Dear Community, I have predicted the structure of a transmembrane protein with 5 transmembrane helices. When I use Modeller it is not confident with the last helix, so I end up with a structure missing the last one. When I use AlphaFold (server 31.03.25) four of the helices are transmembrane and the fifth just points somewhere else but not back into the membrane. I predicted the transmembrane helices using DeepTMHMM - 1.0, so I actually expect the last helix to go back into the membrane. I would like to show the prediction in my next publication, but the paper will not be about modelling protein structures. The structure is just to explain that the predicted protein structure matches well with known proteins that function as quinone reductases, so it is safe to assume that it has a similar biological function. How can I proceed to get a better orientation of my last transmembrane helix without placing it randomly in the "right" direction, it should at least make some sense in terms of the neighboring transmembrane helices. Thanks for any advice!
Dear Stefanie Becker Prediction of the protein structure of membrane proteins is (still) harder (for programs like AlphaFold) than for non-membrane proteins.
You might consider trying I-Tasser https://seq2fun.dcmb.med.umich.edu//I-TASSER/
When it comes to the topology of a membrane protein you might consider TOPCONS https://topcons.cbr.su.se/pred/
Best regards
PS. Perhaps the following paper is of interest to you
Article Prediction of Lipid-Binding Regions in Cytoplasmic and Extra...
(The indicated link in this paper for the program/server TOPDB is no longer available, the current link is https://topdb.unitmp.org )
RNA function follows form – why is it so hard to predict?
AlphaFold’s highly accurate structural models transformed protein biology,but RNA lags behind...
"Researchers have been working to address these challenges, and, in recent years, several AI-based RNA-structure-prediction tools have emerged. Before 2020, most of the methods for predicting RNA structure were based on algorithms defined by specific physical or mathematical models, according to Jianyi Yang, a computational biologist at Shandong University in Qingdao, China. But the success of AlphaFold has inspired people in the RNA field to apply AI to this problem, too, he says.
Yang and his colleagues designed a fully automated (and freely available) AI tool, trRosettaRNA, which combines deep learning with elements of Rosetta, a computational tool used for determining molecular structures that was created by David Baker at the University of Washington in Seattle, who shared the 2024 chemistry Nobel with the creators of AlphaFold..."
https://www.nature.com/articles/d41586-025-00920-8
Hello! You should be able to download PDB coordinates and then with Swiss-Prot viewer (old) modify and visualize the result.
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