmacal Research volume, 26(157). doi:10.1007/BF02976663

  • Kwon, Y. (2002). Handbook of Essential Pharmacokinetics, Pharmacodynamics and Drug Metabolism for Industrial Scientists. New York: Springer US. doi:10.1007/b112416

  • Lagares, L. M., Minovski, N., & Novič, M. (2019). Multiclass Classifier for P-Glycoprotein Substrates, Inhibitors, and Non-Active Compounds. (M. V. Diudea, Ed.) Molecules, 24(10). doi:10.3390/molecules24102006

  • Lagares, L., Minovski, N., Alfonso, A., Benfenati, E., Wellens, S., Culot, M., . . . Novič, M. (2020). Homology Modeling of the Human P-glycoprotein (ABCB1) and Insights into Ligand Binding through Molecular Docking Studies. International Journal of Molecular Sciences, 21(11), 4058. doi:10.3390/ijms21114058

  • Lang, P. F., & Smith, B. C. (2003). Ionization Energies of Atoms and Atomic Ions. Journal of Chemical Education, 80(8), 938. doi:/10.1021/ed080p938

  • Langmuir, I. (1917). The Shapes of Group Molecules Forming the Surfaces of Liquids. 4, 251-7. doi:10.1073/pnas.3.4.251

  • le Maire, A., Teyssier, C., Balaguer, P., Bourguet, W., & Germain, P. (2019). Regulation of RXR-RAR Heterodimers by RXR- and RAR-Specific Ligands and Their Combinations. Cells, 8(11), 1392. doi:10.3390/cells8111392

  • le Maire, L., Alvarez, S., Shankaranarayanan, P., Lera, A. R., Bourguet, W., & Gronemeyer, H. (2012). Retinoid receptors and therapeutic applications of RAR/RXR modulators. Current Topics in Medicinal Chemistry, 12(6), 505-27. doi:10.2174/156802612799436687

  • Leach, A. R. (2001). Molecular modelling : principles and applications. New York: Harlow.

  • Lee, H. M., & Moon, A. (2016). Amygdalin Regulates Apoptosis and Adhesion in Hs578T Triple-Negative Breast Cancer Cells. Biomolecules & Therapeutics, 24(1), 62-6. doi:10.4062/biomolther.2015.172

  • Lele, R. D. (2021). HISTORY OF MEDICINE IN INDIA. National Center of Indian Medical Heritage.

  • Lellau, T. F., & Liebezeit, G. (2003). Cytotoxic and Antitumor Activitiesof Ethanolic Extracts of Salt Marsh Plants from the Lower Saxonian Wadden Sea, Southern NorthSea. Pharmaceutical Biology, 41(4), 293-300. doi:10.1076/phbi.41.4.293.15668

  • Leo, A., Hansch, C., & Elkins, D. (1971). Partition coefficients and their uses. Chemical Reviews, 71(6), 525-616. doi:10.1021/cr60274a001

  • Li, X., Li, Y., Yu, C., Xue, W., Hu, J., Li, B., . . . Zhu, F. (2019). What Makes Species Productive of Anti-Cancer Drugs? Clues from Drugs' Species Origin, Druglikeness, Target and Pathway. Anti-Cancer Agents in Medicinal Chemistry, 19(2), 194-203. doi:10.2174/1871520618666181029132017

  • Liao, Z. G., Ling, Y., Zhong, Y., & Ping, Q. N. (2005). The simultaneous determination of laetrile, paeoniflorin and paeonol in Jingzhi Guizhi Fuling capsule by HPLC. Zhongguo Zhong Yao Za Zhi, 30(16), 1252-4.

  • Lipfert, L., Fischer, J. E., Wei, N., Scafonas, A., Su, Q., Yudkovitz, J., . . . Reszka, A. A. (2006). Antagonist-Induced, Activation Function-2-Independent Estrogen Receptor α Phosphorylation. Molecular Endocrinology, 20(3), 516-33. doi:10.1210/me.2005-0190

  • Lipinski, C. A., Feeney, P. J., Lombardo, F., & Dominy, B. W. (2001). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 46(1-3), 3-26. doi:10.1016/S0169-409X(00)00129-0

  • Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23(1-3), 3-25. doi:10.1016/S0169-409X(96)00423-1

  • Liton, M. A., Ali, M. I., & Hossain, M. T. (2012). Accurate pKa calculations for trimethylaminium ion with a variety of basis sets and methods combined with CPCM continuum solvation methods. Computational and Theoretical Chemistry, 999. doi:10.1016/j.comptc.2012.08.001

  • Maia, J. D., Carvalho, G. A., Mangueira Jr, C. P., Santana, S. R., Cabral, L. A., & Rocha, G. B. (2012). GPU Linear Algebra Libraries and GPGPU Programming for Accelerating MOPAC Semiempirical Quantum Chemistry Calculations. Journal of Chemical Theory and Computation, 8(9), 3072-81. doi:10.1021/ct3004645

  • Makarevic, J., Rutz, J., Juengel, E., Kaulfuss, S., Reiter, M., Tsaur, I., . . . Blaheta, R. A. (2014). Amygdalin Blocks Bladder Cancer Cell Growth In Vitro by Diminishing Cyclin A and cdk2. Plos One, 9(8). doi:journal.pone.0105590

