研究序列及其相应的三维结构之间的关系有助于结构生物学家解决蛋白质折叠问题。尽管有几种实验和计算机模拟方法,仍然从序列中理解或解码三维结构仍然是一个谜。在这种情况下,结构预测的准确性起着不可或缺的作用。为了解决这个问题,已创建更新的Web服务器(CSSP-2.0),以通过部署现有算法来提高我们以前版本的CSSP的准确性。它使用输入作为概率,并将二级结构的共识预测为高度精确的三态Q3(螺旋,strand,和线圈)。这个预测是使用六种最近表现最好的方法来实现的:MUFOLD-SS,RaptorX,PSSpredv4,PSIPRED,JPredv4和Porter5.0。CSSP-2.0验证包括涉及来自PDB的各种蛋白质类别的数据集,CullPDB,和AlphaFold数据库。我们的结果表明,共识Q3预测的准确性有了显著提高。使用CSSP-2.0,晶体学可以从整个复杂结构中挑选出稳定的规则二级结构,这将有助于推断假设蛋白质的功能注释。Web服务器可在https://bioserver3免费获得。物理。iisc.AC.in/cgi-bin/cssp-2/.
Studying the relationship between sequences and their corresponding three-dimensional structure assists structural biologists in solving the protein-folding problem. Despite several experimental and in-silico approaches, still understanding or decoding the three-dimensional structures from the sequence remains a mystery. In such cases, the accuracy of the structure prediction plays an indispensable role. To address this issue, an updated web server (CSSP-2.0) has been created to improve the accuracy of our previous version of CSSP by deploying the existing algorithms. It uses input as probabilities and predicts the consensus for the secondary structure as a highly accurate three-state Q3 (helix, strand, and coil). This prediction is achieved using six recent top-performing methods: MUFOLD-SS, RaptorX, PSSpred v4, PSIPRED, JPred v4, and Porter 5.0. CSSP-2.0 validation includes datasets involving various protein classes from the PDB, CullPDB, and AlphaFold databases. Our results indicate a significant improvement in the accuracy of the consensus Q3 prediction. Using CSSP-2.0, crystallographers can sort out the stable regular secondary structures from the entire complex structure, which would aid in inferring the functional annotation of hypothetical proteins. The web server is freely available at https://bioserver3.physics.iisc.ac.in/cgi-bin/cssp-2/.