Developing Therapeutics for COVID-19 and Other Viral Infections Using Physics Based and Data-Driven Approaches
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: closed (31 August 2023)
Special Issue Editors
Interests: computational chemistry; developing scripts; web portals and algorithms for drug discovery; non-covalent interactions; bioinformatics; chemoinformatics
Special Issues, Collections and Topics in MDPI journals
Interests: molecular crystals; temperature and pressure induced phase transitions; monte carlo simulation; molecular dynamics simulations; Orientational and conformational disorder in molecular crystals
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
COVID-19, caused by the SARS-CoV-2 virus, has become the most devastating health care challenge of this century. The outbreaks caused by SARS and MERS coronaviruses, swine- and avian-origin influenza, and Ebola and Zika viruses cannot be overlooked. At the same time, we cannot help but admire the progress made by scientists in the field of experimental and computational drugs and diagnostics development during the last few decades. Evidently, when mankind is in grave danger, as in the current crisis, one must focus on acquiring the appropriate knowledge to tackle the disaster. Since the arrival of computers in our lives and in almost every branch of science, the importance of computational modeling and data science is evident. In particular, significant progress has been made in high-throughput screening and in the development of reliable and fast computational scoring/ranking approaches for lead compound identification from extensive chemical libraries that contain compounds in the order of 106 to 1012. Given that multidrug-resistant variants of viruses emerge over time and certain viruses such as SARS-CoV-2 have the potential to mutate at a faster rate, computational approaches to diagnosis and therapeutics are in high demand when compared to their experimental counterparts, which are time-consuming, very expensive, and not economically sustainable. This Special Issue is devoted to promoting research in the area of the computational development of diagnostics and therapeutics for COVID-19 and other associated viral infections. We recommend the submission of articles in which the results from computational screening (molecular docking) or de novo design are validated using either experimental techniques or by employing more accurate and reliable approaches with superior ranking potential. In particular, we encourage authors to submit articles based on computational approaches for identifying lead compounds that employ scoring functions based on the electronic structure theory, machine learning, or deep learning. Regarding the design of diagnostic compounds, this area is not limited to optical or infrared probes, but can also include studies devoted to diagnostic platforms that use biosensors and bioelectronics.
Prof. Dr. G. Narahari Sastry
Prof. Dr. Natarajan Arul Murugan
Guest Editors
Manuscript Submission Information
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Keywords
- COVID-19
- SARS-CoV-2
- machine learning
- virtual screening
- molecular docking
- binding
- free-energy calculations
- druggabiliy prediction
