Mechanistic Dissection of Entropic Penalty upon Ligand Binding and Molecular Flexibility via Molecular Dynamics Simulations and Machine Learning

Molecular flexibility plays a crucial role in how molecules behave, reorganize, and interact with their surroundings. While experiments measure molar entropy for small molecules, and molecular dynamics (MD) simulations capture molecular motions, understanding configuration entropy and the interconnected internal motions, such as torsion rotations and angle bending, remains a formidable challenge.

To unravel these contributions, researchers employed MD trajectories and devised an internal coordinate PC-entropy (iPC-entropy) method to investigate the origins of entropy and shed light on how specific motions influence the thermodynamic landscape. The studies successfully captured molar entropy, pinpointed key torsional motions as primary contributors, and discovered a critical angle-torsion coupling where angle bending was strongly correlated with torsional rotation.

This coupling exhibits a nonlinear increase with molecular size. By evaluating entropic changes upon protein-ligand binding, the researchers found that the main entropic penalty stems from ligand dihedral rigidification rather than protein reorganization. Furthermore, they identified specific dihedral rotations that become restricted.

To enhance the accuracy of computer-aided drug discovery, the researchers propose systematic corrections for approaches considering solely rotamers, enabling reliable reproduction of the relative entropic penalty. The findings provide a deeper understanding of the molecular origins of entropy and how entropic changes impact binding thermodynamics, offering valuable mechanistic insights to guide drug development.