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Updated: Aug 22, 2025
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
Published on: July 8, 2025
DREAMM: a web-based server for drugging protein-membrane interfaces as a novel workflow for targeted drug design
Alexios Chatzigoulas1,2, Zoe Cournia1,2
1Biomedical Research Foundation, Academy of Athens, Athens 11527, Greece.
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.
