In this mini-review, we explore the new prediction methods for drug combination synergy relying on high-throughput combinatorial screens. The fast progress of the field is witnessed in the more than thirty original machine learning methods published since 2021, a clear majority of them based on deep learning techniques. We aim to put these articles under a unifying lens by highlighting the core technologies, the data sources, the input data types and synergy scores used in the methods, as well as the prediction scenarios and evaluation protocols that the articles deal with. Our finding is that the best methods accurately solve the synergy prediction scenarios involving known drugs or cell lines while the scenarios involving new drugs or cell lines still fall short of an accurate prediction level.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.sbi.2024.102827 | DOI Listing |
Cell Commun Signal
January 2025
Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
Background: Ovarian cancer (OC), particularly high-grade serous ovarian carcinoma (HGSOC), is the leading cause of mortality from gynecological malignancies worldwide. Despite the initial effectiveness of treatment, acquired resistance to poly(ADP-ribose) polymerase inhibitors (PARPis) represents a major challenge for the clinical management of HGSOC, highlighting the necessity for the development of novel therapeutic strategies. This study investigated the role of 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3), a pivotal regulator of glycolysis, in PARPi resistance and explored its potential as a therapeutic target to overcome PARPi resistance.
View Article and Find Full Text PDFVirol J
January 2025
Medi-X Pingshan, Southern University of Science and Technology, Shenzhen, Guangdong, 518118, China.
Background: SHEN26 (ATV014) is an oral RNA-dependent RNA polymerase (RdRp) inhibitor with potential anti-SARS-CoV-2 activity. Safety, tolerability, and pharmacokinetic characteristics were verified in a Phase I study. This phase II study aimed to verify the efficacy and safety of SHEN26 in COVID-19 patients.
View Article and Find Full Text PDFReprod Biol Endocrinol
January 2025
Department of Molecular and Developmental Medicine, Siena University, Siena, 53100, Italy.
Background: Endocrine-disrupting chemicals (EDCs) interfere with the endocrine system and negatively impact reproductive health. Biochanin A (BCA), an isoflavone with anti-inflammatory and estrogen-like properties, has been identified as one such EDC. This study investigates the effects of BCA on transcription, metabolism, and hormone regulation in primary human granulosa cells (GCs), with a specific focus on the activation of bitter taste receptors (TAS2Rs).
View Article and Find Full Text PDFMalar J
January 2025
PATH, 2201 Westlake Ave Ste 200, Seattle, WA, 98121, USA.
Background: The World Health Organization conditionally recommends reactive drug administration to reduce malaria transmission in settings approaching elimination. However, few studies have evaluated the impact of reactive focal drug administration (rFDA) in sub-Saharan Africa, and none have evaluated it under programmatic conditions. In 2016, Senegal's national malaria control programme introduced rFDA, the presumptive treatment of compound members of a person with confirmed malaria, and reactive mass focal drug administration (rMFDA), an expanded effort including neighbouring compounds during an outbreak, in 10 low transmission districts in the north of the country.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
School of Computer Science and Technology, University of Science and Technology of China, 443 Huangshan Road, Hefei, 230027, China.
Background: Drug-drug interactions (DDIs) especially antagonistic ones present significant risks to patient safety, underscoring the urgent need for reliable prediction methods. Recently, substructure-based DDI prediction has garnered much attention due to the dominant influence of functional groups and substructures on drug properties. However, existing approaches face challenges regarding the insufficient interpretability of identified substructures and the isolation of chemical substructures.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!