Prediction of protein structures, functions and interactions using the IntFOLD7, MultiFOLD and ModFOLDdock servers.
Prediction of protein structures, functions and interactions using the IntFOLD7, MultiFOLD and ModFOLDdock servers.
复制标题
DOI：
10.1093/nar/gkad297
复制
发表时间：
2023-07-05
影响因子：
14.9
通讯作者：
中科院分区：
文献类型：
--
作者：
位于阅读大学的IntFOLD服务器在过去十年中一直是提供免费获得蛋白质结构和功能准确预测的领先方法。在后AlphaFold 2世界中，精确的三级结构模型可广泛用于更多的蛋白质靶点，因此预测界重新关注蛋白质-配体相互作用的精确建模以及四级结构组装的建模。在本文中，我们描述了IntFOLD的最新改进，它通过包括最新的深度学习方法，同时还集成了准确的模型质量估计和蛋白质-配体相互作用的3D模型，保持了其具有竞争力的结构预测性能。此外，我们还介绍了两种新的服务器方法：MultiFOLD，用于精确建模三级和四级结构，其性能已被独立验证优于标准AlphaFold 2方法，以及ModFOLDdock，它为四级结构模型提供世界领先的质量估计。IntFOLD 7、MultiFOLD和ModFOLDdock服务器可从https://www.reading.ac.uk/bioinf/获得。在阅读大学使用IntFOLD 7、MultFOLD和ModFOLDdock服务器预测蛋白质、结构、功能和相互作用。
The IntFOLD server based at the University of Reading has been a leading method over the past decade in providing free access to accurate prediction of protein structures and functions. In a post-AlphaFold2 world, accurate models of tertiary structures are widely available for even more protein targets, so there has been a refocus in the prediction community towards the accurate modelling of protein-ligand interactions as well as modelling quaternary structure assemblies. In this paper, we describe the latest improvements to IntFOLD, which maintains its competitive structure prediction performance by including the latest deep learning methods while also integrating accurate model quality estimates and 3D models of protein-ligand interactions. Furthermore, we also introduce our two new server methods: MultiFOLD for accurately modelling both tertiary and quaternary structures, with performance which has been independently verified to outperform the standard AlphaFold2 methods, and ModFOLDdock, which provides world-leading quality estimates for quaternary structure models. The IntFOLD7, MultiFOLD and ModFOLDdock servers are available at: https://www.reading.ac.uk/bioinf/. Prediction of protein, structures, functions and interactions at the University of Reading using the IntFOLD7, MultFOLD and ModFOLDdock servers.
登录
查看更多内容
影响因子：
16.6
作者：
Hiranuma N;Park H;Baek M;Anishchenko I;Dauparas J;Baker D
通讯作者：
Baker D
影响因子：
64.8
作者：
Jumper J;Evans R;Pritzel A;Green T;Figurnov M;Ronneberger O;Tunyasuvunakool K;Bates R;Žídek A;Potapenko A;Bridgland A;Meyer C;Kohl SAA;Ballard AJ;Cowie A;Romera-Paredes B;Nikolov S;Jain R;Adler J;Back T;Petersen S;Reiman D;Clancy E;Zielinski M;Steinegger M;Pacholska M;Berghammer T;Bodenstein S;Silver D;Vinyals O;Senior AW;Kavukcuoglu K;Kohli P;Hassabis D
通讯作者：
Hassabis D
DOI：
10.1107/s0907444913007051
发表时间：
2013-05
期刊：
Acta crystallographica. Section D, Biological crystallography
影响因子：
--
作者：
Biasini M;Schmidt T;Bienert S;Mariani V;Studer G;Haas J;Johner N;Schenk AD;Philippsen A;Schwede T
通讯作者：
Schwede T
影响因子：
14.9
作者：
McGuffin LJ;Aldowsari FMF;Alharbi SMA;Adiyaman R
通讯作者：
Adiyaman R
影响因子：
14.9
作者：
Roche DB;Buenavista MT;Tetchner SJ;McGuffin LJ
通讯作者：
McGuffin LJ