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Biology subjects

Sankaran, B.

Publications and source records attributed to Sankaran, B..

At least 19 recordsLinked to original sources

Programmable De Novo Design of Mesoporous Protein Crystal Frameworks

Three-dimensional protein crystals are ordered, porous macroscopic materials with potential applications in catalysis, biosensing, and biomedicine. However, most protein crystals are obtained by empirical screening, providing limited control over the lattice architecture, pore geometry or component composition that determine material function. Here, we present a modular strategy for the programmable design of highly porous, framework-like protein crystals using predefined protein-protein interactions. This strategy yielded over 30 distinct protein crystals, including single-component and multicomponent P213 and I213 lattices that grow to over 100 micrometers in size. Small-angle X-ray scattering and electron microscopy showed close agreement between experimental lattices and computational models. RFdiffusion-guided design generated isomorphous variants with matched lattice parameters, enabling coherent protein crystal alloys, epitaxial core-shell growth and reversible shell assembly. The designed crystals exhibit tunable mesoporous architectures, with limiting apertures of 2-18 nm, and support genetically encoded incorporation of fluorescent protein guests. These results establish a general route to programmable lattice engineering of protein crystals and position them as genetically encoded, compositionally tunable mesoporous materials.

synthetic biology↗

De novo design of autocatalytically forming intra- and intermolecular isopeptide bonds to construct rigid covalent protein assemblies

Isopeptide bonds are amide bonds between amino acid side chains that can form autocatalytically, notably in the pili of Gram-positive bacteria. Here, we design de novo proteins that form both intramolecular and intermolecular isopeptide bonds entirely autocatalytically. We report over 50 designs that form isopeptide bonds, validated by mass spectrometry and 5 crystal structures. We redesign these constructs as split proteins that form a covalent intermolecular isopeptide crosslink when combined. These split designs are orthogonal to the existing isopeptide-based SpyTag/Catcher system, and their formation can be regulated by temperature, providing control over the timing of crosslinking in protein assemblies. We extend these designs to create rigid domain crosslinks that enable the construction of large well ordered symmetric rings of up to 215 kDa that are irreversibly covalently crosslinked by multiple isopeptide bonds into a single molecule. Our results provide insight into the determinants of isopeptide bond formation, considerably expand the set of isopeptide bond crosslinking systems, and establish a framework to construct fully covalent rigid protein assemblies.

biophysics↗

Computational design of membrane fusion proteins

The fusion of two distinct biological membranes is an evolutionarily conserved process essential to cellular organization and physiology. Membrane fusion is driven by the refolding of fusogenic proteins into low-energy postfusion states that overcome the energetic barrier to bilayer merger. Here we report a computational method for the design of synthetic fusogens inspired by the architecture of the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex. Using machine learning-guided protein design to extensively remodel backbone geometry and sequence, we generated heterodimeric SNARE-like assemblies that efficiently catalyze cell-cell membrane fusion. These minimal two-component fusogens exhibit substantially higher fusion activity than native multisubunit SNARE complexes. Structural and functional analyses identify the key determinants required for fusogenic activity and reveal a modularity that enables control of fusion through chemically induced heterodimerization. In addition to cell-cell fusion, the synthetic fusogens drive fusion between endoplasmic reticulum and mitochondrial membranes from human cells, demonstrating their potential as tools for programmable manipulation of intracellular membranes. Together, these results establish a general framework for the rational design of synthetic fusogens and expand the toolkit for engineering membrane dynamics in living systems.

biochemistry↗

A Hidden Binding Pocket in the β- ketoacyl-ACP Synthase FabB

Assembly-line enzymes carry out multi-step synthesis of diverse metabolites by using a handful of catalytic motifs in which minor structural differences control substrate specificity and reaction order. Here we examine differences in substrate binding to FabB and FabF, the two {beta}-ketoacyl-ACP synthases (KSs) responsible for fatty acid elongation in Escherichia coli, by exploring a peculiar mutational effect. In FabB, a blocking mutation in the acyl binding pocket yields a shifted, but broad product profile, while in FabF, the same mutation disrupts the binding of acyl chains longer than eight carbons (C8). X-ray crystal structures of the FabB mutant provide an explanation: a second, previously unobserved binding pocket allows medium-to-long acyl chains ([≥] C8) to bind with an alternate conformation. Molecular simulations suggest that this pocket is more stable in FabB than in FabF, where mutations reduce the catalytic competency of longer chains instead of shifting them to the alternate pocket. Our findings indicate that homologous KSs differ not only in their primary binding sites but also in the availability of alternative binding modes that can buffer against mutational effects and enable functional diversification.

