Special Issue "Computational Chemical Biology"
Deadline for manuscript submissions: 31 January 2019
Assoc. Prof. Dr. J. B. Brown
Prof. Dr. Jürgen Bajorath
The biological screening of compound collections continues to provide many new active chemical entities for further consideration. Large-magnitude screening campaigns typically require computational support for data analysis and the selection of preferred hits for follow-up studies. Here, the requirements for lead-like molecules in medicinal chemistry and probe-like compounds in chemical biology differ. Furthermore, the experimental studies must often be further extended through computational means, for example to identify analogues of interesting active compounds or map currently known targets. To these ends, computational chemical biology is tasked with delivering interpretation and prediction tools with significant potential to complement experimental investigations. In this Special Issue, we are seeking contributions focusing on new computational methodologies, practical solutions, and perspectives with immediate relevance for chemical biology. Papers on diverse sub-topics such as, for example, molecular structure–selectivity analysis, single- and multi-target assay data exploration, or bioactivity modelling through artificial intelligence approaches including, but not limited to, machine learning are welcome.
Manuscripts are ideally written to include both experimental and computational viewpoints. In addition, papers reporting new computational concepts for chemical biology are highly desired.
Assoc. Prof. Dr. J. B. Brown
Prof. Dr. Jürgen Bajorath
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 papers will be 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 monthly 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 1800 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.
- Bioactivity assay analysis
- Computational structure–activity relationship
- High-throughput screening
- Pattern recognition/machine learning
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: In silico approach for uptake of phenols via membrane transporters: case study based on computational models of transport activity for transporter bilitranslocase
Authors: Katja Venko* and Marjana Novič*
Affiliation: Laboratory for Cheminformatics, Theory Department, National Institute of Chemistry, SI-1000 Ljubljana, Slovenia
Abstract: Phenols are naturally accessible agents and the most abundant antioxidants present in a human normal diet. Numerous beneficial applications of phenols as preventive/therapeutic agents in cancer and inflammatory, neurodegenerative and cardiovascular diseases have increased interest of researchers, consumers, food and drug manufacturers. Therefore, knowing the bioavailability of phenols from diet uptake is of high interest. Since experimental structural and functional data on membrane transporters are limited, the in silico modelling is really challenging and urgent tool in the discovery of adverse effects and more efficient transporter substrates. We focused our research on specific and extremely attractive transporter bilitranslocase (BTL). BTL has broader tissue expression (vascular endothelium, absorptive and excretory epithelia) and can transport wide variety of poly-aromatic compounds. With available BTL data (inhibition constant pKi [mmol L-1]) for 120 poly-aromatic organic compounds we developed new robust and reliable QSAR models for BTL transport activity that can be extrapolated on new untested 310 phenolic compounds. The results show that dietary phenols and some new drug candidates are likely to be transported via BTL. Moreover, the bioavailability profile of studied compounds on BTL data and 16 transporters from Metrabase was characterized. Such systematic analysis of available experimental data of BTL transport activity is good exemplum for transport ability characterization and prediction. Using the same computational approach reliable and validated in silico models could be built also for other transporters that have available experimental data.
Keywords: phenols; membrane transporter bilitranslocase; transport activity; cellular uptake; in silico models
Title: Mechanistic and structural insights on the IL-15 system through molecular dynamic simulations
Article type: Article
Author: Jean‐Yves Le Questel