Medical research is at the forefront of addressing pressing global challenges, including preventing and treating cardiovascular, autoimmune, and oncological diseases, neurodegenerative disorders, and the growing resistance of pathogens to antibiotics. Understanding the molecular mechanisms underlying these diseases, using advanced medical approaches and cutting-edge technologies, structure-based drug design, and personalized medicine, is critical for developing effective therapies, specifically anticancer treatments. Background/Objectives: One of the key drivers of cancer at the cellular level is the abnormal activity of protein enzymes, specifically serine, threonine, or tyrosine residues, through a process known as phosphorylation. While tyrosine kinase-mediated phosphorylation constitutes a minor fraction of total cellular phosphorylation, its dysregulation is critically linked to carcinogenesis and tumor progression. Methods: Small-molecule inhibitors, such as imatinib or erlotinib, are designed to halt this process, restoring cellular equilibrium and offering targeted therapeutic approaches. However, challenges persist, including frequent drug resistance and severe side effects associated with these therapies. Nanomedicine offers a transformative potential to overcome these limitations. Results: By leveraging the unique properties of nanomaterials, it is possible to achieve precise drug delivery, enhance accumulation at target sites, and improve therapeutic efficacy. Examples include nanoparticle-based delivery systems for TKIs and the combination of nanomaterials with photothermal or photodynamic therapies to enhance treatment effectiveness. Combining nanomedicine with traditional treatments holds promise and perspective for synergistic and more effective cancer management. Conclusions: This review delves into recent advances in understanding tyrosine kinase activity, the mechanisms of their inhibition, and the innovative integration of nanomedicine to revolutionize cancer treatment strategies.
- Publication type
- Journal Article MeSH
- Review MeSH
Periodontitis is a globally prevalent chronic inflammatory disease that leads to periodontal pocket formation and eventually destroys tooth-supporting structures. Hence, the drastic increase in dental implants for periodontitis has become a severe clinical issue. Injectable hydrogel based on extracellular matrix (ECM) is highly biocompatible and tissue-regenerative with tailor-made mechanical properties and high payload capacity for in situ delivery of bioactive molecules to treat periodontitis. This therapeutic tool not only enhances the drug release efficiency and treatment efficacy but also reduces operation time. Nevertheless, it remains challenging to optimize the mechanical properties and intelligent control drug release rate of injectable hydrogels to achieve the highest therapeutic outcome. Literature precedent has shown the modulation of polymer backbones (synthetic polymers, natural polysaccharides, and proteins), crosslinking strategies, other bioactive constituents, and potentially the incorporation of nanomaterials that overall improve the desirable physiochemical and biological performances as well as biodegradability. In this review, we summarize the recent advances in the development, design, and material characterizations of common injectable hydrogels. Furthermore, we highlight cutting-edge representative examples of polysaccharide-, protein- and nanocomposite-based hydrogels that mediate regenerative factors and anti-inflammatory drugs for periodontal regeneration. Finally, we express our perspectives on potential challenges and future development of multifunctional injectable hydrogels for periodontitis.
- Publication type
- Journal Article MeSH
- Review MeSH
The Takeda G protein-coupled receptor 5 (TGR5), also known as GPBAR1 (G protein-coupled bile acid receptor), is a membrane-type bile acid receptor that regulates blood glucose levels and energy expenditure. These essential functions make TGR5 a promising target for the treatment of type 2 diabetes and metabolic disorders. Currently, most research on developing TGR5 agonists focuses on modifying the structure of bile acids, which are the endogenous ligands of TGR5. However, TGR5 agonists with nonsteroidal structures have not been widely explored. This study aimed at discovering new TGR5 agonists using bile acid derivatives as a basis for a computational approach. We applied a combination of pharmacophore-based, molecular docking, and molecular dynamic (MD) simulation to identify potential compounds as new TGR5 agonists. Through pharmacophore screening and molecular docking, we identified 41 candidate compounds. From these, five candidates were selected based on criteria including pharmacophore features, a docking score of less than 9.2 kcal/mol, and similarity in essential interaction patterns with a reference ligand. Biological assays of the five hits confirmed that Hit-3 activates TGR5 similarly to the bile acid control. This was supported by MD simulation results, which indicated that a hydrogen bond interaction with Tyr240 is involved in TGR5 activation. Hit-3 (CSC089939231) represents a new nonsteroidal lead that can be further optimized to design potent TGR5 agonists.
