Biology subjects

Kuhlman, B.

Publications and source records attributed to Kuhlman, B..

23 records · Page 2Linked to original sources

bioRxiv2023

De novo design of stable proteins that efficaciously inhibit oncogenic G proteins

Many protein therapeutics are competitive inhibitors that function by binding to endogenous proteins and preventing them from interacting with native partners. One effective strategy for engineering competitive inhibitors is to graft structural motifs from a native partner into a host protein. Here, we develop and experimentally test a computational protocol for embedding binding motifs in de novo designed proteins. The protocol uses an "inside-out" approach: Starting with a structural model of the binding motif docked against the target protein, the de novo protein is built by growing new structural elements off the termini of the binding motif. During backbone assembly, a score function favors backbones that introduce new tertiary contacts within the designed protein and do not introduce clashes with the target binding partner. Final sequences are designed and optimized using the molecular modeling program Rosetta. To test our protocol, we designed small helical proteins to inhibit the interaction between Gq and its effector PLC-{beta} isozymes. Several of the designed proteins remain folded above 90{degrees}C and bind to Gq with equilibrium dissociation constants tighter than 80 nM. In cellular assays with oncogenic variants of Gq, the designed proteins inhibit activation of PLC-{beta} isozymes and Dbl-family RhoGEFs. Our results demonstrate that computational protein design, in combination with motif grafting, can be used to directly generate potent inhibitors without further optimization via high throughput screening or selection. statement for broader audienceEngineered proteins that bind to specific target proteins are useful as research reagents, diagnostics, and therapeutics. We used computational protein design to engineer de novo proteins that bind and competitively inhibit the G protein, Gq, which is an oncogene for uveal melanomas. This computational method is a general approach that should be useful for designing competitive inhibitors against other proteins of interest.

synthetic biology↗

bioRxiv2022

AlphaFold accurately predicts distinct conformations based on oligomeric state of a de novo designed protein

Using the molecular modeling program Rosetta, we designed a de novo protein, called SEWN0.1, that binds the heterotrimeric G protein Gq. The design is helical, well-folded, and primarily monomeric in solution at a concentration of 10 uM. However, when we solved the crystal structure of SEWN0.1, we observed a dimer in a conformation incompatible with binding Gq. Unintentionally, we had designed a protein that adopts alternate conformations depending on its oligomeric state. Recently, there has been tremendous progress in the field of protein structure prediction as new methods in artificial intelligence have been used to predict structures with high accuracy. We were curious if the structure prediction method AlphaFold could predict the structure of SEWN0.1 and if the prediction depended on oligomeric state. When AlphaFold was used to predict the structure of monomeric SEWN0.1, it produced a model that resembles the Rosetta design model and is compatible with binding Gq, but when used to predict the structure of a dimer, it predicted a conformation that closely resembles the SEWN0.1 crystal structure. AlphaFolds ability to predict multiple conformations for a single protein sequence should be useful for engineering protein switches.

biophysics↗

bioRxiv2020

An optogenetic switch for the Set2 methyltransferase provides evidence for rapid transcription-dependent and independent dynamics of H3K36 methylation

Histone H3 lysine 36 methylation (H3K36me) is a conserved histone modification associated with transcription and DNA repair. Although the effects of H3K36 methylation have been studied, the short-term genome-wide dynamics of H3K36me deposition and removal are not known. We established rapid and reversible optogenetic control for Set2, the sole H3K36 methyltransferase in yeast, by fusing the enzyme with the light activated nuclear shuttle (LANS) domain. Early H3K36me3 dynamics identified rapid methylation in vivo, with total H3K36me3 levels correlating with RNA abundance. Although genes exhibited disparate levels of H3K36 methylation, relative rates of H3K36me3 accumulation were largely linear and consistent across genes, suggesting a rate-limiting mechanism for H3K36me3 deposition. Removal H3K36me2/3 was also rapid and highly dependent on the demethylase Rph1. However, the per-gene rate of H3K36me3 loss weakly correlated with RNA abundance and followed exponential decay, suggesting H3K36 demethylases act in a global, stochastic manner.

molecular biology↗

bioRxiv2017

Control of microtubule dynamics using an optogenetic microtubule plus end-F-actin cross-linker

We developed a novel optogenetic tool, SxIP-iLID, to facilitate the reversible recruitment of factors to microtubule (MT) plus ends in an End Binding (EB) protein-dependent manner using blue light. We show that SxIP-iLID can track MT plus ends and recruit tgRFP-SspB upon blue light activation. We then used this system to investigate the effects of cross-linking MT plus ends and F-actin in Drosophila S2 cells to gain insight into spectraplakin function and mechanism. We show that SxIP-iLID can be used to temporally recruit a F-actin binding domain to MT plus ends and cross-link the MT and F-actin networks. Light-mediated MT-F-actin cross-linking decreases MT growth velocities and generates a MT exclusion zone in the lamella. SxIP-iLID facilitates the general recruitment of specific factors to MT plus ends with temporal control enabling researchers to systematically regulate MT plus end dynamics and probe MT plus end function in many biological processes.\n\nSummarySxIP-iLID is a novel optogenetic tool designed to assess the spatiotemporal role of proteins on microtubule dynamics. We establish that optogenetic cross-linking of microtubule and actin networks decreases MT growth velocities and increases the cell area void of microtubules.

cell biology↗

bioRxiv2017

The Rosetta all-atom energy function for macromolecular modeling and design

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosettas success is the energy function: amodel parameterized from small molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, beta_nov15. Applying these concepts,we explain how to use Rosetta energies to identify and analyze the features of biomolecular models.Finally, we discuss the latest advances in the energy function that extend capabilities from soluble proteins to also include membrane proteins, peptides containing non-canonical amino acids, carbohydrates, nucleic acids, and other macromolecules.

biophysics↗