The partitioning of small molecules in cell membranes - a key parameter for pharmaceutical applications - typically relies on experimentally available bulk partitioning coefficients. Computer simulations provide a structural resolution of the insertion thermodynamics via the potential of mean force but require significant sampling at the atomistic level. Here, we introduce high-throughput coarse-grained molecular dynamics simulations to screen thermodynamic properties. This application of physics-based models in a large-scale study of small molecules establishes linear relationships between partitioning coefficients and key features of the potential of mean force. This allows us to predict the structure of the insertion from bulk experimental measurements for more than 400 000 compounds. The potential of mean force hereby becomes an easily accessible quantity - already recognized for its high predictability of certain properties, e.g., passive permeation. Further, we demonstrate how coarse graining helps reduce the size of chemical space, enabling a hierarchical approach to screening small molecules.

In silico screening of drug-membrane thermodynamics reveals linear relations between bulk partitioning and the potential of mean force / Menichetti, R.; Kanekal, K. H.; Kremer, K.; Bereau, T.. - In: THE JOURNAL OF CHEMICAL PHYSICS. - ISSN 0021-9606. - 147:12(2017), p. 125101. [10.1063/1.4987012]

In silico screening of drug-membrane thermodynamics reveals linear relations between bulk partitioning and the potential of mean force

Menichetti R.;
2017-01-01

Abstract

The partitioning of small molecules in cell membranes - a key parameter for pharmaceutical applications - typically relies on experimentally available bulk partitioning coefficients. Computer simulations provide a structural resolution of the insertion thermodynamics via the potential of mean force but require significant sampling at the atomistic level. Here, we introduce high-throughput coarse-grained molecular dynamics simulations to screen thermodynamic properties. This application of physics-based models in a large-scale study of small molecules establishes linear relationships between partitioning coefficients and key features of the potential of mean force. This allows us to predict the structure of the insertion from bulk experimental measurements for more than 400 000 compounds. The potential of mean force hereby becomes an easily accessible quantity - already recognized for its high predictability of certain properties, e.g., passive permeation. Further, we demonstrate how coarse graining helps reduce the size of chemical space, enabling a hierarchical approach to screening small molecules.
2017
12
Menichetti, R.; Kanekal, K. H.; Kremer, K.; Bereau, T.
In silico screening of drug-membrane thermodynamics reveals linear relations between bulk partitioning and the potential of mean force / Menichetti, R.; Kanekal, K. H.; Kremer, K.; Bereau, T.. - In: THE JOURNAL OF CHEMICAL PHYSICS. - ISSN 0021-9606. - 147:12(2017), p. 125101. [10.1063/1.4987012]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/315298
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? 13
  • Scopus 33
  • ???jsp.display-item.citation.isi??? 34
social impact