Synthesis and biological evaluation of novel mono- and bivalent ASGP-R-targeted drug-conjugates

Pharmaceutical Strategies to Improve Druggability of Potential Drug Candidates in Nonalcoholic Fatty Liver Disease Therapy

Nonalcoholic fatty liver disease (NAFLD) has become globally prevalent and is the leading cause of chronic liver disease. Although NAFLD is reversible without medical intervention in the early stage, the condition could be sequentially worsened to nonalcoholic steatohepatitis (NASH) and, eventually, cirrhosis and hepatic cancer. The progression of NAFLD is related to various factors such as genetics, pre-disposed metabolic disorders, and immunologic factors. Thankfully, to date, there have been accumulating research efforts and, as a result, different classes of potent drug candidates have been discovered. In addition, there have also been various attempts to explore pharmaceutical strategies to improve the druggability of drug candidates. In this review, we provided a brief overview of the drug candidates that have undergone clinical trials. In the latter part, strategies for developing better drugs are discussed.

Design and synthesis of atorvastatin derivatives with enhanced water solubility, hepatoselectivity and stability

Statins are effective 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-R) inhibitors, which are successfully used for cardiovascular disease treatment. Statins' side effects are generally attributed to poor bioavailability and hepatoselectivity, which are closely related to their high lipophilicity. Targeted delivery of statins to the liver is considered as a way to reduce unwanted side effects. Herein we report on synthesis and evaluation of atorvastatin conjugates targeting the galactose-specific hepatic asialoglycoprotein receptor (ASGPR). The prepared conjugates showed greater water solubility compared to unmodified atorvastatin. The synthesised compounds demonstrated potent binding to the ASGPR with submicromolar K D values. The conjugates with an amide bond connecting atorvastatin and the targeting moiety displayed the optimal stability under model conditions, as they underwent hydrolysis only when incubated with the intracellular protease. The hydrolysis products effectively inhibited HMG-R activity. The results suggest that the designed amide-based compounds have the potential to be further developed as orally administered prodrugs of atorvastatin.

A Comprehensive Review on Liver Targeting: Emphasis on Nanotechnology- based Molecular Targets and Receptors Mediated Approaches

BACKGROUND

The pathogenesis of hepatic diseases involves several cells, which complicates the delivery of pharmaceutical agents. Many severe liver diseases affecting the worldwide population cannot be effectively treated. Major hindrances or challenges are natural physiological barriers and non-specific targeting of drugs administered, leading to inefficient treatment. Hence, there is an earnest need to look for novel therapeutic strategies to overcome these hindrances. A kind of literature has reported that drug safety and efficacy are incredibly raised when a drug is incorporated inside or attached to a polymeric material of either hydrophilic or lipophilic nature. This has driven the dynamic investigation for developing novel biodegradable materials, drug delivery carriers, target-specific drug delivery systems, and many other novel approaches.

OBJECTIVE

Present review is devoted to summarizing receptor-based liver cell targeting using different modified novel synthetic drug delivery carriers. It also highlights recent progress in drug targeting to diseased liver mediated by various receptors, including asialoglycoprotein, mannose and galactose receptor, Fc receptor, low-density lipoprotein, glycyrrhetinic, and bile acid receptor. The essential consideration is given to treating liver cancer targeting using nanoparticulate systems, proteins, viral and non-viral vectors, homing peptides and gene delivery.

CONCLUSION

Receptors based targeting approach is one such approach that was explored by researchers to develop novel formulations which can ensure site-specific drug delivery. Several receptors are on the surfaces of liver cells, which are highly overexpressed in various disease conditions. They all are helpful for the treatment of liver cancer.

