![]() Click to download a java version of the TM-score program.Click RMSD.f to download the source code for calculating RMSD only.Click TMscore_subroutine.f to download the subroutine code that can quickly calculate TM-score and be conveniently included as a subroutine in any Fortran program.Higher speed to run the program (See above step). The TM-score source code and compile it on your machine, which gives you Nevertheless, it is recommended to download >g77 -static -O3 -lm -o TMscore TMscore.fĬlick TMscore_cpp to download the executable programįor Linux system. >gfortran -static -O3 -ffast-math -lm -o TMscore TMscore.f To download the newest version of the TM-score source code in Fortran77. >g++ -static -O3 -ffast-math -lm -o TMscore TMscore.cpp Such as Mac, which does not support static build): (you can ignore the '-static' option for some machines, You can compile the program in your Linux computer by To download the newest version of the TM-score source code in C++. Input Email: (optional, where results will be sent to).Merge all chains and compare them as monomers). These are complex structures (server will Input Structure 2, Experimental structure in PDB format (mandatory):.Please copy and paste your structure file here. TM-score on-line ( view an example of output) Please read " Problem and Solution", if you have problem on how to calculate Higher than 0.5 assume generally the same fold in SCOP/CATH. Scores below 0.17 correspond to randomly chosen unrelated proteins whereas structures with a score TM-score has the value in (0,1], where 1 indicates a perfect match between two structures.įollowing strict statistics of structures in the PDB, (2) TM-score introduces a length-dependent scale to normalize theĭistance errors and makes the magnitude of TM-score length-independent Similarity than to the local structural variations (1) TM-score weights smaller distance errors stronger than larger distanceĮrrors and makes the score value more sensitive to the global fold It is designed to solve two major problems in traditional metrics such as Use the mobile_state and target_state argument to be explicit in such cases.TM-score is a metric for assessing the topological similarity of protein structures. By defaults, all states (like in NMR structures or trajectories) are considered, this might yield a bad or suboptimal alignment for a single state.You can skirt this problem by making a temporary object and aligning your original to the copy. Else, PyMOL will answer with: ExecutiveAlign: invalid selections for alignment. The molecules you want to align need to be in two different objects.Number of aligned atoms before refinement.Number of aligned atoms after refinement.align ( string mobile, string target, float cutoff = 2.0, int cycles = 5, float gap =- 10.0, float extend =- 0.5, int max_gap = 50, string object = None, string matrix = 'BLOSUM62', int mobile_state = 0, int target_state = 0, int quiet = 1, int max_skip = 0, int transform = 1, int reset = 0 ) Note that the output prints "RMS" but it is in fact "RMSD" and the units are Angstroms.Ĭmd. The RMSD can also be captured with a python script, see the API paragraph below. The all-atom RMSD can be obtained by setting cycles=0 and thus not doing any outlier rejection. The RMSD of the aligned atoms (after outlier rejection!) is reported in the text output. can be saved to a clustalw sequence alignment file.graphical representation of aligned atom pairs as lines in the 3D viewer.cutoff = float: outlier rejection cutoff in RMS Īn alignment object can be created with the object= somename argument.target = string: atom selection of target object.mobile = string: atom selection of mobile object.[, matrix [, mobile_state [, target_state Usage align mobile, target [, cutoff [, cycles ![]()
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