modern day Picasso right here 👌🏻😂

🫡 🙌 looking forward to some fun collaborations!!

This tool is 🔥🔥🔥 Going to be a game changer. Congrats @bornanovak.bsky.social @jefflotthammer.bsky.social and @alexholehouse.bsky.social

oh!! Almost forgot @alexholehouse.bsky.social will be talking about this work *TODAY* during IDP subgroup at 3:20 pm in Petree Hall C!

Lastly, the collaborative nature of this project is what made it so enjoyable. The countless discussions and white boarding together are some of my favorite parts of science. We have even more exciting stuff coming soon so stay tuned!!

I hope you take a look! If anyone wants to chat about this at #bps2025 come check out his poster or reach out!

It was a pleasure to work closely together with Borna on this work. It’s super exciting pushing beyond what was possible with ALBATROSS alone. Like usual, we strive very hard to make sure our tools are not only as accurate as possible but also widely accessible for both experts and non-experts.

Congratulations friend!! Very well deserved 🤓

Yall I can hardly contain my excitement! I'm happy to share that I’m joining the new cohort of
@HHMINews
#HannaGrayFellows! I'm grateful for the opportunity to advance my research and connect with this great community.

Thank you to @alexholehouse.bsky.social and the NSF for funding support as well as @lindorfflarsen.bsky.social for useful feedback during BPS a few years ago.

Because our approach explores local sampling, we can identify subregions within disordered proteins that are poorly sampled, enabling a per-residue assessment of sampling. This is especially useful for assessing if we should trust conclusions from a particular subregion.

By comparing sampling among independent simulation replicas and with a well-sampled polymer model, we can distinguish between situations in which local regions fold (repeatedly adopt the same local structure) or become energetically trapped in different locally frozen states.

To address this problem, and inspired by prior work from Lyle et al. (doi.org/10.1063/1.48...), we devise an approach to place an approximate empirical upper bound on the local conformational sampling given the size of the ensemble.

These isoenergetic landscapes exacerbate challenges associated with biophysical simulations. For example, one common challenge in a simulation is that you’re always “blind to” regions of conformational space that have yet to be sampled.

One challenge with biophysical simulations of disordered proteins is that they have heterogeneous isoenergetic conformational landscapes.

While important for cellular function, disordered proteins present several unique challenges for experimental characterization. Consequently, biophysicists often complement experimental approaches with computational simulations to better understand disordered protein function.

Intrinsically disordered proteins are ubiquitous across the Tree of Life and play many different important roles in cellular information processing and signaling. For a more detailed review please see: www.nature.com/articles/s41...

I’m excited to share my most recent manuscript describing an approach to assess local conformational sampling in simulations of intrinsically disordered proteins. This one’s for my computational biophysics aficionados www.biorxiv.org/content/10.1... a 🧵

A labor of love - our review on why IDRs matter for cellular function is live in Nat. Rev. Mol. Cell. Biol:
www.nature.com/articles/s41...

Working with Birthe Kraglund on this was such a pleasure, and we hope this review will be helpful to a broad audience!