Predicting the permeability coefficient (P) of drugs permeating through the cell membrane is of paramount importance in drug discovery. We here propose an approach for calculating P based on bias-exchange metadynamics. The approach allows constructing from atomistic simulations a model of permeation taking explicitly into account not only the "trivial" reaction coordinate, the position of the drug along the direction normal to the lipid membrane plane, but also other degrees of freedom, for example, the torsional angles of the permeating molecule, or variables describing its solvation/desolvation. This allows deriving an accurate picture of the permeation process, and constructing a detailed molecular model of the transition state, making a rational control of permeation properties possible. We benchmarked this approach on the permeation of ethanol molecules through a POPC membrane, showing that the value of P calculated with our model agrees with the one calculated by a long unbiased molecular dynamics of the same system.
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http://dx.doi.org/10.1021/jp301083h | DOI Listing |
Nat Mach Intell
January 2025
Engineering Laboratory, University of Cambridge, Cambridge, UK.
Molecular dynamics simulation is an important tool in computational materials science and chemistry, and in the past decade it has been revolutionized by machine learning. This rapid progress in machine learning interatomic potentials has produced a number of new architectures in just the past few years. Particularly notable among these are the atomic cluster expansion, which unified many of the earlier ideas around atom-density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message-passing neural network with equivariant features that exhibited state-of-the-art accuracy at the time.
View Article and Find Full Text PDFCarbon-carbon (C/C) composites are attractive materials for high-speed flights and terrestrial atmospheric reentry applications due to their insulating thermal properties, thermal resistance, and high strength-to-weight ratio. It is important to understand the evolving structure-property correlations in these materials during pyrolysis, but the extreme laboratory conditions required to produce C/C composites make it difficult to quantify the properties . This work presents an atomistic modeling methodology to pyrolyze a crosslinked phenolic resin network and track the evolving thermomechanical properties of the skeletal matrix during simulated pyrolysis.
View Article and Find Full Text PDFSoft Matter
January 2025
Dipartimento di Chimica e Chimica Industriale, University of Pisa, via Moruzzi 13, Pisa 56124, Italy.
In the field of chiral smectic liquid crystals, orthoconic antiferroelectric liquid crystals (OAFLCs) have attracted the interest of the scientific community due to the very high tilt angle, close to 45°, and the consequent optical properties. In the present study, the first H NMR investigation is reported on two samples, namely 3F5HPhF9 and 3F7HPhF8, showing the phase sequence isotropic-SmC*-SmC* and the phase sequence isotropic-SmA-SmC*-SmC*, respectively, when cooling from the isotropic to the crystalline phases. To this aim, the liquid crystals were doped with a small amount of deuterated probe biphenyl-4,4'-diol-d.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Chemistry, Kansas State University, Manhattan, Kansas 66506, United States.
Gold nanoparticles can exhibit unique physical and chemical properties, such as plasmon resonances or photoluminescence. These nanoparticles have many atoms, which leads to high computational costs for density functional theory (DFT) calculations. In this work, we used the FLARE++ (fast learning of atomistic rare events) code and incorporated an active learning algorithm to construct force fields for gold thiolate-protected nanoclusters.
View Article and Find Full Text PDFJ Phys Chem B
January 2025
Department of Chemistry, Indian Institute of Technology Kharagpur, Kharagpur 721302, India.
The microbial aminotransferase enzyme DapC is vital for lysine biosynthesis in various Gram-positive bacteria, including . Characterization of the enzyme's conformational dynamics and identifying the key residues for ligand binding are crucial for the development of effective antimicrobials. This study employs atomistic simulations to explore and categorize the dynamics of DapC in comparison to other classes of aminotransferase.
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