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In Silico Magic in Drug Discovery: Quest for Dengue Therapeutics

In this modern medical era, scientists are putting in a lot of effort to discover new and potential drugs to treat diseases. A team of Assoc. Prof. ChM Dr. Rozana Othman from the Faculty of Pharmacy, Universiti Malaya, is endlessly working to search for a new drug to treat dengue infections using a high-tech computer-based drug discovery approach that may herald a new era in anti-dengue viral therapeutics.


Dr. Othman and her research team are on a mission to find an effective treatment for dengue, which is a serious burden type of disease in tropical and sub-tropical climate regions. Dengue is a neglected tropical disease that spreads from mosquitoes to humans. There is no specific treatment for dengue, but some pre-existing antiviral medicines have been repurposed as anti-dengue but are reported to be mild in effectiveness. Thus, scientists from Universiti Malaya are turning to advanced computer programming tools to screen the derivatives of the pre-established antiviral compounds called Spirooxindole.


Figure 1: Aedes aegypti: Primary vector of dengue:

Spirooxindoles a promising class of antiviral drugs due to their structural and drug-like properties. The unique 3D structures comprising different spiro rings with patterns that resemble those in nature make them attractive for this research study. They are highly effective against viruses, do not easily develop resistance, work against different viruses, and are less likely to be toxic. Therefore, the primary focus of this research is to discover the synthetic or naturally occurring derivatives of Spirooxindoles, which have great potential in treating dengue illnesses.


According to Dr. Othman, besides working on Spirooxindoles, more than 15,000 compounds have been screened till now, and potential 3-4 compounds have been set for the anti-dengue drug discovery through a computational approach. Free and commercially available molecular docking and molecular dynamic simulation tools such as Auto dock Vina, Schrodinger, Pymol, Biovia Discovery Studio, Chimera, AMBER etc. are employed for the initial investigation of the binding of compounds to the enzyme of the dengue virus. After finding the promising drug candidates for the dengue virus using computational tools, the next step is experimentation in the laboratory to find their efficacy against dengue. The wet lab experiment will be used to validate the computational results to see whether the screened compounds are inhibiting the virus proteins. There is more plan on the collaborative research on the animal model of dengue virus with several universities to give this project a better understanding and establish the potential drug candidates for clinical trials.

Figure 2: Spirooxindole as pre-established antiviral agent
(Reference: Ye N, Chen H, Wold EA, Shi PY, Zhou J. Therapeutic Potential of Spirooxindoles as Antiviral Agents. ACS Infect Dis. 2016 Jun 10;2(6):382-92)

In the era of rapid drug discovery, computational tools have imparted a pivotal role as a time saviour and cost minimisation in screening and discovering novel drugs against fatal diseases. It is like a pre-screening computational algorithm that brings forth the top-potential compounds, making it easier for the scientists to shift one step closer to further experimental design in the laboratory and animal models.

The most interesting and exciting thing about working with computational drug discovery is that one can visualise how the compounds interact with the virus at a molecular level and where the compounds perfectly fit into the active sites of the viral proteins. However, despite these advantages, there are challenges. The servers, like guardians of computational drug discovery, can be tough to deal with. The process may seem easy after getting the resultant image, but behind the scenes, artificial intelligence (AI) and machine learning can enhance the output by performing complex programming to produce meaningful results. This computational drug discovery approach requires not only scientific knowledge but also a deep understanding of computer tools, coding, and the intricate patterns of machine learning.

Figure 3: Predictive AI machine learning and computational drug discovery over traditional drug discovery approach

This study aims to provide a comprehensive understanding of the inhibitory mechanism demonstrated by Spirooxindole derivatives and many other compounds in visually insightful 3D representations. It allows the visualisation of interaction sites, which provide insights into the potential of the screened compounds against dengue. Moreover, computational analysis enables the evaluation of diverse aspects pertaining to medications, such as pH, toxicity, and involvement of potential biological pathways. Furthermore, it is also possible to make predictions on the pharmacokinetics of the compounds, including several factors like absorption, distribution, metabolism, and excretion. Thus, the computational approach for screening prospective drug candidates for dengue therapy, with Spirooxindole as the core molecule, becomes more efficient, saving both time and budget.


Researchers featured:

Associate Professor Dr. Rozana Othman
Department of Pharmaceutical Chemistry
Faculty of Pharmacy, Universiti Malaya
Associate Professor Dr. Nurshamimi Nor Rashid
Department of Molecular Medicine
Faculty of Medicine, Universiti Malaya
Professor Dr. Noorsaadah Abd Rahman
Universiti Malaya
Ke Han Tan, Yean Kee Lee, Choon Han Heh & Nurshamimi Nor Rashid
Author: Ashok Kumar Mandal
I am Ashok Kumar Mandal, from the beautiful country Nepal. Currently, I am a postgraduate student at the Faculty of Medicine, Universiti Malaya, Malaysia pursuing a Master of Medical Science.
My main area of study is researching new drugs to reduce the problems that obesity causes with blood vessels and how those problems affect high blood pressure. My academic interests are centered around natural product chemistry, cardiovascular research, public health, and nano-formulation for cancers, underscoring my dedication to advancing scientific knowledge in these areas.
Siti Farhana Bajunid Shakeeb Arsalaan Bajunid
Assistant Registrar, Universiti Malaya


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