scholarly journals In Silico Identification of Potential Druggable Binding Sites on CIN85 SH3 Domain

2021 ◽  
Vol 22 (2) ◽  
pp. 534
Author(s):  
Serena Vittorio ◽  
Thomas Seidel ◽  
Arthur Garon ◽  
Rosaria Gitto ◽  
Thierry Langer ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Binding Sites ◽  
Drug Targets ◽  
Migration And Invasion ◽  
Protein Protein Interactions ◽  
Physiological Processes ◽  
Binding Surface ◽  
Traditional Drug ◽  
Substantial Progress ◽  
Binding Pockets

Protein-protein interactions (PPIs) play a pivotal role in the regulation of many physiological processes. The dysfunction of some PPIs interactions led to the alteration of different biological pathways causing various diseases including cancer. In this context, the inhibition of PPIs represents an attractive strategy for the design of new antitumoral agents. In recent years, computational approaches were successfully used to study the interactions between proteins, providing useful hints for the design of small molecules able to modulate PPIs. Targeting PPIs presents several challenges mainly due to the large and flat binding surface that lack the typical binding pockets of traditional drug targets. Despite these hurdles, substantial progress has been made in the last decade resulting in the identification of PPI modulators where some of them even found clinical use. This study focuses on MUC1-CIN85 PPI which is involved in the migration and invasion of cancer cells. Particularly, we investigated the presence of druggable binding sites on the CIN85 surface which provided new insights for the structure-based design of novel MUC1-CIN85 PPI inhibitors as anti-metastatic agents.

scholarly journals A Comprehensive Review on Current Advances in Peptide Drug Development and Design

2019 ◽  
Vol 20 (10) ◽  
pp. 2383 ◽  
Author(s):  
Andy Chi-Lung Lee ◽  
Janelle Louise Harris ◽  
Kum Kum Khanna ◽  
Ji-Hong Hong
Keyword(s):  
Drug Development ◽  
Binding Affinity ◽  
Protein Interactions ◽  
Binding Sites ◽  
Drug Targets ◽  
Peptide Drug ◽  
Protein Protein Interactions ◽  
Cellular Functions ◽  
Endogenous Protein ◽  
Binding Interfaces

Protein–protein interactions (PPIs) execute many fundamental cellular functions and have served as prime drug targets over the last two decades. Interfering intracellular PPIs with small molecules has been extremely difficult for larger or flat binding sites, as antibodies cannot cross the cell membrane to reach such target sites. In recent years, peptides smaller size and balance of conformational rigidity and flexibility have made them promising candidates for targeting challenging binding interfaces with satisfactory binding affinity and specificity. Deciphering and characterizing peptide–protein recognition mechanisms is thus central for the invention of peptide-based strategies to interfere with endogenous protein interactions, or improvement of the binding affinity and specificity of existing approaches. Importantly, a variety of computation-aided rational designs for peptide therapeutics have been developed, which aim to deliver comprehensive docking for peptide–protein interaction interfaces. Over 60 peptides have been approved and administrated globally in clinics. Despite this, advances in various docking models are only on the merge of making their contribution to peptide drug development. In this review, we provide (i) a holistic overview of peptide drug development and the fundamental technologies utilized to date, and (ii) an updated review on key developments of computational modeling of peptide–protein interactions (PepPIs) with an aim to assist experimental biologists exploit suitable docking methods to advance peptide interfering strategies against PPIs.

scholarly journals Targeting the cryptic sites: NMR-based strategy to improve protein druggability by controlling the conformational equilibrium

2020 ◽  
Vol 6 (40) ◽  
pp. eabd0480
Author(s):  
Yumiko Mizukoshi ◽  
Koh Takeuchi ◽  
Yuji Tokunaga ◽  
Hitomi Matsuo ◽  
Misaki Imai ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Protein Interactions ◽  
Binding Sites ◽  
Drug Targets ◽  
Conformational Equilibrium ◽  
Wild Type ◽  
Protein Protein Interactions ◽  
Hit Rate ◽  
Open Conformation ◽  
Ligand Binding Sites

Cryptic ligand binding sites, which are not evident in the unligated structures, are beneficial in tackling with difficult but attractive drug targets, such as protein-protein interactions (PPIs). However, cryptic sites have thus far not been rationally pursued in the early stages of drug development. Here, we demonstrated by nuclear magnetic resonance that the cryptic site in Bcl-xL exists in a conformational equilibrium between the open and closed conformations under the unligated condition. While the fraction of the open conformation in the unligated wild-type Bcl-xL is estimated to be low, F143W mutation that is distal from the ligand binding site can substantially elevate the population. The F143W mutant showed a higher hit rate in a phage-display peptide screening, and the hit peptide bound to the cryptic site of the wild-type Bcl-xL. Therefore, by controlling the conformational equilibrium in the cryptic site, the opportunity to identify a PPI inhibitor could be improved.

