Computer-Aided Drug Design and Molecular Synthesis

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Center of Health Sciences, Laboratory of Molecular Modeling and Computational Structural Biology, Federal University of Rio de Janeiro, IPPN, Av. Carlos Chagas Filho 373, Bloco H, Rio de Janeiro 21941-599, Brazil
Interests: molecular modeling; computational and medicinal chemistry; molecular simulations; structural biology
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LaDMol-QM (Molecular Diversity and Medicinal Chemistry Laboratory), Departament of Organic Chemistry, Federal Rural University of Rio de Janeiro (UFRRJ), Seropédica, RJ, Brazil
Interests: Alzheimer; cancer; inflammation; multi-target compounds; theranostics; medicinal chemistry; organic synthesis
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Special Issue Information

Dear Colleagues,

In silico approaches such as molecular simulations, QM/MM simulations, molecular docking, chemoinformatics, and artificial intelligence have become fundamental in the drug design process. It can even be said that it is impossible today for a new drug to be invented without going through the “sieve” of in silico research. Moreover, molecular synthesis also plays a central role in drug design and discovery by enabling the development of desired compounds, allowing chemists to build, modify, and optimize hit and lead compounds and helping researchers explore structure–activity relationships, improve potency and selectivity, and enhance properties such as stability and bioavailability. Ultimately, without efficient and innovative synthetic methods, promising drug concepts would never progress into viable therapeutic agents.

To celebrate the promising advances in the important synergistic combination of computational chemistry and molecular synthesis, the journal Scientia Pharmaceutica invites scientists to submit original papers or reviews, for this Special Issue titled “Computer-Aided Drug Design and Molecular Synthesis”. This Issue will focus on the following topics: computer-aided drug design; molecular dynamics simulations; Monte Carlo simulations; QM/MM simulations; molecular docking; chemoinformatics; in silico databases; data mining; machine learning; pharmacophore-based virtual screening; combinatorial chemistry; QSAR; in silico ADMET; and organic synthesis.

We look forward to receiving your contributions.

Prof. Dr. Osvaldo Andrade Santos-Filho
Dr. Arthur Eugen Kümmerle
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Scientia Pharmaceutica is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • computer-aided drug design
  • molecular dynamics simulations
  • Monte Carlo simulations
  • molecular docking
  • virtual screening
  • pharmacophore-based virtual screening
  • synthetic methodology
  • structure–activity relationship (SAR)
  • bioactive small molecules
  • drug design and synthesis
  • heterocyclic compound synthesis

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Published Papers (1 paper)

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Research

17 pages, 4760 KB  
Article
MD + QC Methodology for Studying the Interaction of Bioactive Molecules with Amino Acids: The Case of Arbidol Interaction with Aromatic Amino Acids and Its Spectral-Luminescent Validation
by Sophia S. Borisevich, Edward M. Khamitov, Gulshat A. Masyagutova, Olga I. Yarovaya and Sergey L. Khursan
Sci. Pharm. 2026, 94(1), 20; https://doi.org/10.3390/scipharm94010020 - 4 Mar 2026
Viewed by 508
Abstract
A comprehensive MD + QC methodology was developed and applied to evaluate various aspects of Arbidol interactions with functional amino acids of surface proteins of influenza virus and SARS-CoV-2. The spatial structure, solvation features, conformational behavior of Arb AA (AA–Trp, Tyr, Phe, and [...] Read more.
A comprehensive MD + QC methodology was developed and applied to evaluate various aspects of Arbidol interactions with functional amino acids of surface proteins of influenza virus and SARS-CoV-2. The spatial structure, solvation features, conformational behavior of Arb AA (AA–Trp, Tyr, Phe, and Val) complexes were established, and the statistics of intermolecular interactions in the complex were described. It was found that Arb can participate in strong and long-lived π-π stacking interactions with aromatic amino acids. The binding energy (BE) of Arbidol and amino acids in aqueous solution was estimated using an explicit solvation model, QTAIM analysis and correlation of BE vs. total electron density at the bond critical points of the complex. Theoretical calculations were validated by experimental studies of fluorescence (FL) quenching of aromatic AA by Arbidol. Spectral-fluorescent properties of Arbidol hydrochloride in aqueous solutions were studied, and the luminescence quantum yield for the electronically excited state of Arb was determined. Full article
(This article belongs to the Special Issue Computer-Aided Drug Design and Molecular Synthesis)
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