calibur处理ROSETTA输出的多个结构文件,clustering 下载网址:https://sourceforge.net/projects/calibur/ 安装: 1$ tar zxvf calibur.tar.gz2$ cd calibur3$ make 安装完成后,会产生calibur和calibur-lite两个可执行文件。 添加环境变量: 1$ vim ~/.bashrc2#calibur3export PATH=$Programs/calibur:$PATH4$ source...
L. Jr. A new clustering of antibody CDR loop conformations. J. Mol. Biol. 406, 228–256 (2011). CAS PubMed Google Scholar King, C. et al. Removing T-cell epitopes with computational protein design. Proc. Natl Acad. Sci. USA 111, 8577–8582 (2014). CAS PubMed PubMed Central ...
PubMedPubMed CentralGoogle Scholar North, B., Lehmann, A. & Dunbrack, R. L. Jr. A new clustering of antibody CDR loop conformations.J. Mol. Biol.406, 228–256 (2011). CASPubMed King, C. et al. Removing T-cell epitopes with computational protein design.Proc. Natl Acad. Sci. USA11...
A new clustering of antibody CDR loop conformations. J. Mol. Biol. 406, 228–256 (2011). Article CAS PubMed Google Scholar Adolf-Bryfogle, J., Xu, Q., North, B., Lehmann, A. & Dunbrack, R.L. PyIgClassify: a database of antibody CDR structural classifications. Nucleic Acids Res...
K. et al. Predicting multiple conformations via sequence clustering and AlphaFold2. Nature 625, 832–839 (2024). Article CAS PubMed Google Scholar Abramson, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024). Article CAS PubMed...
Our docking studies and clustering provided atomistic structural insights into state-dependent drug-channel interactions that play a key role in differentiating safe and harmful hERG blockers and can explain hERG channel facilitation through drug interactions with its open-state hydro...
1. 首先,非标准残基都需要转换成.params文件,使用 <path-to-Rosetta>/main/source/scripts/python/public/molfile_to_params.py -n TPP TPP.mol2 --chain=F --clobber --keep-names 转换,此命令会产生TPP_0001.pdb和TPP.params两个文件; 2. 其次,如果配体需要进行构象搜索,可以使用obabel,这个免费且简单...
database in a low-resolution fragment assembly stage. Subsequent models are filtered to omit trajectories with chain breaks or poor scores, and passing models are subjected to minimization in an all-atom scoring function. Finally, models are chosen from the resulting ensemble through clustering. ...
The generated sequences exhibited significant variation in physicochemical properties and amino acid composition, with no discernible clustering (Fig. 3d, Supplementary files chemical_profiles.csv, and identity_matrix.csv), underling the capability of ProteinMPNN to generate an extensive array of possible...
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