Bioinformatic and Biochemical Identification of Phytochemical Drug Candidates
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Medicinal Chemistry".
Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 1933
Special Issue Editors
2. Al-Qasemi Research Center- Al-Qasemi Academic College, Baqa-El-Gharbia P.O. Box 124, Israel
Interests: drug resistance; novel compounds and drug discovery; secondary metabolites; structure–function relationship; advanced extraction and fractionation strategies; phytochemical screening and composition; computer-aided drug design; non-communicable diseases; communicable diseases
Special Issues, Collections and Topics in MDPI journals
Interests: diabetes; insulin resistance; immunometabolism drug discovery and development; immune–metabolic cross-talk in the context of insulin resistance
Special Issues, Collections and Topics in MDPI journals
Interests: biodata science and machine learning algorithms; computational techniques in data sets to aid deseases analysis and identification of potential drug targets functional prediction and classification of proteins; mapping differential gene expression to potential epigenetic modifications at gene and exon levels
Interests: diabetes type 2; medicinal plants; green chemistry; phytochemicals
Special Issues, Collections and Topics in MDPI journals
Interests: docking; molecular dynamic simulations; bioinformatics; phytochemicals; drug targets
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Chronic diseases are defined as conditions that require ongoing medical attention lasting for one or more year(s). Chronic diseases such as diabetes, cancer and heart disease impose a significant burden on the healthcare systems and are the major causes of disability and death worldwide. The lack of access to essential medicines for chronic diseases is a major challenge, especially in developing countries. According to the World Health Organization (WHO), the rate of chronic diseases in the low- and middle-income countries is expected to increase until 2030. Unfortunately, the national drug policies of these countries do not include the essential medicines for chronic diseases.
Phytochemical drug discovery provides important leads against various pharmacological targets. A large number of herbs used in the traditional medicine and natural active ingredients have now been incorporated into the modern healthcare system worldwide. Indeed, nature is the best provider of medicines due to the fact that natural products have been optimized to interact with the biological systems through a long process of natural selection. For this reason, natural products have been a source of therapeutics for millennia, and during the past century, many drugs have been developed from natural sources. Currently, we are witnessing great progress in evidence-based modern medicine and pharmacology. The characterization of pharmacological and biological effects of herbal-based medicines is becoming increasingly competitive and complex, with experts belonging to different scientific fields, including botany, chemistry, biochemistry, immunology, molecular biology, taking part in this research. The development of novel natural drugs is now more achievable due to modern techniques for separation, structure elucidation, screening, and bio- and chemo-informatics.
With the rapidly increasing body of biological data available and the intensive time and human resources allocated to the discovery of new drugs, the need for computational methods has substantially increased. This goal can be achieved by filtering a large number of leads in the early stage of drug development before launching the drug and subjecting it to the costly and labor-intensive experimental lab test phases, as well as the preclinical and clinical testing. Through bioinformatics and computer-aided drug design, new and potent natural hits can be mined. As a result, the time and costs required for the discovery of new drugs can be substantially lowered. Bioinformatics is also implemented within translational drug discovery for chronic diseases. For instance, the comparison of gene expressions between healthy and cancerous cell lines based on databases can shed light on the possible genes affecting the disease progression and treatment of cancers and thus offers repositioning opportunities for existing drugs.
We invite researchers to contribute original research and review articles investigating chronic diseases and bioinformatics tools for natural drug selection. We are particularly interested in articles that explore aspects of medicinal plants and their active compounds in the treatment of chronic diseases, with a focus on the in silico methods of drug discovery pipelines. Research articles must combine experimental evidence with computer-based methods of drug discovery in order to be considered.
Potential topics include, but are not limited to:
- Predictive computational approaches in the field of computational chemistry, e.g., predictive ADMET (absorption, distribution, metabolism, elimination, and toxicity), pharmacophore modeling, virtual screening, and the quantitative structure–activity relationship.
- Structural bioinformatics, e.g., molecular docking, molecular dynamic simulations, free energy calculations.
- Expression and NGS data analysis.
- Isolation and characterization of novel phytochemicals for treating chronic diseases.
- Recent advances in drug discovery using medicinal plants in the treatment of chronic diseases and disorders.
Prof. Dr. Hilal Zaid
Dr. Akhilesh Tamrakar
Dr. Ahmad Barghash
Dr. Sleman Kadan
Dr. Siba Shanak
Guest Editors
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Keywords
- diabetes
- cancer
- natural products
- bioinformatics
- drug discovery
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