Discovery of Indolinone-Based Multikinase Inhibitors as Potential Therapeutics for Idiopathic Pulmonary Fibrosis

CardioGenAI: a machine learning-based framework for re-engineering drugs for reduced hERG liability

The link between in vitro hERG ion channel inhibition and subsequent in vivo QT interval prolongation, a critical risk factor for the development of arrythmias such as Torsade de Pointes, is so well established that in vitro hERG activity alone is often sufficient to end the development of an otherwise promising drug candidate. It is therefore of tremendous interest to develop advanced methods for identifying hERG-active compounds in the early stages of drug development, as well as for proposing redesigned compounds with reduced hERG liability and preserved primary pharmacology. In this work, we present CardioGenAI, a machine learning-based framework for re-engineering both developmental and commercially available drugs for reduced hERG activity while preserving their pharmacological activity. The framework incorporates novel state-of-the-art discriminative models for predicting hERG channel activity, as well as activity against the voltage-gated NaV1.5 and CaV1.2 channels due to their potential implications in modulating the arrhythmogenic potential induced by hERG channel blockade. We applied the complete framework to pimozide, an FDA-approved antipsychotic agent that demonstrates high affinity to the hERG channel, and generated 100 refined candidates. Remarkably, among the candidates is fluspirilene, a compound which is of the same class of drugs as pimozide (diphenylmethanes) and therefore has similar pharmacological activity, yet exhibits over 700-fold weaker binding to hERG. Furthermore, we demonstrated the framework's ability to optimize hERG, NaV1.5 and CaV1.2 profiles of multiple FDA-approved compounds while maintaining the physicochemical nature of the original drugs. We envision that this method can effectively be applied to developmental compounds exhibiting hERG liabilities to provide a means of rescuing drug development programs that have stalled due to hERG-related safety concerns. Additionally, the discriminative models can also serve independently as effective components of virtual screening pipelines. We have made all of our software open-source at https://github.com/gregory-kyro/CardioGenAI to facilitate integration of the CardioGenAI framework for molecular hypothesis generation into drug discovery workflows.Scientific contributionThis work introduces CardioGenAI, an open-source machine learning-based framework designed to re-engineer drugs for reduced hERG liability while preserving their pharmacological activity. The complete CardioGenAI framework can be applied to developmental compounds exhibiting hERG liabilities to provide a means of rescuing drug discovery programs facing hERG-related challenges. In addition, the framework incorporates novel state-of-the-art discriminative models for predicting hERG, NaV1.5 and CaV1.2 channel activity, which can function independently as effective components of virtual screening pipelines.

Recent advances in the potential effects of natural products from traditional Chinese medicine against respiratory diseases targeting ferroptosis

Respiratory diseases, marked by structural changes in the airways and lung tissues, can lead to reduced respiratory function and, in severe cases, respiratory failure. The side effects of current treatments, such as hormone therapy, drugs, and radiotherapy, highlight the need for new therapeutic strategies. Traditional Chinese Medicine (TCM) offers a promising alternative, leveraging its ability to target multiple pathways and mechanisms. Active compounds from Chinese herbs and other natural sources exhibit anti-inflammatory, antioxidant, antitumor, and immunomodulatory effects, making them valuable in preventing and treating respiratory conditions. Ferroptosis, a unique form of programmed cell death (PCD) distinct from apoptosis, necrosis, and others, has emerged as a key area of interest. However, comprehensive reviews on how natural products influence ferroptosis in respiratory diseases are lacking. This review will explore the therapeutic potential and mechanisms of natural products from TCM in modulating ferroptosis for respiratory diseases like acute lung injury (ALI), asthma, pulmonary fibrosis (PF), chronic obstructive pulmonary disease (COPD), lung ischemia-reperfusion injury (LIRI), pulmonary hypertension (PH), and lung cancer, aiming to provide new insights for research and clinical application in TCM for respiratory health.

