Biology subjects

Koludarov, I.

Publications and source records attributed to Koludarov, I..

11 recordsLinked to original sources

bioRxiv2026

ProtSpace: Protein Universe in Your Browser

AO_SCPLOWBSTRACTC_SCPLOWProtein Language Models (pLMs) generate per-protein embeddings that encode functional, structural, and evolutionary information, yet the relationships captured in these representations remain difficult to explore systematically. ProtSpace (https://protspace.app) is a web application for interactive visualization of pLM embedding spaces, enabling hypothesis generation directly in the browser without installation. Unlike traditional network-based tools that exclusively visualize amino acid sequence similarity, ProtSpace explores embedding spaces, revealing relationships often not captured by traditional comparisons. Users provide protein sequences or pre-computed embeddings through a Google Colab notebook or the Python CLI; the pipeline applies dimensionality reduction, retrieves 38 annotation types spanning UniProt, InterPro, NCBI Taxonomy, TED structural domains, and sequence-based predictors served via Biocentral, and produces a portable binary file for the browser-based viewer. WebGL-accelerated rendering supports interactive exploration of over 570,000 proteins. Distinctive features include per-point pie charts for multi-label annotations and integrated 3D structure viewing through AlphaFold2 predictions. All computation happens on the users machine, ensuring data privacy. We demonstrate the utility of ProtSpace through a progressive zoom-in across biological scales: from global proteome organization of Swiss-Prot, through cross-species comparison revealing conserved and lineage-specific families, to functional hypothesis generation within the beta-lactamase superfamily. ProtSpace is freely available at https://protspace.app under the Apache 2.0 license. KO_SCPLOWEYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWPOINTSC_SCPLOWO_LIProtSpace is a free, open-source web application that visualizes protein Language Model (pLM) embeddings as interactive maps, scaling to 570,000 proteins entirely client-side. C_LIO_LIA zero-installation Google Colab notebook and a Python CLI prepare visualization-ready bundles from FASTA files, UniProt queries, or pre-computed HDF5 embeddings, automatically retrieving 38 annotation types from five sources (UniProt, InterPro, NCBI Taxonomy, TED structural domains, and Biocentral sequence predictors) alongside custom CSV metadata. C_LIO_LIApplication examples demonstrate that embedding visualizations generate testable biological hypotheses at multiple scales, from proteome-wide organization through species-level comparison to family-level functional discovery, and that these are complementary to traditional sequence-based analyses. C_LI

bioinformatics↗

bioRxiv2026

How Ant Genomes Repeatedly Reinvent Venom

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSVenoms from ants (Formicidae) are chemically extraordinarily diverse, yet their genomic architecture and evolutionary dynamics remain opaque. The "aculeatoxin hypothesis" assumes that most venom peptides in stinging insects (aculeates) evolutionarily derive from a single gene family, the aculeatoxins. The recent refutation of this hypothesis for bees raises fundamental questions about venom evolution in ants, which contribute most aculeatoxins. MethodsIn order to trace venom peptide evolution, we performed synteny-aware comparative genomics across 25 ant species spanning major subfamilies. We analyzed phylogeny through sequences, structures, and embeddings from Protein Language Models (pLMs). ResultsWe identified three conserved genomic regions (GR1-GR3) as evolutionary hotspots for ant venom genes, each exhibiting distinct evolutionary dynamics. Most remarkably, we discovered genuine melittin orthologs in ants at the conserved bee syntenic position (GR2), pushing the origin of this scaffold back to early aculeates, with a possible origin deeper in Hymenoptera. Gene copy numbers vary dramatically (0-17 genes per region), with predatory species showing expansions and formicine ants (subfamily Formicinae, which rely on formic acid spraying) showing reductions. Twenty-two distinct toxin clades emerge, with region-specific distributions suggesting repeated recruitment to conserved platforms. SignificanceAnts evolutionarily succeed by combining single-copy conservation (bee-like at GR2), massive gene duplication (snake-like at GR1), and repeated lineage-specific recruitment to conserved genomic platforms (GR3). This multi-modal evolution on stable genomic scaffolds, evidenced here, reconciles previously conflicting models of venom evolution and reveals how genomic architecture constrains, yet repeatedly enables, molecular innovation. Our findings highlight a general principle of genome evolution: complex adaptive traits can arise not from a single origin or mechanism, but through recurrent reuse of permissive genomic loci shaped by ecology. Such principles are likely relevant not only to other venomous animals, but more broadly to the evolution of complex multi-genic traits.