  • Makarević, J., Rutz, J., Juengel, E., Kaulfuss, S., Tsaur, I., Nelson, K., . . . Blaheta, R. A. (2014). Amygdalin Influences Bladder Cancer Cell Adhesion and Invasion In Vitro. Plos One, 9(10). doi:10.1371/journal.pone.0110244

  • Makarević, J., Tsaur, I., Juengel, E., Borgmann, H., Nelson, K., Thomas, C., . . . Blaheta, R. A. (2016). Amygdalin delays cell cycle progression and blocks growth of prostate cancer cells in vitro. Life Sciences, 147, 137-42. doi:10.1016/j.lfs.2016.01.039

  • Manganaro, А. (2020). Carcinogenicity oral classification model (IRFMN) (version 1.0.0). Retrieved from QMRF identifier (JRC Inventory):To be entered by JRC: https://www.vegahub.eu/vegahub-dwn/qmrf/QMRF_SFO_CLASS.pdf

  • Marmolejo-Ramos, F., & Tian, T. (2010). he shifting boxplot. A boxplot based on essential summary statistics around the mean. International Journal of Psychological Research, 3(1), 37-45. doi:10.21500/20112084.823

  • Martin, T. M., & Young, D. M. (2001). Prediction of the Acute Toxicity (96-h LC50) of Organic Compounds in the Fathead Minnow (Pimephales Promelas) Using a Group Contribution Method. Chemical Research in Toxicology, 14(10), 1378-85. doi:doi.org/10.1021/tx0155045

  • Martin, T. M., Harten, R., Venkatapathy, S., & Young, D. M. (2008). A Hierarchical Clustering Methodology for the Estimation of Toxicity. Toxicology Mechanisms and Methods, 18(2), 251-66. doi:10.1080/15376510701857353

  • Martin, T. M., Lilavois, C. R., & Barron, M. G. (2017). Prediction of pesticide acute toxicity using two dimensional chemical descriptors and target species classification. SAR and QSAR in Environmental Research, 28(6), 525-39. doi:10.1080/1062936X.2017.1343204

  • Martone, R., Fulginei, F. R., & Salvini, A. (2007). Comparative analysis between modern heuristics and hybrid algorithms. COMPEL Int J for Computation and Maths in Electrical and Electronic, 26(2).

  • Mercader, A., Castro, E. A., & Toropov, A. A. (2001). Maximum Topological Distances Based Indices as Molecular Descriptors for QSPR. 4. Modeling the Enthalpy of Formation of Hydrocarbons from Elements. International Journal of Molecular Sciences, 2(2), 121-32. doi:10.3390/i2020121

  • Mezey, P. G. (1993). Shape in chemistry: an introduction to molecular shape and topology. VCH.

  • Milazzo, S., Ernst, E., Lejeune, S., Boehm, K., & Horneber, M. (2011). Laetrile treatment for cancer. Cochrane Database of Systematic Reviews, 9(11). doi:10.1002/14651858.CD005476.pub3

  • Milazzo, S., Lejeune, S., & Ernst, E. (2007). Laetrile for cancer: a systematic review of the clinical evidence. Supportive Care in Cancer, 15(6), 583-95. doi:10.1007/s00520-006-0168-9

  • Miller, K. W., Anderson, J. L., & Stoewsand, G. S. (1981). Amygdalin metabolism and effect on reproduction of rats fed apricot kernels. Journal of Toxicology and Environmental Health, 7(3-4), 457-67. doi:10.1080/15287398109529994

  • Mingos, D. P., & Wales, D. J. (1990). Introduction to cluster chemistry. Englewood Cliffs, N.J.

  • Mirkin, B. (2019). Core Data Analysis: Summarization, Correlation, and Visualization. Springer International Publishing.

  • Mirmiranpour, H., Khaghani, S., Zandieh, A., Khalilzadeh, O., Gerayesh-Nejad, S., Morteza, A., & Esteghamati, A. (2012). Amygdalin inhibits angiogenesis in the cultured endothelial cells of diabetic rats. Indian Journal of Pathology and Microbiology, 55(2), 211-4. doi:10.4103/0377-4929.97874

  • Moertel, C. G., Fleming, T. F., Rubin, J., Kvols, L. K., Sarna, G., Koch, R., . . . Davignon, P. (1982). A clinical trial of amygdalin (Laetrile) in the treatment of human cancer. The New England Journal of Medicine, 306(4), 201-6. doi:10.1056/NEJM198201283060403

  • Moertel, C. G., Fleming, T. R., Rubin, J., Kvols, L. K., Sarna, G., Koch, R., . . . Davignon, J. P. (1982). A Clinical Trial of Amygdalin (Laetrile) in the Treatment of Human Cancer. The New England Journal of Medicine, 306, 201-6. doi:10.1056/NEJM198201283060403

  • Molinspiration:. (2020, 12 29). Drug-likeness & bioactivity score. Retrieved from https://www.molinspiration.com/docu/miscreen/druglikeness.html

