Design, synthesis of new 3H-imidazo[4,5-b]pyridine derivatives and evaluation of their inhibitory properties as mixed lineage kinase 3 inhibitors.

Mixed-lineage protein kinase 3 (MLK3) is implicated in several human cancers and neurodegenerative diseases. A series of 3H-imidazo[4,5-b]pyridine derivatives were designed, synthesized and evaluated as novel MLK3 inhibitors. A homology model of MLK3 was developed and all designed compounds were docked to assess their binding pattern and affinity toward the MLK3 active site. Based on this knowledge, we synthesized and experimentally evaluated the designed compounds. Majority of the compounds showed significant inhibition of MLK3 in the enzymatic assay. In particular, compounds 9a, 9e, 9j, 9 k, 12b and 12d exhibited IC50 values of 6, 6, 8, 11, 14 and 14 nM, respectively. Furthermore, compounds 9a, 9e, 9 k and 12b exhibited favorable physicochemical properties among these compounds.

TWN-RENCOD: A novel method for protein binding site comparison.

Several diverse proteins possess similar binding sites. Protein binding site comparison provides valuable insights for the drug discovery and development. Binding site similarities are useful in understanding polypharmacology, identifying potential off-targets and repurposing of known drugs. Many binding site analysis and comparison methods are available today, however, these methods may not be adequate to explain variation in the activity of a drug or a small molecule against a number of similar proteins. Water molecules surrounding the protein surface contribute to structure and function of proteins. Water molecules form diverse types of hydrogen-bonded cyclic water-ring networks known as topological water networks (TWNs). Analysis of TWNs in binding site of proteins may improve understanding of the characteristics of binding sites. We propose TWN-based residue encoding (TWN-RENCOD), a novel binding site comparison method which compares the aqueous environment in binding sites of similar proteins. As compared to other existing methods, results obtained using our method correlated better with differences in wide range of activity of a known drug (Sunitinib) against nine different protein kinases (KIT, PDGFRA, VEGFR2, PHKG2, ITK, HPK1, MST3, PAK6 and CDK2).

Small Molecule Inhibitors of DYRK1A Identified by Computational and Experimental Approaches.

Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a protein kinase with diverse functions in cell regulation. Abnormal expression and activity of DYRK1A contribute to numerous human malignancies, Down syndrome, and Alzheimer's disease. Notably, DYRK1A has been proposed as a potential therapeutic target for the treatment of diabetes because of its key role in pancreatic ß-cell proliferation. Consequently, DYRK1A is an attractive drug target for a variety of diseases. Here, we report the identification of several DYRK1A inhibitors using our in-house topological water network-based approach. All inhibitors were further verified by in vitro assay.

High-Throughput Platform for Real-Time Monitoring of ATP-Generating Enzymes in Living Cells Based on a Lanthanide Probe.

Remarkable variation between cell-free and cellular measurements of enzyme activity triggered the unmet need to develop tools for monitoring enzyme activity in living cells. Such tools will advance our understanding of the biological functions of enzymes and their potential impact on drug discovery. We report in this study a universal assay for monitoring ATP-generating enzymes in living cells using a self-assembled Tb3+ complex probe. Modulation of the rheological properties of cell culture media enabled shifting the lifetime of the Tb3+ complex in the presence of ATP from micro-to-millisecond range. Based on the response of the Tb3+ complex to ATP, cellular assays for 5 ATP-generating enzymes were developed. Remarkably, assessment of the activity of these enzymes in living cells is made possible for the first time. The pyruvate kinase M2 (PKM2) assay has been optimized for high-throughput screening (HTS) and further implemented in the identification of novel scaffolds as PKM2 inhibitors.

The Study on the hERG Blocker Prediction Using Chemical Fingerprint Analysis.

Human ether-a-go-go-related gene (hERG) potassium channel blockage by small molecules may cause severe cardiac side effects. Thus, it is crucial to screen compounds for activity on the hERG channels early in the drug discovery process. In this study, we collected 5299 hERG inhibitors with diverse chemical structures from a number of sources. Based on this dataset, we evaluated different machine learning (ML) and deep learning (DL) algorithms using various integer and binary type fingerprints. A training set of 3991 compounds was used to develop quantitative structure-activity relationship (QSAR) models. The performance of the developed models was evaluated using a test set of 998 compounds. Models were further validated using external set 1 (263 compounds) and external set 2 (47 compounds). Overall, models with integer type fingerprints showed better performance than models with no fingerprints, converted binary type fingerprints or original binary type fingerprints. Comparison of ML and DL algorithms revealed that integer type fingerprints are suitable for ML, whereas binary type fingerprints are suitable for DL. The outcomes of this study indicate that the rational selection of fingerprints is important for hERG blocker prediction.

