Computational methods in drug discovery

Scholarly Works

• Ariyanto, A.; Kusuma, W. A.; Muhaimin, M.; Kamarulzaman, E. E.; Fakih, T. M.; Muchtaridi, M. Integrated Phytochemical and Pharmacological Insights into Premna serratifolia for Drug Discovery: A Narrative Review. Plants 2026, 15, 2176. doi:10.3390/plants15142176
• Afolabi, S. O.; Feoktistova, V. A.; Skorb, E. V.; Shityakov, S. Classical Substructure Search versus LLM-assisted keyword retrieval in SciFinder: A Case Study on GABAB1 Ligand Discovery Using a Phenibut Scaffold. Computational Biology and Chemistry 2026, 109245. doi:10.1016/j.compbiolchem.2026.109245
• Lee, K.; Moldagulov, G.; Grzybowski, B. A. The Fragility of Bioactivity Prediction: Rigorous Dataset Splits Expose the Illusion of ML Accuracy. Chemistry (Weinheim an der Bergstrasse, Germany) 2026, e71208. doi:10.1002/chem.71208
• Guaitoli, V.; Alvarez-Ginarte, Y. M.; Montero-Cabrera, L. A.; De la Nuez Veulens, A.; Leclerc, F. IGF-1 receptor ATP-competitive inhibitors for the treatment of Ewing sarcoma: a comprehensive virtual screening analysis for a dataset of molecules showing a wide range of chemical structures. In silico pharmacology 2026, 14, 160. doi:10.1007/s40203-026-00668-7
• Mohammed, M. O.; Moronfolu, I. A.; Ola-Williams, I. O.; Adediran, R. I. GC–MS phytochemical profiling, antibacterial screening, and molecular docking analysis of the ethanolic extract of Cassia fistula stem-bark: an in-vitro and in-silico approach. Discover Chemistry 2026, 3. doi:10.1007/s44371-026-00766-7
• Ishfaq, A.; Tajammal, A.; Maira, R.; Qureshi, A. W.; Aleeza, B.; Basra, M. A. R. Antibacterial flavonoid derivatives: in silico ADMET, DFT, Molecular Docking, MD Simulation and in vitro verification. In silico pharmacology 2026, 14, 153. doi:10.1007/s40203-026-00644-1
• Howard, J. B.; Narayanasamy, A.; Lindert, S. Improving Protein Structure Prediction Using Integrative Cryo-EM and Ion Mobility Mass Spectrometry Modeling. Journal of chemical theory and computation 2026, 22, 5909–5917. doi:10.1021/acs.jctc.6c00265
• Tuncal, A.; Kalkan, R. Integrative In Silico Identification of TP53-Associated Drug Repurposing Candidates in Lung Adenocarcinoma. Pharmaceuticals (Basel, Switzerland) 2026, 19, 761. doi:10.3390/ph19050761
• Huang, Z.; Yang, L.; Qin, C.; Xing, Y.; Yu, H.; Zhou, X.; Zheng, B.; Wang, Y.; Gao, X.; Yang, W. Disentangled diffusion model for 3D molecular generation with protein-ligand interaction priors. Bioinformatics (Oxford, England) 2026, 42. doi:10.1093/bioinformatics/btag165
• Kumari, N.; Tantray, J.; Agrawal, A.; Nagdev, S.; Kumar, M. V.; Rout, S. K. Strategic Pathways for Future GPCR Research and Development. Emerging Paradigms in Pharmaceutical Research; Springer Nature Singapore, 2026; pp 269–295. doi:10.1007/978-981-95-9081-0_11
• Tyukavin, A. I.; Kadyrov, G. I.; Zharikov, M. V.; Suchkov, S. V. Systems biology and personalized medicine through the lens of bioinformatics. Pharmacy Formulas 2026, 7, 60–79. doi:10.17816/phf700602
• Nadeem, S.; Siddique, F.; Mahmood, K. Theoretical investigation of Push–Pull substituted trans-stilbenes as potential natural chromophores: a DFT and TD-DFT study on charge transfer. Molecular Physics 2026. doi:10.1080/00268976.2026.2664230
• Bostandoost, R.; Lechowicz, A.; Hanafy, W. A.; Shenoy, P.; Hajiesmaili, M. Quantifying the Carbon Reduction of DAG Workloads: A Job Shop Scheduling Perspective. In Proceedings of the 2nd International Workshop on Systems and Methods for Sustainable Large-Scale AI (GreenSys), ACM, 2026; pp 1–6. doi:10.1145/3802973.3804454
• Yılmaz, M.; Kebiroğlu, M. H. Unveiling the Pharmacological Potential of a Pyrazole–Benzodioxole Hybrid Computational Analysis, ADMET Screening, and Molecular Docking Against ABL Tyrosine Kinase. ChemistrySelect 2026, 11. doi:10.1002/slct.73323
• Avdičević, A.; Lešnik, S.; Bren, U.; Čavka, L. CDK4/6 Inhibitors for Breast Cancer Therapy-A Review of Clinical Trials, Structural and Computational Approaches. Pharmaceuticals (Basel, Switzerland) 2026, 19, 610. doi:10.3390/ph19040610
• Espaillat, A. Enhancing Drug Discovery and Development Through Artificial Intelligence. Revolutionizing Ophthalmology; Springer Nature Switzerland, 2026; pp 141–154. doi:10.1007/978-3-032-19336-0_12
• Halahakoon, A. J. In silico analysis of tubulin self-assembly inhibition and pharmaceutical profiling of novel vinca alkaloid derivatives. Journal of Research in Pharmacy 2026, 30, 388–403. doi:10.12991/jrespharm.1695512
• Dauod, S.; Taha, M. O. Recent developments in pharmacophore-based modeling of Ca2+/Calmodulin-dependent protein kinase II delta (CaMkIIδ) inhibitors for heart failure therapy. Expert opinion on drug discovery 2026, 21, 417–431. doi:10.1080/17460441.2026.2643408
• Ameji, P. J.; Uzairu, A.; Shallangwa, G. A.; Uba, S.; Ibrahim, M. T. Chemoinformatics-based discovery of new indole-1,2,4 triazole analogues with potential for the treatment of typhoid fever. Discover Chemistry 2026, 3. doi:10.1007/s44371-026-00559-y
• Zhang, L.; Wang, Z.; Liu, W.; Duan, X.; Dai, Q. Twin cross contrastive learning with multi-modality fusion for drug-target affinity prediction. Artificial intelligence in medicine 2026, 176, 103394. doi:10.1016/j.artmed.2026.103394

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