scholarly journals Macrocycles as protein–protein interaction inhibitors

2017 ◽  
Vol 474 (7) ◽  
pp. 1109-1125 ◽  
Author(s):  
Patrick G. Dougherty ◽  
Ziqing Qian ◽  
Dehua Pei
Keyword(s):  
Small Molecules ◽  
Protein Interactions ◽  
Cyclic Peptides ◽  
Macrocyclic Compounds ◽  
Protein Protein Interactions ◽  
Intracellular Protein ◽  
Drug Candidates ◽  
Protein Protein Interaction ◽  
The Past ◽  
Conventional Drug

Macrocyclic compounds such as cyclic peptides have emerged as a new and exciting class of drug candidates for inhibition of intracellular protein–protein interactions, which are challenging targets for conventional drug modalities (i.e. small molecules and proteins). Over the past decade, several complementary technologies have been developed to synthesize macrocycle libraries and screen them for binding to therapeutically relevant targets. Two different approaches have also been explored to increase the membrane permeability of cyclic peptides. In this review, we discuss these methods and their applications in the discovery of macrocyclic compounds against protein–protein interactions.

scholarly journals Discovery of cell active macrocyclic peptides with on-target inhibition of KRAS signaling

2021 ◽  
Author(s):  
Shuhui Lim ◽  
Nicolas Boyer ◽  
Nicole Boo ◽  
Chunhui Huang ◽  
Gireedhar Venkatachalam ◽  
...  
Keyword(s):  
Small Molecules ◽  
Protein Interactions ◽  
Therapeutic Targets ◽  
Protein Protein Interactions ◽  
Intracellular Protein ◽  
Macrocyclic Peptides

Macrocyclic peptides have the potential to address intracellular protein-protein interactions (PPIs) of high value therapeutic targets that have proven largely intractable to small molecules. Here, we report broadly applicable lessons...

scholarly journals Recent advances in the development of protein–protein interactions modulators: mechanisms and clinical trials

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Haiying Lu ◽  
Qiaodan Zhou ◽  
Jun He ◽  
Zhongliang Jiang ◽  
Cheng Peng ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Drug Discovery ◽  
Small Molecules ◽  
Protein Interactions ◽  
Clinical Studies ◽  
New Drugs ◽  
Protein Protein Interactions ◽  
The Past ◽  
Recent Advances ◽  
Novel Drugs

Abstract Protein–protein interactions (PPIs) have pivotal roles in life processes. The studies showed that aberrant PPIs are associated with various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Therefore, targeting PPIs is a direction in treating diseases and an essential strategy for the development of new drugs. In the past few decades, the modulation of PPIs has been recognized as one of the most challenging drug discovery tasks. In recent years, some PPIs modulators have entered clinical studies, some of which been approved for marketing, indicating that the modulators targeting PPIs have broad prospects. Here, we summarize the recent advances in PPIs modulators, including small molecules, peptides, and antibodies, hoping to provide some guidance to the design of novel drugs targeting PPIs in the future.

Small-molecule modulation of p53 protein-protein interactions

2020 ◽  
Vol 401 (8) ◽  
pp. 921-931 ◽  
Author(s):  
Ave Kuusk ◽  
Helen Boyd ◽  
Hongming Chen ◽  
Christian Ottmann
Keyword(s):  
Tumor Suppressor ◽  
Small Molecules ◽  
Small Molecule ◽  
Protein Interactions ◽  
P53 Protein ◽  
Tumor Suppressor Protein ◽  
Protein Protein Interactions ◽  
Mdm2 Protein ◽  
Protein Protein Interaction ◽  
Altered Proteins

AbstractSmall-molecule modulation of protein-protein interactions (PPIs) is a very promising but also challenging area in drug discovery. The tumor suppressor protein p53 is one of the most frequently altered proteins in human cancers, making it an attractive target in oncology. 14-3-3 proteins have been shown to bind to and positively regulate p53 activity by protecting it from MDM2-dependent degradation or activating its DNA binding affinity. PPIs can be modulated by inhibiting or stabilizing specific interactions by small molecules. Whereas inhibition has been widely explored by the pharmaceutical industry and academia, the opposite strategy of stabilizing PPIs still remains relatively underexploited. This is rather interesting considering the number of natural compounds like rapamycin, forskolin and fusicoccin that exert their activity by stabilizing specific PPIs. In this review, we give an overview of 14-3-3 interactions with p53, explain isoform specific stabilization of the tumor suppressor protein, explore the approach of stabilizing the 14-3-3σ-p53 complex and summarize some promising small molecules inhibiting the p53-MDM2 protein-protein interaction.

