Special Issue "In Silico Approaches in Drug Design"
Deadline for manuscript submissions: 30 April 2022.
Interests: molecular modeling; computational and medicinal chemistry; molecular simulations; structural biology
Special Issues, Collections and Topics in MDPI journals
Special Issue in Pharmaceuticals: Artificial Intelligence Applied to Medicinal Chemistry and Structural Biology
Special Issue in Molecules: Medicinal Computational Chemistry
In the last few decades, computational methods have been successfully applied by the pharmaceutical community. This is mainly due to the development of both new theoretical approaches and new hardware and software technologies. In this context, in silico approaches such as molecular simulations, QM/MM simulations, chemoinformatics, artificial intelligence, etc., became fundamental in the drug design process. It can even be said that today it is impossible for a new drug to be invented without going through the “sieve” of in silico research. To celebrate the success story and advances in the important synergistic combination of drug design and in silico investigation, the journal Pharmaceuticals invites fellow scientists to submit original papers or reviews, which will be published in a Special Issue on “In silico Approaches in Drug Design 2021”. Such an issue will contemplate the following topics: computer-aided drug design, molecular dynamics simulations, Monte Carlo simulations, QM/MM simulations, molecular docking, chemoinformatics, in silico databases, data mining, machine learning, pharmacophore-based virtual screening, combinatorial chemistry, QSAR, and in silico ADMET.
Looking forward to your contribution.Prof. Dr. Osvaldo Andrade Santos-Filho
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. Pharmaceuticals 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 2000 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.
- Computer-aided drug design
- Molecular dynamics simulations
- Monte Carlo simulations
- QM/MM simulations
- Molecular docking
- In silico database
- Data mining
- Machine learning
- Pharmacophore-based virtual screening
- Combinatorial chemistry
- In silico ADMET
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: Computational Structure-Based Drug Design Approaches in SARS-CoV-2 Investigations
Authors: Osvaldo Andrade Santos-Filho
Affiliation: Laboratório de Modelagem Molecular e Biologia Estrutural Computacional, Instituto de Pesquisas de Produtos Naturais Walter Mors, Centro de Ciências da Saúde, Universidade Federal do Rio de Janeiro, Bloco H, Cidade Universitária, 21941-902, Rio de Janeiro, RJ, Brazil
Abstract: At the end of 2019, a new strain of CoV of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) was identified to be the cause of a very contagious respiratory disease in China. The disease, known as COVID-19, rapidly spread around the world and became a global pandemic. Since then, scientists from all the world have worked tirelessly to develop medicines to prevent and treat the disease. Some emergency vaccines were developed and are now available, but up to now, no effective drug has been developed to treat people which were already infected by the disease. In this review, applications of some computational structure-based drug design approaches in COVID-19 studies are presented, including virtual screening by molecular docking, molecular dynamics simulations, and quantum enzymology by multiscale modeling.
Title: A multi-level computational approach to drug design: Particle informatics and process simulation study of a sildenafil nanocrystal formulation
Authors: Andreas Ouranidis
Affiliation: Aristotle University of Thessaloniki, Thessaloniki, Greece
Title: In silico structure-based screening of Philippine natural products against the SARS-CoV-2 (COVID-19) RNA-dependent RNA polymerase (RdRp)
Authors: Alexandra Isabelle D. Ang1, Maria Constancia O. Carrillo1, Junie B. Billones1, Marilen Parungao Balolong2, Lyre Anni E. Murao3, Stephani Joy Y. Macalino4*
Affiliation: 1Department of Physical Sciences and Mathematics, College of Arts and Sciences, University of the Philippines Manila, Manila 1000, Philippines; [email protected] (A.I.D.A.); [email protected] (M.C.O.C.); [email protected] (J.B.B.) 2Department of Biology, College of Arts and Sciences University of the Philippines Manila; [email protected] 3Department of Biological Sciences and Environmental Studies, College of Science and Mathematics, University of the Philippines Mindanao; [email protected] 4Chemistry Department, De La Salle University, 2401 Taft Avenue, Manila 0992, Philippines
Abstract: COVID-19 is a viral infection caused by SARS-CoV-2, an RNA virus related to the viruses which caused the SARS and MERS epidemics. The disease has affected approximately 114 million people worldwide to date, yet no drug has been approved for treatment. In the Southeast Asia, Philippines is one of the hardest hit countries of this deadly disease. RNA-dependent RNA polymerase (RdRp) has been identified as an attractive target for anti-viral treatment. Like a number of other RNA viruses, SARS-CoV-2 utilizes RdRp to facilitate the replication of its genome. For this reason, inhibition of this enzyme has been associated with the possibility of reduced viral loads in those affected. Computational tools such as molecular dynamics (MD) and molecular docking provide a way to perform virtual high-throughput screening before in vivo and in vitro studies and expedite the drug discovery process. This study aims to identify potential candidates from Philippine natural products that are able to inhibit SARS-Cov-2 RdRp through the use of computational methods.
Title: 2-Aminothiophene derivatives design by CADD exerts promising antileishmanial activity
Authors: Isadora Silva Luna, Francisco Jaime Bezerra Mendonça Junior, Klinger Antônio da Franca Rodrigues, Luciana Scotti, Eugene Muratov, Marcus Tullius Scotti
Affiliation: Universidade Estadual da Paraíba
Abstract: In this work, we performed the design, ADMET prediction, synthesis, and structure-activity relationship studies of new 2-aminothiophene derivatives (2AT) candidates for anti-leishmania drugs. Theoretical studies were carried out using the energies values (KJ/mol) obtained for each molecule in its Z and E configurations, and the prediction of cytotoxicity risks and ADMET properties. The selected 2AT were synthesized in good yields and their structures were confirmed by spectroscopic and spectrometric techniques. Leishmanicidal activity tests demonstrated that most of the compounds showed activity against promastigote and amastigote forms of Leishmania (Leishmania) amazonensis with IC50 values below 10µM, once again demonstrating the validity of CADD studies to predict compounds with promising leishmanicidal activity, and confirming that 2AT are privileged structures for the design of leishmanicidal agents.