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Journal of Chromatography. A Oct 2023The value of the concept of retention indices (RI) to the practice of gas chromatography (GC) is highlighted, where the RI of a compound is one component of the strategy... (Review)
Review
The value of the concept of retention indices (RI) to the practice of gas chromatography (GC) is highlighted, where the RI of a compound is one component of the strategy to identify the compound. The widespread reliance on GC and then on mass spectrometry for 'identification', may result in inadequate confirmation of molecular identity. However, RI do provide a useful tentative indication of the possible molecule(s). Thus, the RI value is a useful first measure of the molecule identity, and shown here to be valuable provided limitations are recognised. An author has a responsibility to correctly calculate the index and then use the values for (tentative) identification. Tables of reference RI values are useful in this respect, but finding an 'exact match' RI value does not confirm the identity. Hence, it is necessary to understand how the RI value may be incorrectly used in this respect. The reviewer of written research is charged with ensuring the index values are applied in a rigorous manner. Selected case studies from our own work, support the care that must be exercised when reporting RI values. In terms of advanced GC operations, mention is made of multidimensional gas chromatography and comprehensive two-dimensional gas chromatography to acquire RI values on both the first and second columns in the two-column separation experiment.
Topics: Gas Chromatography-Mass Spectrometry; Mass Spectrometry; Reference Values
PubMed: 37717451
DOI: 10.1016/j.chroma.2023.464376 -
Pharmaceutics Apr 2022Hyaluronic acid (HA) has a special position among glycosaminoglycans. As a major component of the extracellular matrix (ECM). This simple, unbranched polysaccharide is... (Review)
Review
Hyaluronic acid (HA) has a special position among glycosaminoglycans. As a major component of the extracellular matrix (ECM). This simple, unbranched polysaccharide is involved in the regulation of various biological cell processes, whether under physiological conditions or in cases of cell damage. This review summarizes the history of this molecule's study, its distinctive metabolic pathway in the body, its unique properties, and current information regarding its interaction partners. Our main goal, however, is to intensively investigate whether this relatively simple polymer may find applications in protecting against ionizing radiation (IR) or for therapy in cases of radiation-induced damage. After exposure to IR, acute and belated damage develops in each tissue depending upon the dose received and the cellular composition of a given organ. A common feature of all organ damage is a distinct change in composition and structure of the ECM. In particular, the important role of HA was shown in lung tissue and the variability of this flexible molecule in the complex mechanism of radiation-induced lung injuries. Moreover, HA is also involved in intermediating cell behavior during morphogenesis and in tissue repair during inflammation, injury, and would healing. The possibility of using the HA polymer to affect or treat radiation tissue damage may point to the missing gaps in the responsible mechanisms in the onset of this disease. Therefore, in this article, we will also focus on obtaining answers from current knowledge and the results of studies as to whether hyaluronic acid can also find application in radiation science.
PubMed: 35456670
DOI: 10.3390/pharmaceutics14040838 -
Biological Research Jul 2019In the growth condition(s) of plants, numerous secondary metabolites (SMs) are produced by them to serve variety of cellular functions essential for physiological... (Review)
Review
In the growth condition(s) of plants, numerous secondary metabolites (SMs) are produced by them to serve variety of cellular functions essential for physiological processes, and recent increasing evidences have implicated stress and defense response signaling in their production. The type and concentration(s) of secondary molecule(s) produced by a plant are determined by the species, genotype, physiology, developmental stage and environmental factors during growth. This suggests the physiological adaptive responses employed by various plant taxonomic groups in coping with the stress and defensive stimuli. The past recent decades had witnessed renewed interest to study abiotic factors that influence secondary metabolism during in vitro and in vivo growth of plants. Application of molecular biology tools and techniques are facilitating understanding the signaling processes and pathways involved in the SMs production at subcellular, cellular, organ and whole plant systems during in vivo and in vitro growth, with application in metabolic engineering of biosynthetic pathways intermediates.
Topics: Cell Culture Techniques; Gene Expression Regulation, Plant; Plant Growth Regulators; Plant Physiological Phenomena; Plant Roots; Plant Shoots; Plants; Secondary Metabolism; Signal Transduction; Stress, Physiological
PubMed: 31358053
DOI: 10.1186/s40659-019-0246-3 -
Journal of Chemical Information and... Oct 2023Computationally generating new synthetically accessible compounds with high affinity and low toxicity is a great challenge in drug design. Machine learning models beyond...
