Biology subjects

Fernandez-Quintero, M. L.

Publications and source records attributed to Fernandez-Quintero, M. L..

At least 19 recordsLinked to original sources

bioRxiv2026

De novo designed single-domain antibodies protect against lethal cobra venom neurotoxicity in vivo

Generative protein design can now rapidly produce de novo binders with high affinity and functional activity against a wide range of targets, including lethal snake venom toxins. However, so far most reported successes rely on new-to-nature scaffolds with limited therapeutic precedent. Single-domain antibodies (VHHs) offer a clinically validated alternative scaffold that can bind and neutralize long-chain -neurotoxins, which are some of the most lethal components in snake venoms. Here we compare three recently established de novo design models with VHH-design capabilities (Germinal, RFantibody, and BoltzGen) for their ability to generate VHHs against the neurotoxin -cobratoxin from the monocled cobra (Naja kaouthia). Using standardized model inputs and evaluation criteria based on AlphaFold3 interface confidence (ipTM) and RMSD self-consistency, we find that Germinal was the only method to generate designs passing stringent in silico criteria for experimental testing. We therefore performed a larger Germinal design campaign employing three different VHH frameworks and experimentally validated 46 designs in vitro. Of these, 42 expressed as soluble proteins and we identified four binding hits derived from two of the three tested frameworks. Of the four binders, two lead candidates were further characterized and demonstrated high affinity (KDs of 4.1 nM and 10.8 nM), monomeric behavior and low polyreactivity, indicating favorable biophysical and developability properties, as well as functional toxin neutralization in vitro. To assess their therapeutic potential we investigated their ability to protect against -cobratoxin toxicity in vivo. Both candidates fully protected mice after -cobratoxin challenge, with 100% survival compared to a lethal control. One candidate also retained notable neutralization capacity against whole venom of Naja kaouthia with a survival of 56%, while the other protected 22% when tested in a rescue setting. Together, we demonstrate that de novo VHH design can generate high affinity single-domain antibodies with in vivo protection against lethal cobra venom neurotoxicity, and provide practical insights into method- and framework-dependent performance.

bioengineering↗

bioRxiv2026

Convergent antigenic drift of the influenza hemagglutinin lateral patch across time and species

The lateral patch epitope of the H1 hemagglutinin (HA) was a dominant target of antibodies following exposure to the 2009 pandemic H1N1 virus. However, the conservation and potential for antigenic drift in the lateral patch remain unresolved. Here, we used lateral patch-specific monoclonal antibodies (mAbs) to understand the antigenicity of the lateral patch of human, avian, and swine H1Nx viruses spanning from 1918 to 2022. We identified discrete mutations that evaded lateral patch-targeting mAbs in pre- and post-2009 H1N1 viruses, leading to genetic differences in lateral patch-targeting antibodies in individuals across birth years. We observed that the lateral patch remains well conserved across zoonotic sources, suggesting existing lateral patch antibodies could protect against a future H1Nx pandemic. Together, these data support that lateral patch antigenic drift has shaped the human B cell repertoire against influenza viruses and that the lateral patch remains an attractive target for pandemic preparedness.

microbiology↗

bioRxiv2026

Disulphide and sequence-encoded conformational priors guide nanobody structure prediction

Nanobody binding is largely governed by the HCDR3 loop, which adopts distinct placement regimes relative to the framework: compact, framework-contacting (kinked blueprint) and solvent-exposed (extended blueprint). Many nanobodies also contain additional cysteines that form non-canonical disulphide bonds, imposing covalent constraints on binding-loop conformations. Current structure predictors are typically trained and benchmarked with smooth coordinate-based objectives, so models may appear reasonable under root-mean-square deviation (RMSD), while adopting an incorrect HCDR3 blueprint or failing to recover the native disulphide connectivity, impacting paratope geometry and functional interpretation. Here, we show that the HCDR3 blueprint is predictable from sequence alone, allowing for explicit constraints during modelling. We implement these principles into NbForge, a lightweight nanobody folding model that incorporates blueprint- and disulphide-aware inductive biases and is trained with filtered self-distillation. NbForge improves recovery of HCDR3 blueprint and non-canonical disulphide formation over previous lightweight models and achieves coordinate accuracy at par to state-of-the-art, large, resource-intensive predictors, while running at sub-second inference speed. We show that using NbForge monomer models as templates further improves the success rate of predicting nanobody-antigen complexes. Together, these results motivate blueprint- and disulphide-aware benchmarks for nanobody modelling beyond RMSD, and show that appropriate inductive biases can close the performance gap to heavyweight predictors. We make the sequence classifier (NbFrame) and NbForge available for download and via a user-friendly web server.

