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May 8, 2019Quantitative Biology612 citationsOpen Access

Progress in molecular docking

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JFJiyu FanAFAiling FuLZLe Zhang

Key Points

  • The aim is to explore advancements in molecular docking techniques and their applications in drug design.
  • Introduced principles and procedures of molecular docking.
  • Compared various docking applications for efficiency.
  • Reviewed latest innovations such as deep learning integration.
  • Current docking applications face limitations in predicting binding affinity accurately.
  • Recommendation to integrate big biological data into scoring functions for enhancement.
  • Highlighting the evolving nature of molecular docking through advanced computational methods.

Abstract

Background In recent years, since the molecular docking technique can greatly improve the efficiency and reduce the research cost, it has become a key tool in computer‐assisted drug design to predict the binding affinity and analyze the interactive mode. Results This study introduces the key principles, procedures and the widely‐used applications for molecular docking. Also, it compares the commonly used docking applications and recommends which research areas are suitable for them. Lastly, it briefly reviews the latest progress in molecular docking such as the integrated method and deep learning. Conclusion Limited to the incomplete molecular structure and the shortcomings of the scoring function, current docking applications are not accurate enough to predict the binding affinity. However, we could improve the current molecular docking technique by integrating the big biological data into scoring function.

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Cite This Study

Fan et al. (2019) studied this question.

synapsesocial.com/papers/69d6b49aabefa4d4d4aa7f80https://doi.org/10.1007/s40484-019-0172-y
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