  • Moran, C., & Chatterjee, K. (2015). Resistance to thyroid hormone due to defective thyroid receptor alpha. Best practice & research. Clinical endocrinology & metabolism, 29(4), 647-57. doi:10.1016/j.beem.2015.07.007

  • Mortelmans, K., & Zeiger, E. (2000). The Ames Salmonella/microsome mutagenicity assay. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, 455(1-2), 29-60. doi:10.1016/S0027-5107(00)00064-6

  • Moya, C., Klamt, A., & Palomar, J. (2015). A Comprehensive Comparison of the IEFPCM and SS(V)PE Continuum Solvation Methods with the COSMO Approach. Journal of Chemical Theory and Computation, 11(9), 4220-5. doi:10.1021/acs.jctc.5b00601

  • Mueller, W. R., Szymanski, K., Knop, J. V., & Trinajstic, N. (1990). Molecular topological index. Journal of Chemical Information and Modeling, 30(2), 160-3. doi:10.1021/ci00066a011

  • Murray, J. S., & Sen, K. (1996). Molecular Electrostatic Potentials. Elsevier Science.

  • Nagasawa, T., Mathew, C. D., Mauger, J., & Yamada, H. (1988). Nitrile Hydratase-Catalyzed Production of Nicotinamide from 3-Cyanopyridine in Rhodococcus rhodochrous J1. Applied and Environmental Microbiology, 54(7), 1766-9.

  • National Center for Biotechnology Information. (2020, December 29). National Library of Medicine. Retrieved from https://pubchem.ncbi.nlm.nih.gov

  • Newmark, J., Brady, R. O., Grimley, P. M., Gal, A. E., Waller, S. G., & Thistlethwaite, J. R. (1981). Amygdalin (Laetrile) and prunasin beta-glucosidases: distribution in germ-free rat and in human tumor tissue. Proc Natl Acad Sci U S A, 78(10), 6513-6. doi:10.1073/pnas.78.10.6513

  • Nicolaides, N. C., Chrousos, G., & Kino, T. (updated 2020 Nov 21). Glucocorticoid Receptor. Retrieved from https://www.ncbi.nlm.nih.gov/books/NBK279171/

  • Ohlinger, W. S., Klunzinger, P. E., Deppmeier, B. J., & Hehre, W. J. (2009). Efficient Calculation of Heats of Formation†. The Journal of Physical Chemistry A, 113(10), 2165-75. doi:10.1021/jp810144q

  • Oprea, T. I. (2000). Property distribution of drug-related chemical databases. Journal of Computer-Aided Molecular Design, 14(3), 251-64. doi:10.1023/a:1008130001697

  • Otto, T., & Sicinski, P. (2017). Cell cycle proteins as promising targets in cancer therapy. Nature Reviews Cancer, 17, 93-115. doi:10.1038/nrc.2016.138

  • Ouyang, X., Zhou, S., To Su, C. T., Ge, Z., Li, R., & Kwoh, C. K. (2013). CovalentDock: automated covalent docking with parameterized covalent linkage energy estimation and molecular geometry constraints. Journal of Computational Chemistry, 34(4), 326-36. doi:10.1002/jcc.23136

  • Oxtoby, D. W., Gillis, H. P., & Campion, A. (2007). Principles of Modern Chemistry. Thomson/Brooks Cole.

  • Padilla, S., Corum, D., Padnos, B., Hunter, D., Beam, A., Houck, K., . . . Reif, D. (2012). Zebrafish developmental screening of the ToxCast™ Phase I chemical library. Reproductive Toxicology, 33(2), 174-87. doi:10.1016/j.reprotox.2011.10.018

  • Palm, K., Stenberg, P., & Luthman, K. (1997). Polar Molecular Surface Properties Predict the Intestinal Absorption of Drugs in Humans. Pharmaceutical Research, 14, 568-71. doi:10.1023/A:1012188625088

  • Paoletti, I., De Gregorio, V., Baroni, A., Tufano, M. A., Donnarumma, G., & Perez, J. J. (2013). Amygdalin analogues inhibit IFN-γ signalling and reduce the inflammatory response in human epidermal keratinocytes. Inflammation, 36, 1316–1326. doi:10.1007/s10753-013-9670-7

  • Park, H. J., Yoon, S. H., Han, L. S., Zheng, L. T., Jung, K. H., Uhm, Y. K., . . . Hong, S. P. (2005). Amygdalin inhibits genes related to cell cycle in SNU-C4 human colon cancer cells. World Journal of Gastroenterology, 11(33), 5156-61. doi:10.3748/wjg.v11.i33.5156

  • Paterni, I., Granchi, C., Katzenellenbogen, J. A., & Minutolo, F. (2014). Estrogen receptors alpha (ERα) and beta (ERβ): subtype-selective ligands and clinical potential. Steroids, 90, 13-29. doi:10.1016/j.steroids.2014.06.012

