PubChem 2023 update

Gene Ontology: tool for the unification of biology

Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206

Database resources of the National Center for Biotechnology Information: update

Wheeler, D. L. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh073 · Cited by 10,695

SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

Weininger, D. (1988) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci00057a005 · Cited by 7,436

UniProt: the universal protein knowledgebase in 2021

The UniProt Consortium, Bateman, A., Martin, M.-J., Orchard, S., Magrane, M., Agivetova, R., Ahmad, S., Alpi, E., Bowler-Barnett, E. H., Britto, R., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1100 · Cited by 6,372

Database resources of the National Center for Biotechnology Information

Agarwala, R., Barrett, T., Beck, J., Benson, D., Bollin, C., Bolton, E. E., Bourexis, D., Brister, J., Bryant, S. H., Canese, K., et al. (2017) · Nucleic Acids Res. · doi:10.1093/nar/gkx1095 · Cited by 6,277

PubChem Substance and Compound databases

Kim, S., Thiessen, P. A., Bolton, E. E., Chen, J., Fu, G., Gindulyte, A., Han, L., He, J., He, S., Shoemaker, B. A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv951 · Cited by 5,436

PubChem in 2021: new data content and improved web interfaces

Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa971 · Cited by 3,953

The Gene Ontology resource: enriching a GOld mine

The Gene Ontology Consortium, Carbon, S., Douglass, E., Good, B. M., Unni, D. R., Harris, N. L., Mungall, C. J., Basu, S., Chisholm, R. L., Dodson, R. J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1113 · Cited by 3,555

PubChem 2019 update: improved access to chemical data

Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1033 · Cited by 3,249

NCBI Taxonomy: a comprehensive update on curation, resources and tools

Schoch, C. L., Ciufo, S., Domrachev, M., Hotton, C. L., Kannan, S., Khovanskaya, R., Leipe, D., Mcveigh, R., O’Neill, K., Robbertse, B., et al. (2020) · Database · doi:10.1093/database/baaa062 · Cited by 2,635

Enhancing Molecular Property Prediction through Task-Oriented Transfer Learning: Integrating Universal Structural Insights and Domain-Specific Knowledge

Duan, Y., Yang, X., Zeng, X., Wang, W., Deng, Y., & Cao, D. (2024) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.4c00692 · Cited by 14

Enhancing MD simulations: ASGARD’s automated analysis for GROMACS

Martínez, A. R., Nelen, J., Carmena‐Bargueño, M., Martínez-Cortés, C., Luque, I., & Pérez‐Sánchez, H. (2024) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2024.2349527 · Cited by 13

17-β-Estradiol—β-Cyclodextrin complex as an aqueous solution: Structural and physicochemical characterization supported by MM and QM calculations

Mazurek, A., Szeleszczuk, Ł., Bethanis, K., Christoforides, E., Dudek, M. K., Wielgus, E., & Pisklak, D. M. (2024) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2024.138710 · Cited by 13

GOLEM: Automated and Robust Cryo-EM-Guided Ligand Docking with Explicit Water Molecules

Zhao, Z., & Tajkhorshid, E. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c00917 · Cited by 13

Do Molecular Fingerprints Identify Diverse Active Drugs in Large-Scale Virtual Screening? (No)

Venkatraman, V., Gaiser, J., Demekas, D., Roy, A., Xiong, R., & Wheeler, T. J. (2024) · Pharmaceuticals · doi:10.3390/ph17080992 · Cited by 13

Synthesis, structural characterization, DFT and molecular dynamics simulations of dinuclear (μ-hydroxo)-bridged triethanolamine copper( ii ) complexes: efficient candidates towards visible light-mediated photo-Fenton degradation of organic dyes

Chauhan, C., Tanuj, T., Kumar, R., Kumar, J., Sharma, S., Benmansour, S., & Kumar, S. (2024) · Dalton Transactions · doi:10.1039/d4dt01463d · Cited by 14

Generating knowledge graphs through text mining of catalysis research related literature

Behr, A. S., Chernenko, D., Koßmann, D., Neyyathala, A., Hanf, S., Schunk, S. A., & Kockmann, N. (2024) · Catalysis Science & Technology · doi:10.1039/d4cy00369a · Cited by 14

Investigating the synergy of rapidly synthesized iron oxide predecessor and plasma-gaseous species for dye-removal to reuse water in irrigation

