Drug discovery and development are intense, lengthy and interdisciplinary processes. Traditionally, drugs were discovered by synthesizing compounds in time-consuming multi-step experimental investigations followed by in vitro and in vivo biological screening. Promising candidates were then further studied for their pharmacokinetic properties, metabolism and potential toxicity. Today, the process of drug discovery has been revolutionized due to the advances in genomics, proteomics, and bioinformatics. Efficient technologies such as combinatorial chemistry, high throughput screening (HTS), virtual screening, de novo design and structure-based drug design contribute greatly to drug discovery. Peptides are emerging as a novel class of drugs for cancer therapy, and many efforts have been made to develop peptide-based pharmacologically active compounds. This paper presents a review of current advances and novel approaches in experimental and computational drug discovery and design. We also present a novel bioactive peptide analogue, designed using the Resonant Recognition Model (RRM), and discuss its potential use for cancer therapeutics.
Keywords: Digital signal processing, drug discovery, cancer therapeutics, frequency, peptide de novo design, protein function, pharmacokinetic properties, potential toxicity, combinatorial chemistry, high throughput screening (, virtual screening, structure-based drug design, computational drug discovery, Resonant Recognition Model, cancer
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