Chitosan Derivatives as Carriers for Drug Delivery and Biomedical Applications.

Over the past few decades, chitosan (CS) has gained the attention of researchers investigating newer biomaterial-based carriers for drugs in pharmaceutical and biomedical research. Combined with its nontoxic behavior, biodegradability, and biocompatibility, chitosan has found widespread applications in the fields of drug delivery, tissue engineering, and cosmetics. As a novel drug carrier, chitosan is regarded as one of the promising biomaterials in the pharmaceutical industry. The extensive use of this cationic biopolysaccharide in the delivery of therapeutic agents has brought a few limitations of chitosan into the limelight. Various chemical modifications of chitosan can minimize these limitations and improve the efficacy of chitosan as a drug carrier. The effectiveness of several chemically modified chitosan derivatives, including trimethyl chitosan, thiolated chitosan, PEGylated chitosan, and other chitosan derivatives, has been investigated by many researchers for the controlled and target specific delivery of therapeutics. The chemically modified chitosan derivatives exhibited greater importance in the current scenario on drug delivery due to their solubility in wide range of media along with their interaction with pharmaceutically active ingredients. Chitosan derivatives have also attracted attention in several biomedical fields, including wound healing, hyperthermia therapy, tissue engineering, and bioadhesives. The present review narrates the sources and common physicochemical properties of chitosan, including several important synthetic modifications to obtain chemically modified chitosans and their applications in target-specific drug delivery, along with several biomedical applications.

QSAR modeling of algal low level toxicity values of different phenol and aniline derivatives using 2D descriptors.

The deposition of different types of phenol and aniline derivatives in the aquatic environment leads to toxicity to living organisms. Under such condition, evaluation of these toxicants is very much important. Due to non-availability of sufficient experimental data as well as sufficient number of Quantitative Structure-Activity Relationship (QSAR) models for the low level toxicity values for such pollutants, we have employed here the partial least squares (PLS) regression for the development of robust and predictive QSAR models using low level toxicity values against algal species. Here, we have used both Extended Topochemical Atom (ETA) and non-ETA indices as 2D descriptors for model development. The statistical validation parameters ensure the robustness and the predictivity of the developed models. From the insights of the final PLS models, it can be concluded that presence of nitro groups (in the ortho position to phenolic hydroxyl group increasing intramolecular hydrogen bonding capacity), presence of chlorine substituents (influencing lipophilicity) especially at the para position, oxygen and nitrogen at the topological distance three, aliphatic side chain (contributing to hydrophobicity), molecules with large size atoms and higher molecular bulk will increase the toxicity towards the algal species. On the other hand, the phenol ring without any substituent or with a polar substituent (like amino group), presence of chlorine at ortho-ortho or ortho-para position, absence of nitro group, presence of chlorine and oxygen at the topological distance three, presence of lower number of aliphatic groups will decrease the toxic effect towards the algal species.

QSAR modeling with ETA indices for cytotoxicity and enzymatic activity of diverse chemicals.

The discharge of huge amount of chemicals from industries into the environment has led to toxicity towards different living species. Therefore, risk assessment of these chemicals is essential. In order to comply with the ethical issues, in this present work, we have developed quantitative structure-activity relationship (QSAR) models for cytotoxicity against GFS (goldfish scale) tissue (Crassius auratus) and enzymatic activity against PLHC-1 cell line (topminnow hepatoma cell line) (Poeciliopsis lucida). The final models were developed by means of PLS (Partial Least Squares) regression method applying only ETA (extended topochemical atom) descriptors. The results obtained from various validation parameters (obtained from the both datasets) suggested that the developed models are statistically robust and predictive. From the insights obtained from the models developed from the Neutral Red dye (NR) dataset, it can be concluded that presence of bulky atoms, unsaturation, branching and hetero atoms (most importantly N, Cl) enhance the cytotoxicity towards the Goldfish scale tissue. On the other hand, in case of the Ethoxyresorufin-O-deethylase (EROD) dataset, presence of higher electronegative atoms (O, Cl), polycyclic aromatic hydrocarbons (PAHs) with more number of rings and absence of polar groups and hydrogen bond acceptors enhance enzymatic activity of the PLHC-1 cell line.