Attention is all you need: utilizing attention in AI-enabled drug discovery.

Recently, attention mechanism and derived models have gained significant traction in drug development due to their outstanding performance and interpretability in handling complex data structures. This review offers an in-depth exploration of the principles underlying attention-based models and their advantages in drug discovery. We further elaborate on their applications in various aspects of drug development, from molecular screening and target binding to property prediction and molecule generation. Finally, we discuss the current challenges faced in the application of attention mechanisms and Artificial Intelligence technologies, including data quality, model interpretability and computational resource constraints, along with future directions for research. Given the accelerating pace of technological advancement, we believe that attention-based models will have an increasingly prominent role in future drug discovery. We anticipate that these models will usher in revolutionary breakthroughs in the pharmaceutical domain, significantly accelerating the pace of drug development.

RDscan: Extracting RNA-disease relationship from the literature based on pre-training model.

With the rapid advancements in molecular biology and genomics, a multitude of connections between RNA and diseases has been unveiled, making the efficient and accurate extraction of RNA-disease (RD) relationships from extensive biomedical literature crucial for advancing research in this field. This study introduces RDscan, a novel text mining method developed based on the pre-training and fine-tuning strategy, aimed at automatically extracting RD-related information from a vast corpus of literature using pre-trained biomedical large language models (LLM). Initially, we constructed a dedicated RD corpus by manually curating from literature, comprising 2,082 positive and 2,000 negative sentences, alongside an independent test dataset (comprising 500 positive and 500 negative sentences) for training and evaluating RDscan. Subsequently, by fine-tuning the Bioformer and BioBERT pre-trained models, RDscan demonstrated exceptional performance in text classification and named entity recognition (NER) tasks. In 5-fold cross-validation, RDscan significantly outperformed traditional machine learning methods (Support Vector Machine, Logistic Regression and Random Forest). In addition, we have developed an accessible webserver that assists users in extracting RD relationships from text. In summary, RDscan represents the first text mining tool specifically designed for RD relationship extraction, and is poised to emerge as an invaluable tool for researchers dedicated to exploring the intricate interactions between RNA and diseases. Webserver of RDscan is free available at https://cellknowledge.com.cn/RDscan/.

Identification of RNA­dependent liquid­liquid phase separation proteins using an artificial intelligence strategy.

RNA-dependent liquid-liquid phase separation (LLPS) proteins play critical roles in cellular processes such as stress granule formation, DNA repair, RNA metabolism, germ cell development, and protein translation regulation. The abnormal behavior of these proteins is associated with various diseases, particularly neurodegenerative disorders like amyotrophic lateral sclerosis and frontotemporal dementia, making their identification crucial. However, conventional biochemistry-based methods for identifying these proteins are time-consuming and costly. Addressing this challenge, our study developed a robust computational model for their identification. We constructed a comprehensive dataset containing 137 RNA-dependent and 606 non-RNA-dependent LLPS protein sequences, which were then encoded using amino acid composition, composition of K-spaced amino acid pairs, Geary autocorrelation, and conjoined triad methods. Through a combination of correlation analysis, mutual information scoring, and incremental feature selection, we identified an optimal feature subset. This subset was used to train a random forest model, which achieved an accuracy of 90% when tested against an independent dataset. This study demonstrates the potential of computational methods as efficient alternatives for the identification of RNA-dependent LLPS proteins. To enhance the accessibility of the model, a user-centric web server has been established and can be accessed via the link: http://rpp.lin-group.cn.

PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization.

Many studies have proved that small nucleolar RNAs (snoRNAs) play critical roles in the development of various human complex diseases. Discovering the associations between snoRNAs and diseases is an important step toward understanding the pathogenesis and characteristics of diseases. However, uncovering associations via traditional experimental approaches is costly and time-consuming. This study proposed a bounded nuclear norm regularization-based method, called PSnoD, to predict snoRNA-disease associations. Benchmark experiments showed that compared with the state-of-the-art methods, PSnoD achieved a superior performance in the 5-fold stratified shuffle split. PSnoD produced a robust performance with an area under receiver-operating characteristic of 0.90 and an area under precision-recall of 0.55, highlighting the effectiveness of our proposed method. In addition, the computational efficiency of PSnoD was also demonstrated by comparison with other matrix completion techniques. More importantly, the case study further elucidated the ability of PSnoD to screen potential snoRNA-disease associations. The code of PSnoD has been uploaded to https://github.com/linDing-groups/PSnoD. Based on PSnoD, we established a web server that is freely accessed via http://psnod.lin-group.cn/.

iLoc-miRNA: extracellular/intracellular miRNA prediction using deep BiLSTM with attention mechanism.

