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<title>A Simulation Model for the Non-Electrogenic Uniport Carrier-Assisted Transport of Ions across Lipid Membranes</title>
<creator>Scorciapino, Mariano Andrea</creator>
<creator>Picci, Giacomo</creator>
<creator>Quesada Pato, Roberto</creator>
<creator>Lippolis, Vito</creator>
<creator>Caltagirone, Claudia</creator>
<subject>Anion receptors</subject>
<subject>Anion recognition</subject>
<subject>Chloride transport</subject>
<subject>Dipicolineamide</subject>
<subject>Lipid vesicles</subject>
<subject>Squaramide</subject>
<subject>Supramolecular medicinal chemistry</subject>
<subject>Synthetic transporters</subject>
<subject>Variable time-step</subject>
<subject>Water to lipid partition</subject>
<description>Impressive work has been completed in recent decades on the transmembrane anion&#xd;
transport capability of small synthetic transporters from many different structural classes. However,&#xd;
very few predicting models have been proposed for the fast screening of compound libraries before&#xd;
spending time and resources on the laboratory bench for their synthesis. In this work, a new&#xd;
approach is presented which aims at describing the transport process by taking all the steps into&#xd;
explicit consideration, and includes all possible experiment-derived parameters. The algorithm is&#xd;
able to simulate the macroscopic experiments performed with lipid vesicles to assess the ion-transport&#xd;
ability of the synthetic transporters following a non-electrogenic uniport mechanism. While keeping&#xd;
calculation time affordable, the final goal is the curve-fitting of real experimental data—so, to obtain&#xd;
both an analysis and a predictive tool. The role and the relative weight of the different parameters&#xd;
is discussed and the agreement with the literature is shown by using the simulations of a virtual&#xd;
benchmark case. The fitting of real experimental curves is also shown for two transporters of different&#xd;
structural type.</description>
<date>2023-03-30</date>
<date>2023-03-30</date>
<date>2022-03</date>
<type>info:eu-repo/semantics/article</type>
<identifier>http://hdl.handle.net/10259/7625</identifier>
<identifier>10.3390/membranes12030292</identifier>
<identifier>2077-0375</identifier>
<language>eng</language>
<relation>Membranes. 2022, V. 12, n. 3, 292</relation>
<relation>https://doi.org/10.3390/membranes12030292</relation>
<relation>info:eu-repo/grantAgreement/MIUR/PRIN 2017/2017EKCS35/IT/</relation>
<rights>http://creativecommons.org/licenses/by/4.0/</rights>
<rights>info:eu-repo/semantics/openAccess</rights>
<rights>Atribución 4.0 Internacional</rights>
<publisher>MDPI</publisher>
</thesis></metadata></record></GetRecord></OAI-PMH>