Target Prediction of 5,10,15,20-Tetrakis(4'-Sulfonatophenyl)-Porphyrin Using Molecular Docking

Photodegradation of psychotropic medications: Impact on efficacy, safety, and drug properties

Antipsychotics and antidepressants are essential psychotropic medications used for treating various mental health conditions such as depression, schizophrenia, and bipolar disorder. However, when exposed to light, these compounds are susceptible to photodegradation, potentially changing their biological activity and safety profiles. This study evaluates the pharmacokinetic and pharmacodynamic properties of several photoproducts derived from 13 psychotropic drugs. We used computational methods to predict the biological activity, toxicity, and drug-like properties of the photoproducts. Our results indicate that photoproducts such as amisulpride_TP166, TP246, quetiapine_D4, and quetiapine_PH1 show enhanced biological affinity and ADME-Tox profiles similar to their parent compounds, suggesting possible therapeutic advantages in their interaction with targeted receptors. However, some of the photocompounds exhibit lower predicted binding affinities when interacting with those receptors compared to their parent compounds, indicating a possible loss of function. These findings emphasize the need for further investigation into the effects and safety of drug photoproducts, particularly in the context of long-term pharmacotherapy.

Enhanced Binding Site Identification in Protein-Ligand Complexes with a Combined Blind Docking and Dipolar Electron Paramagnetic Resonance Approach

Understanding protein-drug complex structures is crucial for elucidating therapeutic mechanisms and side effects. Blind docking facilitates site identification but is hindered by computational complexity and imprecise scoring, causing ambiguity. Dipolar electron paramagnetic resonance (EPR) provides spin-spin distances but struggles to determine relative positions within complexes. We present a novel approach combining GPU-accelerated blind docking with EPR distance constraints to enhance binding site detection. Our algorithm uses a single EPR distance distribution to filter and validate docking results. Ligand poses from blind docking are clustered, filtered by expected distances, and refined through focused docking. To illustrate our approach, we investigated human serum albumin binding with porphyrin-based photosensitizers used in photodynamic therapy. Combining docking and EPR, we identified possible binding sites, demonstrating that EPR data significantly reduce possible configurations and provide experimentally validated information. This strategy produces a detailed map of photoligand binding sites, revealing that binding may occur away from standard albumin sites and often involves multiple locations. Furthermore, it overcomes key limitations of fluorescence-based methods, which are prone to misinterpretation in albumin studies due to non one-to-one donor-acceptor relationships. By resolving ambiguities in both blind docking and EPR, our framework provides a versatile platform for investigating EPR-active ligands.

Construction of Photosensitizer Candidates in Photodynamic Therapy: Computer Aided Design, Calculation, and Screening

Thiophene and pyrrole units are extensively utilized in light-responsive materials and have significantly advanced the field of organic photovoltaics (OPV). This progress has inspired our exploration of photosensitizers (PS) for photodynamic therapy (PDT). Currently, traditional PS face limitations in clinical application, including a restricted variety and narrow applicability. Drawing upon molecular design concepts from OPV, we aim to transcend these limitations in PDT. Given the abundance of candidate molecules, effective screening is crucial. Theoretical calculations and electronic structure analyses serve as precise and practical screening methods. In this study, we adopted strategies successfully employed in OPV molecular design, focusing on donor-acceptor (D-A) and acceptor-donor-acceptor (A-D-A) structures. Using density functional theory (DFT) and time-dependent density functional theory (TDDFT), we systematically designed combinations of promising organic fragments. These fragments include polythiophene and polypyrrole-dominated donor structures, paired with five electron acceptors: indene (Ind), diketopyrrole (DPP), naphthalimide (Ni), benzothiazole (Btd), and dithiazolyl diketopyrrole (Tbo). Through meticulous calculations, we obtained electronic structures and spectral properties for all candidate molecules, facilitating an efficient screening process. Our findings highlight that those combinations of polypyrrole-based frameworks with DPP, Ni, and Btd show significant promise for PS applications. Approximately 13% of candidates were selected through comprehensive comparison, markedly reducing molecular design time and experimental costs. This interdisciplinary approach holds potential to pave the way for more targeted and successful PS designs.

Metabolomics-driven approaches for identifying therapeutic targets in drug discovery

Identification of therapeutic targets can directly elucidate the mechanism and effect of drug therapy, which is a central step in drug development. The disconnect between protein targets and phenotypes under complex mechanisms hampers comprehensive target understanding. Metabolomics, as a systems biology tool that captures phenotypic changes induced by exogenous compounds, has emerged as a valuable approach for target identification. A comprehensive overview was provided in this review to illustrate the principles and advantages of metabolomics, delving into the application of metabolomics in target identification. This review outlines various metabolomics-based methods, such as dose-response metabolomics, stable isotope-resolved metabolomics, and multiomics, which identify key enzymes and metabolic pathways affected by exogenous substances through dose-dependent metabolite-drug interactions. Emerging techniques, including single-cell metabolomics, artificial intelligence, and mass spectrometry imaging, are also explored for their potential to enhance target discovery. The review emphasizes metabolomics' critical role in advancing our understanding of disease mechanisms and accelerating targeted drug development, while acknowledging current challenges in the field.

