Advances in the Use of Computational Methods in the Design of Targeted Pleiotropic Drugs

The multifactorial nature of diseases involving metabolism, cancer and neurodegeneration often requires the use of multiple drugs with widely variable side effect and pharmacokinetic profiles. Additionally, novel ways to disrupt biological activities have been realized through the use of synthetically pleiotropic compounds like PROTACs. However, designing multi-target coverage without encountering undue toxicity remains a significant challenge. This difficult task may be amenable to new techniques like machine learning and physics-based calculations like Free Energy Perturbation. This Research Topic serves to be a focal point for new research and novel reviews addressing the use of new computational techniques for the design of selective pleiotropic drugs

The goals of this Research Topic are as follows:

1) Stimulate a collection of new perspectives on synthetic pleiotropism (e.g. PROTACs, molecular glues)

2) Highlight new computational techniques for affording selective compounds that can still intentionally hit multiple targets

3) Highlight new computational techniques for biological pathway deconvolution especially with respect to cross-pathway feedback

4) Showcase new computational techniques for predicting pleiotropic compounds with good DMPK

For this Research Topic, we encourage the submission of mini-reviews and original publications concerning the following topics:

1) Computational advances in pleiotropic target pathway discovery and validation

2) Computational advances in engineering selectivity against a narrow set of biological targets

3) Computational advances in the design of PROTACs, molecular glues and other compound families employing synthetic pleiotropism

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: Physics-Based Methods, Machine Learning, Medicinal Chemistry, Selectivity, Pleiotropism, Drug Discovery

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.