Emerging opportunities to treat idiopathic pulmonary fibrosis: Design, discovery, and optimizations of small-molecule drugs targeting fibrogenic pathways

Idiopathic pulmonary fibrosis (IPF) is the most common fibrotic form of idiopathic diffuse lung disease. Due to limited treatment options, IPF patients suffer from poor survival. About ten years ago, Pirfenidone (Shionogi, 2008; InterMune, 2011) and Nintedanib (Boehringer Ingelheim, 2014) were approved, greatly changing the direction of IPF drug design. However, limited efficacy and side effects indicate that neither can reverse the process of IPF. With insights into the occurrence of IPF, novel targets and agents have been proposed, which have fundamentally changed the treatment of IPF. With the next-generation agents, targeting pro-fibrotic pathways in the epithelial-injury model offers a promising approach. Besides, several next-generation IPF drugs have entered phase II/III clinical trials with encouraging results. Due to the rising IPF treatment requirements, there is an urgent need to completely summarize the mechanisms, targets, problems, and drug design strategies over the past ten years. In this review, we summarize known mechanisms, target types, drug design, and novel technologies of IPF drug discovery, aiming to provide insights into the future development and clinical application of next-generation IPF drugs.

Discovery and Anticancer Activity of Novel 1,3,4-Thiadiazole- and Aziridine-Based Indolin-2-ones via In Silico Design Followed by Supramolecular Green Synthesis

Three crucial anticancer scaffolds, namely indolin-2-one, 1,3,4-thiadiazole, and aziridine, are explored to synthesize virtually screened target molecules based on the c-KIT kinase protein. The stem cell factor receptor c-KIT was selected as target because most U.S. FDA-approved receptor tyrosine kinase inhibitors bearing the indolin-2-one scaffold profoundly inhibit c-KIT. Molecular hybrids of indolin-2-one with 1,3,4-thiadiazole (IIIa-m) and aziridine (VIa and VIc) were afforded through a modified Schiff base green synthesis using β-cyclodextrin-SO₃H in water as a recyclable proton-donor catalyst. A computational study found that indolin-2,3-dione forms a supramolecular inclusion complex with β-cyclodextrin-SO₃H through noncovalent interactions. A molecular docking study of all the synthesized compounds was executed on the c-KIT kinase domain, and most compounds displayed binding affinities similar to that of Sunitinib. On the basis of the pharmacokinetic significance of the aryl thioether linkage in small molecules, 1,3,4-thiadiazole hybrids (IIIa-m) were extended to a new series of 3-((5-(phenylthio)-1,3,4-thiadiazol-2-yl)imino)indolin-2-ones (IVa-m) via thioetherification using bis(triphenylphosphine)palladium(II)dichloride as the catalyst for C-S bond formation. Target compounds were tested against NCI-60 human cancer cell lines for a single-dose concentration. Among all three series of indolin-2-ones, the majority of compounds demonstrated broad-spectrum activity toward various cancer cell lines. Compounds IVc and VIc were further evaluated for a five-dose anticancer study. Compound IVc showed a potent activity of IC₅₀ = 1.47 μM against a panel of breast cancer cell lines, whereas compound VIc exhibited the highest inhibition for a panel of colon cancer cell lines at IC₅₀ = 1.40 μM. In silico ADME property descriptors of all the target molecules are in an acceptable range. Machine learning algorithms were used to examine the metabolites and phase I and II regioselectivities of compounds IVc and VIc, and the results suggested that these two compounds could be potential leads for the treatment of cancer.

Targeting Ferroptosis for Lung Diseases: Exploring Novel Strategies in Ferroptosis-Associated Mechanisms

Ferroptosis is an iron-dependent regulated necrosis characterized by the peroxidation damage of lipid molecular containing unsaturated fatty acid long chain on the cell membrane or organelle membrane after cellular deactivation restitution system, resulting in the cell membrane rupture. Ferroptosis is biochemically and morphologically distinct and disparate from other forms of regulated cell death. Recently, mounting studies have investigated the mechanism of ferroptosis, and numerous proteins play vital roles in regulating ferroptosis. With detailed studies, emerging evidence indicates that ferroptosis is found in multiple lung diseases, demonstrating that ferroptosis appears to be particularly important for lung diseases. The mounting interest in ferroptosis drugs specifically targeting the ferroptosis mechanism holds substantial therapeutic promise in lung diseases. The present review emphatically summarizes the functions and integrated molecular mechanisms of ferroptosis in various lung diseases, proposing that multiangle regulation of ferroptosis might be a promising strategy for the clinical treatment of lung diseases.

