Several emerging and remerging viral infections, such as Coronavirus disease-19 (COVID-19), Nipah, Zika, West Nile, Middle East Respiratory Syndrome (MERS) and Ebola, have caused severe public health concerns within the past few decades. A number of these viruses have caused wide-spread outbreaks, resulting in high mortality and morbidity throughout the world. Though vaccines are available for some of these viral infections, there is a lack of potential and promising drug molecules against many emerging viruses. Thus, novel strategies and approaches for developing drugs against emerging and re-emerging viral infections is of upmost importance in addressing current and future disease outbreaks. Identification of potential molecular targets, screening of unexplored lead molecules from plants, microorganisms, and terrestrial environments and repurposing of existing drug molecules are some of the latest research areas in emerging viral infections drug discovery. Bioinformatics and computational biology approaches greatly help to reduce the complexities in the these conventional drug discovery pipelines. These data and omics-driven approaches include the identification of novel and potential molecular targets, prediction of the three-dimensional structures of these targets, interaction modelling and validation of potential molecular targets. The integration of data science with computational biology also helps to screen potential lead molecules with ideal drug likeliness, pharmacokinetic and toxicities features required for drug development. Computational modelling particularly provides significant insights into the experimental validation phase, reducing the time, cost, and other complexities associated with conventional drug discovery.
This Research Topic aims to provide an update on various aspects of drug discovery for emerging viral infections (such as COVID-19, Nipah, Zika, West Nile, Middle East Respiratory Syndrome (MERS), and Ebola) that utilize data science, computational biology, bioinformatics, and integrated omics approaches. The overall goal is to highlight cutting-edge research exploring novel in silico drug discovery approaches that can be scaled-up to a further experimental level.
This Research Topic encourages Original Research, Reviews and Mini-Reviews on the following (but not limited to) topics:
• Prediction and construction of metabolic networks of emerging viral pathogens
• Screening of mutational variants of existing viral targets and their structural analysis
• Prediction of novel molecular targets for emerging viral infections
• Interaction modelling of potential molecular targets against emerging viral diseases
• Screening of novel lead molecules with ideal drug likeliness, pharmacokinetics, toxicities from natural origin or by chemical biology approaches
• Conformational studies of the interaction modelling of novel lead molecules and their targets
• Application of repurposed drugs against emerging viral infections by in silico approach
• Molecular dynamic simulations and energy calculation assessment of the interaction modelling of novel lead molecules and viral targets.
• Data sciences (machine learning and artificial intelligence) towards drug discovery for emerging viral infections
• Scope of in silico prediction in drug development of emerging viral infections.
Several emerging and remerging viral infections, such as Coronavirus disease-19 (COVID-19), Nipah, Zika, West Nile, Middle East Respiratory Syndrome (MERS) and Ebola, have caused severe public health concerns within the past few decades. A number of these viruses have caused wide-spread outbreaks, resulting in high mortality and morbidity throughout the world. Though vaccines are available for some of these viral infections, there is a lack of potential and promising drug molecules against many emerging viruses. Thus, novel strategies and approaches for developing drugs against emerging and re-emerging viral infections is of upmost importance in addressing current and future disease outbreaks. Identification of potential molecular targets, screening of unexplored lead molecules from plants, microorganisms, and terrestrial environments and repurposing of existing drug molecules are some of the latest research areas in emerging viral infections drug discovery. Bioinformatics and computational biology approaches greatly help to reduce the complexities in the these conventional drug discovery pipelines. These data and omics-driven approaches include the identification of novel and potential molecular targets, prediction of the three-dimensional structures of these targets, interaction modelling and validation of potential molecular targets. The integration of data science with computational biology also helps to screen potential lead molecules with ideal drug likeliness, pharmacokinetic and toxicities features required for drug development. Computational modelling particularly provides significant insights into the experimental validation phase, reducing the time, cost, and other complexities associated with conventional drug discovery.
This Research Topic aims to provide an update on various aspects of drug discovery for emerging viral infections (such as COVID-19, Nipah, Zika, West Nile, Middle East Respiratory Syndrome (MERS), and Ebola) that utilize data science, computational biology, bioinformatics, and integrated omics approaches. The overall goal is to highlight cutting-edge research exploring novel in silico drug discovery approaches that can be scaled-up to a further experimental level.
This Research Topic encourages Original Research, Reviews and Mini-Reviews on the following (but not limited to) topics:
• Prediction and construction of metabolic networks of emerging viral pathogens
• Screening of mutational variants of existing viral targets and their structural analysis
• Prediction of novel molecular targets for emerging viral infections
• Interaction modelling of potential molecular targets against emerging viral diseases
• Screening of novel lead molecules with ideal drug likeliness, pharmacokinetics, toxicities from natural origin or by chemical biology approaches
• Conformational studies of the interaction modelling of novel lead molecules and their targets
• Application of repurposed drugs against emerging viral infections by in silico approach
• Molecular dynamic simulations and energy calculation assessment of the interaction modelling of novel lead molecules and viral targets.
• Data sciences (machine learning and artificial intelligence) towards drug discovery for emerging viral infections
• Scope of in silico prediction in drug development of emerging viral infections.
