Computational Study Identifies Three Drug Targets for Persistent Oral Pathogen Olsenella uli

A computational subtractive proteomics study has uncovered three high-affinity enzyme targets within the oral bacterium Olsenella uli DSM 7084, offering a structured blueprint for developing targeted antimicrobials against treatment-resistant endodontic infections. Published in Discover Bacteria, the investigation applied an in silico pipeline to screen the pathogen’s complete proteome against human metabolic pathways, bacterial essentiality databases, and pharmaceutical chemical libraries. Persistent root canal pathologies and periapical periodontitis frequently recur because recalcitrant anaerobic bacteria endure chemo-mechanical instrumentation and intracanal medicaments. By cataloging the metabolic machinery that allows this gram-positive rod to survive inside cleaned root canals while comparing it against host biochemistry, researchers mapped twenty-one strain-specific metabolic pathways that operate independently of human biology.

The biological challenge presented by Olsenella uli stems directly from its specialized survival capabilities within instrumented root canal spaces. In post-treatment endodontic environments subjected to chemo-mechanical debridement, Olsenella uli frequently predominates over other gram-positive rods, including Atopobium parvulum, demonstrating an intrinsic capacity to withstand standard disinfectant protocols. Belonging to the family Coriobacteriaceae, Olsenella uli occupies an ecological niche that encompasses both coronal and root caries, periapical lesions, and advanced periodontal pockets alongside other oral pathogens like Streptococcus mutans, Porphyromonas gingivalis, and Prevotella intermedia. To address this clinical limitation, the research team designed a multi-phase bioinformatics framework aimed at pinpointing narrow-spectrum molecular targets whose inhibition would selectively eliminate Olsenella uli without inducing off-target cytotoxicity in human host tissues.

To establish the non-homologous foundation of the target screening pipeline, the authors cross-referenced the complete metabolic pathways of Olsenella uli DSM 7084 and Homo sapiens using the Kyoto Encyclopedia of Genes and Genomes database. This initial comparative mapping revealed twenty-one unique, strain-specific metabolic pathways present exclusively in the bacterial pathogen and absent in human cellular architecture. The protein sequences corresponding to the genes within these pathogen-specific pathways were retrieved in FASTA format from the National Center for Biotechnology Information. A two-phase sequence similarity analysis was subsequently conducted to ensure complete host non-homology and absolute bacterial essentiality. In the first phase, BLASTP sequence alignment was executed against the non-redundant human proteome applying strict exclusion criteria, including an expectation value threshold of 0.005, a sequence identity cutoff of 35 percent or lower, and a minimum bit score of 100. Proteins passing this initial filter were verified as non-homologous, substantially lowering the theoretical probability of autoimmune cross-reactivity or clinical side effects in host tissues during downstream pharmaceutical intervention.

Following host non-homology verification, the remaining bacterial sequences entered the second phase of subtractive screening, where essentiality was established against the Database of Essential Genes. Essential genes are functionally indispensable for basic cellular survival, reproduction, and metabolic integrity across prokaryotic and eukaryotic organisms. Conducting a microbial BLASTP comparison with a rigorous expectation value cutoff of 10 to the power of negative 10 and a minimum bit score of 100 revealed fourteen non-homologous essential proteins indispensable for the physiological viability of Olsenella uli DSM 7084. Because traditional drug discovery timelines commonly span ten to fifteen years and incur high financial burdens, identifying indispensable proteins computationally narrows down potential candidates early in the investigative process.

The fourteen prioritized essential proteins were then evaluated through in silico physicochemical profiling using the ProtParam bioinformatics analytical suite. This evaluation computed fundamental parameters including theoretical isoelectric point, molecular weight, instability index, aliphatic index, and the grand average of hydropathicity to determine which candidates possess adequate stability for biochemical assaying and drug development. The analysis indicated that the majority of the proteins exhibited acidic or nearly neutral electrical characteristics, with theoretical isoelectric points ranging between 4.66 and 6.58. The aliphatic index, which quantifies the relative structural volume occupied by aliphatic side chains such as alanine, valine, isoleucine, and leucine, fell between 70.0 and 102.64 across the screened sequences. These high aliphatic index values reflect strong intrinsic thermostability and a substantial proportion of hydrophobic amino acids, creating an amphipathic structure where hydrophobic domains coexist alongside charged, polar residues. Importantly, the computed instability index confirmed that eight of the fourteen essential proteins maintained values below the threshold of 40, verifying them as thermodynamically stable in vitro targets suitable for druggability screening.

The eight stable, non-homologous essential proteins next underwent druggability and subcellular localization assessments to identify candidates compatible with known chemical scaffolds and clinical delivery routes. Druggability was evaluated through sequence alignment against DrugBank version 4.3 using default parameters, screening entries that encompass Food and Drug Administration approved small molecules, peptide-based biotechnological drugs, nutraceutical formulations, and experimental compounds. This step categorized proteins matching existing database entries as established druggable targets, while non-matching sequences were classified as novel targets requiring de novo screening. Simultaneously, the biological distribution of the eight proteins was predicted using the CELLO version 2.5 multi-class support vector machine classification system. The localization output revealed that the majority of the screened enzymes reside within the bacterial cytoplasm.

To enable molecular interaction modeling, three-dimensional structures of the prioritized targets were constructed using the iterative threading assembly refinement platform known as I-TASSER. Operating under default configurations to avoid subjective template bias, I-TASSER dynamic simulation trajectories generated structural coordinates alongside built-in confidence indicators, including C-scores ranging between negative 5 and 2, where elevated scores designate high-confidence structural models. Alongside tertiary structure generation, phyletic profiling was conducted using BLASTP against related bacterial proteomes to determine the conservation of each candidate. The comparative profiling revealed that four of the eight targets—MurD, MurA, Alr, and MurI—are universally conserved across related oral anaerobic pathogens, indicating strong evolutionary maintenance. The authors noted that universally conserved targets support broad-spectrum anaerobic therapy, whereas ThiD provides a specialized avenue for narrow-spectrum, precision inhibition of Olsenella uli.

Molecular docking simulations were subsequently carried out on the eight prioritized targets using AutoDock version 4.2 to quantify binding interactions with corresponding DrugBank compounds retrieved from PubChem. Protein coordinate files were converted to PDBQT format by assigning Kollman charges and polar hydrogens, and three-dimensional grids measuring 70 by 70 by 70 points were centered over catalytic binding pockets mapped by PockDrug software. The Lamarckian genetic algorithm performed thirty independent docking runs per complex with a population size of 150, crossover rate of 0.8, mutation rate of 0.02, 27,000 generations, and 2,500,000 maximized energy evaluations. To prioritize complexes demonstrating robust physiological inhibition, a stringent binding energy threshold of negative 8.0 kilocalories per mole was applied. Interactions surpassing this benchmark are widely recognized as indicating stable, high-affinity binding configurations. Three top-performing complexes cleared this threshold: UDP-N-acetylglucosamine-1-carboxyvinyltransferase, UDP-N-acetylmuramoylalanine-D-glutamate ligase, and alanine racemase, demonstrating exceptional predicted affinity for their respective docked ligands.

Among the top-performing interactions, UDP-N-acetylglucosamine-1-carboxyvinyltransferase, commonly designated as MurA, achieved the lowest binding energy of negative 9.66 kilocalories per mole when docked with Uridine-Diphosphate-N-Acetylglucosamine. Detailed residue analysis identified major hydrogen bonds linking the ligand’s benzene ring hydroxyl group and phenyl ring to the protein main chain at glutamine 297, proline 300, glutamine 311, and aspartate 321, with valine 214 and arginine 224 acting as critical active-site contact residues. The second complex, UDP-N-acetylmuramoylalanine-D-glutamate ligase or MurD, achieved a binding energy of negative 9.16 kilocalories per mole with Uridine-5′-Diphosphate-N-Acetylmuramoyl-L-Alanine. MurD catalyzes the addition of meso-diaminopimelic acid during cell-wall assembly; docking showed glycine 203, serine 232, arginine 277, and alanine 280 interacting with the ligand’s nucleosyl and hydroxyl moieties, alongside hydrogen bonds with serine 281.

The identification of MurA, MurD, and alanine racemase underscores a functional concentration within the bacterial peptidoglycan assembly cascade. Peptidoglycan synthesis is completely absent from human host cells, substantially minimizing the danger of mechanism-based pharmaceutical toxicity or off-target clinical effects. In Actinobacteria and related taxa, the absence of functional redundancy across the Mur catalytic pathway reinforces its attractiveness as an antibacterial target, as bacteria cannot readily bypass Mur pathway inhibition without accumulating costly fitness mutations in conserved catalytic residues. Despite these favorable in silico energetic profiles and structural binding alignments, the study authors emphasize that all reported findings remain entirely computational. Because the predictive models, docking scores, and binding affinities were derived through computational simulations, comprehensive wet-lab validation and in vitro microbiological testing remain essential requirements to confirm active-site inhibition, evaluate compound stability, and establish antimicrobial efficacy against living cultures of Olsenella uli DSM 7084.

Subject of Research: Subtractive proteomics and drug target identification for Olsenella uli

Article Title: Exploration of the proteome of Olsenella uli DSM 7084 to identify potential drug targets against oral infections

Article References: Akhtar, M. S., Talat, A., Bhardwaj, T., Alsahag, M., Alisaac, A., Ali, N. M., Ahmad, A., Zamzami, M. A., Choudhry, H., & Qadri, I. (2026). Exploration of the proteome of Olsenella uli DSM 7084 to identify potential drug targets against oral infections. Discover Bacteria, 3(1), Article 1. https://doi.org/10.1007/s44351-025-00038-2

Image Credits: AI Generated

DOI: 10.1007/s44351-025-00038-2

Keywords: Olsenella uli, subtractive proteomics, endodontic infections, drug target discovery, molecular docking, alanine racemase, peptidoglycan biosynthesis, AutoDock, I-TASSER, DrugBank, Database of Essential Genes, Coriobacteriaceae, UDP-N-acetylglucosamine-1-carboxyvinyltransferase, UDP-N-acetylmuramoylalanine-D-glutamate ligase, antimicrobial resistance, CELLO subcellular localization, ProtParam