This dataset contains simulation trajectory for 24-residue RS-Peptide. The RS-peptide is a highly charged intrinsically disordered region (IDR) found in serine/arginine-rich proteins, such as the serine/arginine-rich splicing factor 1 (SRSF1), known to play a crucial role in RNA metabolism. These trajectories were created as a part of the publication "ExEnDiff: An Experiment-guided Diffusion model for protein conformational Ensemble generation", that introduces a deep-learning-based method that enables the rapid generation of diverse protein conformations while ensuring they adhere to key physical principles through guidance from experiments. METHODOLOGY We ran long unbiased simulations of up to 2 milliseconds of simulation time, with 20 unique starting structures, each run with 100 clones of ~1 micro-second each using Amber03ws force field and Tip4p/2005 water model. The system was initially solvated, and neutralizing ions were added. Energy minimization was performed using the steepest descent algorithm to remove steric clashes, with a maximum force tolerance of 1000 kJ/mol/nm. The system underwent equilibration in two stages: first, a 100 ps NVT equilibration at 300K, with temperature kept constant using the v-rescale thermostat (with a time constant of 0.1 ps), followed by a 1 ns NPT equilibration at 1 bar with the Parrinello-Rahman barostat (with a time constant of 2.0 ps). The production simulation was run with a 2 fs time step. Electrostatic interactions were treated using Particle Mesh Ewald (PME) with a cutoff of 1.0 nm, and other non-bonded interactions were modified with the Potential-shift-Verlet scheme with a cutoff of 1.2 nm. Constraints on bonds involving hydrogen were applied using the LINCS algorithm. The simulations were performed in the Folding@Home distributed computing environment. ACKNOWLDEGEMENT We would also like to thank the Folding@home community and Géraud Krawezik (software engineer at Flatiron Institute) for helping us set up Folding@home simulations.