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Allostery describes the functional coupling between sites in biomolecules. Recently, the role of changes in protein dynamics for allosteric communication has been highlighted. A quantitative and predictive description of allostery is fundamental for understanding biological processes. Here, we integrate an ensemble-based perturbation approach with the analysis of biomolecular rigidity and flexibility to construct a model of dynamic allostery. Our model, by definition, excludes the possibility of conformational changes, evaluates static, not dynamic, properties of molecular systems, and describes allosteric effects due to ligand binding in terms of a novel free-energy measure. We validated our model on three distinct biomolecular systems: eglin c, protein tyrosine phosphatase 1B, and the lymphocyte function-associated antigen 1 domain. In all cases, it successfully identified key residues for signal transmission in very good agreement with the experiment. It correctly and quantitatively discriminated between positively or negatively cooperative effects for one of the systems. Our model should be a promising tool for the rational discovery of novel allosteric drugs.

The catalytic subunit of protein kinase A (PKA-C) is subject to several post- or cotranslational modifications that regulate its activity both spatially and temporally. Among those, N-myristoylation increases the kinase affinity for membranes and might also be implicated in substrate recognition and allosteric regulation. Here, we investigated the effects of N-myristoylation on the structure, dynamics, and conformational equilibrium of PKA-C using atomistic molecular dynamics simulations. We found that the myristoyl group inserts into the hydrophobic pocket and leads to a tighter packing of the A-helix against the core of the enzyme. As a result, the conformational dynamics of the A-helix are reduced and its motions are more coupled with the active site. Our simulations suggest that cation-π interactions among W30, R190, and R93 are responsible for coupling these motions. Two major conformations of the myristoylated N-terminus are the most populated: a long loop (LL conformation), similar to Protein Data Bank (PDB) entry 1CMK , and a helix-turn-helix structure (HTH conformation), similar to PDB entry 4DFX , which shows stronger coupling between the conformational dynamics observed at the A-helix and active site. The HTH conformation is stabilized by S10 phosphorylation of the kinase via ionic interactions between the protonated amine of K7 and the phosphate group on S10, further enhancing the dynamic coupling to the active site. These results support a role of N-myristoylation in the allosteric regulation of PKA-C.

We present a thermodynamical approach to identify changes in macromolecular structure and dynamics in response to perturbations such as mutations or ligand binding, using an expansion of the Kullback-Leibler Divergence that connects local population shifts in torsion angles to changes in the free energy landscape of the protein. While the Kullback-Leibler Divergence is a known formula from information theory, the novelty and power of our implementation lies in its formal developments, connection to thermodynamics, statistical filtering, ease of visualization of results, and extendability by adding higher-order terms. We present a formal derivation of the Kullback-Leibler Divergence expansion and then apply our method at a first-order approximation to molecular dynamics simulations of four protein systems where ligand binding or pH titration is known to cause an effect at a distant site. Our results qualitatively agree with experimental measurements of local changes in structure or dynamics, such as NMR chemical shift perturbations and hydrogen-deuterium exchange mass spectrometry. The approach produces easy-to-analyze results with low background, and as such has the potential to become a routine analysis when molecular dynamics simulations in two or more conditions are available. Our method is implemented in the MutInf code package and is available on the SimTK website at https://simtk.org/home/mutinf.