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分子计算机建模在抗癌药物研发中的重要性。

Importance of molecular computer modeling in anticancer drug development.

作者信息

Geromichalos George D

机构信息

Department of Cell Culture, Molecular Modeling and Drug Design, Symeonidion Research Center, Theagenion Cancer Hospital, Thessaloniki, Greece.

出版信息

J BUON. 2007 Sep;12 Suppl 1:S101-18.

Abstract

Increasing insight into the genetics and molecular biology of cancer has resulted in the identification of an increasing number of potential molecular targets for anticancer drug discovery and development. These targets can be approached through exploitation of emerging structural biology, "rational" drug design, screening of chemical libraries, or a combination of these methods. The result is the rapid discovery of new anticancer drugs. The processes used by academic and industrial scientists to discover new drugs has recently experienced a true renaissance with many new and exciting techniques being developed in the past 5-10 years. In this review, we will attempt to outline these latest protocols that chemists and biomedical scientists are currently employing to rapidly bring new drugs to the clinic. Structure-based drug design is perhaps the most elegant approach for discovering compounds exhibiting high specificity and efficacy. Nowadays, a number of recent successful drugs have in part or in whole emerged from a structure-based research approach. Many advances including crystallography and informatics are behind these successes. Of great importance is also the impact these advances in structure-based drug design are likely to have on the economics of drug discovery. As the structures of more and more proteins and nucleic acids become available, molecular docking is increasingly considered for lead discovery. Recent studies consider the hit-rate enhancement of docking screens and the accuracy of docking structure predictions. As more structures are determined experimentally, docking against homology-modeled targets also becomes possible for more proteins. With more docking studies being undertaken, the "drug-likeness" and specificity of docking hits is also being examined. In this article we discuss the application of molecular modeling, molecular docking and virtual molecular high-throughput, targeted drug screening to anticancer drug discovery. Currently, scientists are focusing on designing and discovering potential inhibitors against cancer-related proteins that play critical roles in the development of a variety of tumors. Future research breakthroughs with the aid of computer-aided molecular design and chemo-bioinformatics will bring not only new hope, but also create a new class of anticancer drugs that will help millions of cancer patients.

摘要

对癌症遗传学和分子生物学的深入了解,使得越来越多潜在的分子靶点被识别出来,用于抗癌药物的研发。这些靶点可以通过利用新兴的结构生物学、“理性”药物设计、化学文库筛选或这些方法的组合来实现。结果是新抗癌药物的快速发现。学术和工业科学家用于发现新药的过程最近经历了真正的复兴,在过去5至10年中开发了许多新的、令人兴奋的技术。在这篇综述中,我们将试图概述化学家和生物医学科学家目前正在采用的这些最新方案,以便迅速将新药推向临床。基于结构的药物设计可能是发现具有高特异性和疗效化合物的最优雅方法。如今,许多近期成功的药物部分或全部源自基于结构的研究方法。包括晶体学和信息学在内的许多进展促成了这些成功。基于结构的药物设计的这些进展对药物研发经济学可能产生的影响也非常重要。随着越来越多蛋白质和核酸的结构得以确定,分子对接在先导化合物发现中越来越受到重视。近期研究考虑了对接筛选的命中率提高以及对接结构预测的准确性。随着更多结构通过实验确定,针对同源建模靶点的对接对于更多蛋白质也成为可能。随着更多对接研究的开展,对接命中物的“类药性”和特异性也在被研究。在本文中,我们讨论分子建模、分子对接和虚拟分子高通量靶向药物筛选在抗癌药物发现中的应用。目前,科学家们专注于设计和发现针对在多种肿瘤发展中起关键作用的癌症相关蛋白的潜在抑制剂。借助计算机辅助分子设计和化学生物信息学的未来研究突破不仅将带来新希望,还将创造一类新的抗癌药物,帮助数百万癌症患者。

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