Pharmacophoric Site Identification and Inhibitor Design for Autotaxin.

Autotaxin (ATX) is a potential drug target that is associated with inflammatory diseases and various cancers. In our previous studies, we have designed several inhibitors targeting ATX using computational and experimental approaches. Here, we have analyzed topological water networks (TWNs) in the binding pocket of ATX. TWN analysis revealed a pharmacophoric site inside the pocket. We designed and synthesized compounds considering the identified pharmacophoric site. Furthermore, we performed biological experiments to determine their ATX inhibitory activities. High potency of the designed compounds supports the predictions of the TWN analysis.

Inhibition of ß-site amyloid precursor protein cleaving enzyme 1 and cholinesterases by pterosins via a specific structure-activity relationship with a strong BBB permeability.

We extracted 15 pterosin derivatives from Pteridium aquilinum that inhibited ß-site amyloid precursor protein cleaving enzyme 1 (BACE1) and cholinesterases involved in the pathogenesis of Alzheimer's disease (AD). (2R)-Pterosin B inhibited BACE1, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) with an IC50 of 29.6, 16.2 and 48.1 µM, respectively. The Ki values and binding energies (kcal/mol) between pterosins and BACE1, AChE, and BChE corresponded to the respective IC50 values. (2R)-Pterosin B was a noncompetitive inhibitor against human BACE1 and BChE as well as a mixed-type inhibitor against AChE, binding to the active sites of the corresponding enzymes. Molecular docking simulation of mixed-type and noncompetitive inhibitors for BACE1, AChE, and BChE indicated novel binding site-directed inhibition of the enzymes by pterosins and the structure-activity relationship. (2R)-Pterosin B exhibited a strong BBB permeability with an effective permeability (Pe) of 60.3×10-6 cm/s on PAMPA-BBB. (2R)-Pterosin B and (2R,3 R)-pteroside C significantly decreased the secretion of Aß peptides from neuroblastoma cells that overexpressed human ß-amyloid precursor protein at 500 µM. Conclusively, our study suggested that several pterosins are potential scaffolds for multitarget-directed ligands (MTDLs) for AD therapeutics.

3D-QSAR-aided design of potent c-Met inhibitors using molecular dynamics simulation and binding free energy calculation.

Mesenchymal-epithelial transition factor (c-Met) is a member of receptor tyrosine kinase. It involves in various cellular signaling pathways which includes proliferation, motility, migration, and invasion. Over-expression of c-Met has been reported in various cancers. Hence, it is an ideal therapeutic target for cancer. The main objective of the study is to identify crucial residues involved in the inhibition of c-Met kinase and to design a series of potent imidazo [4,5-b] pyrazine derivatives as c-Met inhibitors. Docking was used to identify important active site residues involved in the inhibition of c-Met kinase which was further validated by 100 ns of molecular dynamics simulation and free energy calculation using molecular mechanics generalized born surface area. Furthermore, binding energy decomposition identified that residues Tyr1230, Met1211, Asp1222, Tyr1159, Met1160, Val1092, Ala1108, and Leu1157 contributed favorably to the binding stability of compound 32. Receptor-guided Comparative Molecular Field Analysis (CoMFA) (q2 = 0.751, NOC = 6, r2 = 0.933) and Comparative Molecular Similarity Indices Analysis (COMSIA) (q2 = 0.744, NOC = 6, r2 = 0.950) models were generated based on the docked conformation of the most active compound 32. The robustness of these models was tested using various validation techniques and found to be predictive. The results of CoMFA and CoMSIA contour maps exposed the regions favorable to enhance the activity. Based on this information, 27 novel c-Met inhibitors were designed. These designed compounds exhibited potent activity than the most active compound of the existing dataset. Communicated by Ramaswamy H. Sarma.

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

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.

Discovery and optimization of ATX inhibitors via modeling, synthesis and biological evaluation.

Autotaxin (ATX) is a potential target for the treatment of various cancers. A new series of ATX inhibitors was rationally designed and synthesized based on our previous study. Biological evaluation and structure-activity relationship (SAR) of this series are discussed. Among fourteen synthesized derivatives, six compounds (2, 3, 4, 12, 13 and 14) exhibited enhanced ATX inhibitory activities with IC50 values in the low nanomolar range. Molecular interactions of all the synthesized compounds within the active site of ATX were studied through molecular docking studies. Herein, we describe our lead optimization efforts that resulted in the identification of a potent ATX inhibitor (compound 4 with IC50 = 1.23 nM, FS-3 and 2.18 nM, bis-pNPP). Furthermore, pharmacokinetic properties of this most promising compound are profiled.

