Cole DeForest

@coledeforest.bsky.social

1948 Followers 533 Following

Weyerhaeuser Endowed Professor of Chemical Engineering & Bioengineering, University of Washington | User-Programmable Biomaterials | Photochemistry | Optogenetics | Protein Engineering http://www.coledeforest.com

Stimuli-responsive biomaterials hold great promise in controlled therapeutic delivery, tissue engineering, and biosensing applications. Recently, molecular assembly via autonomous compilation has been employed to create topologically specified protein cargos that can be site-specifically tethered to and conditionally released from biomaterials following user-programmable Boolean logic. Prior implementation has been confined to simple fluorescent protein outputs and model protease inputs. In this manuscript, we extend the applicability of this framework by assembling all 7 unique logical operations emanating from a YES/OR/AND 3-input operator set to deliver bioactive proteins spanning diverse categories: growth factors (epidermal growth factor), model enzymes (β-lactamase, NanoLuciferase, and thioredoxin A), therapeutic nanobodies (anti-human epidermal growth factor receptor 2), de novo-engineered cytokines (Neoleukin), and fluorescent proteins (mGreenLantern). In so doing, we demonstrate programmable biomacromolecule release from material anchors in response to precise combinations of three orthogonal protease actuators while maintaining native bioactivity. Through inclusion of a photocleavable protein motif, we further establish that visible light can be employed as an additional input in specifying logic-based protein release. We anticipate these methods will powerfully expand opportunities for targeted therapeutic delivery and beyond.
Protein-based biomaterials have risen in popularity in recent years owing to their genetic encodability, sequence specificity, monodispersity, and ability to interface with biological systems in comparison with synthetic polymer-based materials. Though naturally derived and minimally engineered proteins have been at the forefront of these efforts, recent advances in computational protein design offer exciting opportunities for next-generation biomaterial development. In this work, we employ de novo protein design methodologies to generate a suite of self-assembling multimeric proteins, whose step-growth heteropolymerization into bulk hydrogels and condensates can be exogenously triggered through small-molecule addition. Our results highlight how changes in programmed multimer valency and their triggered assembly yield materials with varying structures and viscoelasticity. We anticipate that these approaches will prove useful in rapidly generating large libraries of stimuli-responsive biomaterials that are precisely tailored to specific applications in the biosciences and beyond.
Stimulus-responsive materials have enabled advanced applications in biosensing, tissue engineering and therapeutic delivery. Although controlled molecular topology has been demonstrated as an effective route toward creating materials that respond to prespecified input combinations, prior efforts suffer from a reliance on complicated and low-yielding multistep organic syntheses that dramatically limit their utility. Harnessing the power of recombinant expression, we integrate emerging chemical biology tools to create topologically specified protein cargos that can be site-specifically tethered to and conditionally released from biomaterials following user-programmable Boolean logic. Critically, construct topology is autonomously compiled during expression through spontaneous intramolecular ligations, enabling direct and scalable synthesis of advanced operators. Using this framework, we specify protein release from biomaterials following all 17 possible YES/OR/AND logic outputs from input combinations of three orthogonal protease actuators, multiplexed delivery of three distinct biomacromolecules from hydrogels, five-input-based conditional cargo liberation and logically defined protein localization on or within living mammalian cells.