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Molecular Advances in Computational Medicine and 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 (30 April 2024) | Viewed by 1700

Special Issue Editor

College of Kyedang General Education, Sangmyung University, Cheonan 31066, Republic of Korea
Interests: systems biology; computational methods; cancer; machine learning; drug interactions

Special Issue Information

Dear Colleagues,

Drug repurposing is a strategy for identifying new uses of existing drugs to reduce the costs and risks associated with conventional drug development. Computer-aided drug design is another substitute method for drug discovery.  However, potential drug candidates from the computational methods frequently do not make it to the market during validation. Therefore, to improve upon predictive power (and validity), these research methods have been expanded to other multi-disciplinary subjects such as bioinformatics, chemistry, systems biology, and machine learning with rapidly increasing open-source tools. In addition, these research materials are also utilized in molecular mRNA, miRNA, pathway, and chemistry, and drug interaction analyses.

This Special Issue intends to compile current novel efforts and ideas for drug discovery design associated with computational methods and integrating molecular materials with no limitations.

Dr. Shinuk Kim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • machine learning
  • drug interaction
  • computational method
  • drug-gene interaction
  • pathway
  • systems biology
  • drug design
  • artificial intelligence in medicine
  • cancer

Published Papers (2 papers)

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Research

18 pages, 2500 KiB  
Article
Development of Novel Peptidyl Nitriles Targeting Rhodesain and Falcipain-2 for the Treatment of Sleeping Sickness and Malaria
by Carla Di Chio, Josè Starvaggi, Noemi Totaro, Santo Previti, Benito Natale, Sandro Cosconati, Marta Bogacz, Tanja Schirmeister, Jenny Legac, Philip J. Rosenthal, Maria Zappalà and Roberta Ettari
Int. J. Mol. Sci. 2024, 25(8), 4410; https://doi.org/10.3390/ijms25084410 - 17 Apr 2024
Viewed by 510
Abstract
In recent decades, neglected tropical diseases and poverty-related diseases have become a serious health problem worldwide. Among these pathologies, human African trypanosomiasis, and malaria present therapeutic problems due to the onset of resistance, toxicity problems and the limited spectrum of action. In this [...] Read more.
In recent decades, neglected tropical diseases and poverty-related diseases have become a serious health problem worldwide. Among these pathologies, human African trypanosomiasis, and malaria present therapeutic problems due to the onset of resistance, toxicity problems and the limited spectrum of action. In this drug discovery process, rhodesain and falcipain-2, of Trypanosoma brucei rhodesiense and Plasmodium falciparum, are currently considered the most promising targets for the development of novel antitrypanosomal and antiplasmodial agents, respectively. Therefore, in our study we identified a novel lead-like compound, i.e., inhibitor 2b, which we proved to be active against both targets, with a Ki = 5.06 µM towards rhodesain and an IC50 = 40.43 µM against falcipain-2. Full article
(This article belongs to the Special Issue Molecular Advances in Computational Medicine and Drug Design)
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10 pages, 1147 KiB  
Communication
Inferring Drug Set and Identifying the Mechanism of Drugs for PC3
by Shinuk Kim
Int. J. Mol. Sci. 2024, 25(2), 765; https://doi.org/10.3390/ijms25020765 - 7 Jan 2024
Viewed by 841
Abstract
Drug repurposing is a strategy for discovering new applications of existing drugs for use in various diseases. Despite the use of structured networks in drug research, it is still unclear how drugs interact with one another or with genes. Prostate adenocarcinoma is the [...] Read more.
Drug repurposing is a strategy for discovering new applications of existing drugs for use in various diseases. Despite the use of structured networks in drug research, it is still unclear how drugs interact with one another or with genes. Prostate adenocarcinoma is the second leading cause of cancer mortality in the United States, with an estimated incidence of 288,300 new cases and 34,700 deaths in 2023. In our study, we used integrative information from genes, pathways, and drugs for machine learning methods such as clustering, feature selection, and enrichment pathway analysis. We investigated how drugs affect drugs and how drugs affect genes in human pancreatic cancer cell lines that were derived from bone metastases of grade IV prostate cancer. Finally, we identified significant drug interactions within or between clusters, such as estradiol-rosiglitazone, estradiol-diclofenac, troglitazone-rosiglitazone, celecoxib-rofecoxib, celecoxib-diclofenac, and sodium phenylbutyrate-valproic acid. Full article
(This article belongs to the Special Issue Molecular Advances in Computational Medicine and Drug Design)
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