In silico pharmacology: Drug membrane partitioning and crossing

Meo, Florent Di; Fabre, Gabin; Berka, Karel; Ossman, Tahani; Chantemargue, Benjamin; Paloncýová, Markéta; Marquet, Pierre; Otyepka, Michal; Trouillas, Patrick

doi:10.1016/j.phrs.2016.06.030

Cited by 51 publications

(34 citation statements)

References 201 publications

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“…An experimental P estimate for d-sotalol based on measurements using PAMPA is in between our computed values for SotC and SotN (see Table 1 and Liu et al, 2012 ). Yet, a direct numerical comparison of our computed and experimental P estimates is extremely challenging, as has been indicated in many previous studies (Orsi et al, 2009 ; Carpenter et al, 2014 ; Di Meo et al, 2016 ; Bennion et al, 2017 ). This is largely because experimentally measured quantities mostly represent so-called apparent values, which typically include contributions from different drug protonation forms at experimental pH, depend on water layer thickness and condition, and may encompass different drug permeation routes (Bermejo et al, 2004 ; Avdeef et al, 2005 ; Ottaviani et al, 2006 ; Orsi et al, 2009 ).…”

Section: Discussionmentioning

confidence: 86%

“…We have employed one such technique, umbrella sampling (US) (Torrie and Valleau, 1977 ), in this report in order to compute the free energies and diffusion coefficients required for drugs to pass through the cell membrane. Similar approaches have been used for various drug molecules in a number of other studies (Carpenter et al, 2014 ; Di Meo et al, 2016 ; Bennion et al, 2017 ), including previous works by our groups (Boiteux et al, 2014 ; Yang et al, 2016 ). The approaches and data presented here serve as preliminary steps in overcoming the many challenges that arise in the messy task of atomistic in silico predictive cardiovascular pharmacology.…”

Section: Introductionmentioning

confidence: 78%

“…Experimental estimates for d-sotalol P are available from a recent study (Liu et al, 2012 ) with a PAMPA P -value of 3.2 × 10 −7 cm/s. A direct comparison between experimental and computed P values is known to be challenging, with many complicating factors precluding direct quantitative assessment of absolute values (Carpenter et al, 2014 ; Di Meo et al, 2016 ; Bennion et al, 2017 ). Nevertheless, we computed P estimates for both SotC and SotN using Equation (8) as was done in our previous study (Vorobyov et al, 2014 ) based on free energy and diffusion coefficient profiles.…”

Section: Resultsmentioning

confidence: 99%

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Digging into Lipid Membrane Permeation for Cardiac Ion Channel Blocker d-Sotalol with All-Atom Simulations

et al. 2018

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Interactions of drug molecules with lipid membranes play crucial role in their accessibility of cellular targets and can be an important predictor of their therapeutic and safety profiles. Very little is known about spatial localization of various drugs in the lipid bilayers, their active form (ionization state) or translocation rates and therefore potency to bind to different sites in membrane proteins. All-atom molecular simulations may help to map drug partitioning kinetics and thermodynamics, thus providing in-depth assessment of drug lipophilicity. As a proof of principle, we evaluated extensively lipid membrane partitioning of d-sotalol, well-known blocker of a cardiac potassium channel Kv11.1 encoded by the hERG gene, with reported substantial proclivity for arrhythmogenesis. We developed the positively charged (cationic) and neutral d-sotalol models, compatible with the biomolecular CHARMM force field, and subjected them to all-atom molecular dynamics (MD) simulations of drug partitioning through hydrated lipid membranes, aiming to elucidate thermodynamics and kinetics of their translocation and thus putative propensities for hydrophobic and aqueous hERG access. We found that only a neutral form of d-sotalol accumulates in the membrane interior and can move across the bilayer within millisecond time scale, and can be relevant to a lipophilic channel access. The computed water-membrane partitioning coefficient for this form is in good agreement with experiment. There is a large energetic barrier for a cationic form of the drug, dominant in water, to cross the membrane, resulting in slow membrane translocation kinetics. However, this form of the drug can be important for an aqueous access pathway through the intracellular gate of hERG. This route will likely occur after a neutral form of a drug crosses the membrane and subsequently re-protonates. Our study serves to demonstrate a first step toward a framework for multi-scale in silico safety pharmacology, and identifies some of the challenges that lie therein.

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Section: Discussionmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 78%

Section: Resultsmentioning

confidence: 99%

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Digging into Lipid Membrane Permeation for Cardiac Ion Channel Blocker d-Sotalol with All-Atom Simulations

et al. 2018

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“…Anesthetic flavonoids were isolated from Tanacetum parthenium (Asteraceae) [ 115 ], Valeriana wallichii (Valerianaceae) [ 116 ] and Artemisia herba-alba (Asteraceae) [ 119 ] by preparative chromatography that was guided by the benzodiazepine radioligand binding assay with GABA A receptors. Phytochemicals mechanistically interact with neuronal membranes as well as anesthetics and anesthesia-related drugs [ 11 , 152 , 153 , 154 ]. In addition to bioassay and radioligand binding assay, the membrane interactivity would give another clue to discover anesthetic phytochemicals.…”

Section: Clinical Applicability Of Phytochemicalsmentioning

confidence: 99%

Anesthetic Agents of Plant Origin: A Review of Phytochemicals with Anesthetic Activity

