Ligand binding remodels protein side-chain conformational heterogeneity

Abstract

While protein conformational heterogeneity plays an important role in many aspects of biological function, including ligand binding, its impact has been difficult to quantify. Macromolecular X-ray diffraction is commonly interpreted with a static structure, but it can provide information on both the anharmonic and harmonic contributions to conformational heterogeneity. Here, through multiconformer modeling of time- and space-averaged electron density, we measure conformational heterogeneity of 743 stringently matched pairs of crystallographic datasets that reflect unbound/apo and ligand-bound/holo states. When comparing the conformational heterogeneity of side chains, we observe that when binding site residues become more rigid upon ligand binding, distant residues tend to become more flexible, especially in non-solvent exposed regions. Among ligand properties, we observe increased protein flexibility as the number of hydrogen bonds decrease and relative hydrophobicity increases. Across a series of 13 inhibitor bound structures of CDK2, we find that conformational heterogeneity is correlated with inhibitor features and identify how conformational changes propagate differences in conformational heterogeneity away from the binding site. Collectively, our findings agree with models emerging from NMR studies suggesting that residual side chain entropy can modulate affinity and point to the need to integrate both static conformational changes and conformational heterogeneity in models of ligand binding.

General theory of specific binding: insights from a genetic-mechano-chemical protein model

“…We decompose the binding entropy into two terms, ∆S = ∆S conf + ∆S 0 , where ∆S conf is the change in conformational entropy, [41][42][43] which depends on the elastic network topology and spring stiness, and ∆S 0 accounts for other contributions to entropy that are not captured directly by the model (e.g., release of frustrated solvent, ligand conformational change, protein entropy change due to plastic deformation). 24,[44][45][46][47][48][49] We calculate ∆S conf for the elastic network by creating sti bonds of strength K Λ between the protein and ligand binding sites (see Methods). Standard normal mode analysis shows that the resulting entropy change is the sum over the variation in the logarithms of the mode energies λ i before and after binding, ∆S conf = − 1 2 i ∆ ln λ i .…”

“…Our model treats deformations as elastic, so it may not generalize well to proteins that undergo plastic deformations upon binding. In fact, the restructuring of intramolecular bonds can result in a gain in entropy 24,44 , or an increase in internal enthalpy. 117 Furthermore, a simplifying assumption in elastic network models is that bonds are at their equilibrium lengths in the ensemble-average protein structure.…”

“…20,21 Recent work has suggested that residues not directly involved in binding may play a role in discrimination via allostery. [22][23][24][25] Here, taking inspiration from the many experimental examinations of molecular discrimination by proteins, such as enzymes, tRNA synthetases, transcription factors, and antibodies , 1,2,[26][27][28][29][30][31][32][33] we propose a simple yet general theory of speci c binding.…”

Peptide-Functionalized Nanoemulsions as a Promising Tool for Isolation and Ex Vivo Culture of Circulating Tumor Cells

“…We associate this fact with the higher molecular weight of this protein, as EGFR has a MW of 69.8 kDa, making it much bigger than EpCAM (with a MW of 29 kDa). Additionally, it is well-known that protein conformation influences inding affinity by affecting the free binding sites [ 44 ]. Similarly, it has been shown that the anion specific conformation can be used to control protein adsorption/desorption on the surface of PSBMA brushes [ 45 ].…”

AtomNet PoseRanker: Enriching Ligand Pose Quality for Dynamic Proteins in Virtual High-Throughput Screens

“…Third, the dynamic nature of proteins is exploited in ligand binding. 10 Different receptor conformations can bind different ligand chemotypes, perhaps best exemplified by the "DFG-in" and "DFG-out" states occupied in different ratios by many protein kinases. 11 Docking a ligand to a rigid receptor conformational substate that deviates from its native bound state (e.g., an apo state) can result in inaccurate predictions of the bound complex that are not useful for further drug design applications.…”