bioinformatics↗

bioRxiv2026

Structural basis for conserved and distinct antigen recognition by a lineage of malaria-protective antibodies

Monoclonal antibodies (mAbs) targeting the Plasmodium falciparum circumsporozoite protein (PfCSP) have demonstrated substantial promise in preventing malaria infection and disease. PfCSP is characterized by a central region composed of repetitive NANP motifs, which serve as major targets for protective antibodies. Several potent mAbs targeting this region exhibit homotypic Fab-Fab interactions, which enhance antigen binding and contribute to their neutralization potency. Among these, mAb 399, encoded by the IGHV3-49/IGKV2D-29 (VH3-49/VK2D-29) germline lineages, forms head-to-head inter-Fab contacts mediated primarily by germline-encoded residues. In this study, we determined high-resolution X-ray crystal and cryo-EM structures of two additional Fabs, derived from the same germline lineages, 7160 and 7118, in complex with PfCSP-derived peptides. Both Fabs bound the NANP6 repeats with high affinity (KD 5-10 nM). Fab 7160 formed similar inter-Fab homotypic interactions to Fab 399 upon binding to an extended repeat peptide (NANP), indicating a conserved mode of recognition. In contrast, Fab 7118, which features a longer CDRH3, does not form homotypic contacts. Instead, Fab 7118 induced a bend in the peptide and adopted a distinct binding mode, which prevents inter-Fab interactions. A cryo-EM structure of Fab 7118 in complex with a recombinant shortened PfCSP construct (rsCSP) further revealed potential disruptions at inter-Fab contact sites. These findings highlight the structural versatility of VH3-49/VK2D-29-derived antibodies and demonstrate that CDR loop variations within a shared antibody lineage can modulate antibody conformation, homotypic Fab-Fab interactions, and epitope engagement. Our study provides mechanistic insights into the diverse strategies by which CSP-specific antibodies can achieve high-avidity binding and protective immunity.

microbiology↗

bioRxiv2025

De novo designed protein enables precise epitope-level control of Gremlin-1 antagonism

Growth-factor antagonists regulate key developmental and pathological processes, yet the molecular principles governing their control remain poorly understood. Gremlin-1 (GREM1) is a secreted antagonist of bone morphogenetic proteins (BMPs) whose dysregulation is implicated in fibrosis and cancer. Here, we report a de novo designed protein that binds GREM1 with sub-nanomolar affinity and selectively releases BMPs for downstream signalling. By integrating generative deep-learning-based protein design with molecular-dynamics-derived flexibility descriptors, we identify a predictive relationship between interface rigidity, desolvation energy, and binding success. The resulting binder, RF1-2, reproduces the native BMP-binding epitope on GREM1 at near-atomic precision, as confirmed by cryo-electron microscopy, and competitively blocks BMP-2 and BMP-4 association. These results establish interface rigidity as a key physical determinant of antagonist inhibition and demonstrate how AI-guided protein design can uncover molecular principles underlying extracellular signalling control.

biochemistry↗

bioRxiv2025

Engineering HIV antibodies with enhanced breadth and potency of neutralization through multistate affinity maturation

Broadly neutralizing antibodies (bnAbs) against HIV hold promise as therapeutic and prophylactic agents, but realizing this potential requires antibodies that function across the antigenic heterogeneity of the HIV envelope glycoprotein (Env). Although numerous bnAbs have been isolated from infected individuals, their breadth and potency may not be sufficient to tackle global viral diversity, motivating efforts to further improve their neutralization capacity. Here, we address this challenge using a multistate antibody engineering approach integrating deep mutational scanning with combinatorial library screening across diverse Env variants. This strategy enables identification of mutation patterns that confer improved binding across antigenically distinct targets. Starting from one of the best-in-class CD4-binding site bnAbs, we performed iterative optimization to increase binding affinity across diverse Env variants. The resulting lead candidate exhibited improved breadth and up to 100-fold higher potency against pseudoviruses from large cross-clade historical and contemporary panels while maintaining biophysical and pharmacokinetic profiles conducive to clinical development. Structural and molecular dynamics analyses revealed a unique tri-tyrosine aromatic triad and reinforced electrostatic contacts that stabilized the bnAb/Env interface. These findings demonstrate that systematic in vitro engineering can generate bnAbs with enhanced breadth and potency, providing a generalizable strategy for developing therapeutic antibodies against highly diverse pathogens.

