Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
3.5
Journals
Processes
Special Issues
Frontiers in Computer-Aided Drug Discovery
share announcement

Frontiers in Computer-Aided Drug Discovery

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Pharmaceutical Processes".

Deadline for manuscript submissions: closed (25 August 2022) | Viewed by 12091

Special Issue Editors

Prof. Dr. Teodorico De Castro Ramalho

E-Mail Website
Guest Editor
Federal University of Lavras, Department of Chemistry, Lavras, CEP 37200973, Brazil
Interests: medicinal chemistry; MD simulation; molecular docking; quantum chemistry (QM/MM calculations) ; multiscale modeling in chemistry
Dr. Zhong-Ru Xie

E-Mail Website
Guest Editor
School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
Interests: computational drug discovery; MD simulation; Alzheimer’s disease
Dr. Kuan Y. Chang

E-Mail Website
Guest Editor
Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung 202, Taiwan
Interests: computational immunology; bioinformatics; health informatics; machine learning

Special Issue Information

Dear Colleagues,

Computer-aided drug design (CADD) techniques can provide important clues about the active sites of molecular targets and molecular interactions. These computational methods, such as QSAR or virtual screening techniques, are now being employed by both pharmaceutical companies and universities to limit the use of animals in cosmetic and pharmacological research, for aiding the rational design of novel and safe drug candidates can support innovative ideas in the drug-discovery trajectory. Due to the rapid advances in these methods, continuous improvements in drug-discovery tools are crucial. In this line, we believe that a Special Issue highlighting inventions and innovative ideas in the CADD field could be of potential importance for scientists, managers and decision-makers in the pharmaceutical industry.

Prof. Dr. Teodorico De Castro Ramalho
Dr. Zhong-Ru Xie
Dr. Kuan Y. Chang
Guest Editors

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. Processes 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 2400 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 immunology
  • bioinformatics
  • health informatics
  • MD simulation
  • medicinal chemistry
  • virtual screening
  • molecular docking and quantum chemistry

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 5745 KiB  
Article
Identifying the Most Potent Dual-Targeting Compound(s) against 3CLprotease and NSP15exonuclease of SARS-CoV-2 from Nigella sativa: Virtual Screening via Physicochemical Properties, Docking and Dynamic Simulation Analysis
by Syed Mohd Danish Rizvi, Talib Hussain, Afrasim Moin, Sheshagiri R. Dixit, Subhankar P. Mandal, Mohd Adnan, Qazi Mohammad Sajid Jamal, Dinesh C. Sharma, Abulrahman Sattam Alanazi and Rahamat Unissa
Processes 2021, 9(10), 1814; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9101814 - 13 Oct 2021
Cited by 10 | Viewed by 4760
Abstract
Background: The outbreak of the coronavirus (SARS-CoV-2) has drastically affected the human population and caused enormous economic deprivation. It belongs to the β-coronavirus family and causes various problems such as acute respiratory distress syndrome and has resulted in a global pandemic. Though various [...] Read more.
Background: The outbreak of the coronavirus (SARS-CoV-2) has drastically affected the human population and caused enormous economic deprivation. It belongs to the β-coronavirus family and causes various problems such as acute respiratory distress syndrome and has resulted in a global pandemic. Though various medications have been under trial for combating COVID-19, specific medicine for treating COVID-19 is unavailable. Thus, the current situation urgently requires effective treatment modalities. Nigella sativa, a natural herb with reported antiviral activity and various pharmacological properties, has been selected in the present study to identify a therapeutic possibility for treating COVID-19. Methods: The present work aimed to virtually screen the bioactive compounds of N. sativa based on the physicochemical properties and docking approach against two SARS-CoV-2 enzymes responsible for crucial functions: 3CLpro (Main protease) and NSP15 (Nonstructural protein 15 or exonuclease). However, simulation trajectory analyses for 100 ns were accomplished by using the YASARA STRUCTURE tool based on the AMBER14 force field with 400 snapshots every 250 ps. RMSD and RMSF plots were successfully obtained for each target. Results: The results of molecular docking have shown higher binding energy of dithymoquinone (DTQ), a compound of N. sativa against 3CLpro and Nsp15, i.e., −8.56 kcal/mol and −8.31 kcal/mol, respectively. Further, the dynamic simulation has shown good stability of DTQ against both the targeted enzymes. In addition, physicochemical evaluation and toxicity assessment also revealed that DTQ obeyed the Lipinski rule and did not have any toxic side effects. Importantly, DTQ was much better in every aspect among the 13 N. sativa compounds and 2 control compounds tested. Conclusions: The results predicted that DTQ is a potent therapeutic molecule that could dual-target both 3CLpro and NSP15 for anti-COVID therapy. Full article
(This article belongs to the Special Issue Frontiers in Computer-Aided Drug Discovery)
►▼ Show Figures

