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Published on: January 28, 2021
ClusPro FMFT-SAXS: Ultra-fast Filtering Using Small-Angle X-ray Scattering Data in Protein Docking
Mikhail Ignatov1, Andrey Kazennov2, Dima Kozakov1
1Department of Applied Mathematics and Statistics, Stony Brook University, 11794 Stony Brook, NY, USA; Laufer Center for Physical and Quantitative Biology, Stony Brook University, 11794 Stony Brook, NY, USA; Institute for Advanced Computational Sciences, Stony Brook University, 11794 Stony Brook, NY, USA.
We developed FMFT-SAXS, a novel algorithm for rapid small-angle X-ray scattering (SAXS) profile computation. This accelerates protein complex conformational analysis and improves docking results in the ClusPro server.
Area of Science:
- Structural Biology
- Computational Biology
- Biophysics
Background:
- Small-angle X-ray scattering (SAXS) filtering enhances protein docking results.
- Current SAXS filtering is computationally intensive, processing millions of conformations sequentially.
- Fast Manifold Fourier Transform (FMFT) enables rapid energy evaluation for protein interactions.
Purpose of the Study:
- To develop a novel algorithm for massively parallel SAXS computation.
- To accelerate the SAXS filtering step in protein docking protocols.
- To enable exploration of the conformational space of interacting proteins.
Main Methods:
- Developed FMFT-SAXS, a novel algorithm leveraging FMFT for SAXS calculations.
- Exploited the convolutional nature of the SAXS calculation function.
- Applied the algorithm to accelerate SAXS filtering in the ClusPro docking server.
Main Results:
- FMFT-SAXS computes SAXS profiles for millions of conformations in minutes.
- Achieved 1-2 orders of magnitude speedup in SAXS filtering without accuracy loss.
- Validated the approach on benchmark datasets and experimental data.
Conclusions:
- FMFT-SAXS significantly accelerates SAXS-based filtering in protein docking.
- The method enables efficient exploration of protein complex conformational landscapes.
- The algorithm is available via the ClusPro server and as an open-source library.
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