Optimization of ligand functionalized nanoparticles using molecular modeling and machine learning

Optimization of ligand functionalized nanoparticles using molecular modeling and machine learning

Feb 28, 2020 - 3:10 PM
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Yaroslava YingLIngYaroslava Yingling

Department of Materials Science & Engineering, North Carolina State University

(Potoyan)

Ligand-functionalized metal nanoparticles (NPs) are actively used in many applications, such as drug delivery, biosensing, catalysis, supramolecular chemistry and solar energy. The nature of the ligand determines the atomic structure, solubility, stability, electrochemical properties and functionality of NPs. Despite extensive research efforts in understanding the correlation between nanoparticle structure and resultant composite material properties, there has been no systematic studies focusing on the design of ligand chemistry toward optimization of a specific material property mainly due to complexity of underlying processes. Here, we apply a combination of molecular modeling and machine learning (ML) techniques for optimization of ligand functionalized nanoparticles (NPs) for interactions with nucleic acids and other NPs. In our approach we use a combination of high-throughput molecular dynamics simulations and data available from the literature to understand correlations and to train the ML model. We also attempt to address the uncertainty associated with MD simulations in the development of the model. Our methods can significantly speed up the search for a new organic monomers (complex ligands or polymers) design based on experimental data, in silico data and available literature data.

Yaroslava G. Yingling is Professor and Director of Undergraduate Program at Materials Science and Engineering at North Carolina State University.  She received her University Diploma in Computer Science and Engineering from St. Petersburg State Technical University of Russia in 1996 and her PhD in Materials Engineering and High Performance Computing from the Pennsylvania State University in 2002. She carried out postdoctoral research at Penn State University Chemistry Department and at the National Institutes of Health National Cancer Institute prior to joining North Carolina State University in 2007. She received the National Science Foundation CAREER award, American Chemical Society Open Eye Young Investigator Award and was named a NCSU University Faculty Scholar. Research interests in Prof. Yingling’s group are focused on the development of materials informatics for soft materials, advanced computational models and novel algorithms for multiscale molecular modeling of soft and biological materials. She has published more than 90 papers, gave more than 100 invited talks and seminars, organized more than 10 professional symposiums and workshops and has been serving as an Editor for Journal of Materials Science and as an Editorial Board Member of ACS Biomaterials Science and Engineering and ACS Applied Materials and Interfaces.