In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

Paragraph: Italy is currently experiencing the largest COVID-19 outbreak in Europe so far, with more than 100,000 confirmed cases. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing number of restrictions aimed at containing the outbreak and delaying the epidemic peak. Since March 12, the whole country is under lockdown. Here we provide the first quantitative assessment of the impact of such measures on the mobility and the spatial proximity of Italians, through the analysis of a large-scale dataset on deidentified, geo-located smartphone users. With respect to pre-outbreak averages, we estimate a reduction of 50% of the total trips between Italian provinces, following the lockdown. In the same week, the average users' radius of gyration has declined by about 50% and the average degree of the users' proximity network has dropped by 47% at national level. 
 Title: COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown
True

Paragraph: For more than 30 years X-ray crystallography has been by far the most powerful approach for determining the structures of viruses and viral proteins at atomic resolution. The information provided by these structures, which covers many important aspects of the viral life cycle such as cell-receptor recognition, viral entry, nucleic acid transfer and genome replication, has extensively enriched our vision of the virus world. Many of the structures available correspond to potential targets for antiviral drugs against important human pathogens. This article provides an overview of the current knowledge of different structural aspects of the above-mentioned processes. 
 Title: BIOLOGYjMEDICINE Viruses and viral proteins
True

Paragraph: In many biological systems, proteins interact with other organic molecules to produce indispensable functions, in which molecular recognition phenomena are essential. Proteins have kept or gained their functions during molecular evolution. Their functions seem to be flexible, and a few amino acid substitutions sometimes cause drastic changes in function. In order to monitor and predict such drastic changes in the early stages in target populations, we need to identify patterns of structural changes during molecular evolution causing decreases or increases in the binding affinity of protein complexes. In previous work, we developed a likelihood-based index to quantify the degree to which a sequence fits a given structure. This index was named the sequence-structure fitness (SSF) and is calculated empirically based on amino acid preferences and pairwise interactions in the structural environment present in template structures. In the present work, we used the SSF to develop an index to measure the binding affinity of protein-protein complexes defined as the log likelihood ratio, contrasting the fitness of the sequences to the structure of the complex and that of the uncomplexed proteins. We applied the developed index to the complexes formed between influenza A hemagglutinin (HA) and four antibodies. The antibody-antigen binding region of HA is under strong selection pressure by the host immune system. Hence, examination of the long-term adaptation of HA to the four antibodies could reveal the strategy of the molecular evolution of HA. Two antibodies cover the HA receptor-binding region, while the other two bind away from the receptor-binding region. By focusing on branches with a significant decline in binding ability, we could detect key amino acid replacements and investigate the mechanism via conditional probabilities. The contrast between the adaptations to the two types of antibodies suggests that the virus adapts to the immune system at the cost of structural change. 
 Title: A Likelihood-based Index of Protein-Protein Binding Affinities with Application to Influenza HA Escape from Antibodies

False