Design, synthesis, docking and biological evaluation of 4-phenyl-thiazole derivatives as autotaxin (ATX) inhibitors.

The autotaxin-lysophophatidic acid (ATX-LPA) signaling pathway is involved in several human diseases such as cancer, autoimmune diseases, inflammatory diseases neurodegenerative diseases and fibrotic diseases. Herein, a series of 4-phenyl-thiazole based compounds was designed and synthesized. Compounds were evaluated for their ATX inhibitory activity using FS-3 and human plasma assays. In the FS-3 assay, compounds 20 and 21 significantly inhibited the ATX at low nanomolar level (IC50=2.99 and 2.19nM, respectively). Inhibitory activity of 21 was found to be slightly better than PF-8380 (IC50=2.80nM), which is one of the most potent ATX inhibitors reported till date. Furthermore, 21 displayed higher potency (IC50=14.99nM) than the first clinical ATX inhibitor, GLPG1690 (IC50=242.00nM) in the human plasma assay. Molecular docking studies were carried out to explore the binding pattern of newly synthesized compounds within active site of ATX. Docking studies suggested the putative binding mode of the novel compounds. Good ATX inhibitory activity of 21 was attributed to the hydrogen bonding interactions with Asn230, Trp275 and active site water molecules; electrostatic interaction with catalytic zinc ion and hydrophobic interactions with amino acids of the hydrophobic pocket.

Receptor-guided 3D-QSAR studies, molecular dynamics simulation and free energy calculations of Btk kinase inhibitors.

BACKGROUND: Bruton tyrosine kinase (Btk) plays an important role in B-cell development, differentiation, and signaling. It is also found be in involved in male immunodeficiency disease such as X-linked agammaglobulinemia (XLA). Btk is considered as a potential therapeutic target for treating autoimmune diseases and hematological malignancies. RESULTS: In this work, a combined molecular modeling study was performed on a series of thieno [3,2-c] pyridine-4-amine derivatives as Btk inhibitors. Receptor-guided COMFA (q 2 = 0.574, NOC = 3, r 2 = 0.924) and COMSIA (q 2 = 0.646, NOC = 6, r 2 = 0.971) models were generated based on the docked conformation of the most active compound 26. All the developed models were tested for robustness using various validation techniques. Furthermore, a 5-ns molecular dynamics (MD) simulation and binding free energy calculations were carried out to determine the binding modes of the inhibitors and to identify crucial interacting residues. The rationality and stability of molecular docking and 3D-QSAR results were validated by MD simulation. The binding free energies calculated by the MM/PBSA method showed the importance of the van der Waals interaction. CONCLUSIONS: A good correlation between the MD results, docking studies, and the contour map analysis were observed. The study has identified the key amino acid residues in Btk binding pocket. The results from this study can provide some insights into the development of potent, novel Btk inhibitors.

Design of Novel Chemotherapeutic Agents Targeting Checkpoint Kinase 1 Using 3D-QSAR Modeling and Molecular Docking Methods.

BACKGROUND: Checkpoint kinase 1 (Chk1) has emerged as a potential therapeutic target for design and development of novel anticancer drugs. OBJECTIVE: Herein, we have performed three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses on a series of diazacarbazoles to design potent Chk1 inhibitors. METHODS: 3D-QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Docking studies were performed using AutoDock. RESULTS: The best CoMFA and CoMSIA models exhibited cross-validated correlation coefficient (q2) values of 0.631 and 0.585, and non-cross-validated correlation coefficient (r2) values of 0.933 and 0.900, respectively. CoMFA and CoMSIA models showed reasonable external predictabilities (r2 pred) of 0.672 and 0.513, respectively. CONCLUSION: A satisfactory performance in the various internal and external validation techniques indicated the reliability and robustness of the best model. Docking studies were performed to explore the binding mode of inhibitors inside the active site of Chk1. Molecular docking revealed that hydrogen bond interactions with Lys38, Glu85 and Cys87 are essential for Chk1 inhibitory activity. The binding interaction patterns observed during docking studies were complementary to 3D-QSAR results. Information obtained from the contour map analysis was utilized to design novel potent Chk1 inhibitors. Their activities and binding affinities were predicted using the derived model and docking studies. Designed inhibitors were proposed as potential candidates for experimental synthesis.

