Artificial Intelligence-Powered Drug Discovery and Development

Dear Colleagues,

Drug development is an expensive and time-consuming process. Compounded with the fact that few drug candidates end with a viable product, tools that can reduce the number of resources spent developing unsuccessful drug candidates are valuable. There are many facets that a successful drug must account for; a drug must not only be effective in altering the target’s activity, but also have favorable pharmacokinetic properties, minimal off-target effects and toxicity, etc. Artificial intelligence (AI)-powered in silico methods that utilize machine learning (ML) and deep learning (DL) algorithms to screen and/or generate compounds can be designed to account for these and a myriad of other chemical features, facilitating either the filtration or generation of compounds that meet the criteria for a viable drug. In vitro and in vivo validations are still necessary parts of the process, of course, but ML/DL models can be a substantial boon to the industry by providing an advantageous starting point in the drug development process.

This Special Issue will focus on advances in AI-powered solutions in the field of drug discovery and development. Both review and original research manuscripts are welcome.

Dr. Xudong Huang
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. Biomolecules is an international peer-reviewed open access monthly 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.

• drug discovery
• artificial intelligence
• machine learning
• deep learning
• virtual screening