Biology subjects

Nair, S.

Publications and source records attributed to Nair, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Systematic exploration of predicted quaternary structures within pandemic-relevant viral proteomes

Mechanistic understanding of viral protein-protein interactions enables global health security and pandemic preparedness, yet experimental characterisation remains difficult, costly, and often restricted to specialised laboratories. Here, we describe an in silico campaign using AlphaFold2 and AlphaFold-Multimer to predict monomers and dimer structures within 2,812 viral proteomes from 23 viral families relevant to human health. We report high-confidence predicted structures of 5,279 hetero-, and 2,749 homo-dimers. Structural clustering of interfaces reduces the set fivefold to 1,598 consolidated by form and function, of which 471 (29.5%) lacked detectable similarity to experimentally determined interfaces in the PDB. These clusters yielded two notable findings: new data on vaccinology-relevant glycoproteins, and accurate prediction of the specificity and cleavage-site recognition of viral proteases, which are targets for anti-viral development. Viral monomers and high-confidence dimers are available for interactive browsing in the Pandemic Preparedness Portal of the AlphaFold Database (https://alphafold.ebi.ac.uk/), and the full dataset is available for bulk download.

bioinformatics↗

bioRxiv2026

The Human Bindome: A Proteome-scale Atlas of Designed Binder Candidates

Affinity reagents such as antibodies are indispensable for interrogating proteins biological function. Yet they are costly and frequently unreliable, with unknown sequences, posing challenges to reproducible experimental research. Deep learning-based protein design can now in silico generate affinity reagents achieving reliable experimental success rates, but has remained largely confined to specialist laboratories. Here we present the Human Bindome, a proteome-scale atlas of high-confidence in silico protein binder candidates. By embedding the experimentally benchmarked BindCraft method in an accelerated, parallelized framework with automated domain-level target selection, we generated 306,146 binder candidates covering 8,296 human proteins (40.9% of the full proteome). Every candidate carries a defined sequence, a predicted binder-target structure model, and in silico confidence metrics. We characterize proteome-wide coverage and show that binder epitopes frequently overlap functional sites. This positions the Bindome as a resource of genetically encodable perturbagens for site-specific, modular control of protein function. The Bindome is freely available through a web interface (https://bindome.epfl.ch), with agentic, natural-language querying and as data splits for machine-learning model development. We anticipate that the Bindome will be valuable for the scientific community by providing affinity and perturbation reagents with broad applications in dissecting biological mechanisms as well as in drug and target discovery.

synthetic biology↗

bioRxiv2026

Diatoms maintain metabolic activity in deep ocean twilight zones

Phytoplankton are primarily confined to the sunlit epipelagic zone, yet intact algal cells persist in the oceans mesopelagic twilight zone where light is minimal. However, their survival strategies in the deeper ocean remain unknown. Here, we isolate Chaetoceros sp. DS1 from 1000 m depth and reveal its survival mechanisms under prolonged darkness and high pressure, including membrane lipid remodeling and enhanced antioxidant defenses. Importantly, DS1 maintains a latent photosynthetic reserve that activates upon exposure to dim blue light and higher pressure typical of the twilight zone, enabling photosynthesis and nutrient uptake. It exhibits metabolic flexibility by utilizing stored carbon in darkness and assimilating organic carbon under dim light. Global meta-omics data show widespread, transcriptionally active Chaetoceros-like diatoms in the twilight zone, expressing blue-light sensors and protein synthesis genes. These findings identify the ocean twilight zone as a previously overlooked niche for metabolically active phytoplankton, expanding understanding of deep-ocean microbial ecology and carbon cycling.

ecology↗

bioRxiv2026

PDBe-SIFTS: an open-source tool for Structure Integration with Function, Taxonomy, and Sequences, featuring improved alignment, scoring scheme, and accelerated search

