Identification of inhibitors of the RGS homology domain of GRK2 by docking-based virtual screening.

AIMS: G protein-coupled receptor (GPCR) kinases (GRKs) are mainly involved in the desensitization of GPCRs. Among them, GRK2 has been described to be upregulated in many pathological conditions and its crucial role in cardiac hypertrophy, hypertension, and heart failure promoted the search for pharmacological inhibitors of its activity. There have been several reports of potent and selective inhibitors of GRK2, most of them directed to the kinase domain of the protein. However, the homologous to the regulator of G protein signaling (RH) domain of GRK2 has also been shown to regulate GPCRs signaling. Herein, we searched for potential inhibitors of receptor desensitization mediated by RH domain of GRK2. MATERIALS AND METHODS: We performed a docking-based virtual screening utilizing the crystal structure of GRK2 to search for potential inhibitors of the interaction between GRK2 and Gαq protein. To evaluate the biological activity of compounds we measured, calcium response of histamine H1 receptor (H1R) using Fura-2AM dye and H1R internalization by saturation binding experiments in A549 cells. GRK2(45-178)GFP translocation was determined in HeLa cells through confocal fluorescence imaging. KEY FINDINGS: We identified inhibitors of GRK2 able to reduce the RH mediated desensitization of the histamine H1 receptor and GRK2 translocation to plasma membrane. Also candidates presented adequate lipophilia and cytotoxicity profile. SIGNIFICANCE: We obtained compounds with the ability of reducing RH mediated actions of GRK2 that can be useful as a starting point in the development of novel drug candidates aimed to treat pathologies were GRK2 plays a key role.

Homology Model and Docking-Based Virtual Screening for Ligands of Human Dyskerin as New Inhibitors of Telomerase for Cancer Treatment.

Immortality is one of the main features of cancer cells. Tumor cells have an unlimited replicative potential, principally due to the holoenzyme telomerase. Telomerase is composed mainly by dyskerin (DKC1), a catalytic retrotranscriptase (hTERT) and an RNA template (hTR). The aim of this work is to develop new inhibitors of telomerase, selecting the interaction between hTR⁻DKC1 as a target. We designed two models of the human protein DKC1: homology and ab initio. These models were evaluated by different procedures, revealing that the homology model parameters were the most accurate. We selected two hydrophobic pockets contained in the PUA (pseudouridine synthase and archaeosine transglycosylase) domain, using structural and stability analysis. We carried out a docking-based virtual screen on these pockets, using the reported mutation K314 as the center of the docking. The hDKC1 model was tested against a library of 450,000 drug-like molecules. We selected the first 10 molecules that showed the highest affinity values to test their inhibitory activity on the cell line MDA MB 231 (Monroe Dunaway Anderson Metastasis Breast cancer 231), obtaining three compounds that showed inhibitory effect. These results allowed us to validate our design and set the basis to continue with the study of telomerase inhibitors for cancer treatment.

Novel Insights for Inhibiting Mutant Heterodimer IDH1wt-R132H in Cancer: An In-Silico Approach.

BACKGROUND: Isocitrate dehydrogenase 1 (IDH1) is a dimeric enzyme responsible for supplying the cell's nicotinamide adenine dinucleotide phosphate (NADPH) reserves via dehydrogenation of isocitrate (ICT) and reduction of NADP+. Mutations in position R132 trigger cancer by enabling IDH1 to produce D-2-hydroxyglutarate (2-HG) and reduce inhibition by ICT. Mutant IDH1 can be found as a homodimer or a heterodimer. OBJECTIVE: We propose a novel strategy to inhibit IDH1 R132 variants as a means not to decrease the concentration of 2-HG but to provoke a cytotoxic effect, as the cell malignancy at this point no longer depends on 2-HG. We aim to inhibit the activity of the mutant heterodimer to block the wild-type subunit. Limiting the NADPH reserves in a cancerous cell will enhance its susceptibility to the oxidative stress provoked by chemotherapy. METHODS: We performed a virtual screening using all US FDA-approved drugs to replicate the loss of inhibition of mutant IDH1 by ICT. We characterized our results based on molecular interactions and correlated them with the described phenotypes. RESULTS: We replicated the loss of inhibition by ICT in mutant IDH1. We identified 20 drugs with the potential to inhibit the heterodimeric isoform. Six of them are used in cancer treatment. CONCLUSIONS: We present 20 FDA-approved drugs with the potential to inhibit IDH1 wild-type activity in mutated cells. We believe this work may provide important insights into current and new approaches to dealing with IDH1 mutations. In addition, it may be used as a basis for additional studies centered on drugs presenting differential sensitivities to different IDH1 isoforms.

CoDNaS: a database of conformational diversity in the native state of proteins.

