In-silico screening of drug candidates for thermoresponsive liposome formulations

Author:

Balouch MartinORCID,Šrejber MartinORCID,Šoltys MarekORCID,Janská Petra,Štěpánek FrantišekORCID,Berka KarelORCID

Abstract

AbstractLiposomal formulations can be advantageous in a number of scenarios such as targeted delivery to reduce the systemic toxicity of highly potent Active Pharmaceutical Ingredients (APIs), to increase drug bioavailability by prolonging systemic circulation, to protect labile APIs from degradation in the gastrointestinal tract, or to improve skin permeation in dermal delivery. However, not all APIs are suitable for encapsulation in liposomes. Some of the issues are too high permeability of the API across the lipid bilayer, which may lead to premature leakage, too low permeability, which may hinder the drug release process, or too strong membrane affinity, which may reduce the overall efficacy of drug release from liposomes. Since the most reliable way to test API encapsulation and release from liposomes so far has been experimental, an in silico model capable of predicting API transport across the lipid bilayer might accelerate formulation development. In this work, we demonstrate a new in silico approach to compute the temperature dependent permeability of a set of compounds across the bilayer of virtual liposomes constructed by molecular dynamics simulation. To validate this approach, we have conducted a series of experiments confirming the model predictions using a homologous series of fluorescent dyes. Based on the performance of individual molecules, we have defined a set of selection criteria for identifying compatible APIs for stable encapsulation and thermally controlled release from liposomes. To further demonstrate the in silico-based methodology, we have screened the DrugBank database, identified potent drugs suitable for liposome encapsulation and successfully carried out the loading and thermal release of one of them - an antimicrobial compound cycloserine.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3