bioengineering↗

bioRxiv2025

A bi-directional binding site linking the α2δ-1 subunit to the intrinsic speed control process in VSD I of voltage-gated calcium channels

Voltage-gated calcium channels communicate electrical signals in membranes of excitable cells into cellular responses like secretion of hormones and neurotransmitters, or the contraction of heart and skeletal muscle cells. Their activation properties are tuned to match their specific functions. Consequently, the different members of the calcium channel family activate over a wide range of voltages and with greatly differing speeds. The skeletal muscle CaV1.1 and the cardiac/neuronal CaV1.2 represent two structurally closely related channels with particularly slow and fast activation kinetics, respectively. Both channel paralogs associate with the auxiliary calcium channel subunit 2{delta}-1, which is a known regulator of activation properties. By expressing CaV1.1 and CaV1.2 with and without 2{delta}-1 in a new double-knockout muscle cell line, we demonstrate that 2{delta}-1 regulates activation kinetics of the two channels in opposite directions. Molecular dynamics simulation revealed a string of charged amino acids connecting 2{delta}-1 to the intrinsic speed-control mechanism of voltage-sensing domain I (VSD I) in CaV1.1. Charge-neutralizing mutations of any of these charged amino acids abolished the 2{delta}-1 modulation and accelerated current kinetics. Together, these results reveal the molecular mechanism by which the 2{delta}-1 subunit regulates the intrinsic speed-control mechanism in the VSD I of CaV1.1 calcium channels.

biophysics↗

bioRxiv2025

CryoEM Structures of Antibodies Elicited by Germline-Targeting HIV MPER Epitope-Scaffolds

Applying cryoEM to small protein complexes is usually challenging due to their lack of features for particle alignment. Here, we characterized antibody responses to 21 kDa HIV membrane-proximal external region germline-targeting (MPER-GT) immunogens through cryoEM by complexing them with 10E8 or Fabs derived from MPER-GT immunized animals. Distinct antibody-antigen interactions were analyzed using atomic models generated from cryoEM maps. Mutagenesis screening revealed off-target mAbs that do not compete with 10E8 bind non-MPER epitopes, and the two most dominant epitopes were verified by cryoEM. The structures of 10E8-class on-target Fabs showed binding patterns that resemble the YxFW motif in the 10E8 HCDR3 loop. Additionally, we demonstrate that high-resolution maps can be generated from heterogeneous samples with pooled competing Fabs. Overall, our findings will facilitate the optimization of MPER GT-antigens and push the size limit for cryoEM-based epitope mapping with smaller antigens and heterogeneous antibody mixes. HighlightsO_LIElucidate the structural basis of increased 10E8 affinity to GT12 over GT10.2 C_LIO_LICryoEM epitope mapping reveals three main binding sites on MPER-GT immunogens C_LIO_LIProof of concept for application of CryoEM epitope mapping to small immunogens C_LIO_LIStructural characterization and MD analysis confirms 10E8-like interactions of the MPER-specific Fabs C_LI

immunology↗

bioRxiv2025

Predicting the conformational flexibility of antibody and T-cell receptor CDRs

AbstractMany proteins are highly flexible and their ability to adapt their shape can be fundamental to their functional properties. We can now computationally predict a single, static protein structure with high accuracy. However, we are not yet able to reliably predict structural flexibility. A major factor limiting such predictions is the scarcity of suitable training data. Here, we focus on predicting the structural flexibility of the functionally important antibody and T-cell receptor CDR3 loops. We extracted a dataset of CDR3 like loop motifs from the PDB to create ALL-conformations, a dataset containing 1.2 million structures and more than 100,000 unique sequences. Using this dataset, we develop ITsFlexible a method classifying CDR3 flexibility, which outperforms all alternative approaches on our crystal structure datasets and successfully generalises to MD simulations. We also used ITsFlexible to predict the flexibility of three completely novel CDRH3 loops and experimentally determined their conformations using cryo-EM.

