Biology subjects

Bera, A.

Publications and source records attributed to Bera, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Programming N-linked glycan composition through de novo protein design

N-linked glycans are ubiquitous post-translational modifications that mediate diverse biological processes, including cell signaling and adhesion, molecular recognition, and host-pathogen interactions. Despite their importance, N-linked glycans have largely remained beyond the reach of biomolecular design due to a lack of methods capable of jointly modeling glycans and protein structure. Here, we develop a general all-atom computational pipeline for creating de novo glycoproteins in which the amino acid sequence encodes both the location and composition of N-linked glycans. The method uses three-dimensional protein structure to tune glycan accessibility to processing enzymes in the eukaryotic secretory pathway. Systematic increases in steric restriction progressively reduced processing, shifting glycans from heterogeneous complex-type structures toward increasingly underprocessed oligomannose-type species resembling those found on many viral glycoproteins. Despite this programmed restriction, the resulting oligomannose glycans remained accessible for biological recognition, inhibiting uropathogenic Escherichia coli adhesion to human bladder cells and binding mannose-binding lectin. These results establish steric control of N-glycan processing as a genetically encodable design principle and extend computational protein design to functional glycoproteins with programmed composition.

biochemistry↗

bioRxiv2026

Complex enzyme active site scaffolding by iteratively detuned catalytic guidance

De novo enzyme design requires sequences whose structures reproduce prescribed catalytic geometries. This remains challenging for active sites that couple multiple catalytic residues, cofactors and substrates. Here we introduce the Catalytic Guidance Engine (CaGE), which optimizes designed sequences to satisfy complex sets of functional constraints by alternating constraint guided structure prediction trajectories with sequence design, gradually fading the strength of the constraint information over cycles to nudge the designed sequence towards satisfying all the constraints. We train RF3 to accept atom-pair distances and other design conditions, and use classifier-free guidance to fade their influence over multiple design cycles. We also develop training-free motif guidance protocols which operate at inference time by directly adjusting selected atoms towards the design target geometry during diffusion sampling. CaGE improves catalytic-motif geometry across a diverse enzyme benchmark and yields sequences that recover complex target active sites in independent AF3 predictions. We experimentally demonstrate the power of CaGE by designing active enzymes with complex catalytic sites: a nonheme-iron design positions four active-site residues around an iron centre and a transition-state ligand, and a PLP-dependent design positions four catalytic residues around a PLP cofactor with multiple functional groups. Active site substitutions and a 2.7[A] crystal structure support the designed mechanisms and structures. Thus, CaGE provides a route to functional de novo enzymes with complex active sites.

bioengineering↗

bioRxiv2026

Generative design of programmable asymmetric β-barrel nanopores

Protein nanopores are powerful tools for molecular sensing, sequencing, and separation, but designing pores with programmable function remains challenging. Native homo-oligomeric transmembrane {beta} barrels (TMBs) are used for these applications, but their uniform lumens limit spatial resolution and analyte discrimination. Although monomeric TMBs can be designed using energy-based methods, these approaches remain highly manual and limited to structural design rather than function. Here, we present a generative AI framework for TMB design, with backbone and sequence design models trained on a curated distillation set. We characterized 48 designs spanning 0.7-1.5 nm in diameter, diverse lumen chemistries, and hydrophobic thicknesses. Crystal structures closely match the design models. We demonstrate that our method produces customizable nanopores for ion sensing, DNA translocation, and transport across polymer membranes.

biochemistry↗

bioRxiv2026

Genomic rDNA instabilities in Arabidopsis epigenetic mutants alter location-based rRNA gene expression patterns

