A marine sponge associated fungal metabolite monacolin X suppresses angiogenesis by down regulating VEGFR2 signaling.

Cancer is one of the leading causes of global death and there is an urgent need for the development of cancer treatment; targeting VEGFR2 could be one of the promising therapies. In the present study, previously isolated marine fungal metabolite monacolin X, suppresses in vitro angiogenic characteristics such as proliferation, migration, adhesion, invasion and tube formation of HUVECs when stimulated by VEGF, at a non-toxic concentration. Monacolin X downregulated VEGFR2, PKCα and PKCη mRNA expression. Further, monacolin X inhibited in vivo angiogenesis in CAM assay, vascular sprouting in aortic ring, decreased ISV and SIV length and diameter in Tg (Kdr:EGFP)/ko1 zebrafish embryos. Monacolin X showed reduced protein expression of pVEGFR2, pAKT1, pMAPKAPK2, pFAK and pERK1 in breast cancer lines and in DMBA induced mammary carcinoma in SD rats showed tumor regression and anti-angiogenesis ability via decrease pVEGFR2 and pAKT1 protein expression. In silico studies also revealed monacolin X ability to bind to crucial amino acid Cys 919 in the active site of VEGFR2 suggesting it to be a potent VEGFR2 inhibitor.

Molecular Docking and Dynamic Simulation Studies of Terpenoids of I. wightii (Bentham) H. Hara against Acetylcholinesterase and Histone Deacetylase3 Receptors.

BACKGROUND: Genus Isodon (Lamiaceae) is a prolific source for bioactive terpenoids. Nowadays, people move towards natural products because of undesirable effects of chemotherapeutic drugs. OBJECTIVE: In silico and in vitro approaches were attempted to screen bioactive terpenoids isolated from Isodon wightii with acetylcholinesterase and histone deacetylase3 receptors. METHODS: Terpenoids such as abietic acid, oleanolic acid, α-amyrin acetate, ß-amyrin acetate were docked with AchE and HDAC3 receptors using AutoDock Vina (version 1.1.2). Further, GROMACS 5.1.2 package was used to perform molecular dynamic simulation. In vitro apoptosis was tested using hoechst 33258 and acridine orange/ethidium bromide. RESULTS: Ligplot analysis indicated that abietic acid had strong binding efficiency with AchE and HDAC3 receptors forming one and four hydrogen bonds respectively. Root mean square deviation analysis showed AchE-abietic acid and HDAC3-abietic acid complexes with high deviation which later attains equilibrium around ~25000ps and ~10000ps respectively. Root mean square fluctuation study showed that the complexes have high fluctuations indicates the high flexibility of residues. Solvent accessible surface area revealed the favourable interacting region of AchE and HDAC3 receptors with abietic acid in the range of ~215nm2 to ~235nm2 and ~157nm2 to ~175nm2 respectively. Apoptosis inducing the activity of abietic acid was tested against HeLa cells. Hoechst 33258 staining showed increased apoptosis by abietic acid in a concentration-dependent manner. AO/EtBr dual staining showed early apoptosis at 25-75µg/mL and necrosis at 100-125µg/mL abietic acid. CONCLUSION: In silico and in vitro studies suggest that abietic acid could be a promising terpenoid for treating Alzheimer's disease and cervical cancer.

Molecular Dynamics Validation of Crizotinib Resistance to ALK Mutations (L1196M and G1269A) and Identification of Specific Inhibitors.

Anaplastic lymphoma kinase (ALK) positive non-small cell lung cancer (NSCLC) patients are mostly treated with ALK tyrosine kinase inhibitors (TKIs). Crizotinib is the first generation ALK inhibitor practiced as a primary chemo to combat cancer cells followed by second generation inhibitor ceritinib which are effective against crizotinib resistant ALK mutations. However, patients treated with these drugs invariably relapsed because of the development of new drug resistance mutations. In this study we explored the crizotinib resistance in the presence of ALK mutations L1196M and G1269A through molecular dynamics simulation studies. Further mutation specific inhibitors CID 71748211 and CID 71728095 were identified to potentially inhibit ALK with mutations L1196M and G1269A, respectively. This computational investigation in-sighted the molecular factors involved in crizotinib resistance which enhanced in the identification of new ALK drugs that brings individualized medicine to treat ALK positive NSCLC patients with specific mutations. J. Cell. Biochem. 118: 3462-3471, 2017. © 2017 Wiley Periodicals, Inc.

Evolution- and structure-based computational strategy reveals the impact of deleterious missense mutations on MODY 2 (maturity-onset diabetes of the young, type 2).

Heterozygous mutations in the central glycolytic enzyme glucokinase (GCK) can result in an autosomal dominant inherited disease, namely maturity-onset diabetes of the young, type 2 (MODY 2). MODY 2 is characterised by early onset: it usually appears before 25 years of age and presents as a mild form of hyperglycaemia. In recent years, the number of known GCK mutations has markedly increased. As a result, interpreting which mutations cause a disease or confer susceptibility to a disease and characterising these deleterious mutations can be a difficult task in large-scale analyses and may be impossible when using a structural perspective. The laborious and time-consuming nature of the experimental analysis led us to attempt to develop a cost-effective computational pipeline for diabetic research that is based on the fundamentals of protein biophysics and that facilitates our understanding of the relationship between phenotypic effects and evolutionary processes. In this study, we investigate missense mutations in the GCK gene by using a wide array of evolution- and structure-based computational methods, such as SIFT, PolyPhen2, PhD-SNP, SNAP, SNPs&GO, fathmm, and Align GVGD. Based on the computational prediction scores obtained using these methods, three mutations, namely E70K, A188T, and W257R, were identified as highly deleterious on the basis of their effects on protein structure and function. Using the evolutionary conservation predictors Consurf and Scorecons, we further demonstrated that most of the predicted deleterious mutations, including E70K, A188T, and W257R, occur in highly conserved regions of GCK. The effects of the mutations on protein stability were computed using PoPMusic 2.1, I-mutant 3.0, and Dmutant. We also conducted molecular dynamics (MD) simulation analysis through in silico modelling to investigate the conformational differences between the native and the mutant proteins and found that the identified deleterious mutations alter the stability, flexibility, and solvent-accessible surface area of the protein. Furthermore, the functional role of each SNP in GCK was identified and characterised using SNPeffect 4.0, F-SNP, and FASTSNP. We hope that the observed results aid in the identification of disease-associated mutations that affect protein structure and function. Our in silico findings provide a new perspective on the role of GCK mutations in MODY2 from an evolution-based structure-centric point of view. The computational architecture described in this paper can be used to predict the most appropriate disease phenotypes for large-genome sequencing projects and to provide individualised drug therapy for complex diseases such as diabetes.