bioinformatics↗

bioRxiv2024

Structural serology of polyclonal antibody responses to mRNA-1273 and NVX-CoV2373 COVID-19 vaccines

Current COVID-19 vaccines are largely limited in their ability to induce broad, durable immunity against emerging viral variants. Design and development of improved vaccines utilizing existing platforms requires an in-depth understanding of the antigenic and immunogenic properties of available vaccines. Here we examined the antigenicity of two of the original COVID-19 vaccines, mRNA-1273 and NVX-CoV2373, by electron microscopy-based polyclonal epitope mapping (EMPEM) of serum from immunized non-human primates (NHPs) and clinical trial donors. Both vaccines induce diverse polyclonal antibody (pAb) responses to the N-terminal domain (NTD) in addition to the receptor-binding domain (RBD) of the Spike protein, with the NTD supersite being an immunodominant epitope. High-resolution cryo-EMPEM studies revealed extensive pAb responses to and around the supersite with unique angles of approach and engagement. NTD supersite pAbs were also the most susceptible to variant mutations compared to other specificities, indicating that ongoing Spike ectodomain-based vaccine design strategies should consider immuno-masking this site to prevent induction of these strain-specific responses.

immunology↗

bioRxiv2024

De novo designed pMHC binders facilitate T cell induced killing of cancer cells

The recognition of intracellular antigens by CD8+ T cells through T-cell receptors (TCRs) is central to adaptive immunity, enabling responses against infections and cancer. The recent approval of TCR-gene-edited T cells for cancer therapy demonstrates the therapeutic advantage of using pMHC recognition to eliminate cancer. However, identification and selection of TCRs from patient material is complex and influenced by the TCR repertoire of the donors used. To overcome these limitations, we here present a rapid and robust de novo binder design platform leveraging state-of-the-art generative models, including RFdiffusion, ProteinMPNN, and AlphaFold2, to engineer minibinders (miBds) targeting the cancer-associated pMHC complex, NY-ESO-1(157-165)/HLA-A*02:01. By incorporating in silico cross-panning and molecular dynamics simulations, we enhanced specificity screening to minimise off-target interactions. We identified a miBd that exhibited high specificity for the NY-ESO-1-derived peptide SLLMWITQC in complex with HLA-A*02:01 and minimal cross-reactivity in mammalian display assays. We further demonstrate the therapeutic potential of this miBd by integrating it into a chimeric antigen receptor, as de novo Binders for Immune-mediated Killing Engagers (BIKEs). BIKE-transduced T cells selectively and effectively killed NY-ESO-1+ melanoma cells compared to non-transduced controls, demonstrating the promise of this approach in precision cancer immunotherapy. Our findings underscore the transformative potential of generative protein design for accelerating the discovery of high-specificity pMHC-targeting therapeutics. Beyond CAR-T applications, our workflow establishes a foundation for developing miBds as versatile tools, heralding a new era of precision immunotherapy.

immunology↗

bioRxiv2024

Structural basis of broad protection against influenza virus by a human antibody targeting the neuraminidase active site via a recurring motif in CDR H3

Influenza viruses evolve rapidly, driving seasonal epidemics and posing global pandemic threats. While neuraminidase (NA) has emerged as a vaccine target, shared molecular features of NA antibody responses are still not well understood. Here, we describe cryo-electron microscopy structures of the broadly protective human antibody DA03E17, which was previously identified from an H1N1-infected donor, in complex with NA from A/H1N1, A/H3N2, and B/Victoria-lineage viruses. DA03E17 targets the highly conserved NA active site using its long CDR H3, which features a DR (Asp-Arg) motif that engages catalytic residues and mimics sialic acid interactions. We further demonstrate that this motif is conserved among several NA active site-targeting antibodies, indicating a common receptor mimicry strategy. We also identified potential antibody precursors containing this DR motif in all donors of a healthy human donor BCR database, highlighting the prevalence of this motif and its potential as vaccine targeting. Our findings reveal shared molecular features in NA active site-targeting antibodies, offering insights for NA-based universal influenza vaccine design.

