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J Phys Chem B. 2018 Mar 8;122(9):2544-2555. doi: 10.1021/acs.jpcb.7b12658. Epub 2018 Feb 22.

Benchmark Study Based on 2P2IDB to Gain Insights into the Discovery of Small-Molecule PPI Inhibitors.

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College of Pharmaceutical Sciences , Zhejiang University , Hangzhou , Zhejiang 310058 , China.
State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health , Macau University of Science and Technology , Avenida Wai Long , Taipa , Macau (SAR) , China.
Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering , Jiangsu University of Technology , Changzhou 213001 , China.
Institute of Functional Nano and Soft Materials (FUNSOM) , Soochow University , Suzhou , Jiangsu 215123 , China.


Protein-protein interactions (PPIs) have been regarded as novel and highly promising drug targets in drug discovery. Numerous new experimental techniques and computational approaches have been developed to assist the design of PPI modulators during the past two decades. However, identification and optimization of small-molecule inhibitors targeting PPIs is still a particularly challenging task due to the "undruggable" profiles of PPI interfaces. Nowadays, in silico screening, especially docking-based virtual screening, has emerged as an effective method to complement experimental high-throughput screening in identifying novel and potent small-molecule PPI inhibitors. Here, on the basis of the 2P2IDB database, we explored the structural features of the known small-molecule PPI inhibitors and analyzed the characteristics of the PPI binding pockets. More importantly, we evaluated the sampling power and screening power of six popular docking programs for PPI targets. Our results indicate that the chlorinated conjugate group and amidelike linkage are two types of privileged fragments of PPI inhibitors; the average druggability of the binding sites of the PPI targets in 2P2IDB is slightly worse than that of traditional ones; both academic and commercial docking programs exhibit an acceptable accuracy on pose prediction for PPI inhibitors, but their screening powers for identifying PPI inhibitors are still not satisfactory. It is expected that our work can provide valuable guidance on the construction of PPI-focused library, the determination of druggable PPI binding pocket, and the selection of docking program for the screening of small-molecule PPI inhibitors.

[Indexed for MEDLINE]

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