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Advances in Elucidating Disease Mechanisms and Designing Therapeutics Using Computer-Aided Simulations and Modeling

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: 25 June 2024 | Viewed by 577

Special Issue Editor


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Guest Editor
Department of Chemistry, University of Illinois at Chicago, Chicago, IL, USA
Interests: nanoscale simulations; computational chemistry; supramolecular self-assembly; drug design; ligand docking; GPCRs

Special Issue Information

Dear Colleagues,

Drug design for discovering new therapies for a large range of illnesses has been one of the most prominent and quickly developing areas of chemistry. Traditionally, it has relied on the guess work of chemists, which incurs high costs due to experiments involving synthesis, cellular assays, and animal models. Recent advances in computer-aided modeling can help circumvent these costs by predicting which drugs will be effective and avoiding those that will be ineffective in experiments. In addition, the elucidation of the disease mechanism through the protein structure and dynamics can also aid in designing new therapeutics. The development of machine learning algorithms can predict and design new drugs for specific types of illnesses, thus making computer-aided drug design even more efficient. This open access Special Issue will bring together research on the development and application of computer-aided drug-discovery methods in collaboration with experimental research. The main aim of this Special Issue is to develop collaboration between computer-aided drug design methods and experimental studies to design news therapeutics more efficiently.

Topics of this Special Issue may include, but are not limited to:

Fragment-based drug design, G-protein signaling, enzyme kinetics, G-protein receptors, cellular signaling, biostructures, ligand docking, machine learning for drug design, and lead optimization.

Dr. Pavel Rehak
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

  • X-ray diffraction
  • electron scanning microscopy
  • protein crystallization
  • protein structure
  • drug design approaches
  • G-protein-coupled receptors
  • G-protein signaling
  • enzyme kinetics
  • ligand docking
  • lead optimization
  • machine learning
  • quantum computing

Published Papers (1 paper)

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Review

23 pages, 729 KiB  
Review
Tumor-Derived Antigenic Peptides as Potential Cancer Vaccines
by Stanislav Sotirov and Ivan Dimitrov
Int. J. Mol. Sci. 2024, 25(9), 4934; https://doi.org/10.3390/ijms25094934 - 30 Apr 2024
Viewed by 216
Abstract
Peptide antigens derived from tumors have been observed to elicit protective immune responses, categorized as either tumor-associated antigens (TAAs) or tumor-specific antigens (TSAs). Subunit cancer vaccines incorporating these antigens have shown promise in inducing protective immune responses, leading to cancer prevention or eradication. [...] Read more.
Peptide antigens derived from tumors have been observed to elicit protective immune responses, categorized as either tumor-associated antigens (TAAs) or tumor-specific antigens (TSAs). Subunit cancer vaccines incorporating these antigens have shown promise in inducing protective immune responses, leading to cancer prevention or eradication. Over recent years, peptide-based cancer vaccines have gained popularity as a treatment modality and are often combined with other forms of cancer therapy. Several clinical trials have explored the safety and efficacy of peptide-based cancer vaccines, with promising outcomes. Advancements in techniques such as whole-exome sequencing, next-generation sequencing, and in silico methods have facilitated the identification of antigens, making it increasingly feasible. Furthermore, the development of novel delivery methods and a deeper understanding of tumor immune evasion mechanisms have heightened the interest in these vaccines among researchers. This article provides an overview of novel insights regarding advancements in the field of peptide-based vaccines as a promising therapeutic avenue for cancer treatment. It summarizes existing computational methods for tumor neoantigen prediction, ongoing clinical trials involving peptide-based cancer vaccines, and recent studies on human vaccination experiments. Full article
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