For molecular modelers, predicting the three-dimensional structure of biomolecules, such as proteins, can often be a challenging task. Understanding these structures is key to unraveling biological mechanisms and accelerating drug discovery. Thankfully, SAMSON, the integrative molecular design platform, offers tools that make structure prediction more accessible—one of the most notable being AlphaFold-2.
Why AlphaFold-2?
AlphaFold-2 is renowned for its accuracy in predicting protein structures using deep learning. If you often work with protein sequences but lack immediate access to advanced computational resources, SAMSON’s cloud-based integration of AlphaFold-2 is a game-changer. Here, we’ll walk you through how to utilize this feature within SAMSON effectively.
Getting Started with AlphaFold-2 in SAMSON
Using AlphaFold-2 through SAMSON is streamlined and user-friendly. Here’s how you can predict protein structures in just a few steps:
- Navigate to the
Home > Predictsection in SAMSON. - Select the AlphaFold-2 service.
- Upload one or more FASTA files containing the protein sequences you wish to analyze.
- Choose between AlphaFold models (e.g., monomer or multimer) and select a database for multiple sequence alignment.
- Click
Start predictionto initiate the process.
The predictions are automatically processed in the cloud, which eliminates the need for having a high-performance computer locally. This accessibility is particularly helpful for researchers working remotely or those with minimal infrastructure.
Viewing and Interpreting Results
Once the calculations are complete, the results can be reviewed on SAMSON. Simply go to Interface > Cloud jobs, or check the job status directly on your SAMSON Connect Account. The predicted proteins are colorized based on pLDDT (predicted Local Distance Difference Test) values, making it easier to assess the reliability of each segment of the structure.
Computing Resources
SAMSON ensures robust computational performance by offering a selection of cloud machines, including those equipped with powerful NVIDIA A100 GPUs. This scalability allows you to select resources that align with your budget and project requirements.
You can purchase computing credits directly from SAMSON Connect or request credits via email.
Ethical Use and Citing
It’s important to remember that any findings resulting from the AlphaFold service should properly cite the AlphaFold paper. If you also use AlphaFold-Multimer, it’s equally essential to include the relevant citation for that tool.
Overcoming Barriers in Structure Prediction
AlphaFold-2 in SAMSON addresses a major pain for molecular modelers: obtaining reliable protein structures without the need for excessive computational expertise or infrastructure. Whether you’re studying protein mechanisms or exploring potential drug designs, this tool provides a straightforward and efficient solution.
For more technical details and guides, please visit the full documentation page at https://documentation.samson-connect.net/tutorials/bsp/bsp/.
SAMSON and all SAMSON Extensions are free for non-commercial use. You can download SAMSON at https://www.samson-connect.net.