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Recent Advances in Artificial Intelligence-Based Drug Discovery

This special issue belongs to the section “Computational and Theoretical Chemistry“.

Special Issue Information

Dear Colleagues,

Drug discovery is the process through which potential new compounds are identified by means of biology, chemistry, and pharmacology. Billions of dollars are invested annually in research aimed at discovering, designing, and developing new drugs for a wide range of diseases. However, the research and development of novel drugs are still time-consuming and sometimes difficult to accomplish. With the development of new experimental techniques, vast amounts of datasets now flow through the different stages of drug development. Biomedical research, especially for the field of drug discovery, is currently experiencing a global paradigm shift with artificial intelligence (AI) technologies and their application to “Big Data”. Therefore, a key challenge for future drug discovery research is the development of powerful AI-based computational tools that can capture multiple dimensions of biomedical insights. We invite investigators to contribute research articles and reviews describing recent findings which use AI-based computational techniques for research in computer-aided drug discovery.

Prof. Dr. Xing Chen
Prof. Dr. Qi Zhao
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). 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

  • drug–target interactions prediction
  • small molecule drug–noncoding RNA association prediction
  • drug–pathway interaction prediction
  • synergistic drug combination prediction
  • anti-cancer drug response prediction
  • drug–drug interaction prediction
  • computer-aided drug design
  • computational drug repositioning

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Molecules - ISSN 1420-3049