The location of microRNAs (miRNAs) in cells determines their function in regulation activity. Studies have shown that miRNAs are stable in the extracellular environment that mediates cell-to-cell communication and are located in the intracellular region that responds to cellular stress and environmental stimuli. Though in situ detection techniques of miRNAs have made great contributions to the study of the localization and distribution of miRNAs, miRNA subcellular localization and their role are still in progress. Recently, some machine learning-based algorithms have been designed for miRNA subcellular location prediction, but their performance is still far from satisfactory. Here, we present a new data partitioning strategy that categorizes functionally similar locations for the precise and instructive prediction of miRNA subcellular location in Homo sapiens. To characterize the localization signals, we adopted one-hot encoding with post padding to represent the whole miRNA sequences, and proposed a deep bidirectional long short-term memory with the multi-head self-attention algorithm to model. The algorithm showed high selectivity in distinguishing extracellular miRNAs from intracellular miRNAs. Moreover, a series of motif analyses were performed to explore the mechanism of miRNA subcellular localization. To improve the convenience of the model, a user-friendly web server named iLoc-miRNA was established (http://iLoc-miRNA.lin-group.cn/).

ViRBase v3.0: a virus and host ncRNA-associated interaction repository with increased coverage and annotation.

As a means to aid in the investigation of viral infection mechanisms and identification of more effective antivirus targets, the availability of a source which continually collects and updates information on the virus and host ncRNA-associated interaction resources is essential. Here, we update the ViRBase database to version 3.0 (http://www.virbase.org/ or http://www.rna-society.org/virbase/). This update represents a major revision: (i) the total number of interaction entries is now greater than 820,000, an approximately 70-fold increment, involving 116 virus and 36 host organisms, (ii) it supplements and provides more details on RNA annotations (including RNA editing, RNA localization and RNA modification), ncRNA SNP and ncRNA-drug related information and (iii) it provides two additional tools for predicting binding sites (IntaRNA and PRIdictor), a visual plug-in to display interactions and a website which is optimized for more practical and user-friendly operation. Overall, ViRBase v3.0 provides a more comprehensive resource for virus and host ncRNA-associated interactions enabling researchers a more effective means for investigation of viral infections.

RNAPhaSep: a resource of RNAs undergoing phase separation.

Liquid-liquid phase separation (LLPS) partitions cellular contents, underlies the formation of membraneless organelles and plays essential biological roles. To date, most of the research on LLPS has focused on proteins, especially RNA-binding proteins. However, accumulating evidence has demonstrated that RNAs can also function as 'scaffolds' and play essential roles in seeding or nucleating the formation of granules. To better utilize the knowledge dispersed in published literature, we here introduce RNAPhaSep (http://www.rnaphasep.cn), a manually curated database of RNAs undergoing LLPS. It contains 1113 entries with experimentally validated RNA self-assembly or RNA and protein co-involved phase separation events. RNAPhaSep contains various types of information, including RNA information, protein information, phase separation experiment information and integrated annotation from multiple databases. RNAPhaSep provides a valuable resource for exploring the relationship between RNA properties and phase behaviour, and may further enhance our comprehensive understanding of LLPS in cellular functions and human diseases.

Temporal Control of Fluorescent EuW10 Aggregates for Autonomous DNA Capture and Information Encryption.

Self-assembly exploits noncovalent interaction to offer an effective method for the fabrication of materials. For Na9 [EuW10 O36 ] ⋅ 32H2 O (EuW10 ), the negative charges and abundant oxygen atoms on its surface provide a handle for static self-assembly. New properties are envisioned for EuW10 aggregates which are able to display such kinetics and time-programming characteristics, in order to satisfy more complex and intelligent application scenarios, such as DNA binding and information encryption. In this work, EuW10 coupling with stimuli-responsive dodecyl dimethylamine oxide (C12 DMAO) can generate versatile aggregates with pH-responsive properties. We demonstrated the temporal programming of the assembly and disassembly of EuW10 nanospheres using a pH clock reaction of acid/urease hydrolysis. The pH clock reaction endows EuW10 assemblies with dynamical properties, in which the charges and fluorescence changes are coded in this system. These fluorescent assemblies provide new application in time-programmed DNA capture and information encryption.

