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00README

* 0. Introduction This directory contains a computer program for predicting one-dimensional protein structures (secondary structures [SS], contact numbers [CN], and residue-wise contact orders [RWCO]) by the method of critical random networks described in: Ref. 1 (Description of the software) "CRNPRED: Highly accurate prediction of one-dimensional protein structures by large-scale critical random networks." Kinjo AR, Nishikawa K. submitted (2006) and Ref. 2 (Method of critical random networks) "Predicting secondary structures, contact numbers, and residue-wise contact orders of native protein structure from amino acid sequence using critical random networks." Kinjo AR, Nishikawa K. BIOPHYSICS, 1:67-74 (2005) (DOI: 10.2142/biophysics.1.67). This software is in public domain. You can use, modify and/or destroy it freely, but we do not take any responsibility for the consequences of your use. * 1. INSTALLING CRNPRED. To install the CRNPRED program, you need the following: (0) UNIX-like operating system (Linux, MacOS X, *BSD, etc.) (1) bash (or zsh) (2) make (3) gcc (4) PSI-BLAST and related databases (amino acid sequences and BLOSUM scoring matrices). First, set the environment variable CRNPRED_DIR to this directory (that is, the directory containing this file "00README"). If you are using sh, ksh, bash, or zsh, write export CRNPRED_DIR=/path/to/this/directory in your ~/.profile and do % . ~/.profile If you are using csh or tcsh, write setenv CRNPRED_DIR /path/to/this/directory in your ~/.cshrc and do % source ~/.cshrc To compile the program, do % (cd ${CRNPRED_DIR}/src; make install) Then the program named "xpredm" is installed under the directory ${CRNPRED_DIR}/bin. After xpredm has been installed, test it by running % ${CRNPRED_DIR}/bin/xpredm sample/d3nul__.prof > hoge.out Compare hoge.out with sample/d3nul__.out. There are a few sample inputs and outputs in the directory named "sample". * 2. RUNNING CRNPRED. Make sure you have set the environment variable CRNPRED_DIR appropriately. A utility shell script "run_crn.sh" is available for your convenience. If you have FASTA format amino acid sequence file (say, "test.seq"), do ${CRNPRED_DIR}/bin/run_crn.sh -d uniref100 test.seq where "uniref100" is the sequence database used by PSI-BLAST. Then, after some time, you have a file named "test.seq.d.out" which contains the result of the prediction. If it does not work, check the content of "run_crn.sh" and modify the environment variables such as BLASTDB, BLASTMAT, and CRNPRED_DIR, or you may have to change the first line "#!/bin/sh" to something like "#!/usr/bin/env bash" or "#!/usr/bin/env/ zsh". Run ${CRNPRED_DIR}/bin/run_crn.sh -h to see other options. Alternatively, you can directly run the program. You first need to run PSI-BLAST to make a position-specific scoring matrix: blastpgp -d nr -h 0.0005 -j 3 -i test.seq -Q test.prof > /dev/null Then do ${CRNPRED_DIR}/bin/xpredm test.prof > test.out The result is saved in "test.out". * 3. INTERPRETING THE RESULTS. Below is an example of prediction. * Lines starting with "AA" show the amino acid sequence you fed. * Lines starting with "SS" show the predicted secondary structures where "H", "E", and "C" mean "alpha-helix", "beta-strand", and "coils", respectively. * Lines starting with "CN" show the predicted contact numbers in 2-state description where "B" and "E" mean "buried" and "exposed", respectively. The threshold values are the average contact number for each residue type (see Appendix below for the list of the average contact numbers). * Lines after "># AA : SS P_H P_E P_C : CN : RWCO" are the details of the prediction: o The column corresponding to "AA" indicates the residue numbers and the amino acid residues. o The column corresponding to "SS" indicates the predicted secondary structure followed by the ad hoc probability for each secondary structure class (i.e., "P_H" for the probability for the residue to be in the alpha-helix class, etc.). o The column corresponding to "CN" indicates the predicted contact numbers in 2-state description ("B" or "E") followed by the real predicted contact numbers. o The column corresponding to "RWCO" indicates the predicted residue-wise contact orders (real numbers). ---------sample output starts here-------- >prediction for: test.prof # * * * * * * AA: SWQSYVDDHLMCDVEGNHLTAAAILGQDGSVWAQSAKFPQLKPQEIDGIKKDFEEPGFLA SS: CCHHHHHHHHHCCCCCCCCHEEEEECCCCCEEEECCCCCCCCHHHHHHHHHCCCCCCCCC CN: BBBBBBEBBEBBBBBBBBEEEEEEEEEEEEEEEEEBBBBBEEBBEBBBEEBEBBBBBBBB # * * * * * * AA: PTGLFLGGEKYMVIQGEQGAVIRGKKGPGGVTIKKTNQALVFGFYDEPMTGGQCNLVVER SS: CCEEEECCCEEEEEECCCCEEEEECCCCCEEEEEECCCEEEEEEECCCCCCHHHHHHHHH CN: EBEEBEBBEEEEEEEBBBBBBEEEEEBBBEEEEEEEEEEEEEEEBBBBBBBBEEEBEEEB # * AA: LGDYLIESEL SS: HHHHHHHCCC CN: EEEBEBBBBB // ># AA : SS P_H P_E P_C : CN : RWCO 1 S : C 11 7 82 : B 14 : 840 2 W : C 23 10 67 : B 22 : 1221 3 Q : H 59 11 30 : B 18 : 864 4 S : H 79 8 12 : B 18 : 860 5 Y : H 86 6 7 : B 25 : 1199 6 V : H 89 5 6 : B 27 : 1276 7 D : H 90 5 6 : E 21 : 855 8 D : H 90 4 6 : B 17 : 728 9 H : H 89 5 6 : B 22 : 954 10 L : H 85 6 8 : E 30 : 1188 11 M : H 72 9 18 : B 24 : 850 12 C : C 44 11 46 : B 22 : 826 13 D : C 18 8 73 : B 18 : 669 14 V : C 10 7 83 : B 22 : 751 15 E : C 8 6 86 : B 17 : 593 16 G : C 8 7 85 : B 18 : 640 17 N : C 10 8 82 : B 17 : 696 18 H : C 16 11 73 : B 24 : 808 19 L : C 30 16 54 : E 32 : 1103 20 T : H 45 22 32 : E 26 : 962 21 A : E 37 43 20 : E 27 : 1017 22 A : E 15 75 10 : E 37 : 1265 23 A : E 7 88 5 : E 38 : 1286 24 I : E 6 89 5 : E 41 : 1341 . . . . ---------sample output ends here-------- * 4. CONTACT INFORMATION Akira Kinjo Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima, 411-8540, JAPAN email: akinjo @ genes . nig . ac . jp * Appendix A. The average contact number of each residue type is listed below: ------------------- 25.430 , /* A */ 21.038 , /* R */ 20.093 , /* N */ 18.594 , /* D */ 29.647 , /* C */ 20.206 , /* Q */ 18.008 , /* E */ 22.505 , /* G */ 23.572 , /* H */ 29.469 , /* I */ 28.173 , /* L */ 18.452 , /* K */ 26.466 , /* M */ 28.057 , /* F */ 20.350 , /* P */ 21.420 , /* S */ 22.747 , /* T */ 26.913 , /* W */ 26.627 , /* Y */ 28.656 , /* V */ ------------------- * Appendix B. ** Faster but less accurate predictions. The default implementation of CRNPRED uses 5000 dimensional state vectors for critical random networks. This makes the prediction process quite slow when you use the program on old computers or when you predict large proteins. If you want predictions quickly, there are two options: (1) linear predictor or (2) 2000 dimensional state vectors. *** Using linear predictor The linear predictor as described in Ref. 2 is implemented as a separate program named "lpredm" which is installed along with xpredm (CRNPRED). Use it as follows: ${CRNPRED_DIR}/bin/lpredm test.prof > test.out *** Using 2000 dimensional CRNPRED To use CRNPRED with 2000 dimensional state vectors, you need to recompile the program. Do it as follows: cd ${CRNPRED_DIR}/src make realclean make NDIM=2000 install cd .. cp w2000/WMATS . cp w2000/WMAT_ENS . This produces the executable file "xpredm" just like before, but it now uses 2000-dimensional state vectors. *** Comparison of predictors Here is a brief summary of speed and accuracy of the linear predictor (lpredm), xpredm(2000), and xpredm (5000). The CPU times were measured for the sample file "sample/d8abp__.prof" (305 AA) on Mac OS X (PPC G5, 2.5GHz). The CPU time is (almost) linearly proportional to the protein length. program speed accuracy note -------------------------------------------------------------- xpredm very slow SS:Q3=81 default (5000) 5min52s CN:Cor=0.75 RWCO:Cor=0.61 xpredm slow SS:Q3=79 (2000) 1min12s CN:Cor=0.74 RWCO:Cor=0.61 lpredm fast SS:Q3=76 0.558s CN:Cor=0.72 RWCO:Cor=0.59 -------------------------------------------------------------- Note that the accuracies are the average values based on a benchmark. The difference between Q3=81 and Q3=79 may seem insignificant on average, but there can be a big difference for individual predictions [e.g., an incorrectly predicted alpha helix with xpred(2000) may be correctly predicted as a beta strand with xpred(5000)]. # Local variables: # mode: outline # End: