#21 · Structural bio & protein design
Sequence patterning governs peptide condensation and membrane translocation
The common thread is that sequence features, including patterning, determine how disordered and membrane-active peptides behave. One item applies high-throughput molecular simulations, machine learning and mixed-integer programming to design phase-separating peptides for nanocondensate formation. Another analyzes disordered polypeptides using shuffle-based normalization of SCD and SHD patterning metrics and a Monte Carlo design algorithm yielding tunable phase behavior. A third uses umbrella-sampling MD to show that transferring the LRLLR motif removes the membrane barrier for smacN but raises it for NR2B9c, indicating that sequence compatibility governs translocation. What is new is the explicit demonstration that a transferable motif's membrane-barrier effect depends on its sequence context, and that patterning metrics are being placed on a normalized footing for design.
Preprints
Engineering nanocondensate formation through sequence composition and patterning
Computational pipeline combining high-throughput molecular simulations, machine learning, and mixed-integer programming designs phase-separating peptides…
Sequence-dependent transferability of the LRLLR membrane translocation motif: A computational study of smacN and NR2B9c peptides.
Umbrella-sampling MD: LRLLR motif transfer removes smacN's membrane barrier but raises NR2B9c's, showing sequence compatibility matters.
Analysis and design of disordered polypeptides with optimized sequence patterning properties
Shuffle-based normalization of SCD and SHD sequence patterning metrics, plus a Monte Carlo design algorithm for IDPs with tunable phase behavior, validated by…
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