Lamichhane, P., Acharya, T. R., Dhakal, O. B., Dahal, R., & Choi, E. H. (2024) · Chemosphere · doi:10.1016/j.chemosphere.2024.143040 · Cited by 14

Detection of host cell microprotein impurities in antibody drug products

Tzani, I., Castro‐Rivadeneyra, M., Kelly, P. S., Strasser, L., Zhang, L., CLYNES, M. M., Karger, B. L., Barron, N., Bones, J., Clarke, C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-51870-0 · Cited by 14

An antimicrobial drug recommender system using MALDI-TOF MS and dual-branch neural networks

Waele, G. D., Menschaert, G., & Waegeman, W. (2024) · eLife · doi:10.7554/elife.93242.4 · Cited by 19

Anti-inflammatory potential of Oroxylum indicum flavonoids: Effects of traditional grilling on aglycone flavonoid content and activity against urban dust-induced inflammation

Choonong, R., Waewaram, V., Buraphaka, H., Krittanai, S., Boonsnongcheep, P., & Putalun, W. (2024) · Food Bioscience · doi:10.1016/j.fbio.2024.105523 · Cited by 13

Integrative Machine Learning, Virtual Screening, and Molecular Modeling for BacA-Targeted Anti-Biofilm Drug Discovery Against Staphylococcal Infections

Almatroudi, A. (2024) · Crystals · doi:10.3390/cryst14121057 · Cited by 13

In silico exploration of potent flavonoids for dengue therapeutics

Phunyal, A., Subin, J. A., & Adhikari, A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0301747 · Cited by 13

Advances in nano-delivery of phytochemicals for glioblastoma treatment

Ambele, M. A., Maebele, L. T., Mulaudzi, T. V., Kungoane, T., & Damane, B. P. (2024) · Discover Nano · doi:10.1186/s11671-024-04172-9 · Cited by 13

Achieving affordable, clean shipping by integrating ship design and clean fuels

Cao, N. N. D., Andrianov, D. I., Vecchi, A., Davis, D., & Brear, M. J. (2025) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2024.104579 · Cited by 13

Barlow Twins deep neural network for advanced 1D drug–target interaction prediction

Schuh, M. G., Boldini, D., Bohne, A. I., & Sieber, S. A. (2025) · Journal of Cheminformatics · doi:10.1186/s13321-025-00952-2 · Cited by 13

Comparative Evaluation and Profiling of Chemical Tools for the Nuclear Hormone Receptor Family 2

Lewandowski, M., Busch, R., Marschner, J. A., & Merk, D. (2025) · ACS Pharmacology & Translational Science · doi:10.1021/acsptsci.4c00719 · Cited by 13

RT-Pred: A web server for accurate, customized liquid chromatography retention time prediction of chemicals

Zakir, M., LeVatte, M., & Wishart, D. S. (2025) · Journal of Chromatography A · doi:10.1016/j.chroma.2025.465816 · Cited by 13

Impact of Persistent Endocrine-Disrupting Chemicals on Human Nuclear Receptors: Insights from In Silico and Experimental Characterization

Ganesh, H., Moran, J., Roy, S., Mathew, J., Ackah-Blay, J., Costello, E., Shan, P., & Dakshanamurthy, S. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26072879 · Cited by 15

Anticancer effects of salvianolic acid A through multiple signaling pathways (Review)

Li, C.-X., Xu, Q., Jiang, S.-T., Liu, D., Tang, C., & Yang, W. (2025) · Molecular Medicine Reports · doi:10.3892/mmr.2025.13541 · Cited by 13

Network pharmacology of apigeniflavan: a novel bioactive compound of Trema orientalis Linn. in the treatment of pancreatic cancer through bioinformatics approaches

Das, R., Agrawal, S., Kumar, P., Singh, A. K., Shukla, P. K., Bhattacharya, I., Tiwari, K. N., Mishra, S. K., & Tripathi, A. K. (2023) · 3 Biotech · doi:10.1007/s13205-023-03570-7 · Cited by 13

Exploring Potentilla nepalensis Phytoconstituents: Integrated Strategies of Network Pharmacology, Molecular Docking, Dynamic Simulations, and MMGBSA Analysis for Cancer Therapeutic Targets Discovery

Praveen, M., Ullah, I., Buendia-Corona, R. E., Khan, I. A., Sayed, M. G., Kabir, R., Bhat, M. A., & Yaseen, M. (2024) · Pharmaceuticals · doi:10.3390/ph17010134 · Cited by 13

