Issue 10, 2021

Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics

Abstract

Bacterial colonization of biotic and abiotic surfaces and antibiotic resistance are grand challenges with paramount societal impacts. However, in the face of increasing bacterial resistance to all known antibiotics, efforts to discover new classes of antibiotics have languished, creating an urgent need to accelerate the antibiotic discovery pipeline. A major deterrent in the discovering of new antibiotics is the limited permeability of molecules across the bacterial envelope. Notably, the Gram-negative bacteria have nutrient specific protein channels (or porins) that restrict the permeability of non-essential molecules, including antibiotics. Here, we have developed the Computational Antibiotic Screening Platform (CLASP) for screening of potential drug molecules through the porins. The CLASP takes advantage of coarse grain (CG) resolution, advanced sampling techniques, and a parallel computing environment to maximize its performance. The CLASP yields comprehensive thermodynamic and kinetic output data of a potential drug molecule within a few hours of wall-clock time. Its output includes the potential of mean force profile, energy barrier, the rate constant, and contact analysis of the molecule with the pore-lining residues, and the orientational analysis of the molecule in the porin channel. In our first CLASP application, we report the transport properties of six carbapenem antibiotics—biapenem, doripenem, ertapenem, imipenem, meropenem, and panipenem—through OccD3, a major channel for carbapenem uptake in Pseudomonas aeruginosa. The CLASP is designed to screen small molecule libraries with a fast turnaround time to yield structure–property relationships to discover antibiotics with high permeability. The CLASP will be freely distributed to enable accelerated antibiotic drug discovery.

Graphical abstract: Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics

Supplementary files

Article information

Article type
Paper
Submitted
16 Nov 2020
Accepted
26 Jan 2021
First published
27 Jan 2021

Soft Matter, 2021,17, 2725-2736

Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics

Y. Dai, H. Ma, M. Wu, T. A. Welsch, S. R. Vora, D. Ren and S. Nangia, Soft Matter, 2021, 17, 2725 DOI: 10.1039/D0SM02035D

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements