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Some individuals with non-small-cell lung cancer (NSCLC) benefit from therapies targeting epidermal growth factor receptor (EGFR), and the characterization of a new mechanism of resistance to the EGFR-specific antibody gefitinib will provide valuable insight into how therapeutic strategies might be designed to overcome this particular resistance mechanism. The G719S and T790M mutations and their combination were involved in causing different conformational redistribution of EGFR. In the present computational study, we analyzed the impact and structural influence of G719S/T790M double mutation (DM) in EGFR with ligand (gefitinib) through molecular dynamic simulation (50 ns) and docking analysis. We observed the escalation in distance between the functional loop and activation loop with respect to T790M mutation compared to the G719S mutation. Furthermore, we confirmed that the G719S mutation causes the ligand to move closer to the hinge region, whereas T790M makes the ligand escape from the binding pocket. Obtained results provide with an explanation for the resistance induced by T790M and a vital clue for the design of drugs to combat gefitinib resistance. [ABSTRACT FROM AUTHOR]

In human, Wnt/β-catenin signaling pathway plays a significant role in cell growth, cell development, and disease pathogenesis. Four human (Rspo)s are known to activate canonicalWnt/β-catenin signaling pathway. Presently, (Rspo)s serve as therapeutic target for several human diseases. Henceforth, basic understanding about themolecular properties of (Rspo)s is essential. We approached this issue by interpreting the biochemical and biophysical properties alongwithmolecular evolution of (Rspo)s thorough computational algorithm methods. Our analysis shows that signal peptide length is roughly similar in (Rspo)s family along with similarity in aa distribution pattern. In Rspo3, four N-glycosylation sites were noted. All members are hydrophilic in nature and showed alike GRAVY values, approximately. Conversely, Rspo3 contains the maximum positively charged residues while Rspo4 includes the lowest. Four highly aligned blocks were recorded through Gblocks. Phylogenetic analysis shows Rspo4 is being rooted with Rspo2 and similarly Rspo3 and Rspo1 have the common point of origin. Through phylogenomics study, we developed a phylogenetic tree of sixty proteins (n= 60) with the orthologs and paralogs seed sequences. Protein-protein network was also illustrated. Results demonstrated in our study may help the future researchers to unfold significant physiological and therapeutic properties of (Rspo)s in various disease models. [ABSTRACT FROM AUTHOR]

Advancement in the gene delivery system have resulted in clinical successes in gene therapy for patients with several genetic diseases, such as immunodeficiency diseases, X-linked adrenoleukodystrophy (X-ALD) blindness, thalassemia, and many more. Among various delivery systems, liposomal mediated gene delivery route is offering great promises for gene therapy. This review is an attempt to depict a portrait about the polymer based liposomal gene delivery systems and their future applications. Herein, we have discussed in detail the characteristics of liposome, importance of polymer for liposome formulation, gene delivery, and future direction of liposome based gene delivery as a whole. [ABSTRACT FROM AUTHOR]

Background: Recent reports suggest the role of nonsynonymous single nucleotide polymorphisms (nsSNPs) in cyclin-dependent kinase 7 (CDK7) gene associated with defect in the DNA repair mechanism that may contribute to cancer risk. Among the various inhibitors developed so far, flavopiridol proved to be a potential antitumor drug in the phase-III clinical trial for chronic lymphocytic leukemia. Here, we described a theoretical assessment for the discovery of new drugs or drug targets in CDK7 protein owing to the changes caused by deleterious nsSNPs. Methods: Three nsSNPs (I63R, H135R, and T285M) were predicted to have functional impact on protein function by SIFT, PolyPhen2, I-Mutant3, PANTHER, SNPs&GO, PhD-SNP, and screening for non-acceptable polymorphisms (SNAP). Furthermore, we analyzed the native and proposed mutant models in atomic level 10 ns simulation using the molecular dynamics (MD) approach. Finally, with the aid of Autodock 4.0 and PatchDock, we analyzed the binding efficacy of flavopiridol with CDK7 protein with respect to the deleterious mutations. Results: By comparing the results of all seven prediction tools, three nsSNPs (I63R, H135R, and T285M) were predicted to have functional impact on the protein function. The results of protein stability analysis inferred that I63R and H135R exhibited less deviation in root mean square deviation in comparison with the native and T285M protein. The flexibility of all the three mutant models of CDK7 protein is diverse in comparison with the native protein. Following to that, docking study revealed the change in the active site residues and decrease in the binding affinity of flavopiridol with mutant proteins. Conclusion: This theoretical approach is entirely based on computational methods, which has the ability to identify the disease-related SNPs in complex disorders by contrasting their costs and capabilities with those of the experimental methods. The identification of disease related SNPs by computational methods has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases. Lay abstract: Cell cycle regulatory protein, CDK7, is linked with DNA repair mechanism which can contribute to cancer risk. The main aim of this study is to extrapolate the relationship between the nsSNPs and their effects in drug-binding capability. In this work, we propose a new methodology which (1) efficiently identified the deleterious nsSNPs that tend to have functional effect on protein function upon mutation by computational tools, (2) analyze d the native protein and proposed mutant models in atomic level using MD approach, and (3) investigated the protein-ligand interactions to analyze the binding ability by docking analysis. This theoretical approach is entirely based on computational methods, which has the ability to identify the disease-related SNPs in complex disorders by contrasting their costs and capabilities with those of the experimental methods. Overall, this approach has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases. [ABSTRACT FROM AUTHOR]

