Targeting peptide‐mediated interactions in omics

Peptide‐mediated interactions (PMIs) play a crucial role in cell signaling network, which are responsible for about half of cellular protein–protein associations in the human interactome and have recently been recognized as a new kind of promising druggable target for drug development and disease therapy. In this article, we give a systematic review regarding the proteome‐wide discovery of PMIs and targeting druggable PMIs (dPMIs) with chemical drugs, self‐inhibitory peptides (SIPs) and protein agents, particularly focusing on their implications and applications for therapeutic purpose in omics. We also introduce computational peptidology strategies used to model, analyze, and design PMI‐targeted molecular entities and further extend the concepts of protein context, direct/indirect readout, and enthalpy/entropy effect involved in PMIs. Current issues and future perspective on this topic are discussed. There is still a long way to go before establishment of efficient therapeutic strategies to target PMIs on the omics scale.

[1]  B. Pierce,et al.  Structural Features of Antibody-Peptide Recognition , 2022, Frontiers in Immunology.

[2]  Wei Wu,et al.  Interleukin‐1α, interleukin‐1β and interleukin‐1 receptor antagonist share a common U‐shaped recognition epitope on interleukin‐1 receptor surface , 2022, Journal of molecular recognition : JMR.

[3]  P. Zhou,et al.  Integrated unsupervised-supervised modeling and prediction of protein-peptide affinities at structural level , 2022, Briefings Bioinform..

[4]  J. Ovádi,et al.  Challenges in Discovering Drugs That Target the Protein–Protein Interactions of Disordered Proteins , 2022, International journal of molecular sciences.

[5]  G. Labesse,et al.  SLiMAn: an integrative web server for exploring short linear motif-mediated interactions in interactomes , 2022, bioRxiv.

[6]  Norman E. Davey,et al.  Proteome‐scale mapping of binding sites in the unstructured regions of the human proteome , 2022, Molecular systems biology.

[7]  A. Ivanov,et al.  Interfacial Peptides as Affinity Modulating Agents of Protein-Protein Interactions , 2022, Biomolecules.

[8]  Wanzhi Huang,et al.  Deep Sequencing of a Systematic Peptide Library Reveals Conformationally‐Constrained Protein Interface Peptides that Disrupt a Protein‐Protein Interaction , 2021, Chembiochem : a European journal of chemical biology.

[9]  R. Vincentelli,et al.  Quantitative fragmentomics allow affinity mapping of interactomes , 2021, bioRxiv.

[10]  Yizhou Jiang,et al.  Making ERRFI1-Derived Peptides ‘Bindable’ to the Allosteric Dimerization Interface of Breast Cancer ERBB3 Kinase by Adding a Nonbonded Interaction System , 2021, International Journal of Peptide Research and Therapeutics.

[11]  D. McCafferty,et al.  Predicting PY motif-mediated protein-protein interactions in the Nedd4 family of ubiquitin ligases , 2021, PloS one.

[12]  G. Dittmar,et al.  A Universal Peptide Matrix Interactomics Approach to Disclose Motif-Dependent Protein Binding , 2021, Molecular & cellular proteomics : MCP.

[13]  Xiang Li,et al.  Mig6 not only inhibits EGFR and HER2 but also targets HER3 and HER4 in a differential specificity: Implications for targeted esophageal cancer therapy. , 2021, Biochimie.

[14]  E. Petsalaki,et al.  Use of viral motif mimicry improves the proteome-wide discovery of human linear motifs , 2021, bioRxiv.

[15]  Li Zhao,et al.  Rational Molecular Profiling of Receptor-Associated Late Transducer Peptide Selectivity Across Her/Rtk Kinases , 2021, International Journal of Peptide Research and Therapeutics.

[16]  J. Staiger,et al.  Mapping of domain-mediated protein-protein interaction by SPOT peptide assay , 2021, STAR protocols.

[17]  Norman E. Davey,et al.  Large scale discovery of coronavirus-host factor protein interaction motifs reveals SARS-CoV-2 specific mechanisms and vulnerabilities , 2021, Nature Communications.

