Pseudokinase drug intervention: a potentially poisoned chalice

2013 ◽  
Vol 41 (4) ◽  
pp. 1083-1088 ◽  
Author(s):  
Jeroen Claus ◽  
Angus J.M. Cameron ◽  
Peter J. Parker
Keyword(s):  
Protein Interactions ◽  
Drug Targets ◽  
Binding Pocket ◽  
Atp Binding ◽  
Potential Drug ◽  
Protein Protein Interactions ◽  
Drug Intervention ◽  
Potential Impact ◽  
Potential Drug Targets ◽  
Selection Of

Pseudokinases, the catalytically impaired component of the kinome, have recently been found to share more properties with active kinases than previously thought. In many pseudokinases, ATP binding and even some activity is preserved, highlighting these proteins as potential drug targets. In both active kinases and pseudokinases, binding of ATP or drugs in the nucleotide-binding pocket can stabilize specific conformations required for activity and protein–protein interactions. We discuss the implications of locking particular conformations in a selection of (pseudo)kinases and the dual potential impact on the druggability of these proteins.

A Comparative Computational Analysis Approach to Predict Significant Protein-Protein Interactions of Human and Vancomycin Resistant Enterococcus faecalis (VRE) to Prioritize Potential Drug Targets

2021 ◽  
Vol 18 ◽  
Author(s):  
Reaz Uddin ◽  
Kanwal Khan
Keyword(s):  
Enterococcus Faecalis ◽  
Protein Interactions ◽  
Drug Targets ◽  
Vancomycin Resistant Enterococcus ◽  
Potential Drug ◽  
Protein Protein Interactions ◽  
Clp Protease ◽  
Vancomycin Resistant ◽  
Novel Drug ◽  
Potential Drug Targets

Background: Various challenges exist in the treatment of infectious diseases due to the significant rise in drug resistance, resulting in the failure of antibiotic treatment. As a consequence, a dire need has arisen for the rethinking of the drug discovery cycle because of the challenge of drug resistance. The underlying cause of the infectious diseases depends upon associations within the Host-pathogen Protein-Protein Interactions (HP-PPIs) network, which represents a key to unlock new pathogenesis mechanism. Hence, the elucidation of significant PPIs is a promising approach for the identification of potential drug targets. Objective: Identification of the most significant HP-PPIs and their partners, and target them to prioritize potential new drug targets against Vancomycin-resistant Enterococcus faecalis (VRE). Methods: We applied a computational approach based on one of the emerging techniques i.e. Interolog methodology to predict the significant Host-Pathogen PPIs. Structure-Based Studies were applied to model shortlisted protein structures and validate them through PSIPRED, PROCHECK, VERIFY3D, and ERRAT tools. Furthermore, 18,000 drug-like compounds from the ZINC library were docked against these proteins to study protein-chemical interactions using the AutoDock based molecular docking method. Results: Study resulted in the identification of 118 PPIs for Enterococcus faecalis, and prioritized two novel drug targets i.e. Exodeoxyribonuclease (ExoA) and ATP-dependent Clp protease proteolytic subunit (ClpP). Consequently, the docking program ranked 2,670 and 3,154 compounds as potential binders against Exodeoxyribonuclease and ATP-dependent Clp protease proteolytic subunit, respectively. Conclusion: Thereby, the current study enabled us to identify and prioritize potential PPIs in VRE and their interacting proteins in human hosts along with the pool of novel drug candidates.

scholarly journals Application of Centrality Measures for Potential Drug Targets: Review

2020 ◽  
Vol 9 (04) ◽  
pp. 24989-24993
Author(s):  
Akula Chandra Sekhar ◽  
Ch. Ambedkar
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Crucial Role ◽  
Drug Targets ◽  
Docking Studies ◽  
Drug Binding ◽  
Centrality Measures ◽  
Potential Drug ◽  
Protein Protein Interactions ◽  
Potential Drug Targets

Protein-Protein Interactions (PPI) have important role in drug binding with the Proteins called drug targets. For identifying the potential drug targets there are different techniques. In this paper we are presenting application of Centrality Measures for identifying the drug targets. Centrality measure indicates importance of node in the graph or network. Protein-Protein Interactions for proteins which are involved in a particular disease are identified and centrality measures will be calculated based on the graph built suing the PPI interactions. Further the nodes which are playing crucial role will be identified using the various centrality measures and these drug targets can be used for drug discovery of a particular disease through insilico docking studies.

Protein-Protein Interactions (PPIs) as an Alternative to Targeting the ATP Binding Site of Kinase

2016 ◽  
pp. 249-277
Author(s):  
Sailu Sarvagalla ◽  
Mohane Selvaraj Coumar
Keyword(s):  
Protein Interactions ◽  
In Silico ◽  
Rational Design ◽  
Kinase Activity ◽  
Hot Spot ◽  
Binding Pocket ◽  
Atp Binding ◽  
Protein Protein Interactions ◽  
Structure Based Drug Design ◽  
Atp Binding Site

Most of the developed kinase inhibitor drugs are ATP competitive and suffer from drawbacks such as off-target kinase activity, development of resistance due to mutation in the ATP binding pocket and unfavorable intellectual property situations. Besides the ATP binding pocket, protein kinases have binding sites that are involved in Protein-Protein Interactions (PPIs); these PPIs directly or indirectly regulate the protein kinase activity. Of recent, small molecule inhibitors of PPIs are emerging as an alternative to ATP competitive agents. Rational design of inhibitors for kinase PPIs could be carried out using molecular modeling techniques. In silico tools available for the prediction of hot spot residues and cavities at the PPI sites and the means to utilize this information for the identification of inhibitors are discussed. Moreover, in silico studies to target the Aurora B-INCENP PPI sites are discussed in context. Overall, this chapter provides detailed in silico strategies that are available to the researchers for carrying out structure-based drug design of PPI inhibitors.

