In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

The infection of a novel coronavirus found in Wuhan of China (2019-nCoV) is rapidly spreading, and the incidence rate is increasing worldwide. Due to the lack of effective treatment options for 2019-nCoV, various strategies are being tested in China, including drug repurposing. In this study, we used our pretrained deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI) to identify commercially available drugs that could act on viral proteins of 2019-nCoV. The result showed that atazanavir, an antiretroviral medication used to treat and prevent the human immunodeficiency virus (HIV), is the best chemical compound, showing a inhibitory potency with Kd of 94.94 nM against the 2019-nCoV 3C-like proteinase, followed by efavirenz (199.17 nM), ritonavir (204.05 nM), and dolutegravir (336.91 nM). Interestingly, lopinavir, ritonavir, and darunavir are all designed to target viral proteinases. However, in our prediction, they may also bind to the replication complex components of 2019-nCoV with an inhibitory potency with Kd < 1000 nM. In addition, we also found that several antiviral agents, such as Kaletra, could be used for the treatment of 2019-nCoV, although there is no real-world evidence supporting the prediction. Overall, we suggest that the list of antiviral drugs identified by the MT-DTI model should be considered, when establishing effective treatment strategies for 2019-nCoV.
China through a drug-target interaction deep learning model

The present study describes the development of SYBR Green based real-time polymerase chain reaction (real-time PCR) for detection and quantitation of canine parvovirus type 2 (CPV 2) in faecal samples of dogs. In this assay, the primers were designed and custom-synthesized based on nucleotide sequence of VP2 gene of CPV 2. A standard curve was plotted using 10-fold serial dilution of standard plasmid DNA and Ct value. The standard curve was found to be linear over a 10 −7 dilution. The real-time PCR results were expressed as the number of DNA copies of CPV 2 per mg of faecal samples and showed range of 1.0 × 10 3 to 7.0 × 10 9 copies of viral DNA per mg of stool samples. The analytical sensitivity of the SYBR Green based real-time PCR was shown to be equivalent to 10 copies. Faecal samples (47) from dogs suspected of CPV 2 infection were analyzed by real-time PCR, haemagglutination (HA) assay and by a conventional PCR and 24, 20 and 22 samples were found positive for CPV 2, respectively. Comparison between the results of three different assays revealed that real-time PCR is more sensitive than HA and conventional PCR and allow the detection of low titers of CPV 2 in infected dogs.
Development of a SYBR Green based real-time PCR assay for detection and quantitation of canine parvovirus in faecal samples

The discovery of epitopes is helpful to the development of SARS-CoV-2 vaccine. The sequences of the surface protein of SARS-CoV-2 and its proximal sequences were obtained by BLAST, the sequences of the whole genome of SARS-CoV-2 were obtained from the GenBank. Based on the NCBI Reference Sequence: NC_045512.2, the conformational and linear B cell epitopes of the surface protein were predicted separately by various prediction methods. Furthermore, the conservation of the epitopes, the adaptability and other evolutionary characteristics were also analyzed. 7 epitopes were predicted, including 5 linear epitopes and 2 conformational epitopes, one of the linear and one of the conformational were coincide. The epitope D mutated easily, but the other epitopes were very conservative and the epitope C was the most conservative. It is worth mentioning that all of the 6 dominated epitopes were absolutely conservative in nearly 1000 SARS-CoV-2 genomes, and they deserved further study. The findings would facilitate the vaccine development, had the potential to be directly applied on the treatment in this disease, but also have the potential to prevent the possible threats caused by other types of coronavirus. Results The primary structure and physicochemical properties of the S/E/M protein were analyzed. The results revealed that the S protein has an average hydrophilic index of -author/funder. All rights reserved. No reuse allowed without permission. : bioRxiv preprint 0.079( Figure S1A ). On the basis of hydrophilicity, it also showed amphoteric properties. There was an outside-in transmembrane helix in 23 residues from position 1214 th to position 1236 th at the N-terminal( Figure S2A ). The protein instability index was 33.01, which revealed the S protein was stable. The E protein has an average hydrophilic index of 1.128( Figure S1B ). It was hydrophobic. An inside-out transmembrane helix in 23 residues from position 12 th to position 34 th at the N-terminal was predicted( Figure S2B ). The protein instability index was 38.68, which revealed the E protein was stable. The M protein has an average hydrophilic index of 0.446( Figure   S1C ). On the basis of hydrophobicity, it also showed amphoteric properties. There were two outside-in transmembrane helices, one was in 20 residues from position 20 th to position 39 th , the another one was in 23 residues from position 78 th to position 100 th , and an inside-out transmembrane helix in 20 residues from position 51 st to position 73 rd , at the N-terminal( Figure S2C ). The protein instability index was 39.14, which revealed the M protein was stable. The optimal template for homology modeling of the S protein of SARS-CoV-2 was the S protein of SARS(PDB ID: 6acc.1), with the sequence identity of 76.47% and the GMQE score of 0.73. According to the evaluation of the structure by Ramachandran plot (Figure 1A) , 99.3% of the residues were located in the most favoured regions and the allowed regions, 0.7% of the residues were located in the disallowed regions, the high-energy regions (Table 1) , which was possibly due to some energy was spent in the protein processing to make these residues enter the high-energy regions [5] . The result generally showed that the structure was reliable. The structure of S protein( Figure 1B) of SARS-CoV-2 is a trimer, which can be divided into a tightly curled tail and a distributed head. The head is mainly composed of β-sheet, irregular curl and turn, which is exposed to the envelope of the virus, contributes to the formation of epitopes. The tail is mainly composed of several α-helices, part of which is embedded in the envelope, hinders the formation of epitopes. The optimal template for homology modeling of the E protein of SARS-CoV-2 was the E protein of SARS(PDB ID: 5x29.1), with the sequence identity of 91.38% and author/funder. All rights reserved. No reuse allowed without permission.

Prediction and Evolution of B Cell Epitopes of Surface Protein in SARS-CoV-2