A holistic view on c-Kit in cancer: Structure, signaling, pathophysiology and its inhibitors

Receptor tyrosine kinases play an important role in many cellular processes, and their dysregulation leads to diseases, most importantly cancer. One such receptor tyrosine kinase is c-Kit, a type-III receptor tyrosine kinase, which is involved in various intracellular signaling pathways. The role of different mutant isoforms of c-Kit has been established in several types of cancers. Accordingly, promising c-Kit inhibition results have been reported for the treatment of different cancers (e.g., gastrointestinal stromal tumors, melanoma, acute myeloid leukemia, and other tumors). Therefore, lots of effort has been put to target c-Kit for the treatment of cancer. Here, we provide a comprehensive compilation to provide an insight into c-Kit inhibitor discovery. This compilation provides key information regarding the structure, signaling pathways related to c-Kit, and, more importantly, pharmacophores, binding modes, and SAR analysis for almost all small-molecule heterocycles reported for their c-Kit inhibitory activity. This work could be used as a guide in understanding the basic requirements for targeting c-Kit, and how the selectivity and efficacy of the molecules have been achieved till today.

The development of 3-substituted indolin-2-one derivatives as kinase inhibitors for cancer therapy

Kinases are pivotal regulators in tumorigenesis and metastasis by modulating the expression of oncogenes and the transcription of antioncogenes directly or indirectly. Correspondingly, multifarious 3-substituted indolin-2-one derivatives as selective kinase inhibitors for cancer therapy exhibited a low nanomolar activity with prominent efficacy, superior response rate and admirable tolerability. Particularly, certain 3-substituted indolin-2-one derivatives have met the requirements for clinical trials or the pharmaceutical market. Herein, we focus on the traits of 3-substituted indolin-2-one derivatives as kinase inhibitors for cancer therapy, overview recent progress of 3-substituted indolin-2-one derivatives as kinase inhibitors for cancer therapy, analyze the selectivity for tyrosine kinases inhibitors and serine/threonine kinases inhibitors from the molecular aspects based on the molecular docking studies, summarize the structure-activity relationships (SARs) as selective kinase inhibitors and provide our perspectives for the development of 3-substituted indolin-2-one derivatives as kinase inhibitors for cancer therapy.

Identification of potential platelet-derived growth factor receptor α inhibitors by computational screening and binding simulations

Platelet-derived growth factor receptor α (PDGFRα) is considered as a promising target for the treatment of fibrotic diseases. In this study, two types of pharmacophore model, which generated by ligand-based and receptor-based method, were put forward to identify novel chemical entities as PDGFRα inhibitors. It was found that some pharmacophore characteristics established by the two approaches overlap each other. In order to elucidate detailed interactions, representative molecules were selected to predict the conformations and binding modes of the molecules by molecular docking method. The calculation results of binding free energy illustrated that the van der Waals energy and nonpolar solvation were the most prominent contribution to the interactions between the inhibitors and PDGFRα. To further verify the accuracy of the docking results and the stability of the complexes system, the binding modes of two potent PDGFRα inhibitors were examined by 100 ns molecular dynamics simulations. Herein, we reported the basic structural requirements of PDGFRα inhibitors for the first time through molecular docking and molecular dynamics simulations. Subsequently, the two pharmacophore models were used for virtual screening to query potential active molecules from Food and Drug Administration approved database. The hit molecules here might provide additional scaffolds for further optimization of PDGFRα inhibitors.