Effects of global treaties on commercial chemicals widely used as additives: a meta-analysis of historical measurements of polybrominated diphenyl ethers

Zhong, G., Li, Z., Jones, K. C., & Zhu, Y. B. (2025) · The Lancet Planetary Health · doi:10.1016/s2542-5196(25)00114-7 · Cited by 12

The FMO3/TMAO/HSP90β axis aggravates MAFLD by disrupting mitochondrial protein homeostasis

Guo, J., Wang, Y., Zhang, D., Shi, C., Zhang, X., Li, X., & Gong, Z. (2025) · Cellular Signalling · doi:10.1016/j.cellsig.2025.111960 · Cited by 13

Probing the optimal architecture and molecular mechanism of insect odorant receptor heteromeric channels

Xue, W., Lu, X., Tian-min, Z., Guo, Y., Li, Y.-H., Li, G., Xu, C. S., & Lu, H. (2025) · Communications Biology · doi:10.1038/s42003-025-08572-0 · Cited by 12

In Vitro Evaluation of Flavonoids for Enzyme Inhibition, Antioxidant, Antimicrobial and Anticancer Properties with Molecular Docking Insights

Bayrak, S., Gerni, S., Öztürk, C., Bakan, B., Elmas, Ş., & M.Aliyeva, A. T. M. H. D. N. (2025) · Food Biophysics · doi:10.1007/s11483-025-10034-3 · Cited by 12

Microbially-mediated halogenation and dehalogenation cycling of organohalides in the ocean

Zhou, N., Li, Q., Liang, Z., Yu, K., Zhang, C., Wang, H., Li, P., He, Z., & Wang, S. (2025) · Nature Communications · doi:10.1038/s41467-025-65696-x · Cited by 15

Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals market

von Borries, K. J. F., Beckwith, K. V., Goodman, J. M., Chiu, W. A., Jolliet, O., & Fantke, P. (2026) · Nature Communications · doi:10.1038/s41467-025-67374-4 · Cited by 16

Integrative Computational Chemistry Approaches in Modern Drug Discovery: Advances in Docking, Pharmacophore Modeling, Molecular Dynamics, and Virtual Screening

Altharawi, A., & Alqahtani, S. M. (2026) · Pharmaceutics · doi:10.3390/pharmaceutics18050565 · Cited by 20

Advancing chemical carcinogenicity prediction modeling: opportunities and challenges

Mittal, A., & Ahuja, G. (2023) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2023.04.002 · Cited by 12

Identifying potential drug-target interactions based on ensemble deep learning

Zhou, L., Wang, Y., Peng, L., Li, Z., & Luo, X. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1176400 · Cited by 12

Dissolution thermodynamics and polymorphic transformation behaviors of glutathione

Fu, J., Wang, F., Shi, Y., Wang, C., Zhao, J., Hou, Y., Zhuang, W., Ying, H., Yang, P., & Zhang, K. (2023) · Journal of Molecular Liquids · doi:10.1016/j.molliq.2023.122468 · Cited by 12

Calcium-Alginate-Chitosan Nanoparticle as a Potential Solution for Pesticide Removal, a Computational Approach

Yáñez, O., Alegría‐Arcos, M., Suardíaz, R., Morales‐Quintana, L., Castro, R. I., Palma-Olate, J., Galarza, C. E., Catagua-González, Á., Rojas-Pérez, V. E., Urra, G., et al. (2023) · Polymers · doi:10.3390/polym15143020 · Cited by 12

The Critical Function of microRNAs in Developing Resistance against 5- Fluorouracil in Cancer Cells

Sheikhnia, F., Maghsoudi, H., & Majidinia, M. (2023) · Mini-Reviews in Medicinal Chemistry · doi:10.2174/1389557523666230825144150 · Cited by 12

Drug metabolism-related gene ABCA1 augments temozolomide chemoresistance and immune infiltration abundance of M2 macrophages in glioma

Yan, Y., Liu, Y., Liang, Q., & Xu, Z. (2023) · European journal of medical research · doi:10.1186/s40001-023-01370-6 · Cited by 12

ShinyTPs: Curating Transformation Products from Text Mining Results

Palm, E. H., Chirsir, P., Krier, J., Thiessen, P. A., Zhang, J., Bolton, E., & Schymanski, E. (2023) · Environmental Science & Technology Letters · doi:10.1021/acs.estlett.3c00537 · Cited by 15

