Equivalent to Rosetta in Julia

I’ve recently started working at a biotech startup. One of the tools used by these types of companies is the macromolecular modelling tool Rosetta. I don’t totally understand Rosetta’s various capabilities/limitations. To gain better understanding, I was hoping to contrast it with other tools. Specifically, Julia tools, because I’m curious about the bio community.

In the Julia, there are several tools organized under BioJulia. What capabilities of Rosetta have equivalents in BioJulia?

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Not many, to my knowledge. Rosetta is a mature and powerful suite that encompasses core code, protocols and a forcefield. Rosetta can do things that few other softwares can in any language, which does make a comparison difficult.

The structural bioinformatics scene in Julia is more limited, and the following packages include features that can also be found in Rosetta (apologies for any omissions, please add below):

Stay tuned, there are more and more as time goes on!


Now having a year of experience working with Rosetta, I’d like to use my experience to expand @jgreener64’s reply. Specifically, the three components mentioned in:


Forcefields are statistical descriptions of how protein components interact. They are typically used to evaluate a protein shape’s energy score, wherein you want a protein to fold to minimize it’s energy score.

I still don’t totally understand how a forcefield is designed/validated, however I realize this mostly requires me to read a bunch of papers.


I most commonly use Rosetta’s built-in protocols, such as Simple Cyclic Peptide Prediction and Protein Docking. Based off the videos from the 2020 Rosetta boot-camp, a protocol is a series of steps to repeat until convergence. For example, rotating the backbone, mutating side-chains… etc.

You can specify more complicated protocols with PyRosetta or RosettaScripts XML.

Protocols have a tendency to break between Rosetta releases.

Core code

Rosetta’s goals required the creation of much custom C++ mathematical code, as shown in this YouTube video from the 2016 boot-camp. From my high-level perspective, I think most of this mathematical functionality, such as vector and matrix operations, are already built-in to Julia.

Summary: Rosetta would be nice in Julia

Rosetta seems to be an ideal candidate for a Julia re-write, given:

  • It suffers from a three language problem (Python, C++, XML)
  • Compiling it is difficult
  • It mostly deals with throughput-based scientific computations

However, I believe a religious figure once said “May those that wish for a re-implementation of software, write the first lines of code.”


Rosetta is not a single thing, it a monster suite of hundreds of tools written over the last 30 years. Although each of these tools could be rewritten in Julia and for some uses that would be very nice (particularly for adjusting force-field function terms, defining new constraints, and avoiding all that compilation hassle), I can bet that will never happen.

It is more realistic to think to implement one of the things Rosetta does (a docking method, for example) in Julia. But really, that makes sense if one has something original to contribute to the methods instead on simply translating a code.