Hamidreza Ghafouri
@hamidrgh.bsky.social
PhD student @Biocomputing UP lab @University of Padova-Italy 🇮🇹
Research IDPs , Conformational ensembles🍝
Do you have ensembles to deposit in PED?
Don’t hesitate to reach out and share your valuable data with the community
Proteinensemble.org
Research IDPs , Conformational ensembles🍝
Do you have ensembles to deposit in PED?
Don’t hesitate to reach out and share your valuable data with the community
Proteinensemble.org
We also outline key challenges in the field—such as force field accuracy, efficient sampling, and environmental dependency—and call for collaborative benchmarking and standardized protocols.
Kudos to all co-authors and contributors who made this work possible!
Kudos to all co-authors and contributors who made this work possible!
April 7, 2025 at 9:08 AM
We also outline key challenges in the field—such as force field accuracy, efficient sampling, and environmental dependency—and call for collaborative benchmarking and standardized protocols.
Kudos to all co-authors and contributors who made this work possible!
Kudos to all co-authors and contributors who made this work possible!
Our framework is built around three pillars:
🔹Experimental techniques
🔹 Computational ensemble generation
🔹 Ensemble validation
🔹Experimental techniques
🔹 Computational ensemble generation
🔹 Ensemble validation
April 7, 2025 at 9:08 AM
Our framework is built around three pillars:
🔹Experimental techniques
🔹 Computational ensemble generation
🔹 Ensemble validation
🔹Experimental techniques
🔹 Computational ensemble generation
🔹 Ensemble validation
🍝 Disordered proteins are central to many biological processes, but their dynamic nature makes structural characterization a major challenge. Here, we present a modular framework that bridges experimental methods with computational tools, like molecular dynamics, knowledge-based sampling, and ML.
April 7, 2025 at 9:08 AM
🍝 Disordered proteins are central to many biological processes, but their dynamic nature makes structural characterization a major challenge. Here, we present a modular framework that bridges experimental methods with computational tools, like molecular dynamics, knowledge-based sampling, and ML.