[18]  G. King,et al.  Trends in peptide drug discovery , 2021, Nature Reviews Drug Discovery.

[19]  P. He,et al.  Structure‐based derivation and optimization of YAP‐like coactivator‐derived peptides to selectively target TEAD family transcription factors by hydrocarbon stapling and cyclization , 2020, Chemical biology & drug design.

[20]  P. Zhou,et al.  Context contribution to the intermolecular recognition of human ACE2-derived peptides by SARS-CoV-2 spike protein: implications for improving the peptide affinity but not altering the peptide specificity by optimizing indirect readout. , 2020, Molecular omics.

[21]  Y. Matsuura,et al.  Anti-Chikungunya Virus Monoclonal Antibody That Inhibits Viral Fusion and Release , 2020, Journal of Virology.

[22]  C. Ottmann,et al.  Ultra-large chemical libraries for the discovery of high-affinity peptide binders , 2020, Nature Communications.

[23]  Xiaowei Yu,et al.  Machine learning-guided evolution of BMP-2 knuckle Epitope-Derived osteogenic peptides to target BMP receptor II , 2020, Journal of drug targeting.

[24]  Peter K. Sorger,et al.  BIOPHYSICAL PREDICTION OF PROTEIN-PEPTIDE INTERACTIONS AND SIGNALING NETWORKS USING MACHINE LEARNING , 2019, Nature Methods.

[25]  Xiaoxin Yin,et al.  Structure-based derivation and intramolecular cyclization of peptide inhibitors from PD-1/PD-L1 complex interface as immune checkpoint blockade for breast cancer immunotherapy. , 2019, Biophysical chemistry.

[26]  Zhongyan Li,et al.  Is protein context responsible for peptide-mediated interactions? , 2019, Molecular omics.

[27]  P. He,et al.  Genome-wide analysis of LXXLL-mediated DAX1/SHP-nuclear receptor interaction network and rational design of stapled LXXLL-based peptides to target the specific network profile. , 2019, International journal of biological macromolecules.

[28]  B. Zhong,et al.  Design, cyclization, and optimization of MMP13-TIMP1 interaction-derived self-inhibitory peptides against chondrocyte senescence in osteoarthritis. , 2019, International journal of biological macromolecules.

[29]  Peng Zhou,et al.  Machine Learning in Quantitative Protein-peptide Affinity Prediction: Implications for Therapeutic Peptide Design. , 2019, Current drug metabolism.

[30]  Hongbo Chi,et al.  Structure-Based Stepwise Screening of PPARγ Antagonists as Potential Competitors with NCOA1 Coactivator Peptide for PPARγ CIS Site , 2018, International Journal of Peptide Research and Therapeutics.

[31]  P. Zhou,et al.  Disrupting the intramolecular interaction between proto-oncogene c-Src SH3 domain and its self-binding peptide PPII with rationally designed peptide ligands , 2018, Artificial cells, nanomedicine, and biotechnology.

[32]  P. Griffin,et al.  PPARγ in Complex with an Antagonist and Inverse Agonist: a Tumble and Trap Mechanism of the Activation Helix , 2018, iScience.

[33]  Yu-Shan Lin,et al.  Understanding and designing head‐to‐tail cyclic peptides , 2018, Biopolymers.

[34]  James C. Collins,et al.  The Current State of Peptide Drug Discovery: Back to the Future? , 2017, Journal of medicinal chemistry.

[35]  Q. You,et al.  Discovery of a head-to-tail cyclic peptide as the Keap1-Nrf2 protein-protein interaction inhibitor with high cell potency. , 2018, European journal of medicinal chemistry.

[36]  Jing Leng,et al.  Peptide Scaffold-Based Discovery of Nonpeptide Natural Medicines to Target PI3K p85 SH2 Domain , 2018, International Journal of Peptide Research and Therapeutics.

[37]  Yilin Deng,et al.  Rational Optimization of Tumor Suppressor‐Derived Peptide Inhibitor Selectivity between Oncogene Tyrosine Kinases ErbB1 and ErbB2 , 2017, Archiv der Pharmazie.