- MeSH
- Humans MeSH
- Ligands MeSH
- Molecular Structure MeSH
- Drug Discovery MeSH
- Receptors, G-Protein-Coupled * agonists metabolism MeSH
- Molecular Dynamics Simulation * MeSH
- Molecular Docking Simulation * MeSH
- Structure-Activity Relationship MeSH
- Bile Acids and Salts chemistry metabolism pharmacology MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.
- MeSH
- Pharmaceutical Preparations chemistry MeSH
- Drug Delivery Systems methods MeSH
- Humans MeSH
- Lipids * chemistry MeSH
- Nanoparticles chemistry MeSH
- Drug Carriers chemistry MeSH
- Computer Simulation MeSH
- Molecular Dynamics Simulation * MeSH
- Machine Learning MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Amphotericin B (AmB) is one of the most effective antifungal drugs, with a strong, dose-dependent activity against most Candida and Aspergillus species responsible for life-threatening infections. However, AmB is severely toxic, which hinders its broad use. In this proof-of-concept study, we demonstrate that prodrugging AmB considerably decreases AmB toxicity without affecting its fungicidal activity. For this purpose, we modified the AmB structure by attaching a designer phosphate promoiety, thereby switching off its mode of action and preventing its toxic effects. The original fungicidal activity of AmB was then restored upon prodrug activation by host plasma enzymes. These AmB prodrugs showed a safer toxicity profile than commercial AmB deoxycholate in Candida and Aspergillus species and significantly prolonged larval survival of infected Galleria mellonella larvae. Based on these findings, prodrugging toxic antifungals may be a viable strategy for broadening the antifungal arsenal, opening up opportunities for targeted prodrug design.
- MeSH
- Amphotericin B * pharmacology MeSH
- Antifungal Agents * pharmacology chemistry chemical synthesis MeSH
- Aspergillus drug effects MeSH
- Candida drug effects MeSH
- Larva drug effects MeSH
- Microbial Sensitivity Tests * MeSH
- Molecular Structure MeSH
- Moths drug effects MeSH
- Prodrugs * pharmacology chemistry chemical synthesis MeSH
- Dose-Response Relationship, Drug MeSH
- Structure-Activity Relationship MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
Mechanismus účinku většiny léčiv je založen na jejich interakci s molekulovými cíli v organismu, tj. biologickými makromolekulami, jako jsou proteiny nebo nukleové kyseliny. Mezi faktory ovlivňující sílu navázání molekuly léčiva na jeho biologický cíl patří celkový počet interakcí, jejich charakter a z něj vyplývající energie vazby. Hodnota energie vazby je zásadním parametrem pro odhad síly interakce. Základní typy těchto intermolekulárních interakcí jsou v přehledovém článku definovány, schematicky znázorněny a doplněny údaji o energii vazby. Dále jsou uvedeny další aspekty navazování léčiv na molekulové cíle, např. solvatace molekul ve vodném pro středí nebo vzdálenost interagujících chemických funkčních skupin. Znalost struktur molekulárních cílů i díky úspěchu současných modelů nám umožňuje tyto interakce využívat pro návrh nových léčiv.
The mechanism of action of most drugs is based on their interaction with molecular targets in the organism, i.e., biological macromolecules such as proteins or nucleic acids. Factors influencing the strength of binding of a drug molecule to its biological target include the total number of interactions, their character, and the resulting binding energy. The value of binding energy is an essential parameter for estimating the strength of the interaction. The basic types of these intermolecular interactions are defined, schematically illustrated, and supported with data on binding energy in this review article. Other aspects of drug binding to molecular targets are also presented, e.g., the solvation of molecules in aqueous environment or the distance of interacting chemical functional groups. Knowledge of the structures of molecular targets and the progress of current models allows us to use these interactions to design new drugs.
