Abstract
The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.
Original language | English |
---|---|
Pages (from-to) | 1643-1653 |
Number of pages | 11 |
Journal | Biochimica et Biophysica Acta - Proteins and Proteomics |
Volume | 1865 |
Issue number | 11 |
DOIs | |
State | Published - Nov 2017 |
Externally published | Yes |
Funding
This work was supported by research grants from the NSERC ( RGPIN-315019 ), National Institutes of Health R01HL128537-01A1 to SYN; from Alberta Innovate Health Solutions (AIHS) and Canadian Institutes for Health Research (CIHR) postdoctoral fellowships (to V.A.N.); from AIHS and Vanier Canada Graduate Studentship (to W.M.) and by Alberta Innovates Technical Future through Strategic Chair in Biomolecular Simulations (to Peter D. Tieleman). The useful discussions with Colleen E. Clancy, Yibo Wang, Peter Tieleman, Toby Allen and Benoît Roux are greatly appreciated.
Funders | Funder number |
---|---|
Vanier Canada Graduate Studentship | W.M |
Foundation for the National Institutes of Health | R01HL128537-01A1 |
National Heart, Lung, and Blood Institute | R01HL128537 |
Canadian Institutes of Health Research | |
Natural Sciences and Engineering Research Council of Canada | RGPIN-315019 |
Alberta Innovates - Health Solutions | |
Alberta Innovates - Technology Futures |
Keywords
- Integral membrane proteins
- Kinetic cell models
- Markov State Models
- Molecular dynamics simulations
- Protein-ligand interactions