scholarly journals Norstictic acid is a selective allosteric transcriptional regulator

2021 ◽  
Author(s):  
Julie M Garlick ◽  
Steven M Sturlis ◽  
Paul A Bruno ◽  
Joel A Yates ◽  
Amanda Peiffer ◽  
...  
Keyword(s):  
Binding Site ◽  
Protein Interactions ◽  
Binding Sites ◽  
Triple Negative ◽  
Transcriptional Coactivator ◽  
Protein Protein Interactions ◽  
Ppi Networks ◽  
Binding Surface ◽  
Inhibitor Discovery

Inhibitors of transcriptional protein-protein interactions (PPIs) have high value both as tools and for therapeutic applications. The PPI network mediated by the transcriptional coactivator Med25, for example, regulates stress-response and motility pathways and dysregulation of the PPI networks contributes to oncogenesis and metastasis. The canonical transcription factor binding sites within Med25 are large (~900 square angstroms) and have little topology, and thus do not present an array of attractive small-molecule binding sites for inhibitor discovery. Here we demonstrate that the depsidone natural product norstictic acid functions through an alternative binding site to block Med25-transcriptional activator PPIs in vitro and in cell culture. Norstictic acid targets a binding site comprised of a highly dynamic loop flanking one canonical binding surface and in doing so, it both orthosterically and allosterically alters Med25-driven transcription in a patient-derived model of triple negative breast cancer. These results highlight the potential of Med25 as a therapeutic target as well as the inhibitor discovery opportunities presented by structurally dynamic loops within otherwise challenging proteins.

Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

2019 ◽  
Vol 26 (21) ◽  
pp. 3890-3910 ◽  
Author(s):  
Branislava Gemovic ◽  
Neven Sumonja ◽  
Radoslav Davidovic ◽  
Vladimir Perovic ◽  
Nevena Veljkovic
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Experimental Studies ◽  
Protein Protein Interactions ◽  
Web Based ◽  
Prediction Tools ◽  
Physiological Processes ◽  
Modern Drug ◽  
Ppi Prediction

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.

scholarly journals Targeted disruption of PKC from AKAP Signaling Complexes

2021 ◽  
Author(s):  
Ameya J. Limaye ◽  
George N. Bendzunas ◽  
Eileen Kennedy
Keyword(s):  
Protein Kinase C ◽  
Protein Kinase ◽  
Signaling Pathways ◽  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Targeted Disruption ◽  
Physiological Processes ◽  
Kinase C ◽  
P Protein

Protein Kinase C (PKC) is a member of the AGC subfamily of kinases and regulates a wide array of signaling pathways and physiological processes. Protein-protein interactions involving PKC and its...

scholarly journals Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows

2017 ◽  
pp. 221-236 ◽  
Author(s):  
Alexander Goncearenco ◽  
Minghui Li ◽  
Franco L. Simonetti ◽  
Benjamin A. Shoemaker ◽  
Anna R. Panchenko
Keyword(s):  
Cancer Therapy ◽  
Protein Interactions ◽  
In Silico ◽  
Drug Targets ◽  
Protein Protein Interactions ◽  
Anti Cancer

An integrated strategy for the discovery of drug targets by the analysis of protein–protein interactions

2004 ◽  
Vol 238 (2) ◽  
pp. 119-130 ◽  
Author(s):  
John M. Peltier ◽  
Srdjan Askovic ◽  
Robert R. Becklin ◽  
Cindy Lou Chepanoske ◽  
Yew-Seng J. Ho ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Drug Targets ◽  
Protein Protein Interactions ◽  
Integrated Strategy

scholarly journals Protein Dynamics in F-like Bacterial Conjugation

Biomedicines ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 362
Author(s):  
Nicholas Bragagnolo ◽  
Christina Rodriguez ◽  
Naveed Samari-Kermani ◽  
Alice Fours ◽  
Mahboubeh Korouzhdehi ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Protein Interactions ◽  
Drug Targets ◽  
Dynamic Models ◽  
Structural Information ◽  
Imaging Techniques ◽  
Antibiotic Resistance Genes ◽  
Protein Protein Interactions ◽  
Secretion Systems ◽  
Type Iv

Efficient in silico development of novel antibiotics requires high-resolution, dynamic models of drug targets. As conjugation is considered the prominent contributor to the spread of antibiotic resistance genes, targeted drug design to disrupt vital components of conjugative systems has been proposed to lessen the proliferation of bacterial antibiotic resistance. Advancements in structural imaging techniques of large macromolecular complexes has accelerated the discovery of novel protein-protein interactions in bacterial type IV secretion systems (T4SS). The known structural information regarding the F-like T4SS components and complexes has been summarized in the following review, revealing a complex network of protein-protein interactions involving domains with varying degrees of disorder. Structural predictions were performed to provide insight on the dynamicity of proteins within the F plasmid conjugative system that lack structural information.

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