Optical control of fast and processive engineered myosins in vitro and in living cells.

Precision tools for spatiotemporal control of cytoskeletal motor function are needed to dissect fundamental biological processes ranging from intracellular transport to cell migration and division. Direct optical control of motor speed and direction is one promising approach, but it remains a challenge to engineer controllable motors with desirable properties such as the speed and processivity required for transport applications in living cells. Here, we develop engineered myosin motors that combine large optical modulation depths with high velocities, and create processive myosin motors with optically controllable directionality. We characterize the performance of the motors using in vitro motility assays, single-molecule tracking and live-cell imaging. Bidirectional processive motors move efficiently toward the tips of cellular protrusions in the presence of blue light, and can transport molecular cargo in cells. Robust gearshifting myosins will further enable programmable transport in contexts ranging from in vitro active matter reconstitutions to microfabricated systems that harness molecular propulsion.

MNDR v3.0: mammal ncRNA-disease repository with increased coverage and annotation.

Many studies have indicated that non-coding RNA (ncRNA) dysfunction is closely related to numerous diseases. Recently, accumulated ncRNA-disease associations have made related databases insufficient to meet the demands of biomedical research. The constant updating of ncRNA-disease resources has become essential. Here, we have updated the mammal ncRNA-disease repository (MNDR, http://www.rna-society.org/mndr/) to version 3.0, containing more than one million entries, four-fold increment in data compared to the previous version. Experimental and predicted circRNA-disease associations have been integrated, increasing the number of categories of ncRNAs to five, and the number of mammalian species to 11. Moreover, ncRNA-disease related drug annotations and associations, as well as ncRNA subcellular localizations and interactions, were added. In addition, three ncRNA-disease (miRNA/lncRNA/circRNA) prediction tools were provided, and the website was also optimized, making it more practical and user-friendly. In summary, MNDR v3.0 will be a valuable resource for the investigation of disease mechanisms and clinical treatment strategies.

CellCall: integrating paired ligand-receptor and transcription factor activities for cell-cell communication.

With the dramatic development of single-cell RNA sequencing (scRNA-seq) technologies, the systematic decoding of cell-cell communication has received great research interest. To date, several in-silico methods have been developed, but most of them lack the ability to predict the communication pathways connecting the insides and outsides of cells. Here, we developed CellCall, a toolkit to infer inter- and intracellular communication pathways by integrating paired ligand-receptor and transcription factor (TF) activity. Moreover, CellCall uses an embedded pathway activity analysis method to identify the significantly activated pathways involved in intercellular crosstalk between certain cell types. Additionally, CellCall offers a rich suite of visualization options (Circos plot, Sankey plot, bubble plot, ridge plot, etc.) to present the analysis results. Case studies on scRNA-seq datasets of human testicular cells and the tumor immune microenvironment demonstrated the reliable and unique functionality of CellCall in intercellular communication analysis and internal TF activity exploration, which were further validated experimentally. Comparative analysis of CellCall and other tools indicated that CellCall was more accurate and offered more functions. In summary, CellCall provides a sophisticated and practical tool allowing researchers to decipher intercellular communication and related internal regulatory signals based on scRNA-seq data. CellCall is freely available at https://github.com/ShellyCoder/cellcall.

cncRNAdb: a manually curated resource of experimentally supported RNAs with both protein-coding and noncoding function.

RNA endowed with both protein-coding and noncoding functions is referred to as 'dual-function RNA', 'binary functional RNA (bifunctional RNA)' or 'cncRNA (coding and noncoding RNA)'. Recently, an increasing number of cncRNAs have been identified, including both translated ncRNAs (ncRNAs with coding functions) and untranslated mRNAs (mRNAs with noncoding functions). However, an appropriate database for storing and organizing cncRNAs is still lacking. Here, we developed cncRNAdb, a manually curated database of experimentally supported cncRNAs, which aims to provide a resource for efficient manipulation, browsing and analysis of cncRNAs. The current version of cncRNAdb documents about 2600 manually curated entries of cncRNA functions with experimental evidence, involving more than 2,000 RNAs (including over 1300 translated ncRNAs and over 600 untranslated mRNAs) across over 20 species. In summary, we believe that cncRNAdb will help elucidate the functions and mechanisms of cncRNAs and develop new prediction methods. The database is available at http://www.rna-society.org/cncrnadb/.

Associations between body circumference and testosterone levels and risk of metabolic dysfunction-associated fatty liver disease: a mendelian randomization study.

BACKGROUD: Body circumference and testosterone levels have been reported as associated with metabolic dysfunction-associated fatty liver disease (MAFLD) risk. However, whether body circumference and testosterone levels play a role in the development of MAFLD remains inconclusive. METHODS: Using a large database of genome-wide association studies, genetic loci that are independent of each other and strongly associated with body circumference and testosterone levels were selected as instrumental variables, the causal relationship between body circumference and testosterone and risk of MAFLD was investigated by two-sample Mendelian randomization methods such as inverse variance weighted (IVW), MR-Egger regression, and weighted median estimator (WME), using the odds ratios (ORs) as evaluation indicators. RESULTS: A total of 344 SNPs were included as instrumental variables in this study, including 180 for waist circumference, 29 for waist-to-hip ratio, and 135 for testosterone levels. Using the above two-sample Mendelian Randomization method to derive the causal association between exposure and outcome. The results of this study showed that three exposure factors were causally associated with the risk of MAFLD. Waist circumference obtained three statistically significant results for IVW, WME and Weighted mode (IVW: OR = 3.53, 95%CI: 2.23-5.57, P < 0.001; WME: OR = 3.88, 95%CI: 1.81-8.29, P < 0.001; Weighted mode: OR = 3.58, 95%CI: 1.05-12.16, P = 0.043). Waist-to-hip ratio obtained one statistically significant result for IVW (OR = 2.29, 95%CI: 1.12-4.66, P = 0.022). Testosterone levels obtained one statistically significant result for IVW (OR = 1.93, 95%CI: 1.30-2.87, P = 0.001). Waist circumference, waist-to-hip ratio and testosterone level were considered as risk factors for MAFLD. The Cochran Q test for IVW and MR-Egger method indicated that there was no intergenic heterogeneity in SNPs. The test for pleiotropy indicated that the possibility of pleiotropy in the causal analysis was weak. CONCLUSION: The results of the two-sample Mendelian randomization analysis showed that waist circumference was the exact risk factor for MAFLD, waist-to-hip ratio and testosterone levels were potential risk factors for MAFLD, the risk of developing MAFLD increases with these three exposure factors.

A quantitative study of airway ultrasound in predicting difficult laryngoscopy: A prospective study.

PURPOSE: As common clinical screening tests cannot effectively predict a difficult airway, and unanticipated difficult laryngoscopy remains a challenge for physicians. We herein used ultrasound to develop some point-of-care predictors for difficult laryngoscopy. METHODS: This prospective observational study included 502 patients who underwent laryngoscopy and a detailed sonographic assessment. Patients under 18 years old, or with maxillofacial deformities or fractures, limited mouth opening, limited neck movement or history of neck surgery were excluded from the study. Laryngoscopic views of all patients were scored and grouping using the modified Cormack-Lehane (CL) scoring system. The measurements acquired comprised tongue width, the longitudinal cross-sectional area of the tongue, tongue volume, the mandible-hyoid bone distance, the hyoid bone-glottis distance, the mandible-hyoid bone-glottis angle, the skin-thyrohyoid membrane distance, the glottis-superior edge of the thyroid cartilage distance (DGTC), the skin-hyoid bone distance, and the epiglottis midway-skin distance. ANOVA and Chi-square were used to compare differences between groups. Logistic regression was used to identify risk factors for difficult laryngoscopy and it was visualized by receiver operating characteristic curves and nomogram. R version 3.6.3 and SPSS version 26.0 were used for statistical analyses. RESULTS: Difficult laryngoscopy was indicated in 49 patients (CL grade Ⅲ - Ⅳ) and easy laryngoscopy in 453 patients (CL grade Ⅰ - Ⅱ). The ultrasound-measured mandible-hyoid bone-glottis angle and DGTC significantly differed between the 2 groups (p < 0.001). Difficult laryngoscopy was predicted by an area under the curve (AUC) of 0.930 with a threshold mandible-hyoid bone-glottis angle of 125.5° and by an AUC of 0.722 with a threshold DGTC of 1.22 cm. The longitudinal cross-sectional area of the tongue, tongue width, tongue volume, the mandible-hyoid distance, and the hyoid-glottis distance did not significantly differ between the groups. CONCLUSION: Difficult laryngoscopy may be anticipated in patients in whom the mandible-hyoid bone-glottis angle is smaller than 125.5° or DGTC is larger than 1.22 cm.

Cellinker: a platform of ligand-receptor interactions for intercellular communication analysis.

MOTIVATION: Ligand-receptor (L-R) interactions mediate cell adhesion, recognition and communication and play essential roles in physiological and pathological signaling. With the rapid development of single-cell RNA sequencing (scRNA-seq) technologies, systematically decoding the intercellular communication network involving L-R interactions has become a focus of research. Therefore, construction of a comprehensive, high-confidence and well-organized resource to retrieve L-R interactions in order to study the functional effects of cell-cell communications would be of great value. RESULTS: In this study, we developed Cellinker, a manually curated resource of literature-supported L-R interactions that play roles in cell-cell communication. We aimed to provide a useful platform for studies on cell-cell communication mediated by L-R interactions. The current version of Cellinker documents over 3,700 human and 3,200 mouse L-R protein-protein interactions (PPIs) and embeds a practical and convenient webserver with which researchers can decode intercellular communications based on scRNA-seq data. And over 400 endogenous small molecule (sMOL) related L-R interactions were collected as well. Moreover, to help with research on coronavirus (CoV) infection, Cellinker collects information on 16 L-R PPIs involved in CoV-human interactions (including 12 L-R PPIs involved in SARS-CoV-2 infection). In summary, Cellinker provides a user-friendly interface for querying, browsing and visualizing L-R interactions as well as a practical and convenient web tool for inferring intercellular communications based on scRNA-seq data. We believe this platform could promote intercellular communication research and accelerate the development of related algorithms for scRNA-seq studies. AVAILABILITY: Cellinker is available at http://www.rna-society.org/cellinker/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Kinase pathway inhibition restores PSD95 induction in neurons lacking fragile X mental retardation protein.

Fragile X syndrome (FXS) is the leading monogenic cause of autism and intellectual disability. FXS is caused by loss of expression of fragile X mental retardation protein (FMRP), an RNA-binding protein that regulates translation of numerous mRNA targets, some of which are present at synapses. While protein synthesis deficits have long been postulated as an etiology of FXS, how FMRP loss affects distributions of newly synthesized proteins is unknown. Here we investigated the role of FMRP in regulating expression of new copies of the synaptic protein PSD95 in an in vitro model of synaptic plasticity. We find that local BDNF application promotes persistent accumulation of new PSD95 at stimulated synapses and dendrites of cultured neurons, and that this accumulation is absent in FMRP-deficient mouse neurons. New PSD95 accumulation at sites of BDNF stimulation does not require known mechanisms regulating FMRP-mRNA interactions but instead requires the PI3K-mTORC1-S6K1 pathway. Surprisingly, in FMRP-deficient neurons, BDNF induction of new PSD95 accumulation can be restored by mTORC1-S6K1 blockade, suggesting that constitutively high mTORC1-S6K1 activity occludes PSD95 regulation by BDNF and that alternative pathways exist to mediate induction when mTORC1-S6K1 is inhibited. This study provides direct evidence for deficits in local protein synthesis and accumulation of newly synthesized protein in response to local stimulation in FXS, and supports mTORC1-S6K1 pathway inhibition as a potential therapeutic approach for FXS.

Albumin-to-alkaline phosphatase ratio as a predictor of tumor recurrence and prognosis in patients with early-stage hepatocellular carcinoma undergoing radiofrequency ablation as initial therapy.

OBJECTIVE: Albumin-to-alkaline phosphatase ratio (AAPR), a newly developed blood biomarker, has been reported to have prognostic value in several types of cancer. This study aimed to investigate the predictive value of AAPR in patients with early-stage hepatocellular carcinoma (HCC) undergoing radiofrequency ablation (RFA) as initial therapy. METHODS: This retrospective study analyzed 445 patients with newly diagnosed HCC undergoing RFA as initial therapy. A series of survival analyses were performed to evaluate the prognostic value of AAPR. Univariate and multivariate analyses were performed to identify independent prognostic factors. An AAPR-based nomogram was constructed, and its predictive performance was validated. RESULTS: Patients with a low AAPR had a significantly reduced recurrence-free survival (RFS) and overall survival (OS) compared with those with a high AAPR. AAPR was found to be an independent prognostic indicator and showed superior discrimination efficacy than other liver function indices. The AAPR-based nomogram had a concordance index value of 0.72 (95% confidence interval [CI]: 0.65-0.79) in the training cohort and 0.72 (95% CI: 0.63-0.81) in the validation cohort, which significantly outperformed other existing staging systems. CONCLUSIONS: AAPR serves as a promising indicator of prognosis in patients with early-stage HCC undergoing RFA. The AAPR-based nomogram might contribute to individualized prognosis prediction and clinical decision making.

Exploration of invasive mechanisms via global ncRNA-associated virus-host crosstalk.

Viral infection is a complex pathogenesis and the underlying molecular mechanisms remain poorly understood. In this study, an integrated multiple resources analysis was performed and showed that the cellular ncRNAs and proteins targeted by viruses were primarily "hubs" and "bottlenecks" in the human ncRNA/protein-protein interaction. The common proteins targeted by both viral ncRNAs and proteins tended to skew toward higher degrees and betweenness compared with other proteins, showed significant enrichment in the cell death process. Specifically, >800 pairs of human cellular ncRNAs and viral ncRNAs that exhibited a high degree of functional homology were identified, representing potential ncRNA-mediated co-regulation patterns of viral invasion. Additionally, clustering analysis further revealed several distinct viral clusters with obvious functional divergence. Overall, this is the first attempt to systematically explore the invasive mechanism via global ncRNA-associated virus-host crosstalk. Our results provide useful information in comprehensively understanding the viral invasive mechanism.

RIscoper: a tool for RNA-RNA interaction extraction from the literature.

MOTIVATION: Numerous experimental and computational studies in the biomedical literature have provided considerable amounts of data on diverse RNA-RNA interactions (RRIs). However, few text mining systems for RRIs information extraction are available. RESULTS: RNA Interactome Scoper (RIscoper) represents the first tool for full-scale RNA interactome scanning and was developed for extracting RRIs from the literature based on the N-gram model. Notably, a reliable RRI corpus was integrated in RIscoper, and more than 13 300 manually curated sentences with RRI information were recruited. RIscoper allows users to upload full texts or abstracts, and provides an online search tool that is connected with PubMed (PMID and keyword input), and these capabilities are useful for biologists. RIscoper has a strong performance (90.4% precision and 93.9% recall), integrates natural language processing techniques and has a reliable RRI corpus. AVAILABILITY AND IMPLEMENTATION: The standalone software and web server of RIscoper are freely available at www.rna-society.org/riscoper/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Structural and Functional Insights into PpgL, a Metal-Independent ß-Propeller Gluconolactonase That Contributes to Pseudomonas aeruginosa Virulence.

Biofilm formation is a critical determinant in the pathopoiesis of Pseudomonas aeruginosa It could significantly increase bacterial resistance to drugs and host defense. Thus, inhibition of biofilm matrix production could be regarded as a promising attempt to prevent colonization of P. aeruginosa and the subsequent infection. PpgL, a periplasmic gluconolactonase, has been reported to be involved in P. aeruginosa quorum-sensing (QS) system regulation. However, the detailed function and catalysis mechanism remain elusive. Here, the crystal structure of PpgL is described in the current study, along with biochemical analysis, revealing that PpgL is a typical ß-propeller enzyme with unique metal-independent lactone hydrolysis activity. Consequently, comparative analysis of seven-bladed propeller lactone-catalyzing enzymes and mutagenesis studies identify the critical sites which contribute to the diverse catalytic and substrate recognition functions. In addition, the reduced biofilm formation and attenuated invasion phenotype resulting from deletion of ppgL confirm the importance of PpgL in P. aeruginosa pathogenesis. These results suggest that PpgL is a potential target for developing new agents against the diseases caused by P. aeruginosa.