Molecular modeling studies on series of Btk inhibitors using docking, structure-based 3D-QSAR and molecular dynamics simulation: a combined approach.

Bruton tyrosine kinase (Btk) is a non-receptor tyrosine kinase. It is a crucial component in BCR pathway and expressed only in hematopoietic cells except T cells and Natural killer cells. BTK is a promising target because of its involvement in signaling pathways and B cell diseases such as autoimmune disorders and lymphoma. In this work, a combined molecular modeling study of molecular docking, 3D-QSAR and molecular dynamic (MD) simulation were performed on a series of 2,5-diaminopyrimidine compounds as inhibitors targeting Btk kinase to understand the interaction and key residues involved in the inhibition. A structure based CoMFA (q (2) = 0.675, NOC = 5, r (2) = 0.961) and COMSIA (q (2) = 0.704, NOC = 6, r (2) = 0.962) models were developed from the conformation obtained by docking. The developed models were subjected to various validation techniques such as leave-five-out, external test set, bootstrapping, progressive sampling and rm (2) metrics and found to have a good predictive ability in both internal and external validation. Our docking results showed the important residues that interacts in the active site residues in inhibition of Btk kinase. Furthermore, molecular dynamics simulation was employed to study the stability of the docked conformation and to investigate the binding interactions in detail. The MD simulation analyses identified several important hydrogen bonds with Btk, including the gatekeeper residue Thr474 and Met477 at the hinge region. Hydrogen bond with active site residues Leu408 and Arg525 were also recognized. A good correlation between the MD results, docking studies and the contour map analysis are observed. This indicates that the developed models are reliable. Our results from this study can provide insights in the designing and development of more potent Btk kinase inhibitors.

3D-QSAR study of tetrahydro-3H-imidazo[4,5-c]pyridine derivatives as VEGFR-2 kinase inhibitors using various charge schemes.

Vascular endothelial growth factor-2 receptor (VEGFR-2) kinase is a promising target for the development of novel anticancer drugs. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on a series of tetrahydro-3H-imidazo[4,5-c]pyridine derivatives to understand the structural basis for VEGFR-2 inhibitory activity. Several 3D-QSAR models were developed using various partial atomic charge schemes. Comparative molecular field analysis (CoMFA) and Comparative molecular similarity indices analysis (CoMSIA) methods were employed to derive these models. The CoMFA models performed better than the CoMSIA models. The reliable CoMFA model was obtained with the Gasteiger-Marsili charge scheme. The model produced statistically significant results with a cross-validated correlation coefficient (q(2)) of 0.635 and a coefficient of determination (r(2)) of 0.930. The model showed reasonable predictive power with predictive correlation coefficient ([Formula: see text]) of 0.582. Robustness of the model was further checked by leave-five-out cross-validation, bootstrapping and progressive scrambling analysis. The model was found to be statistically robust and expected to assist in the design of novel compounds with enhanced VEGFR-2 inhibitory activity.

Modeling study of phenylsulfonylfuroxan derivatives as P-gp inhibitors: a combined approach of CoMFA, CoMSIA and HQSAR.

Multidrug resistance (MDR) is a phenomenon whereby cancer cells experience intrinsic or acquired resistance to a broad spectrum of structurally and functionally distinct chemotherapeutic agents. Permeability glycoprotein (P-gp) is the key protein responsible for the development of MDR in cancer cells, as it exports chemotherapeutic agents from cells. In the present study, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram quantitative structure activity relationship (HQSAR) techniques were used to derive predictive models for phenylsulfonylfuroxan derivatives as P-gp inhibitors. Cross-validated correlation coefficients (q(2)) of 0.811, 0.855, and 0.907 and non-cross-validated correlation coefficients (r(2)) of 0.87, 0.985, and 0.973 were obtained for CoMFA, CoMSIA, and HQSAR derived models, respectively. The predictive power of the models were assessed using an external test set of five compounds and showed reasonable external predictabilities (r(2) pred) of 0.704, 0.517, and 0.713, respectively. Contour and atomic contribution maps were generated to investigate physicochemical requirements of ligands for better receptor binding affinity. 3D Contour maps suggested molecular interactions such as steric and electrostatic effects and hydrogen bond formation. However, atomic contribution maps indicated that ortho and para positions of the R(1) phenylsulfonyl ring are the most desirable regions to modulate P-gp antagonism. The 3(rd) and 4(th) positions of the central five-membered ring were also found to be important. Our results are in line with previous reports. Information obtained from the contour and atomic contribution maps were utilized to design more potent compounds containing different R(1) fragments. In addition, the activities of these more potent compounds were predicted using derived models.