Structure Integration with Function, Taxonomy and Sequences (SIFTS) provides residue-level mappings between UniProt Knowledgebase sequences and Protein Data Bank structures and has historically been generated through internal Protein Data Bank in Europe (PDBe) pipelines. Here, PDBe-SIFTS is presented as a fully open-source, locally deployable implementation of this mapping framework. The pipeline combines fast, scalable sequence search using MMseqs2, an improved bounded scoring scheme for ranking candidate mappings, and residue-level mapping refinement based on backbone connectivity. PDBe-SIFTS is distributed as a Python package with command-line tools for 1) building a sequence search database, 2) identifying the best sequence-structure match, 3) one-to-one mapping at the residue level, and 4) generating SIFTS annotations in PDBx/mmCIF format. Benchmarking on the complete Protein Data Bank archive showed that MMseqs2 reduced archive-scale UniProtKB searches from hours with BLASTP to minutes, approximately 22-36 times faster, while curated mappings were recovered at top rank in 93.1% of cases. The remaining discrepancies mainly involved biologically ambiguous cases such as highly conserved proteins, chimeric constructs, or closely related orthologs. These results show that PDBe-SIFTS enables fast mapping, improving structural coherence in residue-level alignments while delivering the most up-to-date and accurate mappings, comparable to expert curation. Tool: https://github.com/PDBeurope/SIFTS Quick start notebook with example: https://github.com/PDBeurope/SIFTS/tree/master/notebooks Broader audience statementMatching protein sequences to their three-dimensional structures, and mapping annotations across both, is essential for understanding protein function, interactions, and molecular mechanisms. This integrated view enables richer interpretation of biological data and underpins advances in drug discovery, disease research, and protein engineering. PDBe-SIFTS provides an open and functional framework for structure-sequence mapping, allowing researchers and databases to run, inspect, and extend these mappings locally, while benefiting from faster searches, transparent scoring, and structurally informed residue-level alignments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/721839v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@5e6ea6org.highwire.dtl.DTLVardef@1b2754dorg.highwire.dtl.DTLVardef@1334f9forg.highwire.dtl.DTLVardef@1b083a1_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Agentic systems are adept at solving well-scoped, verifiable problems in computational biology

We introduce CompBioBench, a benchmark of 100 diverse tasks for evaluating agentic systems in computational biology. Unlike mathematics and programming, which more readily admit systematic verification, biological data are inherently noisy and open to interpretation. To enable objective evaluation without reducing tasks to prescriptive checklists, we propose a new benchmark construction strategy based on synthetic/augmented data and metadata scrambling/scrubbing of real datasets to create challenging problems that have a single ground-truth answer and require multi-step reasoning, tool use, bespoke code, and interaction with real-world external resources. The benchmark spans genomics, transcriptomics, epigenomics, single-cell analysis, human genetics, and machine learning workflows. Questions are curated by domain experts to cover a broad range of skills with varying difficulty. We evaluate leading general-purpose agentic systems starting from a bare-minimum environment, requiring them to fetch data and tools as needed to solve each problem. We find strong end-to-end performance, with Codex CLI (GPT 5.4) reaching 83% accuracy, Gemini CLI (3.1 Pro) reaching 82%, Claude Code (Opus 4.6) reaching 81%, and Claude Code (Opus 4.7) reaching 78%. On the hardest questions, Claude Code (Opus 4.6) reaches 69%, Codex CLI (GPT 5.4) reaches 59%, and Gemini CLI (3.1 Pro) reaches 49%. CompBioBench provides a practical testbed for measuring the progress of agentic systems in computational biology and for guiding future benchmark design. Data and a public leaderboard are available at https://huggingface.co/collections/Genentech/compbiobench-v1.

