Pharmacophore Modeling, Ensemble Docking, Virtual Screening, and Biological Evaluation on Glycogen Synthase Kinase-3β

In Silico-Motivated Discovery of Novel Potent Glycogen Synthase-3 Inhibitors: 1-(Alkyl/arylamino)-3H-naphtho[1,2,3-de]quinoline-2,7-dione Identified as a Scaffold for Kinase Inhibitor Development

Glycogen synthase kinase-3 (GSK-3) isoforms α and β have diverse roles within cell biology, and have been linked with multiple diseases that include prominent CNS conditions such as Alzheimer's disease and several psychiatric disorders. In this study, motivated by computation, we aimed to identify novel ATP-binding site inhibitors of GSK-3 with CNS-active potential. A ligand screening (docking) protocol against GSK-3β was first optimized, employing an active/decoy benchmarking set, with the final protocol selected based on statistical performance analysis. The optimized protocol involved pre-filtering of ligands using a three-point 3D-pharmacophore, followed by Glide-SP docking applying hinge region hydrogen bonding constraints. Using this approach, the Biogenic subset of the ZINC15 compound database was screened, focused on compounds with potential for CNS-activity. Twelve compounds (generation I) were selected for experimental validation using in vitro GSK-3β binding assays. Two hit compounds, 1 and 2, with 6-amino-7H-benzo[e]perimidin-7-one and 1-(phenylamino)-3H-naphtho[1,2,3-de]quinoline-2,7-dione type scaffolds were identified with IC₅₀ values of 1.63 µM and 20.55 µM, respectively. Ten analogues of 2 (generation II) were selected for structure activity relationship (SAR) analysis and revealed four low micromolar inhibitors (<10 µM), with 19 (IC₅₀ = 4.1 µM)~five times more potent than initial hit compound 2. Selectivity screening of low micromolar inhibitors 14 and 19 (comparing aryl- and alkyl-substituents) against 10 homologous kinases revealed unique selectivity profiles, with both compounds more potent against the GSK-3α isoform (IC₅₀s~2 µM) and, additionally, inhibitors of PKBβ (IC₅₀s < 25 µM). Compound 14 also inhibited ERK2 and 19, PKCγ, but generally good selectivity for GSK-3 isoforms over the other kinases was observed. The compounds had excellent predicted oral bioavailability and CNS-activity profiles, presenting promising candidates for future testing in cellular models of disease.

From Data to Knowledge: Systematic Review of Tools for Automatic Analysis of Molecular Dynamics Output

An increasing number of crystal structures available on one side, and the boost of computational power available for computer-aided drug design tasks on the other, have caused that the structure-based drug design tools are intensively used in the drug development pipelines. Docking and molecular dynamics simulations, key representatives of the structure-based approaches, provide detailed information about the potential interaction of a ligand with a target receptor. However, at the same time, they require a three-dimensional structure of a protein and a relatively high amount of computational resources. Nowadays, as both docking and molecular dynamics are much more extensively used, the amount of data output from these procedures is also growing. Therefore, there are also more and more approaches that facilitate the analysis and interpretation of the results of structure-based tools. In this review, we will comprehensively summarize approaches for handling molecular dynamics simulations output. It will cover both statistical and machine-learning-based tools, as well as various forms of depiction of molecular dynamics output.

Structure-Based Design of Potent Selective Nanomolar Type-II Inhibitors of Glycogen Synthase Kinase-3β

For the first time, the in silico design, screening, and in vitro validation of potent GSK-3β type-II inhibitors are presented. In the absence of crystallographic evidence for a DFG-out GSK-3β activation loop conformation, computational models were designed using an adapted DOLPHIN approach and a method consisting of Prime loop refinement, induced-fit docking, and molecular dynamics. Virtual screening of the Biogenics subset from the ZINC database led to an initial selection of 20 Phase I compounds revealing two low micromolar inhibitors in an isolated enzyme assay. Twenty more analogues (Phase II compounds) related to the hit [pyrimidin-2-yl]amino-furo[3,2-b]furyl-urea scaffold were selected for structure-activity relationship analysis. The Phase II studies led to five highly potent nanomolar inhibitors, with compound 23 (IC₅₀ =0.087 μM) > 100 times more potent than the best Phase I inhibitor, and selectivity for GSK-3β inhibition compared to homologous kinases was observed. Ex vivo experiments (SH-SY5Y cell lines) for tau hyperphosphorylation revealed promising neuroprotective effects at low micromolar concentrations. The type-II inhibitor design has been unraveled as a potential route toward more clinically effective GSK-3β inhibitors.

Molecular modeling studies to discover novel mIDH2 inhibitors with high selectivity for the primary and secondary mutants

Mutant isocitrate dehydrogenase 2 (mIDH2) is an emerging target for the treatment of cancer. AG-221 is the first mIDH2 inhibitor approved by the FDA for acute myeloid leukemia treatment, but its acquired resistance has recently been observed, necessitating the development of new inhibitor. In this study, a multi-step virtual screening protocol was employed for the analysis of a large database of compounds to identify potential mIDH2 inhibitors. To this end, we firstly utilized molecular dynamics (MD) simulations and binding free energy calculations to elucidate the key factors affecting ligand binding and drug resistance. Based on these findings, the receptor-ligand interaction-based pharmacophore (IBP) model and hierarchical docking-based virtual screening were sequentially carried out to assess 212,736 compounds from the Specs database. The resulting hits were finally ranked by PAINS filter and ADME prediction and the top compounds were obtained. Among them, six molecules were identified as mIDH2 putative inhibitors with high selectivity by interacting with the capping residue Asp312. Furthermore, subsequent docking and MD experiments demonstrated that compound V2 might have potential inhibitory activity against the AG-221-resistant mutants, thereby making it a promising lead for the development of novel mIDH2 inhibitors.

