Cancer is an umbrella term covering a plethora of conditions characterized by unscheduled and uncontrolled cellular proliferation. What triggers an oncogenic transformation can vary from genetic predisposition, environmental influences, infectious agents, to ageing. These transform normal cells into cancerous ones by derailing a wide spectrum of regulatory and downstream effector pathways. It is just this complexity that has hampered the development of effective and specific cancer therapies. In my lab we have taken a complementary approach to the experimental progress to quantify and interrogate the interactions in molecular and cell signaling pathways implicated in cancers through computational means via a hierarchical multiscale modeling approach based on molecular dynamics and quantum chemical simulations, free energy based molecular recognition algorithms, deterministic network-based kinetic modeling, and hybrid discrete-continuum stochastic dynamics protocols. In my talk I will discuss the foundations and applications of our approach, their utility and predictive value in light of the scope for therapeutic intervention by focusing on two specific cell signaling cascades, namely, DNA repair, and growth factor-mediated proliferation pathways.
