Biomolecules | Highly Cited Papers in 2024–2025 in the “Bioinformatics and Systems Biology” Section

We welcome you to read our most highly cited papers published in 2024 and 2025, which are listed below. As all of the articles published in Biomolecules (ISSN: 2218-273X) are open access, you have free and unlimited access to the full text.

1. “Advances in AI for Protein Structure Prediction: Implications for Cancer Drug Discovery and Development”
by Xinru Qiu, Han Li, Greg Ver Steeg and Adam Godzik
Biomolecules 2024, 14(3), 339; https://doi.org/10.3390/biom14030339
Full text available online: https://www.mdpi.com/2218-273X/14/3/339

2. “SynerGNet: A Graph Neural Network Model to Predict Anticancer Drug Synergy”
by Mengmeng Liu, Gopal Srivastava, J. Ramanujam and Michal Brylinski
Biomolecules 2024, 14(3), 253; https://doi.org/10.3390/biom14030253
Full text available online: https://www.mdpi.com/2218-273X/14/3/253

3. “The Historical Evolution and Significance of Multiple Sequence Alignment in Molecular Structure and Function Prediction”
by Chenyue Zhang, Qinxin Wang, Yiyang Li, Anqi Teng, Gang Hu, Qiqige Wuyun and Wei Zheng
Biomolecules 2024, 14(12), 1531; https://doi.org/10.3390/biom14121531
Full text available online: https://www.mdpi.com/2218-273X/14/12/1531

4. “Structure-Based Approaches for Protein–Protein Interaction Prediction Using Machine Learning and Deep Learning”
by Despoina P. Kiouri, Georgios C. Batsis and Christos T. Chasapis
Biomolecules 2025, 15(1), 141; https://doi.org/10.3390/biom15010141
Full text available online: https://www.mdpi.com/2218-273X/15/1/141

5. “Serum Biomarker Signatures of Choroid Plexus Volume Changes in Multiple Sclerosis”
by Dejan Jakimovski, Robert Zivadinov, Ferhan Qureshi, Murali Ramanathan, Bianca Weinstock-Guttman, Eleonora Tavazzi, Michael G. Dwyer and Niels Bergsland
Biomolecules 2024, 14(7), 824; https://doi.org/10.3390/biom14070824
Full text available online: https://www.mdpi.com/2218-273X/14/7/824

6. “BSA Binding and Aggregate Formation of a Synthetic Amino Acid with Potential for Promoting Fibroblast Proliferation: An In Silico, CD Spectroscopic, DLS, and Cellular Study”
by Hayarpi Simonyan, Rosanna Palumbo, Satenik Petrosyan, Anna Mkrtchyan, Armen Galstyan, Ashot Saghyan, Pasqualina Liana Scognamiglio, Caterina Vicidomini, Marta Fik-Jaskólka and Giovanni N. Roviello
Biomolecules 2024, 14(5), 579; https://doi.org/10.3390/biom14050579
Full text available online: https://www.mdpi.com/2218-273X/14/5/579

7. “Novel Insights into the Antimicrobial and Antibiofilm Activity of Pyrroloquinoline Quinone (PQQ); In Vitro, In Silico, and Shotgun Proteomic Studies”
by Mai M. Labib, Alaa M. Alqahtani, Hebatallah H. Abo Nahas, Rana M. Aldossari, Bandar Fahad Almiman, Sarah Ayman Alnumaani, Mohammad El-Nablaway, Ebtesam Al-Olayan, Maha Alsunbul and Essa M. Saied
Biomolecules 2024, 14(8), 1018; https://doi.org/10.3390/biom14081018
Full text available online: https://www.mdpi.com/2218-273X/14/8/1018

8. “In Silico Investigation of Parkin-Activating Mutations Using Simulations and Network Modeling”
by Naeyma N. Islam, Caleb A. Weber, Matt Coban, Liam T. Cocker, Fabienne C. Fiesel, Wolfdieter Springer and Thomas R. Caulfield
Biomolecules 2024, 14(3), 365; https://doi.org/10.3390/biom14030365
Full text available online: https://www.mdpi.com/2218-273X/14/3/365

9. “GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues”
by Tianjiao Zhang, Ziheng Zhang, Liangyu Li, Jixiang Ren, Zhenao Wu, Bo Gao and Guohua Wang
Biomolecules 2024, 14(4), 436; https://doi.org/10.3390/biom14040436
Full text available online: https://www.mdpi.com/2218-273X/14/4/436

10. “A Review for Artificial Intelligence Based Protein Subcellular Localization”
by Hanyu Xiao, Yijin Zou, Jieqiong Wang and Shibiao Wan
Biomolecules 2024, 14(4), 409; https://doi.org/10.3390/biom14040409
Full text available online: https://www.mdpi.com/2218-273X/14/4/409