Title: Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics
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. more »« less
Vasan, Archit Kumar; Haloi, Nandan; Ulrich, Rebecca Joy; Metcalf, Mary Elizabeth; Wen, Po-Chao; Metcalf, William W.; Hergenrother, Paul J.; Shukla, Diwakar; Tajkhorshid, Emad
(, Proceedings of the National Academy of Sciences)
Andrej Sali, Bioengineering &
(Ed.)
Significance Antibiotic resistance in Gram-negative pathogens has been identified as an urgent threat to human health by the World Health Organization. The major challenge with treating infections by these pathogens is developing antibiotics that can traverse the dense bacterial outer membrane (OM) formed by a mesh of lipopolysaccharides. Effective antibiotics permeate through OM porins, which have evolved for nutrient diffusion; however, the conformational states of these porins regulating permeation are still unclear. Here, we used molecular dynamics simulations, free energy calculations, Markov-state modeling, and whole-cell accumulation assays to provide mechanistic insight on how a porin shifts between open and closed states. We provide a mechanism of how Gram-negative bacteria confer resistance to antibiotics.
Aduru, Sai Varun; Szenkiel, Karolina; Rahman, Anika; Ahmad, Mehrose; Fabozzi, Maya; Smith, Robert P.; Lopatkin, Allison J.
(, Microbiology Spectrum)
Zhang, Xue
(Ed.)
ABSTRACT Bacterial growth and metabolic rates are often closely related. However, under antibiotic selection, a paradox in this relationship arises: antibiotic efficacy decreases when bacteria are metabolically dormant, yet antibiotics select for resistant cells that grow fastest during treatment. That is, antibiotic selection counterintuitively favors bacteria with fast growth but slow metabolism. Despite this apparent contradiction, antibiotic resistant cells have historically been characterized primarily in the context of growth, whereas the extent of analogous changes in metabolism is comparatively unknown. Here, we observed that previously evolved antibiotic-resistant strains exhibited a unique relationship between growth and metabolism whereby nutrient utilization became more efficient, regardless of the growth rate. To better understand this unexpected phenomenon, we used a simplified model to simulate bacterial populations adapting to sub-inhibitory antibiotic selection through successive bottlenecking events. Simulations predicted that sub-inhibitory bactericidal antibiotic concentrations could select for enhanced metabolic efficiency, defined based on nutrient utilization: drug-adapted cells are able to achieve the same biomass while utilizing less substrate, even in the absence of treatment. Moreover, simulations predicted that restoring metabolic efficiency would re-sensitize resistant bacteria exhibiting metabolic-dependent resistance; we confirmed this result using adaptive laboratory evolutions ofEscherichia coliunder carbenicillin treatment. Overall, these results indicate that metabolic efficiency is under direct selective pressure during antibiotic treatment and that differences in evolutionary context may determine both the efficacy of different antibiotics and corresponding re-sensitization approaches. IMPORTANCEThe sustained emergence of antibiotic-resistant pathogens combined with the stalled drug discovery pipelines highlights the critical need to better understand the underlying evolution mechanisms of antibiotic resistance. To this end, bacterial growth and metabolic rates are often closely related, and resistant cells have historically been characterized exclusively in the context of growth. However, under antibiotic selection, antibiotics counterintuitively favor cells with fast growth, and slow metabolism. Through an integrated approach of mathematical modeling and experiments, this study thereby addresses the significant knowledge gap of whether antibiotic selection drives changes in metabolism that complement, and/or act independently, of antibiotic resistance phenotypes.
Biocide use is essential and ubiquitous, exposing microbes to sub-inhibitory concentrations of antiseptics, disinfectants, and preservatives. This can lead to the emergence of biocide resistance, and more importantly, potential cross-resistance to antibiotics, although the degree, frequency, and mechanisms that give rise to this phenomenon are still unclear. Here, we systematically performed adaptive laboratory evolution of the gut bacteria Escherichia coli in the presence of sub-inhibitory, constant concentrations of ten widespread biocides. Our results show that 17 out of 40 evolved strains (43%) also decreased the susceptibility to medically relevant antibiotics. Through whole-genome sequencing, we identified mutations related to multidrug efflux proteins ( mdfA and acrR ), porins ( envZ and ompR ), and RNA polymerase ( rpoA and rpoBC ), as mechanisms behind the resulting (cross)resistance. We also report an association of several genes ( yeaW , pyrE , yqhC , aes , pgpA , and yeeP - isrC ) and specific mutations that induce cross-resistance, verified through mutation repairs. A greater capacity for biofilm formation with respect to the parent strain was also a common feature in 11 out of 17 (65%) cross-resistant strains. Evolution in the biocides chlorophene, benzalkonium chloride, glutaraldehyde, and chlorhexidine had the most impact in antibiotic susceptibility, while hydrogen peroxide and povidone-iodine the least. No cross-resistance to antibiotics was observed for isopropanol, ethanol, sodium hypochlorite, and peracetic acid. This work reinforces the link between exposure to biocides and the potential for cross-resistance to antibiotics, presents evidence on the underlying mechanisms of action, and provides a prioritized list of biocides that are of greater concern for public safety from the perspective of antibiotic resistance. Significance Statement Bacterial resistance and decreased susceptibility to antimicrobials is of utmost concern. There is evidence that improper biocide (antiseptic and disinfectant) use and discard may select for bacteria cross-resistant to antibiotics. Understanding the cross-resistance emergence and the risks associated with each of those chemicals is relevant for proper applications and recommendations. Our work establishes that not all biocides are equal when it comes to their risk of inducing antibiotic resistance; it provides evidence on the mechanisms of cross-resistance and a risk assessment of the biocides concerning antibiotic resistance under residual sub-inhibitory concentrations.
