3D-QSAR study of microsomal prostaglandin E2 synthase (mPGES-1) inhibitors

Three-Dimensional-QSAR and Relative Binding Affinity Estimation of Focal Adhesion Kinase Inhibitors

Precise binding affinity predictions are essential for structure-based drug discovery (SBDD). Focal adhesion kinase (FAK) is a member of the tyrosine kinase protein family and is overexpressed in a variety of human malignancies. Inhibition of FAK using small molecules is a promising therapeutic option for several types of cancer. Here, we conducted computational modeling of FAK-targeting inhibitors using three-dimensional structure-activity relationship (3D-QSAR), molecular dynamics (MD), and hybrid topology-based free energy perturbation (FEP) methods. The structure-activity relationship (SAR) studies between the physicochemical descriptors and inhibitory activities of the chemical compounds were performed with reasonable statistical accuracy using CoMFA and CoMSIA. These are two well-known 3D-QSAR methods based on the principle of supervised machine learning (ML). Essential information regarding residue-specific binding interactions was determined using MD and MM-PB/GBSA methods. Finally, physics-based relative binding free energy (ΔΔGRBFEA→B) terms of analogous ligands were estimated using alchemical FEP simulation. An acceptable agreement was observed between the experimental and computed relative binding free energies. Overall, the results suggested that using ML and physics-based hybrid approaches could be useful in synergy for the rational optimization of accessible lead compounds with similar scaffolds targeting the FAK receptor.

Structural Insights from Molecular Modeling of Isoindolin-1-One Derivatives as PI3Kγ Inhibitors against Gastric Carcinoma

The upregulation of phosphoinositol-3-kinase γ (PI3Kγ) is deemed to be positively correlated with tumor-associated-macrophage (TAM)-mediated gastric carcinoma (GC). PI3Kγ suppresses tumor necrosis factor-alpha (TNF-α) and interleukin-12 (IL-12) through activation of the AKT/mTOR pathway, which promotes the immunosuppressant phenotype of TAM. Unlike α and β isoforms, δ and γ isoforms are primarily distributed in leucocytes and macrophages. Dual inhibitors against PI3Kδ and PI3Kγ have been proven to have merits in targeting solid tumors. Furthermore, it has been found that PI3Kδ is activated by cytokines, while PI3Kγ is activated by G-protein-coupled receptors (GPCRs). This facilitates determining the functional difference between these two isoforms. For this goal, selective inhibitors would be immensely helpful. In the current manuscript, we conducted various molecular modeling studies with a series of isoindolin-1-one derivatives as potent PI3Kγ inhibitors by combining molecular docking, molecular dynamics (MD), molecular mechanics, Poisson–Boltzmann/generalized Born surface area (MM-PB/GBSA) binding free energy calculation, and three-dimensional structure–activity relationship (3D-QSAR) study. To evaluate the selectivity of γ isoform over δ, the molecular modeling studies of idelalisib analogs reported as PI3Kδ inhibitors were also investigated. The contour polyhedrons were generated from the comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) around the ligand-bound active site for both isoforms, which could emphasize plausible explanations for the physicochemical factors that affect selective ligand recognition. The binding modalities of the two isoforms using CoMFA and MD models were compared, which suggested some key differences in the molecular interactions with the ligands and could be summarized as three subsites (one affinity subsite near the C-helix and DFG and two hydrophobic subsites). In the context of the structure–activity relationship (SAR), several new compounds were designed using a fragment-substitution strategy with the aim of selectively targeting PI3Kγ. The pIC50 values of the designed compounds were predicted by the 3D-QSAR models, followed by the MM-PB/GBSA binding energy estimation. The overall findings suggest that the designed compounds have the potential to be used as PI3Kγ inhibitors with a higher binding affinity and selectivity.

