Computational modeling of polymeric nanoparticles as drug carriers have been extensively studied due to their varied functionalities, tunable structures and the capability of controlled drug release. Nano particulate polymeric drug delivery systems enable a cell specific targeting with negligible side effects and drug release based on change in physiological conditions. Eight common polymers are modeled and the various properties have been predicted. ADMET, QSAR, thermodynamic and electronic properties have been predicted and compared using SAR as well as quantum mechanical density functional methods. Comparison of the predicted properties suggests that chitosan, which is a natural polymer and has some advantages over others is a promising drug carrier candidate for tumor

G, Kavitha

Kutty, K Narayanan

P K, Krishnan Namboori

Silviya, Ann Elizabeth

English

International Journal of Drug Delivery

   
 
International Journal of Drug Delivery 7 (2015) 27-31 
http://www.arjournals.org/index.php/ijdd/index 
 
Original Research Article 
             
Insilico modeling of chitosan as a drug delivery system   
  Ann Elizabeth Silviya1, Kavitha G2,3, K Narayanan Kutty3 , Krishnan Namboori PK4* 
 
*Corresponding author: 
 
Krishnan Namboori PK 
 
1Department of ECE, AMRITA Vishwa 
Vidyapeetham, Coimbatore-641 112 
2Research and development centre, 
Bharathiar University, Coimbatore-641 
046 
3Department of Physics, AMRITA 
Vishwa Vidyapeetham, Amritapuri, 
Kollam-690525 
4Computational Chemistry Research 
Group, AMRITA Vishwa 
Vidyapeetham, Coimbatore-641 112. 
 
 
 
A b s t r a c t  
Computational modeling of polymeric nanoparticles as drug carriers have been extensively studied 
due to their varied functionalities, tunable structures and the capability of controlled drug release. 
Nano particulate polymeric drug delivery systems enable a cell specific targeting with negligible side 
effects and drug release based on change in physiological conditions. Eight common polymers are 
modeled and the various properties have been predicted. ADMET, QSAR, thermodynamic and 
electronic properties have been predicted and compared using SAR as well as quantum mechanical 
density functional methods. Comparison of the predicted properties suggests that chitosan, which is 
a natural polymer and has some advantages over others is a promising drug carrier candidate for 
tumor. 
Keywords: Drug delivery systems, chitosan, QSAR, quantum mechanical modeling 
 
 
Introduction 
Drug delivery systems (DDS) have been developed to carry the 
drugs to specific targets,especially to tumor sites without being 
exposed to other normal tissues or organs. The administrated drug 
may interact with the biomolecules that they pass through and may 
damage the normal cells also [1]. Moreover, rapid clearance from 
the bloodstream and the inability to cross certain membrane 
barriers are some additional problems faced by the drug 
molecules. This may lead into a decrease in bioavailability, limit the 
efficacy and leave few tumor cells from not exposing to the entire 
dose. A proper drug delivery system may overcome the difficulties 
and prevent the drug from rapid clearance and improve the 
availability at the target site. The drug carrier properties[2] 
amounting to its efficiency include solubility, stability, molecular 
weight, molecular volume, interaction with drug molecules, 
charging and discharging of drugs etc. The drug carriers should be 
stable to biological fluids, free from rapid degradation and 
clearance from the bloodstream and should be biocompatible and 
non-toxic.2 The design of an efficient drug carrier system depends 
on several factors like drug-carrier interaction, transport of drug 
molecules through the body to the desired site and the drug 
release profile. The development of such systems mainly aims at 
delivering drugs to specific target cells, 
necessitating biological efficiency and smartness. With the outburst 
of nano-systems, a number of efficient novel drug delivery systems 
have entered into the scene. Polymeric nanoparticles are 
advantageous [3,4] systems because of their varied and efficient 
properties like biocompatibility, increased efficacy and capability of 
controlled drug release. Proper optimization of the drug carrier 
system for each drug is a time consuming and difficult task. 
Moreover, in most cases, the suggested systems fail to work 
properly in the biological real environments, necessitating a proper 
designing phase before the systems are really developed. 
Computational modeling and simulation may provide a design 
phase for the ÂDrug Delivery SystemÊ to be considered. The natural 
polymer chitosan has conquered the scene recently due to its 
biocompatibility, low toxicity, and biodegradability. The advanced 
development of chitosan nano systems has led to new smart drug 
delivery systems that release their drug payloads under varying 
environmental stimuli. Computational analysis of these nano-
systems facilitates prediction of properties in the design phase 
itself helping in developing smart drug delivery systems. A 
preliminary computational analysis of common drug delivery 
systems to assess the efficiency of each system has been taken up 
in this work. Structure-Activity Relationship (SAR) studies and 
quantum mechanical modeling are two important methods in 
designing and developing a drug delivery system. The structure 
could be described by using descriptors or by physicochemical 
properties like logP, logD, solubility etc. 
ISSN: 0975-0215 
  