The model plant species Arabidopsis thaliana has two nucleolus organizer regions (NORs), each consisting of tandem repeats of 45S rRNA genes on chromosomes 2 (NOR2) and 4 (NOR4). In the ecotype Col-0, the rRNA gene subtypes mapping to NOR2 are mostly silenced during development, whereas those mapping to NOR4 are mostly active. Using molecular and genetic mapping approaches, we demonstrate in multiple epigenetic mutants the occurrence of NOR conversions involving loss of rDNA and the associated telomeres in one NOR and replacement of the lost sequences with the corresponding sequences from the other NOR. We studied mutants of evolutionarily conserved chromatin remodelers DECREASE IN DNA METHYLATION 1 (DDM1) and CHROMATIN ASSEMBLY FACTOR 1 (CAF-1), and plant-specific CHROMOMETHYLASE 2 (CMT2) DNA methyltransferase. We observed NOR conversions in ddm1 and caf-1 mutants, where such NOR conversions altered the rRNA variant expression patterns, which often confound the data pertaining to release of rRNA gene silencing. We delineated the effects of these mutations on the rDNA instability-mediated alterations in rRNA variant expression from their effects on the actual release of rRNA gene silencing. We also show that these mutations release rRNA gene silencing independently of their effect on rDNA genomic instability involving NOR conversions.

plant biology↗

bioRxiv2025

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↗

bioRxiv2025

Structural insights into the mechanism of C3 side chain fragmentation in cephalosporins with SME-1 class A carbapenemase

Cephalosporins remain one of the largest classes of antibiotics used clinically, with a diverse group of dual substituents at C3 and C7 positions. The fragmentation of the C-3 side chain from the C3 position after hydrolysis by Serine or metallo-{beta} lactamase leaving an exo-methylene group has been introduced in the literature recently, but the exact mechnism by which it happens remains unclear until now. Our incrystallo findings suggest that the fragmentation of the C3 side chain will depend on the C3 atom and its hybridization state. A C3 carbon with sp2 hybridization will not allow fragmentation, but a sp3 hybridized carbon will facilitate the detachment of the side chain. Furthermore, heteroatoms like Sulfur, on C3 position, bearing vacant d-orbitals participate in {pi}-cloud delocalization, making the detachment of C3 side chain energetically unfeasible. For the sp3 hybridized carbon at C3, the fragmentation of the bond was independent of the C3 atom. We observed fragmentation of the C3-C3 bond for all three heteroatoms, Nitrogen, Oxygen, and sulfur, at the C3 position. We validated our crystallographic findings with mass spectrometry to confirm the fragmentation of the C3 side chain in sp3 carbon and the unfragmented side chain in sp2 carbon and sulfur at C3 position. QM/MM simulations on three types of enzyme-cephalosporin complexes with different C3 side chains confirm the mechanism of fragmentation. Beyond revealing C3 side chain fragmentation in cephalosporins, useful for inhibitor and diagnostic design, our QM/MM methods are useful on incrystallo complexes to show the enzyme catalysis.

biochemistry↗

bioRxiv2025

De novo design of high-affinity miniprotein binders targeting Francisella tularensis virulence factor

Francisella tularensis poses considerable public health risk due to its high infectivity and potential for bioterrorism. Francisella-like lipoprotein (Flpp3), a key virulence factor unique to Francisella, plays critical roles in infection and immune evasion, making it a promising target for therapeutic development. However, the lack of well-defined binding pockets and structural information on native interactions has hindered structure-guided ligand discovery against Flpp3. Here, we used a combination of physics-based and deep-learning methods to design high-affinity miniprotein binders targeting two distinct sites on Flpp3. We identified four binders for site I with binding affinities ranging between 24-110 nM. For the second site, an initial binder showed a dissociation constant (KD) of 81 nM, and subsequent site saturation mutagenesis yielded variants with sub-nanomolar affinities. Circular dichroism confirmed the topology of designed miniproteins. The X-ray crystal structure of Flpp3 in complex with a site I binder is nearly identical to the design model (C root-mean-square deviation: 0.9 [A]). These designed miniproteins provide research tools to explore the roles of Flpp3 in tularemia and should enable the development of new therapeutic candidates.

