Sculpting conducting nanopore size and shape throughde novoprotein design

Abstract

Transmembrane β-barrels (TMBs) are widely used for single molecule DNA and RNA sequencing and have considerable potential for a broad range of sensing and sequencing applications. Current engineering approaches for nanopore sensors are limited to naturally occurring channels such as CsgG, which have evolved to carry out functions very different from sensing, and hence provide sub-optimal starting points. In contrast,de novoprotein design can in principle create an unlimited number of new nanopores with any desired properties. Here we describe a general approach to the design of transmembrane β-barrel pores with different diameter and pore geometry. NMR and crystallographic characterization shows that the designs are stably folded with structures close to the design models. We report the first examples ofde novodesigned TMBs with 10, 12 and 14 stranded β-barrels. The designs have distinct conductances that correlate with their pore diameter, ranging from 110 pS (∼0.5 nm pore diameter) to 430 pS (∼1.1 nm pore diameter), and can be converted into sensitive small-molecule sensors with high signal to noise ratio. The capability to generate on demand β-barrel pores of defined geometry opens up fundamentally new opportunities for custom engineering of sequencing and sensing technologies.One sentence summaryDe novo design enables the generation of stable and quite transmembrane beta-barrel nanopores with tailored sizes, shapes and properties.

Parametrically guided design of beta barrels and transmembrane nanopores using deep learning

“…Protein nanopore engineering has primarily involved making small numbers of mutations in naturally occurring pore-forming proteins, and hence the range of applications has been limited to molecules with roughly the same sizes and diameters of these natural pores. Using a traditional "blueprint" based approach, we have successfully designed de novo beta barrel nanopores with different sizes and shapes 10 , however, the process to generate large beta barrel backbones with control over key features such as beta bulges and register shifts between adjacent strands is difficult and requires significant human expertise. We explored the design of transmembrane beta barrels using the combination of global parametric backbone generation and RFjoint2 described above.…”

“…We first generated backbones using the aforementioned strategy spanning a wide range of overall shapes with 12, 14 and 16 beta strands. For sequence design 10 , we used a previously described approach which favors hydrophobic residues on the surface of the beta barrels and mostly hydrophilic residues within the pore lining. To compare pore conductances with our previously generated beta-barrel pores made using Rosetta blueprint approaches, we made pore backbones with 12 and 14 strands and a combination of different shear numbers and number of residues per strand.…”

“…To compare pore conductances with our previously generated beta-barrel pores made using Rosetta blueprint approaches, we made pore backbones with 12 and 14 strands and a combination of different shear numbers and number of residues per strand. Pore backbones which were successfully predicted with AlphaFold2 (AF2) 27 post sequence design using ProteinMPNN, were then redesigned for optimal membrane pore-like sequences with multiple rounds of Rosetta based sequence design as described previously 10 . After subsequent filtering with AF2 and selecting for sequences with low beta-sheet propensities (calculated using Raptor-X as described previously 9 ), we selected 81 designs for experimental characterization.…”

“…However, a similar approach based on parametrically generated beta barrel backbone structures did not yield designs which folded when produced in the lab, even when the backbones were relaxed to improve hydrogen bonding using Rosetta based structural relaxation 6 . Instead, beta barrels with new structures and functions ranging from fluorescent sensors 6 to transmembrane channels 9,10 have been designed using Rosetta "blueprints." While powerful, this approach can control the overall shape only indirectly through explicit specification of blueprint features such as the strand number, strand lengths, barrel shear [6][7][8] , backbone hydrogen bonding arrangement, positioning of irregularities such as glycine kinks and beta bulges required for continuous hydrogen bonding and backbone strain reduction 6,11 , and tyrosine corners 6 .…”

ProteinMPNN Recovers Complex Sequence Properties of Transmembrane β-barrels

“…Previous success in de novo TMB design utilized the reference Rosetta energy function manually refitted to design sequences with TMB-like properties [7][21]. The successful design of TMBs using this method elucidated properties of designed TMB sequences that are necessary for proper expression and folding in vitro , including the importance of negative design (local destabilization of sequences) to generate sequences with weak β-sheet propensity that slow β-sheet assembly [21][38]. These findings were validated experimentally by Martin et al [22].…”