The AAPS Journal

, 20:59 | Cite as

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications

Review Article Theme: Pharmaceutical Sciences in the Era of Big Data Computing
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  1. Theme: Pharmaceutical Sciences in the Era of Big Data Computing

Abstract

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

KEY WORDS

fragment-based drug design fragment database drug discovery fragment docking virtual screening 

Notes

Acknowledgements

The authors would like to acknowledge the funding supports to the Xie laboratory from the NIH NIDA (P30 DA035778A1) and DOD (W81XWH-16-1-0490). The first author would like to thank Jie in particular, for the consistant support, love, and the memorable and solemn wedding. How lucky the first author is to have Jie as his bride!

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no competing interest.

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Copyright information

© American Association of Pharmaceutical Scientists 2018

Authors and Affiliations

  1. 1.Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of PharmacyUniversity of PittsburghPittsburghUSA
  2. 2.NIH National Center of Excellence for Computational Drug Abuse ResearchUniversity of PittsburghPittsburghUSA
  3. 3.Drug Discovery InstituteUniversity of PittsburghPittsburghUSA
  4. 4.Department of Computational Biology, School of MedicineUniversity of PittsburghPittsburghUSA
  5. 5.Department of Structural Biology, School of MedicineUniversity of PittsburghPittsburghUSA

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