Molecular Modeling Studies of N-phenylpyrimidine-4-amine Derivatives for Inhibiting FMS-like Tyrosine Kinase-3

Overexpression and frequent mutations in FMS-like tyrosine kinase-3 (FLT3) are considered risk factors for severe acute myeloid leukemia (AML). Hyperactive FLT3 induces premature activation of multiple intracellular signaling pathways, resulting in cell proliferation and anti-apoptosis. We conducted the computational modeling studies of 40 pyrimidine-4,6-diamine-based compounds by integrating docking, molecular dynamics, and three-dimensional structure-activity relationship (3D-QSAR). Molecular docking showed that K644, C694, F691, E692, N701, D829, and F830 are critical residues for the binding of ligands at the hydrophobic active site. Molecular dynamics (MD), together with Molecular Mechanics Poison-Boltzmann/Generalized Born Surface Area, i.e., MM-PB(GB)SA, and linear interaction energy (LIE) estimation, provided critical information on the stability and binding affinity of the selected docked compounds. The MD study suggested that the mutation in the gatekeeper residue F691 exhibited a lower binding affinity to the ligand. Although, the mutation in D835 in the activation loop did not exhibit any significant change in the binding energy to the most active compound. We developed the ligand-based comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models. CoMFA (q² = 0.802, r² = 0.983, and QF32 = 0.698) and CoMSIA (q² = 0.725, r² = 0.965 and QF32 = 0.668) established the structure-activity relationship (SAR) and showed a reasonable external predictive power. The contour maps from the CoMFA and CoMSIA models could explain valuable information about the favorable and unfavorable positions for chemical group substitution, which can increase or decrease the inhibitory activity of the compounds. In addition, we designed 30 novel compounds, and their predicted pIC₅₀ values were assessed with the CoMSIA model, followed by the assessment of their physicochemical properties, bioavailability, and free energy calculation. The overall outcome could provide valuable information for designing and synthesizing more potent FLT3 inhibitors.

Designing of the N-ethyl-4-(pyridin-4-yl)benzamide based potent ROCK1 inhibitors using docking, molecular dynamics, and 3D-QSAR

Rho-associated kinase-1 (ROCK1) has been recognized for its pivotal role in heart diseases, different types of malignancy, and many neurological disorders. Hyperactivity of ROCK phosphorylates the protein kinase-C (PKC), which ultimately induces smooth muscle cell contraction in the vascular system. Inhibition of ROCK1 has been shown to be a promising therapy for patients with cardiovascular disease. In this study, we have conducted molecular modeling techniques such as docking, molecular dynamics (MD), and 3-Dimensional structure-activity relationship (3D-QSAR) on a series of N-ethyl-4-(pyridin-4-yl)benzamide-based compounds. Docking and MD showed critical interactions and binding affinities between ROCK1 and its inhibitors. To establish the structure-activity relationship (SAR) of the compounds, 3D-QSAR techniques such as Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were used. The CoMFA (q ² = 0.774, r ² = 0.965, ONC = 6, and r p r e d 2 = 0.703) and CoMSIA (q ² = 0.676, r ² = 0.949, ONC = 6, and r p r e d 2 = 0.548) both models have shown reasonable external predictive activity, and contour maps revealed favorable and unfavorable substitutions for chemical group modifications. Based on the contour maps, we have designed forty new compounds, among which, seven compounds exhibited higher predictive activity (pIC₅₀). Further, we conducted the MD study, ADME/Tox, and SA score prediction using the seven newly designed compounds. The combination of docking, MD, and 3D-QSAR studies helps to understand the coherence modification of existing molecules. Our study may provide valuable insight into the development of more potent ROCK1 inhibitors.

Molecular Modelling Studies on Pyrazole Derivatives for the Design of Potent Rearranged during Transfection Kinase Inhibitors

