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Design of a Novel and Selective IRAK4 Inhibitor Using Topological Water Network Analysis and Molecular Modeling Approaches.

ABSTRACT: Protein kinases are deeply involved in immune-related diseases and various cancers. They are a potential target for structure-based drug discovery, since the general structure and characteristics of kinase domains are relatively well-known. However, the ATP binding sites in protein kinases, which serve as target sites, are highly conserved, and thus it is difficult to develop selective kinase inhibitors. To resolve this problem, we performed molecular dynamics simulations on 26 kinases in the aqueous solution, and analyzed topological water networks (TWNs) in their ATP binding sites. Repositioning of a known kinase inhibitor in the ATP binding sites of kinases that exhibited a TWN similar to interleukin-1 receptor-associated kinase 4 (IRAK4) allowed us to identify a hit molecule. Another hit molecule was obtained from a commercial chemical library using pharmacophore-based virtual screening and molecular docking approaches. Pharmacophoric features of the hit molecules were hybridized to design a novel compound that inhibited IRAK4 at low nanomolar levels in the in vitro assay.

SUBMITTER: Lee MH

PROVIDER: S-EPMC6321621 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Design of a Novel and Selective IRAK4 Inhibitor Using Topological Water Network Analysis and Molecular Modeling Approaches.

Lee Myeong Hwi MH Balupuri Anand A Jung Ye-Rim YR Choi Sungwook S Lee Areum A Cho Young Sik YS Kang Nam Sook NS

Molecules (Basel, Switzerland) 20181129 12

Protein kinases are deeply involved in immune-related diseases and various cancers. They are a potential target for structure-based drug discovery, since the general structure and characteristics of kinase domains are relatively well-known. However, the ATP binding sites in protein kinases, which serve as target sites, are highly conserved, and thus it is difficult to develop selective kinase inhibitors. To resolve this problem, we performed molecular dynamics simulations on 26 kinases in the aq ...[more]

PMID: 30501110

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Project description:Treatment of several autoimmune diseases and types of cancer has been an intense area of research over the past two decades. Many signaling pathways that regulate innate and/or adaptive immunity, as well as those that induce overexpression or mutation of protein kinases, have been targeted for drug discovery. One of the serine/threonine kinases, Interleukin-1 Receptor Associated Kinase 4 (IRAK4) regulates signaling through various Toll-like receptors (TLRs) and interleukin-1 receptor (IL1R). It controls diverse cellular processes including inflammation, apoptosis, and cellular differentiation. MyD88 gain-of-function mutations or overexpression of IRAK4 has been implicated in various types of malignancies such as Waldenström macroglobulinemia, B cell lymphoma, colorectal cancer, pancreatic ductal adenocarcinoma, breast cancer, etc. Moreover, over activation of IRAK4 is also associated with several autoimmune diseases. The significant role of IRAK4 makes it an interesting target for the discovery and development of potent small molecule inhibitors. A few potent IRAK4 inhibitors such as PF-06650833, RA9 and BAY1834845 have recently entered phase I/II clinical trial studies. Nevertheless, there is still a need of selective inhibitors for the treatment of cancer and various autoimmune diseases. A great need for the same intrigued us to perform molecular modeling studies on 4,6-diaminonicotinamide derivatives as IRAK4 inhibitors. We performed molecular docking and dynamics simulation of 50 ns for one of the most active compounds of the dataset. We also carried out MM-PBSA binding free energy calculation to identify the active site residues, interactions of which are contributing to the total binding energy. The final 50 ns conformation of the most active compound was selected to perform dataset alignment in a 3D-QSAR study. Generated RF-CoMFA (q2 = 0.751, ONC = 4, r2 = 0.911) model revealed reasonable statistical results. Overall results of molecular dynamics simulation, MM-PBSA binding free energy calculation and RF-CoMFA model revealed important active site residues of IRAK4 and necessary structural properties of ligand to design more potent IRAK4 inhibitors. We designed few IRAK4 inhibitors based on these results, which possessed higher activity (predicted pIC50) than the most active compounds of the dataset selected for this study. Moreover, ADMET properties of these inhibitors revealed promising results and need to be validated using experimental studies.