bioinformatics↗

bioRxiv2026

AlphaFold Database expands to proteome-scale quaternary structures

Protein function is governed by molecular interactions, yet structural coverage of these interactions remains sparse. The AlphaFold Protein Structure Database (AFDB) transformed access to accurate monomeric protein structures at scale. Here, we expand the AFDB to quaternary structures by predicting 31M candidate homo- and heterodimeric protein complexes, compiled from 4,777 proteomes, including model- and global health organisms. We established confidence criteria via analysis of experimentally determined structures, resulting in 1.81M high-confidence predictions. These models enabled the discovery of emergent structures and topologies not present in monomeric predictions. Additionally, the top 1% of structural clusters accounted for [~]44% of all complexes, and [~]8.3% of clusters were conserved across multiple domains of life, pointing to a substantial fraction of ancient, universally retained assemblies. Structural search highlighted that high-confidence predictions are anchored in experimental multimer space, yet 31.3% extend beyond detectable PDB coverage. These freely accessible proteome-scale predictions facilitate functional and mechanistic hypothesis generation across biology.

synthetic biology↗

bioRxiv2026

Resident cardiac macrophages are not required for normal atrioventricular node conduction

Resident cardiac macrophages are understood to facilitate atrioventricular (AV) node conduction because they purportedly couple to AV node myocytes via connexin43 (Cx43) containing gap junctions. We tested this mechanism using biophysical modelling, high-resolution imaging of mouse and human AV conduction tissue, and pharmacological macrophage depletion. In silico, coupling macrophage membrane phenotypes to HCN4+ AV node myocytes imposed an electrotonic load that suppressed pacemaking and promoted conduction slowing, including stable 2:1 block in strand simulations. Anatomically, HCN4-defined components of the mouse AV conduction axis were essentially devoid of Cx43 and overlap of CD68+ macrophages and Cx43 was negligible in both mouse AV node and human penetrating bundle. Finally, near-complete macrophage depletion with CSF1R inhibition (PLX5622) did not alter AV electrical activity in vivo or ex vivo. Together, these data argue against a physiologically relevant role for Cx43-mediated macrophage-myocyte electrical coupling in normal AV node function. HIGHLIGHTSO_LIModelling predicts that AV node automaticity and conduction would be suppressed if macrophages coupled to AV node myocytes C_LIO_LIThe mouse AV conduction axis is essentially devoid of Cx43, currently considered responsible for macrophage-AV node myocyte coupling C_LIO_LIOverlap of macrophages and Cx43 expression is not discernible in the Cx43-expressing human distal AV node C_LIO_LIMacrophage depletion by CSF1R inhibition does not impact AV electrical activity in vivo or ex vivo C_LI

physiology↗

bioRxiv2026

Can Antisense lncRNA bind to the product of its sense pair?

Long non-coding RNAs (lncRNAs) account for a major proportion of the transcriptional output in complex organismal genomes. Their emergence as auxiliary regulators of gene expression as well as their roles in metastasis and cancer progression has put them in the limelight. LncRNAs perform multitudes of functions and often moonlight as regulators, scaffolds and guides. Most lncRNAs are cell and tissue specific and can act as markers for diseases as well as targets for therapeutic interventions. LncRNAs are also known to make use of higher order structures such as G-quadruplexes (G4) to facilitate complex functions and interactions. THAP9-antisense1 (AS1) is a lncRNA coding gene (recently annotated by Ensembl) that codes for 12 lncRNA transcripts and has been implicated in many disease pathologies like gastric cancer, spontaneous neutrophil apoptosis, hepatocellular carcinoma, and the progression of oesophageal cancer. It is the antisense gene pair of the THAP9 gene ( a transposase derived gene) with which it shares a promoter. THAP9-AS1 has been reported to be dysregulated during stress and several cancers. However, the exact role of the lncRNA is not well understood. Bioinformatics driven strategies are used to identify putative quadruplex forming sequences (PQSs) within the lncRNA THAP9-AS1. The identified PQSs are further validated using biophysical, spectroscopic and molecular biology driven techniques. The importance of each G-tract in the formation of a particular RNA G-quadruplex (rG4) is studied via the investigation of several deletion mutants. The findings demonstrate the rG4 forming potential of the identified PQSs within THAP9-AS1.

