Query: Peptide–Protein Interactions: From Drug Design toSupramolecular Biomaterials

Candidate papers:

abstract: The self recognition and self assembly of biomolecules are spontaneous processes that occur in Nature and allow the formation of ordered structures, at the nanoscale or even at the macroscale, under thermodynamic and kinetic equilibrium as a consequence of specific and local interactions. In particular, peptides and peptidomimetics play an elected role, as they may allow a rational approach to elucidate biological mechanisms to develop new drugs, biomaterials, catalysts, or semiconductors. The forces that rule self recognition and self assembly processes are weak interactions, such as hydrogen bonding, electrostatic attractions, and van der Waals forces, and they underlie the formation of the secondary structure (e.g. a helix, b sheet, polyproline II helix) which plays a key role in all biological processes. Here, we present recent and significant examples whereby design was successfully applied to attain the desired structural motifs toward function. These studies are important to understand the main interactions ruling the biological processes and the onset of many pathologies. The types of secondary structure adopted by peptides during self assembly have a fundamental importance not only on the type of nano or macro structure formed but also on the properties of biomaterials, such as the types of interaction, encapsulation, non covalent interaction, or covalent interaction, which are ultimately useful for applications in drug delivery.
author_names: Andrea Caporale

Simone Adorinni

Doriano Lamba

Michele Saviano
title: Peptide Protein Interactions: From Drug Design to Supramolecular Biomaterials
venue: Molecules
year: 2021

abstract: Summary A structural database of peptide protein interactions is important for drug discovery targeting peptide mediated interactions. Although some peptide databases, especially for special types of peptides, have been developed, a comprehensive database of cleaned peptide protein complex structures is still not available. Such cleaned structures are valuable for docking and scoring studies in structure based drug design. Here, we have developed PepBDB a curated Peptide Binding DataBase of biological complex structures from the Protein Data Bank (PDB) PepBDB presents not only cleaned structures but also extensive information about biological peptide protein interactions, and allows users to search the database with a variety of options and interactively visualize the search results. Availability and implementation PepBDB is available at http:/huanglab.phys.hust.edu.cn/pepbdb/
author_names: Zeyu Wen

Jiahua He

Huanyu Tao

Shengyou Huang
title: PepBDB: a comprehensive structural database of biological peptide protein interactions
venue: Bioinform.
year: 2019

abstract: Fluorinated compounds, while rarely used by nature, are emerging as fundamental ingredients in biomedical research, with applications in drug discovery, metabolomics, biospectroscopy, and, as the focus of this review, peptide/protein engineering. Leveraging the fluorous effect to direct peptide assembly has evolved an entirely new class of organofluorine building blocks from which unique and bioactive materials can be constructed. Here, we discuss three distinct peptide fluorination strategies used to design and induce peptide assembly into nano micro and macro supramolecular states that potentiate high ordered organization into material scaffolds. These fluorine tailored peptide assemblies employ the unique fluorous environment to boost biofunctionality for a broad range of applications, from drug delivery to antibacterial coatings. This review provides foundational tactics for peptide fluorination and discusses the utility of these fluorous directed hierarchical structures as material platforms in diverse biomedical applications.
author_names: Janna N Sloand

Scott H Medina
title: Fluorinated peptide biomaterials
venue: Peptide science
year: 2021

abstract: The Rosetta Peptiderive protocol identifies, in a given structure of a protein protein interaction, the linear polypeptide segment suggested to contribute most to binding energy. Interactions that feature a 'hot segment' a linear peptide with significant binding energy compared to that of the complex, may be amenable for inhibition and the peptide sequence and structure derived from the interaction provide a starting point for rational drug design. Here we present a web server for Peptiderive, which is incorporated within the ROSIE web interface for Rosetta protocols. A new feature of the protocol also evaluates whether derived peptides are good candidates for cyclization. Fast computation times and clear visualization allow users to quickly assess the interaction of interest. The Peptiderive server is available for free use at http:/rosie.rosettacommons.org/peptiderive.
author_names: Yuval Sedan

Orly Marcu

Sergey Lyskov

Ora Schueler-Furman
title: Peptiderive server: derive peptide inhibitors from protein protein interactions
venue: Nucleic Acids Res.
year: 2016

abstract: The dynamic formation of selective protein protein interactions is an essential part of the cellular signal transduction cascades. Although these interactions have a great potential for drug development, disruption of protein protein interactions with small molecules has been proven difficult. We have used a rational approach to map sequences that participate in protein protein interactions and have demonstrated that peptides corresponding to these sequences act as highly specific inhibitors or activators of signalling events and can serve as selective drugs, in basic research and in animal models of human diseases.
author_names: Daria Mochly-Rosen