Recent advancements in deep learning and generative models have significantly expanded the applications of virtual screening for drug-like compounds. Here, we introduce a multitarget transformer model, PCMol, that leverages the latent protein embeddings derived from AlphaFold2 as a means of conditioning a de novo generative model on different targets. Incorporating rich protein representations allows the model to capture their structural relationships, enabling the chemical space interpolation of active compounds and target-side generalization to new proteins based on embedding similarities. In this work, we benchmark against other existing target-conditioned transformer models to illustrate the validity of using AlphaFold protein representations over raw amino acid sequences. We show that low-dimensional projections of these protein embeddings cluster appropriately based on target families and that model performance declines when these representations are intentionally corrupted. We also show that the PCMol model generates diverse, potentially active molecules for a wide array of proteins, including those with sparse ligand bioactivity data. The generated compounds display higher similarity known active ligands of held-out targets and have comparable molecular docking scores while maintaining novelty. Additionally, we demonstrate the important role of data augmentation in bolstering the performance of generative models in low-data regimes. Software package and AlphaFold protein embeddings are freely available at https://github.com/CDDLeiden/PCMol.
- MeSH
- Protein Conformation MeSH
- Ligands MeSH
- Models, Molecular * MeSH
- Proteins * chemistry metabolism MeSH
- Drug Design * MeSH
- Publication type
- Journal Article MeSH
Lens epithelium-derived growth factor p75 (LEDGF/p75), member of the hepatoma-derived growth-factor-related protein (HRP) family, is a transcriptional co-activator and involved in several pathologies including HIV infection and malignancies such as MLL-rearranged leukemia. LEDGF/p75 acts by tethering proteins to the chromatin through its integrase binding domain. This chromatin interaction occurs between the PWWP domain of LEDGF/p75 and nucleosomes carrying a di- or trimethylation mark on histone H3 Lys36 (H3K36me2/3). Our aim is to rationally devise small molecule drugs capable of inhibiting such interaction. To bootstrap this development, we resorted to X-ray crystallography-based fragment screening (FBS-X). Given that the LEDGF PWWP domain crystals were not suitable for FBS-X, we employed crystals of the closely related PWWP domain of paralog HRP-2. As a result, as many as 68 diverse fragment hits were identified, providing a detailed sampling of the H3K36me2/3 pocket pharmacophore. Subsequent structure-guided fragment expansion in three directions yielded multiple compound series binding to the pocket, as verified through X-ray crystallography, nuclear magnetic resonance and differential scanning fluorimetry. Our best compounds have double-digit micromolar affinity and optimally sample the interactions available in the pocket, judging by the Kd-based ligand efficiency exceeding 0.5 kcal/mol per non-hydrogen atom. Beyond π-stacking within the aromatic cage of the pocket and hydrogen bonding, the best compounds engage in a σ-hole interaction between a halogen atom and a conserved water buried deep in the pocket. Notably, the binding pocket in LEDGF PWWP is considerably smaller compared to the related PWWP1 domains of NSD2 and NSD3 which feature an additional subpocket and for which nanomolar affinity compounds have been developed recently. The absence of this subpocket in LEDGF PWWP limits the attainable affinity. Additionally, these structural differences in the H3K36me2/3 pocket across the PWWP domain family translate into a distinct selectivity of the compounds we developed. Our top-ranked compounds are interacting with both homologous LEDGF and HRP-2 PWWP domains, yet they showed no affinity for the NSD2 PWWP1 and BRPF2 PWWP domains which belong to other PWWP domain subfamilies. Nevertheless, our developed compound series provide a strong foundation for future drug discovery targeting the LEDGF PWWP domain as they can further be explored through combinatorial chemistry. Given that the affinity of H3K36me2/3 nucleosomes to LEDGF/p75 is driven by interactions within the pocket as well as with the DNA-binding residues, we suggest that future compound development should target the latter region as well. Beyond drug discovery, our compounds can be employed to devise tool compounds to investigate the mechanism of LEDGF/p75 in epigenetic regulation.
