Breast cancer is one of the most common cancers among the women around the world. Several genes are known to be responsible for conferring the susceptibility to breast cancer. Among them, TP53 is one of the major genetic risk factor which is known to be mutated in many of the breast tumor types. TP53 mutations in breast cancer are known to be related to a poor prognosis and chemo resistance. This renders them as a promising molecular target for the treatment of breast cancer. In this study, we present a computational based screening and molecular dynamic simulation of breast cancer associated deleterious non-synonymous single nucleotide polymorphisms in TP53. We have predicted three deleterious coding non-synonymous single nucleotide polymorphisms rs11540654 (R110P), rs17849781 (P278A) and rs28934874 (P151T) in TP53 with a phenotype in breast tumors using computational tools SIFT, Polyphen-2 and MutDB. We have performed molecular dynamics simulations to study the structural and dynamic effects of these TP53 mutations in comparison to the wild-type protein. Results from our simulations revealed a detailed consequence of the mutations on the p53 DNA-binding core domain that may provide insight for therapeutic approaches in breast cancer.

Fibronectin type III domain containing 5 (FNDC5) is a transmembrane protein. Upon cleavage, it yields a peptide called irisin that is supposedly bind to an unknown receptor and facilitates browning of white adipose tissue (WAT). Increased levels of irisin are associated with increased levels of energy expenditure markers PGC-1α, UCP-1, besides abundance of beige adipocytes in WAT. Though varied sizes of irisin were reported in humans and rodents it is not yet clear about the actual size of the irisin produced physiologically. Hence, we cloned and expressed human irisin (32-143 aa of FNDC5) in Escherichia coli based on the proposed cleavage site that yields 12.5 kDa peptide to study its antigenicity and other biological functions in vitro. We purified recombinant human irisin (rh-irisin) to 95% homogeneity with simple purification method with a yield of 25 mg/g wet cell pellet. rh-irisin has been detected by commercially available antibodies from different sources with similar antigenicity. Biological activity of the rh-irisin was confirmed by using 3T3-L1 pre-adipocyte differentiation by Oil red O staining. Further, rh-irisin treatment on pre-adipocytes showed increased expression of markers associated with energy expenditure. As it is involved in energy expenditure process, it could be considered as potential therapeutic option for various metabolic diseases.

The observable mutated isoforms of epidermal growth factor receptor (EGFR) are important considerable therapeutic benchmarks in moderating the non-small cell lung cancer (NSCLC). Recently, quinazoline-based ATP competitive inhibitors have been developed against the EGFR; however, these imply the mutation probabilities, which contribute to the discovery of high probable novel inhibitors for EGFR mutants. Therefore, SAR-based bioactivity analysis, molecular docking and computational toxicogenomics approaches were performed to identify and evaluate new analogs of gefitinib against the ligand-binding domain of the EGFR double-mutated model. From the diverse groups of molecular clustering and molecular screening strategies, top high-binding gefitinib-analogues were identified and studied against EGFR core cavity through three-phase ensemble docking approach. Resulted high possible leads showed good binding orientations than gefitinib (positive control) thus they were subjected to pharmacophore analysis that possesses possible molecular assets to tight binding with EGFR domain. Residues Ser720, Arg841 and Trp880 were observed as novel hot spots and involved in H-bonds, pi-stacking and π-cation interactions that contribute additional electrostatic potency to sustain stability and complexity of protein-ligand complexes, thus they have ability to profoundly adopted by pharmacophoric features. Furthermore, lead molecules have an inhibition percent probability, anticancer potency, toxic impacts, flexible pharmacokinetics, potential gene-chemical interactions towards EGFR were revealed by computational systems biology tools. Our multiple screening strategies confirmed that the druggable sub-pocket was crucial to strong EGFR-ligand binding. The essential pharmacophoric features of ligands provided viewpoints for new inhibitors envisaging, and predicted scaffolds could used as anticancer agents against selected EGFR mutated isoforms.

Review Article: Current Knowledge on Microarray Technology - An Overview

Epigallocatechin gallate (EGCG) is a major polyphenols of green tea may have the possibility to inhibit epidermal growth factor receptor (EGFR) activity and lead to reduce non-small cell lung cancer (NSCLC) progression. However, EGCG has some toxic features; moreover, there is a lack of explorations into the molecular interaction mechanisms of EGCG and the EGFR. In this examination, integration of quantitative structure–activity relationship (QSAR) modeling, pharmacophore-based virtual screening, and ensemble docking approaches were used to predict potential novel EGCG analogs as effective EGFR inhibitors. QSAR modeling of logP and logS predictions and toxicity endpoint investigation for a set of 82 compounds were shown good predictive ability and robustness from the applicability domain and confusion matrix elucidations. Virtual screening and docking studies revealed that seven high potential EGCG analogs as strong EGFR binders. Molecular interactions interpretations indicated some insights into the structural features of ligands that efficiently interfere with mutation possible residues (Gly⁷¹⁹ and Thr⁷⁹⁰) of the EGFR. The hydrogen bonds, hydrophobic interactions, atomic π-cation interactions and salt bridges of ligands are contributing additional stability to receptor structure, which can lead to blocking the intracellular protein-tyrosine kinase activity, including EGFR associated pathways activation in NSCLC. Therefore, this can characterize as a block-cluster mechanism between EGCG analogs and EGFR complexes. In silico anti-EGFR and anticancer activity predictions suggested that, ligands could act as promising pharmacological, anticancer, and drug-like templates of EGFR towards moderating the NSCLC progressions. These results and provided pinpoints could be beneficial to recognize probable therapeutic targets for NSCLC therapy.

The present study was to explore expectation and examination of therapeutic potential quercetin analogs as efficient anticancer agents against human epidermal growth factor receptor (EGFR), which is a consistent hallmark for moderating the non-small-cell lung carcinoma (NSCLC). Here, ligand-based virtual screening, pharmacophore approach and molecular docking were established as rational strategies for recognition of small analogs against the ligand binding domain of EGFR (PDB code: 1XKK). Adverse effects, toxicogenomics and pharmacokinetics reported that 10 candidates showed reliable consequences with less side effects and more efficient for target receptor. Protein–ligand interaction profiles revealed that the probable H-bonds, atomic-π contacts, salt bridges and van der Waals interactions sustain the complexity and stability of receptor structure; thus, they could complicate to generate single alteration acquired for drug resistance. In silico anticancer properties explain the lead scaffolds which are assumed to be flexible and experimentally proved chemicals. The overall consequences indicated that recognized leads could be utilized as reference skeletons for new inhibitors envisaging toward EGFR to ameliorate NSCLC and other malignant disorders.