Revisiting the intersection of amyloid, pathologically modified tau and iron in Alzheimer's disease from a ferroptosis perspective

The complexity of Alzheimer's disease (AD) complicates the search for effective treatments. While the key roles of pathologically modified proteins has occupied a central role in hypotheses of the pathophysiology, less attention has been paid to the potential role for transition metals overload, subsequent oxidative stress, and tissue injury. The association of transition metals, the major focus heretofore iron and amyloid, the same can now be said for the likely pathogenic microtubular associated tau (MAPT). This review discusses the interplay between iron, pathologically modified tau and oxidative stress, and connects many related discoveries. Basic principles of the transition to pathological MAPT are discussed. Iron, its homeostatic mechanisms, the recently described phenomenon of ferroptosis and purported, although still controversial roles in AD are reviewed as well as considerations to overcome existing hurdles of iron-targeted therapeutic avenues that have been attempted in AD. We summarize the involvement of multiple pathological pathways at different disease stages of disease progression that supports the potential for a combinatorial treatment strategy targeting multiple factors.

Discovery of Selective, Substrate-Competitive, and Passive Membrane Permeable Glycogen Synthase Kinase-3β Inhibitors: Synthesis, Biological Evaluation, and Molecular Modeling of New C-Glycosylflavones

Glycogen synthase kinase-3β (GSK-3β) is a key enzyme responsible for tau hyperphosphorylation and is a viable therapeutic target of Alzheimer's disease (AD). We developed a new class of GSK-3β inhibitors based on the 6- C-glycosylflavone isoorientin (1). The new inhibitors are passive membrane permeable and constitutively attenuate GSK-3β mediated tau hyperphosphorylation and amyloid neurotoxicity in an AD cellular model. Enzymatic assays and kinetic studies demonstrated that compound 30 is a GSK-3β substrate-competitive inhibitor with distinct kinase selectivity, isoform-selectivity and over 310-fold increased potency as compared to 1. Structure-activity relationship analyses and in silico modeling suggest the mechanism of actions by which the hydrophobic, π-cation, and orthogonal multipolar interactions of 30 with the substrate site are critical for the GSK-3β inhibition and selectivity. The results provide new insights into GSK-3β drug discovery. The new inhibitors are valuable chemical probes and drug leads with therapeutic potential to tackle AD and other GSK-3β relevant diseases.

Changing Paradigm from one Target one Ligand Towards Multi-target Directed Ligand Design for Key Drug Targets of Alzheimer Disease: An Important Role of In Silico Methods in Multi-target Directed Ligands Design

Alzheimer disease (AD) is now considered as a multifactorial neurodegenerative disorder and rapidly increasing to an alarming situation and causing higher death rate. One target one ligand hypothesis does not provide complete solution of AD due to multifactorial nature of the disease and one target one drug fails to provide better treatment against AD. Moreover, currently available treatments are limited and most of the upcoming treatments under clinical trials are based on modulating single target. So, the current AD drug discovery research is shifting towards a new approach for a better solution that simultaneously modulates more than one targets in the neurodegenerative cascade. This can be achieved by network pharmacology, multi-modal therapies, multifaceted, and/or the more recently proposed term "multi-targeted designed drugs". Drug discovery project is a tedious, costly and long-term project. Moreover, multi-target AD drug discovery added extra challenges such as the good binding affinity of ligands for multiple targets, optimal ADME/T properties, no/less off-target side effect and crossing of the blood-brain barrier. These hurdles may be addressed by insilico methods for an efficient solution in less time and cost as computational methods successfully applied to single target drug discovery project. Here, we are summarizing some of the most prominent and computationally explored single targets against AD and further, we discussed a successful example of dual or multiple inhibitors for same targets. Moreover, we focused on ligand and structure-based computational approach to design MTDL against AD. However, it is not an easy task to balance dual activity in a single molecule but computational approach such as virtual screening docking, QSAR, simulation and free energy is useful in future MTDLs drug discovery alone or in combination with a fragment-based method. However, rational and logical implementations of computational drug designing methods are capable of assisting AD drug discovery and play an important role in optimizing multi-target drug discovery.

Pharmacophore-based screening and drug repurposing exemplified on glycogen synthase kinase-3 inhibitors

The current study was conducted to elaborate a novel pharmacophore model to accurately map selective glycogen synthase kinase-3 (GSK-3) inhibitors, and perform virtual screening and drug repurposing. Pharmacophore modeling was developed using PHASE on a data set of 203 maleimides. Two benchmarking validation data sets with focus on selectivity were assembled using ChEMBL and PubChem GSK-3 confirmatory assays. A drug repurposing experiment linking pharmacophore matching with drug information originating from multiple data sources was performed. A five-point pharmacophore model was built consisting of a hydrogen bond acceptor (A), hydrogen bond donor (D), hydrophobic (H), and two rings (RR). An atom-based 3D quantitative structure-activity relationship (QSAR) model showed good correlative and satisfactory predictive abilities (training set [Formula: see text]; test set: [Formula: see text]; whole data set: stability [Formula: see text]). Virtual screening experiments revealed that selective GSK-3 inhibitors are ranked preferentially by Hypo-1, but fail to retrieve nonselective compounds. The pharmacophore and 3D QSAR models can provide assistance to design novel, potential GSK-3 inhibitors with high potency and selectivity pattern, with potential application for the treatment of GSK-3-driven diseases. A class of purine nucleoside antileukemic drugs was identified as potential inhibitor of GSK-3, suggesting the reassessment of the target range of these drugs.