Antiviral Methods and Protocols

Gong, Edwin Yunhao

doi:10.1007/978-1-62703-484-5

Cited by 8 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The analog, compound 6, had an improved antiviral activity as it inhibited MNV and the HuNoV GI.1 replicon with EC 50 values around 0.2 µM and 1.7 µM, respectively. In addition, compound 6 had a better antiviral effect against MNV and the HuNoV GI.1 replicon than 2CMC, which is currently used as the benchmark antiviral compound in norovirus research [13,14].…”

Section: Discussionmentioning

confidence: 99%

“…We determined that compound 6 acts at a post-entry step, most likely acting at the time viral genome replication starts. In fact, the presence of compound 6 is required at the same time points as that of the nucleoside analog 2CMC [14]. Hence, the first hypothesis was that compound 6 was also an RdRp targeting compound.…”

Section: Discussionmentioning

confidence: 99%

“…To assess whether resistant variants to compound 6 would easily arise (thus the class of compounds would have a low barrier to resistance) or if many passages (months) and multiple mutations would be required to confer resistance to the compound (high barrier to resistance), we passaged the virus in the presence of compound 6 up to 30 consecutive times [15][16][17][18][19]. The latter indicates a high barrier to resistance similar to 2CMC [14]. Out of the three mutants independently selected, two mutants (1 and 3) showed a reasonable shift in EC 50 against compound 6 (6-8 fold).…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Discovery of a Novel Class of Norovirus Inhibitors with High Barrier of Resistance

et al. 2021

View full text Add to dashboard Cite

Human noroviruses (HuNoVs) are the most common cause of viral gastroenteritis resulting in ~219,000 deaths annually and a societal cost of ~USD60 billion. There are no antivirals or vaccines available to treat and/or prevent HuNoV. In this study, we performed a large-scale phenotypical antiviral screening using the mouse norovirus (MNV), which included ~1000 drug-like small molecules from the Drug Design and Synthesis Centre (Sapienza University, Rome). Compound 3‑((3,5-dimethylphenyl)sulfonyl)-5-chloroindole-N-(phenylmethanol-4-yl)-2.carboxamide (compound 1) was identified as an inhibitor of MNV replication with an EC50 of 0.5 ± 0.1 µM. A series of 10 analogs were synthesized of which compound 6 showed an improved potency/selectivity (EC50 0.2 ± 0.1 µM) against MNV; good activity was also observed against the HuNoV GI replicon (EC50 1.2 ± 0.6 µM). Time-of-drug-addition studies revealed that analog 6 acts at a time point that coincides with the onset of viral RNA replication. After six months of selective pressure, two compound 6res variants were independently selected, both harboring one mutation in VPg and three mutations in the RdRp. After reverse engineering S131T and Y154F as single mutations into the MNV backbone, we did not find a markedly compound 6res phenotype. In this study, we present a class of novel norovirus inhibitors with a high barrier to resistance and in vitro antiviral activity.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Discovery of a Novel Class of Norovirus Inhibitors with High Barrier of Resistance

et al. 2021

View full text Add to dashboard Cite

show abstract

Bacteria Inspired Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

View full text Add to dashboard Cite

In this chapter, we present a set of algorithms that are inspired by the different bacteria behavioural patterns, i.e., bacterial foraging algorithm (BFA), bacterial colony chemotaxis (BCC) algorithm, superbug algorithm (SuA), bacterial colony optimization (BCO) algorithm, and viral system (VS) algorithm. We first describe the general knowledge of bacteria foraging behaviour in Sect. 2.1. Then, the fundamentals and performances of BFA, BCC algorithm, SuA, BCO algorithm, and VS algorithm are introduced in Sects. 2.2 and 2.3, respectively. Finally, Sect. 2.4 summarises this chapter.

show abstract