Analysis and Visualization of Protein Channels, Tunnels, and Pores with MOLEonline and ChannelsDB 2.0.

Channels, tunnels, and pores serve as pathways for the transport of molecules and ions through protein structures, thus participating to their functions. MOLEonline ( https://mole.upol.

AlphaFind: discover structure similarity across the proteome in AlphaFold DB.

AlphaFind is a web-based search engine that provides fast structure-based retrieval in the entire set of AlphaFold DB structures. Unlike other protein processing tools, AlphaFind is focused entirely on tertiary structure, automatically extracting the main 3D features of each protein chain and using a machine learning model to find the most similar structures. This indexing approach and the 3D feature extraction method used by AlphaFind have both demonstrated remarkable scalability to large datasets as well as to large protein structures.

ChannelsDB 2.0: a comprehensive database of protein tunnels and pores in AlphaFold era.

ChannelsDB 2.0 is an updated database providing structural information about the position, geometry and physicochemical properties of protein channels-tunnels and pores-within deposited biomacromolecular structures from PDB and AlphaFoldDB databases. The newly deposited information originated from several sources.

Mol* Volumes and Segmentations: visualization and interpretation of cell imaging data alongside macromolecular structure data and biological annotations.

Segmentation helps interpret imaging data in a biological context. With the development of powerful tools for automated segmentation, public repositories for imaging data have added support for sharing and visualizing segmentations, creating the need for interactive web-based visualization of 3D volume segmentations. To address the ongoing challenge of integrating and visualizing multimodal data, we developed Mol* Volumes and Segmentations (Mol*VS), which enables the interactive, web-based visualization of cellular imaging data supported by macromolecular data and biological annotations.

αCharges: partial atomic charges for AlphaFold structures in high quality.

The AlphaFold2 prediction algorithm opened up the possibility of exploring proteins' structural space at an unprecedented scale. Currently, >200 million protein structures predicted by this approach are deposited in AlphaFoldDB, covering entire proteomes of multiple organisms, including humans. Predicted structures are, however, stored without detailed functional annotations describing their chemical behaviour.