scholarly journals Computational redesign of a fluorogen activating protein with Rosetta

2021 ◽  
Vol 17 (11) ◽  
pp. e1009555
Author(s):  
Nina G. Bozhanova ◽  
Joel M. Harp ◽  
Brian J. Bender ◽  
Alexey S. Gavrikov ◽  
Dmitry A. Gorbachev ◽  
...  
Keyword(s):  
Protein Design ◽  
De Novo ◽  
Binding Pocket ◽  
Fluorescent Imaging ◽  
Fine Tuning ◽  
Ligand Docking ◽  
Pose Prediction ◽  
Functional Protein ◽  
Split System

The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encoded fluorescent imaging tools through the design of fluorogen activating proteins (FAPs). While there is already a handful of such probes available, each of them went through laborious cycles of in vitro screening and selection. Computational modeling approaches are evolving incredibly fast right now and are demonstrating great results in many applications, including de novo protein design. It suggests that the easier task of fine-tuning the fluorogen-binding properties of an already functional protein in silico should be readily achievable. To test this hypothesis, we used Rosetta for computational ligand docking followed by protein binding pocket redesign to further improve the previously described FAP DiB1 that is capable of binding to a BODIPY-like dye M739. Despite an inaccurate initial docking of the chromophore, the incorporated mutations nevertheless improved multiple photophysical parameters as well as the overall performance of the tag. The designed protein, DiB-RM, shows higher brightness, localization precision, and apparent photostability in protein-PAINT super-resolution imaging compared to its parental variant DiB1. Moreover, DiB-RM can be cleaved to obtain an efficient split system with enhanced performance compared to a parental DiB-split system. The possible reasons for the inaccurate ligand binding pose prediction and its consequence on the outcome of the design experiment are further discussed.

scholarly journals Rational construction of compact de novo-designed biliverdin-binding proteins

2018 ◽  
Author(s):  
Molly M. Sheehan ◽  
Michael S. Magaraci ◽  
Ivan A. Kuznetsov ◽  
Joshua A. Mancini ◽  
Goutham Kodali ◽  
...  
Keyword(s):  
Protein Design ◽  
De Novo ◽  
Binding Pocket ◽  
Heptad Repeat ◽  
Hydrophobic Core ◽  
Protein Scaffold ◽  
Self Assembling ◽  
High Resolution Structure ◽  
Rational Construction

Abstract:We report the rational construction of a de novo-designed biliverdin-binding protein by first principles of protein design, informed by energy minimization modeling in Rosetta. The self-assembling tetrahelical bundles bind biliverdin IXa (BV) cofactor auto-catalytically in vitro, similar to photosensory proteins that bind BV (and related bilins, or linear tetrapyrroles) despite lacking sequence and structural homology to the natural counterparts. Upon identifying a suitable site for cofactor ligation to the protein scaffold, stepwise placement of residues stabilized BV within the hydrophobic core. Rosetta modeling was used in the absence of a high-resolution structure to define the structure-function of the binding pocket. Holoprotein formation indeed stabilized BV, resulting in increased far-red BV fluorescence. By removing segments extraneous to cofactor stabilization or bundle stability, the initial 15-kilodalton de novo-designed fluorescence-activating protein (“dFP”) was truncated without altering its optical properties, down to a miniature 10-kilodalton “mini,” in which the protein scaffold extends only a half-heptad repeat beyond the hypothetical position of the bilin D-ring. This work demonstrates how highly compact holoprotein fluorochromes can be rationally constructed using de novo protein design technology and natural cofactors.

scholarly journals Uncovering the functional residues ofArabidopsisisoprenoid biosynthesis enzyme HDS

2019 ◽  
Vol 117 (1) ◽  
pp. 355-361 ◽  
Author(s):  
Jin-Zheng Wang ◽  
Yongxing Lei ◽  
Yanmei Xiao ◽  
Xiang He ◽  
Jiubo Liang ◽  
...  
Keyword(s):  
Rational Design ◽  
Binding Pocket ◽  
Mep Pathway ◽  
Fine Tuning ◽  
Ligand Docking ◽  
Stunted Growth ◽  
Mutant Phenotypes ◽  
Retrograde Signal

