New preprint: CV-SVGD combines Stein variational gradient descent with parallel restrained MD for multidimensional sampling. In peptide tests, it recovered free-energy surfaces with less aggregate MD sampling than umbrella-sampling references. arxiv.org/abs/2610.27429
Bin Zhang
Bin Zhang
@binzmit.bsky.social
Associate Professor at MIT Chemistry; Enthusiastic about chromatin, biophysics, molecular dynamics, and AI.
52 followers21 following10 posts
Our new model simulates limited-valency sticker interactions in biomolecular condensates. Simulations reveal a trade-off: heterogeneous spacer interactions promote condensation but can disrupt sticker-mediated organization and robust molecular recruitment. doi.org/10.1021/acs....
How open is “open” chromatin? Our new Nature Genetics paper uses nucleosome-resolution modeling to reveal condensed euchromatin domains with short, accessible regulatory regions at the surface. www.nature.com/articles/s41...
Pretraining implicit solvent, or coarse grained, models is difficult, limiting the transferability of the resulting ML force fields. However, Justin just figured out a novel method for pretraining using protein language models. More can be found at: arxiv.org/abs/2601.05388
Bin Zhang reposted
Excited to see our IGME models applied to unravel the free energy landscape of the tetra-nucleosome. Wonderful collaboration with @binzmit.bsky.social! Congrats to all the authors!
Thrilled to share our new JCP editorial (shorturl.at/6mKdY), co-authored with @tamar_schlick, introducing the special collection “Chromatin Structure and Dynamics: Recent Advancements.” Huge thanks to all the outstanding contributors!
Our preprint on a single-bead-per-nucleotide DNA model is live! This model reproduces both atomistic simulations and persistent length for a variety of sequences. It's compatible with openMM, allowing for highly efficient GPU simulations. www.biorxiv.org/content/10.1....
You are up to date.