DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Machine Learning of Performance Space Mapping for the DPD Simulation of Drug Delivery to Endothelial Cells

Journal Article · · Molecular Simulation
 [1];  [1];  [2];  [2];  [1]
  1. Case Western Reserve University, Cleveland, OH (United States)
  2. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Despite huge effort over the years, the design of functionalised nanocarriers (NCs) for targeted drug delivery to endothelial cells is still to be completely unveiled. Dissipative particle dynamics (DPD) simulation is used to study the adhesion of NCs to endothelial cells under the influence of series of parameters such as shape, size, and ligand density of the NCs. However, preparing a performance space mapping that illustrates the penetration depths of NCs as a function of variations in their properties requires simulations of all possible NCs with the above-mentioned properties, which is not feasible. This challenge was addressed by leveraging a Gaussian process regression (GPR)-informed active learning strategy and an extensive exploration of numerous samples, each representing different properties of NCs. The performance space mapping reveals that NCs with rod and disc shapes exhibit superior penetration capabilities compared to those with a spherical shape. Furthermore, it demonstrates that smaller-sized rod-shaped NCs and larger-sized disc-shaped NCs tend to achieve better penetration. When considering smaller NCs, the influence of ligand density appears to be limited. On the contrary, for larger NCs, an increase in ligand density correlates with greater penetration depth, underscoring its substantial role in shaping their penetration capabilities.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); National Science Foundation (NSF)
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
2350884
Report Number(s):
LLNL-JRNL-864050; 1097475
Journal Information:
Molecular Simulation, Journal Name: Molecular Simulation Journal Issue: 10 Vol. 50; ISSN 0892-7022
Publisher:
Taylor & FrancisCopyright Statement
Country of Publication:
United States
Language:
English

References (34)

Machine learning of lubrication correction based on GPR for the coupled DPD–DEM simulation of colloidal suspensions journal January 2021
Size, geometry and mobility of protein assemblage regulate the kinetics of membrane wrapping on nanoparticles journal July 2021
Surface wave excitations and backflow effect over dense polymer brushes journal March 2016
Dynamic Simulations of Hard-Sphere Suspensions Under Steady Shear journal January 1993
Janus Nanoparticles Enable Entropy-Driven Mixing of Bicomponent Hydrogels journal October 2019
Predicting molecular ordering in a binary liquid crystal using machine learning journal August 2019
Effect of Particle Diameter and Surface Composition on the Spontaneous Fusion of Monolayer-Protected Gold Nanoparticles with Lipid Bilayers journal August 2013
Simulation and modelling of slip flow over surfaces grafted with polymer brushes and glycocalyx fibres journal September 2012
Computer simulation of the translocation of nanoparticles with different shapes across a lipid bilayer journal July 2010
Structure and elasticity of bush and brush-like models of the endothelial glycocalyx journal January 2018
Biodistribution and clearance of a filamentous plant virus in healthy and tumor-bearing mice journal February 2014
Adhesion dynamics of functionalized nanocarriers to endothelial cells: a dissipative particle dynamics study journal January 2023
Molecular modeling of the relationship between nanoparticle shape anisotropy and endocytosis kinetics journal June 2012
Nanoinclusions in Dry Polymer Brushes journal January 2006
Design rules for nanomedical engineering: from physical virology to the applications of virus-based materials in medicine journal March 2013
Conformational switching of modified guest chains in polymer brushes journal July 2013
Supervised learning for accurate mesoscale simulations of suspension flow in wall-bounded geometries journal May 2022
Membrane penetration and trapping of an active particle journal February 2019
Adsorption of a spherical nanoparticle in polymer brushes: Brownian dynamics investigation journal September 2013
Adhesion of nanoparticles to polymer brushes studied with the ghost tweezers method journal January 2015
Interactions between Grafted Cationic Dendrimers and Anionic Bilayer Membranes journal August 2013
Statistical Mechanics of Dissipative Particle Dynamics journal May 1995
The Role of Machine Learning in the Understanding and Design of Materials journal November 2020
Endothelial Targeting of High-Affinity Multivalent Polymer Nanocarriers Directed to Intercellular Adhesion Molecule 1 journal February 2006
Effect of ligand density, receptor density, and nanoparticle size on cell targeting journal February 2013
Selective membrane wrapping on differently sized nanoparticles regulated by clathrin assembly: A computational model journal June 2022
Morphology of Polymer Brushes Infiltrated by Attractive Nanoinclusions of Various Sizes journal June 2013
Inclusion Free Energy of Nanoparticles in Polymer Brushes journal October 2012
Margination Propensity of Vascular-Targeted Spheres from Blood Flow in a Microfluidic Model of Human Microvessels journal February 2013
Excess free energy of nanoparticles in a polymer brush journal August 2008
Collective ordering of colloids in grafted polymer layers journal January 2013
Effect of solvent quality on the dispersibility of polymer-grafted spherical nanoparticles in polymer solutions journal September 2012
Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows journal February 2021
Critical Conditions of Adhesion and Separation of Functionalized Nanoparticles on Polymer Grafted Substrates journal April 2019