[38]  P. Güntert,et al.  Proteome‐wide analysis of phospho‐regulated PDZ domain interactions , 2018, Molecular systems biology.

[39]  Junmin Yu,et al.  Structure-based rational design of self-inhibitory peptides to disrupt the intermolecular interaction between the troponin subunits C and I in neuropathic pain. , 2017, Bioorganic chemistry.

[40]  Norman E. Davey,et al.  Discovery of short linear motif‐mediated interactions through phage display of intrinsically disordered regions of the human proteome , 2017, The FEBS journal.

[41]  Ghulam Md Ashraf,et al.  Protein-Protein Interaction (PPI) Network: Recent Advances in Drug Discovery. , 2017, Current drug metabolism.

[42]  Jian Zhu,et al.  Rational derivation of CETP self-binding helical peptides by π-π stacking and halogen bonding: Therapeutic implication for atherosclerosis. , 2016, Bioorganic chemistry.

[43]  Shi-jie Han,et al.  Targeting the SH3 domain of human osteoclast‐stimulating factor with rationally designed peptoid inhibitors , 2016, Journal of peptide science : an official publication of the European Peptide Society.

[44]  Tong Wang,et al.  Rational Design of an Orthogonal Molecular Interaction System at the Complex Interface of Lung Cancer-Related MDM2 Protein with p53 Peptide , 2016 .

[45]  F. Fratev.  PPARγ helix 12 exhibits an antagonist conformation. , 2016, Physical chemistry chemical physics : PCCP.

[46]  Philip M. Kim,et al.  Motif mediated protein-protein interactions as drug targets , 2016, Cell Communication and Signaling.

[47]  N. Yusoff,et al.  A Cell Internalizing Antibody Targeting Capsid Protein (p24) Inhibits the Replication of HIV-1 in T Cells Lines and PBMCs: A Proof of Concept Study , 2016, PloS one.

[48]  T. Pawson,et al.  Selection of recombinant anti‐SH3 domain antibodies by high‐throughput phage display , 2015, Protein science : a publication of the Protein Society.

[49]  Y. Ivarsson,et al.  High-throughput methods for identification of protein-protein interactions involving short linear motifs , 2015, Cell Communication and Signaling.

[50]  Barry Honig,et al.  Predicting Peptide-Mediated Interactions on a Genome-Wide Scale , 2015, PLoS Comput. Biol..

[51]  J. Ladbury,et al.  Potent and selective inhibition of SH3 domains with dirhodium metalloinhibitors , 2015, Chemical science.

[52]  T. Hoffmann,et al.  Peptide therapeutics: current status and future directions. , 2015, Drug discovery today.

[53]  Peng Zhou,et al.  Indirect Readout in Protein-Peptide Recognition: A Different Story from Classical Biomolecular Recognition , 2014, J. Chem. Inf. Model..

[54]  Aidan Budd,et al.  Short linear motifs: ubiquitous and functionally diverse protein interaction modules directing cell regulation. , 2014, Chemical reviews.

[55]  L. Walensky,et al.  Hydrocarbon-Stapled Peptides: Principles, Practice, and Progress , 2014, Journal of medicinal chemistry.

[56]  Tony Pawson,et al.  Large-scale interaction profiling of PDZ domains through proteomic peptide-phage display using human and viral phage peptidomes , 2014, Proceedings of the National Academy of Sciences.

[57]  Chao Yang,et al.  Computational peptidology: a new and promising approach to therapeutic peptide design. , 2013, Current medicinal chemistry.

[58]  Zhi-Min Yuan,et al.  MDM2 and MDMX: Alone and together in regulation of p53. , 2012, Translational cancer research.

[59]  Toby J. Gibson,et al.  iELM—a web server to explore short linear motif-mediated interactions , 2012, Nucleic Acids Res..

[60]  R. Karchin,et al.  Yeast two-hybrid junk sequences contain selected linear motifs , 2011, Nucleic acids research.