biochemistry↗

De novo design of protein nanoparticles with integrated functional motifs

Computational design of self-assembling proteins has long relied on pre-existing structures and sequences, fundamentally limiting control over their structural and functional properties. Recent machine learning-based methods have transformed our ability to design functional small de novo proteins and oligomers, yet methods to design large de novo protein assemblies with structures tailored to specific applications are still underexplored. Here, we develop a generalizable method for designing de novo symmetric protein complexes that incorporate target functional motifs into their structures. We report 34 new protein nanoparticles that form on-target assemblies with cubic point group symmetries. The nanoparticles exhibit a wide variety of backbones that were designed with atom-level accuracy, as evidenced by several cryo-EM and crystal structures that reveal minimal deviations from the design models. We use the method to generate a de novo antigen-tailored nanoparticle vaccine that elicits robust immune responses in mice. These results establish a generalizable approach that can be used to design functional self-assembling protein complexes with structures tailored to specific applications.

biochemistry↗

A Sequence Motif Enables Widespread Use of Non-Canonical Redox Cofactors in Natural Enzymes

Non-canonical redox cofactors (NRCs) are promising alternatives to nicotinamide adenine dinucleotide (phosphate) (NAD(P)+) for biomanufacturing due to low cost and exquisite electron delivery control, yet their adoption is limited by the scarcity of compatible enzymes. Here, we screened the aldehyde dehydrogenase (ALDH) protein family and identified a conserved RH/QxxR sequence motif that enables widespread NRC activity among natural enzymes. Bos taurus ALDH3a1 and Pseudanabaena biceps ALDH exhibit unprecedented turnover with nicotinamide mononucleotide (NMN+), with kcat values matching or exceeding that of NAD+ and surpassing most engineered NRC-active enzymes by 10 to 105-fold, based on the relative NRC to native activity. Structural and dynamic analyses reveal this motif reinforces cofactor positioning and pre-organizes the active site without dependence on the adenosine monophosphate moiety of NAD+. When introduced into diverse ALDH scaffolds, the RH/QxxR motif enhances NMN+ activity up to 60-fold. In addition to NMN+, this motif also supports activity across multiple non-nucleotide, simple synthetic NRCs such as 1-(2-carbamoylmethyl)nicotinamide (AmNA+). These findings elucidate Natures solution to the engineering challenge of obtaining NRC-active enzymes and offers a blueprint to mine latent evolutionary plasticity in natural enzymes that serve as superior engineering starting points.

synthetic biology↗

Designed NGF mimetics with reduced nociceptive signatures in neurons

The clinical use of Nerve Growth Factor (NGF) for neuronal regeneration has been hampered by pain sensitization side effects. NGF signals through the receptor tyrosine kinase TrkA and the co-receptor p75NTR; pain sensitization is thought to involve p75NTR. We sought to overcome this limitation by de novo design of a TrkA agonist that does not bind p75NTR. We designed homodimeric TrkA engaging constructs that dimerize TrkA subunits in a variety of geometries, and identified those eliciting the strongest signaling. The resulting designed agonists are able to stimulate transdifferentiated neurons and neuroblastoma cell lines, leading to neurite outgrowth and neuronal differentiation, with considerably reduced transcription of inflammation and pain related genes. These agonists are promising candidates for promoting neuronal regeneration without adverse side effects. HighlightsO_LIDe novo designed TrkA agonists activate MAPK and PI3K-AKT signaling C_LIO_LIRigid fusions allow for highly tunable signaling signatures C_LIO_LITrkA agonists lead to neurite outgrowth in neuroblastoma cells comparable to retinoic acid C_LIO_LIModulation of the TrkA pathway without co-stimulating p75NTR leads to a downregulation of inflammatory and nociceptive signature in neurons. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/648806v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@c48066org.highwire.dtl.DTLVardef@c9c5a7org.highwire.dtl.DTLVardef@cf8ebdorg.highwire.dtl.DTLVardef@a4345a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

Inhibition of ice recrystallization with designed twistless helical repeat proteins

Given the repetitive structure of crystalline ice, its unsurprising that highly active ice-binding proteins, often with beta-roll structures, also have repeating motifs. Here, we introduce a de novo designed family of ice-binding twistless alpha-helical repeat (iTHR) proteins. Each iTHR protein comprises two planar layers of parallel alpha-helices connected by loops--a structural topology not seen in native ice-binding proteins. The ice-binding helices feature an ordered array of TXXXAXXXAXX motifs, spaced to match the pyramidal {201} and secondary prism plane {110} ice lattice facets, and engineered with a 98.2{degrees} turn angle per residue to orient threonines uniformly towards the ice surface. iTHR proteins show high solubility, thermostability, and produce varied ice crystal morphologies depending on their intended target facet. Crucially, iTHRs exhibit ice recrystallization inhibition (IRI) at critical concentrations comparable to those of many native globular ice-binding proteins. Extensive site-specific mutagenesis shows that ice-binding activity in iTHR proteins is robust, remaining largely unaffected by changes in chemical composition. Variation in the repeat number reveals a non-monotonic relationship to IRI activity. X-ray crystal structures of two designs confirm the intended orientation of threonines, uniformly pointing toward the ice surface. The iTHR family provides a versatile platform to systematically investigate the complex structure-activity relationships underlying protein-ice interactions.

