Effect of Configurational Entropy on Molecular Association

Christopher Forrey
Polymers Division, MSEL

Michael Gilson
Center for Advanced Research in Biotechnology (UMBI)
and Chemical Science Laboratory (NIST)

Computers are widely used in the pharmaceutical and biotechnology industries and academia to help understand and predict the strength of molecular association.  Molecular association is at the heart of numerous important phenomena, including receptor-ligand and protein-protein binding, self- and supra-molecular assembly, and phase behavior.  Underlying these phenomena are fundamental questions: will two given molecules bind each other?  What dictates the strength of association? How do modifications affect interaction?  Despite the universal relevance of these questions, approaches to these problems are quite dissimilar, depending upon the community doing the investigation.

        Pharmaceutical science has invested heavily in predicting receptor-ligand docking, in which the potential energy of rigid models of moleclues are used to determine association strength.  In contrast, more physics-based approaches employ dynamic molecular models, in which  molecular behavior depends critically on the tendency of a molecule to explore its entire configuration space.

        We propose a novel method drawing from both approaches, employing Langevin dynamics to perform dynamic-docking of simple toy molecular models.  Our model receptor molecules are comprised of  a sequence of connected particles whose 3D arrangement is imposed by the arbitrary selection of bond-stretching, bond angle, and torsional potentials.  "Docking" simulations are performed, in which "ligands" of complementary shape are allowed to dynamically associate with model "receptors".  To introduce flexibility, we systematically vary the strength of angular and torsional interaction potentials of our model molecules.  We then dock a set of model molecules differing only in the degree of fluctuations about their preset structure (ie flexibility).  Our simulation results allow us to quantitatively explore the effect of flexibility / configurational entropy on binding of model molecules.

CATEGORY: Biotechnology

Mentors Name: Kalman Migler

 Polymers Division, MSEL

A207, Building 224, stop 8544

                                                                               Tel: (301) 975-4876

Email: kalman.migler@nist.gov

Is your mentor a Sigma Xi Member: No