Plant Secondary Metabolites as Modulators of Mitochondrial Health: An Overview of Their Anti-Oxidant, Anti-Apoptotic, and Mitophagic Mechanisms

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(1), P. 380 - 380

Published: Jan. 4, 2025

Plant secondary metabolites (PSMs) are a diverse group of bioactive compounds, including flavonoids, polyphenols, saponins, and terpenoids, which have been recognised for their critical role in modulating cellular functions. This review provides comprehensive analysis the effects PSMs on mitochondrial health, with particular emphasis therapeutic potential. Emerging evidence shows that these improve function by reducing oxidative stress, promoting biogenesis, regulating key processes such as apoptosis mitophagy. Mitochondrial dysfunction, hallmark many pathologies, neurodegenerative disorders, cardiovascular diseases, metabolic syndrome, has shown to benefit from protective PSMs. Recent studies show can dynamics, stabilise membranes, enhance bioenergetics, offering significant promise prevention treatment mitochondrial-related diseases. The molecular mechanisms underlying effects, modulation signalling pathways direct interactions proteins, discussed. integration into strategies is highlighted promising avenue improving efficacy while minimising side commonly associated synthetic drugs. also highlights need future research elucidate specific roles individual synergistic within complex plant matrices, may further optimise utility. Overall, this work valuable insights health potential natural agents targeting dysfunction.

Language: Английский

---

Deep Eutectic Solvents Enhancing Drug Solubility and Its Delivery

Journal of Medicinal Chemistry, Journal Year: 2024, Volume and Issue: 67(17), P. 14807 - 14819

Published: Aug. 26, 2024

Deep eutectic solvents (DES) are environmentally friendly with the potential to dissolve bioactive compounds without affecting their characteristics. DES has special qualities that can be customized meet unique characteristics of a biomolecule/active pharmaceutical ingredient (API) in accordance various therapeutic needs, providing reliable approach opening door for creation cutting-edge drug formulations by resolving solubility issues pharmaceutics. This study outlines newly developing approaches solve problem inefficient API extraction due poor solubility. These emerging strategies also have capacity alter chemical and physical stability API, which triggers drug's shelf life possible health benefits. It is anticipated highlighted methods processes will developed capitalize on improve delivery sector.

Language: Английский

---

Prioritizing Computational Cocrystal Prediction Methods for Experimental Researchers: A Review to Find Efficient, Cost-Effective, and User-Friendly Approaches

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(22), P. 12045 - 12045

Published: Nov. 9, 2024

Pharmaceutical cocrystals offer a versatile approach to enhancing the properties of drug compounds, making them an important tool in formulation and development by improving therapeutic performance patient experience pharmaceutical products. The prediction involves using computational theoretical methods identify potential cocrystal formers understand interactions between active ingredient coformers. This process aims predict whether two or more molecules can form stable structure before performing experimental synthesis, thus saving time resources. In this review, commonly used are first overviewed then evaluated based on three criteria: efficiency, cost-effectiveness, user-friendliness. Based these considerations, we suggest researchers without strong experiences which tools should be tested as step workflow rational design cocrystals. However, optimal choice depends specific needs resources, combining from different categories powerful approach.

Language: Английский

---

Navigating Solid-Form Screening Using In Silico Methods Validated with Experimental Data for a Drug-like Molecule

Crystal Growth & Design, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

Language: Английский

---

Prediction of drug solubility in polymer with COSMO-SAC

Journal of the Taiwan Institute of Chemical Engineers, Journal Year: 2025, Volume and Issue: 173, P. 106177 - 106177

Published: May 16, 2025

Language: Английский

---

In silico cocrystal screening using COSMO-RS: A rapid and efficient approach for solubility prediction and crystal engineering

Journal of Molecular Liquids, Journal Year: 2025, Volume and Issue: unknown, P. 127841 - 127841

Published: June 1, 2025

Language: Английский

---

Economic Analysis of Battery Energy Storage Integration in a 100MW Solar Farm Using PVsyst and SAM

Published: April 3, 2024

The adoption of solar photovoltaic (PV) systems has seen a surge as the world shifts towards renewable energy sources (RES). Solar farms have gained interest for their environmental benefits. To optimize these farms, integrating PV with battery storage (BESS) become essential. This paper conducts comprehensive economic analysis 100 MW DC farm in Chicago 4-hour BESS using PVsyst and System Advisor Model (SAM). study provides benefits drawbacks this integration by considering technological factors. outcomes aim to reaffirm viability from both technical standpoints, providing substantial outputs while outlining critical financial factors stakeholders sector. Analysis simulation results presents an output 153.58 GWh per year payback period 13 years. When peak demand price escalation are included, is reduced 11.7 emphasizes such shift. comparative research shows cost implications varied times associated incorporating into layouts, offering significant insights issues decision-making industry. Additionally, it anticipated that will yield benefits, estimated save 2 million tons CO2e emissions over its lifespan, equating annual reduction 64,337 metric CO2e.

Language: Английский

---

Deep Supramolecular Language Processing for Co-crystal Prediction

Published: June 18, 2024

Approximately 40% of marketed drugs exhibit suboptimal pharmacokinetic profiles. Co-crystallization, where pairs molecules form a multicomponent crystal, constitutes promising strategy to enhance physicochemical properties without compromising the pharmacological activity. However, finding co-crystal is resource-intensive, due vast number possible combinations. We present DeepCocrystal, novel deep learning approach designed predict formation by processing 'chemical language' from supramolecular vantage point. Rigorous validation DeepCocrystal showed balanced accuracy 78% in realistic scenarios, outperforming existing models. By leveraging molecular string representations, can also estimate uncertainty its predictions. harness this capability challenging prospective study, and successfully discovered two diflunisal, an anti-inflammatory drug. This study underscores potential -- particular chemical language accelerate co-crystallization, ultimately drug development, both academic industrial contexts.

Language: Английский

---

Pyridine derivatives sublimation processes: Fundamental aspects and application for two-component crystals screening

Physical Chemistry Chemical Physics, Journal Year: 2024, Volume and Issue: 26(34), P. 22558 - 22571

Published: Jan. 1, 2024

The saturated vapour pressures of five heterocyclic compounds containing the pyridine fragment, namely, three isomers aminopyridine (2-aminopyridine (2AmPy), 3-aminopyridine (3AmPy), and 4-aminopyridine (4AmPy)); 3-hydroxypyridine (3OHPy) 2-(1

Language: Английский

---

Charge balanced aggregation: A universal approach to aqueous organic nanocrystals

Journal of Controlled Release, Journal Year: 2024, Volume and Issue: 375, P. 552 - 573

Published: Sept. 21, 2024

Language: Английский

---