Application of the Aliivibrio fischeri bacterium bioassay for assessing single and mixture effects of antibiotics and copper

Narciso, A., Caracciolo, A. B., Grenni, P., Rauseo, J., Patrolecco, L., Spataro, F., & Mariani, L. (2023) · FEMS Microbiology Ecology · doi:10.1093/femsec/fiad125 · Cited by 13

Unveiling the mechanisms of nephrotoxicity caused by nephrotoxic compounds using toxicological network analysis

Xi, K., Zhang, M., Li, M., Tang, Q., Zhao, Q., & Chen, W. (2023) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2023.102075 · Cited by 12

Agro-industrial by-products as alternative additives for the agronomic valorization of pig slurry through pH modification

Chrysanthopoulos, S., Coutinho, J., Silva, A. C., Brito, L., & Fangueiro, D. P. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.140052 · Cited by 12

In vivo distribution of cerebrospinal fluid tracer in human upper spinal cord and brain stem

Melin, E., Pripp, A. H., Eide, P. K., & Ringstad, G. A. (2023) · JCI Insight · doi:10.1172/jci.insight.173276 · Cited by 13

Decoding Drug Response With Structurized Gridding Map-Based Cell Representation

Yin, J., Zhang, H., Sun, X., You, N., Mou, M., Lu, M., Pan, Z., Li, F., Li, H., Zeng, S., et al. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2023.3342280 · Cited by 12

Chia seeds oil ameliorate chronic immobilization stress-induced neurodisturbance in rat brains via activation of the antioxidant/anti-inflammatory/antiapoptotic signaling pathways

Khalifa, N. E., Noreldin, A. E., Khafaga, A. F., El-Beskawy, M., Khalifa, E., El‐Far, A. H., Fayed, A.-H. A., & Zakaria, A. (2023) · Scientific Reports · doi:10.1038/s41598-023-49061-w · Cited by 12

Phytochemical investigation and anti-inflammatory potential of Atriplex leucoclada Boiss

Ahmed, H. S., Mohamed, E. I. A., Amin, E., Moawad, A. S., Abdel‐Bakky, M. S., Almahmoud, S. A., & Afifi, N. (2023) · BMC Complementary Medicine and Therapies · doi:10.1186/s12906-023-04281-5 · Cited by 12

Assessment of iridoids and their similar structures as antineoplastic drugs by in silico approach

Neupane, P., Subin, J. A., & Adhikari, R. (2024) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2024.2314262 · Cited by 12

Prediction and integration of metabolite-protein interactions with genome-scale metabolic models

Habibpour, M., Razaghi‐Moghadam, Z., & Nikoloski, Z. (2024) · Metabolic Engineering · doi:10.1016/j.ymben.2024.02.008 · Cited by 12

Machine learning and DFT coupling: A powerful approach to explore organic amine catalysts for ring-opening polymerization reaction

Zhong, H., Wu, Y., Li, X., & Shi, T. (2024) · Chemical Engineering Science · doi:10.1016/j.ces.2024.119955 · Cited by 12

Evaluation of Antibiotic Biodegradation by a Versatile and Highly Active Recombinant Laccase from the Thermoalkaliphilic Bacterium Bacillus sp. FNT

Sánchez-SanMartín, J., Márquez, S. L., Espina, G., Cortés-Antíquera, R., Sun, J., & Blamey, J. M. (2024) · Biomolecules · doi:10.3390/biom14030369 · Cited by 12

Target prediction and potential application of dihydroartemisinin on hepatocarcinoma treatment

Guo, W., Liu, Y., Chen, B., & Fan, L. (2024) · Naunyn-Schmiedeberg s Archives of Pharmacology · doi:10.1007/s00210-024-03123-6 · Cited by 12

Exploring the mechanism of dendrobine in treating metabolic associated fatty liver disease based on network pharmacology and experimental validation

Li, F., Wu, J., Zhu, Y., Zhang, X., Wang, M., & Zhou, S. (2024) · Hereditas · doi:10.1186/s41065-024-00322-2 · Cited by 12

The mitochondrial calcium uniporter: Balancing tumourigenic and anti‐tumourigenic responses

Colussi, D. M., & Stathopulos, P. B. (2024) · The Journal of Physiology · doi:10.1113/jp285515 · Cited by 12

Computational Screening of Hydrophobic Zeolites for the Removal of Emerging Organic Contaminants from Water

