Insights on peptide topology in the computational design of protein ligands: the example of lysozyme binding peptides

被引:3
|
作者
Cantarutti, Cristina [1 ]
Vargas, M. Cristina [2 ]
Foumthuim, Cedrix J. Dongmo [1 ,3 ]
Dumoulin, Mireille [4 ]
La Manna, Sara [5 ]
Marasco, Daniela [5 ]
Santambrogio, Carlo [6 ]
Grandori, Rita [6 ]
Scoles, Giacinto [1 ]
Soler, Miguel A. [1 ,7 ]
Corazza, Alessandra [1 ]
Fortuna, Sara [1 ,7 ,8 ]
机构
[1] Univ Udine, Dept Med, Piazzale M Kolbe 4, I-33100 Udine, Italy
[2] Ctr Invest & Estudios Avanzados, Dept Fis Aplicada, Unidad Merida, Inst Politecn Nacl Cinvestav, Apartado Postal 73 Cordemex, Merida 97310, Mexico
[3] Ca Foscari Univ Venice, Dept Mol Sci & Nanosyst, Campus Sci Via Torino 155, I-30172 Venice, Italy
[4] Univ Liege, Ctr Prot Engn, Dept Life Sci, InBios, Liege, Belgium
[5] Univ Naples Federico II, Dept Pharm, I-80134 Naples, Italy
[6] Univ Milano Bicocca, Dept Biotechnol & Biosci, Piazza Sci, Milan, Italy
[7] Italian Inst Technol IIT, Via Melen 83,B Block, I-16152 Genoa, Italy
[8] Univ Trieste, Dept Chem & Pharmaceut Sci, Via Giorgieri 1, I-34127 Trieste, Italy
关键词
MOLECULAR-DYNAMICS; STRUCTURAL-CHANGES; ORGANIC-MOLECULES; HIGH-AFFINITY; TEMPERATURE; RECOGNITION; SITE;
D O I
10.1039/d1cp02536h
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
Herein, we compared the ability of linear and cyclic peptides generated in silico to target different protein sites: internal pockets and solvent-exposed sites. We selected human lysozyme (HuL) as a model target protein combined with the computational evolution of linear and cyclic peptides. The sequence evolution of these peptides was based on the PARCE algorithm. The generated peptides were screened based on their aqueous solubility and HuL binding affinity. The latter was evaluated by means of scoring functions and atomistic molecular dynamics (MD) trajectories in water, which allowed prediction of the structural features of the protein-peptide complexes. The computational results demonstrated that cyclic peptides constitute the optimal choice for solvent exposed sites, while both linear and cyclic peptides are capable of targeting the HuL pocket effectively. The most promising binders found in silico were investigated experimentally by surface plasmon resonance (SPR), nuclear magnetic resonance (NMR), and electrospray ionization mass spectrometry (ESI-MS) techniques. All tested peptides displayed dissociation constants in the micromolar range, as assessed by SPR; however, both NMR and ESI-MS suggested multiple binding modes, at least for the pocket binding peptides. A detailed NMR analysis confirmed that both linear and cyclic pocket peptides correctly target the binding site they were designed for.
引用
收藏
页码:23158 / 23172
页数:15
相关论文
共 50 条
  • [1] Computational design of peptide ligands
    Vanhee, Peter
    van der Sloot, Almer M.
    Verschueren, Erik
    Serrano, Luis
    Rousseau, Frederic
    Schymkowitz, Joost
    TRENDS IN BIOTECHNOLOGY, 2011, 29 (05) : 231 - 239
  • [2] PepComposer: computational design of peptides binding to a given protein surface
    Obarska-Kosinska, Agnieszka
    Iacoangeli, Alfredo
    Lepore, Rosalba
    Tramontano, Anna
    NUCLEIC ACIDS RESEARCH, 2016, 44 (W1) : W522 - W528
  • [3] Computational design of cyclic peptides to inhibit protein-peptide interactions
    Delaunay, Maxence
    Ha-Duong, Tap
    BIOPHYSICAL CHEMISTRY, 2023, 296
  • [4] Computational Design of Peptide Ligands for Ochratoxin A
    Heurich, Meike
    Altintas, Zeynep
    Tothill, Ibtisam E.
    TOXINS, 2013, 5 (06): : 1202 - 1218
  • [5] Computational Design of the Sequence and Structure of a Protein-Binding Peptide
    Sammond, Deanne W.
    Bosch, Dustin E.
    Butterfoss, Glenn L.
    Purbeck, Carrie
    Machius, Mischa
    Siderovski, David P.
    Kuhlman, Brian
    JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 2011, 133 (12) : 4190 - 4192
  • [6] Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands
    King, Matthew D.
    Phillips, Paul
    Turner, Matthew W.
    Katz, Michael
    Lew, Sarah
    Bradburn, Sarah
    Andersen, Tim
    McDougal, Owen M.
    BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION, 2016, 44 (01) : 63 - 67
  • [7] Synthetic and Computational Design Insights toward Mimicking Protein Binding of Phosphate
    Fowler, Whitney C.
    Deng, Chuting
    Teodoro, O. Therese
    de Pablo, Juan J.
    Tirrell, Matthew V.
    BIOCONJUGATE CHEMISTRY, 2024, 35 (03) : 300 - 311
  • [8] Computational and Theoretical Insights into Protein and Peptide Translocation
    Makarov, Dmitrii E.
    PROTEIN AND PEPTIDE LETTERS, 2014, 21 (03): : 217 - 226
  • [9] Computational Prediction of Protein-Peptide Binding
    Antes, Iris
    Glaser, Manuel
    Patronov, Atanas
    BIOPHYSICAL JOURNAL, 2014, 106 (02) : 647A - 647A
  • [10] Computational insights into the molecular dynamics of the binding of ligands in the methanol dehydrogenase
    Lee, One-Sun
    Lee, Sung Haeng
    CHEMISTRY LETTERS, 2024, 53 (08)