biochemistry↗

bioRxiv2026

DNA synthesis inside the hepatitis B virus creates a high-energy spool

The Hepatitis B Virus (HBV) capsid assembles around an RNA pregenome which is reverse-transcribed into double-stranded DNA. It remains unclear how this DNA, which is stiff, bulky, and has significant negative charge, is accommodated within the capsid. The organization of the genome will answer this and lend insight into the viral reverse transcription reaction. We determined the structures of mature HBV and Duck HBV, finding that the DNA forms a spool that is coaxial with the capsids fivefold symmetry and interacts with charges on the capsid interior. We calculate that the energy of DNA bending would create a metastable capsid that just awaits a trigger for DNA release. Thus, we see how nature has created a fragile energy minimum that enables genome uncoating.

microbiology↗

bioRxiv2026

Deep learning-guided design of cell type-specific AAV promoters

Precise cell type targeting is critical for both clinical and experimental applications of adeno-associated viral (AAV) vectors, yet engineering vectors with cell type-specific activity remains a challenge. Here, we compared three strategies leveraging single-cell chromatin accessibility data to design cell type-specific AAV promoters, including a deep learning-based method to generate de novo regulatory sequences. When applied to target retinal ganglion cells or horizontal cells in mouse retina, deep learning-guided design consistently outperformed rational approaches, yielding synthetic promoters with stronger and more specific expression in vivo. Synthetic AAV promoters supported diverse transgenes, enabling the recording and ablation of targeted cells. Promoter activity was also maintained in human retinal organoids, suggesting that deep learning-designed sequences may be suitable for translation. Our findings highlight the potential of deep learning to synthesize cell type-specific AAV promoters and establish a versatile platform for cell type targeting with broad implications for gene therapy and basic research.

synthetic biology↗

bioRxiv2026

Stress-Survival Pathway Profiling Reveals MCM10 as a Candidate Biomarker of Hispanic Colorectal Cancer Disparities

BackgroundColorectal cancer (CRC) remains the second leading cause of cancer mortality in the U.S., with significant racial and ethnic disparities in incidence, survival, and mortality rates. The rising incidence of early-onset CRC and the frequent presentation at advanced stages of CRC among the Hispanics makes this an important ethnic group to study. A deeper understanding of the complex interplay between molecular, genetic, and environmental factors is critical for developing targeted therapies to reduce the prevalence in specific racial and ethnic groups, such as Hispanics. This study explores the role of stress-survival pathway (SSP) genes in early-onset and late-stage CRC, primarily focusing on disparities between Hispanics and Non-Hispanic Whites (NHWs). Additionally, this study investigates the role of MCM10, in contributing to CRC disparities among the Hispanic populations with an emphasis of early-onset and late-stage CRC Hispanics. MethodsOne of our previous studies had identified some SSP protein coding genes associated with CRC. The transcript and protein level expressions of these genes were validated in CRC cell lines, cDNA arrays, and tissue microarrays, using qRT-PCR and immunohistochemistry, respectively. The transcript level expressions of differentially expressed SSP genes were further evaluated in Hispanic and NHWs tumor tissues, including early onset and late-stage cohorts. Additionally, we performed cellular, physiological, and functional assays to explore the role of MCM10 in tumor progression, before and after siRNA mediated knockdown of MCM10. High-throughput transcriptomic and proteomic analyses were performed to reveal the underlying molecular mechanism. ResultsWe observed the differential expressions of twelve SSP genes in CRC cell lines, at the transcript level; that of ten genes in early and late stages using cDNA arrays, and nine genes at the protein levels using tissue microarrays and immunohistochemistry. Hispanic CRC samples showed differential expression of all nine SSP genes compared to NHWs, in early-onset, and late-stage CRC, with all genes being upregulated other than CDK4 and PRDX4 in late-stage CRC and CDK4 in early-onset CRC. Our functional study demonstrated that MCM10 knockdown in CRC cell lines significantly reduced cell proliferation, growth, invasion, and migration by inducing cell cycle arrest, apoptosis, and reactive oxygen species pathways. The integrative RNA-sequencing and proteomics study identified that PPFIA1 could be associated with MCM10 mediated cancer progression. The role of MCM10 and PPFIA1 in cancer progression has also been validated by CRISPR-Cas9 mediated MCM10 knock out, using a Hispanic CRC patient derived organoid. ConclusionThe differential expression of SSP genes suggest a potential molecular contribution to CRC disparities in the Hispanic population. The essential oncogenic role of MCM10 and its axis with PPFIA1 was identified; this could lead to a new avenue for therapeutics targeting the MCM10-PPFIA1 axis, thereby, combating early-onset and advanced-stage CRC in this high-risk ethnic group. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=177 HEIGHT=200 SRC="FIGDIR/small/698057v2_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@11528c8org.highwire.dtl.DTLVardef@288d15org.highwire.dtl.DTLVardef@466703org.highwire.dtl.DTLVardef@150890_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