- MeSH
- Small Molecule Libraries chemistry pharmacology chemical synthesis MeSH
- Crystallography, X-Ray MeSH
- Humans MeSH
- Intercellular Signaling Peptides and Proteins metabolism chemistry MeSH
- Models, Molecular MeSH
- Molecular Structure MeSH
- Protein Domains MeSH
- Drug Design * MeSH
- Dose-Response Relationship, Drug MeSH
- Structure-Activity Relationship MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
This review comprehensively summarizes recent advances in the field of hydrazinecarboxamide (semicarbazide) derivatives, highlighting their significant therapeutic potential and a broad spectrum of biological activities. As a promising and privileged scaffold in medicinal chemistry, hydrazinecarboxamides have emerged as a versatile class of compounds with significant bioactive properties. Based on their substitutions, their structural diversity permits extensive chemical modifications to enhance their interactions with various biological targets to combat multiple disorders. Notable, this group of compounds has shown significant efficacy against numerous cancer cell lines through diverse mechanisms of action and potent inhibition of enzymes, including cholinesterases, carbonic anhydrases, cyclooxygenases, lipoxygenases, etc. Beyond these, they have also been investigated for their anticonvulsive, analgesic/anti-inflammatory, and antioxidant properties, with detailed structure-activity relationships. For many applications, the hybridization of hydrazinecarboxamides with other bioactive scaffolds, such as primaquine, is of particular interest and offers advantages. Despite their promises, challenges such as suboptimal physicochemical properties and selectivity issues of certain derivatives require further effort. The review aims to inspire future innovation in the design and development of new potential hydrazinecarboxamide-based drugs, addressing existing challenges and expanding their therapeutic applications.
- MeSH
- Anti-Inflammatory Agents pharmacology chemistry MeSH
- Anticonvulsants * pharmacology chemistry MeSH
- Antioxidants * pharmacology chemistry MeSH
- Hydrazines * chemistry pharmacology chemical synthesis MeSH
- Enzyme Inhibitors pharmacology chemistry chemical synthesis MeSH
- Humans MeSH
- Molecular Structure MeSH
- Antineoplastic Agents * pharmacology chemistry MeSH
- Semicarbazides chemical synthesis chemistry pharmacology MeSH
- Structure-Activity Relationship MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
The insulin-linked polymorphic region is a variable number of tandem repeats region of DNA in the promoter of the insulin gene that regulates transcription of insulin. This region is known to form the alternative DNA structures, i-motifs and G-quadruplexes. Individuals have different sequence variants of tandem repeats and although previous work investigated the effects of some variants on G-quadruplex formation, there is not a clear picture of the relationship between the sequence diversity, the DNA structures formed, and the functional effects on insulin gene expression. Here we show that different sequence variants of the insulin linked polymorphic region form different DNA structures in vitro. Additionally, reporter genes in cellulo indicate that insulin expression may change depending on which DNA structures form. We report the crystal structure and dynamics of an intramolecular i-motif, which reveal sequences within the loop regions forming additional stabilising interactions that are critical to formation of stable i-motif structures. The outcomes of this work reveal the detail in formation of stable i-motif DNA structures, with potential for rational based drug design for compounds to target i-motif DNA.
- MeSH
- DNA * chemistry genetics MeSH
- G-Quadruplexes * MeSH
- Insulin * chemistry genetics MeSH
- Nucleic Acid Conformation MeSH
- Crystallography, X-Ray MeSH
- Humans MeSH
- Models, Molecular MeSH
- Nucleotide Motifs MeSH
- Polymorphism, Genetic MeSH
- Promoter Regions, Genetic * MeSH
- Genes, Reporter MeSH
- Base Sequence MeSH
- Tandem Repeat Sequences genetics MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