biophysics↗

Massively parallel assessment of designed protein solution properties using mass spectrometry and peptide barcoding

Library screening and selection methods can determine the binding activities of individual members of large protein libraries given a physical link between protein and nucleotide sequence, which enables identification of functional molecules by DNA sequencing. However, the solution properties of individual protein molecules cannot be probed using such approaches because they are completely altered by DNA attachment. Mass spectrometry enables parallel evaluation of protein properties amenable to physical fractionation such as solubility and oligomeric state, but current approaches are limited to libraries of 1,000 or fewer proteins. Here, we improved mass spectrometry barcoding by co-synthesizing proteins with barcodes optimized to be highly multiplexable and minimally perturbative, scaling to libraries of >5,000 proteins. We use these barcodes together with mass spectrometry to assay the solution behavior of libraries of de novo-designed monomeric scaffolds, oligomers, binding proteins and nanocages, rapidly identifying design failure modes and successes.

biochemistry↗

Design of facilitated dissociation enables control over cytokine signaling duration

Protein design has focused primarily on the design of ground states, ensuring they are sufficiently low energy to be highly populated1. Designing the kinetics and dynamics of a system requires, in addition, the design of excited states that are traversed in transitions from one low-lying state to another2,3. This is a challenging task as such states must be sufficiently strained to be poorly populated, but not so strained that they are not populated at all, and because protein design methods have generally focused on creating near-ideal structures4-7. Here we describe a general approach for designing systems which use an induced-fit power stroke8 to generate a structurally frustrated9 and strained excited state, allosterically driving protein complex dissociation. X-ray crystallography, double electron-electron resonance spectroscopy, and kinetic binding measurements demonstrate that incorporating excited states enables design of effector-induced increases in dissociation rates as high as 6000-fold. We highlight the power of this approach by designing cytokine mimics which can be dissociated within seconds from their receptors.

biochemistry↗

Conformational flexibility is a critical factor in designing broad-spectrum human norovirus protease inhibitors

Human norovirus (HuNoV) infection is a global health and economic burden. Currently, there are no licensed HuNoV vaccines or antiviral drugs available. The protease encoded by the HuNoV genome plays a critical role in virus replication by cleaving the polyprotein and is, therefore, an excellent target for developing small molecule inhibitors. While rupintrivir, a potent small-molecule inhibitor of several picornavirus proteases, effectively inhibits GI.1 protease, it is an order of magnitude less effective against GII protease. Other GI.1 protease inhibitors also tend to be less effective against GII proteases. To understand the structural basis for the potency difference, we determined the crystal structures of proteases of GI.1, pandemic GII.4 (Houston and Sydney), and GII.3 in complex with rupintrivir. These structures show that the open substrate pocket in GI protease binds rupintrivir without requiring significant conformational changes, whereas, in GII proteases, the closed pocket flexibly extends, reorienting arginine-112 in the BII-CII loop to accommodate rupintrivir. Structures of R112A protease mutants with rupintrivir, coupled with enzymatic and inhibition studies, suggest R112 is involved in displacing both substrate and ligands from the active site, implying a role in the release of cleaved products during polyprotein processing. Thus, the primary determinant for differential inhibitor potency between the GI and GII proteases is the increased flexibility in the BII-CII loop of the GII proteases caused by H-G mutation in this loop. Therefore, the inherent flexibility of the BII-CII loop in GII proteases is a critical factor to consider when developing broad-spectrum inhibitors for HuNoV proteases. IMPORTANCEHuman noroviruses are a significant cause of sporadic and epidemic gastroenteritis worldwide. There are no vaccines or antiviral drugs currently available to treat infections. Our work elucidates the structural differences between GI.1 and GII proteases in response to inhibitor binding and will inform the future development of broad-spectrum norovirus protease inhibitors.

