Protein-ligand binding affinity prediction using multi-instance learning with docking structures by Hyojin Kim, Heesung Shim, Aditya Ranganath, Stewart He, Garrett Stevenson, Jonathan E. Allen

“…IntroductionRecent advances in 3D structure-based deep learning approaches demonstrate improved accuracy in predicting protein-ligand binding affinity in drug discovery. These methods complement physics-based computational modeling such as molecular docking for virtual high-throughput screening. …”
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Pharmacophore-based virtual screening for identification of marine sponge bioactive compound inhibitors against Alzheimer's disease by Suruthi SS, Prashanth KK, Baskaran A

“…Alzheimer's disease is a hereditary neurodegenerative disease that occurs sporadically and causes amnestic cognitive impairment. Traditional drug discovery methods have faced challenges in this regard, leading researchers to explore natural products as potential therapeutics. …”
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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

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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

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

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

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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

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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. …”
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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—one of the most important datasets in the drug discovery domain. We compare QAML with classical machine learning to evaluate their relative performance. …”
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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.…”
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Why is the New York Times Writing so Much about Alzheimer's Disease Therapies? by Tamas Bartfai

“…Ad is so devastating that there is a great public interest in the drug discovery process as evinced by the sheer number of articles in the serious popular press. …”
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DeepTGIN: a novel hybrid multimodal approach using transformers and graph isomorphism networks for protein-ligand binding affinity prediction by Guishen Wang, Hangchen Zhang, Mengting Shao, Yuncong Feng, Chen Cao, Xiaowen Hu

“…Abstract Predicting protein-ligand binding affinity is essential for understanding protein-ligand interactions and advancing drug discovery. Recent research has demonstrated the advantages of sequence-based models and graph-based models. …”
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Network analyses of brain tumor multiomic data reveal pharmacological opportunities to alter cell state transitions by Brandon Bumbaca, Jonah R. Huggins, Marc R. Birtwistle, James M. Gallo

“…In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. …”
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Computational antidiabetic assessment of Salvia splendens L. polyphenols: SMOTE, ADME, ProTox, docking, and molecular dynamic studies by Hatun A. Alomar, Wafaa M. El Kady, Asmaa A. Mandour, Amany A. Naim, Neveen I. Ghali, Taghreed A. Ibrahim, Noha Fathallah

“…This study utilizes artificial intelligence and machine learning to enhance drug discovery, focusing on the antidiabetic effects of Salvia splendens leaf extract among the global epidemic of diabetes mellitus. …”
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Evaluation of Anti-Cancer, Pro-Apoptotic, and Anti-Metastatic Effects of Synthetic Analogue Compound 2-Imino-7-Methoxy-4-(4-fluorophenyl)-2H-1,3-Thiazino [3,2-a] Benzimidazole on P... by Mpho Ndou, Marthe C. D. Fotsing, Michael H. K. Kengne, Edwin M. Mmutlane, Derek T. Ndinteh, Mthokozisi B.C. Simelane, Lesetja Motadi, Mpho Choene

“… Synthetic compounds are widely used in cancer drug discovery. Chemotherapies aim to inhibit proliferation and induce apoptosis however, they have limitations. …”
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Rare Cell Population Analysis in Early-Stage Breast Cancer Patients by Stefan Schreier, Prapaphan Budchart, Suparerk Borwornpinyo, Lakkana Adireklarpwong, Prakasit Chirappapha, Wannapong Triampo, Panuwat Lertsithichai

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A Comprehensive Review of the Diversity of Fungal Secondary Metabolites and Their Emerging Applications in Healthcare and Environment by Khushbu Wadhwa, Neha Kapoor, Hardeep Kaur, Eman A. Abu-Seer, Mohd. Tariq, Sazada Siddiqui, Virendra Kumar Yadav, Parwiz Niazi, Pankaj Kumar, Saad Alghamdi

“…Investigators further highlighted the importance of omics technologies in understanding the regulation and biosynthesis of SMs, which offers an understanding of novel applications in drug discovery and sustainable agriculture. Finally, the authors have addressed the potential for genetic manipulation and biotechnological innovations for further exploitation of fungal SMs for commercial and environmental benefits.…”
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Img2Side: A Transfer Learning Based Model for Predicting Drug Side Effects Using 2D Chemical Structural Images by Muhammad Asad Arshed, Muhammad Ibrahim, Shahzad Mumtaz, Tenvir Ali, Gyu Sang Choi

“…Every approved drug should be either free from DSEs or these should be minor and reported properly. The drug discovery process should be capable of predicting and preventing these effects in advance. …”
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