scholarly journals Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

2021 ◽  
Vol 8 ◽  
Author(s):  
Juan J. Perez ◽  
Roman A. Perez ◽  
Alberto Perez
Keyword(s):  
Small Molecules ◽  
Protein Interactions ◽  
Cyclic Peptides ◽  
Therapeutic Agents ◽  
Protein Protein Interactions ◽  
Computational Tools ◽  
Regulatory Pathways ◽  
Physiological Processes ◽  
Pharmacokinetic Properties ◽  
Direct Use

Protein-protein interactions (PPIs) mediate a large number of important regulatory pathways. Their modulation represents an important strategy for discovering novel therapeutic agents. However, the features of PPI binding surfaces make the use of structure-based drug discovery methods very challenging. Among the diverse approaches used in the literature to tackle the problem, linear peptides have demonstrated to be a suitable methodology to discover PPI disruptors. Unfortunately, the poor pharmacokinetic properties of linear peptides prevent their direct use as drugs. However, they can be used as models to design enzyme resistant analogs including, cyclic peptides, peptide surrogates or peptidomimetics. Small molecules have a narrower set of targets they can bind to, but the screening technology based on virtual docking is robust and well tested, adding to the computational tools used to disrupt PPI. We review computational approaches used to understand and modulate PPI and highlight applications in a few case studies involved in physiological processes such as cell growth, apoptosis and intercellular communication.

scholarly journals The Fluorescent Two-Hybrid Assay to Screen for Protein–Protein Interaction Inhibitors in Live Cells

2014 ◽  
Vol 19 (4) ◽  
pp. 516-525 ◽  
Author(s):  
Larisa Yurlova ◽  
Maarten Derks ◽  
Andrea Buchfellner ◽  
Ian Hickson ◽  
Marc Janssen ◽  
...  
Keyword(s):  
Small Molecules ◽  
Protein Interactions ◽  
Mammalian Cells ◽  
Live Cells ◽  
Protein Protein Interactions ◽  
Stapled Peptides ◽  
Protein Protein Interaction ◽  
Real Time Visualization ◽  
Two Hybrid

Protein–protein interactions (PPIs) are attractive but challenging targets for drug discovery. To overcome numerous limitations of the currently available cell-based PPI assays, we have recently established a fully reversible microscopy-assisted fluorescent two-hybrid (F2H) assay. The F2H assay offers a fast and straightforward readout: an interaction-dependent co-localization of two distinguishable fluorescent signals at a defined spot in the nucleus of mammalian cells. We developed two reversible F2H assays for the interactions between the tumor suppressor p53 and its negative regulators, Mdm2 and Mdm4. We then performed a pilot F2H screen with a subset of compounds, including small molecules (such as Nutlin-3) and stapled peptides. We identified five cell-penetrating compounds as potent p53–Mdm2 inhibitors. However, none exhibited intracellular activity on p53–Mdm4. Live cell data generated by the F2H assays enable the characterization of stapled peptides based on their ability to penetrate cells and disrupt p53–Mdm2 interaction as well as p53–Mdm4 interaction. Here, we show that the F2H assays enable side-by-side analysis of substances’ dual Mdm2–Mdm4 activity. In addition, they are suitable for testing various types of compounds (e.g., small molecules and peptidic inhibitors) and concurrently provide initial data on cellular toxicity. Furthermore, F2H assays readily allow real-time visualization of PPI dynamics in living cells.

Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Protein Protein Interactions ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Protein Protein Interactions ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

An efficient transient assays system using Agrobacterium-mediated transformation of onion (Allium cepa) epidermal cells

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Yu-Miao Zhang ◽  
Jun Wang ◽  
Tao Wu
Keyword(s):  
Subcellular Localization ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Epidermal Cells ◽  
Cyclin Dependent Kinase ◽  
Protein Subcellular Localization ◽  
Protein Protein Interactions ◽  
Efficient System ◽  
Protein Protein Interaction ◽  
Onion Epidermal Cells

In this study, the Agrobacterium infection medium, infection duration, detergent, and cell density were optimized. The sorghum-based infection medium (SbIM), 10-20 min infection time, addition of 0.01% Silwet L-77, and Agrobacterium optical density at 600 nm (OD600), improved the competence of onion epidermal cells to support Agrobacterium infection at >90% efficiency. Cyclin-dependent kinase D-2 (CDKD-2) and cytochrome c-type biogenesis protein (CYCH), protein-protein interactions were localized. The optimized procedure is a quick and efficient system for examining protein subcellular localization and protein-protein interaction.

Decoding Protein-protein Interactions: An Overview

2020 ◽  
Vol 20 (10) ◽  
pp. 855-882
Author(s):  
Olivia Slater ◽  
Bethany Miller ◽  
Maria Kontoyianni
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Drug Repurposing ◽  
Protein Docking ◽  
Target Space ◽  
Protein Protein Interactions ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Interaction Sites ◽  
Long Time

Drug discovery has focused on the paradigm “one drug, one target” for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

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