genomics↗

bioRxiv2025

Generating Hybrid Proteins with the MSA-Transformer

Protein superfamilies display extensive sequence and functional divergence, providing a rich landscape for engineering functionally enhanced variants. We present a stochastic, iterative framework that leverages the MSA-Transformer to generate intermediate sequences between a homologous pair of user-specified "source" and "target" proteins in sequence space. Sequence sites to "mask" is either selected by embedding-based dissimilarity or by row-attention information, while beam search concurrently explores multiple mutational pathways. Pre-trained sparse autoencoders combined with sequence and structural analyses are used to trace the inheritance and exchange of features across the "mutational pathway", revealing "hybrid" sequences that integrate properties of both source and target proteins. Applied across diverse protein families, the framework produces sequences that occupy biologically meaningful regions of sequence space and achieve higher consistency and plausibility scores than random baselines according to in silico metrics. In the B1/B2 metallo-{beta}-lactamase family, hybrids largely retain their core fold recombining structural and active-site motifs from both subclasses, demonstrating the models capacity to preserve catalytic features while exploring novel structural permutations. Code availabilityThe implementation is available via GitHub at https://github.com/santule/protmixy.

bioinformatics↗

bioRxiv2025

Which pLM to choose?

AO_SCPLOWBSTRACTC_SCPLOWProtein-language models (pLMs) provide a novel means for mapping the protein space. Which of these new maps best advances specific biological analyses, however, is not obvious. To elucidate the principles of model selection, we benchmarked fourteen pLMs, spanning several orders of magnitude in parameter count, across a hundred million protein pairs, to assess how well they capture sequence, structure, and function similarity. For each model, we distinguish inherent information, i.e. signal recoverable from raw-embedding distances, and extractable information, i.e. signal revealed through additional supervised training. Three key results emerge. First, pLM protein representation space is inherently different from the space of biological protein representations, i.e. sequences or structures. Here, a size-performance paradox is salient - mid-scale foundation models are as good as much larger ones in reflecting all tested biological properties. Second, pLM representations compress and store biological information in proportion to model size. That is, a lightweight feed-forward network can be trained on embedding pairs to predict said biological properties well - a capacity dividend. Finally, we observe that a task-specific learning radically reshapes the embedding space, gaining inherent understanding of the task, but garbling any further extractions. In other words, smaller pLMs can provide efficient and compute-light general insight. Larger models are advantageous only when fine-tuning is planned to accomplish a specific task. Furthermore, representations generated by "specialist" models are not immediately generalizable throughout protein biology. Thus, for pLMs, bigger isnt always better.

bioinformatics↗

bioRxiv2025

FlatProt: 2D visualization eases protein structure comparison

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSUnderstanding and comparing three-dimensional (3D) structures of proteins can advance bioinformatics, molecular biology, and drug discovery. While 3D models offer detailed insights, comparing multiple structures simultaneously remains challenging, especially on two-dimensional (2D) displays. Existing 2D visualization tools lack standardized approaches for pipelined inspection of large protein sets, limiting their utility in large-scale pre-filtering. ResultsWe introduce FlatProt, a tool designed to complement 3D viewers by enabling standardized 2D visualization of individual protein structures or large sets thereof. By including Foldseek-based family rotation alignment or an inertia-based fallback, FlatProt creates consistent and scalable visual representations for user-defined protein structures. It supports domain-aware decomposition, family-level overlays, and lightweight visual abstraction of secondary structures. FlatProt processes proteins efficiently, as showcased on a subset of the human-proteome. ConclusionFlatProt provides clear, consistent, user-friendly visualizations that support rapid, comparative inspection of protein structures at scale. By bridging the gap between interactive 3D tools and static visual summaries, it enables users to explore conserved features, detect outliers, and prioritize structures for further analysis. AvailabilityGitHub (https://github.com/t03i/FlatProt); Zenodo (https://doi.org/10.5281/zenodo.15697296).

