抄録
<jats:sec><jats:title>Background</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>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.</jats:p></jats:sec>
収録刊行物
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- Quantitative Biology
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Quantitative Biology 7 (2), 83-89, 2019-06
Wiley