MOTIVATION: Conformational diversity is a key concept in the understanding of different issues related with protein function such as the study of catalytic processes in enzymes, protein-protein recognition, protein evolution and the origins of new biological functions. Here, we present a database of proteins with different degrees of conformational diversity. Conformational Diversity of Native State (CoDNaS) is a redundant collection of three-dimensional structures for the same protein derived from protein data bank. Structures for the same protein obtained under different crystallographic conditions have been associated with snapshots of protein dynamism and consequently could characterize protein conformers. CoDNaS allows the user to explore global and local structural differences among conformers as a function of different parameters such as presence of ligand, post-translational modifications, changes in oligomeric states and differences in pH and temperature. Additionally, CoDNaS contains information about protein taxonomy and function, disorder level and structural classification offering useful information to explore the underlying mechanism of conformational diversity and its close relationship with protein function. Currently, CoDNaS has 122 122 structures integrating 12 684 entries, with an average of 9.63 conformers per protein. AVAILABILITY: The database is freely available at http://www.codnas.com.ar/.

Protein conformational diversity modulates sequence divergence.

It is well established that the conservation of protein structure during evolution constrains sequence divergence. The conservation of certain physicochemical environments to preserve protein folds and then the biological function originates a site-specific structurally constrained substitution pattern. However, protein native structure is not unique. It is known that the native state is better described by an ensemble of conformers in a dynamic equilibrium. In this work, we studied the influence of conformational diversity in sequence divergence and protein evolution. For this purpose, we derived a set of 900 proteins with different degrees of conformational diversity from the PCDB database, a conformer database. With the aid of a structurally constrained protein evolutionary model, we explored the influence of the different conformations on sequence divergence. We found that the presence of conformational diversity strongly modulates the substitution pattern. Although the conformers share several of the structurally constrained sites, 30% of them are conformer specific. Also, we found that in 76% of the proteins studied, a single conformer outperforms the others in the prediction of sequence divergence. It is interesting to note that this conformer is usually the one that binds ligands participating in the biological function of the protein. The existence of a conformer-specific site-substitution pattern indicates that conformational diversity could play a central role in modulating protein evolution. Furthermore, our findings suggest that new evolutionary models and bioinformatics tools should be developed taking into account this substitution bias.

On the effect of protein conformation diversity in discriminating among neutral and disease related single amino acid substitutions.

BACKGROUND: Non-synonymous coding SNPs (nsSNPs) that are associated to disease can also be related with alterations in protein stability. Computational methods are available to predict the effect of single amino acid substitutions (SASs) on protein stability based on a single folded structure. However, the native state of a protein is not unique and it is better represented by the ensemble of its conformers in dynamic equilibrium. The maintenance of the ensemble is essential for protein function. In this work we investigated how protein conformational diversity can affect the discrimination of neutral and disease related SASs based on protein stability estimations. For this purpose, we used 119 proteins with 803 associated SASs, 60% of which are disease related. Each protein was associated with its corresponding set of available conformers as found in the Protein Conformational Database (PCDB). Our dataset contains proteins with different extensions of conformational diversity summing up a total number of 1023 conformers. RESULTS: The existence of different conformers for a given protein introduces great variability in the estimation of the protein stability (ΔΔG) after a single amino acid substitution (SAS) as computed with FoldX. Indeed, in 35% of our protein set at least one SAS can be described as stabilizing, destabilizing or neutral when a cutoff value of ±2 kcal/mol is adopted for discriminating neutral from perturbing SASs. However, when the ΔΔG variability among conformers is taken into account, the correlation among the perturbation of protein stability and the corresponding disease or neutral phenotype increases as compared with the same analysis on single protein structures. At the conformer level, we also found that the different conformers correlate in a different way to the corresponding phenotype. CONCLUSIONS: Our results suggest that the consideration of conformational diversity can improve the discrimination of neutral and disease related protein SASs based on the evaluation of the corresponding Gibbs free energy change.

PCDB: a database of protein conformational diversity.

PCDB (http://www.pcdb.unq.edu.ar) is a database of protein conformational diversity. For each protein, the database contains the redundant compilation of all the corresponding crystallographic structures obtained under different conditions. These structures could be considered as different instances of protein dynamism. As a measure of the conformational diversity we use the maximum RMSD obtained comparing the structures deposited for each domain. The redundant structures were extracted following CATH structural classification and cross linked with additional information. In this way it is possible to relate a given amount of conformational diversity with different levels of information, such as protein function, presence of ligands and mutations, structural classification, active site information and organism taxonomy among others. Currently the database contains 7989 domains with a total of 36581 structures from 4171 different proteins. The maximum RMSD registered is 26.7 Å and the average of different structures per domain is 4.5.