Solvent Sites Improve Docking Performance of Protein-Protein Complexes and Protein-Protein Interface-Targeted Drugs

被引:6
|
作者
Mayol, Gonzalo F. [1 ,2 ]
Defelipe, Lucas A. [1 ,2 ,4 ]
Arcon, Juan Pablo [1 ,2 ,3 ]
Turjanski, Adrian G. [1 ,2 ]
Marti, Marcelo A. [1 ,2 ]
机构
[1] Univ Buenos Aires FCEyN UBA, Dept Quim Biol, Fac Ciencias Exactas & Nat, C1428EHA, Buenos Aires, Argentina
[2] Fac Ciencias Exactas & Nat IQUIBICEN CONICET, Inst Quim Biol, C1428EHA, Buenos Aires, Argentina
[3] Inst Res Biomed IRB, Barcelona 08028, Spain
[4] European Mol Biol Lab Hamburg Unit, D-22607 Hamburg, Germany
关键词
MOLECULAR-DYNAMICS SIMULATIONS; WEB SERVER; AMBER; THERMODYNAMICS; IDENTIFICATION; PREDICTION; INHIBITORS;
D O I
10.1021/acs.jcim.2c00264
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Protein-protein interactions (PPIs) are essential, and modulating their function through PPI-targeted drugs is an important research field. PPI sites are shallow protein surfaces readily accessible to the solvent, thus lacking a proper pocket to fit a drug, while their lack of endogenous ligands prevents drug design by chemical similarity. The development of PPI-blocking compounds is, therefore, a tough challenge. Mixed solvent molecular dynamics has been shown to reveal protein-ligand interaction hot spots in protein active sites by identifying solvent sites (SSs). Furthermore, our group has shown that SSs significantly improve protein-ligand docking. In the present work, we extend our analysis to PPI sites. In particular, we analyzed water, ethanol, and phenol-derived sites in terms of their capacity to predict protein-drug and protein-protein interactions. Subsequently, we show how this information can be incorporated to improve both protein-ligand and protein-protein docking. Finally, we highlight the presence of aromatic clusters as key elements of the corresponding interactions.
引用
收藏
页码:3577 / 3588
页数:12
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