biochemistry↗

Computational design of serine hydrolases

Enzymes that proceed through multistep reaction mechanisms often utilize complex, polar active sites positioned with sub-angstrom precision to mediate distinct chemical steps, which makes their de novo construction extremely challenging. We sought to overcome this challenge using the classic catalytic triad and oxyanion hole of serine hydrolases as a model system. We used RFdiffusion1 to generate proteins housing catalytic sites of increasing complexity and varying geometry, and a newly developed ensemble generation method called ChemNet to assess active site geometry and preorganization at each step of the reaction. Experimental characterization revealed novel serine hydrolases that catalyze ester hydrolysis with catalytic efficiencies (kcat/Km) up to 3.8 x 103 M-1 s-1, closely match the design models (C RMSDs < 1 [A]), and have folds distinct from natural serine hydrolases. In silico selection of designs based on active site preorganization across the reaction coordinate considerably increased success rates, enabling identification of new catalysts in screens of as few as 20 designs. Our de novo buildup approach provides insight into the geometric determinants of catalysis that complements what can be obtained from structural and mutational studies of native enzymes (in which catalytic group geometry and active site makeup cannot be so systematically varied), and provides a roadmap for the design of industrially relevant serine hydrolases and, more generally, for designing complex enzymes that catalyze multi-step transformations.

biochemistry↗

The structural and biophysical basis of substrate binding to the hydrophobic groove in Ubiquilin Sti1 domains

Ubiquilins are molecular chaperones that play multifaceted roles in proteostasis, with point mutations in UBQLN2 leading to altered phase separation properties and Amyotrophic Lateral Sclerosis (ALS). Our mechanistic understanding of this essential process has been hindered by a lack of structural information on the Sti1 domain, which is essential for Ubiquilin chaperone activity and phase separation. Here, we present the first crystal structure of a Ubiquilin family Sti1 domain bound to a transmembrane domain (TMD) and show that ALS mutations disrupt the Sti1-TMD interaction. We then demonstrate that Ubiquilins contain multiple conserved, internal sequences that bind to the Sti1 domain, including the PXX region which is a hotspot for ALS mutations. We propose that these placeholder sequences prevent solvent exposure of the Sti1 hydrophobic groove and contribute to the multivalency that drives Ubiquilin phase separation. Together, this work provides a new paradigm for understanding how Sti1 domains modulate Ubiquilin chaperone activity and phase separation and offer insights into the molecular basis of ALS pathogenesis.

biochemistry↗

Sculpting conducting nanopore size and shape through de novo protein design

Transmembrane {beta}-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 novo protein 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 {beta}-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 of de novo designed TMBs with 10, 12 and 14 stranded {beta}-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 {beta}-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.

synthetic biology↗

Improving protein expression, stability, and function with ProteinMPNN

Natural proteins are highly optimized for function, but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here we show that the deep neural network ProteinMPNN together with evolutionary and structural information provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.

biochemistry↗

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN

The design of novel protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. A new generation of deep learning methods promises to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

biochemistry↗

Structure of Orthoreovirus RNA Chaperone σNS, a Component of Viral Replication Factories

The reovirus {sigma}NS RNA-binding protein is required for formation of intracellular compartments during viral infection that support viral genome replication and capsid assembly. Despite its functional importance, a mechanistic understanding of {sigma}NS is lacking. We conducted structural and biochemical analyses of an R6A mutant of {sigma}NS that forms dimers instead of the higher-order oligomers formed by wildtype (WT) {sigma}NS. The crystal structure of selenomethionine-substituted {sigma}NS-R6A reveals that the mutant protein forms a stable antiparallel dimer, with each subunit having a well-folded central core and a projecting N-terminal arm. The dimers interact with each other by inserting the N-terminal arms into a hydrophobic pocket of the neighboring dimers on either side to form a helical assembly that resembles filaments of WT {sigma}NS in complex with RNA observed using cryo-EM. The interior of the crystallographic helical assembly is positively charged and of appropriate diameter to bind RNA. The helical assembly is disrupted by bile acids, which bind to the same hydrophobic pocket as the N-terminal arm, as demonstrated in the crystal structure of {sigma}NS-R6A in complex with bile acid. This finding suggests that the N-terminal arm functions in conferring context-dependent oligomeric states of {sigma}NS, which is supported by the structure of {sigma}NS lacking the N-terminal arm. We discovered that {sigma}NS displays RNA helix destabilizing and annealing activities, likely essential for presenting mRNA to the viral RNA-dependent RNA polymerase for genome replication. The RNA chaperone activity is reduced by bile acids and abolished by N-terminal arm deletion, suggesting that the activity requires formation of {sigma}NS oligomers. Our studies provide structural and mechanistic insights into the function of {sigma}NS in reovirus replication.

biochemistry↗

Blueprinting expandable nanomaterials with standardized protein building blocks

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies in comparison has been much more complex, largely due to the irregular shapes of protein structures1. Here we describe extendable linear, curved, and angled protein building blocks, as well as inter-block interactions that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight "train track" assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence-structure relationships, it has not been previously possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank 3D canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to "back of an envelope" architectural blueprints.

biochemistry↗