Bioinfo Chem
Latest Issue - Volume 7 Number 1 2025
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Bioinfo Chem
Bioinfo and Chem is an international, open access, peer-reviewed journal that publishes: Original Research; Reviews; Hypothesis formation and commentaries in the following fields Computational biomodelling, Bioinformatics, Computational genomics, Mol
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Bioinfo Chem
Volume 7 Number 1 2025
Table of Contents
Research Article
Computational Biology
Prediction of Protein–Metal Ion-Binding Sites Using Sequence Homology and Machine-Learning Methods
Zihan Tian 1, Cao Wei 1, Yutaka Moriwaki 1, Tohru Terada 1, Shugo Nakamura 1, Kazuya Sumikoshi 1, Fang Chun 1, and Kentaro Shimizu 1*
The sensitivity of the machine-learning method was 0.8239, and many metal ion-binding sites were predicted only by the machine-learning method.
Abstract | Full Text |PDF (885 KB) | Open Access Article
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Harmine: A Natural β-Carboline with Promising Multi-Targeted Anticancer Potential
Harmine shows multi-targeted anticancer activity, offering potential as a natural, safer alternative to conventional chemotherapy for various cancers.
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Network Pharmacology and Docking-Based Evaluation of Quercetin as an Inhibitor of PI3K Pathway in Glioblastoma
This study highlights quercetin’s multi-target inhibition of PI3K signaling in GBM, suggesting a safer, plant-based therapeutic alternative.
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Virtual Screening and Computational Analysis of Natural Compound Targeting CDK4/6 for Pan-Cancer Therapeutic Potential
This study identifies Luteolin as a potential multi-target CDK4/6 inhibitor with broader anti-cancer action than current synthetic drugs.
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Computational Elucidation of EGCG Interaction with PD-L1: A Natural Strategy for Immune Checkpoint Modulation in Melanoma
Epigallocatechin gallate (EGCG) offers a safe, natural alternative to antibody therapies by directly targeting PD-L1 and modulating immune response pathways.
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Targeting Mutant KRAS G12C with Berberine Derivatives: A Molecular Docking and Dynamics Approach in Colorectal Cancer
Berberine offers a natural, safe, and multi-pathway alternative for selectively targeting KRAS G12C in colorectal cancer therapy development.
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Artificial Intelligence in Drug Discovery: Systematic Review and Meta-Analysis of Predictive Performance, Structural Modeling, and Translational Reliability
This study demonstrates how AI improves prediction accuracy, accelerates drug discovery, reduces experimental burden, and enhances the reliability of therapeutic design workflows.
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