Fecal microbiota transplantation to prevent acute graft-versus-host disease: pre-planned interim analysis of donor effect by Swetha Reddi, Liliia Senyshyn, Maryam Ebadi, Daniel Podlesny, Samuel S. Minot, Ted Gooley, Amanda J. Kabage, Geoffrey R. Hill, Stephanie J. Lee, Alexander Khoruts, Armin Rashidi

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Initial Development of Automated Machine Learning-Assisted Prediction Tools for Aryl Hydrocarbon Receptor Activators by Paulina Anna Wojtyło, Natalia Łapińska, Lucia Bellagamba, Emidio Camaioni, Aleksander Mendyk, Stefano Giovagnoli

“…The initial dataset was obtained by combining the ChEMBL and WIPO databases which contained 978 molecules with EC₅₀ values. …”
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Quantitative structure–activity relationships of chemical bioactivity toward proteins associated with molecular initiating events of organ-specific toxicity by Domenico Gadaleta, Marina Garcia de Lomana, Eva Serrano-Candelas, Rita Ortega-Vallbona, Rafael Gozalbes, Alessandra Roncaglioni, Emilio Benfenati

“…Utilizing bioactivity data from the ChEMBL 33 database, various machine learning algorithms, chemical features and methods to assess prediction reliability were compared and applied to develop robust models to predict compound activity. …”
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Towards accurate L4 ocean colour products: Interpolating remote sensing reflectance via DINEOF by Christian Marchese, Simone Colella, Vittorio Ernesto Brando, Maria Laura Zoffoli, Gianluca Volpe

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Pathogenic Huntingtin aggregates alter actin organization and cellular stiffness resulting in stalled clathrin-mediated endocytosis by Surya Bansi Singh, Shatruhan Singh Rajput, Aditya Sharma, Sujal Kataria, Priyanka Dutta, Vaishnavi Ananthanarayanan, Amitabha Nandi, Shivprasad Patil, Amitabha Majumdar, Deepa Subramanyam

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Machine learning and molecular dynamics simulations predict potential TGR5 agonists for type 2 diabetes treatment by Ojochenemi A. Enejoh, Chinelo H. Okonkwo, Hector Nortey, Olalekan A. Kemiki, Ainembabazi Moses, Ainembabazi Moses, Florence N. Mbaoji, Abdulrazak S. Yusuf, Olaitan I. Awe

“…This study used machine learning-based models (ML), molecular docking (MD), and molecular dynamics simulations (MDS) to explore novel small molecules as potential TGR5 agonists.MethodsBioactivity data for known TGR5 agonists were obtained from the ChEMBL database. The dataset was cleaned and molecular descriptors based on Lipinski’s rule of five were selected as input features for the ML model, which was built using the Random Forest algorithm. …”
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Quantifying conformational changes in the TCR:pMHC-I binding interface by Benjamin McMaster, Benjamin McMaster, Christopher J. Thorpe, Christopher J. Thorpe, Jamie Rossjohn, Jamie Rossjohn, Charlotte M. Deane, Hashem Koohy

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Effect of Acetyl tributyl citrate on bone metabolism based on network toxicology and molecular docking technology by Xuan Lin, Kun Lin, Yue Lai, Qingping Peng, Miao Xu, Yiting Xu, Jialin Yang, Huan Liu, Jianlin Shen

“…Leveraging the exhaustive exploration of databases such as ChEMBL, STITCH, GeneCards, and OMIM, we have identified a comprehensive list of 164 potential targets intimately associated with both ATBC and bone metabolism. …”
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Nicotinic α7 receptors on cholinergic neurons in the striatum mediate cocaine-reinforcement, but not food reward by Michael Fritz, Michael Fritz, Michael Fritz, Priscila Batista Rosa, Daniel Wilhelms, Daniel Wilhelms, Maarit Jaarola, Johan Ruud, David Engblom, Anna M. Klawonn, Anna M. Klawonn, Anna M. Klawonn, Anna M. Klawonn

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Beyond-local neural information processing in neuronal networks by Johannes Balkenhol, Barbara Händel, Sounak Biswas, Johannes Grohmann, Jóakim v. Kistowski, Juan Prada, Conrado A. Bosman, Hannelore Ehrenreich, Sonja M. Wojcik, Samuel Kounev, Robert Blum, Thomas Dandekar

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Investigating the inflammatory mechanism of notoginsenoside R1 in Diabetic nephropathy via ITGB8 based on network pharmacology and experimental validation by ChangYan Li, Chen Geng, JiangMing Wang, Luyao Shi, JingYuan Ma, Zhang Liang, WenXing Fan

“…Three methods were used to predict NGR1 drug targets: ChEMBL, SuperPred, and Swiss Target Prediction. Drug targets are linked to diseases by molecular docking. …”
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Better understanding the phenotypic effects of drugs through shared targets in genetic disease networks by Elena Díaz-Santiago, Aurelio A. Moya-García, Jesús Pérez-García, Raquel Yahyaoui, Raquel Yahyaoui, Christine Orengo, Florencio Pazos, James R. Perkins, James R. Perkins, James R. Perkins, Juan A. G. Ranea, Juan A. G. Ranea, Juan A. G. Ranea, Juan A. G. Ranea