bioinformatics↗

bioRxiv2024

ProtSpace: a tool for visualizing protein space

Protein language models (pLMs) generate high-dimensional representations of proteins, so called embeddings, that capture complex information stored in the set of evolved sequences. Interpreting these embeddings remains an important challenge. ProtSpace provides one solution through an open-source Python package that visualizes protein embeddings interactively in 2D and 3D. The combination of embedding space with protein 3D structure view aids in discovering functional patterns readily missed by traditional sequence analysis. We present two examples to showcase ProtSpace. First, investigations of phage data sets showed distinct clusters of major functional groups and a mixed region, possibly suggesting bias in todays protein sequences used to train pLMs. Second, the analysis of venom proteins revealed unexpected convergent evolution between scorpion and snake toxins; this challenges existing toxin family classifications and added evidence refuting the aculeatoxin family hypothesis. ProtSpace is freely available as a pip-installable Python package (source code & documentation) with examples on GitHub (https://github.com/tsenoner/protspace) and as a web interface (https://protspace.rostlab.org). The platform enables seamless collaboration through portable JSON session files.

bioinformatics↗

bioRxiv2022

Domain loss enables evolution of novel functions in a gene superfamily, including snake 3-finger toxins

Three-finger toxins (3FTxs) are a functionally diverse family of toxins, apparently unique to venoms of caenophidian snakes. Although the ancestral function of 3FTxs is antagonism of nicotinic acetylcholine receptors (nAChR), redundancy conferred by accumulation of duplicate genes has facilitated extensive neofunctionalization, such that derived members of the family interact with a range of targets. 3FTxs are members of the Ly6/uPAR family, but their non-toxin ancestor remains unknown. Combining traditional phylogenetic approaches, manual synteny analysis, and cutting-edge machine learning techniques (including AlphaFold2 and ProtT5), we have reconstructed a detailed evolutionary history of 3FTxs. We identify their immediate ancestor as a non-secretory Ly6, unique to squamate reptiles, and propose that changes in molecular ecology resulting from loss of a membrane-anchoring domain (MaD) and changes in gene expression, paved the way for evolution of one of the most important families of snake toxins.

molecular biology↗

bioRxiv2022

Bee core venom genes predominantly originated before aculeate stingers evolved

Venoms, which have evolved numerous times in animals, are ideal models of convergent trait evolution. However, detailed genomic studies of toxin-encoding genes exist for only a few animal groups. The hyper-diverse hymenopteran insects are the most speciose venomous clade, but investigation of the origin of their venom genes has been largely neglected. Utilising a combination of genomic and proteo-transcriptomic data, we investigated the origin of 11 toxin genes in 29 published and three new hymenopteran genomes and compiled an up-to-date list of prevalent bee venom proteins. Observed patterns indicate that bee venom genes predominantly originate through single gene co-option with gene duplication contributing to subsequent diversification. Most Hymenoptera venom genes are shared by all members of the clade and only melittin and the new venom protein family anthophilin1 appear unique to the bee lineage. Most venom proteins thus predate the mega-radiation of hymenopterans and the evolution of the aculeate stinger.