  • Paul, B. K., & Guchhait, N. (2011). TD–DFT investigation of the potential energy surface for Excited-State Intramolecular Proton Transfer (ESIPT) reaction of 10-hydroxybenzo[h]quinoline: Topological (AIM) and population (NBO) analysis of the intramolecular hydrogen bonding interaction. Journal of Luminescence, 131(9), 1918-26. doi:10.1016/j.jlumin.2011.04.046

  • Perez, J. J. (2013). Amygdalin analogs for the treatment of psoriasis. Future Medical Chemistry, 5(7), 799-808. doi:10.4155/fmc.13.27

  • Perrin, D. D., Dempsey, B., & Serjeant, E. P. (1981). pKa Prediction for Organic Acids and Bases. Springer, Dordrecht. doi:10.1007/978-94-009-5883-8

  • Petersilka, M., Gossmann, U. J., & Gross, E. K. (1996). Excitation Energies from Time-Dependent Density-Functional Theory. Physical Review Letters, 76(8), 1212. doi:10.1103/PhysRevLett.76.1212

  • Petitjean, M. (1992). Applications of the radius-diameter diagram to the classification of topological and geometrical shapes of chemical compounds. Journal of Chemical Information and Modeling, 32. doi:10.1021/ci00008a012

  • Pike, J. W., & Meyer, M. B. (2010). he vitamin D receptor: new paradigms for the regulation of gene expression by 1,25-dihydroxyvitamin D(3). Endocrinology and metabolism clinics of North America, 39(2), 255-69. doi:10.1016/j.ecl.2010.02.007

  • Politzer, P., & Laurence, P. R. (1985). Molecular electrostatic potentials: an effective tool for the elucidation of biochemical phenomena. Environmental Health Perspectives, 61, 191-202. doi:10.1289/ehp.8561191

  • Prabhu, D. S., Selvam, A. P., & Rajeswari, V. D. (2018). Effective anti-cancer property of Pouteria sapota leaf on breast cancer cell lines. Biochemistry and biophysics reports, 15, 39-44. doi:10.1016/j.bbrep.2018.06.004

  • Prajapati, R., Singh, U., Patil, A., Khomane, K., Bagul, P., Bansal, A., & Sangamwar, A. (2013). Metrics for comparing neuronal tree shapes based on persistent homology. Journal of Computer-aided Molecular Design, 347-63. doi:10.1007/s10822-013-9650-x

  • Priestman, T. (2012). Cancer Chemotherapy in Clinical Practice. London: Springer-Verlag.

  • Qian, L., Xie, B., Wang, Y., & Qian, J. (2015). Amygdalin-mediated inhibition of non-small cell lung cancer cell invasion in vitro. International Journal of Clinical and Experimental Pathology, 8(5), 5363-70.

  • Raghunand, N., He, X., van Sluis, R., Mahoney, B., Baggett, B., Taylor, C. W., . . . Gillies, R. J. (1999). Enhancement of chemotherapy by manipulation of tumour pH. British Journal of Cancer, 80(7), 1005-11. doi:10.1038/sj.bjc.6690455

  • Randic, M. (1975). Characterization of molecular branching. Journal of the American Chemical Society, 97(23), 6609–15. doi:10.1021/ja00856a001

  • Rauf, A. (2013). A dielectric study on human blood and plasma. International Journal of Science, Environment and Technology, 2(6), 1396-400.

  • Regan, P. T., Malagelada, J. R., DiMagno, E. P., & Gianzman, S. L. (1977). Comparative effects of antacids, cimetidine and enteric coating on the therapeutic response to oral enzymes in severe pancreatic insufficiency. The New England Journal of Medicine, 297, 854-8. doi:10.1056/NEJM197710202971603

  • Ren, P., Chun, J., Thomas, D. G., Schnieders, M. J., Marucho, M., Zhang, J., & Baker, N. A. (2012). Biomolecular electrostatics and solvation: a computational perspective. Quarterly Reviews of Biophysics, 45(4), 427-91. doi:10.1017/S003358351200011X

  • Ribeiro, T., Lemos, F., Preto, M., Azevedo, J., Sousa, M. L., Leão, P. N., . . . Urbatzka, R. (2017). Cytotoxicity of portoamides in human cancer cells and analysis of the molecular mechanisms of action. PLoS ONE, 12(12). doi:10.1371/journal.pone.0188817

  • Rossotti, F. J., & Rossotti, H. (1961). Chapter 2: Activity and Concentration Quotients. In McGraw–Hill, The Determination of Stability Constants.

  • Rouvray, D. H. (2002). The rich legacy of half a century of the Wiener index. In R. B. King, & D. H. Rouvray, Topology in Chemistry: Discrete Mathematics of Molecules (pp. 16-37). Horwood Publishing.

