Antimicrobial Peptides (AMPs) have been considered as potential alternatives for infection therapeutics since antibiotic resistance has been raised as a global problem. The AMPs are a group of natural peptides that play a crucial role in the immune system in various organisms AMPs have features such as a short length and efficiency against microbes. Importantly, they have represented low toxicity in mammals which makes them potential candidates for peptide-based drugs. Nevertheless, the discovery of AMPs is accompanied by several issues which are associated with labour-intensive and time-consuming wet-lab experiments. During the last decades, numerous studies have been conducted on the investigation of AMPs, either natural or synthetic type, and relevant data are recently available in many databases. Through the advancement of computational methods, a great number of AMP data are obtained from publicly accessible databanks, which are valuable resources for mining patterns to design new models for AMP prediction. However, due to the current flaws in assessing computational methods, more interrogations are warranted for accurate evaluation/analysis. Considering the diversity of AMPs and newly reported ones, an improvement in Machine Learning algorithms are crucial. In this review, we aim to provide valuable information about different types of AMPs, their mechanism of action and a landscape of current databases and computational tools as resources to collect AMPs and beneficial tools for the prediction and design of a computational model for new active AMPs.

Effects of magnetic fields (MFs) on the activities of antioxidant enzymes of suspension‐cultured tobacco cells were investigated. Compared with the control cells, exposure of the cells to static MF with the magnitudes of 10 and 30 mT for 5 days, 5 h each day, increased the activity of superoxide dismutase (SOD). In contrast, the activity of the catalase (CAT) and ascorbate peroxidase (APX) was decreased by MF, compared with those of the control cells. Level of lipid peroxidation was also increased by MF. It suggests that MF could deteriorate antioxidant defense system of plant cells. Bioelectromagnetics.

Exposure to magnetic field (MF) can affect cellular metabolism remotely. Cardio-toxic effects of Doxorubicin (DOXO) have limited clinical uses at high dose. MF due to its effect on reactive oxygen species (ROS) lifetime, may provide a suitable choice to boost the efficacy of this drug at low dose. Here, we investigated the potential effects of homogenous static magnetic field (SMF) on DOXO-induced toxicity and proliferation rate of cancer cells. The results indicated that SMF similar to DOXO decreased the cell viability as well as the proliferation rate of MCF-7 and HFF cells. Moreover, combination of 10 mT SMF and 0.1 µM DOXO decreased the viability and proliferation rate of cancer and normal cells in a synergetic manner. In spite of high a GSH level in cancer cell, SMF boosts the generation and lifetime of ROS at low dose of DOXO, and overcame to GSH mediated drug resistance. The results also confirmed that SMF exposure decreased 50% iron content of cells, which is attributed to iron homeostasis. In conclusion, these findings suggest that SMF can decrease required dose of chemotherapy drugs such as DOXO and thereby decrease their side effect.