biochemistry↗

bioRxiv2025

Tubulin isotypes contribute opposing properties to balance anaphase spindle morphogenesis

Faithful chromosome segregation requires proper function of the mitotic spindle, which is built from, and depends on, the coordinated regulation of many microtubules and the activities of molecular motors and MAPs. In addition, microtubules themselves are assembled from multiple variants, or isotypes of - and {beta}-tubulin, yet whether they mediate the activities of motors and MAPs required for proper spindle function remains poorly understood. Here, we use budding yeast to reveal that -tubulin isotypes regulate opposing outward- and inward-directed forces in the spindle midzone that facilitate optimal spindle elongation and length control. Moreover, we show that the isotypes mediate balanced spindle forces by differentially localizing the antagonistic force generators Cin8 (kinesin-5) and Kar3 (kinesin-14) to interpolar microtubules. Our results reveal new roles for tubulin isotypes in orchestrating motor and MAP activities and provide insights into how forces in the spindle are properly calibrated to ensure proper mitotic spindle morphogenesis.

cell biology↗

bioRxiv2025

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↗

bioRxiv2025

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↗

bioRxiv2024

Accurate de novo design of high-affinity protein binding macrocycles using deep learning

The development of macrocyclic binders to therapeutic proteins typically relies on large-scale screening methods that are resource-intensive and provide little control over binding mode. Despite considerable progress in physics-based methods for peptide design and deep-learning methods for protein design, there are currently no robust approaches for de novo design of protein-binding macrocycles. Here, we introduce RFpeptides, a denoising diffusion-based pipeline for designing macrocyclic peptide binders against protein targets of interest. We test 20 or fewer designed macrocycles against each of four diverse proteins and obtain medium to high-affinity binders against all selected targets. Designs against MCL1 and MDM2 demonstrate KD between 1-10 M, and the best anti-GABARAP macrocycle binds with a KD of 6 nM and a sub-nanomolar IC50 in vitro. For one of the targets, RbtA, we obtain a high-affinity binder with KD < 10 nM despite starting from the target sequence alone due to the lack of an experimentally determined target structure. X-ray structures determined for macrocycle-bound MCL1, GABARAP, and RbtA complexes match very closely with the computational design models, with three out of the four structures demonstrating Ca RMSD of less than 1.5 [A] to the design models. In contrast to library screening approaches for which determining binding mode can be a major bottleneck, the binding modes of RFpeptides-generated macrocycles are known by design, which should greatly facilitate downstream optimization. RFpeptides thus provides a powerful framework for rapid and custom design of macrocyclic peptides for diagnostic and therapeutic applications.

biochemistry↗

bioRxiv2024

Controlling semiconductor growth with structured de novo protein interfaces

Protein design now enables the precise arrangement of atoms on the nanometer length scales of inorganic crystal nuclei, opening up the possibility of templating the growth of metal oxides including semiconductors. We designed proteins presenting regularly repeating interfaces containing functional groups that organize ions and water molecules, and characterized their ability to bind to and template metal oxides. Two interfaces promoted the growth of hematite under conditions that otherwise resulted in the formation of magnetite. Three interfaces promoted ZnO nucleation under conditions where traditional ZnO-binding peptides and control proteins were ineffective. Designed cyclic assemblies with these ZnO nucleating interfaces lining interior cavities promoted ZnO growth within the cavity. CryoEM analysis of a designed octahedral nanocage revealed atomic density likely corresponding to the growing ZnO directly adjacent to the designed nucleation promoting interfaces. These findings demonstrate that designed proteins can direct the formation of metal oxides not observed in biological systems, opening the door to protein-semiconductor hybrid materials. One Sentence SummaryWe describe the design of structured protein interfaces that bind to, promote, and localize the growth of zinc oxide and hematite, inorganic materials which are not found in biological systems.

