Docking the New Drug of Lung Cancer
Cancer refers to the abnormal growth of cells resulting in the formation of a mass of cells.[1] Cancerous cells do not undergo through cell induced death and hence have degree of viability. Cancerous cells can be malignant of benign. Often, benign tumors do not cause health problems and do not spread to other body parts while malignant tumors do. Lung cancer is the type of cancer that starts in the lungs often in the bronchi lining.[2] It is the most prevalent type of cancer in the world and is mostly caused by smoking.[3]
Types of lung cancer
Lung cancer is classified into two primary types. These classifications include non-small cell lung carcinoma (NSCLC) and small cell lung carcinoma (SCLC).[4] SCLC accounts for about 20-25% of lung cancers. SCLC cells are small and have rapid growth rate.[5] On the other hand, NSCLC accounts for 75-80% of lung cancers. Julie explains that the growth and manner of spreading of these two types vary.[6] Moreover, NSCLC and NSCLC show different response to cancer treatments and hence proper diagnosis of the exact type is essential.
Examples of drugs for the treatment of Lung Cancer
Drugs used in the treatment of lung cancer depends on the type involved. Some of the drugs used in the treatment of NSCLC include Bevacizumab, Certinib, Cetuximab, Docetaxel, Crizotinib, Gefitinib, Gilotrif, Irinotecan, Paclitaxel, Ramucirumab, Pemetrexed and Cisplatin.[7] Drugs used in the treatment of SCLC include such as Cisplatin, Docetaxel, Etoposide, Carboplatin, Vinblastine, Topotecan Hydrochloride and Etoposide.[8]
Examples of side effects
Chemotherapy is associated with various side effects. For instance, Addario explains that chemotherapy is associated with nausea, loss of hair, reduced level of white and red blood cells, fatigue, change of skin and nails and peripheral neuropathy.[9] Moreover, chemotherapy can cause infertility, heart and lung damage, and disease to the bones. Consequently, lung cancer results in decreased life quality with poor health. The cost of life for individuals with lung cancer is very high.
Systems Biology approach-detect side effects: Intermolecular Interaction Examination
As earlier mentioned, various treatments are often associated with diverse side effects. The diverse effects exhibited by lung cancer treatments are due to the complexity of the disease.[10] The pathogenesis of cancer is complex because it is associated with various factors that interact to cause it. Some of the factors that are associated with cancer include genetics, environmental and diet. Lung cancer patients often exhibit diverse side effects. Hartwell explains that the treatment of cancer is associated with changes in the genetic composition.[11] Such changes cause differences in the effects of the drug due to changes in molecular interactions in the body.[12] The biological functioning of proteins depends on their molecular interactions with other proteins. Consequently, there are complex protein networks whose interactions might offer indispensable insights regarding cancer’s drug design to curtail possible side effects. Such study of the progressive interaction of proteins in the body can be studied using systems biology approach.
The systems approach allows for the study of the complex molecular interaction in the body.[13] Wolkenhauer and colleagues explain that systems biology approach (referred to as SBA henceforth) is essential for the future of cancer treatment for various reasons. For instance, SBA would help in the personalization of lung cancer drugs for patients in various stages. SBA would also help in identifying early markers to allow for non-invasive prognosis depending on the development of cancer. Moreover, SBA would allow the improvement of lung cancer treatment by allowing comparison of gene expression and the biochemical interactions in cancerous cells.[14] This paper evaluates the later role of SBA in identifying the various side effects of drugs as a method of improving treatment.
There exist various SBA methods that can be used to provide insights regarding the oncogenesis of cancer. Such SBA methods include such as database screening, molecular docking, 3D QSAR pharmacophore modeling and Density Functional Theory (DFT) calculations.[15] These methods are used to study various biomarkers such as chymase inhibitors and human epidermal growth factor receptor 2 (HER2).[16] These methods allow for the evaluation of the entire regulatory and signaling pathway. For instance, QSAR is essential for quantitatively understanding molecular structures relationships with their biological functions.[17] The pharmacophore model is essential in identifying compounds that have features that are chemically similar to that in question.[18] The interaction of cancer drugs with these molecular structures are then studied. Molecular docking approach is for evaluation of interactions and affinity of the binding sites for the various biological compounds.
From an earlier discussion, cancer drugs were explained to exhibit diverse side effects due to high molecular heterogeneity and genome plasticity.[19] With the use of SBA, it would be possible to identify molecular interactions in an individual to allow for a novel and personalized treatment scheme. This personalization is due to an understanding of the molecular interaction and hence possible side effects in various treatment regimes.
Bibliography
Addario, Bonnie J. “Navigating Lung Cancer.” Lung Cancer Foundation.
