The tp53 gene is found to be mutated in 50% of all the cancers. The p53 protein, a product of tp53 gene, is a multi-domain protein. It consists of a core DNA binding domain (DBD) which is responsible for its binding and transcription of downstream target genes. The mutations in p53 protein are responsible for creating cancerous conditions and are found to be occurring at a high frequency in the DBD region of p53. Some of these mutations are also known to be temperature sensitive (ts) in nature. They are known to exhibit partial or strong binding with DNA in the temperature range (298–306 K). Whereas, at 310 K and above they show complete loss in binding. We have analyzed the changes in binding and conformational behavior at 300 K and 310 K for three of the ts-mutants viz., V143A, R249S and R175H. QM-MM simulations have been performed on the wild type and the above mentioned ts-mutants for 30 ns each. The optimal estimate of free energy of binding for a particular number of interface hydrogen bonds was calculated using the maximum likelihood method as described by Chodera et. al (2007). This parameter has been observed to be able to mimic the binding affinity of the p53 ts-mutants at 300 K and 310 K. Thus the correlation between MM-GBSA free energy of binding and hydrogen bonds formed by the interface residues between p53 and DNA has revealed the temperature dependent nature of these mutants. The role of main chain dihedrals was obtained by performing dihedral principal component analysis (PCA). This analysis, suggests that the conformational variations in the main chain dihedrals (ϕ and ψ) of the p53 ts-mutants may have caused reduction in the overall stability of the protein. The solvent exposure of the side chains of the interface residues were found to hamper the binding of the p53 to the DNA. Solvent Accessible Surface Area (SASA) also proved to be a crucial property in distinguishing the conformers obtained at 300 K and 310 K for the three ts-mutants from the wild type at 300 K.

p53 is a transcription factor involved in the expression of a number of downstream genes in response to genotoxic stress. It is activated through post translation modifications in normal as well as cancerous cells. However, due to mutations occurring in p53 in cancer cells it is not able to perform its function of DNA binding which leads to cell proliferation. It is found to be mutated in 50% of the cancers. These mutations occur at a high frequency in the DNA binding region of the p53. Among the known seven hot spot cancer mutations G245S, R249S, and R273C have been studied here using quantum mechanics and molecular mechanics (QM-MM) simulations. These mutations along with their experimentally proven rescue mutations have also been included in the present work. A comparative study of these cancer mutations along with wild type and their rescue mutations has been performed. A computational measure based on the free energy changes occurring in the binding of the p53 to the DNA has been presented. A correlation between the DNA binding property and important interaction between p53 and DNA has been observed for all the mutants. The keys residues which contribute to the binding of p53 to DNA by forming crucial hydrogen bonds have also been discussed in detail. A 30 ns simulation study was analyzed to observe the local structural changes and DNA binding property of p53 in case of wild type, cancer and rescue mutants.

Objectives Reliable identification of population-specific variants is important for building the single nucleotide polymorphism (SNP) profile. In this study, genomic variation using allele frequency differences of pharmacologically important genes for Gujarati Indians in Houston (GIH) and Indian Telugu in the U.K. (ITU) from the 1000 Genomes Project vis-à-vis global population data was studied to understand its role in drug response. Methods Joint genotyping approach was used to derive variants of GIH and ITU independently. SNPs of both these populations with significant allele frequency variation (minor allele frequency ≥ 0.05) with super-populations from the 1000 Genomes Project and gnomAD based on Chi-square distribution with p-value of ≤ 0.05 and Bonferroni’s multiple adjustment tests were identified. Population stratification and fixation index analysis was carried out to understand genetic differentiation. Functional annotation of variants was carried out using SnpEff, VEP and CADD score. Results Population stratification of VIP genes revealed four clusters viz., single cluster of GIH and ITU, one cluster each of East Asian, European, African populations and Admixed American was found to be admixed. A total of 13 SNPs belonging to ten pharmacogenes were identified to have significant allele frequency variation in both GIH and ITU populations as compared to one or more super-populations. These SNPs belong to VKORC1 (rs17708472, rs2359612, rs8050894) involved in Vitamin K cycle, cytochrome P450 isoforms CYP2C9 (rs1057910), CYP2B6 (rs3211371), CYP2A2 (rs4646425) and CYP2A4 (rs4646440); ATP-binding cassette (ABC) transporter ABCB1 (rs12720067), DPYD1 (rs12119882, rs56160474) involved in pyrimidine metabolism, methyltransferase COMT (rs9332377) and transcriptional factor NR1I2 (rs6785049). SNPs rs1544410 (VDR), rs2725264 (ABCG2), rs5215 and rs5219 (KCNJ11) share high fixation index (≥ 0.5) with either EAS/AFR populations. Missense variants rs1057910 (CYP2C9), rs1801028 (DRD2) and rs1138272 (GSTP1), rs116855232 (NUDT15); intronic variants rs1131341 (NQO1) and rs115349832 (DPYD) are identified to be ‘deleterious’. Conclusions Analysis of SNPs pertaining to pharmacogenes in GIH and ITU populations using population structure, fixation index and allele frequency variation provides a premise for understanding the role of genetic diversity in drug response in Asian Indians.

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The transcription factor p53 is one of the most widely studied cancer proteins. Its temperature-sensitive nature suggests reduction in functionality at physiological temperatures. Temperature-induced conformational variations and their impact on its functional ability still remain unexplored. A total of 20.8 μs molecular dynamics simulations of wildtype p53 in the apo and the DNA-bound states have been performed at 300 K and 310 K. Further, Markov State Modeling (MSM) analyses were performed, considering C α −C α distances as reaction coordinates. Filtering of these distances based on correlation with the time-independent components (tICs) resulted in 16 and 32 distances for apo and DNA-bound systems, respectively. Individual MSM analyses using these filtered distances were performed for both p53 systems. These C α −C α residue pairs belonged to the N-terminal, S6/7 β-turn, loop L2, loop L3, and hydrophobic core residues. At physiological temperatures, apo-p53 exhibits exposure of its hydrophobic core, where the temperature-sensitive hotspot residues were also located. This exposure was the result of the S6/7 β-turn and N-terminal moving apart. In the DNA-bound p53 system, loop L1 attains an open conformation at physiological temperatures, which weakens the DNA binding. It is already known that p53 mutants that lack DNA binding also tend to show similar conformational variations. The S6/7 β-turn along with the already known functionally important loop L2 may pose as regions to be targeted to overcome the loss in binding of temperature-sensitive wildtype p53. Rescue strategies directed toward these temperature-sensitive regions may be useful to recuperate its strong binding at physiological temperatures.