  • Sabudak, T., & Guler, N. (2009). Trifolium L.--a review on its phytochemical and pharmacological profile . Phytotherapy research : PTR, 23(3), 439-46. doi:10.1002/ptr.2709

  • Sakthivel, K. M., Kannan, N., Angeline, A., & Guruvayoorappan, C. (2012). Anticancer activity of Acacia nilotica (L.) Wild. Ex. Delile subsp. indica against Dalton's ascitic lymphoma induced solid and ascitic tumor model. Asian Pacific journal of cancer prevention : APJCP, 13(8), 3989-95. doi:10.7314/apjcp.2012.13.8.3989

  • Salahuddin, S., Farrugia, L., Sammut, C., O'Halloran, M., & Porter, E. (2017 ). Dielectric properties of fresh human blood. International Conference on Electromagnetics in Advanced Applications (ICEAA). Verona, Italy . doi:10.1109/ICEAA.2017.8065249

  • Salehi, B., Abu-Reidah, I. M., Sharopov, F., Karazhan, N., Sharifi-Rad, J., Akram, M., . . . Pezzani, R. (2021). Vicia plants-A comprehensive review on chemical composition and phytopharmacology. Phytotherapy research : PTR, 35(2), 790-809. doi:10.1002/ptr.6863

  • Sander, R. (2015). Compilation of Henry's law constants (version 4.0) for water as solvent. Atmospheric Chemistry and Physics, 15, 4399-981. doi:10.5194/acp-15-4399-2015

  • Sangster, J. M. (1997). Octanol-Water Partition Coefficients: Fundamentals and Physical Chemistry. Wiley.

  • Scarpin, K. M., Graham, J. D., Mote, P. A., & Clarke, C. L. (2009). Progesterone action in human tissues: regulation by progesterone receptor (PR) isoform expression, nuclear positioning and coregulator expression. Nuclear receptor signaling, 7. doi:10.1621/nrs.07009

  • Scatena, R., Bottoni, P., Pontoglio, A., Mastrototaro, L., & Giardina, B. (2008). Glycolytic enzyme inhibitors in cancer treatment. Expert Opinion on Investigational Drugs, 17(10), 1533-45. doi:10.1517/13543784.17.10.1533

  • Schürmann, G., & Klamt, A. (1993). COSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient. Journal of the Chemical Society, Perkin Transactions 2, 799-805. doi:10.1039/P29930000799

  • Scott, J. S., Bailey, A., Davies, R. D., Degorce, S. L., MacFaul, P. A., Gingell, H., . . . Smith, P. D. (2016). Tetrahydroisoquinoline Phenols: Selective Estrogen Receptor Downregulator Antagonists with Oral Bioavailability in Rat. Medicinal Chemistry Letters, 7(1), 94-9. doi:10.1021/acsmedchemlett.5b00413

  • Sebaugh, J. L. (2011). Guidelines for accurate EC50/IC50 estimation. Pharmaceutical Statistics, 10, 128-34. doi:10.1002/pst.426

  • Seigler, D. S., Pauli, G. F., Fröhlich, R., Wegelius, E., Nahrstedt, A., Glander, K. E., & Ebinger, J. E. (2005). Cyanogenic glycosides and menisdaurin from Guazuma ulmifolia, Ostrya virginiana, Tiquilia plicata, and Tiquilia canescens. Phytochemistry, 66(13), 1567-80. doi:10.1016/j.phytochem.2005.02.021

  • Seyfried, Т. N., & Huysentruyt, L. C. (2013). On the origin of cancer metastasis. Critical Reviews in Oncogenesis, 18(1-2), 43-73. doi:10.1615/critrevoncog.v18.i1-2.40

  • Shi, J., Chen, Q., Xu, M., Xia, Q., Zheng, T., Teng, J., . . . Fan, L. (2019). Recent updates and future perspectives about amygdalin as a potential anticancer agent: A review. Cancer Medicine, 8(6), 3004-11. doi:10.1002/cam4.2197

  • Shils, M. E., & Hermann, M. G. (1982). Unproved dietary claims in the treatment of patients with cancer. Bulletin of the New York Academy of Medicine, 58(3), 323-40.

  • Shim, S. M., & Kwon, H. (2010). Metabolites of amygdalin under simulated human digestive fluids. International Journal of Food Sciences and Nutrition, 61(8), 770-9. doi:10.3109/09637481003796314

  • Shishkovsky, K. R. (1980). Administrative law... Laetrile and other drugs to be used by the terminally ill are not exempt from the safety and effectiveness requirements of the Federal Food, Drug, and Cosmetic Act of 1938. Fordham Urban Law Journal, 57(2), 364-88.

  • Shoombuatong, W., Schaduangrat, N., & Nantasenamat, C. (2018). Towards understanding aromatase inhibitory activity via QSAR modeling. EXCLI Journal, 17, 688-708. doi:10.17179/excli2018-1417

  • Sims, M. T., Abbott, L. C., Cowling, S. J., Goodby, J. W., & Moore, J. N. (2017). Principal molecular axis and transition dipole moment orientations in liquid crystal systems: an assessment based on studies of guest anthraquinone dyes in a nematic host. Physical Chemistry Chemical Physics(19), 813-27. doi:10.1039/C6CP05979A

  • Smolensky, D., Rhodes, D., McVey, D. S., Fawver, Z., Perumal, R., Herald, T., & Noronha, L. (2018). High-Polyphenol Sorghum Bran Extract Inhibits Cancer Cell Growth Through ROS Induction, Cell Cycle Arrest, and Apoptosis. Journal of medicinal food, 21(10), 990-8. doi:10.1089/jmf.2018.0008