Project description:Interleukin-1-receptor-associated kinase 4 (IRAK4) possesses a crucial function in the toll-like receptor (TLR) signaling pathway, and the dysfunction of this molecule could lead to various infectious and immune-related diseases in addition to cancers. IRAK4 genetic variants have been linked to various types of diseases. Therefore, we conducted a comprehensive analysis to recognize the missense variants with the most damaging impacts on IRAK4 with the employment of diverse bioinformatics tools to study single-nucleotide polymorphisms' effects on function, stability, secondary structures, and 3D structure. The residues' location on the protein domain and their conservation status were investigated as well. Moreover, docking tools along with structural biology were engaged in analyzing the SNPs' effects on one of the developed IRAK4 inhibitors. By analyzing IRAK4 gene SNPs, the analysis distinguished ten variants as the most detrimental missense variants. All variants were situated in highly conserved positions on an important protein domain. L318S and L318F mutations were linked to changes in IRAK4 secondary structures. Eight SNPs were revealed to have a decreasing effect on the stability of IRAK4 via both I-Mutant 2.0 and Mu-Pro tools, while Mu-Pro tool identified a decreasing effect for the G198E SNP. In addition, detrimental effects on the 3D structure of IRAK4 were also discovered for the selected variants. Molecular modeling studies highlighted the detrimental impact of these identified SNP mutant residues on the druggability of the IRAK4 ATP-binding site towards the known target inhibitor, HG-12-6, as compared to the native protein. The loss of important ligand residue-wise contacts, altered protein global flexibility, increased steric clashes, and even electronic penalties at the ligand-binding site interfaces were all suggested to be associated with SNP models for hampering the HG-12-6 affinity towards IRAK4 target protein. This given model lays the foundation for the better prediction of various disorders relevant to IRAK4 malfunction and sheds light on the impact of deleterious IRAK4 variants on IRAK4 inhibitor efficacy.

Project description:BackgroundBeta-site amyloid precursor protein cleaving enzyme (BACE-1) is a single-membrane protein belongs to the aspartyl protease class of catabolic enzymes. This enzyme involved in the processing of the amyloid precursor protein (APP). The cleavage of APP by BACE-1 is the rate-limiting step in the amyloid cascade leading to the production of two peptide fragments Aβ40 and Aβ42. Among two peptide fragments Aβ42 is the primary species thought to be responsible for the neurotoxicity and amyloid plaque formation that lead to memory and cognitive defects in Alzheimer's disease (AD). AD is a ravaging neurodegenerative disorder for which no disease-modifying treatment is currently available. Inhibition of BACE-1 is expected to stop amyloid plaque formation and emerged as an interesting and attractive therapeutic target for AD.MethodsLigand-based computational approach was used to identify the molecular chemical features required for the inhibition of BACE-1 enzyme. A training set of 20 compounds with known experimental activity was used to generate pharmacophore hypotheses using 3D QSAR Pharmacophore Generation module available in Discovery studio. The hypothesis was validated by four different methods and the best hypothesis was utilized in database screening of four chemical databases like Maybridge, Chembridge, NCI and Asinex. The retrieved hit compounds were subjected to molecular docking study using GOLD 4.1 program.ResultsAmong ten generated pharmacophore hypotheses, Hypo 1 was chosen as best pharmacophore hypothesis. Hypo 1 consists of one hydrogen bond donor, one positive ionizable, one ring aromatic and two hydrophobic features with high correlation coefficient of 0.977, highest cost difference of 121.98 bits and lowest RMSD value of 0.804. Hypo 1 was validated using Fischer randomization method, test set with a correlation coefficient of 0.917, leave-one-out method and decoy set with a goodness of hit score of 0.76. The validated Hypo 1 was used as a 3D query in database screening and retrieved 773 compounds with the estimated activity value <100 nM. These hits were docked into the active site of BACE-1 and further refined based on molecular interactions with the essential amino acids and good GOLD fitness score.ConclusionThe best pharmacophore hypothesis, Hypo 1, with high predictive ability contains chemical features required for the effective inhibition of BACE-1. Using Hypo 1, we have identified two compounds with diverse chemical scaffolds as potential virtual leads which, as such or upon further optimization, can be used in the designing of new BACE-1 inhibitors.

Dataset Information

Design of a Novel and Selective IRAK4 Inhibitor Using Topological Water Network Analysis and Molecular Modeling Approaches.

Publications

Design of a Novel and Selective IRAK4 Inhibitor Using Topological Water Network Analysis and Molecular Modeling Approaches.

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