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The Protein Folding Server uses a new computational technique developed in our group to map a protein's potential landscape. It can generate transitional motions of a protein to the known native state from unstructured conformations or between user-specified conformations.

Protein conformations can be submitted by PDB ids or structures can be uploaded in PDB format. Two types of output are produced: global analysis of the energy landscape (e.g., Ramachandran plots, potential energy plots, classification of roadmap pathways) and analysis of specific pathways (e.g., animations, energy profiles, timed contact maps). Output examples are available on the submission page. See the FAQ for more details.

We invite you to:

Our approach is based on a class of motion planning techniques known as probabilistic roadmap methods. Given one or more protein conformations (e.g., the native structure), we constuct a roadmap containing thousands of feasible folding pathways that together approximate the protein's potential energy landscape, concentrated in the region near the specified conformation(s). Our method typically runs in only a few hours on a PC. In contrast, a molecular dynamics simulation would require months of supercomputer time to compute a single, partial trajectory.

We have validated our technique by comparing the secondary structure formation order on pathways extracted from our roadmap with experimental data. For example, it was able to capture the subtle folding differences between the structurally similar proteins G and L. Protein G, domain B1
Image of protein G, domain B1
Protein L, domain B1
Image of protein L, domain B1

Please see our project webpage for more information about our technique and research.
If you have any questions or comments, please email proteinfolding@cs.tamu.edu.

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