immunology↗

bioRxiv2024

Trapped ion mobility spectrometry-guided molecular discrimination between plasmalogens and other ether lipids in lipidomics experiments

Trapped Ion Mobility Spectrometry (TIMS) has demonstrated promissing potential as a powerful discriminating method when coupled with mass spectrometry, enhancing the precision of feature annotation. Such a technique is particularly valuable for lipids, where a large number of isobaric but structurally distinct molecular species often coexist within the same sample matrix. In this study we explored the potential of ion mobility for ether lipid isomer differentiation. Mammalian ether phospholipids are characterized by a fatty alcohol residue at the sn-1 position of their glycerol backbone. Ether lipids can make up to 20% of the total phospholipid mass. They are present in a broad range of tissues where they are for example crucial for nervous system function, membrane homeostasis and inter-as well as intracellular signaling. Molecular ether lipid species are difficult to distinguish analytically, as they occur as 1-O-alkyl and 1-O-alkenyl subclasses, with the latter being also known as plasmalogens. Isomeric ether lipid pairs can be separated with reversed-phase chromatography. However, their precise identification remains challenging due to the lack of clear internal reference points, inherent to the nature of lipid profiles and the lack of sufficient commercially available standard substances. Here, we demonstrate - with focus on phosphatidylethanolamines - that ion mobility measurements allow to discriminate between the ether lipid subclasses through distinct differences in their gas phase geometries. This approach offers significant advantages as it does not depend on the variability of chromatography. However, the current resolution in the ion mobility dimension is not sufficient to baseline separate 1-O-alkyl and 1-O-alkenyl isobars, and the observed differences are not yet accurately represented in existing collision cross section databases. Despite these challenges, the predictable properties of the ion mobility behavior of ether lipid species can significantly support their accurate annotation and hold promise for future advancements in lipid research.

biochemistry↗

bioRxiv2024

A single mutation in dairy cow-associated H5N1 viruses increases receptor binding breadth

Clade 2.3.4.4b H5N1 is causing an unprecedented outbreak in dairy cows in the United States. To understand if recent H5N1 viruses are changing their receptor use, we screened recombinant hemagglutinin (HA) from historical and recent 2.3.4.4b H5N1 viruses for binding to distinct glycans bearing terminal sialic acids. We found that H5 from A/Texas/37/2024, an isolate from the dairy cow outbreak, has increased binding breadth to glycans bearing terminal 2,3 sialic acids, the avian receptor, compared to historical and recent 2.3.4.4b H5N1 viruses. We did not observe any binding to 2,6 sialic acids, the receptor used by human seasonal influenza viruses. We identified a single mutation outside of the receptor binding site, T199I, was responsible for increased binding breadth, as it increased receptor binding site flexibility. Together, these data show recent H5N1 viruses are evolving increased receptor binding breadth which could impact the host range and cell types infected with H5N1.

microbiology↗

bioRxiv2024

Assessing AF2's ability to predict structural ensembles of proteins

Recent breakthroughs in protein structure prediction have enhanced the precision and speed at which protein configurations can be determined, setting new benchmarks for accuracy and efficiency in the field. However, the fundamental mechanisms of biological processes at a molecular level are often connected to conformational changes of proteins. Molecular dynamics (MD) simulations serve as a crucial tool for capturing the conformational space of proteins, providing valuable insights into their structural fluctuations. However, the scope of MD simulations is often limited by the accessible timescales and the computational resources available, posing challenges to comprehensively exploring protein behaviors. Recently emerging approaches have focused on expanding the capability of AlphaFold2 (AF2) to predict conformational substates of protein structures by manipulating the input multiple sequence alignment (MSA). These approaches operate under the assumption that the MSA also contains information about the heterogeneity of protein structures. Here, we benchmark the performance of various workflows that have adapted AF2 for ensemble prediction focusing on the subsampling of the MSA as implemented in ColabFold and compare the obtained structures with ensembles obtained from MD simulations and NMR. As test cases, we chose four proteins namely the bovine pancreatic inhibitor protein (BPTI), thrombin and two antigen binding fragments (antibody Fv and nanobody), for which reliable experimentally validated structural information (X-ray and/or NMR) was available. Thus, we provide an overview of the levels of performance and accessible timescales that can currently be achieved with machine learning (ML) based ensemble generation. In three out of the four test cases, we find structural variations fall within the predicted ensembles. Nevertheless, significant minima of the free energy surfaces remain undetected. This study highlights the possibilities and pitfalls when generating ensembles with AF2 and thus may guide the development of future tools while informing upon the results of currently available applications.

