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Khushboo Sinha, Shahid Parwez, Shahana MV, Ananya Yadav, Mohammad Imran Siddiqi & Dibyendu Banerjee. (2023) Machine learning and biological evaluation-based identification of a potential MMP-9 inhibitor, effective against ovarian cancer cells SKOV3. Journal of Biomolecular Structure and Dynamics 0:0, pages 1-19.
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Chigozie J. O. Anarado, Ebuka H. Onyilogwu, Chigozie J. Ezeorah, Nnaemeka Nnaji, Chukwujindu M. A. Iwegbue, Ilknur Babahan-Bircan, Fatih Eyduran, Esin Poyrazoglu Coban, Muruvvet Abbak, Ali Özmen, Safiye Emirdağ, Ilke Demirkaya, Halil Biyik & Oguejiofo T. Ujam. (2023) Anticancer and antimicrobial activities of a novel 4-nitrobenzohydrazone and the Cu(II), Ni(II), Co(II), and Mn(II) complexes. Inorganic and Nano-Metal Chemistry 0:0, pages 1-17.
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Gabriel C. Veríssimo, Mateus Sá M. Serafim, Thales Kronenberger, Rafaela S. Ferreira, Kathia M. Honorio & Vinícius G. Maltarollo. (2022) Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern. Expert Opinion on Drug Discovery 17:9, pages 929-947.
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Kit-Kay Mak, Madhu Katyayani Balijepalli & Mallikarjuna Rao Pichika. (2022) Success stories of AI in drug discovery - where do things stand?. Expert Opinion on Drug Discovery 17:1, pages 79-92.
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Mateus Sá Magalhães Serafim, Valtair Severino dos Santos Júnior, Jadson Castro Gertrudes, Vinícius Gonçalves Maltarollo & Kathia Maria Honorio. (2021) Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade. Expert Opinion on Drug Discovery 16:9, pages 961-975.
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Articles from other publishers (20)
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Mateus Sá Magalhães Serafim, Simone Queiroz Pantaleão, Elany Barbosa da Silva, James H. McKerrow, Anthony J. O’Donoghue, Bruno Eduardo Fernandes Mota, Kathia Maria Honorio & Vinícius Gonçalves Maltarollo. (2023) The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study. Frontiers in Drug Discovery 3.
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Fatima Noor, Muhammad Asif, Usman Ali Ashfaq, Muhammad Qasim & Muhammad Tahir ul Qamar. (2023) Machine learning for synergistic network pharmacology: a comprehensive overview. Briefings in Bioinformatics 24:3.
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Mehmet Akif Özdemir, Gizem Dilara Özdemir, Merve Gül, Onan Güren & Utku Kürşat Ercan. (2023) Machine learning to predict the antimicrobial activity of cold atmospheric plasma-activated liquids. Machine Learning: Science and Technology 4:1, pages 015030.
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Karel Diéguez-Santana & Humberto González-Díaz. (2023) Machine learning in antibacterial discovery and development: A bibliometric and network analysis of research hotspots and trends. Computers in Biology and Medicine 155, pages 106638.
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Ruoqi Yang, Guiping Zhao, Lili Zhang, Yu Xia, Huijuan Yu, Bin Yan & Bin Cheng. (2022) Identification of potential extracellular signal-regulated protein kinase 2 inhibitors based on multiple virtual screening strategies. Frontiers in Pharmacology 13.
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Gabriel Corrêa Veríssimo, Valtair Severino dos Santos Junior, Philipe Oliveira Fernandes, Shoichi Ishida, Ryosuke Kojima, Yasushi Okuno, Jadson Castro Gertrudes & Vinicius Gonçalves Maltarollo. (2022) GCN-Based Structure-Activity Relationship and DFT Studies of Staphylococcus aureus FabI Inhibitors. International Journal of Quantitative Structure-Property Relationships 7:1, pages 1-16.
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Ruoqi Yang, Xuan Zha, Xingyi Gao, Kangmin Wang, Bin Cheng & Bin Yan. (2022) Multi-stage virtual screening of natural products against p38α mitogen-activated protein kinase: predictive modeling by machine learning, docking study and molecular dynamics simulation. Heliyon 8:9, pages e10495.
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Ioana-Andreea Lungu, Octavia-Laura Moldovan, Victoria Biriș & Aura Rusu. (2022) Fluoroquinolones Hybrid Molecules as Promising Antibacterial Agents in the Fight against Antibacterial Resistance. Pharmaceutics 14:8, pages 1749.
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Jennifer M. Cantrell, Carolina H. Chung & Sriram Chandrasekaran. (2022) Machine learning to design antimicrobial combination therapies: Promises and pitfalls. Drug Discovery Today 27:6, pages 1639-1651.
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Raymond Schuch, Cara Cassino & Xavier Vila-Farres. (2022) Direct Lytic Agents: Novel, Rapidly Acting Potential Antimicrobial Treatment Modalities for Systemic Use in the Era of Rising Antibiotic Resistance. Frontiers in Microbiology 13.
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Michael Stiven Ramirez Campos, David Alejandro Galeano López, Jorman Arbey Castro Rivera, Diana C. Rodriguez, Oscar J. Perdomo & Alvaro David Orjuela-Cañon. 2022. Applied Computer Sciences in Engineering. Applied Computer Sciences in Engineering
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Jin-Tong Li, Ya-Wen Wei, Meng-Yu Wang, Chun-Xiao Yan, Xia Ren & Xian-Jun Fu. (2021) Antibacterial Activity Prediction Model of Traditional Chinese Medicine Based on Combined Data-Driven Approach and Machine Learning Algorithm: Constructed and Validated. Frontiers in Microbiology 12.
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Karel Diéguez-Santana & Humberto González-Díaz. (2021) Towards machine learning discovery of dual antibacterial drug–nanoparticle systems. Nanoscale 13:42, pages 17854-17870.
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Rohan Gupta, Devesh Srivastava, Mehar Sahu, Swati Tiwari, Rashmi K. Ambasta & Pravir Kumar. (2021) Artificial intelligence to deep learning: machine intelligence approach for drug discovery. Molecular Diversity 25:3, pages 1315-1360.
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Sk. Abdul Amin, Suvankar Banerjee, Samayaditya Singh, Insaf Ahmed Qureshi, Shovanlal Gayen & Tarun Jha. (2021) First structure–activity relationship analysis of SARS-CoV-2 virus main protease (Mpro) inhibitors: an endeavor on COVID-19 drug discovery. Molecular Diversity 25:3, pages 1827-1838.
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Mahsa Mirzaei, Irini Furxhi, Finbarr Murphy & Martin Mullins. (2021) A Machine Learning Tool to Predict the Antibacterial Capacity of Nanoparticles. Nanomaterials 11:7, pages 1774.
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Paula Carracedo-Reboredo, Jose Liñares-Blanco, Nereida Rodríguez-Fernández, Francisco Cedrón, Francisco J. Novoa, Adrian Carballal, Victor Maojo, Alejandro Pazos & Carlos Fernandez-Lozano. (2021) A review on machine learning approaches and trends in drug discovery. Computational and Structural Biotechnology Journal 19, pages 4538-4558.
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