Editing PySSA

[[File:PySSAHorizontalLogoVar.png|700px|center]]


[https://github.com/urban233/PySSA PySSA] ('Python rich client for visual protein Sequence to Structure Analysis') is an open software project that aims to combine PyMOL and ColabFold to enable the prediction and analysis of 3D protein structures for the scientific end-user. PySSA allows the creation of managed and shareable projects with defined workflows for the prediction and analysis of protein structures, which can be conveniently carried out by scientists without any special computer skills or programming knowledge on their local computers. PySSA can help make protein structure prediction accessible for research and development in protein chemistry and molecular biology, and for teaching.
In addition to the prediction and analysis capabilities, PySSA has a more user-friendly interface for interacting with PyMOL, such as creating high-quality ray-tracing images in a few clicks.

[[Image:PySSAGCC2024Poster.png|right|350px|thumb|Poster for GCC (German Conference of Cheminformatics) 2024]]


A [https://chemrxiv.org/engage/chemrxiv/article-details/668d352501103d79c57e2828 preprint] is already available under the ChemRxiv preprint server.

== Install ==
PySSA is currently only available for the Windows operating system. Please use the wiki inside the GitHub repository to install the software. Click [https://github.com/urban233/PySSA/wiki/Installation-for-Windows-Operating-System here] to access the installation guide.

[[Image:PySSAMainWindow.png|left|300px|thumb|Main window of PySSA]]

== Features ==
The main features are:
* 3D protein structure prediction (powered by ColabFold)
* Analysis of two protein structures
** Structure alignment with RMSD colored protein pair
** Distance data visualizer for viewing a distance plot, histogram and table
* Creating high-quality ray-tracing images in a few clicks
* Working in user created projects
* Can be used by scientists without any special computer skills or programming knowledge

== Use Cases ==
A "Use Case" refers to a specific scenario that demonstrates how the software can be used to accomplish a particular task or objective. There are three interconnected use cases that progressively demonstrate the capabilities of PySSA: the first use case illustrates how to use PySSA to validate the ColabFold prediction method, the second involves comparing the wild-type protein to a mutated protein to determine if the amino acids crucial for receptor interaction remain in the same position, and the third showcases how to generate a high-quality, ray-traced image of a specific amino acid.
Click [https://github.com/urban233/PySSA/wiki/Use-Cases here] to access the videos.

== User PyMOL interaction ==
[[Image:PySSAPredictionDialog.png|right|300px|thumb|Prediction dialog to set up a protein prediction using ColabFold]]
PySSA attempts to minimize the number of GUI components of the PyMOL window, providing the end-user with a nearly blank PyMOL viewer window to ensure that they are not distracted by buttons, command line interfaces, or log messages. This approach aims to provide a more intuitive user experience and PySSA is focusing exclusively on proteins and protein pairs within PyMOL. It should be noted that, at the present time, it is only possible to adjust (e.g., alter the color or representation) entire chains, rather than individual atoms. This represents a significant regression in the functionality for standard PyMOL users but ensures that the interaction remains centered on the end-user and easily understandable for those who work mainly in a laboratory.

== Architecture ==
PySSA is written in pure Python and is among the first programs to utilize WSL2 in a production environment. It employs multiple instances of PyMOL, designated as User PyMOL, for direct user interaction with objects (proteins or protein pairs), and auxiliary PyMOLs, which are background instances utilized for tasks such as image rendering or distance analysis. The protein prediction is facilitated by ColabFold, which operates exclusively within the WSL2 environment. The WSL2 utilizes a specialized AlamaLinux distribution that includes ColabFold pre-installed.ColabFold communicates with a web server, MMSeqs2, to execute the MSA necessary for structure prediction.

[[Image:PySSAArchitecture.png|left|400px|thumb|PySSA architecture on a local computer. The MSA generation for the ColabFold
prediction is performed on a remote web server running the MMseqs2 software]]