Title:Lead Optimization Resources in Drug Discovery for Diabetes
Volume: 19
Issue: 6
Author(s): Pragya Tiwari*, Ashish Katyal, Mohd F. Khan, Ghulam Md. Ashraf* Khurshid Ahmad*
Affiliation:
- Department of Biotechnology, MG Institute of Management and Technology, Lucknow-Kanpur Road, Lucknow,India
- King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589,Saudi Arabia
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan,Korea
Keywords:
Computational biology, diabetes, drug discovery, e-resources, quantitative structure-activity relationship, therapeutic
targets.
Abstract:
Background: Diabetes, defined as a chronic metabolic syndrome, exhibits global prevalence
and phenomenal rise worldwide. The rising incidence accounts for a global health crisis, demonstrating a
profound effect on low and middle-income countries, particularly people with limited healthcare facilities.
Methods: Highlighting the prevalence of diabetes and its socio-economic implications on the population
across the globe, the article aimed to address the emerging significance of computational biology
in drug designing and development, pertaining to identification and validation of lead molecules for
diabetes treatment.
Results: The drug discovery programs have shifted the focus on in silico prediction strategies minimizing
prolonged clinical trials and expenses. Despite technological advances and effective drug therapies,
the fight against life-threatening, disabling disease has witnessed multiple challenges. The lead optimization
resources in computational biology have transformed the research on the identification and optimization
of anti-diabetic lead molecules in drug discovery studies. The QSAR approaches and
ADMET/Toxicity parameters provide significant evaluation of prospective “drug-like” molecules from
natural sources.
Conclusion: The science of computational biology has facilitated the drug discovery and development
studies and the available data may be utilized in a rational construction of a drug ‘blueprint’ for a particular
individual based on the genetic organization. The identification of natural products possessing
bioactive properties as well as their scientific validation is an emerging prospective approach in antidiabetic
drug discovery.
