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Search Results: CCHTS
Combinatorial Chemistry & High Throughput Screening
ISSN: 1386-2073 (Print)
eISSN: 1875-5402 (Online)
Impact Factor :
1.6
CiteScore:
3.1
- 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.
Editor-in-Chief:
LiS Consulting
Lawrence, KS
USA
Special Issues With Active Call for Papers
Artificial Intelligence Methods for Biomedical, Biochemical and Bioinformatics Problems
Recently, a large number of technologies based on artificial intelligence have been developed and applied to solve a diverse range of problems in the areas of biomedical, biochemical and bioinformatics problems. By utilizing powerful computing resources and massive amounts of data, methods based on artificial intelligence can significantly improve the reliability and performance of many devices and platforms for biomedical, biochemical and bioinformatics applications. Techniques including machine learning, deep neural networks, artificial intelligence, optimization algorithms,... see more
Exploring Spectral Graph Theory in Combinatorial Chemistry
Combinatorial chemistry involves the synthesis and analysis of a large number of diverse compounds simultaneously. Traditional methods rely on brute-force experimentation, which can be time-consuming and resource-intensive. Spectral graph theory, a branch of mathematics dealing with the properties of graphs in relation to the eigenvalues and eigenvectors of matrices associated with the graph, offers a unique perspective for studying molecular structures and relationships. Objectives: This aims to explore the application of Spectral Graph Theory in... see more
Intersection of Chemical Graph Theory and Molecular Sciences
Chemical graph theory has become increasingly critical in molecular sciences, offering advanced capabilities in the modeling, design, and analysis of chemical structures via molecular graphs. This special issue aims to not only explore these fundamental aspects but also to push the boundaries of CCHTS applications. By integrating the concept of metric dimension—a tool to measure the uniqueness of a structure's chemical properties—this issue will highlight innovative approaches in studying chemical biological activity, profiles, product reactivity,... see more
Advances in the design of antibody & protein with conformational dynamics and artificial intelligence approaches
“Antibodies & Protein Design” section focuses on the utilization of multiple strategies to engineer and optimize antibodies and proteins that serve diverse analytical strategies, such as combinatorial protein design, structure-based design, sequence-based design, and other techniques that incorporate principles of protein-protein interactions, allosteric regulation, and post-translational modifications. Example applications include targeted drug delivery, immunotherapy, and immunoassay development, each supporting advances in medicine, healthcare, and broader biotechnology. see more
Sustainable Combinatorial Chemistry for Green Process Development
Combining combinatorial chemistry with chemical engineering and green chemistry principles can directly contribute to the development of more environmentally friendly, economical and efficient chemical processes. Therefore, the proposed theme provides a framework that addresses both industrial and academic studies in terms of developing sustainability and environmentally friendly chemical processes. It can serve as a bridge that can attract the attention of chemical engineers and applied chemistry researchers. The scope of this theme covers the following... see more