A Data and Informatics Driven Drug Discovery Framework to Bridge Traditional and Modern Medicine

Abstract

Systems biological models of complex diseases provide a rational way to target their molecular control mechanisms. On the other hand, traditional medicinal systems offer empirical evidence for efficacy of plant extracts against diseases. Informed with our recent research explorations, we propose a data and informatics driven integrative framework that bridges traditional and modern medicine for prospection of therapeutic phytochemicals. This framework has the potential to transform the drug discovery process by intelligently juxtaposing knowledge derived from complementary domains and enables hypothesis driven search for therapeutic molecules.

From Side Chains Rattling on Picoseconds to Ensemble Simulations of Protein Folding

“…The other major way of performing such a clustering is to use kinetic clustering such as, for example, in Markov state models (MSMs). [40][41][42] Here, rather than grouping conformations together based solely on their structural similarity, as above, the clustering is performed based on the transitions between states, as observed in the underlying simulations (Figure 4). One advantage over a purely energetic clustering is that two conformations that might be very close energetically, but distant kinetically, will end up in different states.…”