Brauer, J., & Fischer, M. (2024) · ChemPhysChem · doi:10.1002/cphc.202400347 · Cited by 12

Integrating Network Pharmacology with in vitro Experiments to Validate the Efficacy of Celastrol Against Hepatocellular Carcinoma Through Ferroptosis

Cai, B., Qi, M., Zhang, X., & Zhang, D. (2024) · Drug Design Development and Therapy · doi:10.2147/dddt.s450324 · Cited by 12

Investigation of the Anti-Inflammatory Properties of Bioactive Compounds from Olea europaea: In Silico Evaluation of Cyclooxygenase Enzyme Inhibition and Pharmacokinetic Profiling

Karagiannis, T. C., Ververis, K., Liang, J. J., Pitsillou, E., Kagarakis, E. A., Yi, D. T. Z., Xu, V., Hung, A., & El‐Osta, A. (2024) · Molecules · doi:10.3390/molecules29153502 · Cited by 12

Direct RAS inhibitors turn 10

Ostrem, J. M. L., Peters, U., & Shokat, K. M. (2024) · Nature Chemical Biology · doi:10.1038/s41589-024-01691-5 · Cited by 12

Gliotoxin triggers cell death through multifaceted targeting of cancer-inducing genes in breast cancer therapy

Nambiar, S. S., Ghosh, S. S., & Saini, G. K. (2024) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2024.108170 · Cited by 12

Leveraging multiple data types for improved compound-kinase bioactivity prediction

Theisen, R., Wang, T., Ravikumar, B., Rahman, R., & Cichońska, A. (2024) · Nature Communications · doi:10.1038/s41467-024-52055-5 · Cited by 13

Exploration of alpha-glucosidase inhibitors: A comprehensive in silico approach targeting a large set of triazole derivatives

Abchır, O., Khedraoui, M., Yamari, I., Nour, H., Errougui, A., Samadi, A., & Chtita, S. (2024) · PLoS ONE · doi:10.1371/journal.pone.0308308 · Cited by 12

Identification of novel natural compounds against CFTR p.Gly628Arg pathogenic variant

Khan, M. U., Sakhawat, A., Rehman, R., Wali, A. H., Ghani, M. U., Akram, A., Javed, M. A., Ali, Q., Zhou, Y., Ali, D., et al. (2024) · AMB Express · doi:10.1186/s13568-024-01762-9 · Cited by 12

Web of venom: exploration of big data resources in animal toxin research

Zancolli, G., von Reumont, B. M., Anderluh, G., Çalışkan, F., Chiusano, M. L., Fröhlich, J., Hapeshi, E., Hempel, B.-F., Ikonomopoulou, M. P., Jungo, F., et al. (2024) · GigaScience · doi:10.1093/gigascience/giae054 · Cited by 15

An eco-friendly smartphone based HPTLC method versus conventional densitometric one for determination of Naltrexone and Bupropion

Moaaz, E. M., Abdel‐Moety, E. M., Rezk, M. R., & Fayed, A. S. (2024) · BMC Chemistry · doi:10.1186/s13065-024-01285-1 · Cited by 12

Ginsenoside Rg1 improves cigarette smoke-induced ferroptosis in COPD by regulating PERK/ATF4 axis to inhibit endoplasmic reticulum stress

Tan, W., Liang, Z., Tan, X., & Tan, X. (2024) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2024.150946 · Cited by 12

Integrated systems pharmacology, molecular docking, and MD simulations investigation elucidating the therapeutic mechanisms of BHD in Alzheimer’s disease treatment

Chowdhury, M. R., Karamveer, K., Tiwary, B. K., Nampoothiri, N. K., Erva, R. R., & Vijaykumar, S. D. (2024) · Metabolic Brain Disease · doi:10.1007/s11011-024-01460-2 · Cited by 12

Transcend the boundaries: Machine learning for designing polymeric membrane materials for gas separation

Xu, J., Suleiman, A., Liu, G., Zhang, R., Jiang, M., Guo, R., & Luo, T. (2024) · Chemical Physics Reviews · doi:10.1063/5.0205433 · Cited by 16

Exploring novel and potent glycogen synthase kinase-3β inhibitors through systematic drug designing approach

Ganai, S. A., Suma Mohan, S., & Padder, S. A. (2025) · Scientific Reports · doi:10.1038/s41598-025-85868-5 · Cited by 14

