Combinatorial Chemistry & High Throughput Screening

Journal Impact Factor: 1.7
Scopus Cite Score: 3.5

Indexed in: Scopus, SCI Expanded, MEDLINE/PubMed

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Aims and Scope:
Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal:

  • Target identification and validation
  • Assay design, development, miniaturization and comparison
  • High throughput/high content/in silico screening and associated technologies
  • Label-free detection technologies and applications
  • Stem cell technologies
  • Biomarkers
  • ADMET/PK/PD methodologies and screening
  • Probe discovery and development, hit to lead optimization
  • Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries)
  • Chemical library design and chemical diversity
  • Chemo/bio-informatics, data mining
  • Compound management
  • Pharmacognosy
  • Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products)
  • Natural Product Analytical Studies
  • Bipharmaceutical studies of Natural products
  • Drug repurposing
  • Data management and statistical analysis
  • Laboratory automation, robotics, microfluidics, signal detection technologies
  • Current & Future Institutional Research Profile
  • Technology transfer, legal and licensing issues
  • Patents

In these respective subject areas, Combinatorial Chemistry & High Throughput Screening is intended to function as the most comprehensive and up-to-date medium available. The journal should be of value to individuals engaged in the process of drug discovery and development, in the settings of industry, academia or government.
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Editor-in-Chief:

  • Gerald H. LushingtonMolecular Graphics and Modeling Laboratory
    LiS Consulting
    Lawrence, KS
    United States of America

ISSN: 1386-2073 (Print)

eISSN: 1875-5402 (Online)

Special Issues With Active Call for Papers

Submission closes on: Sep 17, 2026
Multi-Omics and Multimodal Data Fusion in Drug Discovery: From Target Identification to Personalized Therapy

Modern drug discovery faces systemic challenges in combating complex diseases, whose mechanisms involve interactive networks across genomic, transcriptomic, proteomic, metabolomic, and other molecular layers. Single-omics or conventional approaches often fail to capture this complexity comprehensively. This thematic issue explores strategies for integrating multi-omics data (including genomics, transcriptomics, proteomics, metabolomics, and epigenomics) with multimodal information such as chemical structures, bioactivity profiles, clinical phenotypes, imaging features, and real-world data. By leveraging advanced data fusion techniques​(e.g., graph neural... see more

Impact Factor: 1.7
Guest Editor(s): Dr. Huan Yang
Co-Guest Editor(s): Dr. Quan Zou
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