Predicting Permeation of Compounds across the Outer Membrane ofP. aeruginosaUsing Molecular Descriptors: Advantages and Limitations

Author:

Manrique P. D.,Leus I. V.,Ĺopez C. A.,Mehla J.,Malloci G.,Gervasoni S.,Vargiu A. V.,Kinthada R.,Herndon L.,Hengartner N. W.,Walker J. K.,Rybenkov V. V.,Ruggerone P.,Zgurskaya H. I.,Gnanakaran S.

Abstract

The ability of Gram-negative pathogens to adapt and protect themselves against antibiotics is a growing threat to public health. The low permeability of the outer membrane (OM) in combination with effective multidrug efflux pumps, constitute the two main antibiotic resistance mechanisms. Though much efforts have been devoted to discover new antibiotics that can bypass these defense mechanisms, no new antibiotic classes have been introduced into clinics in the last 35 years. Models that identify specific descriptors of molecular properties and predict the likelihood that a given compound is capable of successfully permeate the OM and inhibit bacterial growth while avoiding efflux could facilitate the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors of 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negativePseudomonas aeruginosa. While part of these descriptors are computed using traditional approaches based on the physicochemical properties intrinsic to the compounds, ensemble docking and all-atom molecular dynamics (MD) simulations are used to derive additional bacterium-specific mechanistic properties. Descriptors of compound permeation across the OM were calculated using all-atom MD simulations of the compounds in different subregions of the OM model. Descriptors of interactions with efflux pumps were calculated from ensemble docking of compounds targeting specific binding pockets of MexB, the major efflux transporter ofP. aeruginosa. Using these descriptors and the measured antibacterial inhibitory concentrations of compounds, we design and implement a statistical protocol to identify a subset of the molecular properties that are predictive of whether a given compound is a strong or weak permeator across the Gram-negative OM. Our results indicate that 88.4% of the compounds that show measurable antibacterial activity, follow very consistent rules of permeation, which highlight the critical role that the interaction between the compound and the OM have at predicting permeation. The remaining 11.6% of the compounds, although less predictive, are characterized by distinctive structural markers that can be used to minimize classification errors. An implementation of the permeation rules and the structural markers uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Taken together, our analysis sheds new light on the key molecular properties that drug candidates should have in order to be effective at OM permeation/inhibition ofP. aeruginosa, and opens the gate to similar data-driven studies in other Gram-negative pathogens.

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