Projects

Translocation Transfer

Matteo Ceccarelli

Affiliation:

Department of Physics
University of Cagliari
Cittadella universitaria
0904 Monserrato
Italy

Contact:

Email: matteo.ceccarelli@dsf.unica.it

Expertise:

The demand of new drugs for combating multidrug-resistant bacteria appears more urgent for Gram-negative bacteria. The presence of the additional outer membrane, which hinders the access of molecules to internal targets, renders the development of anti-infectives challenging. Today we have few exploratory cases where physical/chemical rules have been proposed to modulate permeation through the outer membrane. In order to explore quantitatively the transport route represented by porins in enterobacterial species, we have recently developed a scoring function that is able to rank molecules according to their permeation [1]. This scoring function is based on general molecular properties (size, charge, electric dipole) and trained with permeation data of 9 beta-lactam antibiotics through 8 porins from enterobacteriaceae. Then, it was verified using in vitro time-kill assays and electrophysiology. We selected a large number of not beta-lactam molecules for which accumulation data in E.coli are available from literature (153 molecules, [2]). After calculating the molecular descriptors for each molecule, we used the scoring function to predict their permeation through the main porin from Escherichia coli, OmpF. The computed correlation between permeation and accumulation is not high, R=0.47, considering the entire set of molecules. However, not considering those few molecules likely not using porins to enter the cell, we obtained a higher correlation, R=0.80. Though internal accumulation does not imply that permeation occurs through porins, the high correlation obtained indicates that in fact porins represents the main pathway for the entry of molecules in E.coli. The capability of the scoring function to predict the permeation of a dataset chemically diverse from the one used to train the scoring function, it is a proof that (i) the scoring function can predict well permeation, and (ii) it has general application, as by construction does not depend on specific chemical groups. Thus, the efficiency of our scoring function (thousand of molecules per day) would allow its use in screening large virtual databases to identify new scaffolds with good permeation.

References:

  • Acosta-Gutierrez, S. et al. ACS Infect. Dis.2018, 4, 1487 Richter, M. F. et al. Nature2017, 545, 299