A mouse model of classical trigeminal neuralgia via intradural compression of the trigeminal nerve

IntroductionTrigeminal neuralgia (TN) is a debilitating orofacial pain condition that adversely affects quality of life. Although heterogeneous, the most common form of TN is classical TN, characterized by paroxysmal bouts of pain in response to otherwise innocuous stimuli. It is believed that classical TN results from neurovascular compression of the trigeminal nerve. However, the underlying pathophysiology of TN is not well understood, thus limiting the development of targeted therapies. Current animal models lack translational relevance, particularly in their inability to replicate intradural nerve root compression, a core anatomic component of TN. MethodsWe developed a TN mouse model that achieves intradural nerve root compression via a retro-orbital approach confirmed by anatomic dissection and magnetic resonance imaging. To assess behavioral outcomes, we measured orofacial pain through facial wiping and interaction with a reward stimulus. Pharmacological responsiveness was tested using carbamazepine administration. Mechanistic studies included calcium imaging of trigeminal ganglia (TG), electrophysiologic recordings to measure resting membrane potential and rheobase, and immunohistochemical analysis of the TG. ResultsThe model elicited orofacial neuropathic pain, substantiated by increased facial wiping and reduced interaction with a reward stimulus, behaviors that suggest both spontaneous and evoked pain. Carbamazepine attenuated these behaviors, suggesting pharmacologic relevance to current TN treatment. Calcium imaging showed heightened spontaneous activity in the TG, and electrophysiologic recordings revealed an increased resting membrane potential and a reduced rheobase. Finally, immunohistochemical studies showed infiltration of CD45+ cells, demyelination and an increase in CGRP expression in the TG, supporting the presence of neuroinflammation after nerve root compression. ConclusionThese findings show that our approach replicates the anatomy and clinical presentation of classical TN in humans. This model may represent a new and robust platform for future mechanistic studies of TN and subsequent preclinical evaluation of therapies in mice.

neuroscience↗

bioRxiv2025

Selective Targeting of Kinesin on Lipid Droplets in the Liver Reduces Serum Lipids

The liver controls plasma lipids by secreting lipid-rich very low density lipoproteins (VLDL) into blood. Inside hepatocytes in the liver, Lipid Droplets (LDs) are transported to the smooth Endoplasmic Reticulum (sER) by kinesin-1 motors, and then catabolized in the sER to supply lipids for VLDL assembly. LDs are the only cellular organelle bounded by a phospholipid monolayer, and are thus distinct from all other (bilayer-bounded) organelles. It is therefore plausible that a given protein can bind to the LD membrane using mechanisms that are completely different from all other organelles. Indeed, here we find that kinesin-1 uses its tail domain to bind LDs, but alternative mechanisms to bind other organelles. A peptide corresponding to kinesins tail domain therefore competes with, and removes kinesin-1 selectively from LDs with minimal effect on other organelles. Delivery of lipids for VLDL assembly is consequently reduced, causing a remarkable reduction of [~]50% of secreted lipids (triglycerides and cholesterol) in cell culture. We further develop Orally fed Egg-liposomes as a method to deliver kinesin tail domain peptide to the liver of Zebrafish. The peptide reverses diet-induced hyperlipidaemia in Zebrafish larvae and brings the larvae back to a normolipidaemic state, thus confirming the effectiveness of our method in a physiologically relevant in-vivo situation. Strikingly, the peptide causes no unwanted accumulation of lipids in the liver, no toxicity and no developmental or behavioural defects in Zebrafish. Using a peptide to displace proteins (e.g. kinesin) selectively from LDs provides a conceptually novel and radically different approach against hyperlipidaemia. This monolayer-versus-bilayer strategy can be potentially extended to target other LD-bound proteins that function as key regulators of Lipid metabolism.

