Abstract: Doxorubicin, also known as Adriamycin, is an
anthracycline class of drug used in cancer chemotherapy. It is used in
the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute
leukemia, breast cancer, lung cancer, endometrium cancer and ovary
cancers. It functions via intercalating DNA and ultimately killing
cancer cells. The major side effects of doxorubicin are hair loss,
myelosuppression, nausea & vomiting, oesophagitis, diarrhea, heart
damage and liver dysfunction. The minor modifications in the
structure of compound exhibit large variation in the biological
activity, has prompted us to carry out the synthesis of sulfonamide
derivatives. Sulfonamide is an important feature with broad spectrum
of biological activity such as antiviral, antifungal, diuretics, antiinflammatory,
antibacterial and anticancer activities. Structure of the
synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilinoethyl)
benzene sulfonamide confirmed by proton nuclear magnetic
resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools
to assure the position of all protons and hence stereochemistry of the
molecule. Further we have reported the binding potential of
synthesized sulfonamide analogues in comparison to doxorubicin
drug using Auto Dock 4.2 software. Computational binding energy
(B.E.) and inhibitory constant (Ki) has been evaluated for the
synthesized compound in comparison of doxorubicin against Poly
(dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences.
The in vitro cytotoxic study against human breast cancer cell lines
confirms the better anticancer activity of the synthesized compound
over currently in use anticancer drug doxorubicin. The IC50 value of
the synthesized compound is 7.12 μM whereas for doxorubicin is 7.2
μM.
Abstract: NFκB activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFa) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are no any quantitative or qualitative results of comparison assessment on inhibition effect between different single drugs or drug combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific single drugs and drug combinations on the NFκB pathway in MM, especially the prediction of synergistic drug combinations.