Computational Investigation of Aromatic Oligoamide Foldamers.

摘要

Foldamers are synthetic oligomers that adopt defined secondary structures in solution. Their functionality relies on their shape. We use all-atom molecular dynamics (MD) simulations with improved force field parameters to study the structure and dynamics of foldamers. This work includes three projects involving aromatic foldamers: 1) DNA-binding foldamers; 2) molecular encapsulation by foldamers; 3) folding-unfolding and handedness inversion in helical foldamers.;In the first project, we investigate DNA-binding foldamers. Ligands that are capable of binding DNA in a sequence specific manner and interrupting transcription factor-DNA interactions are of a great interest due their ability to inhibit a number of human cancers. We apply MD to optimize the design of cyclic foldamers (experimentally shown to bind to DNA) by evaluating the influence of the shape of the foldamer on binding affinity and selectivity as well as the dynamics of DNA upon foldamer binding.;In the second project, we investigate molecular capsules. Encapsulation can be useful in molecular recognition, catalysis, and drug delivery. Foldamers composed of pyridine and quinoline units have experimentally been shown to form helical capsules and encapsulate small ligands. However, no detailed information on ligand-capsule interactions and dynamics or on the mechanism of encapsulation has been reported, despite the fact that such information is crucial for rational design of capsules. We address these issues through MD simulations.;In the third project, we investigate the molecular details of handedness inversion by helical foldamers. As is well known, helical molecules possess handedness, which affects their function. Experimental studies have determined 1 the kinetic rate constants and free energy barriers for racemization for aromatic oligoamides derived from 8-amino-2-quinolinecarboxilic acid. However, the detailed atomistic picture of helix unfolding and handedness inversion is missing. We use MD simulations coupled with energy biasing method, metadynamics, to address this question.