Self-activating chitosan-based nanoparticles for sphingosin-1 phosphate modulator delivery and selective tumor therapy.

This study reports on the design and synthesis of hypoxia responsive nanoparticles (HRNPs) composed of methoxy polyethylene glycol-4,4 dicarboxylic azolinker-chitosan (mPEG-Azo-chitosan) as ideal drug delivery platform for Fingolimod (FTY720, F) delivery to achieve selective and highly enhanced TNBC therapy in vivo. Herein, HRNPs with an average size of 49.86 nm and a zeta potential of +3.22 mV were synthetized, which after PEG shedding can shift into a more positively-charged NPs (+30.3 mV), possessing self-activation ability under hypoxia situation in vitro, 2D and 3D culture. Treatment with lower doses of HRNPs@F significantly reduced MDA-MB-231 microtumor size to 15 %, induced apoptosis by 88 % within 72 h and reduced highly-proliferative 4 T1 tumor weight by 87.66 % vs. ∼30 % for Fingolimod compared to the untreated controls. To the best of our knowledge, this is the first record for development of hypoxia-responsive chitosan-based NPs with desirable physicochemical properties, and selective self-activation potential to generate highly-charged nanosized tumor-penetrating chitosan NPs. This formulation is capable of localized delivery of Fingolimod to the tumor core, minimizing its side effects while boosting its anti-tumor potential for eradication of TNBC solid tumors.

Molecular targets, therapeutic agents and multitasking nanoparticles to deal with cancer stem cells: A narrative review.

There is increasing evidence that malignant tumors are initiated and maintained by a sub-population of tumor cells that have similar biological properties to normal adult stem cells. This very small population of Cancer Stem Cells (CSC) comprises tumor initiating cells responsible for cancer recurrence, drug resistance and metastasis. Conventional treatments such as chemotherapy, radiotherapy and surgery, in addition to being potentially toxic and non-specific, may paradoxically increase the population, spread and survival of CSCs. Next-generation sequencing and omics technologies are increasing our understanding of the pathways and factors involved in the development of CSCs, and can help to discover new therapeutic targets against CSCs. In addition, recent advances in nanomedicine have provided hope for the development of optimal specific therapies to eradicate CSCs. Moreover, the use of artificial intelligence and nano-informatics can elucidate new drug targets, and help to design drugs and nanoparticles (NPs) to deal with CSCs. In this review, we first summarize the properties of CSCs and describe the signaling pathways and molecular characteristics responsible for the emergence and survival of CSCs. Also, the location of CSCs within the tumor and the effect of host factors on the creation and maintenance of CSCs are discussed. Newly discovered molecular targets involved in cancer stemness and some novel therapeutic compounds to combat CSCs are highlighted. The optimum properties of anti-CSC NPs, including blood circulation and stability, tumor accumulation and penetration, cellular internalization, drug release, endosomal escape, and aptamers designed for specific targeting of CSCs are covered. Finally, some recent smart NPs designed for therapeutic and theranostic purposes to overcome CSCs are discussed.

Deciphering anti-biofilm property of Arthrospira platensis-origin peptides against Staphylococcusaureus.

Arthrospira platensis is a valuable natural health supplement consisting of various types of vitamins, dietary minerals, and antioxidants. Although different studies have been conducted to explore the hidden benefits of this bacterium, its antimicrobial property has been poorly understood. To decipher this important feature, here, we extended our recently introduced optimization algorithm (Trader) for aligning amino acid sequences associated with the antimicrobial peptides (AMPs) of Staphylococcus aureus and A.platensis. As a result, similar amino acid sequences were identified, and several candidate peptides were generated accordingly. The obtained peptides were then filtered based on their potential biochemical and biophysical properties, and their 3D structures were simulated based on homology modeling techniques. Next, to investigate how the generated peptides can interact with S. aureus proteins (i.e., heptameric state of the hly and homodimeric form of the arsB), molecular docking approaches were used. The results indicated that four peptides included better molecular interactions relative to the other generated ones in terms of the number/average length of hydrogen bonds and hydrophobic interactions. Based on the outcomes, it can be concluded that the antimicrobial property of A.platensis might be associated with its capability in disturbing the membrane of pathogens and their functions.

Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries.

To attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed.