Article
Biochemical Research Methods
Yiyan Yang, Xiaofang Jiang
Summary: In this study, a method called Evolink was developed to rapidly identify genotypes associated with phenotypes in large-scale multispecies microbial datasets. Compared with other similar tools, Evolink consistently performed well in terms of precision, sensitivity, and computation time when applied to simulated and real-world flagella datasets. The application of Evolink on flagella and gram-staining datasets revealed findings consistent with known markers and supported by the literature. Overall, Evolink has the potential to be widely used for identifying gene families associated with traits of interest.
Article
Chemistry, Multidisciplinary
Bryan Dafniet, Natacha Cerisier, Batiste Boezio, Anaelle Clary, Pierre Ducrot, Thierry Dorval, Arnaud Gohier, David Brown, Karine Audouze, Olivier Taboureau
Summary: An integrated system pharmacology network and a chemogenomic library of 5000 small molecules have been developed to assist in target identification and mechanism deconvolution in phenotypic assays. This platform showcases the potential of combining advanced technologies in drug discovery.
JOURNAL OF CHEMINFORMATICS
(2021)
Article
Microbiology
Caitlin M. A. Simopoulos, Zhibin Ning, Leyuan Li, Mona M. Khamis, Xu Zhang, Mathieu Lavallee-Adam, Daniel Figeys
Summary: Metaproteomics is a useful tool for studying microbial communities, but the data acquisition process can be time-consuming and resource-intensive. In this study, the researchers developed a computational framework called MetaProClust-MS1 to prioritize samples for follow-up analysis using tandem mass spectrometry (MS/MS). The framework successfully identified microbial responses and disease diagnostic features in gut microbiome data. The study also demonstrated the potential of MetaProClust-MS1 in clinical settings and large-scale metaproteomic screening.
Article
Biotechnology & Applied Microbiology
Marjan Barazandeh, Divya Kriti, Corey Nislow, Guri Giaever
Summary: Chemogenomic profiling is a powerful method for studying the cellular response to small molecules. This study analyzed two large yeast chemogenomic datasets and found robust chemogenomic response signatures, providing further support for their biological relevance.
Article
Biochemistry & Molecular Biology
Kaiyang Liu, Xi Chen, Yue Ren, Chaoqun Liu, Tianyi Lv, Ya'nan Liu, Yanling Zhang
Summary: Polypharmacology has emerged as a new paradigm in drug discovery, playing a crucial role in addressing polygenic diseases. This paper introduces multi-target-based polypharmacology prediction (mTPP), an approach that employs virtual screening and machine learning to explore the relationship between the action of multiple targets and the overall efficacy of drugs. Through the mTPP model, potential hepatoprotective components and candidates with potential effects against drug-induced liver injury (DILI) are identified. The model demonstrates accuracy in predicting the viabilities of APAP-induced injury cells, indicating its potential for aiding the development of polypharmacology and the discovery of multi-target drugs.
CHEMICO-BIOLOGICAL INTERACTIONS
(2022)
Article
Biochemical Research Methods
Giulia Muzio, Leslie O'Bray, Laetitia Meng-Papaxanthos, Juliane Klatt, Krista Fischer, Karsten Borgwardt
Summary: Network-based genome-wide association studies aim to identify associations between genetic markers and complex traits by aggregating the effects of multiple markers and testing entire genes, pathways, or networks. However, current approaches have limitations such as greedy feature selection and lack of multiple testing correction. To address these issues, this study proposes networkGWAS, a computationally efficient and statistically reliable method that combines mixed models and neighborhood aggregation for network-based genome-wide association studies.
Article
Cardiac & Cardiovascular Systems
Bang Truong, Lori Hornsby, Brent I. Fox, Chiahung Chou, Jingyi Zheng, Jingjing Qian
Summary: A pharmacovigilance study was conducted to assess the drug-drug interactions (DDIs) between direct oral anticoagulants (DOACs) and antineoplastic agents. The results showed that there was no signal of DDIs, except for DOAC-neratinib combination. The concern regarding potential DDIs between DOACs and antineoplastic treatments may be unnecessary.
JOURNAL OF THROMBOSIS AND THROMBOLYSIS
(2023)
Article
Microbiology
Balaji Sundararaman, Matthew D. Sylvester, Varvara K. Kozyreva, Zenda L. Berrada, Russell B. Corbett-Detig, Richard E. Green
Summary: Genomic epidemiology uses pathogens' whole-genome sequences to understand and manage the spread of infectious diseases. We developed a cost-effective method called CNERs to generate whole-genome enrichment probes, which successfully enriched Mycobacterium tuberculosis DNA and demonstrated its utility for lineage identification and drug-resistance characterization.
Article
Oncology
Norah A. Alturki, Mutaib M. Mashraqi, Khurshid Jalal, Kanwal Khan, Zarrin Basharat, Ahmad Alzamami
Summary: This study aims to identify important drug targets from the core genome of colorectal cancer associated F. nucleatum and validate the inhibition stability through bioinformatics and dynamics simulation approaches. The findings have implications for researchers working on colorectal cancer, its microbiome, and potential treatments.
Article
Multidisciplinary Sciences
Douglas O. Ochora, Reagan M. Mogire, Rael J. Masai, Redemptah A. Yeda, Edwin W. Mwakio, Joseph G. Amwoma, Dancan M. Wakoli, Abiy Yenesew, Hoseah M. Akala
Summary: This study tested the antiplasmodial activities of approved drugs using a target-similarity approach and found that some of these drugs showed excellent antiplasmodial activity, indicating their potential as antimalarials.
Article
Biotechnology & Applied Microbiology
Laura Raniere Borges dos Anjos, Vinicius Alexandre Fiaia Costa, Bruno Junior Neves, Ana Paula Junqueira-Kipnis, Andre Kipnis
Summary: In silico chemogenomics approach was used to identify drugs or drug candidates with potential anti-MABSC activity by comparing the sequences of M. abscessus proteins with therapeutic targets. Six drugs including ezetimibe, furosemide, itraconazole, miconazole (MCZ), tamoxifen (TAM), and thiabendazole (THI) were selected for experimental validation. MCZ and TAM showed promising antibacterial activity against M. abscessus and can be used as molecular scaffolds for the development of new analogs.
WORLD JOURNAL OF MICROBIOLOGY & BIOTECHNOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Annarita Fiorillo, Gianni Colotti, Cecile Exertier, Anastasia Liuzzi, Francesca Seghetti, Alessandra Salerno, Jessica Caciolla, Andrea Ilari
Summary: Trypanothione reductase (TR) plays a key role in the redox homeostasis of trypanosomatid parasites and is essential for their survival in the oxidative environment. We conducted a fragment-based crystal screening and identified 12 new ligands binding to five different sites, including an allosteric pocket named the doorstop pocket, which hampers TR activity. Another site, known as the Z-site, located within the trypanothione cavity, has not yet been explored for inhibition.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Chemistry, Analytical
Jiawen Lyu, Yan Wang, Chengfei Ruan, Xiaolei Zhang, Kejia Li, Mingliang Ye
Summary: This study introduces a method utilizing mechanical stress induced protein precipitation (MSIPP) for drug target deconvolution, with a streamlined workflow allowing in situ sample preparation on microparticle surfaces. The MSIPP method has been successfully applied to multiple drug compounds and revealed DHFR as a target of Raltitrexed.
ANALYTICA CHIMICA ACTA
(2021)
Article
Chemistry, Medicinal
Juan Hu, Alix Chan, Emel Adaligil, Ivy Kekessie, Mifune Takahashi, Aimin Song, Christian N. Cunningham, Brian M. Paegel
Summary: A scalable permeation assay was developed for combinatorial library screening, which can determine the cellular permeability of molecules. This method is particularly useful for investigating compounds that target undruggable targets, providing important insights into their drug-like properties.
JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Review
Pharmacology & Pharmacy
Gisele Nishiguchi, Sourav Das, Jason Ochoada, Heather Long, Richard E. Lee, Zoran Rankovic, Anang A. Shelat
Summary: The quality of lead compounds is crucial for the success of chemical probe and drug discovery programs, especially with high-throughput screening being a dominant lead generation paradigm. This article discusses a strategy implemented a decade ago to build one of the largest compound collections in academia, and a recent multidisciplinary effort aimed at enhancing and expanding the collection.
DRUG DISCOVERY TODAY
(2021)
Article
Biochemistry & Molecular Biology
Mingyang Wang, Zhe Wang, Huiyong Sun, Jike Wang, Chao Shen, Gaoqi Weng, Xin Chai, Honglin Li, Dongsheng Cao, Tingjun Hou
Summary: This paper introduces the molecular representation and assessment metrics used in DL-based de novo drug design, summarizes the features of each architecture, and prospects the potential challenges and future directions of DL-based molecular generation.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Guoli Xiong, Zhijiang Yang, Jiacai Yi, Ningning Wang, Lei Wang, Huimin Zhu, Chengkun Wu, Aiping Lu, Xiang Chen, Shao Liu, Tingjun Hou, Dongsheng Cao
Summary: DDInter is a curated DDI database with comprehensive data, practical medication guidance, intuitive function interface, and powerful visualization designed to assist clinicians in screening dangerous drug combinations and improving health systems.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Chemistry, Multidisciplinary
Xiaoqin Pan, Xuan Lin, Dongsheng Cao, Xiangxiang Zeng, Philip S. Yu, Lifang He, Ruth Nussinov, Feixiong Cheng
Summary: This review introduces guidelines on utilizing deep learning methodologies and tools for drug repurposing, which is of great importance in drug development. The article summarizes the commonly used bioinformatics and pharmacogenomics databases for drug repurposing and discusses the recently developed sequence-based and graph-based representation approaches as well as state-of-the-art deep learning-based methods. The applications of drug repurposing in fighting the COVID-19 pandemic are presented, along with an outline of future challenges.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2022)
Article
Biochemical Research Methods
Zhenxing Wu, Dejun Jiang, Jike Wang, Xujun Zhang, Hongyan Du, Lurong Pan, Chang-Yu Hsieh, Dongsheng Cao, Tingjun Hou
Summary: Molecular property prediction models based on machine learning algorithms are important tools in early stages of drug discovery. This study introduces a new pre-training method, K-BERT, which can extract chemical information from SMILES and provides superior predictions compared to traditional models.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Xiao-Chen Zhang, Jia-Cai Yi, Guo-Ping Yang, Cheng-Kun Wu, Ting-Jun Hou, Dong-Sheng Cao
Summary: This paper presents a deep neural network model called ABC-Net, which can directly predict graph structures. By using the divide-and-conquer principle, atoms or bonds are modeled as single points in the center, and a fully convolutional neural network is leveraged to identify and predict relevant properties, enabling the recovery of molecular structures. Experimental results demonstrate significant improvement in recognition performance with this method.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Zhe Wang, Hong Pan, Huiyong Sun, Yu Kang, Huanxiang Liu, Dongsheng Cao, Tingjun Hou
Summary: The fastDRH server is a free and open accessed web platform for predicting and analyzing protein-ligand complex structures. It integrates multiple features such as molecular docking, docking pose rescoring, and hotspot residue prediction to provide key information to users clearly. With a success rate of >80% in benchmark for protein-ligand binding mode prediction, the fastDRH server is a reliable tool for drug discovery projects.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Chemistry, Applied
Zheng-Fei Yang, Ran Xiao, Guo-Li Xiong, Qin-Lu Lin, Ying Liang, Wen-Bin Zeng, Jie Dong, Dong-sheng Cao
Summary: A novel multi-layer sweetness evaluation system based on machine learning methods was proposed to evaluate sweet properties of compounds with different chemical spaces and categories, providing quantitative predictions of sweetness. The study obtained sweetness-related chemical basis and structure transforming rules using molecular cloud and matched molecular pair analysis (MMPA) methods. The research aims to facilitate food scientists with efficient screening and precise development of high-quality sweeteners.
Article
Pharmacology & Pharmacy
Lingjie Bao, Zhe Wang, Zhenxing Wu, Hao Luo, Jiahui Yu, Yu Kang, Dongsheng Cao, Tingjun Hou
Summary: In this study, a model called AMGU was developed to predict the inhibitory activities of small molecules against various kinases. The AMGU model outperformed other models on both internal and external test sets, demonstrating its enhanced generalizability. Additionally, a method called edges masking was devised to explain the predictive mechanisms, and a web server called KIP was developed for predicting the polypharmacology effects of small molecules on the kinome.
ACTA PHARMACEUTICA SINICA B
(2023)
Article
Biochemistry & Molecular Biology
Gaoqi Weng, Xuanyan Cai, Dongsheng Cao, Hongyan Du, Chao Shen, Yafeng Deng, Qiaojun He, Bo Yang, Dan Li, Tingjun Hou
Summary: PROTAC-DB 2.0 is an updated online database that contains structural and experimental data about PROTACs. This second version expands the number of PROTACs to 3270 and provides additional information to aid in the understanding and design of PROTACs.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Chemistry, Medicinal
Jialu Wu, Junmei Wang, Zhenxing Wu, Shengyu Zhang, Yafeng Deng, Yu Kang, Dongsheng Cao, Chang-Yu Hsieh, Tingjun Hou
Summary: ALipSol is a attention-driven mixture-of-experts (MoE) model that accurately predicts the lipophilicity and aqueous solubility of drugs. By breaking down the complex endpoints into simpler ones and assigning specific expert networks, combining transfer learning and attention mechanism, ALipSol achieves significant performance improvement on different datasets.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Chemistry, Medicinal
Teng-Zhi Long, Shao-Hua Shi, Shao Liu, Ai-Ping Lu, Zhao-Qian Liu, Min Li, Ting-Jun Hou, Dong-Sheng Cao
Summary: This study constructed a high-quality dataset and established a series of classification models using machine learning algorithms to predict hematotoxicity. The best model based on Attentive FP showed excellent performance on both the validation and test sets. Additionally, the study utilized SHAP and atom heatmap methods to identify important features and structural fragments related to hematotoxicity, and employed MMPA and representative substructure derivation technique to further investigate the transformation principles and distinctive structural features of hematotoxic chemicals.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Multidisciplinary
Liu-Xia Zhang, Jie Dong, Hui Wei, Shao-Hua Shi, Ai-Ping Lu, Gui-Ming Deng, Dong-Sheng Cao
Summary: Traditional Chinese Medicine (TCM) has a long history in treating various diseases, and TCM ingredient databases are becoming increasingly important in the modernization of TCM. However, existing databases lack simplification functions for extracting key ingredients and lack quality control and standardization. To address these issues, a high-quality and standardized Traditional Chinese Medicine Simplified Integrated Database (TCMSID) was developed, providing abundant data sources and analysis platforms to promote the modernization and internationalization of TCM.
JOURNAL OF CHEMINFORMATICS
(2022)
Article
Multidisciplinary Sciences
Ruoru Wu, Zhihao Shu, Fei Zou, Shaoli Zhao, Saolai Chan, Yaxian Hu, Hong Xiang, Shuhua Chen, Li Fu, Dongsheng Cao, Hongwei Lu
Summary: In this study, the significance of serum myoglobin (Mb) in the pathogenesis of diabetic kidney disease (DKD) was investigated. The results suggest that serum Mb may serve as a potential indicator for DKD and is associated with renal function impairment caused by metabolic syndrome components.
SCIENTIFIC REPORTS
(2022)
Article
Instruments & Instrumentation
Jiayin Deng, Zhuyifan Ye, Wenwen Zheng, Jian Chen, Haoshi Gao, Zheng Wu, Ging Chan, Yongjun Wang, Dongsheng Cao, Yanqing Wang, Simon Ming-Yuen Lee, Defang Ouyang
Summary: Microspheres have attracted attention from the pharmaceutical and medical industry due to their excellent biodegradability and long controlled-release characteristics. This research successfully built a prediction model using machine learning techniques to accelerate microspheres product development for small-molecule drugs. The consensus model achieved high accuracy in predicting the in vitro drug release profiles and can provide meaningful insights for microspheres development.
DRUG DELIVERY AND TRANSLATIONAL RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Jiashun Mao, Shenghui Guan, Yongqing Chen, Amir Zeb, Qingxiang Sun, Ranlan Lu, Jie Dong, Jianmin Wang, Dongsheng Cao
Summary: Antimicrobial resistance could be a serious threat to millions of lives. Antimicrobial peptides (AMPs) offer an alternative to conventional antibiotics for combating infectious diseases. However, developing and optimizing AMPs face significant challenges, and advanced methods are needed to overcome these challenges and create effective AMP-driven treatments.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)