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Molecular Advances in Computational Chemistry for Drug Design

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: closed (10 October 2024) | Viewed by 3143

Special Issue Editor

Special Issue Information

Dear Colleagues,

The impressive recent progress made advancing the richness of scientific data and enhancing commonly available computational power is supporting the development of innovative computational approaches for drug design. Overall, the field has benefited from the power of the artificial intelligence (AI) algorithms implemented in countless applications, including ligand- and structure-based methods. Innovative AI-based methods have been reported for rational de novo design of promising compounds, property prediction, ADME/Tox profiling, docking simulations, and MM/MD calculations and analysis. In parallel, enhanced computational power has allowed the development of targeted MD/MM approaches capable of extensively simulating the molecular recognition processes, thus gaining information concerning the complex stability and free energy from the corresponding interaction.

Overall, this Special Issue aims to publish manuscripts dealing with novel computational approaches in drug design by considering both methodological and applicative studies, with a view to offering a picture of the fields in which computational chemistry can impact the drug discovery process.

Prof. Dr. Giulio Vistoli
Guest Editor

Manuscript Submission Information

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Keywords

  • drug design
  • computational chemistry
  • artificial intelligence
  • molecular docking
  • molecular mechanics
  • molecular dynamics
  • ADME/Tox predictions
  • property calculation

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Published Papers (1 paper)

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Review

45 pages, 3445 KiB  
Review
Prioritizing Computational Cocrystal Prediction Methods for Experimental Researchers: A Review to Find Efficient, Cost-Effective, and User-Friendly Approaches
by Beáta Lemli, Szilárd Pál, Ala’ Salem and Aleksandar Széchenyi
Int. J. Mol. Sci. 2024, 25(22), 12045; https://doi.org/10.3390/ijms252212045 - 9 Nov 2024
Cited by 2 | Viewed by 2535
Abstract
Pharmaceutical cocrystals offer a versatile approach to enhancing the properties of drug compounds, making them an important tool in drug formulation and development by improving the therapeutic performance and patient experience of pharmaceutical products. The prediction of cocrystals involves using computational and theoretical [...] Read more.
Pharmaceutical cocrystals offer a versatile approach to enhancing the properties of drug compounds, making them an important tool in drug formulation and development by improving the therapeutic performance and patient experience of pharmaceutical products. The prediction of cocrystals involves using computational and theoretical methods to identify potential cocrystal formers and understand the interactions between the active pharmaceutical ingredient and coformers. This process aims to predict whether two or more molecules can form a stable cocrystal structure before performing experimental synthesis, thus saving time and resources. In this review, the commonly used cocrystal prediction methods are first overviewed and then evaluated based on three criteria: efficiency, cost-effectiveness, and user-friendliness. Based on these considerations, we suggest to experimental researchers without strong computational experiences which methods and tools should be tested as a first step in the workflow of rational design of cocrystals. However, the optimal choice depends on specific needs and resources, and combining methods from different categories can be a more powerful approach. Full article
(This article belongs to the Special Issue Molecular Advances in Computational Chemistry for Drug Design)
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