bioengineering↗

bioRxiv2024

Design of High Affinity Binders to Convex Protein Target Sites

While there has been progress in the de novo design of small globular miniproteins (50-65 residues) to bind to primarily concave regions of a target protein surface, computational design of minibinders to convex binding sites remains an outstanding challenge due to low level of overall shape complementarity. Here, we describe a general approach to generate computationally designed proteins which bind to convex target sites that employ geometrically matching concave scaffolds. We used this approach to design proteins binding to TGF{beta}RII, CTLA-4 and PD-L1 which following experimental optimization have low nanomolar to picomolar affinities and potent biological activity. Co-crystal structures of the TGF{beta}RII and CTLA-4 binders in complex with the receptors are in close agreement with the design models. Our approach provides a general route to generating very high affinity binders to convex protein target sites.

biochemistry↗

bioRxiv2023

Small-molecule binding and sensing with a designed protein family

Despite transformative advances in protein design with deep learning, the design of small-molecule-binding proteins and sensors for arbitrary ligands remains a grand challenge. Here we combine deep learning and physics-based methods to generate a family of proteins with diverse and designable pocket geometries, which we employ to computationally design binders for six chemically and structurally distinct small-molecule targets. Biophysical characterization of the designed binders revealed nanomolar to low micromolar binding affinities and atomic-level design accuracy. The bound ligands are exposed at one edge of the binding pocket, enabling the de novo design of chemically induced dimerization (CID) systems; we take advantage of this to create a biosensor with nanomolar sensitivity for cortisol. Our approach provides a general method to design proteins that bind and sense small molecules for a wide range of analytical, environmental, and biomedical applications.

biochemistry↗

bioRxiv2022

De novo designed ice-binding proteins from twist-constrained helices

Attaining molecular-level control over solidification processes is a crucial aspect of materials science. To control ice formation, organisms have evolved bewildering arrays of ice-binding proteins (IBPs) but these have poorly understood structure-activity relationships. We propose that reverse engineering using de novo computational protein design can shed light on structureactivity relationships of IBPs. We hypothesized that the model alpha-helical winter flounder antifreeze protein (wfAFP) uses an unusual under-twisting of its alpha-helix to align its putative ice-binding threonine residues in exactly the same direction. We test this hypothesis by designing a series of straight three-helix bundles with an ice-binding helix projecting threonines and two supporting helices constraining the twist of the ice-binding helix. We find that ice recrystallization inhibition by the designed proteins increases with the degree of designed under-twisting, thus validating our hypothesis and opening up new avenues for the computational design of icebinding proteins. Significance StatementIce-binding proteins (IBPs) modulate ice nucleation and growth in cold-adapted organisms so that they can survive in ice-laden environments at (sub)freezing temperatures. The functional repertoire of IBPs is diverse, ranging from inhibition of recrystallization and freezing point depression to shaping of ice crystals and ice nucleation. Precisely how these activities arise from the structure and ice-binding properties of IBPs is poorly understood. We demonstrate through de novo computational protein design that constraining the twist of an ice-binding helix is a key feature determining its ice-binding activity, opening new avenues for the design of synthetic IBPs with activities tailored to the requirements of specific applications, such as cell and tissue cryopreservation.

bioengineering↗

bioRxiv2022

Robust deep learning based protein sequence design using ProteinMPNN

While deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here we describe a deep learning based protein sequence design method, ProteinMPNN, with outstanding performance in both in silico and experimental tests. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4%, compared to 32.9% for Rosetta. Incorporation of noise during training improves sequence recovery on protein structure models, and produces sequences which more robustly encode their structures as assessed using structure prediction algorithms. We demonstrate the broad utility and high accuracy of ProteinMPNN using X-ray crystallography, cryoEM and functional studies by rescuing previously failed designs, made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target binding proteins. One-sentence summaryA deep learning based protein sequence design method is described that is widely applicable to current design challenges and shows outstanding performance in both in silico and experimental tests.

biophysics↗

bioRxiv2022

Optimization of the precursor supply for an enhanced FK-506 production in Streptomyces tsukubaensis

