De novo design of allosterically switchable protein assemblies

Pillai, Arvind; Idris, Abbas; Philomin, Annika; Weidle, Connor; Skotheim, Rebecca; Leung, Philip J. Y.; Broerman, Adam; Demakis, Cullen; Borst, Andrew J.; Praetorius, Florian; Baker, David

doi:10.1101/2023.11.01.565167

Cited by 3 publications

(2 citation statements)

References 69 publications

(116 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While much of cellular biochemistry computes decisions, it had been unclear how directed evolution could straightforwardly tune proteins with such capabilities. Apart from interest in this as a fundamental problem, a solution is also needed for protein engineering since dynamic, multistate, and computational properties are of intense current interest, especially, for protein design [109][110][111][112][113] .…”

Section: Discussionmentioning

confidence: 99%

Light-directed evolution of dynamic, multi-state, and computational protein functionalities

Gligorovski,

Labagnara,

Rahi

2024

Preprint

View full text Add to dashboard Cite

Directed evolution is a powerful method in biological engineering. Current approaches were devised for evolving steady-state properties such as enzymatic activity or fluorescence intensity. A fundamental problem remains how to evolve dynamic, multi-state, or computational functionalities, e.g., folding times, on-off kinetics, state-specific activity, stimulus-responsiveness, or switching and logic capabilities. These require applying selection pressure on all of the states of a protein of interest (POI) and the transitions between them. We realized that optogenetics and cell cycle oscillations could be leveraged for a novel directed evolution paradigm (‘optovolution’) that is germane for this need: We designed a signaling cascade in budding yeast where optogenetic input switches the POI between off (0) and on (1) states. In turn, the POI controls a Cdk1 cyclin, which in the re-engineered cell cycle system is essential for one cell cycle stage but poisonous for another. Thus, the cyclin must oscillate (1-0-1-0…) for cell proliferation. In this system, evolution can act efficiently on the dynamics, transient states, and input-output relations of the POI in every cell cycle. Further, controlling the pacemaker, light, directs and tunes selection pressures. Optovolution isin vivo, continuous, self-selecting, and genetically robust. We first evolved two optogenetic systems, which relay 0/1 input to 0/1 output: We obtained 25 new variants of the widely used LOV transcription factor El222. These mutants were stronger, less leaky, or green- and red-responsive. The latter was conjectured to be impossible for LOV domains but is needed for multiplexing and lowering phototoxicity. Evolving the PhyB-Pif3 optogenetic system, we discovered that loss ofYOR1makes supplementing the expensive and unstable chromophore phycocyanobilin (PCB) unnecessary. Finally, we demonstrate the generality of the method by creating and evolving a destabilized rtTA transcription factor, which performs an AND operation between transcriptional and doxycycline input. Optovolution makes coveted, difficult-to-change protein functionalities evolvable.

show abstract

Section: Discussionmentioning

confidence: 99%

Light-directed evolution of dynamic, multi-state, and computational protein functionalities

Gligorovski,

Labagnara,

Rahi

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The mass photometry assays were performed following previously published protocol( 49 ). All mass photometry measurements were carried out in an instrument TwoMP (Refeyn) Mass photometer.…”

Section: Supplementary Materialsmentioning

confidence: 99%

De novo design of diverse small molecule binders and sensors using Shape Complementary Pseudocycles

An,

Said,

Tran

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

A general method for designing proteins to bind and sense any small molecule of interest would be widely useful. Due to the small number of atoms to interact with, binding to small molecules with high affinity requires highly shape complementary pockets, and transducing binding events into signals is challenging. Here we describe an integrated deep learning and energy based approach for designing high shape complementarity binders to small molecules that are poised for downstream sensing applications. We employ deep learning generated psuedocycles with repeating structural units surrounding central pockets; depending on the geometry of the structural unit and repeat number, these pockets span wide ranges of sizes and shapes. For a small molecule target of interest, we extensively sample high shape complementarity pseudocycles to generate large numbers of customized potential binding pockets; the ligand binding poses and the interacting interfaces are then optimized for high affinity binding. We computationally design binders to four diverse molecules, including for the first time polar flexible molecules such as methotrexate and thyroxine, which are expressed at high levels and have nanomolar affinities straight out of the computer. Co-crystal structures are nearly identical to the design models. Taking advantage of the modular repeating structure of pseudocycles and central location of the binding pockets, we constructed low noise nanopore sensors and chemically induced dimerization systems by splitting the binders into domains which assemble into the original pseudocycle pocket upon target molecule addition.One Sentence SummaryWe use a pseuodocycle-based shape complementarity optimizing approach to design nanomolar binders to diverse ligands, including the flexible and polar methotrexate and thyroxine, that can be directly converted into ligand-gated nanopores and chemically induced dimerization systems.

show abstract

Binding and sensing diverse small molecules using shape-complementary pseudocycles

An,

Said,

Tran

et al. 2024

Science

View full text Add to dashboard Cite

We describe an approach for designing high-affinity small molecule–binding proteins poised for downstream sensing. We use deep learning–generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.

show abstract

De novo design of allosterically switchable protein assemblies

Cited by 3 publications

References 69 publications

Light-directed evolution of dynamic, multi-state, and computational protein functionalities

Light-directed evolution of dynamic, multi-state, and computational protein functionalities

De novo design of diverse small molecule binders and sensors using Shape Complementary Pseudocycles

Binding and sensing diverse small molecules using shape-complementary pseudocycles

Contact Info

Product

Resources

About