Addressing the challenges of acute fish toxicity hazard classification using a non-animal defined approach

Macmillan, D. S., Ambure, P. S., Aranda, V., Bayona, Y., Bonderovic, V., Dawick, J., Fabre, N., Fischer, S., Hodges, G., Mut, Á. L., et al. (2025) · Environmental Toxicology and Chemistry · doi:10.1093/etojnl/vgaf046 · Cited by 12

Identifying new therapeutics for focused ultrasound-enhanced drug delivery in the management of glioblastoma

Holman, R., & McDannold, N. J. (2025) · Frontiers in Oncology · doi:10.3389/fonc.2025.1507940 · Cited by 12

Selected herbicides screened for toxicity and analysed as inhibitors of both cholinesterases

Pehar, V., Kolić, D., Zandona, A., Šinko, G., Katalinić, M., Stepanić, V., & Kovarik, Z. (2023) · Chemico-Biological Interactions · doi:10.1016/j.cbi.2023.110506 · Cited by 12

Evaluation of Metabolomics as Diagnostic Targets in Oral Squamous Cell Carcinoma: A Systematic Review

Alapati, S., Fortuna, G., Ramage, G., & Delaney, C. (2023) · Metabolites · doi:10.3390/metabo13080890 · Cited by 11

A review of SARS-CoV-2 drug repurposing: databases and machine learning models

Elkashlan, M., Ahmad, R. M., Hajar, M., Jasmi, F. A., Corchado, J. M., Nasarudin, N. A., & Mohamad, M. S. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1182465 · Cited by 15

Cytotoxicity Analysis and In Silico Studies of Three Plant Extracts with Potential Application in Treatment of Endothelial Dysfunction

Ungureanu, A. R., Popovici, V., Oprean, C., Danciu, C., Schröder, V., Olaru, O. T., Mihai, D. P., Popescu, L., Luță, E. A., Chițescu, C. L., et al. (2023) · Pharmaceutics · doi:10.3390/pharmaceutics15082125 · Cited by 12

Fusion of Multiple Spectra for Investigating Chemical Bonding Properties via Machine Learning

Guo, S., Jiang, J., Ren, H., & Wang, S. (2023) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.3c01709 · Cited by 12

One product, many patents: Imperfect intellectual property rights in the pharmaceutical industryPreprint

Gupta, C. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3748158 · Cited by 12

ApisTox: a new benchmark dataset for the classification of small molecules toxicity on honey bees

Adamczyk, J., Poziemski, J., & Siedlecki, P. S. (2025) · Scientific Data · doi:10.1038/s41597-024-04232-w · Cited by 12

A membrane permeability database for nonpeptidic macrocycles

Feng, Q., Chavez, D. D., Kihlberg, J. O., & Poongavanam, V. (2025) · Scientific Data · doi:10.1038/s41597-024-04302-z · Cited by 12

Anticancer Potential of Cymbopogon citratus L. Essential Oil: In Vitro and In Silico Insights into Mitochondrial Dysfunction and Cytotoxicity in Cancer Cells

Maksimović, T., Minda, D. I., Şoica, C., Mioc, A., Mioc, M., Colibăşanu, D., Lukinich-Gruia, A. T., Pricop, M.-A., Jianu, C., & Gogulescu, A. (2025) · Plants · doi:10.3390/plants14091341 · Cited by 12

Emerging contaminants of perfluoroalkyl carboxylic acids (PFCAs): a review of sources, occurrence, and accumulation in plants

Wang, C., Jaafar, W. Z. W., Lai, S. H., & Li, J. (2025) · Environmental Geochemistry and Health · doi:10.1007/s10653-025-02766-5 · Cited by 14

Deep Generation Model Guided by the Docking Score for Active Molecular Design

Yang, Y., Hsieh, C., Kang, Y., Hou, T., Liu, H., & Yao, X. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c00572 · Cited by 13

Machine Learning Prediction of the Redox Activity of Quinones

Kichev, I., Borislаvov, L., Tadjer, A., & Stoyanova, R. K. (2023) · Materials · doi:10.3390/ma16206687 · Cited by 10

Binding of perilipin 3 to membranes containing diacylglycerol is mediated by conserved residues within its PAT domain

Stříbný, J., & Schneiter, R. (2023) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2023.105384 · Cited by 11

Machine Learning-Based Screening for Potential Singlet Fission Chromophores: The Challenge of Imbalanced Data Sets

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