Drug-Nanoparticle Composites: A Predictive Model for Mass Loading

Drug-Nanoparticle Composites: A Predictive Model for Mass Loading

Natalia Sizochenko (Interdisciplinary Center of Nanotoxicity, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS, USA) and Jerzy Leszczynski (Interdisciplinary Center for Nanotoxicity, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS, USA)
Copyright: © 2017 |Pages: 10
DOI: 10.4018/JNN.2017010101
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Polymeric nanoparticles represent attractive targets for the controlled delivery of therapeutic drugs. Drug-nanoparticle conjugates are convenient targets to enhance solubility and membrane permeability of drugs, prolong circulation time and minimize non-specific uptake. The behavior of drugs-loaded nanoparticles is governed by various factors. Understanding of these effects is very important for design of drug-nanoparticle systems, that could be suitable for treating the particular diseases. The aim of the current study is a complementary molecular docking followed by quantitative structure-activity relationships modeling for drugs payload on polymeric nanoparticles. Twenty-one approved drugs were considered. Docking of drugs was performed towards a simplified polymeric surface. Binding energies agreed well with the observed mass loading. Quantitative structure-activity relationships model supported this data. Effects of electronegativity and hydrophobicity were discussed. Developed model may contribute to the development of other useful nano-sized polymeric drug carriers to deliver a spectrum of therapeutic and imaging agents for medical purposes.
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1. Introduction

Drug development is an expensive and time-consuming process. In order to save time and money, in most cases it is more effective to improve efficacy and safety of known drugs, rather than develop new drugs. For this purpose, different methods such as individualized drug therapy, dose titration, and therapeutic drug monitoring were developed (Tiwari, et al., 2012). One of the possible ways of drug delivery is the usage of nanoparticles. Poly(ε-caprolactone), poly(lactic acid), poly(glycolic acid), and their copolymers are the most popular polymers to be used as drug carriers (Jeong, Bae, Lee & Kim, 1997; Brewer, Coleman, & Lowman, 2011). They are safe, highly biodegradable and approved by the US Food and Drug Administration (FDA) (Tiwari et al., 2012; Chiellini & Solaro, 1996). In addition, polymeric nanoparticles are suitable species for the surface modification. Hence, polymeric nanoparticles suitable candidates for drug delivery. Different drugs that can be explored in combination with polymeric nanoparticles include: small molecules, proteins, nucleic acids, diagnostic agents (Morachis, Mahmoud & Almutairi, 2012). Targeted drug delivery using polymeric nanoparticles has a vast potential in diagnosis and treatment (Torchilin, 2007; Singh & Lillard, 2009). Application of such species as drug carriers can notably reduce side effects and increase residence time in the body (Brewer, Coleman, & Lowman, 2011; Scarpa et al., 2016; Mørch, et al., 2015). Polymeric nanoparticles could also be used to deliver multiple drugs simultaneously (Scarpa et al., 2016; Mørch et al., 2015). They can stabilize and protect loaded drugs from degradation (Panyam & Labhasetwar, 2003).

Physical and chemical properties of both polymeric nanoparticles and drugs have influence on drug delivery. Systematical evaluation of the influence of different physicochemical parameters of drugs and nanomaterials was performed in different papers (Morachis, Mahmoud & Almutairi, 2012; Wang & Dormidontova, 2010; Bae, Fukushima, Harada & Kataoka, 2003). For instance, binding affinity and specificity are two important aspects of nanoparticle targeting that characterize the performance of nanoparticle delivery systems (Wang & Dormidontova, 2010). Wang and Dormidontova found that nanoparticle affinity is affected by variations in the binding energy, number of ligands, tether length, density, and nanoparticle’s size (Wang & Dormidontova, 2010).

Effectiveness of a drug delivery device is system-dependent on drug loading and drug release. High drug loading capacity is the necessity for a successful delivery (Bae, Fukushima, Harada & Kataoka, 2003). In general, release/loading rates depend on drug solubility, sorption-desorption processes, drug diffusion and erosion/diffusion processes in nanoparticle.

Properties of nanoparticles loaded with drug can be predicted using simulation methods. In silico predictions of properties of nanomaterials represent the cutting edge of non-testing methods. For instance, Costache et al. modeled drug-polymer interactions in polyethylene glycol-tyrosine copolymer nanospheres (Costache, Sheihet, Zaveri, Knight & Kohn, 2009). However, all atoms simulations usually require big amounts of computer time. Simple and quick methods, such as molecular docking or Quantitative Structure-Property Relationship (QSAR) analysis could be applied to identify candidate materials (Winkler et al., 2014; Sizochenko & Leszczynski, 2016; Rasulev et al., 2017). Such modeling could be used to fill the informational gap between modern theories of mechanisms of nanoparticle’s action and property predictions.

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