Evaluating translational science knowledge gains following an online short course for a general scientific audience by Amanda L. Vogel, Shadab F. Hussain, Jessica M. Faupel-Badger

“…Students reported the course helped them learn about the trajectory of a drug discovery and development initiative, where their own work fit in, and scientific and operational approaches to apply in their own work. …”
Get full text

Isolation and Bioactivity of Natural Products from <i>Streptomyces</i> sp. MA37 by Fleurdeliz Maglangit, Qing Fang, Jioji N. Tabudravu, Kwaku Kyeremeh, Marcel Jaspars, Hai Deng

“…The isolation and characterization of bioactive metabolites from <i>Streptomyces</i> species continue to represent a vital area of research, given their potential in natural product drug discovery. In this study, we characterize a new siderophore called legonoxamine I, together with a known compound, streptimidone, from the talented soil bacterium <i>Streptomyces</i> sp. …”
Get full text

Advances in the Development and Application of Human Organoids: Techniques, Applications, and Future Perspectives by Zhangcheng Zhu, Yiwen Cheng, Xia Liu, Wenwen Ding, Jiaming Liu, Zongxin Ling, Lingbin Wu

“…This progress has expanded their application across several domains, including regenerative medicine, where organoids offer potential for tissue replacement and repair; disease modeling, which allows for the study of disease mechanisms and progression in a controlled environment; drug discovery and evaluation, where organoids provide a more accurate platform for testing drug efficacy and safety; and microecological research, where they contribute to understanding the interactions between microbes and host tissues. …”
Get full text

Antioxidant, Antimicrobial, and Protein Kinase Inhibition Profiling of C. ambrosioides Seed Extracts along with RP-HPLC by Saira Bano, Muhammad Waleed Baig, Mohammad K. Okla, Syeda Saniya Zahra, Nosheen Akhtar, Wahidah H. Al-Qahtani, Hamada AbdElgawad, Ihsan-Ul Haq

“…The validation of underexplored traditional plant remedies represents a reservoir of novel leads for drug discovery. In line with this, in vitro total phenolics and flavonoids content, multimode antioxidants, antimicrobial, cytotoxicity, and protein kinase inhibition assays were conducted on C. ambrosioides seed extracts in addition to RP-HPLC. …”
Get full text

The algebraic extended atom-type graph-based model for precise ligand–receptor binding affinity prediction by Farjana Tasnim Mukta, Md Masud Rana, Avery Meyer, Sally Ellingson, Duc D. Nguyen

“…The AGL-EAT-Score marks a significant advancement in drug design, offering a tool that could potentially refine and accelerate the drug discovery process. Scientific Contribution The AGL-EAT-Score presents an algebraic graph-based framework that predicts ligand-receptor binding affinity by constructing multiscale weighted colored subgraphs from the 3D structure of protein-ligand complexes. …”
Get full text

Molecular Characterization and Antibacterial Potential of Endophytic Fungal Isolates from Selected Mangroves along the Coastline of Kenya by Teresia Nyambura Wacira, Huxley Mae Makonde, Carren Moraa Bosire, Cromwell Mwiti Kibiti

“…It is recommended that the pure compounds from these extracts be isolated for further bioactivity tests and structural elucidation for consideration as lead molecules in drug discovery. In addition, the genes responsible for the enhanced bioactivity in these isolates can be characterized and bioengineered for pharmaceutical application.…”
Get full text

Novel tetracycline hybrids: synthesis, characterization, docking studies and in-vitro evaluation of antibacterial activity by Mansi Shah, Bhanubhai Suhagia, Sunita Goswami, Sneha Sagar, Arpit Patwari

“…These hybrids can serve as a promising lead compound for antibiotic drug discovery.…”
Get full text

InceptionDTA: Predicting drug-target binding affinity with biological context features and inception networks by Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi

“…Predicting drug-target binding affinity via in silico methods is crucial in drug discovery. Traditional machine learning relies on manually engineered features from limited data, leading to suboptimal performance. …”
Get full text

Explication of Pharmacological Proficiency of Phytoconstituents from Adansonia digitata Bark: An In Vitro and In Silico Approaches by Sangavi P., Gowtham Kumar S., Nachammai KT., Chandrabose Selvaraj, Langeswaran K.

