The direct-site hypothesis assumes general anesthetics bind ion channels to impact protein equilibrium and function, inducing anesthesia. Despite advancements in the field, a first principle all-atom demonstration of this structure-function premise is still missing. We focus on the clinically used sevoflurane interaction to anesthetic-sensitive Kv1.2 mammalian channel to resolve if sevoflurane binds protein’s well-characterized open and closed structures in a conformation-dependent manner to shift channel equilibrium. We employ an innovative approach relying on extensive docking calculations and free-energy perturbation of all potential binding sites revealed by the latter, and find sevoflurane binds open and closed structures at multiple sites under complex saturation and concentration effects. Results point to a non-trivial interplay of site and conformation-dependent modes of action involving distinct binding sites that increase channel open-probability at diluted ligand concentrations. Given the challenge in exploring more complex processes potentially impacting channel-anesthetic interaction, the result is revealing as it demonstrates the process of multiple anesthetic binding events alone may account for open-probability shifts recorded in measurements.

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2,2,2-Trichloroethanol (TCE) is the active form of the sedative hypnotic drug chloral hydrate, one of the oldest sleep medications in the market. Understanding of TCE’s action mechanisms to its many targets, particularly within the ion channel family, could benefit from the state-of-the-art computational molecular studies. In this direction, we employed de novo modeling aided by the force field toolkit to develop CHARMM36-compatible TCE parameters. The classical potential energy function was calibrated targeting molecular conformations, local interactions with water molecules, and liquid bulk properties. Reference data comes from both tabulated thermodynamic properties and ab initio calculations at the MP2 level. TCE solvation free energy calculations in water and oil reproduce a lipophilic, yet nonhydrophobic, behavior. Indeed, the potential mean force profile for TCE partition through the phospholipid bilayer reveals the sedative’s preference for the interfacial region. The calculated partition coefficient also matches experimental measures. Further validation of the proposed parameters is supported by the model’s ability to recapitulate quenching experiments demonstrating TCE binding to bovine serum albumin.

Small-molecule modulators of diverse voltage-gated K+ (Kv) channels may help treat severe neurological disorders. However, the development of selective modulators requires an understanding of their mechanism-of-action (MoA). We applied an orthogonal approach to elucidate the MoA of an imidazolidinedione derivative (AUT5), which is a highly specific positive allosteric modulator (PAM) of Kv3.1 and Kv3.2 channels. AUT5 modulation involves positive cooperativity and preferential stabilization of the open state. Critically, we found that the unique and highly conserved extracellular turret region of Kv3.1 and Kv3.2 essentially governs AUT5 modulation. Furthermore, leveraging on the cryo-EM structure of Kv3.1a, atomistic blind docking calculations revealed four equivalent AUT5 binding sites near the turrets and between the voltage-sensing and pore domains of the channel’s tetrameric assembly. Therefore, the unique Kv3 turret emerges as a novel structural correlate of the selective MoA of a new class of Kv3 channel PAMs with a therapeutic potential.

Macromolecular processes are governed by their free energy landscape and thus often depend on a delicate balance of enthalpy and entropy. The hydrophobic effect, which is crucial for protein folding, is largely governed differences in rotational solvent entropy. It is therefore essential to have a quantitative understanding of the thermodynamics of solvation, and in particular the associated rotational entropies. To quantify the entropic effects of local features, such as individual amino acids, spatial resolution is required. Whereas several methods yield solute entropies from atomistic simulations, spatially resolved solvation shell entropies are notoriously difficult to obtain. Here we present a new method, which employs a mutual information expansion to compute spatially resolved rotational solvent entropies. Mutual information terms are calculated using a non-parametric k-nearest-neighbor density estimator, which we adapted for SO(3) n , the group of rotations and its product spaces. We assessed and applied our method to atomistic simulations of pure water and small proteins, where we quantified pronounced topological effects and entropy losses due to correlated dynamics at hydrophobic interfaces.