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Title: Discovering the permeation through the outer membrane of gram-negative bacteria using molecular dynamics simulations
Authors: Deylami, Javad
Keywords: Science::Medicine::Computer applications
Science::Biological sciences::Biophysics
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Deylami, J. (2022). Discovering the permeation through the outer membrane of gram-negative bacteria using molecular dynamics simulations. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: We are in the age of the antibiotic resistance, and the pharmaceutical industry faces a crisis. The trend of antibiotic resistant leads to over-prescribing antibiotics because general practitioners perceiving a greater risk in not prescribing antibi- otics compared with their unnecessary use. Consequently, billions of unnecessary antibiotic courses are administered annually in primary care clinics, leading to increased risk of antimicrobial resistance as a major global health challenge with significant health and economic ramifications. Furthermore, the cost of developing an antibiotic is US$ ∼ 1.5 billion, resulting in a significant lack of financial inducement in antibiotic discovery. In particular, improving the efficiency of antibiotics against Gram-negative bacteria remains a significant challenge due to its cell envelope complexity. One of the main issues is that passing along the outer membrane is extremely difficult and, indeed, is impossible for most antibiotics. This makes permeability assessment a fundamentally important process in drug design pipelines. Along with the substantial costs of antibiotic design processes (e.g. screening) using traditional experimental and clinical methods, they cannot provide physicochemical insights at the atomic level and become enduring at some point. Together with these techniques, computational methods have played a pivotal role in revealing detailed information about Gram-negative bacteria architecture and functions. In recent years, all-atom and coarse-grained molecular dynamics simulation techniques have been robust and powerful approaches to study the Gram-negative bacteria outer membrane dynamics, structural properties, and antibiotic-resistant functions. In this thesis, we addressed a long-standing question of “what is the permeation rate of antibiotics, when they pass through the outer membrane of Escherichia coli bacteria?”. We employed molecular dynamics simulation to assess the permeation of several clinically essential antibiotics through the Escherichia coli outer membrane. We herein used two computational descriptors, the inhomogeneous solubility-diffusion model and the number of formed hydrogen bonds, to shed light on the question of which antibiotic can permeate better along with the OM of Escherichia coli bacterium. We recognized the profound effects of antibiotics hydrogen bond formation and their electrostatic interactions with cations, which play critical roles in the passive permeation. Our permeability results corroborate well with experimental data and delineate how the physicochemistry of antibiotics impact their permeation through OM, revealing new detailed insights of antibiotic interaction with Escherichia coli OM. Finally, we investigated the molecular properties, dynamics, and permeation of OccAB porins, which belong to one of the most dangerous Gram-negative bacteria pathogens, Acinetobacter baumannii, using all-atom simulations. The permeation characterization unravels that OccAB1-4 porins are highly selective for the ions. Even though the OccAB1 porin has the largest pore radius, OccAB2 porin is the most unstable porin, which is together with its less interaction with Ca2+ cations. In addition, OccAB1-4 porins showed high permeability to Cl− ions compared to K+ ions. In a nutshell, we demonstrated how synergizing theory, computation, and experiment play a critical role in choosing the right antibiotic for the patient, and illuminating the new insights of permeation through the Gram-negative pathogens outer membrane, ultimately providing the basis for developing new compound screening techniques for the pharmaceutical industry.
DOI: 10.32657/10356/162657
Schools: School of Physical and Mathematical Sciences 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: embargo_20241107
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Theses

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