The methylerythritol phosphate (MEP) pathway is responsible for producing isoprenoids, metabolites with essential functions in the bacterial kingdom and plastid-bearing organisms including plants and Apicomplexa. Additionally, the MEP-pathway intermediate methylerythritol cyclodiphosphate (MEcPP) serves as a plastid-to-nucleus retrograde signal. A suppressor screen of the high MEcPP accumulating mutant plant (ceh1) led to the isolation of 3 revertants (designatedRceh1–3) resulting from independent intragenic substitutions of conserved amino acids in the penultimate MEP-pathway enzyme, hydroxymethylbutenyl diphosphate synthase (HDS). The revertants accumulate varying MEcPP levels, lower than that ofceh1, and exhibit partial or full recovery of MEcPP-mediated phenotypes, including stunted growth and induced expression of stress response genes and the corresponding metabolites. Structural modeling of HDS and ligand docking spatially position the substituted residues at the MEcPP binding pocket and cofactor binding domain of the enzyme. Complementation assays confirm the role of these residues in suppressing theceh1mutant phenotypes, albeit to different degrees. In vitro enzyme assays of wild type and HDS variants exhibit differential activities and reveal an unanticipated mismatch between enzyme kinetics and the in vivo MEcPP levels in the correspondingRcehlines. Additional analyses attribute the mismatch, in part, to the abundance of the first and rate-limiting MEP-pathway enzyme, DXS, and further suggest MEcPP as a rheostat for abundance of the upstream enzyme instrumental in fine-tuning of the pathway flux. Collectively, this study identifies critical residues of a key MEP-pathway enzyme, HDS, valuable for synthetic engineering of isoprenoids, and as potential targets for rational design of antiinfective drugs.

scholarly journals Expanding functional protein sequence space using generative adversarial networks

2019 ◽  
Author(s):  
Donatas Repecka ◽  
Vykintas Jauniskis ◽  
Laurynas Karpus ◽  
Elzbieta Rembeza ◽  
Jan Zrimec ◽  
...  
Keyword(s):  
Protein Design ◽  
Sequence Space ◽  
Protein Sequence ◽  
Protein Function ◽  
De Novo ◽  
Protein Sequences ◽  
Generative Adversarial Networks ◽  
Functional Protein ◽  
Generative Adversarial Network

ABSTRACTDe novo protein design for catalysis of any desired chemical reaction is a long standing goal in protein engineering, due to the broad spectrum of technological, scientific and medical applications. Currently, mapping protein sequence to protein function is, however, neither computationionally nor experimentally tangible 1,2. Here we developed ProteinGAN, a specialised variant of the generative adversarial network 3 that is able to ‘learn’ natural protein sequence diversity and enables the generation of functional protein sequences. ProteinGAN learns the evolutionary relationships of protein sequences directly from the complex multidimensional amino acid sequence space and creates new, highly diverse sequence variants with natural-like physical properties. Using malate dehydrogenase as a template enzyme, we show that 24% of the ProteinGAN-generated and experimentally tested sequences are soluble and display wild-type level catalytic activity in the tested conditions in vitro, even in highly mutated (>100 mutations) sequences. ProteinGAN therefore demonstrates the potential of artificial intelligence to rapidly generate highly diverse novel functional proteins within the allowed biological constraints of the sequence space.

scholarly journals De novo design of potent and resilient hACE2 decoys to neutralize SARS-CoV-2

Science ◽  
2020 ◽  
Vol 370 (6521) ◽  
pp. 1208-1214 ◽  
Author(s):  
Thomas W. Linsky ◽  
Renan Vergara ◽  
Nuria Codina ◽  
Jorgen W. Nelson ◽  
Matthew J. Walker ◽  
...  
Keyword(s):  
Protein Design ◽  
De Novo ◽  
High Specificity ◽  
Spike Protein ◽  
Host Proteins ◽  
Angiotensin Converting Enzyme 2 ◽  
Cryo Electron Microscopy ◽  
De Novo Protein Design ◽  
Single Spike

We developed a de novo protein design strategy to swiftly engineer decoys for neutralizing pathogens that exploit extracellular host proteins to infect the cell. Our pipeline allowed the design, validation, and optimization of de novo human angiotensin-converting enzyme 2 (hACE2) decoys to neutralize severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The best monovalent decoy, CTC-445.2, bound with low nanomolar affinity and high specificity to the receptor-binding domain (RBD) of the spike protein. Cryo–electron microscopy (cryo-EM) showed that the design is accurate and can simultaneously bind to all three RBDs of a single spike protein. Because the decoy replicates the spike protein target interface in hACE2, it is intrinsically resilient to viral mutational escape. A bivalent decoy, CTC-445.2d, showed ~10-fold improvement in binding. CTC-445.2d potently neutralized SARS-CoV-2 infection of cells in vitro, and a single intranasal prophylactic dose of decoy protected Syrian hamsters from a subsequent lethal SARS-CoV-2 challenge.

scholarly journals A high-quality reference genome assembly of the saltwater crocodile, Crocodylus porosus, reveals patterns of selection in Crocodylidae

2019 ◽  
Author(s):  
Arnab Ghosh ◽  
Matthew G. Johnson ◽  
Austin B. Osmanski ◽  
Swarnali Louha ◽  
Natalia J. Bayona-Vásquez ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Genome Structure ◽  
Protein Domain ◽  
Structure Evolution ◽  
Functional Protein ◽  
High Quality ◽  
Saltwater Crocodile ◽  
Crocodylus Porosus

AbstractCrocodilians are an economically, culturally, and biologically important group. To improve researchers’ ability to study genome structure, evolution, and gene regulation in the clade, we generated a high-quality de novo genome assembly of the saltwater crocodile, Crocodylus porosus, from Illumina short read data from genomic libraries and in vitro proximity-ligation libraries. The assembled genome is 2,123.5 Mb, with N50 scaffold size of 17.7 Mb and N90 scaffold size of 3.8 Mb. We then annotated this new assembly, increasing the number of annotated genes by 74%. In total, 96% of 23,242 annotated genes were associated with a functional protein domain. Furthermore, multiple non-coding functional regions and mappable genetic markers were identified. Upon analysis and overlapping the results of branch length estimation and site selection tests for detecting potential selection, we found 16 putative genes under positive selection in crocodilians, ten in C. porosus and six in A. mississippiensis. The annotated C. porosus genome will serve as an important platform for osmoregulatory, physiological and sex determination studies, as well as an important reference in investigating the phylogenetic relationships of crocodilians, birds, and other tetrapods.

scholarly journals Rosetta and the Journey to Predict Proteins’ Structures, 20 Years on

2020 ◽  
Vol 15 (6) ◽  
pp. 611-628
Author(s):  
Jad Abbass ◽  
Jean-Christophe Nebel
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Protein Design ◽  
Structure Prediction ◽  
De Novo ◽  
Protein Docking ◽  
Ligand Docking ◽  
Ancient Egyptian ◽  
Docking Protein ◽  
Prediction Approach

For two decades, Rosetta has consistently been at the forefront of protein structure prediction. While it has become a very large package comprising programs, scripts, and tools, for different types of macromolecular modelling such as ligand docking, protein-protein docking, protein design, and loop modelling, it started as the implementation of an algorithm for ab initio protein structure prediction. The term ’Rosetta’ appeared for the first time twenty years ago in the literature to describe that algorithm and its contribution to the third edition of the community wide Critical Assessment of techniques for protein Structure Prediction (CASP3). Similar to the Rosetta stone that allowed deciphering the ancient Egyptian civilisation, David Baker and his co-workers have been contributing to deciphering ’the second half of the genetic code’. Although the focus of Baker’s team has expended to de novo protein design in the past few years, Rosetta’s ‘fame’ is associated with its fragment-assembly protein structure prediction approach. Following a presentation of the main concepts underpinning its foundation, especially sequence-structure correlation and usage of fragments, we review the main stages of its developments and highlight the milestones it has achieved in terms of protein structure prediction, particularly in CASP.

Biological Assembly of Modular Protein Building Blocks as Sensing, Delivery, and Therapeutic Agents

2020 ◽  
Vol 11 (1) ◽  
pp. 35-62 ◽  
Author(s):  
Emily A. Berckman ◽  
Emily J. Hartzell ◽  
Alexander A. Mitkas ◽  
Qing Sun ◽  
Wilfred Chen
Keyword(s):  
Protein Design ◽  
Biomedical Applications ◽  
De Novo ◽  
Building Blocks ◽  
Specific Protein ◽  
Therapeutic Agents ◽  
Biological Functions ◽  
Functional Protein ◽  
Wide Range ◽  
De Novo Protein Design

Nature has evolved a wide range of strategies to create self-assembled protein nanostructures with structurally defined architectures that serve a myriad of highly specialized biological functions. With the advent of biological tools for site-specific protein modifications and de novo protein design, a wide range of customized protein nanocarriers have been created using both natural and synthetic biological building blocks to mimic these native designs for targeted biomedical applications. In this review, different design frameworks and synthetic decoration strategies for achieving these functional protein nanostructures are summarized. Key attributes of these designer protein nanostructures, their unique functions, and their impact on biosensing and therapeutic applications are discussed.

scholarly journals Resonant fluctuations of selection pressure exponentially accelerate fitness valley crossing

2022 ◽  
Author(s):  
Mario E Di Salvo ◽  
Kimberly A Reynolds ◽  
Milo M Lin
Keyword(s):  
Protein Evolution ◽  
Selection Pressure ◽  
De Novo ◽  
Pressure Fluctuations ◽  
Time Dependent ◽  
Time Varying ◽  
Fluctuating Selection ◽  
Functional Protein ◽  
Protein Size

