Neuronal reprogramming is an innovative technique for converting non-neuronal somatic cells into neurons that can be used to replace lost or damaged neurons, providing a potential effective therapeutic strategy for central nervous system (CNS) injuries or diseases. Transcription factors have been used to induce neuronal reprogramming, while their reprogramming efficiency is relatively low, and the introduction of exogenous genes may result in host gene instability or induce gene mutation. Therefore, their future clinical application may be hindered by these safety concerns. Compared with transcription factors, small-molecule compounds have unique advantages in the field of neuronal reprogramming, which can overcome many limitations of traditional transcription factor-induced neuronal reprogramming. Here, we review the recent progress in the research of small-molecule compound-mediated neuronal reprogramming and its application in CNS regeneration and repair.
Humans ; Cellular Reprogramming/drug effects* ; Neurons/cytology* ; Animals ; Transcription Factors ; Small Molecule Libraries/pharmacology* ; Nerve Regeneration

The application of small molecule targeted drugs for lung cancer has significantly improved the survival of lung cancer patients. However, these drugs have a wide variety of types, fast development and market launch of new drugs, complex adverse reactions, and are mostly used at home, which increases the risk of irrational drug use. At the same time, insufficient monitoring of efficacy and safety is also prone to occur, ultimately affecting treatment outcomes. This consensus focuses on 43 small molecule targeted drugs or combinations for lung cancer, providing standardized recommendations for rational drug use and monitoring of efficacy/adverse reactions in clinical practice. The recommendations are regarding drug selection, dosage adjustment, efficacy monitoring, adverse reaction monitoring, and improvement of patient compliance. This consensus aims to improve the rational use and efficacy/safety monitoring quality of small molecule targeted drugs for lung cancer, ensure the effectiveness and safety of drug treatment, prolong the survival of lung cancer patients and improve their quality of life.
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Humans ; Lung Neoplasms/drug therapy* ; Antineoplastic Agents/adverse effects* ; Consensus ; Molecular Targeted Therapy ; Drug Monitoring ; Small Molecule Libraries/therapeutic use*

Artificial intelligence (AI) researchers and cheminformatics specialists strive to identify effective drug precursors while optimizing costs and accelerating development processes. Digital molecular representation plays a crucial role in achieving this objective by making molecules machine-readable, thereby enhancing the accuracy of molecular prediction tasks and facilitating evidence-based decision making. This study presents a comprehensive review of small molecular representations and AI-driven drug discovery downstream tasks utilizing these representations. The research methodology begins with the compilation of small molecule databases, followed by an analysis of fundamental molecular representations and the models that learn these representations from initial forms, capturing patterns and salient features across extensive chemical spaces. The study then examines various drug discovery downstream tasks, including drug-target interaction (DTI) prediction, drug-target affinity (DTA) prediction, drug property (DP) prediction, and drug generation, all based on learned representations. The analysis concludes by highlighting challenges and opportunities associated with machine learning (ML) methods for molecular representation and improving downstream task performance. Additionally, the representation of small molecules and AI-based downstream tasks demonstrates significant potential in identifying traditional Chinese medicine (TCM) medicinal substances and facilitating TCM target discovery.
Artificial Intelligence ; Drug Discovery/methods* ; Humans ; Machine Learning ; Medicine, Chinese Traditional ; Small Molecule Libraries/chemistry*

The human pregnane X receptor (hPXR) plays a critical role in the metabolism, transport and clearance of xenobiotics in the liver and intestine. The hPXR can be activated by a structurally diverse of drugs to initiate clinically relevant drug-drug interactions. In this article, in silico investigation was performed on a structurally diverse set of drugs to identify critical structural features greatly related to their agonist activity towards hPXR. Heuristic method (HM)-Best Subset Modeling (BSM) and HM-Polynomial Neural Networks (PNN) were utilized to develop the linear and non-linear quantitative structure-activity relationship models. The applicability domain (AD) of the models was assessed by Williams plot. Statistically reliable models with good predictive power and explain were achieved (for HM-BSM, r (2)=0.881, q LOO (2) =0.797, q EXT (2) =0.674; for HM-PNN, r (2)=0.882, q LOO (2) =0.856, q EXT (2) =0.655). The developed models indicated that molecular aromatic and electric property, molecular weight and complexity may govern agonist activity of a structurally diverse set of drugs to hPXR.
Computer Simulation ; Humans ; Models, Statistical ; Molecular Weight ; Neural Networks (Computer) ; Quantitative Structure-Activity Relationship ; Receptors, Steroid ; agonists ; chemistry ; Small Molecule Libraries ; chemistry ; Static Electricity

