School of Electrical and Computer Engineering, Health Innovations Research Institute, RMIT University, Melbourne 3001 Australia.
Curr Pharm Biotechnol. 2011 Aug;12(8):1117-27. doi: 10.2174/138920111796117436.
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.
药物发现和开发是一个高强度、长周期且跨学科的过程。传统上，药物是通过耗时的多步实验研究合成化合物，然后进行体外和体内生物筛选来发现的。有前途的候选药物随后会进一步研究其药代动力学特性、代谢和潜在毒性。如今，由于基因组学、蛋白质组学和生物信息学的进步，药物发现的过程已经发生了革命性的变化。组合化学、高通量筛选（HTS）、虚拟筛选、从头设计和基于结构的药物设计等高效技术极大地促进了药物发现。肽类正在成为癌症治疗的一类新型药物，并且已经做出了许多努力来开发基于肽的具有药理活性的化合物。本文综述了实验和计算药物发现和设计方面的最新进展和新方法。我们还介绍了一种使用共振识别模型（RRM）设计的新型生物活性肽类似物，并讨论了其在癌症治疗中的潜在用途。