Using a Heat Diffusion Model to Detect Potential Drug Resistance Genes of Mycobacterium tuberculosis

2020 ◽  
Vol 27 (8) ◽  
pp. 711-717 ◽  
Author(s):  
Ze-Jia Cui ◽  
Wei-Tong Zhang ◽  
Qiang Zhu ◽  
Qing-Ye Zhang ◽  
Hong-Yu Zhang
Keyword(s):  
Molecular Dynamics ◽  
Drug Resistance ◽  
Diffusion Model ◽  
Protein Interactions ◽  
Drug Targets ◽  
Sequence Data ◽  
Heat Diffusion ◽  
Dynamics Simulation ◽  
Potential Drug ◽  
Protein Protein Interactions

Background: Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is one of the oldest known and most dangerous diseases. Although the spread of TB was controlled in the early 20th century using antibiotics and vaccines, TB has again become a threat because of increased drug resistance. There is still a lack of effective treatment regimens for a person who is already infected with multidrug-resistant Mtb (MDR-Mtb) or extensively drug-resistant Mtb (XDRMtb). In the past decades, many research groups have explored the drug resistance profiles of Mtb based on sequence data by GWAS, which identified some mutations that were significantly linked with drug resistance, and attempted to explain the resistance mechanisms. However, they mainly focused on several significant mutations in drug targets (e.g. rpoB, katG). Some genes which are potentially associated with drug resistance may be overlooked by the GWAS analysis. Objective: In this article, our motivation is to detect potential drug resistance genes of Mtb using a heat diffusion model. Methods: All sequencing data, which contained 127 samples of Mtb, i.e. 34 ethambutol-, 65 isoniazid-, 53 rifampicin- and 45 streptomycin-resistant strains. The raw sequence data were preprocessed using Trimmomatic software and aligned to the Mtb H37Rv reference genome using Bowtie2. From the resulting alignments, SAMtools and VarScan were used to filter sequences and call SNPs. The GWAS was performed by the PLINK package to obtain the significant SNPs, which were mapped to genes. The P-values of genes calculated by GWAS were transferred into a heat vector. The heat vector and the Mtb protein-protein interactions (PPI) derived from the STRING database were inputted into the heat diffusion model to obtain significant subnetworks by HotNet2. Finally, the most significant (P < 0.05) subnetworks associated with different phenotypes were obtained. To verify the change of binding energy between the drug and target before and after mutation, the method of molecular dynamics simulation was performed using the AMBER software. Results: We identified significant subnetworks in rifampicin-resistant samples. Excitingly, we found rpoB and rpoC, which are drug targets of rifampicin. From the protein structure of rpoB, the mutation location was extremely close to the drug binding site, with a distance of only 3.97 Å. Molecular dynamics simulation revealed that the binding energy of rpoB and rifampicin decreased after D435V mutation. To a large extent, this mutation can influence the affinity of drug-target binding. In addition, topA and pyrG were reported to be linked with drug resistance, and might be new TB drug targets. Other genes that have not yet been reported are worth further study. Conclusion: Using a heat diffusion model in combination with GWAS results and protein-protein interactions, the significantly mutated subnetworks in rifampicin-resistant samples were found. The subnetwork not only contained the known targets of rifampicin (rpoB, rpoC), but also included topA and pyrG, which are potentially associated with drug resistance. Together, these results offer deeper insights into drug resistance of Mtb, and provides potential drug targets for finding new antituberculosis drugs.

scholarly journals Protein-Protein Interactions (PPIs) as an Alternative to Targeting the ATP Binding Site of Kinase

2017 ◽  
pp. 1115-1143
Author(s):  
Sailu Sarvagalla ◽  
Mohane Selvaraj Coumar
Keyword(s):  
Protein Interactions ◽  
In Silico ◽  
Rational Design ◽  
Kinase Activity ◽  
Hot Spot ◽  
Binding Pocket ◽  
Atp Binding ◽  
Protein Protein Interactions ◽  
Structure Based Drug Design ◽  
Atp Binding Site

Most of the developed kinase inhibitor drugs are ATP competitive and suffer from drawbacks such as off-target kinase activity, development of resistance due to mutation in the ATP binding pocket and unfavorable intellectual property situations. Besides the ATP binding pocket, protein kinases have binding sites that are involved in Protein-Protein Interactions (PPIs); these PPIs directly or indirectly regulate the protein kinase activity. Of recent, small molecule inhibitors of PPIs are emerging as an alternative to ATP competitive agents. Rational design of inhibitors for kinase PPIs could be carried out using molecular modeling techniques. In silico tools available for the prediction of hot spot residues and cavities at the PPI sites and the means to utilize this information for the identification of inhibitors are discussed. Moreover, in silico studies to target the Aurora B-INCENP PPI sites are discussed in context. Overall, this chapter provides detailed in silico strategies that are available to the researchers for carrying out structure-based drug design of PPI inhibitors.

Sign in / Sign up

Export Citation Format

Share Document