Molecular Simulation of Graphene Oxide (GO) Nanocarriers for Doxorubicin: Effects of PH and GO Pegylation on the Drug Loading, Retention, and Release

Molecular dynamics (MD) simulation as a powerful tool is used to investigate the graphene oxide (GO) based drug delivery system in the process of drug loading, drug carrying and drug release. Doxorubicin (DOX), a widely used anticancer drug, is used as a drug model. The effect of different parameters including pH levels and the oxidation level of GO sheets on the drug loading mechanism is broadly discussed in this study. The drug release from the GO sheet using pH stimulus is explored and results confirmed that GO can release DOX molecules at acidic pH level

Three-Dimensional Simulation of Carmustine Delivery to a Patient-Specific Brain Tumor

This study presents the recent development of three-dimensional patient-specific simulation of carmustine delivery to brain tumor that highlights several crucial factors affecting the delivery. The simulation utilizes the full-brain three-dimensional geometry constructed from magnetic resonance images (MRI) of a brain tumor patient. Prior to the simulation with tumor, the baseline simulation is initially done to obtain the interstitial fluid homeostasis in the normal brain so that the real picture of brain fluid dynamics in human brain is obtained. The simulation is conducted by coupling equations of continuity, motion, and carmustine species conservation, which, in turn, are solved simultaneously to calculate pressure, flow, and drug concentration fields, respectively. Carmustine is delivered by using the commercially available Gliadel wafers following the surgical removal of the tumor. The possible effects of vasogenic edema (due to surgery trauma) to brain fluid dynamics is also included. Here, the compiled results highlight that the drug release profile is, if not more than, as important as the dosage and the possible increase of convection due to edema. This study also reveals that a new strategy, namely convection enhanced delivery (CED) is able to increase drug penetration by enhancing interstitial fluid convection; but, over-enhanced convection may cause toxicity complications to surrounding healthy tissue during later stages of treatment.Singapore-MIT Alliance (SMA

Molecular modeling to study dendrimers for biomedical applications

© 2014 by the authors; licensee MDPI; Basel; Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). Date of Acceptance: 17/11/2014Molecular modeling techniques provide a powerful tool to study the properties of molecules and their interactions at the molecular level. The use of computational techniques to predict interaction patterns and molecular properties can inform the design of drug delivery systems and therapeutic agents. Dendrimers are hyperbranched macromolecular structures that comprise repetitive building blocks and have defined architecture and functionality. Their unique structural features can be exploited to design novel carriers for both therapeutic and diagnostic agents. Many studies have been performed to iteratively optimise the properties of dendrimers in solution as well as their interaction with drugs, nucleic acids, proteins and lipid membranes. Key features including dendrimer size and surface have been revealed that can be modified to increase their performance as drug carriers. Computational studies have supported experimental work by providing valuable insights about dendrimer structure and possible molecular interactions at the molecular level. The progress in computational simulation techniques and models provides a basis to improve our ability to better predict and understand the biological activities and interactions of dendrimers. This review will focus on the use of molecular modeling tools for the study and design of dendrimers, with particular emphasis on the efforts that have been made to improve the efficacy of this class of molecules in biomedical applications.Peer reviewedFinal Published versio

On the role of specific drug binding in modelling arterial eluting stents

In this paper we consider drug binding in the arterial wall following delivery by a drug-eluting stent. Whilst it is now generally accepted that a non-linear saturable reversible binding model is required to properly describe the binding process, the precise form of the binding model varies between authors. Our particular interest in this manuscript is in assessing to what extent modelling specific and non-specific binding in the arterial wall as separate phases is important. We study this issue by extending a recently developed coupled model of drug release and arterial tissue distribution, and comparing simulated profiles of drug concentration and drug mass in each phase within the arterial tissue

Modeling the Effects of Drug Binding on the Dynamic Instability of Microtubules

We propose a stochastic model that accounts for the growth, catastrophe and rescue processes of steady state microtubules assembled from MAP-free tubulin. Both experimentally and theoretically we study the perturbation of microtubule dynamic instability by S-methyl-D-DM1, a synthetic derivative of the microtubule-targeted agent maytansine and a potential anticancer agent. We find that to be an effective suppressor of microtubule dynamics a drug must primarily suppress the loss of GDP tubulin from the microtubule tip.Comment: 17 pages, 11 figures, to appear in Phys. Bio

Computational structure‐based drug design: Predicting target flexibility

The role of molecular modeling in drug design has experienced a significant revamp in the last decade. The increase in computational resources and molecular models, along with software developments, is finally introducing a competitive advantage in early phases of drug discovery. Medium and small companies with strong focus on computational chemistry are being created, some of them having introduced important leads in drug design pipelines. An important source for this success is the extraordinary development of faster and more efficient techniques for describing flexibility in three‐dimensional structural molecular modeling. At different levels, from docking techniques to atomistic molecular dynamics, conformational sampling between receptor and drug results in improved predictions, such as screening enrichment, discovery of transient cavities, etc. In this review article we perform an extensive analysis of these modeling techniques, dividing them into high and low throughput, and emphasizing in their application to drug design studies. We finalize the review with a section describing our Monte Carlo method, PELE, recently highlighted as an outstanding advance in an international blind competition and industrial benchmarks.We acknowledge the BSC-CRG-IRB Joint Research Program in Computational Biology. This work was supported by a grant from the Spanish Government CTQ2016-79138-R.J.I. acknowledges support from SVP-2014-068797, awarded by the Spanish Government.Peer ReviewedPostprint (author's final draft