Recent Trends in Drug Design and Discovery

INTRODUCTION

Structure-based drug design is a wide area of identification of selective inhibitors of a target of interest. From the time of the availability of three dimensional structure of the drug targets, mostly the proteins, many computational methods had emerged to address the challenges associated with drug design process. Particularly, drug-likeness, druggability of the target protein, specificity, off-target binding, etc., are the important factors to determine the efficacy of new chemical inhibitors.

OBJECTIVE

The aim of the present research was to improve the drug design strategies in field of design of novel inhibitors with respect to specific target protein in disease pathology. Recent statistical machine learning methods applied for structural and chemical data analysis had been elaborated in current drug design field.

METHODS

As the size of the biological data shows a continuous growth, new computational algorithms and analytical methods are being developed with different objectives. It covers a wide area, from protein structure prediction to drug toxicity prediction. Moreover, the computational methods are available to analyze the structural data of varying types and sizes of which, most of the semi-empirical force field and quantum mechanics based molecular modeling methods showed a proven accuracy towards analysing small structural data sets while statistics based methods such as machine learning, QSAR and other specific data analytics methods are robust for large scale data analysis.

RESULTS

In this present study, the background has been reviewed for new drug lead development with respect specific drug targets of interest. Overall approach of both the extreme methods were also used to demonstrate with the plausible outcome.

CONCLUSION

In this chapter, we focus on the recent developments in the structure-based drug design using advanced molecular modeling techniques in conjunction with machine learning and other data analytics methods. Natural products based drug discovery is also discussed.

Defense involvement of piscidin from striped murrel Channa striatus and its peptides CsRG12 and CsLC11 involvement in an antimicrobial and antibiofilm activity

In this study, we have evaluated bioinformatics characterization and antimicrobial role of two piscidin (Pi) peptide identified from the established transcriptome of striped murrel Channa striatus (Cs). The identified CsPi cDNA contains 256 nucleotides encode a protein with 70 amino acids in length which has two antimicrobial peptides and named CsRG12 and CsLC11. The gene expression analysis with various immune stimulants indicated an induced expression pattern of CsPi. Antibiogram showed that CsRG12 and CsLC11 was active against Staphylococcus aureus ATCC 33592, a major multi-drug resistant (MDR) bacterial pathogen and Bacillus cereus ATCC 2106. The minimum inhibitory concentration (MIC) and antibiofilm assays were conducted to observe the activity of pathogenic bacteria with these derived antimicrobial peptides. Flow cytometry analysis noticed that the CsRG12 and CsLC11 disrupt the membrane formation of S. aureus and B. cereus, which was further assured by scanning electron microscopic (SEM) images that bleb formation leads to disruption around the bacterial membrane. Overall, it is reported that CsPi is involved in innate immunity as the gene expression plays a remarkable role in up and down regulation during infection. In addition, the involvement of peptides in antibiofilm formation and bacterial membrane disruption support its immune character. This study leads to a possibility for the development of therapeutics in aquaculture biotechnology.

Therapeutic effects of gold nanoparticles synthesized using Musa paradisiaca peel extract against multiple antibiotic resistant Enterococcus faecalis biofilms and human lung cancer cells (A549)

Botanical-mediated synthesis of nanomaterials is currently emerging as a cheap and eco-friendly nanotechnology, since it does not involve the use of toxic chemicals. In the present study, we focused on the synthesis of gold nanoparticles using the aqueous peel extract of Musa paradisiaca (MPPE-AuNPs) following a facile and cheap fabrication process. The green synthesized MPPE-AuNPs were bio-physically characterized by UV-Vis spectroscopy, FTIR, XRD, TEM, Zeta potential analysis and EDX. MPPE-AuNPs were crystalline in nature, spherical to triangular in shape, with particle size ranging within 50 nm. The biofilm inhibition activity of MPPE-AuNPs was higher against multiple antibiotic resistant (MARS) Gram-positive Enterococcus faecalis. Light and confocal laser scanning microscopic observations evidenced that the MPPE-AuNPs effectively inhibited the biofilm of E. faecalis when tested at 100 μg mL^-1. Cytotoxicity studies demonstrated that MPPE-AuNPs were effective in inhibiting the viability of human A549 lung cancer cells at higher concentrations of 100 μg mL^-1. The morphological changes in the MPPE-AuNPs treated A549 lung cancer cells were visualized under phase-contrast microscopy. Furthermore, the ecotoxicity of MPPE-AuNPs on the freshwater micro crustacean Ceriodaphnia cornuta were evaluated. Notably, no mortality was recorded in MPPE-AuNPs treated C. cornuta at 250 μg mL^-1. This study concludes that MPPE-AuNPs are non-toxic, eco-friendly and act as a multipurpose potential biomaterial for biomedical applications.