Biology subjects

Ferreira, R. J.

Publications and source records attributed to Ferreira, R. J..

3 recordsLinked to original sources

bioRxiv2022

Long-range communication between transmembrane- and nucleotide-binding domains does not depend on drug binding to mutant P-glycoprotein

The modulation of drug efflux by P-glycoprotein (P-gp, ABCB1) represents one of the most promising approaches to overcome multidrug resistance (MDR) in cancer cells, however the mechanisms of drug specificity and signal-transmission are still poorly understood, hampering the development of more selective and efficient P-gp modulators. In this study, the impact of four P-gp mutations (G185V, G830V, F978A and {Delta}F335) on drug-binding and efflux-related signal-transmission mechanism was comprehensively evaluated in the presence of ligands within the drug-binding pocket (DBP), which are experimentally related with changes in their drug efflux profiles. The severe repacking of the transmembrane helices (TMH), induced by mutations and exacerbated by the presence of ligands, indicates that P-gp is sensitive to perturbations in the transmembrane region. Alterations on drug-binding were also observed as a consequence of the TMH repacking, but were not always correlated with alterations on ligands binding mode and/or binding affinity. Finally, and although all P-gp variants holo systems showed considerable changes in the intracellular coupling helices/nucleotide-binding domain (ICH-NBD) interactions, they seem to be primarily induced by the mutation itself rather than by the presence of ligands within the DBP. The data further suggest that the changes in drug efflux experimentally reported are mostly related with changes on drug specificity rather than effects on signal-transmission mechanism. We also hypothesize that an increase in the drug-binding affinity may also be related with the decreased drug efflux, while minor changes in binding affinities are possibly related with the increased drug efflux observed in transfected cells.

biophysics↗

bioRxiv2020

Simulation-guided engineering of antibiotics for improved bacterial uptake

The Gram-negative bacterial outer membrane poses a major obstacle to the development of much-needed antibiotics against drug-resistant infections. Its chemical composition and porin proteins differ from Gram-positive bacteria and mammalian cells, and heuristics developed for mammalian cell uptake apply poorly. Recently, machinelearning methods have predicted small-molecule uptake into Gram-negative bacteria, offering the possibility to rationally optimize this aspect of antibiotic lead development. Here, we report physics-based methods to prospectively predict Gram-negative bacterial uptake, select, and synthesize promising chemical derivatives targeting E. coli DNA gyrase B. Our methods do not require empirical parameterization and are readily adaptable to new chemical scaffolds. These physics-based predictions well capture experimentally measured uptake (r > 0.95) and are indeed predictive of antimicrobial activity (r > 0.92). These methods can be used prospectively in combination with target-binding simulations to optimize both bacterial uptake and target binding, overcoming important barriers to antibiotic lead generation before small-molecule synthesis.

microbiology↗

bioRxiv2019

Antibiotic uptake across gram-negative outer membranes: better predictions towards better antibiotics

Crossing the gram-negative bacterial membrane poses a major barrier to antibiotic development, as many small molecules that can biochemically inhibit key bacterial processes are rendered microbiologically ineffective by their poor cellular uptake. The outer membrane is the major permeability barrier for many drug-like molecules, and the chemical properties that enable efficient uptake into mammalian cells fail to predict bacterial uptake. We have developed a computational method for accurate prospective prediction of outer-membrane uptake of drug-like molecules, which we combine with a new medium-throughput experimental assay. Parallel molecular dynamics simulations are used to successfully and quantitatively predict experimental permeabilities. For most polar molecules we test, outer membrane permeability also correlates well with whole-cell uptake. The ability to accurately predict and measure outer-membrane uptake of a wide variety of small molecules will enable simpler determination of which molecular scaffolds and which derivatives are most promising prior to extensive chemical synthesis. It will also assist in formulating a more systematic understanding of the chemical determinants of outer-membrane permeability.

biochemistry↗