Figure 1

19 pages, 17213 KiB  
Article
Integrative Network Pharmacology of Moringa oleifera Combined with Gemcitabine against Pancreatic Cancer
by Nursaffa Alisya Sahruddin, Zhong Sun, Norsyasya Adriana Rosdi, Sudha Warrier and Karuppiah Thilakavathy
Processes 2021, 9(10), 1742; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9101742 - 29 Sep 2021
Cited by 1 | Viewed by 2999
Abstract
Gemcitabine (GEM) is the first-line chemotherapy drug for patients with advanced pancreatic cancer. Moringa oleifera (MO) exhibited various biological activities, including anticancer effects. Nevertheless, the effectiveness of their combination against pancreatic cancer has not yet been explored. This study evaluates the effect of [...] Read more.
Gemcitabine (GEM) is the first-line chemotherapy drug for patients with advanced pancreatic cancer. Moringa oleifera (MO) exhibited various biological activities, including anticancer effects. Nevertheless, the effectiveness of their combination against pancreatic cancer has not yet been explored. This study evaluates the effect of MO and GEM against pancreatic cancer through network pharmacology. TCMSP, TCMID, and PubMed were used to identify and screen MO bioactive compounds. MO and GEM genes were predicted through DGIdb, CTD, and DrugBank. Pancreatic cancer genes were retrieved from OMIM and MalaCards. Protein–protein interaction (PPI) and compound-target-pathway network were established via STRING and Cytoscape. Gene ontology (GO) and pathway enrichment analysis were conducted using DAVID Bioinformatic Tools. Catechin, kaempferol, quercetin, and epicatechin that met the drug screening requirements, and three additional compounds, glucomoringin, glucoraphanin, and moringinine, were identified as bioactive compounds in MO. Catechin was found to be the main hub compound in MO. TP53, AKT1, VEGFA, and CCND1 from PPI network were discovered as hub genes to have biological importance in pancreatic cancer. GO and pathway analysis revealed that MO and GEM combination was mainly associated with cancer, including pancreatic cancer, through regulation of apoptosis. Combination therapy between MO and GEM might provide insight in pancreatic cancer treatment. Full article
(This article belongs to the Special Issue Frontiers in Computer-Aided Drug Discovery)
►▼ Show Figures

Figure 1

14 pages, 3345 KiB  
Article
Toward the Identification of Potential α-Ketoamide Covalent Inhibitors for SARS-CoV-2 Main Protease: Fragment-Based Drug Design and MM-PBSA Calculations
by Mahmoud A. El Hassab, Mohamed Fares, Mohammed K. Abdel-Hamid Amin, Sara T. Al-Rashood, Amal Alharbi, Razan O. Eskandrani, Hamad M. Alkahtani and Wagdy M. Eldehna
Processes 2021, 9(6), 1004; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9061004 - 05 Jun 2021
Cited by 21 | Viewed by 3212
Abstract
Since December 2019, the world has been facing the outbreak of the SARS-CoV-2 pandemic that has infected more than 149 million and killed 3.1 million people by 27 April 2021, according to WHO statistics. Safety measures and precautions taken by many countries seem [...] Read more.
Since December 2019, the world has been facing the outbreak of the SARS-CoV-2 pandemic that has infected more than 149 million and killed 3.1 million people by 27 April 2021, according to WHO statistics. Safety measures and precautions taken by many countries seem insufficient, especially with no specific approved drugs against the virus. This has created an urgent need to fast track the development of new medication against the virus in order to alleviate the problem and meet public expectations. The SARS-CoV-2 3CL main protease (Mpro) is one of the most attractive targets in the virus life cycle, which is responsible for the processing of the viral polyprotein and is a key for the ribosomal translation of the SARS-CoV-2 genome. In this work, we targeted this enzyme through a structure-based drug design (SBDD) protocol, which aimed at the design of a new potential inhibitor for Mpro. The protocol involves three major steps: fragment-based drug design (FBDD), covalent docking and molecular dynamics (MD) simulation with the calculation of the designed molecule binding free energy at a high level of theory. The FBDD step identified five molecular fragments, which were linked via a suitable carbon linker, to construct our designed compound RMH148. The mode of binding and initial interactions between RMH148 and the enzyme active site was established in the second step of our protocol via covalent docking. The final step involved the use of MD simulations to test for the stability of the docked RMH148 into the Mpro active site and included precise calculations for potential interactions with active site residues and binding free energies. The results introduced RMH148 as a potential inhibitor for the SARS-CoV-2 Mpro enzyme, which was able to achieve various interactions with the enzyme and forms a highly stable complex at the active site even better than the co-crystalized reference. Full article
(This article belongs to the Special Issue Frontiers in Computer-Aided Drug Discovery)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop