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Updated: Jan 6, 2026
Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Memory-efficient, accelerated protein interaction inference with blocked, multi-GPU D-SCRIPT
Daniel E Schäffer1,2, Samuel Sledzieski3, Lenore Cowen4
1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Summary:
D-SCRIPT is a powerful tool for high-throughput inference of protein-protein interactions (PPIs), but it is expensive in time and memory to infer all PPIs for network-/proteome-level analyses. We introduce D-SCRIPT with blocked multi-GPU parallel inference, which substantially reduces memory usage across tasks and computational systems (13.8× for a representative large proteome) and enables multi-GPU parallelism.
Availability And Implementation:
Blocked multi-GPU parallel inference has been integrated into the main D-SCRIPT package, available at https://github.com/samsledje/D-SCRIPT. An archived version of the code at time of submission can be found at https://doi.org/10.5281/zenodo.16325182.
Related Concept Videos
02:04Protein-protein Interfaces
02:04Protein-Protein Interfaces
02:26Protein Networks
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...