A General Framework for Development and Data Analysis of Competitive High-Throughput Screens for Small-Molecule Inhibitors of Protein−Protein Interactions by Fluorescence Polarization†

Biochemistry ◽  
2004 ◽  
Vol 43 (51) ◽  
pp. 16056-16066 ◽  
Author(s):  
Michael H. A. Roehrl ◽  
Julia Y. Wang ◽  
Gerhard Wagner
Keyword(s):  
Data Analysis ◽  
Small Molecule ◽  
High Throughput ◽  
Protein Interactions ◽  
Fluorescence Polarization ◽  
General Framework ◽  
Small Molecule Inhibitors ◽  
Protein Protein Interactions ◽  
High Throughput Screens

scholarly journals A High-Throughput Screening Strategy to Identify Inhibitors of SSB Protein–Protein Interactions in an Academic Screening Facility

2017 ◽  
Vol 23 (1) ◽  
pp. 94-101 ◽  
Author(s):  
Andrew F. Voter ◽  
Michael P. Killoran ◽  
Gene E. Ananiev ◽  
Scott A. Wildman ◽  
F. Michael Hoffmann ◽  
...  
Keyword(s):  
Small Molecule ◽  
High Throughput ◽  
Protein Interactions ◽  
High Throughput Screening ◽  
Bacterial Infections ◽  
Small Molecule Inhibitors ◽  
Klebsiella Pneumonia ◽  
Protein Protein Interactions ◽  
Response Curves ◽  
Single Stranded Dna

Antibiotic-resistant bacterial infections are increasingly prevalent worldwide, and there is an urgent need for novel classes of antibiotics capable of overcoming existing resistance mechanisms. One potential antibiotic target is the bacterial single-stranded DNA binding protein (SSB), which serves as a hub for DNA repair, recombination, and replication. Eight highly conserved residues at the C-terminus of SSB use direct protein–protein interactions (PPIs) to recruit more than a dozen important genome maintenance proteins to single-stranded DNA. Mutations that disrupt PPIs with the C-terminal tail of SSB are lethal, suggesting that small-molecule inhibitors of these critical SSB PPIs could be effective antibacterial agents. As a first step toward implementing this strategy, we have developed orthogonal high-throughput screening assays to identify small-molecule inhibitors of the Klebsiella pneumonia SSB-PriA interaction. Hits were identified from an initial screen of 72,474 compounds using an AlphaScreen (AS) primary screen, and their activity was subsequently confirmed in an orthogonal fluorescence polarization (FP) assay. As an additional control, an FP assay targeted against an unrelated eukaryotic PPI was used to confirm specificity for the SSB-PriA interaction. Nine potent and selective inhibitors produced concentration–response curves with IC50 values of <40 μM, and two compounds were observed to directly bind to PriA, demonstrating the success of this screen strategy.

Elucidating Protein-protein Interactions Through Computational Approaches and Designing Small Molecule Inhibitors Against them for Various Diseases

2018 ◽  
Vol 18 (20) ◽  
pp. 1719-1736 ◽  
Author(s):  
Sharanya Sarkar ◽  
Khushboo Gulati ◽  
Manikyaprabhu Kairamkonda ◽  
Amit Mishra ◽  
Krishna Mohan Poluri
Keyword(s):  
Small Molecule ◽  
Protein Interactions ◽  
Small Molecule Inhibitors ◽  
Computational Techniques ◽  
Protein Protein Interactions ◽  
Computational Tools ◽  
Computational Approaches ◽  
Protein Protein Interaction ◽  
Wide Range ◽  
Therapeutic Measures

Background: To carry out wide range of cellular functionalities, proteins often associate with one or more proteins in a phenomenon known as Protein-Protein Interaction (PPI). Experimental and computational approaches were applied on PPIs in order to determine the interacting partners, and also to understand how an abnormality in such interactions can become the principle cause of a disease. Objective: This review aims to elucidate the case studies where PPIs involved in various human diseases have been proven or validated with computational techniques, and also to elucidate how small molecule inhibitors of PPIs have been designed computationally to act as effective therapeutic measures against certain diseases. Results: Computational techniques to predict PPIs are emerging rapidly in the modern day. They not only help in predicting new PPIs, but also generate outputs that substantiate the experimentally determined results. Moreover, computation has aided in the designing of novel inhibitor molecules disrupting the PPIs. Some of them are already being tested in the clinical trials. Conclusion: This review delineated the classification of computational tools that are essential to investigate PPIs. Furthermore, the review shed light on how indispensable computational tools have become in the field of medicine to analyze the interaction networks and to design novel inhibitors efficiently against dreadful diseases in a shorter time span.

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