Porphyrin photosensitizer molecules as effective medicine candidates for photodynamic therapy: electronic structure information aided design

Traditional photosensitizers (PS) in photodynamic therapy (PDT) have restricted tissue penetrability of light and a lack of selectivity for tumor cells, which diminishes the efficiency of PDT. Our aim is to effectively screen porphyrin-based PS medication through computational simulations of large-scale design and screening of PDT candidates via a precise description of the state of the light-stimulated PS molecule. Perylene-diimide (PDI) shows an absorption band in the near-infrared region (NIR) and a great photostability. Meanwhile, the insertion of metal can enhance tumor targeting. Therefore, on the basis of the original porphyrin PS segments, a series of metalloporphyrin combined with PDI and additional allosteric Zn-porphyrin-PDI systems were designed and investigated. Geometrical structures, frontier molecular orbitals, ultraviolet-visible (UV-vis) absorption spectra, adiabatic electron affinities (AEA), especially the triplet excited states and spin-orbit coupling matrix elements (SOCME) of these expanded D-A porphyrin were studied in detail using the density functional theory (DFT) and time-dependent density functional theory (TDDFT) methods. PS candidates, conforming type I or II mechanism for PDT, have been researched carefully by molecular docking which targeted Factor-related apoptosis (Fas)/Fas ligand (Fasl) mediated signaling pathway. It was found that porphyrin-PDI, Fe2-porphyrin-PDI, Zn-porphyrin-PDI, Mg-porphyrin-PDI, Zn-porphyrin combined with PDI through single bond (compound 1), and two acetylenic bonds (compound 2) in this work would be proposed as potential PS candidates for PDT process. This study was expected to provide PS candidates for the development of novel medicines in PDT.

Structural basis of antibacterial photodynamic action of curcumin against S. aureus

Antimicrobial photodynamic therapy (aPDT) is an alternative tool to commercial antibiotics for the inactivation of pathogenic bacteria (e.g., S. aureus). However, there is still a lack of understanding of the molecular modeling of the photosensitizers and their mechanism of action through oxidative pathways. Herein, a combined experimental and computational evaluation of curcumin as a photosensitizer against S. aureus was performed. The radical forms of keto-enol tautomers and the energies of curcumin's frontier molecular orbitals were evaluated by density functional theory (DFT) to point out the photodynamic action as well as the photobleaching process. Furthermore, the electronic transitions of curcumin keto-enol tautomers were undertaken to predict the transitions as a photosensitizer during the antibacterial photodynamic process. Moreover, molecular docking was used to evaluate the binding affinity with the S. aureus tyrosyl-tRNA synthetase as the proposed a target for curcumin. In this regard, the molecular orbital energies show that the curcumin enol form has a character of 4.5% more basic than the keto form - the enol form is a more promising electron donor than its tautomer. Curcumin is a strong electrophile, with the enol form being 4.6% more electrophilic than its keto form. In addition, the regions susceptible to nucleophilic attack and photobleaching were evaluated by the Fukui function. Regarding the docking analysis, the model suggested that four hydrogen bonds contribute to the binding energy of curcumin's interaction with the ligand binding site of S. aureus tyrosyl-tRNA synthetase. Finally, residues Tyr36, Asp40, and Asp177 contact curcumin and may contribute to orienting the curcumin in the active area. Moreover, curcumin presented a photoinactivation of 4.5 log unit corroborating the necessity of the combined action of curcumin, light, and O2 to promote the photooxidation damage of S. aureus. These computational and experimental data suggest insights regarding the mechanism of action of curcumin as a photosensitizer to inactivate S. aureus bacteria.

Bioinformatics Tools for the Analysis of Active Compounds Identified in Ranunculaceae Species

The chemical compounds from extracts of three Ranunculaceae species, Aconitum toxicum Rchb., Anemone nemorosa L. and Helleborus odorus Waldst. & Kit. ex Willd., respectively, were isolated using the HPLC purification technique and analyzed from a bioinformatics point of view. The classes of compounds identified based on the proportion in the rhizomes/leaves/flowers used for microwave-assisted extraction and ultrasound-assisted extraction were alkaloids and phenols. Here, the quantifying of pharmacokinetics, pharmacogenomics and pharmacodynamics helps us to identify the actual biologically active compounds. Our results showed that (i) pharmacokinetically, the compounds show good absorption at the intestinal level and high permeability at the level of the central nervous system for alkaloids; (ii) regarding pharmacogenomics, alkaloids can influence tumor sensitivity and the effectiveness of some treatments; (iii) and pharmacodynamically, the compounds of these Ranunculaceae species bind to carbonic anhydrase and aldose reductase. The results obtained showed a high affinity of the compounds in the binding solution at the level of carbonic anhydrases. Carbonic anhydrase inhibitors extracted from natural sources can represent the path to new drugs useful both in the treatment of glaucoma, but also of some renal, neurological and even neoplastic diseases. The identification of natural compounds with the role of inhibitors can have a role in different types of pathologies, both associated with studied and known receptors such as carbonic anhydrase and aldose reductase, as well as new pathologies not yet addressed.