Modulation of the Gloeobacter violaceus Ion Channel by Fentanyl: A Molecular Dynamics Study

Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design

Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.

Towards Quantum-Chemical Modeling of the Activity of Anesthetic Compounds

The modeling of the activity of anesthetics is a real challenge because of their unique electronic and structural characteristics. Microscopic approaches relevant to the typical features of these systems have been developed based on the advancements in the theory of intermolecular interactions. By stressing the quantum chemical point of view, here, we review the advances in the field highlighting differences and similarities among the chemicals within this group. The binding of the anesthetics to their partners has been analyzed by Symmetry-Adapted Perturbation Theory to provide insight into the nature of the interaction and the modeling of the adducts/complexes allows us to rationalize their anesthetic properties. A new approach in the frame of microtubule concept and the importance of lipid rafts and channels in membranes is also discussed.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Predicting the Membrane Permeability of Fentanyl and Its Analogues by Molecular Dynamics Simulations

The lipid membrane is considered a crucial component of opioid general anesthesia. The main drug used for the induction and maintenance of opioid anesthesia is fentanyl and its various analogues. However, these drugs have different clinical effects, and detailed atomic-level insight into the drug–membrane interactions could lead to a better understanding how these drugs exert their anesthetic properties. In this study, we have used extensive umbrella sampling molecular dynamics simulations to study the permeation process of fentanyl and three of its analogues into a variety of simple phospholipid membrane models. Our simulations show that we can accurately predict the permeability coefficients of these drug molecules, which is an important process in understanding how pharmaceuticals reach their molecular targets. We were also able to show that one phospholipid provides more accurate predictions than other lipids commonly used in these types of permeation studies, which will aid future studies of these types of processes.

Initial Stages of Spontaneous Binding of Folate-Based Vectors to Folate Receptor-α Observed by Unbiased Molecular Dynamics

Active targeting is a prospective strategy for controlled drug delivery to malignant tumor tissues. One of the approaches relies on recognition of a bioactive ligand by a receptor expressed abundantly on the surface of cancer cell membranes. A promising ligand-receptor pair is folic acid (or its dianionic form, folate) combined with the folate receptor-α (FRα). A number of targeting drug delivery systems based on folate have been suggested, but the mechanism of binding of the ligand or its derivatives to the receptor is not fully known at the molecular level. The current study summarizes the results from unbiased all-atom molecular dynamics simulations at physiological conditions describing the binding of two forms of folate and four of its synthetically available derivatives to FRα. The models (ca. 185,000 atoms) contain one receptor molecule, embedded in the outer leaflet of a lipid bilayer, and one ligand, all immersed in saline. The bilayer represents a human cancer cell membrane and consists of 370 asymmetrically distributed lipid molecules from 35 types. The ability of the vector molecules to bind to the receptor, the position of binding, and the interactions between them are analyzed. Spontaneous binding on the nanosecond scale is observed for all molecules, but its time, position, and persistence depend strongly on the ligand. Only folate, 5-methyltetrahydrofolate, and raltitrexed bind selectively at the active site of the receptor. Two binding poses are observed, one of them (realized by raltitrexed) corresponding qualitatively to that reported for the crystallographic structure of the complex folate-FRα. Pemetrexed adsorbs nonspecifically on the protein surface, while methotrexate and pteroyl ornithine couple much less to the receptor. The molecular simulations reproduce qualitatively correctly the relative binding affinity measured experimentally for five of the ligands. Analysis of the interactions between the ligands and FRα shows that in order to accomplish specific binding to the active site, a combination of hydrogen bonding, π-stacking, and van der Waals and Coulomb attraction should be feasible simultaneously for the vector molecule. The reported results demonstrate that it is possible to observe receptor-ligand binding without applying bias by representing the local environment as close as possible and contain important molecular-level guidelines for the design of folate-based systems for targeted delivery of anticancer drugs.

In silico studies of the interactions between propofol and fentanyl using Gaussian accelerated molecular dynamics

Fentanyl is a potent opioid analgesic, which for decades has been used routinely in surgical and therapeutic applications. In addition to its analgesic properties, fentanyl also possesses anesthetic properties, which are not well understood. Fentanyl is used in the general anesthesia process to induce and maintain anesthesia in combination with the general anesthetic propofol, which fentanyl is known to potentiate. As the atomic-level mechanism behind the potentiation of propofol is unclear, we have used classical molecular dynamics simulations to study the interactions of these drugs with the Gloeobacter violaceus ion channel (GLIC). This ion channel has been identified as a target for many anesthetic drugs. We identified multiple binding sites using flooding style and Gaussian accelerated molecular dynamics (GaMD) simulations, showing fentanyl acting as a stabiliser that holds propofol within binding sites. Our extensive GaMD simulations were also able to show the pathway by which propofol blocks the channel pore, which has previously been suggested as a mechanism for ion channel modulation. General anesthesia is a multi-drug process and this study provides the first insight into the interactions between two different drugs in the anesthesia process in a relevant biological environment.Communicated by Ramaswamy H. Sarma.

Atomistic Molecular Dynamics Simulations of Propofol and Fentanyl in Phosphatidylcholine Lipid Bilayers

Atomistic molecular dynamics (MD) and steered MD simulations in combination with umbrella sampling methodology were utilized to study the general anesthetic propofol and the opioid analgesic fentanyl and their interaction with lipid bilayers, which is not yet fully understood. These molecules were inserted into two different fully hydrated phospholipid bilayers, namely, dioleoylphosphatidylcholine (DOPC) and dipalmitoylphosphatidylcholine (DPPC), to investigate the effects that these drugs have on the bilayer. We determined the role of the lipid chain length and saturation on the behavior of the two drugs. Pure, fully hydrated DOPC and DPPC bilayers were also simulated, and the results were in excellent agreement with the experimental values. Various structural and mechanical properties of each system, such as the area per lipid, area compressibility modulus, order parameter, lateral lipid diffusion, hydrogen bonds, and radial distribution functions, have been calculated to assess how the drug molecules affect the different bilayers. From the calculated results, we show that fentanyl and propofol generally follow similar trends in each bilayer but adopt different favorable positions close to the headgroup/chain interface at the carbonyl groups. Propofol was shown to selectively form hydrogen bonds at the carbonyl carbon in each bilayer, whereas fentanyl interacts with water molecules at the headgroup interface. From the calculated free-energy profiles, we determined that both molecules show a preference for the low-density, low-order acyl chain region of the bilayers and both significantly preferred the DOPC bilayer with propofol and fentanyl having energy minima at -6.66 and -43.07 kcal mol^-1, respectively. This study suggests that different chain lengths and levels of saturation directly affect the properties of these two important molecules, which are seen to work together to control anesthesia in surgical applications.