Background The ORF1ab of Severe Acute Respiratory Syndrome, SARS Corona Virus, SARS-CoV-2 genome is processed into 15 non-structural proteins, NSPs by proteases and each NSP has a specific role in the life cycle and pathogenicity of the virus. This research analyzes possible drugs for these proteins as targets in computational drug designing using already available experimental drugs from the drug bank database. Methods Out of 471 proteins and 8820 drugs download from Protein Data Bank, PDB and Drug Bank database respectively, 16 proteins similar to NSP 1–15 and 31 drugs as per the “Rule of three” were selected for docking. Out of 88 docking results using PyRx, 18 proteins/chains with three promising drugs, DB01977, DB07132 and DB07535 were analyzed using PyMOL for final results. Results NSPs 3, 5, 11, 14 and 15 were identified as targets for the drugs, DB01977, BD07132 and DB07535. Drugs, DB01977 and DB07535 bind in the same binding pockets of NSP 5 and NSP 15. Drug, DB07132 binds with more number of residues when compared with the other two drugs and this indicates that the strength of protein-drug association is more by this drug with the NSPs than other drugs. Binding pockets of NSPs for these three drugs are very close with many sharing residues in common suggesting of similarity of pharmacophore of these drugs with the target binding pockets. Conclusion The binding pockets of NSPs are well matched with the pharmacophore of drugs and with polar surface of drugs less than or equal to 100 A 2 , drugs, DB01977, DB07132 and DB07535 bind individually and effectively with NSPs 3, 5, 11, 14 and 15 of ORF1ab of SARS-CoV-2 genome to bring changes in the activity of SARS-CoV-2 which may be useful for biological and clinical considerations.
Type 2 diabetes mellitus (T2DM) and its complications are linked to environmental, clinical, and genetic factors. This review analyses the disorders of lipids and their genetics with respect to coronary artery disease (CAD) associated with T2DM. Cell organelles, hepatitis C-virus infection, reactive oxygen species produced in mitochondria, and defective insulin signaling due to the arrest of G1 phase to S phase transition of β-cells have significant roles in the precipitation of the diseases. Adiponectin is anti-inflammatory and anti-atherosclerotic and improves insulin resistance. Low-density lipoprotein (LDL) is atherosclerotic, and LDL-cholesterol in T2DM is associated with high-cardiovascular risk. Further, LDL cholesterol reduction significantly reduces cardiovascular morbidity and mortality. High-density lipoprotein (HDL) is also anti-atherosclerotic due to HDL associated paraoxonase-1 serum enzyme, which prevents LDL oxidative modifications and the development of CAD. Moreover, elevated apolipoprotein B and apolipoprotein A-I (ApoB/ApoA-I) ratio in plasma is also a risk factor for CAD. LDL receptor, adiponectin, and endocannabinoid receptor-1 genes are independently associated with CAD and T2DM. Polymorphism of Apo E2 (epsilon2) is a positive factor to increase the T2DM risk and Apo E4 (epsilon4) is a negative factor to reduce the disease risk. Taq 1B polymorphism of cholesterol ester transfer protein (CETP) gene contributes to the development of atherosclerosis, whereas haplotypes of APOA5, APOC3, APOC4, and APOC5 genes are in the same cluster and are independently associated with high plasma triglyceride level, CAD and T2DM. In conclusion, because various genes, LDLR, CETP, APOA5, Apo E, Apo B, and Apo A-I, are associated with the precipitation of CAD associated with T2DM, a personalized diet-gene intervention therapy may be advocated to reduce the disease precipitation.
Background: Type 2 diabetes mellitus (T2DM) is a complicated disease affecting different populations and the starting age of subjects is as early as 15 years old. Since anthropometric, clinical and genetic risk factors are associated with the development of T2DM, the complications developed due to T2DM are life-threatening. Therefore, this research analyzes the complicating risk factors of T2DM. Materials and methods:An observational study of approximately 10,000 north Indian individuals were contacted and a total of 703 subjects (351 control subjects and 352 T2DM subjects) belonging to north Indian states were recruited for the analysis of the risk factors.Result: Very early onset of T2DM, very large undiagnosed population, high newly diagnosed T2DM subjects, independent effect of complicating risk factors etc. were the results obtained from the research. Conclusion:Considering the complications and early onset of T2DM, despite the other diseases along with T2DM, early mortality and increased mortality due to T2DM were observed in north Indian population.major role in the susceptibility to T2DM. There are much differences seen in insulin secretion and sensitivity and nonalcoholic fatty liver disease and T2DM in subjects with different risk factors [18]. However, new alcohol drinkers in middle age and drink rarely may experience benefit in cardiovascular disease and diabetic complication [19] whereas rare and light drinkers after increasing alcohol consumption over short period of time are associated with lower risk of T2DM [20]. Moreover, cigarette smoking and smoking cessation lead to higher short-term risk of T2DM [21].The long term complications of T2DM are chronic complications in circulatory system that may cause blindness, lower limb gangrene and renal failure in adults. It is also a major risk factor for strokes and other cardiovascular diseases (CVD) [22]. Since T2DM is common, its related disorders such as nephropathy [23], neuropathy and retinopathy are also more common. Diabetic nephropathy is a serious complication of T2DM and the prevalence of nephropathy has been increasing worldwide [24,25]. In subjects with CAD and T2DM, the complications lead to functional and structural vascular alterations of the peripheral Materials and MethodologyIn this research, a preliminary observation of incidence of T2DM subjects of approximately 10,000 was interviewed. Apart from this, 351 control and 352 T2DM subjects from nearby locations of Chandigarh belonging to the states of Haryana, Utter Pradesh, Himachal Pradesh, Jammu Kashmir, Punjab, Delhi, Rajasthan, West Bengal etc. and resident of Chandigarh, Panchkula, Mohali, Baltana, etc. were recruited. This is because these cities/towns have resident migrated populations of these states. They were recruited at referral points /schools / hospitals etc. to administer the questionnaire for the data capture for this research. The subjects were completely analyzed using the criteria for control and T2DM subjects specified by diabetes associations. A formal broc...
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