Cell-penetrating peptides (CPPs) promote the transport of pharmacologically active molecules, such as nanoparticles, plasmid DNA and short interfering RNA. Accurate prediction of new CPPs is a prerequisite for in-depth study of such molecules. Biological experimental predictions can provide an accurate description of the penetrating properties of CPPs. However, predicting CPPs by wet laboratory experiments is both resource-intensive and time-consuming. Therefore, the development of effective calculation method prediction has become an important topic in the study of CPPs. Recently, numerous methods developed for predicting CPPs use amino acid composition, alone and the accuracies of such methods have been limited. In this study, we proposed a new CPP prediction framework, which integrates four amino acid composition features, and utilizes these features to help train Support Vector Machine (SVM) model as a classifier to predict CPPs. When performing on the training dataset CPP924, the proposed method achieves an accuracy of 92.3%, which is significantly better than the state-of-the-art methods. These results suggest that the framework can orchestrate various amino acid composition features predicted models flexibly with good performances.

Non-small cell lung cancer remains the leading cause of cancer-related deaths worldwide with high morbidity and mortality. There is an urgent need to reveal new molecular mechanisms that contribute to NSCLC progression to facilitate drug development and to improve overall survival. Much attention has been paid to the role of circRNAs in NSCLC development. However, the knowledge of circRNAs in NSCLC is still limited, and need to be further explored. The dysregulation of circACC1 was evaluated by qRT-PCR in NSCLC samples and cell lines. The oncogenic role of circACC1 in NSCLC progression was analyzed by CCK8 and colony formation assays. The interaction between the circACC1 and miR-29c-3p, as well as MCL-1, was verified by qRT-PCR, Western blot, luciferase reporter assay, and RIP experiment. Elevated levels of circACC1 were found in NSCLC patients and were negatively correlated with OS. Ectopic expression of circACC1 promoted the capacity of cell growth and clonogenicity, while the inhibition of circACC1 decreased the proliferation and clonogenicity potential. Mechanism studies elucidated that circACC1 contributes to cell growth via directly binding to miR-29c-3p. Transfection of miR-29c-3p mimic blocked circACC1 mediated NSCLC cell proliferation. MCL-1 is a downstream target of miR-29c-3p in NSCLC cells. The circACC1/miR-29c-3p/MCL-1 axis is important in NSCLS proliferation.