An enumerative algorithm for de novo design of proteins with diverse pocket structures

To create new enzymes and biosensors from scratch, precise control over the structure of small-molecule binding sites is of paramount importance, but systematically designing arbitrary protein pocket shapes and sizes remains an outstanding challenge. Using the NTF2-like structural superfamily as a model system, we developed an enumerative algorithm for creating a virtually unlimited number of de novo proteins supporting diverse pocket structures. The enumerative algorithm was tested and refined through feedback from two rounds of large-scale experimental testing, involving in total the assembly of synthetic genes encoding 7,896 designs and assessment of their stability on yeast cell surface, detailed biophysical characterization of 64 designs, and crystal structures of 5 designs. The refined algorithm generates proteins that remain folded at high temperatures and exhibit more pocket diversity than naturally occurring NTF2-like proteins. We expect this approach to transform the design of small-molecule sensors and enzymes by enabling the creation of binding and active site geometries much more optimal for specific design challenges than is accessible by repurposing the limited number of naturally occurring NTF2-like proteins.

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A generative algorithm for de novo design of proteins with diverse pocket structures

10.1101/2020.03.23.003913 ◽

2020 ◽

Author(s):

Benjamin Basanta ◽

Matthew J Bick ◽

Asim K Bera ◽

Christoffer Norn ◽

Cameron M Chow ◽

...

Keyword(s):

Small Molecule ◽

Large Scale ◽

De Novo ◽

Experimental Testing ◽

Biophysical Characterization ◽

Synthetic Genes ◽

Precise Control ◽

Yeast Cell Surface ◽

Naturally Occurring ◽

Genes Encoding

AbstractTo create new enzymes and biosensors from scratch, precise control over the structure of small molecule binding sites is of paramount importance, but systematically designing arbitrary protein pocket shapes and sizes remains an outstanding challenge. Using the NTF2-like structural superfamily as a model system, we developed a generative algorithm for creating a virtually unlimited number of de novo proteins supporting diverse pocket structures. The generative algorithm was tested and refined through feedback from two rounds of large scale experimental testing, involving in total, the assembly of synthetic genes encoding 7896 generated designs and assessment of their stability on the yeast cell surface, detailed biophysical characterization of 64 designs, and crystal structures of 5 designs. The refined algorithm generates proteins that remain folded at high temperatures and exhibit more pocket diversity than naturally occurring NTF2-like proteins. We expect this approach to transform the design of small molecule sensors and enzymes by enabling the creation of binding and active site geometries much more optimal for specific design challenges than is accessible by repurposing the limited number of naturally occurring NTF2-like proteins.

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De Novo Transcriptomic Resources in the Brain of Vespa velutina for Invasion Control

Insects ◽

10.3390/insects11020101 ◽

2020 ◽

Vol 11 (2) ◽

pp. 101

Author(s):

Miao Wang ◽

Hanyu Li ◽

Huoqing Zheng ◽

Liuwei Zhao ◽

Xiaofeng Xue ◽

...

Keyword(s):

Large Scale ◽

Target Genes ◽

De Novo ◽

Transcriptome Profiling ◽

Molecular Study ◽

Snp Markers ◽

Nucleotide Polymorphisms ◽

Illumina Hiseq ◽

Vespa Velutina ◽

Genes Encoding

The invasion of Vespa velutina presents a great threat to the agriculture economy, the ecological environment, and human health. An effective strategy for this hornet control is urgently required, but the limited genome information of Vespa velutina restricts the application of molecular-genomic tools for targeted hornet management. Therefore, we conducted large-scale transcriptome profiling of the hornet brain to obtain functional target genes and molecular markers. Using an Illumina HiSeq platform, more than 41 million clean reads were obtained and de novo assembled into 182,087 meaningful unigenes. A total of 56,400 unigenes were annotated against publicly available protein sequence databases and a set of reliable Simple Sequence Repeats (SSRs) and Single Nucleotide Polymorphisms (SNP) markers were developed. The homologous genes encoding crucial behavior regulation factors, odorant binding proteins (OBPs), and vitellogenin, were also identified from highly expressed transcripts. This study provides abundant molecular targets and markers for invasive hornet control and further promotes the genetic and molecular study of Vespa velutina.

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Expanding the space of protein geometries by computational design of de novo fold families

10.1101/2020.04.14.041772 ◽

2020 ◽

Author(s):

Xingjie Pan ◽

Michael Thompson ◽

Yang Zhang ◽

Lin Liu ◽

James S. Fraser ◽

...

Keyword(s):

De Novo ◽

Design Method ◽

Computational Design ◽

Computational Method ◽

Structural Elements ◽

New Paradigm ◽

Biophysical Characterization ◽

Structure Space ◽

Naturally Occurring ◽

Designer Proteins

AbstractNaturally occurring proteins use a limited set of fold topologies, but vary the precise geometries of structural elements to create distinct shapes optimal for function. Here we present a computational design method termed LUCS that mimics nature’s ability to create families of proteins with the same overall fold but precisely tunable geometries. Through near-exhaustive sampling of loop-helix-loop elements, LUCS generates highly diverse geometries encompassing those found in nature but also surpassing known structure space. Biophysical characterization shows that 17 (38%) out of 45 tested LUCS designs were well folded, including 16 with designed non-native geometries. Four experimentally solved structures closely match the designs. LUCS greatly expands the designable structure space and provides a new paradigm for designing proteins with tunable geometries customizable for novel functions.One Sentence SummaryA computational method to systematically sample loop-helix-loop geometries expands the structure space of designer proteins.

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Computational design of closely related proteins that adopt two well-defined but structurally divergent folds

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1914808117 ◽

2020 ◽

Vol 117 (13) ◽

pp. 7208-7215 ◽

Cited By ~ 5

Author(s):

Kathy Y. Wei ◽

Danai Moschidi ◽

Matthew J. Bick ◽

Santrupti Nerli ◽

Andrew C. McShan ◽

...

Keyword(s):

Large Scale ◽

De Novo ◽

Conformational Transition ◽

Protein Structures ◽

Computational Design ◽

Spectroscopic Characterization ◽

De Novo Design ◽

Viral Fusion ◽

Naturally Occurring ◽

Related Proteins

The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used for de novo design of proteins that fold to a single state with a deep free-energy minimum [P.-S. Huang, S. E. Boyken, D. Baker, Nature 537, 320–327 (2016)], and to reengineer natural proteins to alter their dynamics [J. A. Davey, A. M. Damry, N. K. Goto, R. A. Chica, Nat. Chem. Biol. 13, 1280–1285 (2017)] or fold [P. A. Alexander, Y. He, Y. Chen, J. Orban, P. N. Bryan, Proc. Natl. Acad. Sci. U.S.A. 106, 21149–21154 (2009)], the de novo design of closely related sequences which adopt well-defined but structurally divergent structures remains an outstanding challenge. We designed closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations—one short (∼66 Å height) and the other long (∼100 Å height)—reminiscent of the conformational transition of viral fusion proteins. Crystallographic and NMR spectroscopic characterization shows that both the short- and long-state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large-scale conformational switches between structurally divergent forms.

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Quantification of Histone H3 Lys27 Trimethylation (H3K27me3) by High-Throughput Microscopy Enables Cellular Large-Scale Screening for Small-Molecule EZH2 Inhibitors

CrossRef Listing of Deleted DOIs ◽

10.1177/1087057114559668 ◽

2014 ◽

Vol 20 (2) ◽

pp. 190-201 ◽

Cited By ~ 20

Author(s):

Svenja Luense ◽

Philip Denner ◽

Amaury Fernández-Montalván ◽

Ingo Hartung ◽

Manfred Husemann ◽

...

Keyword(s):

Drug Discovery ◽

Small Molecule ◽

High Throughput ◽

High Throughput Screening ◽

Large Scale ◽

De Novo ◽

Histone H3 ◽

Epigenetic Therapy ◽

Cellular Assays ◽

Cancer Intervention

EZH2 inhibition can decrease global histone H3 lysine 27 trimethylation (H3K27me3) and thereby reactivates silenced tumor suppressor genes. Inhibition of EZH2 is regarded as an option for therapeutic cancer intervention. To identify novel small-molecule (SMOL) inhibitors of EZH2 in drug discovery, trustworthy cellular assays amenable for phenotypic high-throughput screening (HTS) are crucial. We describe a reliable approach that quantifies changes in global levels of histone modification marks using high-content analysis (HCA). The approach was validated in different cell lines by using small interfering RNA and SMOL inhibitors. By automation and miniaturization from a 384-well to 1536-well plate, we demonstrated its utility in conducting phenotypic HTS campaigns and assessing structure-activity relationships (SAR). This assay enables screening of SMOL EZH2 inhibitors and can advance the mechanistic understanding of H3K27me3 suppression, which is crucial with regard to epigenetic therapy. We observed that a decrease in global H3K27me3, induced by EZH2 inhibition, comprises two distinct mechanisms: (1) inhibition of de novo DNA methylation and (II) inhibition of dynamic, replication-independent H3K27me3 turnover. This report describes an HCA assay for primary HTS to identify, profile, and optimize cellular active SMOL inhibitors targeting histone methyltransferases, which could benefit epigenetic drug discovery.

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A role for neutral variation in the evolution of C4 photosynthesis

10.1101/2020.05.19.104299 ◽

2020 ◽

Cited By ~ 1

Author(s):

Shanta Karki ◽

HsiangChun Lin ◽

Florence R Danila ◽

Basel Abu-Jamous ◽

Rita Giuliani ◽

...

Keyword(s):

Large Scale ◽

Adaptive Changes ◽

Environmental Selection ◽

Naturally Occurring ◽

Expression Of Genes ◽

Neutral Variation ◽

Genes Encoding ◽

Genotype Space ◽

Simple Sequence ◽

Phenotypic Convergence

AbstractConvergent trait evolution is a recurrent phenomenon in all domains of the tree of life. While some convergent traits are caused by simple sequence changes, many are associated with extensive changes to the sequence and regulation of large cohorts of genes. It is unknown how organisms traverse this expansive genotype space to assemble such complex convergent phenotypes. C4 photosynthesis is a paradigm of large-scale phenotypic convergence. Conceptual and mathematical models propose that C4 photosynthesis evolved from ancestral C3 photosynthesis through sequential adaptive changes. These adaptive changes could have been rapidly assembled if modifications to the activity and abundance of enzymes of the C4 cycle was neutral in C3 plants. This neutrality would enable populations of C3 plants to maintain genotypes with expression levels of C4 enzymes analogous to those in C4 species and thus enable rapid assembly of a functional C4 cycle from naturally occurring genotypes given shared environmental selection. Here we show that there is substantial natural variation in expression of genes encoding C4 cycle enzymes between natural accessions of the C3 plant Arabidopsis thaliana. We further show through targeted transgenic experiments in the C3 crop Oryza sativa, that high expression of the majority of C4 cycle enzymes in rice is neutral with respect to growth, development, biomass and photosynthesis. Thus, substantial variation in the abundance and activity of C4 cycle enzymes is permissible within the limits of operation of C3 photosynthesis and the emergence of component parts of this complex convergent trait can be facilitated by neutral variation.

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Computational design of a protein family that adopts two well-defined and structurally divergent de novo folds

10.1101/597161 ◽

2019 ◽

Author(s):

Kathy Y. Wei ◽

Danai Moschidi ◽

Matthew J. Bick ◽

Santrupti Nerli ◽

Andrew C. McShan ◽

...

Keyword(s):

Large Scale ◽

De Novo ◽

Conformational Transition ◽

Protein Structures ◽

Computational Design ◽

Spectroscopic Characterization ◽

De Novo Design ◽

Viral Fusion ◽

Naturally Occurring ◽

Viral Fusion Proteins

AbstractThe plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used to de novo design proteins that fold to a single state with a deep free energy minima (Huang et al., 2016), and to reengineer natural proteins to alter their dynamics (Davey et al., 2017) or fold (Alexander et al., 2009), the de novo design of closely related sequences which adopt well-defined, but structurally divergent structures remains an outstanding challenge. Here, we design closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations -- one short (∼66 Å height) and the other long (∼100 Å height) -- reminiscent of the conformational transition of viral fusion proteins (Ivanovic et al., 2013; Podbilewicz, 2014; Skehel and Wiley, 2000). Crystallographic and NMR spectroscopic characterization show that both the short and long state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large scale conformational switches between structurally divergent forms.

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Expanding the space of protein geometries by computational design of de novo fold families

Science ◽

10.1126/science.abc0881 ◽

2020 ◽

Vol 369 (6507) ◽

pp. 1132-1136

Author(s):

Xingjie Pan ◽

Michael C. Thompson ◽

Yang Zhang ◽

Lin Liu ◽

James S. Fraser ◽

...

Keyword(s):

De Novo ◽

Design Method ◽

Computational Design ◽

Structural Elements ◽

New Paradigm ◽

Biophysical Characterization ◽

Structure Space ◽

Naturally Occurring

Naturally occurring proteins vary the precise geometries of structural elements to create distinct shapes optimal for function. We present a computational design method, loop-helix-loop unit combinatorial sampling (LUCS), that mimics nature’s ability to create families of proteins with the same overall fold but precisely tunable geometries. Through near-exhaustive sampling of loop-helix-loop elements, LUCS generates highly diverse geometries encompassing those found in nature but also surpassing known structure space. Biophysical characterization showed that 17 (38%) of 45 tested LUCS designs encompassing two different structural topologies were well folded, including 16 with designed non-native geometries. Four experimentally solved structures closely matched the designs. LUCS greatly expands the designable structure space and offers a new paradigm for designing proteins with tunable geometries that may be customizable for novel functions.

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High performance microbial opsins for spatially and temporally precise perturbations of large neuronal networks

10.1101/2021.04.01.438134 ◽

2021 ◽

Author(s):

Savitha Sridharan ◽

Marta Gajowa ◽

Mora B Ogando ◽

Uday Jagadisan ◽

Lamiae Abdeladim ◽

...

Keyword(s):

High Performance ◽

Large Scale ◽

Biophysical Characterization ◽

Fast Kinetics ◽

Precise Control ◽

Neuronal Populations ◽

Intact Brain ◽

And Behavior

Patterned optogenetic activation of defined neuronal populations in the intact brain can reveal fundamental aspects of the neural codes of perception and behavior. The biophysical properties of existing optogenetic tools, however, constrain the scale, speed, and fidelity of precise optical control. Here we use structure-guided mutagenesis to engineer opsins that exhibit very high potency while retaining fast kinetics. These new opsins enable large-scale, temporally and spatially precise control of population neural activity in vivo and in vitro. We benchmark these new opsins against existing optogenetics tools with whole-cell electrophysiology and all-optical physiology and provide a detailed biophysical characterization of a diverse family of microbial opsins under two-photon illumination. This establishes a toolkit and a resource for matching the optimal opsin to the goals and constraints of patterned optogenetics experiments. Finally, by combining these new opsins with optimized procedures for cell-specific holographic photo-stimulation, we demonstrate the simultaneous co-activation of several hundred spatially defined neurons with a single hologram, and nearly double that number by temporally interleaving holograms at fast rates. These newly engineered opsins substantially extend the capabilities of patterned illumination optogenetic paradigms for addressing neural circuits and behavior.

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Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

10.26434/chemrxiv.11663337.v3 ◽

2020 ◽

Author(s):

Salvador Guardiola ◽

Monica Varese ◽

Xavier Roig ◽

Jesús Garcia ◽

Ernest Giralt

Keyword(s):

Protein Interactions ◽

Cyclic Peptides ◽

General Framework ◽

Large Scale ◽

De Novo ◽

Inhibitory Effect ◽

Original Text ◽

Protein Protein Interactions ◽

Retraction Notice ◽

Pharmaceutical Properties

NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above. ------------------------------------------------------------------------ Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-i3 and PD-i6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our de novo design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.

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