Background: Understanding and predicting molecular basis of disease is one of the major challenges in modern biology and medicine. SNPs associated with complex disorders can create, destroy, or modify protein coding sites. Single amino acid substitutions in the ATM gene are the most common forms of genetic variations that account for various forms of cancer. However, the extent to which SNPs interferes with the gene regulation and affects cancer susceptibility remains largely unknown. Principal findings: We analyzed the deleterious nsSNPs associated with ATM gene based on different computational methods. An integrative scoring system and sequence conservation of amino acid residues was adapted for a priori nsSNP analysis of variants associated with cancer. We further extended our approach on SNPs that could potentially influence protein Post Translational Modifications in ATM gene. Significance: In the lack of adequate prior reports on the possible deleterious effects of nsSNPs, we have systematically analyzed and characterized the functional variants in both coding and non coding region that can alter the expression and function of ATM gene. In silico characterization of nsSNPs affecting ATM gene function can aid in better understanding of genetic differences in disease susceptibility. [ABSTRACT FROM AUTHOR]

Background: A central focus of cancer genetics is the study of mutations that are causally implicated in tumorigenesis. The identification of such causal mutations not only provides insight into cancer biology but also presents anticancer therapeutic targets and diagnostic markers. Missense mutations are nucleotide substitutions that change an amino acid in a protein, the deleterious effects of these mutations are commonly attributed to their impact on primary amino acid sequence and protein structure. Methods: The method to identify functional SNPs from a pool, containing both functional and neutral SNPs is challenging by experimental protocols. To explore possible relationships between genetic mutation and phenotypic variation, we employed different bioinformatics algorithms like Sorting Intolerant from Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), and PupaSuite to predict the impact of these amino acid substitutions on protein activity of mismatch repair (MMR) genes causing hereditary nonpolyposis colorectal cancer (HNPCC). Results: SIFT classified 22 of 125 variants (18%) as 'Intolerant." PolyPhen classified 40 of 125 amino acid substitutions (32%) as "Probably or possibly damaging". The PupaSuite predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Based on the PolyPhen scores and availability of three-dimensional structures, structure analysis was carried out with the major mutations that occurred in the native protein coded by MSH2 and MSH6 genes. The amino acid residues in the native and mutant model protein were further analyzed for solvent accessibility and secondary structure to check the stability of the proteins. Conclusion: Based on this approach, we have shown that four nsSNPs, which were predicted to have functional consequences (MSH2-Y43C, MSH6-Y538S, MSH6-S580L, and MSH6-K854M), were already found to be associated with cancer risk. Our study demonstrates the presence of other deleterious mutations and also endorses with in vivo experimental studies. [ABSTRACT FROM AUTHOR]

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variations in humans. Understanding the functions of SNPs can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. The method to identify functional SNPs from a pool, containing both functional and neutral SNPs is challenging by experimental protocols. To explore possible relationships between genetic mutation and phenotypic variation, different computational algorithm tools like Sorting Intolerant from Tolerant, Polymorphism Phenotyping, UTRscan, FASTSNP, and PupaSuite were used for prioritization of high-risk SNPs in coding region (exonic nonsynonymous SNPs) and noncoding regions (intronic and exonic 5’ and 3’-untranslated region (UTR) SNPs). In this work, we have analyzed the SNPs that can alter the expression and function of transcriptional factor TP53 as a pipeline and for providing a guide to experimental work. We identified the possible mutations and proposed modeled structure for the mutant proteins and compared them with the native protein. These nsSNPs play a critical role in cancer association studies aiming to explain the disparity in cancer treatment responses as well as to improve the effectiveness of the cancer treatments. Our results endorse the study with in vivo experimental protocols. [ABSTRACT FROM AUTHOR]

The article discusses the use of gamma-glutamyl transpeptidase (GGT) glutathione (GSH) metabolism in host-parasite interactions. It states that the active GGT can be released from cells and cancer cells. It mentions that GSH/GGT dependent process corroborate the importance of redox homeostasis in modulation of health and disease conditions and highlights regulatory elements of convergent parasitic strategies.