evolutionary biology↗

bioRxiv2021

Apis mellifera cognition as a tool for scientific engagement

In addition to the crowdsourcing of experimental data, citizen science, and scientific engagement more broadly, serve as a bridge between researchers and the wider community. This serves to foster a greater understanding of the scientific method and science-based solutions generally. Apis mellifera (honeybees) are a well-established model for the study of learning and cognition and can serve as an engaging outreach system for this wider community. Here, we developed and implemented a protocol using well established honeybee conditioning protocols to safely study the effects of caffeine and dopamine on learning performance. Using this protocol, a group of high-school aged students as part of the Ryukyu Girls program demonstrated that caffeine, but not dopamine, significantly reduced the number of trials required for a successful conditioning response. This allowed these students to explore the scientific method in a relatable and engaging way. Simple SummaryGlobal scientific literacy can be improved through widespread and effective community engagement by researchers. We propose Apis mellifera (honeybee) as an public engagement tool due to widespread awareness of colony collapse and the bees importance in food production. Moreover, their cognitive abilities make for engaging experiments. Their relative ease of cultivation means that studies can be performed cost-effectively, especially when partnering with local aperists. Using a proxy for honeybee learning, a group of non-specialist high-school-aged participants obtained data suggesting that caffeine, but not dopamine, improved learning. This hands-on experience facilitated student understanding of the scientific method, factors that shape learning and the importance of learning for hive health.

animal behavior and cognition↗

bioRxiv2021

The parallel origins of vertebrate venoms

Evolution can occur with surprising predictability when organisms face similar ecological challenges. How and why traits arise repeatedly remains a central question in evolutionary biology, but the complexity of most traits makes it challenging to answer. Reptiles and mammals independently evolved oral venoms consisting of proteinaceous cocktails that allow mapping between genotype and phenotype. Although biochemically similar toxins can occur as major venom components across many taxa, whether these toxins evolved via convergent or parallel processes remains unknown. Most notable among them are kallikrein-like serine proteases that form the core of most vertebrate oral venoms. We used a combination of comparative genomics and phylogenetics to investigate whether serine protease recruitment into the venom occurred independently or in parallel in mammalian and reptilian lineages. Using syntenic relationships between genes flanking known toxins, we traced the origin of kallikreins to a single locus containing one or more nearby paralogous kallikrein-like clusters. Independently, phylogenetic analysis of vertebrate serine proteases revealed that kallikrein-like toxins in mammals and reptiles are homologous. Given the shared regulatory and genetic machinery, these findings suggest a unified model underlying vertebrate venom evolution. Namely, the common tetrapod ancestor possessed salivary genes that were biochemically suitable for envenomation. We term such genes toxipotent - in the case of salivary kallikreins they already had potent vasodilatory activity that was weaponized by venomous lineages. Furthermore, the ubiquitous distribution of kallikreins across vertebrates suggests that the evolution of envenomation may be more common than previously recognized, blurring the line between venomous and non-venomous animals.

evolutionary biology↗

bioRxiv2019

Family saga: reconstructing the evolutionary history of a functionally diverse gene family reveals complexity at the genetic origins of novelty

Gene duplication is associated with the evolution of many novel biological functions at the molecular level. The dominant view, often referred to as "neofunctionalization", states that duplications precede many novel gene functions by creating functionally redundant copies which are less constrained than singletons. However, numerous alternative models have been formulated, including some in which novel functions emerge prior to duplication. Unfortunately, few studies have reconstructed the evolutionary history of a functionally diverse gene family sufficiently well to differentiate between these models. Here we examined the evolution of the g2 family of phospholipase A2 (EC 3.1.1.4) in the genomes of 93 species from all major lineages of Vertebrata. This family is evolutionarily important and has been co-opted for a diverse range of functions, including innate immunity and venom. The genomic region in which this family is located is remarkably syntenic. This allowed us to reconstruct all duplication events over hundreds of millions of years of evolutionary history using manual annotation of gene clusters, which enabled the discovery of a large number of previously un-annotated genes. Intriguingly, we found that the same ancestral gene in the phospholipase gene cluster independently acquired novel molecular functions in birds, mammals and snake, and all subsequent expansion of the cluster originates from this locus. This suggests that the locus has a deep ancestral propensity for multiplication, likely conferred by a structural arrangement of genomic material (i.e. the "genomic context" of the locus) that dates back at least the amniote MRCA. These results highlight the underlying complexity of gene family evolution, as well as the historical- and context-dependence of gene family evolution. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/583344v3_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1c3228forg.highwire.dtl.DTLVardef@12053forg.highwire.dtl.DTLVardef@11683c0org.highwire.dtl.DTLVardef@123eb3a_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