Computationally generating new synthetically accessible compounds with high affinity and low toxicity is a great challenge in drug design. Machine learning models beyond conventional pharmacophoric methods have shown promise in the generation of novel small-molecule compounds but require significant tuning for a specific protein target. Here, we introduce a method called selective iterative latent variable refinement (SILVR) for conditioning an existing diffusion-based equivariant generative model without retraining. The model allows the generation of new molecules that fit into a binding site of a protein based on fragment hits. We use the SARS-CoV-2 main protease fragments from Diamond XChem that form part of the COVID Moonshot project as a reference dataset for conditioning the molecule generation. The SILVR rate controls the extent of conditioning, and we show that moderate SILVR rates make it possible to generate new molecules of similar shape to the original fragments, meaning that the new molecules fit the binding site without knowledge of the protein. We can also merge up to 3 fragments into a new molecule without affecting the quality of molecules generated by the underlying generative model. Our method is generalizable to any protein target with known fragments and any diffusion-based model for molecule generation.
PubMed: 37724771
DOI: 10.1021/acs.jcim.3c00667 -
RSC Advances Jul 2023We present a computational study on the optical absorption properties of some systems of interest in the field of drug delivery. In particular we considered as drug...
We present a computational study on the optical absorption properties of some systems of interest in the field of drug delivery. In particular we considered as drug molecules favipiravir (T705, an antiviral molecule) and 5-fluorouracil (5FU, an anticancer molecule) and, on the other hand, pure fullerenes (C, BN, GaN) and doped fullerenes (CB, CBN) are considered as nanocarriers. Some combined configurations between the drug molecules and the carrier nanostructures have been then studied. The optical absorption properties of the above mentioned drug molecules and their carrier nanostructures in the free and bound states are obtained by a TD-DFT method, in gas phase and in aqueous solution. We perform a detailed analysis of the modifications arising in the absorption spectra that take place in some linked configurations between the drug molecules and the carrier nanostructures. These changes could be of importance as an optical fingerprint of the realized drug/carrier link.
PubMed: 37534260
DOI: 10.1039/d3ra00061c -
Molecules (Basel, Switzerland) Jan 2023In our initial publication on the in vitro testing of more than 200 compounds, we demonstrated that small molecules can inhibit phagocytosis. We therefore theorized that...
In our initial publication on the in vitro testing of more than 200 compounds, we demonstrated that small molecules can inhibit phagocytosis. We therefore theorized that a small molecule drug discovery-based approach to the treatment of immune cytopenias (ITP, AIHA, HTR, DHTR) is feasible. Those earlier studies showed that small molecules with anti-phagocytic groups, such as the pyrazole core, are good models for producing efficacious phagocytosis inhibitors with low toxicity. We recently screened a chemical library of 80 compounds containing pyrazole/isoxazole/pyrrole core structures and found four hit molecules for further follow-up, all having the pyrazole core structure. Subsequent evaluation via MTT viability, LDH release, and apoptosis, led to the selection of two lead compounds with negligible toxicity and high efficacy. In an in vitro assay for inhibition of phagocytosis, their IC values were 2-4 µM. The rational development of these discoveries from hit to lead molecule stage, viz. independent synthesis/scale up of hit molecules, and in vivo activities in mouse models of autoimmune disease, will result in the selection of a lead compound(s) for further pre-clinical evaluation.
Topics: Mice; Animals; Phagocytosis; Drug Discovery; Pyrazoles; Structure-Activity Relationship
PubMed: 36677815
DOI: 10.3390/molecules28020757 -
Angewandte Chemie (International Ed. in... Nov 2020A significant amount of attention has been given to the design and synthesis of co-crystals by both industry and academia because of its potential to change a molecule's...