Nir Qvit
title: Peptide inhibitors of protein protein interactions: From rational design to the clinic
year: 2010

abstract: Cyclic peptides are a promising class of bioactive molecules potentially capable of modulating "difficult" targets, such as protein protein interactions. Cyclic peptides have long been used as therapeutics derived from natural product derivatives, but remain an underexplored class of compounds from the perspective of rational drug design, possibly due to the known weaknesses of peptide drugs in general. While cyclic peptides are non"druglike" by the accepted empirical rules, their unique structure may lend itself to both membrane permeability and proteolytic resistance the main barriers to oral delivery. The constrained shape of cyclic peptides also lends itself better to virtual screening approaches, and new tools and successes in this area have been recently noted. An increasing number of strategies are available, both to generate and screen cyclic peptide libraries, and best practises and current successes are described within. This chapter will describe various computational strategies for virtual screening cyclic peptides, along with known implementations and applications. We will explore the generation and screening of diverse combinatorial virtual libraries, incorporating a range of cyclization strategies and structural modifications. More advanced approaches covered include evolutionary algorithms designed to aid in screening large structural libraries, machine learning approaches, and harnessing bioinformatics resources to bias cyclic peptide virtual libraries towards known bioactive structures.
author_names: Fergal J Duffy

Marc Devocelle

Denis C Shields
title: Computational approaches to developing short cyclic peptide modulators of protein protein interactions.
venue: Methods in molecular biology
year: 2015

abstract: A summary of the current status of the application of peptidomimetics in cancer therapeutics as an alternative to peptide drugs is provided. Only compounds that are used in therapy or at least under clinical trials are discussed, using inhibitors of farnesyltransferase, proteasome and matrix metalloproteinases as examples. The design and synthesis of peptidomimetics are most important because of the dominant position peptide and protein protein interactions play in molecular recognition and signalling, especially in living systems. The design of peptidomimetics can be viewed from several different perspectives and peptidomimetics can be categorized in a number of different ways. Study of the vast literature would suggest that medicinal and organic chemists, who deal with peptide mimics, utilize these methods in many different ways. Conventional methods used to treat cancer, from non specific chemotherapy to modern molecularly targeted drugs have generated limited results due to the complexity of the disease as well as lack of molecular classes that can be developed into treatments rapidly, easily and economically. Peptidomimetics that are easy to synthesize and optimize and has been studied in different oncology applications as great biologically amenable compounds and can be considered as a promising alternative molecular class for anticancer drug developments. Peptide can be utilized directly as a cytotoxic agent through various mechanisms or can act as a carrier of cytotoxic agents and radioisotopes by specifically targeting cancer cells. Peptide based hormonal therapy has been extensively studied and utilized for the treatment of breast and prostate cancers. Tremendous amount of clinical data is currently available attesting to the efficiency of peptide based cancer vaccines. Keywords Farnesyltransferase inhibitors, Ras, Metal loproteinase inhibitors, Angiogenesis, Proteasome inhibitors.
author_names: Jeevan R Rajguru

Sonali A Nagare

Ashish A Gawai

Amol G Jadhao

Mrunal K Shirsat
title: Cancer Chemotherapy with Peptides and Peptidomimetics Drug and Peptide Based Vaccines
year: 2019

abstract: Author(s) Smith, Sarah Jane Advisor(s) Tezcan, F. Akif Abstract: Protein protein interactions are ubiquitous throughout nature at many length and time scales from transient interactions between individual proteins for signaling and electron transfer to the self assembly over large distances of bacterial S layer protein coats. Extensive research has been undertaken to attempt to mimic, interrogate, interrupt, or design protein protein interactions, but natural protein protein interactions often form as a result of many accumulated weak interactions over large, heterogeneous molecular surfaces, making them challenging to design. As a way to overcome these challenges, we have previously introduced methods of synthesizing protein protein interactions with minimal surface design through the directional and highly controllable coordination of metal ions on protein surfaces. The goal of this thesis work has been to expand the scope and functionality of these metal directed protein and peptide interactions. First, we show that, like proteins, short peptides can be directed to fold and assemble in biologically relevant ways using coordination chemistry, while incorporating additional metal based functionality on the peptide backbone. We then extend the scale of protein self assembly to highly ordered, crystalline protein nanotubes with tunable diameters. Finally, we demonstrate the ability to assemble protein DNA nanomaterials in a manner that, similar to what is observed in nature, relies on the sum of a number of weak interactions to form highly ordered protein DNA arrays. Overall, we demonstrate the ability to use metal ions to coordinate interactions on scales as small as single protein protein interactions to as large as micrometer scale arrays. Here, we have expanded the functionality of these metal directed protein and peptide interactions. First, we show that peptides can be directed to fold and assemble in biologically relevant ways using coordination chemistry, while incorporating additional metal based functionality on the peptide backbone. We then extend the scale of assembly to highly ordered, crystalline protein nanotubes with tunable diameters. Finally, we demonstrate the ability to assemble protein DNA nanomaterials in a manner that, similar to what is observed in nature, relies on the sum of a number of weak interactions to form highly ordered protein DNA arrays. Overall, we demonstrate the ability to use metal ions to coordinate interactions on scales as small as single protein protein interactions to as large as micrometer scale arrays.
author_names: Sarah Jane Smith
title: Metal Controlled Assembly of Peptide and Protein based Engineered Biomaterials
year: 2016