“…Compared to other drug discovery sources, traditional medicine has significantly contributed to developing innovative therapeutic molecules for preventive and curative medicine. …”
Get full text

System Pharmacological Approach to Investigate and Validate Multitargeted and Therapeutic Effect of Furocoumarins of Apium graveolens L. for Treatment of Kidney Disease by null Yasheshwar, null Gaurav, Rustam Ekkbal, Prem Gupta, Rajendra Gyawali

“…System pharmacological approaches play important roles in drug discovery and development and in biomolecular exploration to investigate the multitarget therapeutic effects of phytochemicals for the treatment of acute and chronic ailments. …”
Get full text

Oleraceins from Portulaca oleracea leaves: Quali-quantitative determination and antioxidant potential by Ciro Cannavacciuolo, Assunta Napolitano, Verena M. Dirsch, Elke H. Heiss, Milena Masullo, Sonia Piacente

Get full text

Screening and evaluation of novel DPP-IV inhibitory peptides in goat milk based on molecular docking and molecular dynamics simulation by Kuo Dang, Jing Lan, Yanli Wang, Daodong Pan, Lihui Du, Shikun Suo, Yali Dang, Xinchang Gao

Get full text

Binding Mode Investigation of Polyphenols from Scrophularia Targeting Human Aldose Reductase Using Molecular Docking and Molecular Dynamics Simulations by Abinaya Manivannan, Prabhakaran Soundararajan, Yoo Gyeong Park, Sugunadevi Sakkiah, Byoung Ryong Jeong

“…Aldose reductase (ALR2), a vital enzyme involved in polyol pathway, has befitted as a novel drug target in antidiabetes drug discovery process. In the present study, the binding mode and pharmacokinetic properties of potential polyphenolic compounds with reported aldose reductase inhibitory activity from the genus Scrophularia have been investigated. …”
Get full text

Extreme Environment Streptomyces: Potential Sources for New Antibacterial and Anticancer Drug Leads? by Periyasamy Sivalingam, Kui Hong, John Pote, Kandasamy Prabakar

Get full text

An insight into the therapeutic impact of quinoxaline derivatives: Recent advances in biological activities (2020–2024) by Aly M. Waseem, Ranya Mohammed Elmagzoub, Mervat Mohammed Mazhar Abdelgadir, Areej Al Bahir, N.S. Abd EL-Gawaad, Ahmed S. Abdel-Samea, Devendra Pratap Rao, Konstantinos Kossenas, Stefan Bräse, Hamada Hashem

“…This review provides a comprehensive overview of the recent advancements in quinoxaline-based therapies, underscoring their potential impact on modern drug discovery and therapeutic applications.…”
Get full text

Interleukin-1β Accelerates the Onset of Stroke in Stroke-Prone Spontaneously Hypertensive Rats by Tsuyoshi Chiba, Tatsuki Itoh, Masaki Tabuchi, Toru Nakazawa, Takao Satou

Get full text

Influence of Heat Treatment on Biocorrosion and Hemocompatibility of Biodegradable Mg-35Zn-3Ca Alloy by Jeong-Hui Ji, Il-Song Park, Yu-Kyoung Kim, Sook-Jeong Lee, Tae-Sung Bae, Min-Ho Lee

Get full text

Evolution of artificial intelligence in healthcare: a 30-year bibliometric study by Yaojue Xie, Yuansheng Zhai, Yuansheng Zhai, Guihua Lu, Guihua Lu

“…Notably, the rapid expansion of emerging topics such as COVID-19 and new drug discovery in recent years is noteworthy. Furthermore, the top five most cited papers in 2023 were all pertinent to the theme of ChatGPT.ConclusionThis study reveals a sustained explosive growth trend in AI technologies within the healthcare sector in recent years, with increasingly profound applications in medicine. …”
Get full text

Performance of Quantum Annealing Machine Learning Classification Models on ADMET Datasets by Hadi Salloum, Kamil Sabbagh, Vladislav Savchuk, Ruslan Lukin, Osama Orabi, Marat Isangulov, Manuel Mazzara

“…This work focuses on experimentally evaluating quantum annealing machine learning (QAML) classification methods, specifically Quantum Support Vector Machines (QSVM) and QBoost, on ADMET datasets&#x2014;one of the most important datasets in the drug discovery domain. We compare QAML with classical machine learning to evaluate their relative performance. …”
Get full text

Oral Administration of Semicarbazide Limits Weight Gain together with Inhibition of Fat Deposition and of Primary Amine Oxidase Activity in Adipose Tissue by Josep Mercader, Zsuzsa Iffiú-Soltész, Sandy Bour, Christian Carpéné

“…Although semicarbazide is currently considered as a food contaminant with deleterious effects, the SSAO inhibition it induces appears as a novel concept to modulate adipose tissue development, which is promising for antiobesity drug discovery.…”
Get full text