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Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition)

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pharmacology".

Deadline for manuscript submissions: 28 February 2026 | Viewed by 19

Special Issue Editor


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Guest Editor
Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Jilin University, Changchun 130012, China
Interests: the relationship between enzyme structure and function; computer-aided drug design; computational structural biology; machine learning
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Special Issue Information

Dear Colleagues,

Network pharmacology is an emerging interdisciplinary field that integrates systems biology, network analysis, and pharmacology to explore the complex interactions between drugs, targets, and diseases. By analyzing the intricate networks of biological systems, network pharmacology aims to provide a holistic understanding of drug actions and their effects on the body, thereby addressing the multifaceted nature of diseases. This approach has revolutionized traditional drug discovery by shifting the focus from single-target to multi-target strategies, enabling the identification of novel therapeutic agents and the optimization of existing ones.

The purpose of this Special Issue is to provide a comprehensive overview of the state of the art in network pharmacology methodologies and their applications in drug discovery and development. We welcome original research articles, review articles, and short communications on one or more of the following topics:

  1. Development, implementation, and application of network pharmacology databases;
  2. Development and application of new network analysis tools and algorithms;
  3. Integration of multi-omics data into network pharmacology studies;
  4. Construction, visualization, and analysis of drug–target interaction networks;
  5. Identification of novel drug targets and pathways through network pharmacology;
  6. Application of network pharmacology in understanding complex diseases and multi-target drug discovery;
  7. Development and application of computational models for predicting drug efficacy and safety;
  8. Case studies on the successful application of network pharmacology in drug discovery and repurposing.

We hope that this Special Issue will serve as an entry point for newcomers into the exciting world of network pharmacology as well as a valuable reference for more experienced practitioners in the field.

Prof. Dr. Weiwei Han
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • network pharmacology
  • machine learning
  • databases
  • drug discovery
  • computer-aided drug design (CADD)
  • data mining

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