Arooj, Mahreen, Sugunadevi Sakkiah, Guang Ping Cao, Songmi Kim, Venkatesh Arulalapperumal, and Keun Woo Lee. “Finding off‐targets, biological pathways, and target diseases for chymase inhibitors via structure‐based systems biology approach.” Proteins: Structure, Function, and Bioinformatics(2015).
Arooj, Mahreen, Sundarapandian Thangapandian, Shalini John, Swan Hwang, Jong Keun Park, and Keun Woo Lee. “3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors.” International journal of molecular sciences 12, no. 12 (2011): 9236-9264.
Driscoll, Barbara. “Lung cancer”. Totowa: N.J. (2003).
Falk, Stephen A., and C. J. Williams. 2010. Lung cancer. Oxford: Oxford University Press.
http://public.eblib.com/choice/publicfullrecord.aspx?p=516283
Hartwell, Lee, David Mankoff, Amanda Paulovich, Scott Ramsey, and Elizabeth Swisher. “Cancer biomarkers: a systems approach.” Nature biotechnology 24, no. 8 (2006): 905-908.
Henderson, David, Lesley A. Ogilvie, Nicholas Hoyle, Ulrich Keilholz, Bodo Lange, Hans Lehrach, and OncoTrack Consortium. “Personalized medicine approaches for colon cancer driven by genomics and systems biology: OncoTrack.” Biotechnology journal 9, no. 9 (2014): 1104-1114.
Minna, John D., Jack A. Roth, and Adi F. Gazdar. “Focus on lung cancer.”Cancer cell 1.1 (2002): 49-52.
Walker, Julie. Lung cancer: current and emerging trends in detection and treatment. New York: Rosen Pub. Group (2006).
Wolkenhauer, Olaf, D. Fell, P. De Meyts, N. Blüthgen, H. Herzel, N. Le Novere, T. Höfer, K. Schürrle, and I. Van Leeuwen. “SysBioMed report: advancing systems biology for medical applications.” IET systems biology 3, no. 3 (2009): 131-136.
[1] Walker, Julie. Lung cancer: current and emerging trends in detection and treatment (New York: Rosen Pub. Group), 7.
[2] Falk, Stephen A., and C. J. Williams. “Lung cancer,” Oxford: Oxford University Press (2010): 4.
[3] Minna, John, Jack, Roth, and Adi, Gazdar, ”Focus on lung cancer,” Cancer Cell 1.1 (2002): 49.
[4] Driscoll, Barbara, “Lung cancer,” Totowa: N.J. (2003): 3.
[5] Walker, Lung cancer, 9.
[6] Ibid
[7] Addario, Bonnie J. “Navigating Lung Cancer,” Lung Cancer Foundation,66-69.
[8] Ibid.
[9] Ibid.
[10] Arooj, Mahreen, Sugunadevi Sakkiah, Guang Ping Cao, Songmi Kim, Venkatesh Arulalapperumal, and Keun Woo Lee. “Finding off‐targets, biological pathways, and target diseases for chymase inhibitors via structure‐based systems biology approach.” Proteins: Structure, Function, and Bioinformatics(2015): 1209.
[11] Hartwell, Lee, David Mankoff, Amanda Paulovich, Scott Ramsey, and Elizabeth Swisher. “Cancer biomarkers: a systems approach.” Nature biotechnology 24, no. 8 (2006): 905.
[12] Arooj, Mahreen, Sugunadevi Sakkiah, Guang Ping Cao, Songmi Kim, Venkatesh Arulalapperumal, and Keun Woo Lee. “Finding off‐targets, biological pathways, and target diseases for chymase inhibitors via structure‐based systems biology approach.” Proteins: Structure, Function, and Bioinformatics(2015): 1209.
[13] Wolkenhauer, Olaf, D. Fell, P. De Meyts, N. Blüthgen, H. Herzel, N. Le Novere, T. Höfer, K. Schürrle, and I. Van Leeuwen. “SysBioMed report: advancing systems biology for medical applications.” IET systems biology 3, no. 3 (2009): 131-134.
[14] Ibid.
[15] Arooj, Mahreen, Sundarapandian Thangapandian, Shalini John, Swan Hwang, Jong Keun Park, and Keun Woo Lee. “3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors.” International journal of molecular sciences 12, no. 12 (2011): 9236.
[16] Henderson, David, Lesley A. Ogilvie, Nicholas Hoyle, Ulrich Keilholz, Bodo Lange, Hans Lehrach, and OncoTrack Consortium. “Personalized medicine approaches for colon cancer driven by genomics and systems biology: OncoTrack.” Biotechnology journal 9, no. 9 (2014): 1106.
[17] Arooj, 3D QSAR pharmacophore , 9238-1940.
[18] Ibid.
[19] Henderson, Personalized medicine, 1106.