cell biology↗

bioRxiv2025

Nona: A unifying multimodal masking framework for functional genomics

The non-coding genome encodes complex regulatory logic that orchestrates gene expression and cell identity. While machine learning models for functional genomics have advanced our understanding of the cis-regulatory code, sequence-to-function models, DNA language models, and generative models have evolved as separate paradigms despite probing the same underlying regulatory biology. We introduce Nona, a multimodal masked modeling framework that unifies these paradigms by learning jointly from DNA sequence and base-resolution functional genomics data. Beyond unifying existing modeling paradigms, Nona enables entirely new modeling objectives. We demonstrate its versatility through three applications: (1) a context-aware sequence-to-function model that improves local predictions by up to 13% by correcting systematic errors in sequence-to-function predictions; (2) a functional language model that integrates functional data into language modeling, learns relevant regulatory sequence motifs, and enables regulatory element design through masked discrete diffusion; (3) functional genotyping, which reveals an unrecognized privacy vulnerability in processed ATAC-seq data and re-identifies individuals from genetic databases with perfect accuracy. Together, these results establish masking as a universal interface for integrated modeling of functional genomics data, unifying disparate approaches while opening new directions for understanding and engineering the regulatory genome.

genomics↗

bioRxiv2025

Linking protein residues in literature and structure

Protein structures are crucial in understanding function, mechanism and disease-causing variants of proteins within any living cell. A number of experimental techniques are employed by researchers to determine said structure. Through structure inspection in molecular viewers combined with supporting biochemical and biophysical experiments, scientists are able to identify a proteins function, reaction mechanism and effects caused by sequence variation. These detailed findings supported by experimental results are documented and described in detail in scientific literature and by open sourcing the accompanying data. By writing a detailed report about the findings and providing evidence in additional files and complementary data formats it has become increasingly difficult for a reader, in particular a non-expert, to access the correct additional information and assess the validity of the drawn conclusion based on experimental results. It often requires a reader to resort to a number of different software packages to access the different data types. Here, we present a first-of-its-kind implementation of an artificial intelligence and text mining supported software tool that allows linking of text mentions of specific protein residues to their corresponding counterpart in the respective protein structure. An identified residue is highlighted in the publication text and upon interaction with the annotation, a molecule viewer displays the associated protein structures in the publication which contain said residue. The viewer is complemented by a display table that contains protein structure quality metrics for each occurrence of a residue. As such a reader can now explore a residue of interest they are currently assessing in a publication within its respective protein structure supported by its experimental evidence in a single view and application.

bioinformatics↗

bioRxiv2025

Large-scale genomic characterisation of phage-plasmids in clinical Enterobacteriaceae isolates

