Dan Hou, Haobin Zhou, Yuting Tang, Ziyuan Liu, Lin Su, Junkai Guo, Janak Lal Pathak, Lihong Wu
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引用次数: 0
Abstract
Purpose: Cancer stands as a significant global public health concern, with traditional therapies potentially yielding severe side effects. Peptide-based cancer therapy is increasingly employed for diseases like cancer due to its advantages of excellent targeting, biocompatibility, and convenient synthesis. With advancements in computer technology and bioinformatics, rational design strategies based on computer technology have been employed to develop more cost-effective and potent anticancer peptides (ACPs). This study aims to explore the current status, hotspots, and future trends in the field of computer-aided design of peptides for cancer treatment through a bibliometric analysis.
Methods: A total of 1547 relevant publications published from 2006 to 2024 were collected from the Web of Science Core Collection. Bibliometric analysis was conducted using tools like CiteSpace, VOSviewer, Bibliometrix, Origin, and an online bibliometric platform.
Results: The research in this field has shown a steady growth trend, with the United States and China making the most significant contributions. Currently, ACP research mainly focuses on cell-penetrating peptides related to drug delivery, which are expected to become future research hotspots. Beyond that, peptide vaccines associated with immunotherapy are also worthy of attention. In addition, molecular dynamics simulation and molecular docking are currently popular research methods. At the same time, deep learning is the emerging keyword, indicating its potential for a more significant impact on future peptide design.
Conclusion: Deep learning technology represents emerging research hotspots with immense potential and promising prospects. As cutting-edge research directions, cellularly penetrating peptides and polypeptide immunotherapy are expected to achieve breakthroughs in cancer treatment. This study provides valuable insights into the computer-aided design of peptides in cancer therapy, contributing significantly to advancing the in-depth research and applications in this area.
期刊介绍：
Drug Design, Development and Therapy is an international, peer-reviewed, open access journal that spans the spectrum of drug design, discovery and development through to clinical applications.
The journal is characterized by the rapid reporting of high-quality original research, reviews, expert opinions, commentary and clinical studies in all therapeutic areas.
Specific topics covered by the journal include:
Drug target identification and validation
Phenotypic screening and target deconvolution
Biochemical analyses of drug targets and their pathways
New methods or relevant applications in molecular/drug design and computer-aided drug discovery*
Design, synthesis, and biological evaluation of novel biologically active compounds (including diagnostics or chemical probes)
Structural or molecular biological studies elucidating molecular recognition processes
Fragment-based drug discovery
Pharmaceutical/red biotechnology
Isolation, structural characterization, (bio)synthesis, bioengineering and pharmacological evaluation of natural products**
Distribution, pharmacokinetics and metabolic transformations of drugs or biologically active compounds in drug development
Drug delivery and formulation (design and characterization of dosage forms, release mechanisms and in vivo testing)
Preclinical development studies
Translational animal models
Mechanisms of action and signalling pathways
Toxicology
Gene therapy, cell therapy and immunotherapy
Personalized medicine and pharmacogenomics
Clinical drug evaluation
Patient safety and sustained use of medicines.
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