Two functional protein sequences can sometimes be separated by a fitness valley - a series of low or non-functional intermediate mutations that must be traversed to reach a more optimal or refined function. Time-varying selection pressure modulates evolutionary sampling of such valleys. Yet, how the amplitude and frequency of fluctuating selection influence the rate of protein evolution is poorly understood. Here, we derive a simple equation for the time-dependent probability of crossing a fitness valley as a function of evolutionary parameters: valley width, protein size, mutation rate, and selection pressure. The equation predicts that, under low selection pressure, the valley crossing rate is magnified by a factor that depends exponentially on valley width. However, after a characteristic time set by the evolutionary parameters, the rate rapidly decays. Thus, there is an optimal frequency of selection-pressure fluctuations that maximizes the rate of protein optimization. This result is reminiscent of the resonance frequency in mechanical systems. The equation unites empirical and theoretical results that were previously disconnected, and is consistent with time-dependent in vitro and clinical data. More generally, these results suggest that seasonal and climate oscillations could synchronously drive protein evolution at the resonant frequency across a range of organism hosts and timescales. This theory could also be applied to optimize de novo protein evolution in laboratory directed evolution using time-varying protocols.

scholarly journals A bottom-up approach for the de novo design of functional proteins

2020 ◽  
Author(s):  
Che Yang ◽  
Fabian Sesterhenn ◽  
Jaume Bonet ◽  
Eva van Aalen ◽  
Leo Scheller ◽  
...  
Keyword(s):  
Protein Design ◽  
Mammalian Cells ◽  
De Novo ◽  
Protein Structures ◽  
Functional Protein ◽  
Regular Secondary Structure ◽  
Bottom Up ◽  
Binding Motifs ◽  
Wide Range ◽  
Novel Protein

AbstractDe novo protein design has enabled the creation of novel protein structures. To design novel functional proteins, state-of-the-art approaches use natural proteins or first design protein scaffolds that subsequently serve as templates for the transplantation of functional motifs. In these approaches, the templates are function-agnostic and motifs have been limited to those with regular secondary structure. Here, we present a bottom-up approach to build de novo proteins tailored to structurally complex functional motifs. We applied a bottom-up strategy to design scaffolds for four different binding motifs, including one bi-functionalized protein with two motifs. The de novo proteins were functional as biosensors to quantify epitope-specific antibody responses and as orthogonal ligands to activate a signaling pathway in engineered mammalian cells. Altogether, we present a versatile strategy for the bottom-up design of functional proteins, applicable to a wide range of functional protein design challenges.

scholarly journals Precision design of single and multi-heme de novo proteins

2020 ◽  
Author(s):  
George H. Hutchins ◽  
Claire E. M. Noble ◽  
Hector Blackburn ◽  
Ben Hardy ◽  
Charles Landau ◽  
...  
Keyword(s):  
Crystal Structure ◽  
De Novo ◽  
Molten Globule ◽  
Computational Design ◽  
Binding Pocket ◽  
Oxygen Binding ◽  
Heme Binding ◽  
Functional Protein ◽  
Precision Design ◽  
Protein Functions

AbstractThe de novo design of simplified porphyrin-binding helical bundles is a versatile approach for the construction of valuable biomolecular tools to both understand and enhance protein functions such as electron transfer, oxygen binding and catalysis. However, the methods utilised to design such proteins by packing hydrophobic side chains into a buried binding pocket for ligands such as heme have typically created highly flexible, molten globule-like structures, which are not amenable to structural determination, hindering precise engineering of subsequent designs. Here we report the crystal structure of a de novo two-heme binding “maquette” protein, 4D2, derived from the previously designed D2 peptide, offering new opportunities for computational design and re-engineering. The 4D2 structure was used as a basis to create a range of heme binding proteins which retain the architecture and stability of the initial crystal structure. A well-structured single-heme binding variant was constructed by computational sequence redesign of the hydrophobic protein core, assessed by NMR, and utilised for experimental validation of computational redox prediction and design. The structure was also extended into a four-heme binding helical bundle resembling a molecular wire. Despite a molecular weight of only 24kDa, imaging by CryoEM illustrated a remarkable level of detail in this structure, indicating the positioning of both the secondary structure and the heme cofactors. The design and determination of atomic-level resolution in such de novo proteins is an invaluable resource for the continued development of novel and functional protein tools.

Sign in / Sign up

Export Citation Format

Share Document