This work is licensed under a Creative Commons Attribution 3.0 License.  
PK et al.  International Journal of Drug Delivery 7 (1) 27-31 [2015] 
 
 
  
PAGE | 28 |
 
Major pharmacophoric attributes among them are ADMET 
descriptor [5] .The toxicity analysis has a very important role in the 
designing of a drug delivery system. The initial prediction of the 
pharmacokinetic properties helps in the optimization and testing of 
the most eligible candidates. Quantum mechanical modeling [6] 
helps in predicting electronic descriptors and can be used for 
studying the interactional efficiency of the molecules with the drug 
delivery systems. DFT computational technique is an efficient 
quantum mechanical level computation used to investigate the 
structural and electronic properties of molecules, materials and 
defects. In this manuscript, eight common drug delivery materials 
have been taken and compared their various properties using SAR 
studies and quantum mechanical modeling. 
Materials and Methods 
Common drug delivery systems targeting tumor cells, chitosan, 
oxyethylene, alkylcyanoacrylate, hydroxy-ethyl-methacrylate, 
isopropyl-acrylamide, vinyl pyrrolidone, Poly Lactic Acid-Poly 
Ethylene Glycol (PLA-PEG) and polylactic-co-glycolic acid (PLGA) 
have been taken for the analysis. The structures of molecules have 
been optimized within Hartree-Fock (HF)[7] level with 
6-31G* basis set. 
Quantum mechanical modeling 
The optimized structures are further subjected to modeling in the 
DFT/B3LYP level using the same basis set. Thermodynamic 
properties such as free energy change (ΔG), enthalpy change 
(ΔH) and entropy change (ΔS) and electronic properties such as 
dipole moment, HOMO and 3 LUMO have been generated (Tables 
I). 
Structure activity relationship (SAR) studies 
Drug delivery related properties, pharmacokinetic and 
pharmacodynamic properties of the systems such as volume, 
mass, log P, log D, log X (where P -partition coefficient, D ă
distribution coefficient and X -solubility), absorption and 
hepatotoxicity have been generated using Âstructure activity 
relationship-SARÊ approach (Table II). Variations in logD values 
with pH have also been found computationally using Associative 
Neural Network (ASNN) algorithm which is a combination of feed-
forward neural network and K- nearest neighbor method (Table III). 
Results and Discussion 
Quantum mechanical modeling 
The modeling of all the selected polymers (Figure 1) generates 
properties such as changes in entropy, enthalpy and free energy, 
dipole moment and HOMO and LUMO. Chitosan is found to be 
thermodynamically stable.  
 
 
Figure1: a)chitosan b)alkylcyanoacrylate c) hydroxy ethyl methacrylate d) isopropyl acrylamidee) oxyethylene f) vinyl pyrolidone g) PLGA h) 
PLA-PEG 
 
  
PK et al.  International Journal of Drug Delivery 7 (1) 27-31 [2015] 
 
 
  
PAGE | 29 |
 
Table 1 displays the thermodynamic and electronic properties of 
the drug delivery systems. The negative values of ΔH and ΔG 
indicate that all the systems are thermodynamically stable and are 
spontaneous at all temperatures. The HOMO and LUMO energy 
levels help to predict the possibility for an interaction. Also the 
frontier orbital energy gap helps to determine the chemical 
reactivity and kinetic stability of a species. Oxy ethylene and 
chitosan shows the higher HOMOLUMO energy gap which shows 
their greater stability and low reactivity. Vinyl pyrrolidone shows the 
lowest energy gap and thus it shows a higher chance for reactivity. 
Dipole moment also gives the interaction ability of the molecule 
with the surrounding medium. The lower values of dipole moment 
for isopropylacrylamide, chitosan and oxyethylene show their lower 
ability for interaction and higher stability. 
 
Table 1: Thermodynamic properties 
 
SAR analysis ADMET descriptors and physicochemical properties of the drug 
carriers are given in Table 2. It is very clear that all the systems are 
nontoxic in nature.  
 
Table 2: ADMET descriptors& physicochemical properties 
 
 
 
The predicted value of aqueous solubility shows that some drug 
carriers have low solubility values compared to others [8,9]. If the 
solubility is high, there is a chance for the carrier to disintegrate 
before reaching the target and release the drug molecule anywhere 
else. This may affect the bioavailability of drug molecule near the 
target. But the drug carriers with low solubility values such as PLA-
PEG, chitosan and PLGA are stable towards dissolution. The log X 
values of all the drug delivery systems are included in Figure 2. 
LogP value is a measure of lipophilicity of the compound [10]. From 
Table I, the log P (-2.62) value of chitosan [11] supports the 
molecule to be more dispersed in water than in lipophilic medium. 
This accounts for its low absorption value. The dissociation rates at 
different pH values for chitosan have been included in Table 3. The 
hydrolysis and dissociation of chitosan in acidic and alkaline media 
can be attributed on the basis of this variation. 
 
PK et al.  International Journal of Drug Delivery 7 (1) 27-31 [2015] 
 
 
  
PAGE | 30 |
 
 
 
 
Figure 2: Aqueous solubility; 1-chitosan 2-alkylcyanoacrylate 3- hydroxy ethyl methacrylate4- isopropyl acrylamide 5- oxyethylene 6- vinyl  
pyrolidone 7- PLGA 8- PLA-PEG 
 
Table 3: pH versus logD 
PK et al.  International Journal of Drug Delivery 7 (1) 27-31 [2015] 
 
 
  
PAGE | 31 |
 
In tumor sites, the pH will be less and will be acidic in nature. The 
chitosan carrier will dissociate in this lower pH, leading into 
discharge of the drug near the target. PLGA is another monomer 
which shows a noticeable change in the logD values. But, PLGA is 
a synthetic polymer which gets separated to glucolic acid and lactic 
acid with change in pH. Chitosan hydrolyzes to glucose which is an 
energy provider. This makes the drug carrier using chitosan more 
favorable. The pH versus logD graph for chitosan is given in Figure 
3. 
 
 
Figure 3: pH versus logD graph of chitosan 
 
 
Conclusions 
In silico prediction of molecular, QSAR, thermodynamic and 
ADMET properties of eight different monomers have been done in 
this paper. The properties of all the common drug carriers were 
compared and found that chitosan is a good candidate to be used 
as a drug carrier for tumor. A low solubility of the compound under 
normal body pH prevents the possibility for the carrier to discharge 
the drugs anywhere else. The hydrolysis of Chitosan is found to be 
pH dependent and it supports the possibility for discharge near the 
tumor target. 
Abbreviations 
ADMET – Absorption, Distribution, Metabolism, Elimination and 
Toxicity 
QSAR – Quantitative Structure Activity Relationship 
DDS – Drug Delivery System 
DFT – Density Functional Theory 
HOMO – Highest Occupied Molecular Orbital 
LUMO – Lowest Unoccupied Molecular Orbital 
  
 
 
References 
 
[1]. Zhang et al. Design of Nanoparticles as 
Drug Carriers for Cancer 
Therapy.Cancer Genomics and 
Proteomics.2006; 3: 147ă158. 
[2]. Agnieszka Z. Wilczewska et al. 
Nanoparticles as drug delivery 
systems.Pharmacol.Reports.2012; 64: 
1020ă1037. 
[3]. Mostafavi SH, Jayachandra Babu R. 
Nano-Sized Drug Delivery. J Mol Pharm 
Org. Process Res. 2013; 1(4): 1ă2. 
[4]. Sanjeeb K Sahoo, VinodLabhasetwar. 
Nanoparticle Interface:An Important 
Determination Nanoparticle-Mediated 
Drug/ Gene Delivery. In: Nanoparticle 
Technology for drug delivery. New 
York:Taylor & Francis Group; 2006. p. 
139-154. 
[5]. van de Waterbeemd H, Gifford E. Admet 
InSilico Modeling : Towards Prediction 
Paradise?.Nat Rev Drug Discov. 2003; 
2(3): 192ă204. 
[6]. Ramachandran KI, Deepa G, Krishnan 
Namboori PK. The Modeling of 
Molecules through Computational 
Methods. In: Computational Chemistry 
and Molecular Modeling- Principles and 
Applications. Germany: Springer 
International; 2008; p. 229-274. 
[7]. Malbouisson LAC et al. Optimization of 
Geometry at Hartree-Fock Level Using 
the Generalized Simulated Annealing. 
Applied Mathematics.2012; 2: 1526-
1531. 
[8]. Wang J, Hou T. Recent Advances on 
Aqueous Solubility Prediction. Comb 
Chem High Throughput Screen. 2011; 
14(5):1-11. 
[9]. James L. McDonagh et al. Uniting 
Cheminformatics and Chemical Theory 
To Predict the Intrinsic Aqueous 
Solubility of Crystalline Drug like 
Molecules. J. Chem. Inf. Model. 2013; 
54(3): 844-856. 
[10]. Kujawski J, Popielarska H, Myka A, 
Drabiŏska B, Bernard MK. The log P 
Parameter as a Molecular Descriptor in 
the Computer-aided Drug Design ă an 
Overview. Comput. Methods Sci. 
Technol. 2012; 18(2): 81ă88. 
[11]. Park JH, Saravanakumar G, Kim K, 
Kwon IC. Targeted delivery of low 
molecular drugs using chitosan and its 
derivatives. Adv. Drug Deliv. Rev. 2010; 
62(1): 28ă41. 
[12]. Kean T, Thanou M. Biodegradation, 
biodistribution and toxicity of chitosan. 
Adv Drug Deliv Rev. 2010; 62(1): 3ă11. 
   


Insilico modeling of chitosan as a drug delivery system

https://www.arjournals.org/index.php/ijdd/article/download/1684/pdf

Insilico modeling of chitosan as a drug delivery system

Abstract

Similar works

Full text

Available Versions

International Journal of Drug Delivery