A significant amount of attention has been given to the design and synthesis of co-crystals by both industry and academia because of its potential to change a molecule's physicochemical properties. Yet, difficulties arise when searching for adequate combinations of molecules (or coformers) to form co-crystals, hampering the efficient exploration of the target's solid-state landscape. This paper reports on the application of a data-driven co-crystal prediction method based on two types of artificial neural network models and co-crystal data present in the Cambridge Structural Database. The models accept pairs of coformers and predict whether a co-crystal is likely to form. By combining the output of multiple models of both types, our approach shows to have excellent performance on the proposed co-crystal training and validation sets, and has an estimated accuracy of 80 % for molecules for which previous co-crystallization data is unavailable.
PubMed: 32797658
DOI: 10.1002/anie.202009467 -
Essays in Biochemistry Dec 2020RNA is crucial for gene expression and regulation. Recent advances in understanding of RNA biochemistry, structure and molecular biology have revealed the importance of... (Review)
Review
RNA is crucial for gene expression and regulation. Recent advances in understanding of RNA biochemistry, structure and molecular biology have revealed the importance of RNA structure in cellular processes and diseases. Various approaches to discovering drug-like small molecules that target RNA structure have been developed. This review provides a brief introduction to RNA structural biology and how RNA structures function as disease regulators. We summarize approaches to targeting RNA with small molecules and highlight their advantages, shortcomings and therapeutic potential.
Topics: Disease; Drug Design; Drug Discovery; Drug Evaluation, Preclinical; High-Throughput Screening Assays; Humans; Molecular Docking Simulation; Molecular Targeted Therapy; RNA; Small Molecule Libraries
PubMed: 33078198
DOI: 10.1042/EBC20200011 -
Bioinformatics (Oxford, England) Jun 2023Deep learning-based molecule generation becomes a new paradigm of de novo molecule design since it enables fast and directional exploration in the vast chemical space....
MOTIVATION
Deep learning-based molecule generation becomes a new paradigm of de novo molecule design since it enables fast and directional exploration in the vast chemical space. However, it is still an open issue to generate molecules, which bind to specific proteins with high-binding affinities while owning desired drug-like physicochemical properties.
RESULTS
To address these issues, we elaborate a novel framework for controllable protein-oriented molecule generation, named CProMG, which contains a 3D protein embedding module, a dual-view protein encoder, a molecule embedding module, and a novel drug-like molecule decoder. Based on fusing the hierarchical views of proteins, it enhances the representation of protein binding pockets significantly by associating amino acid residues with their comprising atoms. Through jointly embedding molecule sequences, their drug-like properties, and binding affinities w.r.t. proteins, it autoregressively generates novel molecules having specific properties in a controllable manner by measuring the proximity of molecule tokens to protein residues and atoms. The comparison with state-of-the-art deep generative methods demonstrates the superiority of our CProMG. Furthermore, the progressive control of properties demonstrates the effectiveness of CProMG when controlling binding affinity and drug-like properties. After that, the ablation studies reveal how its crucial components contribute to the model respectively, including hierarchical protein views, Laplacian position encoding as well as property control. Last, a case study w.r.t. protein illustrates the novelty of CProMG and the ability to capture crucial interactions between protein pockets and molecules. It's anticipated that this work can boost de novo molecule design.
AVAILABILITY AND IMPLEMENTATION
The code and data underlying this article are freely available at https://github.com/lijianing0902/CProMG.
Topics: Amino Acids; Deep Learning; Protein Engineering
PubMed: 37387157
DOI: 10.1093/bioinformatics/btad222 -
Acta Biochimica Et Biophysica Sinica Jun 2023Biomolecular condensates formed by phase separation are involved in many cellular processes. Dysfunctional or abnormal condensates are closely associated with...
Biomolecular condensates formed by phase separation are involved in many cellular processes. Dysfunctional or abnormal condensates are closely associated with neurodegenerative diseases, cancer and other diseases. Small molecules can effectively regulate protein phase separation by modulating the formation, dissociation, size and material properties of condensates. Discovery of small molecules to regulate protein phase separation provides chemical probes for deciphering the underlying mechanism and potential novel treatments for condensate-related diseases. Here we review the advances of small molecule regulation of phase separation. The discovery, chemical structures of recently found small molecule phase separation regulators and how they modulate biological condensates are summarized and discussed. Possible strategies to accelerate the discovery of more liquid-liquid phase separation (LLPS)-regulating small molecules are proposed.
PubMed: 37294104
DOI: 10.3724/abbs.2023106