Liposomes have been attracted considerable attention as phospholipid spherical vesicles, over the past 40 years. These lipid vesicles are valued in biomedical application due to their ability to carry both hydrophobic and hydrophilic agents, high biocompatibility and biodegradability. Various methods have been used for the synthesis of liposomes, so far and numerous modifications have been performed to introduce liposomes with different characteristics like surface charge, size, number of their layers, and length of circulation in biological fluids. This article provides an overview of the significant advances in synthesis of liposomes via active or passive drug loading methods, as well as describes some strategies developed to fabricate their targeted formulations to overcome limitations of the "first-generation" liposomes.
Position-specific Scoring Matrix (PSSM), also called profile, is broadly used for representing the evolutionary history of a given protein sequence. Several investigations reported that the PSSM-based feature descriptors can improve the prediction of various protein attributes such as interaction, function, subcellular localization, secondary structure, disorder regions, accessible surface area, etc. While plenty of algorithms have been suggested for extracting evolutionary features from PSSM in recent years, there is not any integrated standalone tool for providing these descriptors. Here, we introduce PSSMCOOL, a flexible comprehensive R package that generates 38 PSSM-based feature vectors. To our best knowledge, PSSMCOOL is the first PSSM-based feature extraction tool implemented in R. With the growing demand for exploiting machine learning algorithms in computational biology, this package would be a practical tool for machine learning predictions.
Availability
https://cran.r-project.org/web/packages/PSSMCOOL/index.html, https://github.com/BioCool-Lab/PSSMCOOL
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