Drug-Target Interaction Prediction via Dual Laplacian Graph Regularized Logistic Matrix Factorization

Drug-target interactions provide useful information for biomedical drug discovery as well as drug development. However, it is costly and time consuming to find drug-target interactions by experimental methods. As a result, developing computational approaches for this task is necessary and has practical significance. In this study, we establish a novel dual Laplacian graph regularized logistic matrix factorization model for drug-target interaction prediction, referred to as DLGrLMF briefly. Specifically, DLGrLMF regards the task of drug-target interaction prediction as a weighted logistic matrix factorization problem, in which the experimentally validated interactions are allocated with larger weights. Meanwhile, by considering that drugs with similar chemical structure should have interactions with similar targets and targets with similar genomic sequence similarity should in turn have interactions with similar drugs, the drug pairwise chemical structure similarities as well as the target pairwise genomic sequence similarities are fully exploited to serve the matrix factorization problem by using a dual Laplacian graph regularization term. In addition, we design a gradient descent algorithm to solve the resultant optimization problem. Finally, the efficacy of DLGrLMF is validated on various benchmark datasets and the experimental results demonstrate that DLGrLMF performs better than other state-of-the-art methods. Case studies are also conducted to validate that DLGrLMF can successfully predict most of the experimental validated drug-target interactions.

Discovery of Bivalent GalNAc-Conjugated Betulin as a Potent ASGPR-Directed Agent against Hepatocellular Carcinoma

Herein, we describe the design, synthesis, and biological evaluation of novel betulin and N-acetyl-d-galactosamine (GalNAc) glycoconjugates and suggest them as targeted agents against hepatocellular carcinoma. We prepared six conjugates derived via the C-3 and C-28 positions of betulin with one or two saccharide ligands. These molecules demonstrate high affinity to the asialoglycoprotein receptor (ASGPR) of hepatocytes assessed by in silico modeling and surface plasmon resonance tests. Cytotoxicity studies in vitro revealed a bivalent conjugate with moderate activity, selectivity of action, and cytostatic properties against hepatocellular carcinoma cells HepG2. An additional investigation confirmed the specific engagement with HepG2 cells by the enhanced generation of reactive oxygen species. Stability tests demonstrated its lability to acidic media and to intracellular enzymes. Therefore, the selected bivalent conjugate represents a new potential agent targeted against hepatocellular carcinoma. Further extensive studies of the cellular uptake in vitro and the real-time microdistribution in the murine liver in vivo for fluorescent dye-labeled analogue showed its selective internalization into hepatocytes due to the presence of GalNAc ligand in comparison with reference compounds. The betulin and GalNAc glycoconjugates can therefore be considered as a new strategy for developing therapeutic agents based on natural triterpenoids.

New Small-Molecule Glycoconjugates of Docetaxel and GalNAc for Targeted Delivery to Hepatocellular Carcinoma

In this work, we have developed covalent and low molecular weight docetaxel delivery systems based on conjugation with N-acetyl-d-galactosamine and studied their properties related to hepatocellular carcinoma cells. The resulting glycoconjugates have an excellent affinity to the asialoglycoprotein receptor (ASGPR) in the nanomolar range of concentrations and a high cytotoxicity level comparable to docetaxel. Likewise, we observed the 21-75-fold increase in water solubility in comparison with parent docetaxel and prodrug lability to intracellular conditions with half-life values from 25.5 to 42 h. We also found that the trivalent conjugate possessed selective toxicity against hepatoma cells vs control cell lines (20-35 times). The absence of such selectivity in the case of monovalent conjugates indicates the effect of ligand valency. Specific ASGPR-mediated cellular uptake of conjugates was proved in vitro using fluorescent-labeled analogues. In addition, we showed an enhanced generation of reactive oxygen species in the HepG2 cells, which could be inhibited by the natural ligand of ASGPR. Overall, the obtained results highlight the potential of ASGPR-directed cytostatic taxane drugs for selective therapy of hepatocellular carcinoma.

Synthesis and Evaluation of New Trivalent Ligands for Hepatocyte Targeting via the Asialoglycoprotein Receptor

Since the asialoglycoprotein receptor (also known as the "Ashwell-Morell receptor" or ASGPR) was discovered as the first cellular mammalian lectin, numerous drug delivery systems have been developed and several gene delivery systems associated with multivalent ligands for liver disease targeting are undergoing clinical trials. The success of these systems has facilitated the further study of new ligands with comparable or higher affinity and less synthetic complexity. Herein, we designed two novel trivalent ligands based on the esterification of tris(hydroxymethyl) aminomethane (TRIS) followed by the azide-alkyne Huisgen cycloaddition with azido N-acetyl-d-galactosamine. The presented triazolyl glycoconjugates exhibited good binding to ASGPR, which was predicted using in silico molecular docking and assessed by a surface plasmon resonance (SPR) technique. Moreover, we demonstrated the low level of in vitro cytotoxicity, as well as the optimal spatial geometry and the required amphiphilic balance, for new, easily accessible ligands. The conjugate of a new ligand with Cy5 dye exhibited selective penetration into HepG2 cells in contrast to the ASGPR-negative PC3 cell line.