Tsuchiya

2017

Molecules

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The majority of currently used anesthetic agents are derived from or associated with natural products, especially plants, as evidenced by cocaine that was isolated from coca (Erythroxylum coca, Erythroxylaceae) and became a prototype of modern local anesthetics and by thymol and eugenol contained in thyme (Thymus vulgaris, Lamiaceae) and clove (Syzygium aromaticum, Myrtaceae), respectively, both of which are structurally and mechanistically similar to intravenous phenolic anesthetics. This paper reviews different classes of phytochemicals with the anesthetic activity and their characteristic molecular structures that could be lead compounds for anesthetics and anesthesia-related drugs. Phytochemicals in research papers published between 1996 and 2016 were retrieved from the point of view of well-known modes of anesthetic action, that is, the mechanistic interactions with Na+ channels, γ-aminobutyric acid type A receptors, N-methyl-d-aspartate receptors and lipid membranes. The searched phytochemicals include terpenoids, alkaloids and flavonoids because they have been frequently reported to possess local anesthetic, general anesthetic, antinociceptive, analgesic or sedative property. Clinical applicability of phytochemicals to local and general anesthesia is discussed by referring to animal in vivo experiments and human pre-clinical trials. This review will give structural suggestions for novel anesthetic agents of plant origin.

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“…An economically appealing alternative, trading human capital and consumables for computational resources (time and power), is the modeling of drug absorption in the gastrointestinal tract (GIT). In silico models have been developed for both molecular interactions (10), such as receptor binding or transport, and physiology-based pharmacokinetics (PBPK) (11), such as compartment disposition or clearance. Several commercial software packages based on these models (12–14) incorporate drug physiochemical properties (solubility, degradation, permeability, molecular size, aggregation, charge), formulation properties (dosage, drug release profiles, absorption enhancers, matrix polymorphism), and GI physiological properties (gastric emptying, intestinal pH, motility, luminal content, transporters, metabolism, epithelial sequestration, disease state).…”

Section: Introductionmentioning

confidence: 99%

A quantitative model for metabolic intervention using gut microbes

Mays

Nair

2020

Preprint

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5As medicine shifts toward precision-based and personalized therapeutics, utilizing more complex biomolecules to 6 treat increasingly difficult and rare conditions, microorganisms provide an avenue for realizing the production and 7 processing necessary for novel drug pipelines. More so, probiotic microbes can be co-opted to deliver therapeutics 8 by oral administration as living drugs, able to survive and safely transit the digestive tract. As living therapeutics are 9 in their nascency, traditional pharmacokinetic-pharmacodynamic (PK-PD) models for evaluating drug candidates 10 are not appropriate for this novel platform. Using a living therapeutic in late-stage clinical development for 11 phenylketonuria (PKU) as a case study, we adapt traditional oral drug delivery models to properly evaluate and 12 inform the engineering of living therapeutics. We develop the adapted for living therapeutics compartmental 13 absorption and transit (ALT-CAT) model to provide metrics for drug efficacy across nine age groups of PKU patients 14 and evaluate model parameters that are influenced by patient physiology, microbe selection and therapeutic 15 production, and dosing formulations. 16 Importance 17This work describes a kinetic model to study the behavior of orally delivered living therapeutics. Such therapeutics 18 are becoming increasingly relevant and are an exciting mode of drug delivery that stems from the growing interest 19 through the convergence of advances in synthetic biology of probiotics and gut microbes as well as microbiome 20 science. In particular, this work describes the development of a mathematical framework (pharmacokinetic-21 pharmacodynamic, PK-PD) called ALT-CAT to model the behavior of orally delivered engineered bacteria that act as 22 living therapeutics by adapting similar methods that have been developed and widely-used for small molecular drug 23 delivery and absorption. 24 2 Introduction 25The most common and practical route of drug delivery is oral ingestion, pairing patient convenience and high 26 compliance with ease of administration and stability. While a simple initial assessment of a drug's biochemical 27 feasibility for oral delivery can be predicted using the biopharmaceutical classification system (BCS) (1) or rule of 28 five (Ro5) (2), these evaluations do not inform the further complexities of selecting lead candidates, developing a 29 dosage or release strategy, effective bioavailability, and pharmacokinetics. Accordingly, a range of models -in vitro 30(3) and in vivo (4), static (5) and dynamic (6, 7), molecular (8) and system environment (9) -are used extensively in 31 drug development to evaluate and hone desired features. 32 33 An economically appealing alternative, trading human capital and consumables for computational resources (time 34 and power), is the modeling of drug absorption in the gastrointestinal tract (GIT). In silico models have been 35 developed for both molecular interactions (10), such as receptor binding or transport, and physiology-based 36 pharmacokinetics...

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In silico pharmacology: Drug membrane partitioning and crossing

Cited by 51 publications

References 201 publications

Digging into Lipid Membrane Permeation for Cardiac Ion Channel Blocker d-Sotalol with All-Atom Simulations

Digging into Lipid Membrane Permeation for Cardiac Ion Channel Blocker d-Sotalol with All-Atom Simulations

Anesthetic Agents of Plant Origin: A Review of Phytochemicals with Anesthetic Activity

A quantitative model for metabolic intervention using gut microbes

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