  • Soares, J., Greninger, P., Yang, W., Edelman, E. J., Lightfoot, H., Forbes, S., . . . Garnett, M. (2013). Genomics of Drug Sensitivity in Cancer: a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Research, 41(D1), D955-61. doi:10.1093/nar/gks1111

  • Song, Y., Wu, F., & Wu, J. (2016). Targeting histone methylation for cancer therapy: enzymes, inhibitors, biological activity and perspectives. Journal of Hematology & Oncology, 9, 49. doi:10.1186/s13045-016-0279-9

  • Song, Z., & Xu, X. (2014). Advanced research on anti-tumor effects of amygdalin. Journal of Cancer Research and Therapeutics, 1, 3-7. doi:10.4103/0973-1482.139743

  • Soprano, K. J., & Soprano, D. R. (2002). Retinoic Acid Receptors and Cancer. The Journal of Nutrition, 132(12), 3809S–13S. doi:10.1093/jn/132.12.3809S

  • Spalding, B. (1991). Cancer Immunoconjugates: Will Clinical Success Lead to Commercicial Success? Nature Biotechnology, 701-4. doi:10.1038/nbt0891-701

  • Spiegel, M. R. (1992). Theory and Problems of Probability and Statistics. New York: McGraw-Hill.

  • Srikanth, S., & Chen, Z. (2016). Plant Protease Inhibitors in Therapeutics-Focus on Cancer Therapy. Frontiers in Pharmacology, 7, 470. doi:10.3389/fphar.2016.00470

  • Steinbeck, C., Han, Y., Kuhn, S., Horlacher, O., Luttmann, E., & Willighagen, E. (2003). The Chemistry Development Kit (CDK):  An Open-Source Java Library for Chemo- and Bioinformatics. Journal of Chemical Information and Modeling, 43(2), 493-500. doi:10.1021/ci025584y

  • Stewart, J. (2021). Core-core repulsion integrals / MNDO modification to the core-core term. (Stewart Computational Chemistry) Retrieved from MOPAC: http://openmopac.net/manual/cc_rep_int.html

  • Stewart, J. J. (1989). Optimization of parameters for semiempirical methods I. Method. Journal of Computational Chemistry, 10(2), 209-20. doi:10.1002/jcc.540100208

  • Stewart, J. J. (2013). Optimization of parameters for semiempirical methods. Journal of Molecular Modeling, 19(1), 1-32. doi:10.1007/s00894-012-1667-x

  • Sun, H., Chen, L. C., Cao, S., Liang, Y., & Xu, Y. (2019). Warburg Effects in Cancer and Normal Proliferating Cells: Two Tales of the Same Name. Genomics Proteomics Bioinformatics, 17(3), 273-286. doi:10.1016/j.gpb.2018.12.006

  • Sushko, I., Novotarskyi, S., Körner, R., Pandey, A. K., Cherkasov, A., Li, J., . . . Tetko, I. V. (2010). Applicability domains for classification problems: benchmarking of distance to models for AMES mutagenicity set. Journal of Chemical Information and Modeling, 2094-2111. doi:10.1021/ci100253r

  • Swietach, P., Vaughan-Jones, R. D., Harris, A. L., & Hulikova, A. (2014). The chemistry, physiology and pathology of pH in cancer. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1638). doi:10.1098/rstb.2013.0099

  • Syrigos, K. N., Rowlinson-Busza, G., & Epenetos, A. A. (1998). In vitro cytotoxicity following specific activation of amygdalin by beta-glucosidase conjugated to a bladder cancer-associated monoclonal antibody. International Journal of Cancer, 78(6), 712-9. doi:10.1002/(SICI)1097-0215(19981209)78:6<712::AID-IJC8>3.0.CO;2-D

  • Szewczyk, M., Abarzua, S., Schlichting, A., Nebe, B., Piechulla, B., Briese, V., & Richter, D. U. (2014). Effects of extracts from Linum usitatissimum on cell vitality, proliferation and cytotoxicity in human breast cancer cell lines. Journal of Medicinal Plant Research, 8(5), 237-45. doi:10.5897/JMPR2013.5221

  • Taha, K. F., Khalil, M., & Abubakr, M. S. (2020). Identifying cancer-related molecular targets of Nandina domestica Thunb. by network pharmacology-based analysis in combination with chemical profiling and molecular docking studies. Journal of Ethnopharmacology, 249. doi:10.1016/j.jep.2019.112413

  • Takano, Y., & Houk, K. N. (2005). Benchmarking the Conductor-like Polarizable Continuum Model (CPCM) for Aqueous Solvation Free Energies of Neutral and Ionic Organic Molecules. Journal of Chemical Theory and Computation, 1(1), 70-7. doi:10.1021/ct049977a

  • Thole, J. M., Kraft, T. F., Sueiro, L. A., Kang, Y. H., Gills, J. J., Cuendet, M., . . . Lila, M. A. (2006). A comparative evaluation of the anticancer properties of European and American elderberry fruits. Journal of medicinal food, 9(4), 498-504. doi:10.1089/jmf.2006.9.498

  • Todeschini, R., Consonni, V., Mannhold, R., Kubinyi, H., & Timmerman, H. (2008). Handbook of Molecular Descriptors. John Wiley & Sons, Inc.