“…Gaining traction in this field is the use of disease data linking genes with pathological phenotypes and combining this with drugtarget interaction data.MethodsWe introduce methodology to associate drugs with effects, both intended and adverse, using a tripartite network approach that combines drug-target and target-phenotype data, in which targets can be represented as proteins and protein domains.ResultsWe were able to detect associations for over 140,000 ChEMBL drugs and 3,800 phenotypes, represented as Human Phenotype Ontology (HPO) terms. …”
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Inflammatory bowel disease increases the risk of pancreatitis: a two-sample bidirectional Mendelian randomization analysis by Li-Hui Fang, Jia-Qi Zhang, Jin-Ke Huang, Xu-Dong Tang

“…Four independent summary statistics of pancreatitis from the the European Bioinformatics Institute (EMBL-EBI, 10,630 AP cases and 844,679 controls, 1,424 CP cases and 476,104 controls) and FinnGen Consortium (8,446 AP cases, 4,820 CP cases and 437,418 controls) were used for bidirectional MR analyses and sensitivity analysis. …”
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Sequential replacement of PSD95 subunits in postsynaptic supercomplexes is slowest in the cortex by Katie Morris, Edita Bulovaite, Takeshi Kaizuka, Sebastian Schnorrenberg, Candace T Adams, Noboru Komiyama, Lorena Mendive-Tapia, Seth GN Grant, Mathew H Horrocks

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Copper and chromium binding by Pseudomonas aeruginosa strain PA01 for implications of heavy metal detoxification and soil remediation: A computational approach by Shanmuga Priya Ramasamy, Priya Sundararajan, Muthukrishnan Pallikondaperumal, Ponmurugan Karuppiah, Saminathan Kayarohanam, Natarajan Arumugam, Ling Shing Wong, Sinouvassane Djearamane

“…Metal-binding domains were validated through a pattern search against UniProtKB/Swiss-Prot and UniProtKB/TrEMBL databases using the ScanProsite tool. Comparative sequence alignments were conducted between the copper-binding NosD gene of P. aeruginosa, the ferredoxin gene of P. aeruginosa PA01, and the chromium-binding iron hydrogenase 1 gene of Clostridium chromiireducens. …”
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Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery by Arda Halu, Sarvesh Chelvanambi, Julius L. Decano, Joan T. Matamalas, Mary Whelan, Takaharu Asano, Namitra Kalicharran, Sasha A. Singh, Joseph Loscalzo, Masanori Aikawa

“…Using these networks and a large-scale disease-gene network consisting of 569 disease signatures from the Enrichr database, we calculate Pathophenotypic Congruity Scores (PACOS) between input gene signatures and drug perturbation signatures and combine these scores with cheminformatic data from ChEMBL to prioritize drugs. We benchmark our approach by calculating area under the receiver operating characteristic curves (AUROC) for 73 gene sets from the Molecular Signatures Database (MSigDB) using target gene expression profiles from the Comparative Toxicogenomics Database (CTD). …”
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A conserved switch to less catalytically active Polycomb repressive complexes in non-dividing cells by Rachel McCole, James Nolan, David M. Reck, Craig Monger, Samantha Rustichelli, Eric Conway, Gerard L. Brien, Cheng Wang, Orla Deevy, Hannah K. Neikes, Frances M. Bashore, Aoibhinn Mooney, Richard Flavin, Elisabeth Vandenberghe, Sarena F. Flanigan, Diego Pasini, Chen Davidovich, Michiel Vermeulen, Lindsey I. James, Evan Healy, Adrian P. Bracken

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NET Models Meeting 2024 white paper: the current state of neuroendocrine tumour research models and our future aspirations by Po Hien Ear, Ilaria Marinoni, Talya Dayton, Rachael Guenter, Dawn E Quelle, Anna Battistella, Floryne O Buishand, Suganthi Chittaranjan, Yi-Cheih Nancy Du, Ines Marques, Natalia S Pellegata, Samira M Sadowski, Amit Tirosh, Simon April-Monn, Cinzia Aurilia, Renata Jaskula-Sztul, Maria Jesús Baena Moreno, Simone Donati, Katherine A English, Maria Almudena Hernandez Llorens, Harry Hodgetts, Francesca Marini, Maria Martins, Gaia Palmini, Beatriz Soldevilla, Jörg Schrader, Rajesh V Thakker, Kate E Lines

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Immune digital twins for complex human pathologies: applications, limitations, and challenges by Anna Niarakis, Reinhard Laubenbacher, Gary An, Yaron Ilan, Jasmin Fisher, Åsmund Flobak, Kristin Reiche, María Rodríguez Martínez, Liesbet Geris, Luiz Ladeira, Lorenzo Veschini, Michael L. Blinov, Francesco Messina, Luis L. Fonseca, Sandra Ferreira, Arnau Montagud, Vincent Noël, Malvina Marku, Eirini Tsirvouli, Marcella M. Torres, Leonard A. Harris, T. J. Sego, Chase Cockrell, Amanda E. Shick, Hasan Balci, Albin Salazar, Kinza Rian, Ahmed Abdelmonem Hemedan, Marina Esteban-Medina, Bernard Staumont, Esteban Hernandez-Vargas, Shiny Martis B, Alejandro Madrid-Valiente, Panagiotis Karampelesis, Luis Sordo Vieira, Pradyumna Harlapur, Alexander Kulesza, Niloofar Nikaein, Winston Garira, Rahuman S. Malik Sheriff, Juilee Thakar, Van Du T. Tran, Jose Carbonell-Caballero, Soroush Safaei, Alfonso Valencia, Andrei Zinovyev, James A. Glazier

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