RET (rearranged during transfection) kinase, one of the receptor tyrosine kinases, plays a crucial role in the development of the human nervous system. It is also involved in various cell signaling networks responsible for the normal cell division, growth, migration, and survival. Previously reported clinical studies revealed that deregulation or aberrant activation of RET signaling can cause several types of human cancer. For example, medullary thyroid carcinoma (MTC) and multiple endocrine neoplasia (MEN2A, MEN2B) occur due to sporadic mutation or germline RET mutation. A number of RET kinase inhibitors have been approved by the FDA for the treatment of cancer, such as cabozantinib, vandetanib, lenvatinib, and sorafenib. However, each of these drugs is a multikinase inhibitor. Hence, RET is an important therapeutic target for cancer drug design. In this work, we have performed various molecular modelling studies, such as molecular docking and dynamics simulation for the most active compound of the pyrazole series as RET kinase inhibitors. Furthermore, molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) free energy calculation and 3-dimensional quantitative structure-activity relationship (3D-QSAR) were performed using g_mmpbsa and SYBYL-X 2.1 package. The results of this study revealed the crucial binding site residues at the active site of RET kinase and contour map analysis showed important structural characteristics for the design of new highly active inhibitors. Therefore, we have designed ten RET kinase inhibitors, which showed higher inhibitory activity than the most active compound of the series. The results of our study provide insights to design more potent and selective RET kinase inhibitors.

Molecular Modeling Study of c-KIT/PDGFRα Dual Inhibitors for the Treatment of Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are the most common Mesenchymal Neoplasm of the gastrointestinal tract. The tumorigenesis of GISTs has been associated with the gain-of-function mutation and abnormal activation of the stem cell factor receptor (c-KIT) and platelet-derived growth factor receptor alpha (PDGFRα) kinases. Hence, inhibitors that target c-KIT and PDGFRα could be a therapeutic option for the treatment of GISTs. The available approved c-KIT/PDGFRα inhibitors possessed low efficacy with off-target effects, which necessitated the development of potent inhibitors. We performed computational studies of 48 pyrazolopyridine derivatives that showed inhibitory activity against c-KIT and PDGFRα to study the structural properties important for inhibition of both the kinases. The derivative of phenylurea, which has high activities for both c-KIT (pIC₅₀ = 8.6) and PDGFRα (pIC₅₀ = 8.1), was used as the representative compound for the dataset. Molecular docking and molecular dynamics simulation (100 ns) of compound 14 was performed. Compound 14 showed the formation of hydrogen bonding with Cys673, Glu640, and Asp810 in c-KIT, and Cys677, Glu644, and Asp836 in PDGFRα. The results also suggested that Thr670/T674 substitution in c-KIT/PDGFRα induced conformational changes at the binding site of the receptors. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed based on the inhibitors. Contour map analysis showed that electropositive and bulky substituents at the para-position and the meta-position of the benzyl ring of compound 14 was favorable and may increase the inhibitory activity against both c-KIT and PDGFRα. Analysis of the results suggested that having bulky and hydrophobic substituents that extend into the hydrophobic pocket of the binding site increases the activity for both c-KIT and PDGFRα. Based on the contour map analysis, 50 compounds were designed, and the activities were predicted. An evaluation of binding free energy showed that eight of the designed compounds have potential binding affinity with c-KIT/PDGFRα. Absorption, distribution, metabolism, excretion and toxicity (ADMET) and synthetic feasibility tests showed that the designed compounds have reasonable pharmaceutical properties and synthetic feasibility. Further experimental study of the designed compounds is recommended. The structural information from this study could provide useful insight into the future development of c-KIT and PDGFRα inhibitors.

Computational models for the classification of mPGES-1 inhibitors with fingerprint descriptors

Human microsomal prostaglandin [Formula: see text] synthase (mPGES)-1 is a promising drug target for inflammation and other diseases with inflammatory symptoms. In this work, we built classification models which were able to classify mPGES-1 inhibitors into two groups: highly active inhibitors and weakly active inhibitors. A dataset of 1910 mPGES-1 inhibitors was separated into a training set and a test set by two methods, by a Kohonen's self-organizing map or by random selection. The molecules were represented by different types of fingerprint descriptors including MACCS keys (MACCS), CDK fingerprints, Estate fingerprints, PubChem fingerprints, substructure fingerprints and 2D atom pairs fingerprint. First, we used a support vector machine (SVM) to build twelve models with six types of fingerprints and found that MACCS had some advantage over the other fingerprints in modeling. Next, we used naïve Bayes (NB), random forest (RF) and multilayer perceptron (MLP) methods to build six models with MACCS only and found that models using RF and MLP methods were better than NB. Finally, all the models with MACCS keys were used to make predictions on an external test set of 41 compounds. In summary, the models built with MACCS keys and using SVM, RF and MLP methods show good prediction performance on the test sets and the external test set. Furthermore, we made a structure-activity relationship analysis between mPGES-1 and its inhibitors based on the information gain of fingerprints and could pinpoint some key functional groups for mPGES-1 activity. It was found that highly active inhibitors usually contained an amide group, an aromatic ring or a nitrogen heterocyclic ring, and several heteroatoms substituents such as fluorine and chlorine. The carboxyl group and sulfur atom groups mainly appeared in weakly active inhibitors.

Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β

Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q²) was 0.571 and non-cross-validation correlation coefficient (r²) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results.

Microsomal Prostaglandin E2 Synthase-1

The prostanoids and leukotrienes (LTs) formed from arachidonic acid (AA) via the cyclooxygenase (COX)-1/2 and 5-lipoxygenase (5-LO) pathway, respectively, mediate inflammatory responses, chronic tissue remodelling, cancer, asthma and autoimmune disorders, but also possess homeostatic functions in the gastrointestinal tract, uterus, brain, kidney, vasculature and host defence. Based on the manifold functions of these eicosanoids, the clinical use of non-steroidal anti-inflammatory drugs (NSAIDs), a class of drugs that block formation of all prostanoids, is hampered by severe side-effects including gastrointestinal injury, renal irritations and cardiovascular risks. Therefore, anti-inflammatory agents interfering with eicosanoid biosynthesis require a well-balanced pharmacological profile to minimize these on-target side-effects. Current anti-inflammatory research aims at identifying compounds that can suppress the massive formation of pro-inflammatory prostaglandin (PG)E2 without affecting homeostatic PGE2 and PGI2 synthesis. The inducible microsomal prostaglandin E2 synthase-1 (mPGES-1) is one promising target enzyme. We will give an overview about the structure, regulation and function of mPGES-1 and then present novel inhibitors of mPGES-1 that may possess a promising pharmacological profile.

Pharmacophore modeling and virtual screening for novel acidic inhibitors of microsomal prostaglandin E₂ synthase-1 (mPGES-1)

Microsomal prostaglandin E₂ synthase-1 (mPGES-1) catalyzes prostaglandin E₂ formation and is considered as a potential anti-inflammatory pharmacological target. To identify novel chemical scaffolds active on this enzyme, two pharmacophore models for acidic mPGES-1 inhibitors were developed and theoretically validated using information on mPGES-1 inhibitors from literature. The models were used to screen chemical databases supplied from the National Cancer Institute (NCI) and the Specs. Out of 29 compounds selected for biological evaluation, nine chemically diverse compounds caused concentration-dependent inhibition of mPGES-1 activity in a cell-free assay with IC₅₀ values between 0.4 and 7.9 μM, respectively. Further pharmacological characterization revealed that also 5-lipoxygenase (5-LO) was inhibited by most of these active compounds in cell-free and cell-based assays with IC₅₀ values in the low micromolar range. Together, nine novel chemical scaffolds inhibiting mPGES-1 are presented that may possess anti-inflammatory properties based on the interference with eicosanoid biosynthesis.

mPGES-1 as a target for cancer suppression: A comprehensive invited review "Phospholipase A2 and lipid mediators"

Prostaglandin E(2) (PGE(2)) is a bioactive lipid that can elicit a wide range of biological effects associated with inflammation and cancer. The physiological roles of PGE(2) are diverse, mediated in part through activation of key downstream signaling cascades via transmembrane EP receptors located on the cell surface. Elevated levels of COX-2 and concomitant overproduction of PGE(2) are often found in human cancers. These observations have led to the use of non-steroidal anti-inflammatory drugs (NSAIDs) as chemopreventive agents, particularly for colorectal cancer (CRC). Their long-term use, however, may be associated with gastrointestinal toxicity and increased risk of adverse cardiovascular events, prompting the development of other enzymatic targets in this pathway. This review will focus on recent efforts to target the terminal synthase, mPGES-1, for cancer chemoprevention. The role of mPGES-1 in the pathogenesis of various cancers is discussed. In addition, an overview of recent efforts to develop small molecule inhibitors that target the protein with high selectivity is also be reviewed.