Diversity-oriented synthesis (DOS) aims to efficiently generate collections of small molecules with diverse appendages, functional groups, stereochemistry and skeletons, thus yielding diverse biological activities capable of modulating a wide variety of biological processes. In this review, we discussed the common strategies employed in DOS with specific examples from recent literature, including reagent-based approach, substrate-based approach, build-couple-pair strategy and privileged substructure-based DOS. The application of some DOS libraries in drug discovery is also presented.
Drug Design ; Drug Discovery ; Small Molecule Libraries

Primary cilia have critical roles in coordinating multiple cellular signaling pathways. Dysregulation of primary cilia is implicated in various ciliopathies. To identify specific regulators of autophagy, we screened chemical libraries and identified mefloquine, an anti-malaria medicine, as a potent regulator of primary cilia in human retinal pigmented epithelial (RPE) cells. Not only ciliated cells but also primary cilium length was increased in mefloquine-treated RPE cells. Treatment with mefloquine strongly induced the elongation of primary cilia by blocking disassembly of primary cilium. In addition, we found that autophagy was increased in mefloquine-treated cells by enhancing autophagic flux. Both chemical and genetic inhibition of autophagy suppressed ciliogenesis in mefloquine-treated RPE cells. Taken together, these results suggest that autophagy induced by mefloquine positively regulates the elongation of primary cilia in RPE cells.
Autophagy* ; Cilia* ; Humans ; Mefloquine ; Retinaldehyde ; Small Molecule Libraries

PURPOSE: Proprotein convertase subtilisin/kexin type 9 (PCSK9) binds to the low density lipoprotein receptor (LDLR) and promotes degradation of the LDLR. Inhibition of PCSK9 either by reducing its expression or by blocking its activity results in the upregulation of the LDLR and subsequently lowers the plasma concentration of LDL-cholesterol. As a modality to inhibit PCSK9 action, we searched the chemical library for small molecules that block the binding of PCSK9 to the LDLR. MATERIALS AND METHODS: We selected 100 chemicals that bind to PCSK9 where the EGF-AB fragment of the LDLR binds via in silico screening of the ChemBridge chemical library, using the computational GOLD algorithm analysis. Effects of chemicals were evaluated using the PCSK9-LDLR binding assay, immunoblot analysis, and the LDL-cholesterol uptake assay in vitro, as well as the fast performance liquid chromatography assay for plasma lipoproteins in vivo. RESULTS: A set of chemicals were found that decreased the binding of PCSK9 to the EGF-AB fragment of the LDLR in a dose-dependent manner. They also increased the amount of the LDLR significantly and subsequently increased the uptake of fluorescence-labeled LDL in HepG2 cells. Additionally, one particular molecule lowered the plasma concentration of total cholesterol and LDL-cholesterol significantly in wild-type mice, while such an effect was not observed in Pcsk9 knockout mice. CONCLUSION: Our findings strongly suggest that in silico screening of small molecules that inhibit the protein-protein interaction between PCSK9 and the LDLR is a potential modality for developing hypercholesterolemia therapeutics.
Animals ; Cholesterol/*blood ; Cholesterol, LDL/blood ; Hep G2 Cells ; Humans ; Mice ; Mice, Knockout ; Proprotein Convertases/*metabolism ; Receptors, LDL/*metabolism ; Serine Endopeptidases/*metabolism ; *Small Molecule Libraries

Drug Evaluation, Preclinical ; methods ; Humans ; Intracellular Signaling Peptides and Proteins ; metabolism ; Protein Binding ; drug effects ; Small Molecule Libraries ; chemistry ; pharmacology ; Transcription Factors ; metabolism ; Tumor Suppressor Proteins ; metabolism

Coculture Techniques ; Hematopoietic Stem Cells ; cytology ; Humans ; Small Molecule Libraries

As an extension of the structure-based drug discovery, fragment-based drug discovery is matured increasingly, and plays an important role in drug development. Fragments in a small library, with lower molecular mass and high "ligand efficiency", are detected by SPR, MS, NMR, X-ray crystallography technologies and other biophysical methods. Then they are considered as starting points for chemical optimization with the guidance of structural biology methods to get good "drug-like" lead and candidate compounds. In this article, we reviewed the current progress of fragment-based drug discovery and detailed a number of examples to illustrate the novel strategies.
Computer-Aided Design ; Crystallography, X-Ray ; Drug Discovery ; methods ; Ligands ; Magnetic Resonance Spectroscopy ; Peptide Fragments ; chemical synthesis ; chemistry ; Protein Conformation ; Small Molecule Libraries ; Surface Plasmon Resonance