[61]  Joost Schymkowitz,et al.  Computational design of peptide ligands. , 2011, Trends in biotechnology.

[62]  Luisa Montecchi-Palazzi,et al.  Combining peptide recognition specificity and context information for the prediction of the 14‐3‐3‐mediated interactome in S. cerevisiae and H. sapiens , 2011, Proteomics.

[63]  Prisca Boisguerin,et al.  Engineering peptide inhibitors to overcome PDZ binding promiscuity. , 2010, Angewandte Chemie.

[64]  Nir London,et al.  Can self‐inhibitory peptides be derived from the interfaces of globular protein–protein interactions? , 2010, Proteins.

[65]  Patrick Aloy,et al.  Novel Peptide-Mediated Interactions Derived from High-Resolution 3-Dimensional Structures , 2010, PLoS Comput. Biol..

[66]  X. Ye,et al.  Cyclophilin A interacts with influenza A virus M1 protein and impairs the early stage of the viral replication , 2009, Cellular microbiology.

[67]  Wei Zhang,et al.  Characterization of Domain-Peptide Interaction Interface , 2009, Molecular & Cellular Proteomics.

[68]  Eduardo Garcia Urdiales,et al.  Accurate Prediction of Peptide Binding Sites on Protein Surfaces , 2009, PLoS Comput. Biol..

[69]  Alejandro Panjkovich,et al.  3did Update: domain–domain and peptide-mediated interactions of known 3D structure , 2008, Nucleic Acids Res..

[70]  R. Russell,et al.  Peptide-mediated interactions in biological systems: new discoveries and applications. , 2008, Current opinion in biotechnology.

[71]  Patrick Aloy,et al.  Contextual Specificity in Peptide-Mediated Protein Interactions , 2008, PloS one.

[72]  Victor Neduva,et al.  Peptides mediating interaction networks: new leads at last. , 2006, Current opinion in biotechnology.

[73]  S. O’Rahilly,et al.  PPARγ and human metabolic disease , 2006 .

[74]  T. Gibson,et al.  Systematic Discovery of New Recognition Peptides Mediating Protein Interaction Networks , 2005, PLoS biology.

[75]  R. Russell,et al.  Linear motifs: Evolutionary interaction switches , 2005, FEBS letters.

[76]  Dongku Kang,et al.  High-Throughput Screening of Novel Peptide Inhibitors of an Integrin Receptor from the Hexapeptide Library by Using a Protein Microarray Chip , 2004, Journal of biomolecular screening.

[77]  Waltraud X. Schulze,et al.  A Novel Proteomic Screen for Peptide-Protein Interactions* , 2004, Journal of Biological Chemistry.

[78]  L. Castagnoli,et al.  Protein Interaction Networks by Proteome Peptide Scanning , 2004, PLoS biology.

[79]  P. Schmieder,et al.  WW domain sequence activity relationships identified using ligand recognition propensities of 42 WW domains , 2003, Protein science : a publication of the Protein Society.

[80]  Sreenath V. Sharma,et al.  UCS15A, a novel small molecule, SH3 domain-mediated protein–protein interaction blocking drug , 2002, Oncogene.

[81]  W. Lim,et al.  Improving SH3 domain ligand selectivity using a non-natural scaffold. , 2000, Chemistry & biology.

[82]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[83]  C. Brown,et al.  Intrinsic protein disorder in complete genomes. , 2000, Genome informatics. Workshop on Genome Informatics.

[84]  F E Cohen,et al.  Exploiting the basis of proline recognition by SH3 and WW domains: design of N-substituted inhibitors. , 1998, Science.

[85]  M. Bukrinsky,et al.  Role of cyclophilin A in the uptake of HIV-1 by macrophages and T lymphocytes. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[86]  D Cowburn,et al.  Modular peptide recognition domains in eukaryotic signaling. , 1997, Annual review of biophysics and biomolecular structure.

[87]  E. Giralt,et al.  Cyclization of disulfide-containing peptides in solid-phase synthesis. , 2009, International journal of peptide and protein research.