Structural signature of the G719S-T790M double mutation in the EGFR kinase domain and its response to inhibitors.

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.

BSA nanoparticle loaded atorvastatin calcium--a new facet for an old drug.

Background: Currently, the discovery of effective chemotherapeutic agents poses a major challenge to the field of cancer biology. The present study focuses on enhancing the therapeutic and anti cancer properties of atorvastatin calcium loaded BSA (ATV-BSA) nanoparticles in vitro.

Methodology/results: BSA-ATV nanoparticles were prepared using desolvation technique.

In silico profiling and structural insights of missense mutations in RET protein kinase domain by molecular dynamics and docking approach.

A major challenge remaining in drug design efforts towards protein kinase is due to the development of drug resistance initiated by the missense mutations in the kinase catalytic domain. Gain or loss of function mutations in the REarranged during Transfection (RET) tyrosine kinase gene have been associated with the development of a wide range of human associated cancers and Hirschsprung's disease. However, to what extent these mutations might affect bio-molecular functions remains unclear.

Predicting the impact of deleterious mutations in the protein kinase domain of FGFR2 in the context of function, structure, and pathogenesis--a bioinformatics approach.

Fibroblast growth factor receptor 2 (FGFR2) controls a wide range of biological functions by regulating the cellular proliferation, survival, migration and differentiation. A growing body of preclinical data demonstrated that deregulation of the FGFR signalling through genetic modification was observed in various types of cancers. However, the extent to which genetic modifications interfere with gene regulation and their involvement in cancer susceptibility remains largely unknown.

In silico analysis of prion protein mutants: a comparative study by molecular dynamics approach.

Polymorphisms in the human prion proteins lead to amino acid substitutions by the conversion of PrPC to PrPSc and amyloid formation, resulting in prion diseases such as familial Creutzfeldt-Jakob disease, Gerstmann-Straussler-Scheinker disease and fatal familial insomnia. Cation-π interaction is a non-covalent binding force that plays a significant role in protein stability. Here, we employ a novel approach by combining various in silico tools along with molecular dynamics simulation to provide structural and functional insight into the effect of mutation on the stability and activity of mutant prion proteins.

In silico discrimination of nsSNPs in hTERT gene by means of local DNA sequence context and regularity.

Understanding and predicting the significance of novel genetic variants revealed by DNA sequencing is a major challenge to integrate and interpret in medical genetics with medical practice. Recent studies have afforded significant advances in characterization and predicting the association of single nucleotide polymorphisms in human TERT with various disorders, but the results remain inconclusive. In this context, a comparative study between disease causing and novel mutations in hTERT gene was performed computationally.

Disease-causing mutation in extracellular and intracellular domain of FGFR1 protein: computational approach.

In-depth computationally based structural analysis of human fibroblast growth factor type 1 (FGFR1) protein carrying disease-causing mutation was performed in this study. Gain or loss of function due to missense mutations in FGFR1 is responsible for a variety of disorders including Kallmann syndrome, Apert syndrome, Pfeiffer syndrome, Crouzon syndrome, etc. The mutant model of the human FGFR1 protein was subjected to various in silico analysis, and most deleterious SNPs were screened out.

A new insight into structural and functional impact of single-nucleotide polymorphisms in PTEN gene.

Phosphatase and tensin homolog (PTEN) plays essential roles in cellular processes including survival, proliferation, energy metabolism, and cellular architecture. Activating the mutations of PTEN has long been known to produce a variety of disorders, mainly diabetes and cancer in humans. Owing to the importance of PTEN gene, a functional analysis using different in silico approaches was undertaken to explore the possible associations between genetic mutations and phenotypic variation.

Screening of mutations affecting protein stability and dynamics of FGFR1-A simulation analysis.

Single amino acid substitutions in Fibroblast Growth Factor Receptor 1 () destabilize protein and have been implicated in several genetic disorders like various forms of cancer, Kallamann syndrome, Pfeiffer syndrome, Jackson Weiss syndrome, etc. In order to gain functional insight into mutation caused by amino acid substitution to protein function and expression, special emphasis was laid on molecular dynamics simulation techniques in combination with in silico tools such as SIFT, PolyPhen 2.0, I-Mutant 3.

Computational refinement of functional single nucleotide polymorphisms associated with ATM gene.

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.

Path to facilitate the prediction of functional amino acid substitutions in red blood cell disorders--a computational approach.

Background: A major area of effort in current genomics is to distinguish mutations that are functionally neutral from those that contribute to disease. Single Nucleotide Polymorphisms (SNPs) are amino acid substitutions that currently account for approximately half of the known gene lesions responsible for human inherited diseases. As a result, the prediction of non-synonymous SNPs (nsSNPs) that affect protein functions and relate to disease is an important task.