Dataset2 for article: Calcium-Driven Activation of Gelsolin: Mechanism and the Active-State Ensemble

The dataset consists of:

• 00_TRAIN: Training simulation of Gelsolin. The directory contains FL training simulation, single domain training simulation in presence of Ca+2 ions and coupled domains 2-3 and 4-5-6 in actin-capping conformation in presence of Ca+2. 
  From these simulation contact-probability and distance matrices are extracted and used as input for the multi-eGO production force-field generation
• 01_FL_PRIOR: Full-leght molten-globule prior simulation. This simulation was performed with molten-globule prior multi-eGO force-field.
  The contact-probability and distance matrices are used to reweight intradomain contacts during the generation of the multi-eGO production force-field.
• 02_INTERDOM_PRIOR: Inter domain prior simulation: multi-eGO interdomain prior simulation in which intra-domain interaction are learned from the combination of prior and training data, while interdomain ones are left as the prior molten-globule ones.
  The resulting contact probability and distance matrices are used to reweight the interdomain training matrices.
• 03_MEGO_PRODUCTION: Multi-eGO production simulations with different parameter. They also contain the script used to compute the SAXS profile for different frames using PEPSI-SAXS
• 04_SAXS: Codes to analyse the SAXS profile and use DEERPREdict and BME to obtain the final ensemble weights and DEER profiles
• 06_ELViM: ELviM codes and output projections
• 07_MSM: Codes to construct the Markov State Model (MSM) from the ELvim Projection of the ensemble and the MAximum Caliber reweight of the transition matrix
• 08_SAXSfit: Model and analysis codes to fit the SAXS Radius of gyration data and extract global parameters: $n_{eff}$ and $K_{1/2}$
• 09_MEGO_INPUTS: Multi-eGO input matrices and topologies used to generate the production force-fields