Zeiders, Samantha M.; Chmielewski, Jean
(, Chemical Biology & Drug Design)
Abstract The failure to treat everyday bacterial infections is a current threat as pathogens are finding new ways to thwart antibiotics through mechanisms of resistance and intracellular refuge, thus rendering current antibiotic strategies ineffective. Cell‐penetrating peptides (CPPs) are providing a means to improve antibiotics that are already approved for use. Through coadministration and conjugation of antibiotics with CPPs, improved accumulation and selectivity with alternative and/or additional modes of action against infections have been observed. Herein, we review the recent progress of this antibiotic–cell‐penetrating peptide strategy in combatting sensitive and drug‐resistant pathogens. We take a closer look into the specific antibiotics that have been enhanced, and in some cases repurposed as broad‐spectrum drugs. Through the addition and conjugation of cell‐penetrating peptides to antibiotics, increased permeation across mammalian and/or bacterial membranes and a broader range in bacterial selectivity have been achieved.
Liu, Yangyang; Van_Horn, Andrew M; Pham, Minh_T N; Dinh, Bao_Ngoc N; Chen, Rachel; Raphael, Slaybrina_D R; Paulino, Alejandro; Thaker, Kavya; Somadder, Aaryan; Frost, Dominick J; et al
(, Applied and Environmental Microbiology)
Zhou, Ning-Yi
(Ed.)
ABSTRACT Multidrug efflux pumps are the frontline defense mechanisms of Gram-negative bacteria, yet little is known of their relative fitness trade-offs under gut conditions such as low pH and the presence of antimicrobial food molecules. Low pH contributes to the proton-motive force (PMF) that drives most efflux pumps. We show how the PMF-dependent pumps AcrAB-TolC, MdtEF-TolC, and EmrAB-TolC undergo selection at low pH and in the presence of membrane-permeant phytochemicals. Competition assays were performed by flow cytometry of co-culturedEscherichia coliK-12 strains possessing or lacking a given pump complex. All three pumps showed negative selection under conditions that deplete PMF (pH 5.5 with carbonyl cyanide 3-chlorophenylhydrazone or at pH 8.0). At pH 5.5, selection against AcrAB-TolC was increased by aromatic acids, alcohols, and related phytochemicals such as methyl salicylate. The degree of fitness cost for AcrA was correlated with the phytochemical’s lipophilicity (logP). Methyl salicylate and salicylamide selected strongly against AcrA, without genetic induction of drug resistance regulons. MdtEF-TolC and EmrAB-TolC each had a fitness cost at pH 5.5, but salicylate or benzoate made the fitness contribution positive. Pump fitness effects were not explained by gene expression (measured by digital PCR). Between pH 5.5 and 8.0,acrAandemrAwere upregulated in the log phase, whereasmdtEexpression was upregulated in the transition-to-stationary phase and at pH 5.5 in the log phase. Methyl salicylate did not affect pump gene expression. Our results suggest that lipophilic non-acidic molecules select against a major efflux pump without inducing antibiotic resistance regulons.IMPORTANCEFor drugs that are administered orally, we need to understand how ingested phytochemicals modulate drug resistance in our gut microbiome. Bacteria maintain low-level resistance by proton-motive force (PMF)-driven pumps that efflux many different antibiotics and cell waste products. These pumps play a key role in bacterial defense by conferring resistance to antimicrobial agents at first exposure while providing time for a pathogen to evolve resistance to higher levels of the antibiotic exposed. Nevertheless, efflux pumps confer energetic costs due to gene expression and pump energy expense. The bacterial PMF includes the transmembrane pH difference (ΔpH), which may be depleted by permeant acids and membrane disruptors. Understanding the fitness costs of efflux pumps may enable us to develop resistance breakers, that is, molecules that work together with antibiotics to potentiate their effect. Non-acidic aromatic molecules have the advantage that they avoid the Mar-dependent induction of regulons conferring other forms of drug resistance. We show that different pumps have distinct selection criteria, and we identified non-acidic aromatic molecules as promising candidates for drug resistance breakers.
Dai, Yinghui, Ma, Huilin, Wu, Meishan, Welsch, Tory Alane, Vora, Soor Rajiv, Ren, Dacheng, and Nangia, Shikha. Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics. Retrieved from https://par.nsf.gov/biblio/10216176. Soft Matter . Web. doi:10.1039/D0SM02035D.
Dai, Yinghui, Ma, Huilin, Wu, Meishan, Welsch, Tory Alane, Vora, Soor Rajiv, Ren, Dacheng, & Nangia, Shikha. Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics. Soft Matter, (). Retrieved from https://par.nsf.gov/biblio/10216176. https://doi.org/10.1039/D0SM02035D
Dai, Yinghui, Ma, Huilin, Wu, Meishan, Welsch, Tory Alane, Vora, Soor Rajiv, Ren, Dacheng, and Nangia, Shikha.
"Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics". Soft Matter (). Country unknown/Code not available. https://doi.org/10.1039/D0SM02035D.https://par.nsf.gov/biblio/10216176.
@article{osti_10216176,
place = {Country unknown/Code not available},
title = {Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics},
url = {https://par.nsf.gov/biblio/10216176},
DOI = {10.1039/D0SM02035D},
abstractNote = {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.},
journal = {Soft Matter},
author = {Dai, Yinghui and Ma, Huilin and Wu, Meishan and Welsch, Tory Alane and Vora, Soor Rajiv and Ren, Dacheng and Nangia, Shikha},
editor = {null}
}
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