In silico Insights on IL-6: A Potential Target for Multicentric Castleman Disease.

BACKGROUND: Multicentric Castleman Disease (MCD) is a confrontational lymphoproliferative disorder described by symptoms such as lymph node proliferation, unwarranted secretion of inflammatory cytokines, hyperactive immune system, and in severe cases, multiple organ dysfunction. Interleukin-6 (IL-6) is a pleiotropic cytokine which is involved in a large range of physiological processes in our body such as pro-inflammation, anti-inflammation, differentiation of T-cells and is reported to be a key pathological factor in MCD. In the case of MCD, it was observed that IL-6 is overproduced from T-cells and macrophages which disturb Hepcidin, a vital regulator of iron trafficking in macrophage. The present study endeavour to expound the inhibitor which binds to IL-6 protein receptor with high affinity. METHODS: MolegroVirtual Docker software was employed to find the best-established drug from the list of selected inhibitors of IL-6. This compound was subjected to virtual screening against PubChem database to get inhibitors with a very similar structure. These inhibitors were docked to obtain a compound binding with high affinity to the target protein. The established compound and the virtual screened compound were subjected to relative analysis of interactivity energy variables and ADMET profile studies. RESULTS: Among all the selected inhibitors, the virtual screened compound PubChem CID: 101119084 is seen to possess the highest affinity with the target protein. Comparative studies and ADMET analysis further implicate this compound as a better inhibitor of the IL-6 protein. CONCLUSION: Hence, this compound recognized in the study possesses high potential as an IL-6 inhibitor which might assist in the treatment of Multicentric Castleman Disease and should be examined for its efficiency by in vivo studies.

In Silico Insights on GD2 : A Potential Target for Pediatric Neuroblastoma.

BACKGROUND: Originating from the abnormal growth of neuroblasts, pediatric neuroblastoma affects the age group below 15 years. It is an aggressive heterogenous cancer with a high morbidity rate. Biological marker GD2 synthesised by the GD2 gene acts as a powerful predictor of neuroblastoma cells. GD2 gangliosides are sialic acid-containing glycosphingolipids. Differential expression during brain development governs the function of the GD2. The present study explains the interaction of the GD2 with its established inhibitors and discovers the compound having a high binding affinity against the target protein. Technically, during the development of new compounds through docking studies, the best drug among all pre-exist inhibitors was filtered. Hence in reference to the best docked compound, the study proceeded further. METHODOLOGY: The In silico approach provides a platform to determine and establish potential inhibitor against GD2 in Pediatric neuroblastoma. The 3D structure of GD2 protein was modelled by homology base fold methods using Smith-Watermans' Local alignment. A total of 18 established potent compounds were subjected to molecular docking and Etoposide (CID: 36462) manifested the highest affinity. The similarity search presented 336 compounds similar to Etoposide. RESULTS: Through virtual screening, the compound having PubChem ID 10254934 showed a better affinity towards GD2 than the established inhibitor. The comparative profiling of the two compounds based on various interactions such as H-bond interaction, aromatic interactions, electrostatic interactions and ADMET profiling and toxicity studies were performed using various computational tools. CONCLUSION: The docking separated the virtual screened drug (PubChemID: 10254934) from the established inhibitor with a better re-rank score of -136.33. The toxicity profile of the virtual screened drug was also lesser (less lethal) than the established drug. The virtual screened drug was observed to be bioavailable as it does not cross the blood-brain barrier. Conclusively, the virtual screened compound obtained in the present investigation is better than the established inhibitor and can be further augmented by In vitro analysis, pharmacodynamics and pharmacokinetic studies.

An In Silico Investigation of Potential EGFR Inhibitors for the Clinical Treatment of Colorectal Cancer.

Colorectal cancer possesses the third highest diagnostic rate and is the second leading cause of cancer death in the USA as reported by NIH. Epidermal Growth Factor Receptor (EGFR), a transmembrane protein, participates in PLC gamma-1, RAS-RAF-MEK-MAPKs, phosphatidylinositol-3 kinase, Akt pathways and plays a key role in normal functioning of cell division, cell differentiation, apoptosis and migration. This protein is found to be overexpressed in more than 60% of the colorectal cancers. Overexpressed EGFR advances the tumorigenic properties through cell cycle dysregulation and activates signaling pathways linked to cancer such as WNT/ß-catenin, transforming growth factor ß (TGF-ß) and phosphoinositide-3-kinase (PI3K). Inhibiting the overexpressed EGFR protein has been proposed for the treatment and many inhibitors have been reported suppressing the activity of EGFR. However, patients in malignant state of cancer show resistance to those inhibitors, which open a wide space to research for the discovery of novel inhibitors. The present study employed Molecular Docking and Virtual Screening to find novel inhibitors with high affinity against EGFR. Molecular docking of existing inhibitors resulted in the compound titled as BGB-283 (PubChem CID-89670174) having the highest score, which was subjected to similarity search to retrieve the drugs with similar structure. The virtual screening concluded a compound SCHEMBL18435602 (PubChem CID-126517400) which revealed a better affinity with the target protein. A comparative study of both the compounds showed equivalent pharmacokinetic properties. These identified drugs have a high potential to act as EGFR inhibitors and can show promising results in the research of colorectal cancer.