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".

[Q]: Paragraph: Hepatitis C Virus (HCV) infects 2% of the world's population and is the leading cause of liver disease and liver transplantation. It poses a serious and growing worldwide public health problem that will only be partially addressed with the introduction of new antiviral therapies. However, these treatments will not prevent re-infection particularly in high risk populations. The introduction of a HCV vaccine has been predicted, using simulation models in a high risk population, to have a significant effect on reducing the incidence of HCV. A vaccine with 50 to 80% efficacy targeted to high-risk intravenous drug users could dramatically reduce HCV incidence in this population. Virus like particles (VLPs) are composed of viral structural proteins which self-assemble into non-infectious particles that lack genetic material and resemble native viruses. Thus, VLPs represent a safe and highly immunogenic vaccine delivery platform able to induce potent adaptive immune responses. Currently, many VLP-based vaccines have entered clinical trials, while licensed VLP vaccines for hepatitis B virus (HBV) and human papilloma virus (HPV) have been in use for many years. The HCV core, E1 and E2 proteins can self-assemble into immunogenic VLPs while inclusion of HCV antigens into heterogenous (chimeric) VLPs is also a promising approach. These VLPs are produced using different expression systems such as bacterial, yeast, mammalian, plant, or insect cells. Here, this paper will review HCV VLP-based vaccines and their immunogenicity in animal models as well as the different expression systems used in their production. 
 Title: Preclinical Development and Production of Virus-Like Particles As Vaccine Candidates for Hepatitis C
[A]: True


[Q]: Paragraph: Next year will mark the 100th anniversary of the Michaelis-Menten equation [1], one of the most important and well known models in enzymology. Remarkable progress in enzymology over the past hundred years has not only provided deep insight into biological processes, but also has dramatically changed our lives. However, because of limitations in available techniques, enzymologists primarily investigate the in vitro properties and catalytic mechanisms of individual enzymes. Thus, they often fail to address a fundamental scientific question: how are biological processes, most of which are chemical reactions catalyzed by enzymes, coordinated in space and time to produce a living organism [2]? Fortunately, applications of new techniques and, in particular, wide acceptance of the idea of systems have enabled enzymologists to begin studying enzymes in the context of dynamic, complicated biological systems in recent years. Many excellent reviews and research articles on enzymology have been published in the past few years. These articles highlight the latest developments in enzymology, and should prove helpful for understanding how to best integrate the idea of systems into enzymology research. In living organisms, protein post-translational modification (PTM) pathways are large and interconnected networks. Via reversible or irreversible covalent modifications, allo-steric regulations of PTM enzymes and cross-talk of PTM pathways, PTM networks enable organisms to respond to stimuli faster than is possible through gene transcription regulation. Therefore, PTM enzymes, as key nodes of biological networks, are a recent focus of attention. 
 Title: SCIENCE CHINA A glimpse of enzymology within the idea of systems
[A]: False


[Q]: Paragraph: The human severe acute respiratory syndrome coronavirus (SARS-CoV) and the NL63 coronaviruses are human respiratory pathogens for which no effective antiviral treatment exists. The papain-like cysteine proteases encoded by the coronavirus (SARS-CoV: PLpro; NL63: PLP1 and PLP2) represent potential targets for antiviral drug development. Three recent inhibitor-bound PLpro structures highlight the role of an extremely flexible six-residue loop in inhibitor binding. The high binding site plasticity is a major challenge in computational drug discovery/design efforts. From conventional molecular dynamics and accelerated molecular dynamics (aMD) simulations, we find that with conventional molecular dynamics simulation, PLpro translationally samples the open and closed conformation of BL2 loop on a picosecond-nanosecond timescale but does not reproduce the peptide bond inversion between loop residues Tyr269 and Gln270 that is observed on inhibitor GRL0617 binding. Only aMD simulation, starting from the closed loop conformation, reproduced the 180°ϕ-ψ dihedral rotation back to the open loop state. The Tyr-Gln peptide bond inversion appears to involve a progressive conformational change of the full loop, starting at one side, and progressing to the other. We used the SARS-CoV apo X-ray structure to develop a model of the NL63-PLP2 catalytic site. Superimposition of the PLP2 model on the PLpro X-ray structure identifies binding site residues in PLP2 that contribute to the distinct substrate cleavage site specificities between the two proteases. The topological and electrostatic differences between the two protease binding sites also help explain the selectivity of non-covalent PLpro inhibitors. 
 Title: Comparison of SARS and NL63 Papain-Like Protease Binding Sites and Binding Site Dynamics: Inhibitor Design Implications
[A]:
True