Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods

Abstract

The delivery of drugs is a topic of intense research activity in both academia and industry with potential for positive economic, health, and societal impacts. The selection of the appropriate formulation (carrier and drug) with optimal delivery is a challenge investigated by researchers in academia and industry, in which millions of dollars are invested annually. Experiments involving different carriers and determination of their capacity for drug loading are very time-consuming and therefore expensive; consequently, approaches that employ computational/theoretical chemistry to speed have the potential to make hugely beneficial economic, environmental, and health impacts through savings in costs associated with chemicals (and their safe disposal) and time. Here, we report the use of computational tools (data mining of the available literature, principal component analysis, hierarchical clustering analysis, partial least squares regression, autocovariance calculations, molecular dynamics simulations, and molecular docking) to successfully predict drug loading into model drug delivery systems (gelatin nanospheres). We believe that this methodology has the potential to lead to significant change in drug formulation studies across the world.

Chloroquine and hydroxychloroquine for combating COVID-19: Investigating efficacy and hypothesizing new formulations using Bio/chemoinformatics tools

“…Gelatin has been rationally selected as the nanoparticulate matrix material for loading the investigated drugs due to its high biocomptability, suitability for nasal and pulmonary delivery, mucoadhesive properties and its efficiency on loading several hydrophilic and hydrophobic drugs [ 1 , 22 , 42 ]. The successful construction of the gelatin matrix using the adopted molecular dynamics method was obtained after following the same protocols of the authors previous studies [ 23 , 35 ].…”

“…The docking analysis was employed using MOE version 2014.0901 (Chemical Computing Group Inc., Montreal, Canada). The pdb file of the protein nanoparticles matrix was imported to MOE where the identification of the binding site was performed using MOE's “Site finder” tool [ 23 ]. The docking experiment was conducted using the “ triangle matcher” as a placement method.…”

Comparing cefotaxime and ceftriaxone in combating meningitis through nose-to-brain delivery using bio/chemoinformatics tools

“…The gelatin and tripalmitin have been rationally selected as the nanoparticulate matrices material for loading the investigated drugs due to their proven successful compatibility with the olfactory nerves and regions, their successful penetration through the drug brain barrier and their efficiency (especially gelatin) on loading several hydrophilic and hydrophobic drugs [31][32][33] . The successful construction of the gelatin and tripalmitin virtual matrices using the adopted molecular dynamics method was obtained after following the same protocols of the authors previous studies [34][35][36][37] . Table 1 demonstrates the results of docking the investigated drugs; cefotaxime and ceftriaxone on the selected carriers.…”

Evolution of the Computational Pharmaceutics Approaches in the Modeling and Prediction of Drug Payload in Lipid and Polymeric Nanocarriers

“…Another example of multidrug modelling was introduced by Hathout et al [ 44 ] using gelatin as a principle matrix. Ten API were docked on the gelatin matrix simulated by MD, and the obtained ΔG data were correlated with the experimental masses of the loaded drugs.…”