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Structure-Based Design of Drugs and Biologically Active Molecules Based on Computer-Aided Drug Discovery

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 1269

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Guest Editor
Laboratory of Modeling and Computational Chemistry, Federal University of Amapá, Macapá 68902-280, Amapá, Brazil
Interests: drug design; virtual screening; molecular modeling; docking; molecular simulations; quantum chemistry
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Special Issue Information

Dear Colleagues,

Computer-Aided Drug Discovery (CADD) has advanced significantly, particularly with Structure-Based Drug Design (SBDD). SBDD uses three-dimensional models of biological targets, obtained by techniques such as X-ray crystallography and nuclear magnetic resonance (NMR), to guide the creation and optimization of bioactive molecules. SBDD allows the precise identification of ligands with high affinity and specificity, essential for therapeutic efficacy.

Computational tools, such as molecular docking and molecular dynamics, are employed to predict the conformation of ligands and their binding energies to the biological target. Molecular docking remains a vital tool in SBDD, allowing the prediction of the preferred orientation of a molecule in a protein target. Furthermore, the use of machine learning has improved the prediction of pharmacokinetic and toxicological properties, accelerating the development of safe and effective medicines.

CADD and SBDD not only significantly reduce the time and cost associated with developing new drugs but also increase the accuracy in identifying promising compounds. The integration of computational and experimental methods is crucial for successful drug discovery, facilitating the identification and optimization of new drug candidates.

These approaches have proven essential for advances in medicine, promoting the discovery of innovative and personalized therapies that better meet patients’ needs.

Dr. Cleydson Breno Rodrigues dos Santos
Guest Editor

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Keywords

  • drug design
  • virtual screening
  • bioinformatics
  • chemoinformatics
  • quantum chemistry

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Published Papers (1 paper)

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Research

26 pages, 9443 KiB  
Article
Indian Medicinal Plant-Derived Phytochemicals as Potential Antidotes for Snakebite: A Pharmacoinformatic Study of Atrolysin Inhibitors
by Deva Asirvatham Ravi, Du Hyeon Hwang, Ramachandran Loganathan Mohan Prakash, Changkeun Kang and Euikyung Kim
Int. J. Mol. Sci. 2024, 25(23), 12675; https://doi.org/10.3390/ijms252312675 - 26 Nov 2024
Viewed by 891
Abstract
Snakebite envenoming is a significant health threat, particularly in tropical regions, causing substantial morbidity and mortality. Traditional treatments, including antivenom therapy, have limitations and associated risks. This research aims to discover novel phytochemical antidotes for snakebites, specifically targeting the western diamondback rattlesnake ( [...] Read more.
Snakebite envenoming is a significant health threat, particularly in tropical regions, causing substantial morbidity and mortality. Traditional treatments, including antivenom therapy, have limitations and associated risks. This research aims to discover novel phytochemical antidotes for snakebites, specifically targeting the western diamondback rattlesnake (Crotalus atrox) venom metalloproteinase Atrolysin. Utilizing pharmacoinformatic techniques such as molecular docking, high-throughput ligand screening, pharmacophore mapping, pharmacokinetic profiling, and molecular dynamics (MD) simulations, we analyzed phytochemicals from the Indian Medicinal Plants, Phytochemistry And Therapeutics (IMPPAT) database alongside well-known nine metalloproteinase inhibitors from the PubChem database. From an initial set of 17,967 compounds, 4708 unique compounds were identified for further study. These compounds were evaluated based on drug likeness, molecular descriptors, ADME properties, and toxicity profiles. Binding site predictions and molecular docking identified key interacting residues and binding energies, highlighting several promising compounds. Density functional theory (DFT) analysis provided insights into these compounds’ electronic properties and stability. MD simulations assessed the dynamic stability of protein-ligand complexes using parameters such as RMSD, RMSF, the radius of gyration, and hydrogen bond interactions. This study identified top candidates, including CID5291, IMPHY001495, IMPHY014737, IMPHY008983, IMPHY008176, and IMPHY003833, based on their favorable binding energies, interaction forces, and structural stability. These findings suggest that the selected phytochemicals have the potential to serve as effective alternatives to traditional antivenom treatments, offering a promising avenue for further research and development in snakebite management. Full article
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