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Cutting-Edge Computational Biochemistry in Europe

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 4001

Special Issue Editor

Special Issue Information

Dear Colleagues,

Computational biochemistry is a broad scientific area of research that applies computational methods to study biochemical problems. It lies at the interface between biology, chemistry, physics and computer science/informatics and involves the structural and functional characterization of biosystems at the molecular level, including proteins, enzymes, carbohydrates, nucleic acids, lipids, etc. This is accomplished through the application of different computational methods based on a diversity of physical approaches, including classical molecular mechanics, quantum mechanics, hybrid quantum mechanical/molecular mechanics approaches, free energy calculations, docking and virtual screening. 

This Special Issue is dedicated to research efforts from European laboratories in the field of computational biochemistry, including computational enzymology, the study of the dynamics of biomolecules, molecular recognition phenomena, conformational alterations, protein–ligand interactions, and protein folding, among many others. Particular emphasis is put on new methodological developments and algorithms in this rapidly evolving field. Original research articles, reviews, or communications within the scope of computational biochemistry and from researchers based at any Europeean university or scientific institution are welcome.

Dr. Sérgio F. Sousa
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. Molecules is an international peer-reviewed open access semimonthly 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 2700 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

  • computational enzymology
  • QM/MM
  • biomolecular simulations
  • computational drug discovery

Published Papers (1 paper)

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Research

24 pages, 6868 KiB  
Article
New In Vitro-In Silico Approach for the Prediction of In Vivo Performance of Drug Combinations
Molecules 2021, 26(14), 4257; https://doi.org/10.3390/molecules26144257 - 13 Jul 2021
Cited by 9 | Viewed by 3125
Abstract
Pharmacokinetic (PK) studies improve the design of dosing regimens in preclinical and clinical settings. In complex diseases like cancer, single-agent approaches are often insufficient for an effective treatment, and drug combination therapies can be implemented. In this work, in silico PK models were [...] Read more.
Pharmacokinetic (PK) studies improve the design of dosing regimens in preclinical and clinical settings. In complex diseases like cancer, single-agent approaches are often insufficient for an effective treatment, and drug combination therapies can be implemented. In this work, in silico PK models were developed based on in vitro assays results, with the goal of predicting the in vivo performance of drug combinations in the context of cancer therapy. Combinations of reference drugs for cancer treatment, gemcitabine and 5-fluorouracil (5-FU), and repurposed drugs itraconazole, verapamil or tacrine, were evaluated in vitro. Then, two-compartment PK models were developed based on the previous in vitro studies and on the PK profile reported in the literature for human patients. Considering the quantification parameter area under the dose-response-time curve (AUCeffect) for the combinations effect, itraconazole was the most effective in combination with either reference anticancer drugs. In addition, cell growth inhibition was itraconazole-dose dependent and an increase in effect was predicted if itraconazole administration was continued (24-h dosing interval). This work demonstrates that in silico methods and AUCeffect are powerful tools to study relationships between tissue drug concentration and the percentage of cell growth inhibition over time. Full article
(This article belongs to the Special Issue Cutting-Edge Computational Biochemistry in Europe)
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