Implications of the Essential Role of Small Molecule Ligand Binding Pockets in Protein-Protein Interactions

被引:9
作者
Skolnick, Jeffrey [1 ]
Zhou, Hongyi [1 ]
机构
[1] Georgia Inst Technol, Ctr Study Syst Biol, Sch Biol Sci, Atlanta, GA 30332 USA
关键词
HOT-SPOTS; BIOLOGY APPROACH; BONE-MARROW; DOCKING; INHIBITOR; SIMILARITY; PREDICTION; ANTIBODIES; INTERFACES; ALGORITHM;
D O I
10.1021/acs.jpcb.2c04525
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Protein-protein interactions (PPIs) and protein-metabolite interactions play a key role in many biochemical processes, yet they are often viewed as being independent. However, the fact that small molecule drugs have been successful in inhibiting PPIs suggests a deeper relationship between protein pockets that bind small molecules and PPIs. We demonstrate that 2/3 of PPI interfaces, including antibody-epitope interfaces, contain at least one significant small molecule ligand binding pocket. In a representative library of 50 distinct protein-protein interactions involving hundreds of mutations, > 75% of hot spot residues overlap with small molecule ligand binding pockets. Hence, ligand binding pockets play an essential role in PPIs. In representative cases, evolutionary unrelated monomers that are involved in different multimeric interactions yet share the same pocket are predicted to bind the same metabolites/drugs; these results are confirmed by examples in the PDB. Thus, the binding of a metabolite can shift the equilibrium between monomers and multimers. This implicit coupling of PPI equilibria, termed "metabolic entanglement ", was successfully employed to suggest novel functional relationships among protein multimers that do not directly interact. Thus, the current work provides an approach to unify metabolomics and protein interactomics.
引用
收藏
页码:6853 / 6867
页数:15
相关论文
共 122 条
  • [1] ICM - A NEW METHOD FOR PROTEIN MODELING AND DESIGN - APPLICATIONS TO DOCKING AND STRUCTURE PREDICTION FROM THE DISTORTED NATIVE CONFORMATION
    ABAGYAN, R
    TOTROV, M
    KUZNETSOV, D
    [J]. JOURNAL OF COMPUTATIONAL CHEMISTRY, 1994, 15 (05) : 488 - 506
  • [2] [Anonymous], P26038 MOES HUMAN
  • [3] [Anonymous], CBLC TISSUE EXPRESSI
  • [4] [Anonymous], 2022, UNIPROTKB P11233 RAL
  • [5] [Anonymous], 2022, UNIPROTKB P29320 EPH
  • [6] Marker metabolites can be therapeutic targets as well
    Arakaki, Adrian K.
    Skolnick, Jeffrey
    McDonald, John F.
    [J]. NATURE, 2008, 456 (7221) : 443 - 443
  • [7] Identification of metabolites with anticancer properties by computational metabolomics
    Arakaki, Adrian K.
    Mezencev, Roman
    Bowen, Nathan J.
    Huang, Ying
    McDonald, John F.
    Skolnick, Jeffrey
    [J]. MOLECULAR CANCER, 2008, 7 (1)
  • [8] Small-Molecule Inhibitors of Protein-Protein Interactions: Progressing toward the Reality
    Arkin, Michelle R.
    Tang, Yinyan
    Wells, James A.
    [J]. CHEMISTRY & BIOLOGY, 2014, 21 (09): : 1102 - 1114
  • [9] Catalytic antibodies in the bone marrow and other organs of Th mice during spontaneous development of experimental autoimmune encephalomyelitis associated with cell differentiation
    Aulova, Kseniya S.
    Urusov, Andrey E.
    Toporkova, Ludmila B.
    Sedykh, Sergey E.
    Shevchenko, Yuliya A.
    Tereshchenko, Valery P.
    Sennikov, Sergei V.
    Budde, Thomas
    Meuth, Sven G.
    Orlovskaya, Irina A.
    Nevinsky, Georgy A.
    [J]. MOLECULAR BIOLOGY REPORTS, 2021, 48 (02) : 1055 - 1068
  • [10] 2P2Idb v2: update of a structural database dedicated to orthosteric modulation of protein-protein interactions
    Basse, Marie-Jeanne
    Betzi, Stephane
    Morelli, Xavier
    Roche, Philippe
    [J]. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION, 2016,