Extension of a <i>de novo</i> TIM barrel with a rationally designed secondary structure element

Wiese, Jonas Gregor; Shanmugaratnam, S.; Höcker, Birte

doi:10.1002/pro.4064

Cited by 12 publications

(15 citation statements)

References 25 publications

(41 reference statements)

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“…4 , we show structures 486 and 1060 , two examples of such complex structures. In particular, 1068 shows a TIM-barrel fold, a topology which to date has met impressive success in de novo design 62 – 64 , but whose idealized structure has nevertheless proven challenging to extend via additional secondary elements and longer loops 65 , 66 .…”

Section: Resultsmentioning

confidence: 99%

ProtGPT2 is a deep unsupervised language model for protein design

2022

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Protein design aims to build novel proteins customized for specific purposes, thereby holding the potential to tackle many environmental and biomedical problems. Recent progress in Transformer-based architectures has enabled the implementation of language models capable of generating text with human-like capabilities. Here, motivated by this success, we describe ProtGPT2, a language model trained on the protein space that generates de novo protein sequences following the principles of natural ones. The generated proteins display natural amino acid propensities, while disorder predictions indicate that 88% of ProtGPT2-generated proteins are globular, in line with natural sequences. Sensitive sequence searches in protein databases show that ProtGPT2 sequences are distantly related to natural ones, and similarity networks further demonstrate that ProtGPT2 is sampling unexplored regions of protein space. AlphaFold prediction of ProtGPT2-sequences yields well-folded non-idealized structures with embodiments and large loops and reveals topologies not captured in current structure databases. ProtGPT2 generates sequences in a matter of seconds and is freely available.

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Section: Resultsmentioning

confidence: 99%

ProtGPT2 is a deep unsupervised language model for protein design

2022

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“…Recalling the evolution, design, and folding studies of the tryptophan synthase TIM barrel protein − ,− and the impact of the hydrophobic sliding mechanism on HIV-1PR, − we performed a structural ILV hydrophobic clustering of BSLA (PDB ID 1ISP). ILV clusters are domains in the protein identified by calculating close contacts of the side chains of isoleucine (I), leucine (L), and valine (V).…”

Section: Resultsmentioning

confidence: 99%

“…Thus, these results set a reference for future comparative studies of other BSLA constructs and modified (bioconjugate or tethered) systems. Additionally, the results imply that hydrophobic clustering may dictate local surface hydration properties; perhaps through modulation of protein conformations and samplings of the unfolded states. − …”

Section: Introductionmentioning

confidence: 97%

Hydrophobic Clusters Regulate Surface Hydration Dynamics of Bacillus subtilis Lipase A

Jaufer,

Bouhadana,

Fanucci

2024

J. Phys. Chem. B

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The surface hydration diffusivity of Bacillus subtilis Lipase A (BSLA) has been characterized by low-field Overhauser dynamic nuclear polarization (ODNP) relaxometry using a series of spin-labeled constructs. Sites for spin-label incorporation were previously designed via an atomistic computational approach that screened for surface exposure, reflective of the surface hydration comparable to other proteins studied by this method, as well as minimal impact on protein function, dynamics, and structure of BSLA by excluding any surface site that participated in greater than 30% occupancy of a hydrogen bonding network within BSLA. Experimental ODNP relaxometry coupling factor results verify the overall surface hydration behavior for these BSLA spin-labeled sites similar to other globular proteins. Here, by plotting the ODNP parameters of relative diffusive water versus the relative bound water, we introduce an effective "phase-space" analysis, which provides a facile visual comparison of the ODNP parameters of various biomolecular systems studied to date. We find notable differences when comparing BSLA to other systems, as well as when comparing different clusters on the surface of BSLA. Specifically, we find a grouping of sites that correspond to the spinlabel surface location within the two main hydrophobic core clusters of the branched aliphatic amino acids isoleucine, leucine, and valine cores observed in the BSLA crystal structure. The results imply that hydrophobic clustering may dictate local surface hydration properties, perhaps through modulation of protein conformations and samplings of the unfolded states, providing insights into how the dynamics of the hydration shell is coupled to protein motion and fluctuations.

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“…Improving our understanding of the determinants of protein stability (2)(3)(4) would accelerate biological, biomedical, and biotechnology research. In particular, computational models of protein stability are commonly used for a range of applications, including protein design (5)(6)(7), stabilizing naturally occurring proteins (8,9), and predicting the effects of point mutants (10)(11)(12). However, all of these models have important limitations.…”

Section: Introductionmentioning

confidence: 99%

Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation

Kim¹,

Tsuboyama²,

Houliston

et al. 2021

Preprint

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Designing entirely new protein structures remains challenging because we do not fully understand the biophysical determinants of folding stability. Yet some protein folds are easier to design than others. Previous work identified the 43-residue αββ&#945 fold as especially challenging: the best designs had only a 2% success rate, compared to 39-87% success for other simple folds (1). This suggested the αββ&#945 fold would be a useful model system for gaining a deeper understanding of folding stability determinants and for testing new protein design methods. Here, we designed over ten thousand new αββ&#945 proteins and found over three thousand of them to fold into stable structures using a high-throughput protease-based assay. Nuclear magnetic resonance, hydrogen-deuterium exchange, circular dichroism, deep mutational scanning, and scrambled sequence control experiments indicated that our stable designs fold into their designed αββ&#945 structures with exceptional stability for their small size. Our large dataset enabled us to quantify the influence of universal stability determinants including nonpolar burial, helix capping, and buried unsatisfied polar atoms, as well as stability determinants unique to the αββ&#945 topology. Our work demonstrates how large-scale design and test cycles can solve challenging design problems while illuminating the biophysical determinants of folding.

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Extension of a de novo TIM barrel with a rationally designed secondary structure element

Cited by 12 publications

References 25 publications

ProtGPT2 is a deep unsupervised language model for protein design

ProtGPT2 is a deep unsupervised language model for protein design

Hydrophobic Clusters Regulate Surface Hydration Dynamics of Bacillus subtilis Lipase A

Dissecting the stability determinants of a challenging de novo protein fold using massively parallel design and experimentation

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