首页> 外文OA文献 >Proteins and their interacting partners: an introduction to protein–ligand binding site prediction methods
【2h】

Proteins and their interacting partners: an introduction to protein–ligand binding site prediction methods

机译:蛋白质及其相互作用伙伴:蛋白质-配体结合位点预测方法简介

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.
机译:使用体外和/或体内方法阐明蛋白质的生物学和生化作用并随后确定其相互作用伙伴可能是困难且耗时的,因此大多数新测序的蛋白质将具有未知的结构和功能。但是,计算机模拟蛋白质-配体结合位点和蛋白质生化功能的方法提供了另一种实用的解决方案。蛋白质-配体结合位点的表征对于研究新的功能作用至关重要,这可能会影响健康,食品和能源安全等主要生物学研究领域。在本文中,我们讨论了计算机模拟方法在蛋白质-配体结合位点的3D建模中的作用,以及它们在预测生化功能方面的作用。此外,我们详细描述了一些可用的计算机模拟重要替代方法,并讨论了蛋白质结构预测技术(CASP)和连续自动模型评估(CAMEO)项目的关键评估及其影响关于该领域的发展。此外,我们讨论了蛋白质功能预测方法对解决21世纪问题的重要性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号