Recognition Sites for Cancer-targeting Drug Delivery Systems

BACKGROUND

Target-homing drug delivery systems are now gaining significant attention for use as novel therapeutic approaches in antitumor targeting for cancer therapy. Numerous targeted drug delivery systems have been designed to improve the targeting effects because these systems can display a range of favorable properties, thus, providing suitable characteristics for clinical applicability of anticancer drugs, such as increasing the solubility, and improving the drug distribution at target sites. The majority of these targeting systems are designed with respect to differences between cancerous and normal tissues, for instance, the low pH of tumor tissues or overexpressed receptors on tumor cell membranes. Due to the growing number of targeting possibilities, it is important to know the tumor-specific recognition strategies for designing novel, targeted, drug delivery systems. Herein, we identify and summarize literature pertaining to various recognition sites for optimizing the design of targeted drug delivery systems to augment current chemotherapeutic approaches.

OBJECTIVE

This review focuses on the identification of the recognition sites for developing targeted drug delivery systems for use in cancer therapeutics.

METHODS

We have reviewed and compiled cancer-specific recognition sites and their abnormal characteristics within tumor tissues (low pH, high glutathione, targetable receptors, etc.), tumor cells (receptor overexpression or tumor cell membrane changes) and tumor cell organelles (nuclear and endoplasmic reticular dysregulation) utilizing existing scientific literature. Moreover, we have highlighted the design of some targeted drug delivery systems that can be used as homing tools for these recognition sites.

RESULTS AND CONCLUSION

Targeted drug delivery systems are a promising therapeutic approach for tumor chemotherapy. Additional research focused on finding novel recognition sites, and subsequent development of targeting moieties for use with drug delivery systems will aid in the evaluation and clinical application of new and improved chemotherapeutics.

Synthesis and Сytotoxicity of A-Azepanobetulinic Acid N-Methyl-Piperazinylamide

The synthesis of A-azepanobetulinic acid N-methylpiperazinylamide was performed through a series of transformations (oximation, Beckmann rearrangement, reduction) of previously synthesized betulonic acid N-methylpiperazinylamide. In vitro cytotoxic activity was detected for the obtained compound against a number of cancer cell lines, and its potential was revealed as an antibacterial agent.

Drug-Target Interaction Prediction via Dual Laplacian Graph Regularized Matrix Completion

Drug-target interactions play an important role for biomedical drug discovery and development. However, it is expensive and time-consuming to accomplish this task by experimental determination. Therefore, developing computational techniques for drug-target interaction prediction is urgent and has practical significance. In this work, we propose an effective computational model of dual Laplacian graph regularized matrix completion, referred to as DLGRMC briefly, to infer the unknown drug-target interactions. Specifically, DLGRMC transforms the task of drug-target interaction prediction into a matrix completion problem, in which the potential interactions between drugs and targets can be obtained based on the prediction scores after the matrix completion procedure. In DLGRMC, the drug pairwise chemical structure similarities and the target pairwise genomic sequence similarities are fully exploited to serve the matrix completion by using a dual Laplacian graph regularization term; i.e., drugs with similar chemical structure are more likely to have interactions with similar targets and targets with similar genomic sequence similarity are more likely to have interactions with similar drugs. In addition, during the matrix completion process, an indicator matrix with binary values which indicates the indices of the observed drug-target interactions is deployed to preserve the experimental confirmed interactions. Furthermore, we develop an alternative iterative strategy to solve the constrained matrix completion problem based on Augmented Lagrange Multiplier algorithm. We evaluate DLGRMC on five benchmark datasets and the results show that DLGRMC outperforms several state-of-the-art approaches in terms of 10-fold cross validation based AUPR values and PR curves. In addition, case studies also demonstrate that DLGRMC can successfully predict most of the experimental validated drug-target interactions.