Application of Metabolomics and Integrated Computing in Chemical Biology

A special issue of Biology (ISSN 2079-7737).

Deadline for manuscript submissions: 30 April 2026 | Viewed by 3734

Special Issue Editor


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Guest Editor
Department of Biotechnology and Food Science, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa
Interests: computational biochemistry; redox biology; metagenomics; microorganisms; cheminformatics

Special Issue Information

Dear Colleagues,

The use of modeling approaches has culminated in progressive advances in computational and chemical biology, which is envisaged to continuously advance experimental and computational science. Chemical biology studies will continue to be transformed by these advances. While advanced computation skills have long been at the core of training for the physical sciences, they are now becoming critical to the advancement of chemical biology as well. Computational chemical biologists are now leading modern programs that generate and process large datasets in the laboratory and in the field.

This Special Issue will focus on the application of metabolomics and computational modeling to bridge the gap between basic chemical biology and bioinformatics as well as software appreciation, in a way that will enhance ground-breaking discoveries by chemical biologists. It is anticipated that this Special Issue will address ideas that will generate new chemical entities (NCE) and novel active pharmaceutical ingredients (API) against debilitating disorders such as aging, diabetes and its secondary complications, cancer, central nervous system disorders, and microbial diseases, etc. Original research and review articles using computational methods such as molecular docking and advanced molecular dynamic simulations for NCE and API bioprospecting from natural biodiversity, and molecular networking for metabolomics are welcome. Consideration will also be given to papers combining computational and other experimental methods. The overarching objective is to present an up-to-date perspective of this interdisciplinary and insightful field that will benefit chemical biologists and other related fields. This is a Virtual Special Issue and articles will be published as they are accepted and then subsequently compiled in a Special Collection.

Potential topics and themes for consideration include, but are not limited to, the following:

  • Application of metabolomics in quality profiling and characterization of plants and microbes.
  • Bioactive molecule isolation from natural sources (microbes, plants, animals) and molecular docking.
  • Computer-driven NCE/API design from plant and microbial secondary metabolites.
  • Advanced molecular simulations for lead optimization and identification from secondary metabolites.
  • Density functional theory (DFT) calculations for lead compounds.
  • Integrated computational-system-based bioprospecting from natural sources for small molecules identification and development.
  • Computational ligand- and structure-based rationale for API and NCE design.
  • QSAR modeling and applications in bioprospecting from natural sources.
  • Metabolite profiling using molecular networking dereplication methods.

Dr. Saheed Sabiu
Guest Editor

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Keywords

  • chemical biology
  • computational biology
  • metabolomics
  • computational modeling
  • new chemical entities (NCE)
  • active pharmaceutical ingredients (API)
  • characterization
  • metabolite profiling

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Published Papers (2 papers)

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Research

22 pages, 3439 KiB  
Article
Metabolomics Analysis Reveals the Influence Mechanism of Different Growth Years on the Growth, Metabolism and Accumulation of Medicinal Components of Bupleurum scorzonerifolium Willd. (Apiaceae)
by Jialin Sun, Jianhao Wu, Weinan Li, Xiubo Liu and Wei Ma
Biology 2025, 14(7), 864; https://doi.org/10.3390/biology14070864 - 16 Jul 2025
Viewed by 208
Abstract
Bupleurum scorzonerifolium Willd. is a perennial herbaceous plant of the genus Bupleurum in the Apiaceae family. Also known as red Bupleurum, it is mainly distributed in Northeast China, North China and other regions and is a commonly used medicinal plant. It is [...] Read more.
Bupleurum scorzonerifolium Willd. is a perennial herbaceous plant of the genus Bupleurum in the Apiaceae family. Also known as red Bupleurum, it is mainly distributed in Northeast China, North China and other regions and is a commonly used medicinal plant. It is difficult for the wild plant resources of Bupleurum scorzonerifolium Willd. to meet the market demand. In artificial cultivation, there are problems such as a low yield per plant, low quality, weakened stress resistance and variety degradation. The contents of bioactive components and metabolites in traditional Chinese medicinal materials vary significantly across different growth years. The growth duration directly impacts their quality and clinical efficacy. Therefore, determining the optimal growth period is one of the crucial factors in ensuring the quality of traditional Chinese medicinal materials. In this study, Gas Chromatography–Mass Spectrometry (GC-MS) and High-performance liquid chromatography (HPLC) were comprehensively applied to analyze the metabolically differential substances in different parts of Bupleurum scorzonerifolium Willd. By comparing the compositions and content differences of chemical components in different growth years and different parts, the chemical components with significant differences were accurately screened out. In order to further explore the dynamic change characteristics and internal laws of metabolites, a metabolic network was constructed for a visual analysis and, finally, to see the optimal growth years of Bupleurum scorzonerifolium Willd. This result showed that with the accumulation of the growth cycle, the height, root width, fresh mass and saikosaponins content of Bupleurum scorzonerifolium Willd. increased year by year. Except for sodium and calcium elements in the main shoot, the other elements were significantly reduced. In addition, 59 primary metabolites were identified by GC-MS, with the accumulation of the growth cycle, the contents of organic acids, sugars, alcohols and amino acids gradually decreased, while the contents of alkyl, glycosides and other substances gradually increased. There were 53 positive correlations and 18 negative correlations in the triennial Bupleurum scorzonerifolium Willd. grid, all of which were positively correlated with saikosaponins. Therefore, the triennial Bupleurum scorzonerifolium Willd. was considered to be the suitable growth year. It not only provided a new idea and method for the quality evaluation of Bupleurum scorzonerifolium Willd., but also provided a scientific basis for the quality control of Chinese herbs. Full article
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40 pages, 14702 KiB  
Article
Waste to Medicine: Evidence from Computational Studies on the Modulatory Role of Corn Silk on the Therapeutic Targets Implicated in Type 2 Diabetes Mellitus
by Ayesha Akoonjee, Adedayo Ayodeji Lanrewaju, Fatai Oladunni Balogun, Nokwanda Pearl Makunga and Saheed Sabiu
Biology 2023, 12(12), 1509; https://doi.org/10.3390/biology12121509 - 11 Dec 2023
Cited by 5 | Viewed by 3008
Abstract
Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance and/or defective insulin production in the human body. Although the antidiabetic action of corn silk (CS) is well-established, the understanding of the mechanism of action (MoA) behind this potential is lacking. Hence, this [...] Read more.
Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance and/or defective insulin production in the human body. Although the antidiabetic action of corn silk (CS) is well-established, the understanding of the mechanism of action (MoA) behind this potential is lacking. Hence, this study aimed to elucidate the MoA in different samples (raw and three extracts: aqueous, hydro-ethanolic, and ethanolic) as a therapeutic agent for the management of T2DM using metabolomic profiling and computational techniques. Ultra-performance liquid chromatography-mass spectrometry (UP-LCMS), in silico techniques, and density functional theory were used for compound identification and to predict the MoA. A total of 110 out of the 128 identified secondary metabolites passed the Lipinski’s rule of five. The Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis revealed the cAMP pathway as the hub signaling pathway, in which ADORA1, HCAR2, and GABBR1 were identified as the key target genes implicated in the pathway. Since gallicynoic acid (−48.74 kcal/mol), dodecanedioc acid (−34.53 kcal/mol), and tetradecanedioc acid (−36.80 kcal/mol) interacted well with ADORA1, HCAR2, and GABBR1, respectively, and are thermodynamically stable in their formed compatible complexes, according to the post-molecular dynamics simulation results, they are suggested as potential drug candidates for T2DM therapy via the maintenance of normal glucose homeostasis and pancreatic β-cell function. Full article
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