Tacrolimus (FK-506) is a macrolide widely used as immunosuppressant to prevent transplant rejection. Synthetic production of FK-506 is not efficient and costly, whereas the biosynthesis of FK-506 is complex and the level produced by the wild type strain, Streptomyces tsukubaensis, is very low. We therefore engineered FK-506 biosynthesis and the supply of the precursor L-lysine to generate strains with improved FK-506 yield. To increase FK-506 production, first the intracellular supply of the essential precursor lysine was improved in the native host S. tsukubaensis by engineering the lysine biosynthetic pathway. Therefore, a feedback deregulated aspartate kinase AskSt* of S. tsukubaensis was generated by site directed mutagenesis. Whereas overexpression of AskSt* resulted only in a 17% increase in FK-506 yield, heterologous overexpression of a feedback deregulated AskCg* from Corynebacterium glutamicum was proven to be more efficient. Combined overexpression of AskCg* and DapASt, showed a strong enhancement of the intracellular lysine pool following increase in the yield by approximately 73% compared to the wild type. Lysine is coverted into the FK-506 building block pipecolate by the lysine cyclodeaminase FkbL. Construction of a {Delta}fkbL mutant led to a complete abolishment of the FK-506 production, confirming the indispensability of this enzyme for FK-506 production. Chemical complementation of the {Delta}fkbL mutant by feeding pipecolic acid and genetic complementation with fkbL as well as with other lysine cyclodeaminase genes (pipAf, pipASt, originating from Actinoplanes friuliensis and Streptomyces pristinaespiralis, respectively) completely restored FK-506 production. Subsequently, FK-506 production was enchanced by heterologous overexpression of PipAf and PipASp in S. tsukubaensis. This resulted in a yield increase by 65% compared to the WT in the presence of PipAf from A. friuliensis. For further rational yield improvement, the crystal structure of PipAf from A. friuliensis was determined at 1.3 [A] resolution with the cofactor NADH bound and at 1.4 [A] with its substrate lysine. Based on the structure the Ile91 residue was replaced by Val91 in PipAf, which resulted in an overall increase of FK-506 production by approx. 100% compared to the WT.

bioengineering↗

bioRxiv2021

MK2 Expression Promotes Non-Small Cell Lung Cancer Cell Death and Predicts Survival

Non-small cell lung cancers demonstrate intrinsic resistance to cell death even in response to chemotherapy. Previous work suggested that defective nuclear translocation of active caspase 3 may play a role in resistance to cell death. Separately, our group has identified that mitogen activated protein kinase activated protein kinase 2 (MK2) is required for nuclear translocation of active caspase 3 in the execution of apoptosis. This study demonstrates a relatively low expression of MK2 in non-small cell lung carcinoma cell lines compared to small cell carcinoma cell lines. Further, overexpression of MK2 in non-small cell lung carcinoma cell lines results in increased caspase 3 activity and caspase 3 mediated cell death. Higher MK2 transcript levels were observed in patients with earlier-stage non-small cell lung cancer. Higher expression of MK2 is associated with better survival in patients with early stage non-small cell lung cancer across two independent clinical datasets. Using data sets spanning multiple cancer types, we observed improved survival with higher MK2 expression was unique to lung adenocarcinoma. Mechanistically, MK2 promotes nuclear translocation of caspase 3 leading to PARP1 cleavage and execution of cell death. While MK2 can directly phosphorylate caspase 3, neither phosphorylation status of caspase 3 nor the kinase activity of MK2 impacts caspase 3 activation, nuclear translocation and execution of cell death. Rather, a non-kinase function of MK2, specifically trafficking via its nuclear localization sequence, is required for caspase 3 mediated cell death. In summary this study highlights the importance of a non-enzymatic function of MK2 in the execution of apoptosis, which may be leveraged in the adjunctive treatment of NSCLC or other conditions where regulation of apoptosis is crucial.

cancer biology↗