  • Todeschini, Р., & Consonni, V. (2009). Molecular Descriptors for Chemoinformatics. Wiley‐VCH. doi:10.1002/9783527628766

  • Tong, Y., Li, Z., Wu, Y., Zhu, S., Lu, K., & He, Z. (2020). Lotus Leaf Extract Inhibits the Cell Migration and Metastasis of ER- Breast Cancer. Nutrition & Metabolism. doi:10.21203/rs.3.rs-26733/v1

  • Toropov, A., Toropova, A., & Benfenati, E. (2020, 10). NOAEL (IRFMN/CORAL) - v. 1.0.0. (G. J. Lavado, Ed.) Retrieved from https://www.vegahub.eu/vegahub-dwn/qmrf/QMRF_NOAEL_IRFMN.pdf

  • Toropov, A., Toropova, A., Ritano, G., & Benfenati, E. (2019). CORAL: Building up QSAR models for the chromosome aberration test. Saudi Journal of Biological Sciences, 26(6), 1101-06. doi:10.1016/j.sjbs.2018.05.013

  • Toropova, A. P., Toropov, A. A., Benfenati, E., Rallo, R., Leszczynska, D., & Leszczynski, J. (2017). Development of Monte Carlo Approaches in Support of Environmental Research. Advances in QSAR Modeling, 453-69. doi:10.1007/978-3-319-56850-8_12

  • Tro, N. J. (2008). Chemistry: A Molecular Approach. Santa Barbara City College.

  • Tsanov, H., & Tsanov, V. (2021). Theoretical Study of the Process of Passage of Glycoside Amides through the Cell Membrane of Cancer Cell. Anti-Cancer Agents in Medicinal Chemistry, 21(12), 1612-1623. doi:10.2174/1871520620999201103201008

  • Tsanov, V., & Tsanov, H. (2020). Theoretical Analysis for the Safe Form and Dosage of Amygdalin Product. Anti-cancer Agents in Medicinal Chemistry, 20(7), 897-908. doi:10.2174/1871520620666200313163801

  • Tsanov, V., & Tsanov, H. (2022). Theoretical analysis of anticancer cellular effects of glycoside amides, Anticancer Agents Med Chem, 22(6):1171-1200, doi: 10.2174/1871520621666210903122831.

  • Unger, S. H. (1987). Molecular Connectivity in Structure–activity Analysis. Journal of Pharmaceutical Sciences, 76(3), 269-70. doi:10.1002/jps.2600760325

  • Valiña, A. L., Mazumder-Shivakumar, D., & Bruice, T. C. (2004). Probing the Ser-Ser-Lys Catalytic Triad Mechanism of Peptide Amidase:  Computational Studies of the Ground State, Transition State, and Intermediate. Biochemistry, 43(50), 15657-72. doi:10.1021/bi049025r

  • Veber, D. F., Johnson, S. R., Cheng, H. Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular Properties That Influence the Oral Bioavailability of Drug Candidates. Journal of Medicinal Chemistry, 45(12), 2615-23. doi:10.1021/jm020017n

  • Veerapagu, M., Latha, G., Ramanathan, K., & Jeya, K. R. (2020). A Study on the Determination of Phenol, Flavonoid Content and Antioxidant Potential of Manihot esculenta L. Tuber. Indian Journal of Natural Sciences , 10(59), 18682-9.

  • Vetter, J. (2000). Plant cyanogenic glycosides. Toxicon, 38(1), 11-36. doi:0.1016/S0041-0101(99)00128-2

  • Votano, J. R., Parham, M., Hall, L. H., Kier, L. B., Oloff, S., Tropsha, A., . . . Tong, W. (2004). Three new consensus QSAR models for the prediction of Ames genotoxicity. Mutagenesis, 19(5), 365-77. doi:10.1093/mutage/geh043

  • Wagnière, G. H. (1976). Introduction to Elementary Molecular Orbital Theory and to Semiempirical Methods. Springer-Verlag Berlin Heidelberg.

  • Wang, J., & Hou, T. (2011). Recent Advances on Aqueous Solubility Prediction. Combinatorial Chemistry & High Throughput Screening, 14(5), 328-38. doi:10.2174/138620711795508331

  • Wang, X., Dasari, S., Nowakowski, G. S., Lazaridis, K. N., Wieben, E. D., Kadin, M. E., . . . Boddicker, R. L. (2017). Retinoic acid receptor alpha drives cell cycle progression and is associated with increased sensitivity to retinoids in T-cell lymphoma. Oncotarget, 8(16), 26245-26255. doi:10.18632/oncotarget.15441

  • Wei, Y., Xie, Q., & Ito, Y. (2009). Preparative Separation of Axifolin-3-Glucoside, Hyperoside and Amygdalin from Plant Extracts by High Speed Countercurrent Chromatography. Journal of Liquid Chromatography & Related Technologies, 32(7), 1010-22. doi:10.1080/10826070902790983

