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IN SILICO EVALUATION ON THE INTERACTION BETWEEN KETONE BODIES AND OBESITY-ASSOCIATED PROTEINS

  • Project Research
  • 1-5 Chapters
  • Qualitative
  • Library / Doctrinal
  • Abstract : Available
  • Table of Content: Available
  • Reference Style: APA
  • Recommended for : Student Researchers
  • NGN 3000

Background of study

Obesity, has been a pre-existing problem afore time but has been recognized as a global pandemic since the 21st century (Natalia, et al., 2021). Aronne, 2002 defines obesity as the anomalous, irregular or disproportionate gain of weight as a result of fat buildup in the body which adversely leads to the risk of several health related problems such as hypertension, type 2 diabetes, cardiovascular diseases and certain cancer types amongst others (Aronne, 2002; Natalia, et al., 2021; Williams, et al., 2015).

Obesity calculation is based on body mass index ≥ 30kg/m2 which is the measurement of fat buildup by dividing body mass (kg) by the square of the body height (m2) (Aronne, 2002; Kopelman, 2000). In 2016, WHO (world health organization) acknowledged that nearly 2-billion adults worldwide were measured to be overweight and 650 million of that population were found to be obese. The WHO, also estimated that 50% of the population found in Europe had preeminent body weight which could lead to obesity overtime (WHO, 2016).

Furthermore in 2002, certain rural areas in Nigeria were recorded to have a high rate of obesity at 33.7% (Ogah, 2013). Obesity mechanism, involves a complex process and certain physical and biochemical factors have been found to induce this condition some of which include unhealthy diets and eating habits, high calorie food consumption, genetic, epigenetic, and ecological factors. All these factors combined together with the lack of physical activity to burn excess body weight then lead to energy disproportion and fat deposition (William, et al., 2015; Lin, et al., 2017). Due to obesity prevalence overtime, several solutions and control measures have been brought up to ameliorate as well as control the condition. Some of these measures, include physical activity programmes, behavioral lifestyle programmes, pharmacotherapy, diet management, and in severe obese conditions bariatric surgery is recommended (Gonzalez-Muniesa, et al., 2017).

Caloric inhibition, a diet management scheme and nutritional strategy is the commonly used weight loss mechanism as far as diet management is concerned and this research focuses on the use of ketogenic diet which was used successfully in the therapy of epilepsy, as a control measure for obesity (Anton, et al., 2017; Ulamek-Koziol, et al., 2019).

Ketogenic diet is made up of an augmented fat content, minimal carbohydrate content and sufficient amount of protein content. As a result of the proportionate amount of nutrient in the diet composition, there is reduced metabolism of carbohydrate and protein but increased metabolism of fat (Kayode, et al., 2020).

Consequent fat breakdown and reduced carbohydrate and protein breakdown, then leads to reduced blood glucose levels and the stimulation of ketogenesis in the liver which produces increased levels of ketone bodies and fatty acids (Sanjay, et al., 2018; Kulaka and Polotsky, 2013). The resulting ketone bodies are then transported to the blood brain barrier to make available energy for the brain and increased levels of the ketone bodies lead to increased levels of substrates such as creatine, adenine triphosphate (ATP), and phosphocreatine that are essential in the brain (Kayode, et al., 2021; Sanjay, et al., 2018).

 

1.2 Statement of the Problem and objective of study

Obesity, is a predominant disease occurring in a yearly estimate of over 2 billion individuals as a result of excessive fat buildup and this has led to numerous health issues and conditions. With the prevalence of obesity in recent times, several control measures were proposed so as to ameliorate the condition. This study aims at exploring the efficiency of ketogenic diet generated ketone bodies in the prevention and amelioration of obesity using in silico simulations.





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