abstract: Background Protein peptide interactions play a fundamental role in a wide variety of biological processes, such as cell signaling, regulatory networks, immune responses, and enzyme inhibition. Peptides are characterized by low toxicity and small interface areas; therefore, they are good targets for therapeutic strategies, rational drug planning and protein inhibition. Approximately 10% of the ethical pharmaceutical market is protein/peptide based. Furthermore, it is estimated that 40% of protein interactions are mediated by peptides. Despite the fast increase in the volume of biological data, particularly on sequences and structures, there remains a lack of broad and comprehensive protein peptide databases and tools that allow the retrieval, characterization and understanding of protein peptide recognition and consequently support peptide design. Results We introduce Propedia, a comprehensive and up to date database with a web interface that permits clustering, searching and visualizing of protein peptide complexes according to varied criteria. Propedia comprises over 19,000 high resolution structures from the Protein Data Bank including structural and sequence information from protein peptide complexes. The main advantage of Propedia over other peptide databases is that it allows a more comprehensive analysis of similarity and redundancy. It was constructed based on a hybrid clustering algorithm that compares and groups peptides by sequences, interface structures and binding sites. Propedia is available through a graphical, user friendly and functional interface where users can retrieve, and analyze complexes and download each search data set. We performed case studies and verified that the utility of Propedia scores to rank promissing interacting peptides. In a study involving predicting peptides to inhibit SARS CoV 2 main protease, we showed that Propedia scores related to similarity between different peptide complexes with SARS CoV 2 main protease are in agreement with molecular dynamics free energy calculation. Conclusions Propedia is a database and tool to support structure based rational design of peptides for special purposes. Protein peptide interactions can be useful to predict, classifying and scoring complexes or for designing new molecules as well. Propedia is up to date as a ready to use webserver with a friendly and resourceful interface and is available at: https:/bioinfo.dcc.ufmg.br/propedia
author_names: Pedro M Martins

Lucianna Helene Santos

Diego Cesar Batista Mariano

Felippe C Queiroz

Luana L Bastos

Isabela de S Gomes

Pedro H C Fischer

Rafael E O Rocha

Sabrina de Azevedo Silveira

Leonardo H F de Lima

Mariana T Q de Magalhaes

Maria G A Oliveira

Raquel Cardoso de Melo Minardi
title: Propedia: a database for protein peptide identification based on a hybrid clustering algorithm
venue: BMC Bioinform.
year: 2021

abstract: A large number of protein protein interactions (PPIs) are mediated by the interactions between proteins and peptide segments in binding partners, and therefore determination of protein peptide interactions (PpIs) is quite crucial to elucidate important biological processes and design peptides or peptidomimetic drugs that can modulate PPIs. Nowadays, as a powerful computation tool, molecular docking has been widely utilized to predict the binding structures of protein peptide complexes. However, although a number of docking programs have been available, the systematic study on the assessment of their performance for PpIs has never been reported. In this study, a benchmark dataset consisting of 185 protein peptide complexes with peptide length ranging from 5 to 20 residues was employed to evaluate the performance of fourteen docking programs, including three protein protein docking programs (ZDOCK, FRODOCK, and HawkDock) three small molecule docking programs (GOLD, Surflex Dock, and AutoDock Vina) and eight protein peptide docking programs (GalaxyPepDock, MDockPeP, HPEPDOCK, CABS dock, pepATTRACT, DINC, AutoDock CrankPep (ADCP) and HADDOCK peptide docking) A new evaluation parameter, named IL_RMSD, was proposed to measure the docking accuracy. In global docking, HPEPDOCK performs the best to the entire dataset and yields the success rates of 4.3% 27.0% and 58.9% at the top 1, 10 and 100 levels, respectively. In local docking, overall, ADCP achieves the best predictions and reaches the success rates of 11.9% 39.5% and 72.4% at the top 1, 10 and 100 levels, respectively. Furthermore, based on the assessment results, HAVM, a new global docking strategy that employed ADCP to optimize the conformations generated by HPEPDOCK and then re ranked these conformations by VoroMQA (a scoring function for protein complexes) was presented, which shows significantly better performance than HPEPDOCK in our benchmark with the success rates of 9.7% 39.5% and 65.9% at the top 1, 10, 100 levels, respectively. It is expected that our work can provide some helpful insights into the selection and development of improved docking programs for PpIs.
author_names: Gaoqi Weng

Junbo Gao

Zhe Wang

Ercheng Wang

Xueping Hu

Xiaojun Yao

Dongsheng Cao

Tingjun Hou
title: Comprehensive Evaluation of Fourteen Docking Programs on Protein Peptide Complexes and A New Strategy for Improving the Performance of Global Docking.
venue: Journal of chemical theory and computation
year: 2020