Skip to main content Holland Lab | New Spider Silk Publication in PNAS Nexus
Holland Lab | New Spider Silk Publication in PNAS Nexus
51921
wp-singular,post-template-default,single,single-post,postid-51921,single-format-standard,wp-theme-bodega,ajax_fade,page_not_loaded,,select-theme-ver-2.6.1,smooth_scroll,wpb-js-composer js-comp-ver-8.0.1,vc_responsive

New Spider Silk Publication in PNAS Nexus

New Spider Silk Publication in PNAS Nexus

Thrilled to share that our PNAS Nexus paper is now online as an Advance Article , the culmination of more than five years of work.

“Sequence-Encoded Tubular Architectures in Disordered Spider Silk Proteins Revealed by Multiscale Simulations and NMR”

https://academic.oup.com/pnasnexus/article/4/12/pgaf378/8363280?login=true

This project started with a simple question that has puzzled the spider silk field for decades:

How can these massive, intrinsically disordered spidroin proteins stay soluble at extremely high concentration yet, be instantly ready to assemble into one of the toughest materials known?

Answering it required:

🔹 Multiscale MD simulations (coarse-grained MARTINI 2 & 3 + atomistic CHARMM36m/IDPSFF)
🔹 SAXS ensemble modeling over 2,581 conformers
🔹 Solution NMR backbone assignments of notoriously difficult IDP-like sequences
🔹 Custom tools developed by Chris Imboden-Forman (Vesiform, pdbProc, pdbStapler)
🔹 And a lot of persistence.

What we found is both surprising and satisfying:

Spider silk proteins form dynamic ensembles that include metastable tubular architectures ~3–4 nm in diameter and ~50 nm long — a minority population, but absolutely required to reconcile SAXS and NMR data.

These tubules arise from sequence-encoded amphiphilic patterning: hydrophobic poly(Ala) packs the core, while polar Tyr/Gln/Arg residues in Gly-Gly-X motifs stabilize the surface.

SAXS shows you can’t fit the data without them.

NMR and atomistic MD reveal they remain highly dynamic and IDP-like while exhibiting a high beta-turn content that explain the compactness.

It took:

💻 Multiple years of aggregate GPU time,
🧪 Hundreds of NMR hours,
🔍 Countless ensemble fits, simulations, and mutational studies —
but seeing this model come together has been incredibly rewarding.
Huge congratulations to Chris Imboden-Forman Forman (who drove the computational/modeling effort), David Onofrei (NMR), Dillan Stengel, Julian Aldana, Christopher Paolini, and my collaborator Nathan Gianneschi. This was truly a team achievement.

Grateful to DOD-AFOSR for supporting this effort and to everyone who contributed along the way.