biophysics↗

bioRxiv2024

Broadly inhibitory antibodies against severe malaria virulence proteins

Plasmodium falciparum pathology is driven by the accumulation of parasite-infected erythrocytes in microvessels. This process is mediated by the parasites polymorphic erythrocyte membrane protein 1 (PfEMP1) adhesion proteins. A subset of PfEMP1 variants that bind human endothelial protein C receptor (EPCR) through their CIDR1 domains is responsible for severe malaria pathogenesis. A longstanding question is whether individual antibodies can recognize the large repertoire of circulating PfEMP1 variants. Here, we describe two broadly reactive and binding-inhibitory human monoclonal antibodies against CIDR1. The antibodies isolated from two different individuals exhibited a similar and consistent EPCR-binding inhibition of 34 CIDR1 domains, representing five of the six subclasses of CIDR1. Both antibodies inhibited EPCR binding of both recombinant full-length and native PfEMP1 proteins as well as parasite sequestration in bioengineered 3D brain microvessels under physiologically relevant flow conditions. Structural analyses of the two antibodies in complex with two different CIDR1 antigen variants reveal similar binding mechanisms that depend on interactions with three highly conserved amino acid residues of the EPCR-binding site in CIDR1. These broadly reactive antibodies likely represent a common mechanism of acquired immunity to severe malaria and offer novel insights for the design of a vaccine or treatment targeting severe malaria.

immunology↗

bioRxiv2023

Learning high-dimensional reaction coordinates of fast-folding proteins using State Predictive Information Bottleneck and Bias Exchange Metadynamics

Biological events occurring on long timescales, such as protein folding, remain hard to capture with conventional molecular dynamics (MD) simulation. To overcome these limitations, enhanced sampling techniques can be used to sample regions of the free energy landscape separated by high energy barriers, thereby allowing to observe these rare events. However, many of these techniques require a priori knowledge of the appropriate reaction coordinates (RCs) that describe the process of interest. In recent years, Artificial Intelligence (AI) models have emerged as promising approaches to accelerate rare event sampling. However, integration of these AI methods with MD for automated learning of improved RCs is not trivial, particularly when working with undersampled trajectories and highly complex systems. In this study, we employed the State Predictive Information Bottleneck (SPIB) neural network, coupled with bias exchange metadynamics simulations (BE-metaD), to investigate the unfolding process of two proteins, chignolin and villin. By utilizing the high-dimensional RCs learned from SPIB even with poor training data, BE-metaD simulations dramatically accelerate the sampling of the unfolding process for both proteins. In addition, we compare different RCs and find that the careful selection of RCs is crucial to substantially speed up the sampling of rare events. Thus, this approach, leveraging the power of AI and enhanced sampling techniques, holds great promise for advancing our understanding of complex biological processes occurring on long timescales. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/550401v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@18a9296org.highwire.dtl.DTLVardef@9dc2f3org.highwire.dtl.DTLVardef@16a0cf8org.highwire.dtl.DTLVardef@1799db1_HPS_FORMAT_FIGEXP M_FIG TABLE OF CONTENT GRAPHIC C_FIG

biophysics↗

bioRxiv2023

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity and Antibody Developability

The electrostatic properties of proteins arise from the number and distribution of polar and charged residues. Due to their long-ranged nature, electrostatic interactions in proteins play a critical role in numerous processes, such as molecular recognition, protein solubility, viscosity, and antibody developability. Thus, characterizing and quantifying electrostatic properties of a protein is a pre-requisite for understanding these processes. Here, we present PEP-Patch, a tool to visualize and quantify the electrostatic potential on the protein surface and showcase its applicability to elucidate protease substrate specificity, antibody-antigen recognition and predict heparin column retention times of antibodies as an indicator of pharmacokinetics.

biophysics↗