  • Welsh, I. D., & Allison, J. R. (2019). Automated simultaneous assignment of bond orders and formal charges. Journal of Cheminformatics, 11, 18. doi:10.1186/s13321-019-0340-0

  • WHAT MAKES ARMENIA SPECIAL? (2016, August 30). Retrieved from ArmeniaTourInfo: https://www.armeniatourinfo.com/what-makes-armenia-special/

  • Wu, S., Fischer, J., Naciff, J., Laufersweiler, M., Lester, C., Daston, G., & Blackburn, K. (2013). Framework for Identifying Chemicals with Structural Features Associated with the Potential to Act as Developmental or Reproductive Toxicants. Chemical Research in Toxicology, 26(12), 1840-61. doi:10.1021/tx400226u

  • Yamaguchi, H., Wyckoff, J., & Condeelis, J. (2005). Cell migration in tumors. Current Opinion in Cell Biology, 17(5), 559-64. doi:10.1016/j.ceb.2005.08.002

  • Yang, D., Qiu, M., Zou, L. Q., Zhang, W., Jiang, Y., Zhang, D. Y., & Yan, X. (2012). The role of palliative chemotherapy for terminally ill patients with advanced NSCLC. Thoracic Cancer, 4(2), 153-160. doi:10.1111/j.1759-7714.2012.00148.x

  • Yang, H. Y., Chang, H. K., Lee, J. W., Kim, Y. S., Kim, H., Lee, M. H., . . . Kim, C. J. (2013). Amygdalin suppresses lipopolysaccharide-induced expressions of cyclooxygenase-2 and inducible nitric oxide synthase in mouse BV2 microglial cells. Neurological Research, 59-64. doi:10.1179/016164107X172248

  • Yordanova, D., Schultz, T., Kuseva, C., Tankova, K., Ivanova, H., Dermen, I., . . . Mekenyan, O. (2019). Automated and standardized workflows in the OECD QSAR Toolbox. Computational Toxicology, 10, 89-104. doi:10.1016/j.comtox.2019.01.006

  • Young, D. C. (2001). Computational Chemistry: A Practical Guide for Applying Techniques to Real World Problems. John Wiley & Sons, Inc. doi:10.1002/0471220655

  • Young, D. M., Martin, T. M., Venkatapathy, R., & Harten, P. (2008). Are the Chemical Structures in your QSAR Correct? QSAR & Combinatorial Science, 27(11-12), 1337-45. doi:10.1002/qsar.200810084

  • Young, K. H., Pyo, H. S., Hoon, H. D., & Hee, K. J. (2003). Apoptosis induction of persicae semen extract in human promyelocytic leukemia (hl-60) cells. Archives of Pharmacal Research, 26, 157. doi:10.1007/BF02976663

  • Yulvianti, M., & Zidorn, C. (2021). Chemical Diversity of Plant Cyanogenic Glycosides: An Overview of Reported Natural Products. Molecules, 26(3), 719. doi:10.3390/molecules26030719

  • Yusof, I., & Segall, M. D. (2013). Considering the impact drug-like properties have on the chance of success. Drug Discovery Today, 18(13-14), 659-66. doi:10.1016/j.drudis.2013.02.008

  • Zhao, L., Zhou, S., & Gustafsson, J. Å. (2019). Nuclear Receptors: Recent Drug Discovery for Cancer Therapies. Endocrine Reviews, 40(5), 1207-49. doi:10.1210/er.2018-00222

  • Zhou, C., Qian, L., Ma, H., Yu, X., Zhang, Y., Qu, W., . . . Xia, W. (2012). Enhancement of amygdalin activated with β-D-glucosidase on HepG2 cells proliferation and apoptosis. Carbohydrate Polymers, 90(1), 516-23. doi:10.1016/j.carbpol.2012.05.073

  • Zhou, Y., & Liu, X. (2020). The role of estrogen receptor beta in breast cancer. Biomarker Research, 8(39). doi:10.1186/s40364-020-00223-2

  • Zhu, H., Martin, T. M., Young, D. M., & Tropsha, A. (2009). Combinatorial QSAR Modeling of Rat Acute Toxicity by Oral Exposure. Chemical Research in Toxicology, 22(12), 1913-21. doi:10.1186/1752-153X-4-S1-S4

  • Zhu, Y. P., Su, Z. W., & Li, C. H. (1994). Analgesic effect and no physical dependence of amygdalin. Zhongguo Zhong Yao Za Zhi, 19(2), 105-7.

  • Zubatyuk, R., Smith, J. S., Leszczynski, J., & Isayev, O. (2019). Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network. Science Advances, 5(8). doi:10.1126/sciadv.aav6490

  • Божанов, Е., & Вучков, И. (1973). Статистически методи за моделиране и оптимизиране на многофакторни обекти. София: "Техника".

  • Бошев, Н., Полнарев, Б., Атанасов, К., Бошева, М., Занзов, И., Кръстанев, И., . . . Янев, П. (1986). Биологичните константи на човека. София: Държавно издателство "Медицина и физкултура".

  • Петров, Г. (1996/2019). Органична химия. София: Университетско издателство СУ "Св.Климент Охридствки".

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