DREAMM: a web-based server for drugging protein-membrane interfaces as a novel workflow for targeted drug design

Bioinformatics. 2022 Dec 13;38(24):5449-5451. doi: 10.1093/bioinformatics/btac680.

Abstract

Summary: The allosteric modulation of peripheral membrane proteins (PMPs) by targeting protein-membrane interactions with drug-like molecules represents a new promising therapeutic strategy for proteins currently considered undruggable. However, the accessibility of protein-membrane interfaces by small molecules has been so far unexplored, possibly due to the complexity of the interface, the limited protein-membrane structural information and the lack of computational workflows to study it. Herein, we present a pipeline for drugging protein-membrane interfaces using the DREAMM (Drugging pRotein mEmbrAne Machine learning Method) web server. DREAMM works in the back end with a fast and robust ensemble machine learning algorithm for identifying protein-membrane interfaces of PMPs. Additionally, DREAMM also identifies binding pockets in the vicinity of the predicted membrane-penetrating amino acids in protein conformational ensembles provided by the user or generated within DREAMM.

Availability and implementation: DREAMM web server is accessible via https://dreamm.ni4os.eu.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Drug Design*
  • Internet
  • Protein Conformation
  • Proteins* / chemistry
  • Software
  • Workflow

Substances

  • Proteins