The life cycle of certain bacteriophages involves their maintenance within the bacterial cell as extrachromosomal elements, complete with replication and partitioning systems. These "phage-plasmids" (P-Ps) are distributed widely among bacterial phyla but are not typically included during genomic surveillance studies, and previous reports do not consider the context of their host strain diversity. We recently identified a P1-like P-P carrying the blaCTX-M-15 resistance gene in Salmonella enterica serovar Typhi, prompting a subsequent investigation into the overall frequency of P-Ps among gastrointestinal bacteria under routine genomic surveillance within England. We expanded our study to include P-P groups known to be associated with Enterobacteriaceae (P1, D6, SSU5, N15) and scanned a collection of 66,856 genomes of diarrhoeagenic Escherichia spp., Shigella spp. and S. enterica. All four P-P groups were detected in our dataset, totalling 9% of E. coli and Shigella genomes and 2% of S. enterica genomes. A small subset harboured two distinct P-P groups. P1-like P-Ps, some of which carried a cytotoxic necrotising factor, were predominantly associated with Shiga toxin-producing E. coli strains of public health concern, including clonal complexes CC11 (O157:H7), CC29 (O26:H11) and CC165. In contrast, SSU5 group P-Ps were linked with multidrug-resistant lineages of both S. Typhi and Shigella sonnei. We found multiple antimicrobial resistance genes inserted into P-Ps via transposons, integrons and insertion sequences, and numerous defence/anti-defence systems. There was evidence of vertical transmission but also many links across species, time and geography, indicating that horizontal transfer is occurring regularly. Phage-plasmids are often described only as cryptic elements or not detected during genomic surveillance. We show that P-Ps are associated with clinically relevant lineages of human pathogens and can acquire accessory genes that may impact on disease severity and therefore should play a more prominent role in pathogen surveillance and epidemiology.

genomics↗

bioRxiv2025

Assessing scoring metrics for AlphaFold2 and AlphaFold3 protein complex predictions

1.Recent breakthroughs in AI-driven protein structure prediction have revolutionized structural biology, unlocking new possibilities to model complex biomolecular interactions. We evaluated widely-used scoring metrics for assessing models predicted by ColabFold with templates, ColabFold without templates, and AlphaFold3. We benchmarked the optimal cutoffs for these assessment scores using a set of 223 heterodimeric, high-resolution protein structures and their predictions. Our results show that ColabFold with templates and AlphaFold3 perform similarly and both outperform ColabFold without templates. However, the assessment scores perform best on ColabFold without templates. Furthermore, interface-specific scores are more reliable for evaluating protein complex predictions compared to the corresponding global scores. Notably, ipTM and model confidence achieve the best discrimination between correct and incorrect predictions. Based on our results, we developed a weighted combined score, C2Qscore, to improve model quality assessment. We used C2Qscore to analyse dimers from large assemblies solved by cryoEM, revealing potential limitations of the existing metrics when multiple configurations of heterodimers are possible. This study provides insights into the strengths and weaknesses of current scores and offers guidance for improving protein complex model assessment under realistic use case conditions. C2Qscore has been integrated as a tool into our ChimeraX plug-in PICKLUSTER v.2.0 and is also available as a command-line tool on https://gitlab.com/topf-lab/c2qscore. Impact of this workMany essential cellular functions rely on protein complexes, which are now predominantly predicted using AlphaFold by both experts and non-experts. This study systematically evaluates the performance of multiple widely used scoring metrics for distinguishing accurate from poor predictions. The new C2Qscore developed in this study improves the reliability of AlphaFold model assessments, enabling a more consistent and accessible evaluation of protein structures. These advancements support downstream applications in biomedicine, drug discovery, and computational protein design.

bioinformatics↗

bioRxiv2025

Single-cell multiome and enhancer connectome of human retinal pigment epithelium and choroid nominate pathogenic variants in age-related macular degeneration

Age-related macular degeneration (AMD) is a leading cause of vision loss worldwide. Genome-wide association studies (GWAS) of AMD have identified dozens of risk loci that may house disease targets. However, variants at these loci are largely noncoding, making it difficult to assess their function and whether they are causal. Here, we present a single-cell gene expression and chromatin accessibility atlas of human retinal pigment epithelium (RPE) and choroid to systematically analyze both coding and noncoding variants implicated in AMD. We employ HiChIP and Activity-by-Contact modeling to map enhancers in these tissues and predict cell and gene targets of risk variants. We further perform allele-specific self-transcribing active regulatory region sequencing (STARR-seq) to functionally test variant activity in RPE cells, including in the context of complement activation. Our work nominates new pathogenic variants and mechanisms in AMD and offers a rich and accessible resource for studying diseases of the RPE and choroid.

genomics↗