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The somatic mutations in ATP binding cleft of the tyrosine kinase binding domain of EGFR are known to occur in 15–40% of non-small cell lung cancer (NSCLC) patients. Although first and second generation anti-EGFR inhibitors are widely used to treat these patients, their therapeutic efficacy is modest and often results in adverse effects or drug resistance. Therefore, there is a need to develop novel as well as safe anti-EGFR drugs. The rapid emergence of computational drug designing provided a great opportunity to both discover and predict the efficacy of novel EGFR inhibitors from plant sources. In the present study, we designed several chemical analogues of edible curcumin (CUCM) compound and assessed their drug likeliness, ADME and toxicity properties using a diverse range of advanced computational methods. We also have examined the structural plasticity and binding characteristics of EGFR wild-type and mutant forms (S769L and K846R) against ligand molecules like Gefitinib, native CUCM, and different CUCM analogues. Through multidimensional experimental approaches, we conclude that CUCM-36 ((1E,4Z,6E)-1-(3,4-Diphenoxyphenyl)-5-hydroxy-7-(4-hydroxy-3-phenoxyphenyl)-1,4,6-heptatrien-3-one) is the best anti-EGFR compound with high drug-likeness, ADME properties, and low toxicity properties. CUCM-36 compound has demonstrated better affinity towards both wild-type (ΔG is ?8.5?kcal/Mol) and mutant forms (V769L & K846R; ΔG for both is >?9.20?kcal/Mol) compared to natural CUCM and Gefitinib inhibitor. This study advises the future laboratory assays to develop CUCM-36 as a novel drug compound for treating EGFR positive non-small cell lung cancer patients.  相似文献   
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Obesity is a multifactorial metabolic disorder characterized by low grade chronic inflammation. Rare and novel mutations in genes which are vital in several key pathways have been reported to alter the energy expenditure which regulates body weight. The TP53 or p53 gene plays a prominent role in regulating various metabolic activities such as glycolysis, lipolysis, and glycogen synthesis. Recent genome-wide association studies reported that tumor suppressor gene p53 variants play a critical role in the predisposition of type 2 diabetes and obesity. Till date, no reports are available from the Arabian population; hence the present study was intended to assess the association between p53 variants with risk of obesity development in the Saudi population. We have selected three p53 polymorphisms, rs1642785 (C > G), and rs9894946 (A > G), and rs1042522 (Pro72Arg; C > G) and assessed their association with obesity risk in the Saudi population. Phenotypic and biochemical parameters were also evaluated to check their association with p53 genotypes and obesity. Genotyping was carried out on 136 obese and 122 normal samples. We observed that there is significantly increased prevalence p52 Pro72Arg (rs1042522) polymorphism in obese persons when compared to controls at GG genotype in overall comparison (OR: 2.169, 95% CI: 1.086-4.334, p = 0.02716). Male obese subjects showed three-fold higher risk at GG genotype (OR: 3.275, 95% CI: 1.230-8.716, p = 0.01560) and two-fold risk at G allele (OR: 1.827, 95% CI: 1.128-2.958, p = 0.01388) of p53 variant Pro72Arg respectively. This variant has also shown significant influence on cholesterol, LDL level, and random insulin levels in obese subjects (p ≤ 0.05). In conclusion, p53 Pro72Arg variant is highly prevalent among obese individuals and may act as a genetic modifier for obesity development among Saudis.  相似文献   
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Streptococcus pneumonia is the common cause of sepsis and meningitis. Emergence of multiple antibiotic resistant strains in the community‐acquired bacterium is catastrophic. Glucose kinase (GLK) is a regulatory enzyme capable of adding phosphate group to glucose in the first step of streptomycin biosynthesis. The activity of glucose kinase was regulated by the Carbon Catabolite Repression (CCR) system. Therefore, it is important to establish the structure‐function relation of GLK in S. pneumoniae. However, a solved structure for S. pneumoniae GLK is not available at the protein data bank (PDB). Therefore, we created a model of GLK from S. pnemoniae using the X‐ray structure of Glk from E. faecalis as template with MODELLER (a comparative modeling program). The model was validated using protein structure checking tools such as PROCHECK, WHAT IF and ProSA for reliability. The active site amino acid Asp114 in the template is retained in S. pneumoniae GLK model (Asp115). Solvent accessible surface area (ASA) analysis of the GLK model showed that known key residues playing important role in active site for ligand binding and metal ion binding are buried and hence not accessible to solvent. The information thus discussed provides insight to the molecular understanding of glucose kinase in S. pneumoniae.  相似文献   
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Background: Celiac disease (CD) is a genetically complex autoimmune disease which is triggered by dietary gluten. Human leukocyte antigen (HLA) class II genes are known to act as high-risk markers for CD, where >95% of CD patients carry (HLA), DQ2 and/or DQ8 alleles. Therefore, the present study was conducted to investigate the distribution of HLA haplotypes among Saudi CD patients and healthy controls by using the tag single nucleotide polymorphisms (SNP).Methods: HLA-tag SNPs showing strong linkage value (r2>0.99) were used to predict the HLA DQ2 and DQ8 genotypes in 101 Saudi CD patients and in 103 healthy controls by using real-time polymerase chain reaction technique. Genotype calls were further validated by Sanger sequencing method.Results: A total of 63.7% of CD cases and of 60.2% of controls were predicted to carry HLA-DQ2 and DQ8 heterodimers, either in the homozygous or heterozygous states. The prevalence of DQ8 in our CD patients was predicted to be higher than the patients from other ethnic populations (35.6%). More than 32% of the CD patients were found to be non-carriers of HLA risk haplotypes as predicted by the tag SNPs.Conclusion: The present study highlights that the Caucasian specific HLA-tag SNPs would be of limited value to accurately predict CD specific HLA haplotypes in Saudi population, when compared with the Caucasian groups. Prediction of risk haplotypes by tag SNPs in ethnic groups is a good alternate approach as long as the tag SNPs were identified from the local population genetic variant databases.  相似文献   
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