🔥 Benchmark Alert! MotifBench sets a new standard for evaluating protein design methods in motif scaffolding.
Why does this matter? Reproducibility & fair comparison have been lacking—until now.
Paper: https://arxiv.org/abs/2502.12479 | Repo: https://github.com/blt2114/MotifBench
A thread ⬇️
Why does this matter? Reproducibility & fair comparison have been lacking—until now.
Paper: https://arxiv.org/abs/2502.12479 | Repo: https://github.com/blt2114/MotifBench
A thread ⬇️
Comments
âś… Input: a motif (small functional substructure)
🎯 Goal: find a scaffolds (full proteins) that preserves the motif’s geometry.
But what's the state of methods for this problem?
❌ Current evaluation are inconsistent, and results incomparable
❌ Widely used test cases are too easy
❌ Reproducibility is difficult
That’s where MotifBench comes in.
🧪 A standardized evaluation pipeline
🏆 30 challenging motifs as test cases
đź“ŠEasy-to-use eval scripts and a leaderboard for method comparison
Now, results can be easily and consistently measured.
This suggests modern deep learning methods aren’t always better than past methods!
🧩 Know of an important motif? Add it to the benchmark!
🏗️ Help improve the pipeline & metrics (sequence-based? Side-chain-level?)
Let’s shape the future of motif scaffolding together!