+++ /dev/null
-#include <stdio.h>
-#include <stdlib.h>
-#include <math.h>
-#include <stdarg.h>
-
-
-#include "io_lib_header.h"
-#include "util_lib_header.h"
-#include "define_header.h"
-
-#include "dp_lib_header.h"
-
-
-/*
- 23/06/00, Cedric Notredame
-
-
- 1-Content of the data structures.
- 2-Implementing your own function in pdb_align.
- 3-Using that function with T-Coffee (multiple Sequence Alignment).
- 4-Syntax rules as defined by Philipp Bucher (19/06/00).
- 5-Current Shortcomings
- 6-Enquiries.
-
- 1-Content of the data structures
-
- This file only contains a dummy function to help you create
- your own matching potential function (Step 2 in the Notations RULES
-
- int evaluate_match_score ( Constraint_list *CL, int A, int i, int B, int j)
-
- returns a score, expected to be between -100 and 100, that corresponds to the matching of
- A_i with B_j.
-
- Most needed parameters are included in the data structure CL,
- This Data Structure is declared in util_constraint_list.h
- The following, non exhaustive list explains the most common parameters
-
- The neighborhood is computed using:
- ((CL->T[A])->pdb_param)->maximum_distance as a radius for the Bubble
- ((CL->T[A])->pdb_param)->n_excluded_nb are excluded around the central residue
- i.e i-1 and i+1 for n_excluded_nb=1.
-
-
- ((CL->T[A])->Bubble)->nb[i][0] --> Number of residues in the bubble around A_i
- ((CL->T[A])->Bubble)->nb[i][k]=j --> Index of the kth residue in the bubble
- Residues are sorted according to the Ca chain
- ((CL->T[A])->Bubble)->d_nb[i][k]=d --> Distance between A_i and A_j equals d;
-
- ((CL->T[A])->ca[i]->x -----------> Coordinates of the Ca A_i
- ((CL->T[A])->ca[i]->y
- ((CL->T[A])->ca[i]->z
-
-
-
- ((CL->T[A])->len -----------> Length of Chain A.
- ((CL->T[A])->n_atom -----------> n atoms in A.
-
-
- Unspecified parameters can be passed from the command line:
-
- align_pdb -extra_parameters=10, 10.3, 11, 12.4, my_file
-
- The values of these parameters can be accessed in:
-
- ((CL->T[A])->pdb_param)->n_extra_param=4
- ((CL->T[A])->pdb_param)->extra_param[0]="10"
- ((CL->T[A])->pdb_param)->extra_param[1]="10.3"
- ((CL->T[A])->pdb_param)->extra_param[2]="11.6"
- ((CL->T[A])->pdb_param)->extra_param[3]="my_file"
-
- These parameters contain strings! To get the real values, in C, use atoi and atof:
- atoi ( ((CL->T[A])->pdb_param)->extra_param[0])=10;
- atof ( ((CL->T[A])->pdb_param)->extra_param[1])=10.3;
-
- The maximum number of parameters is currently 1000...
-
-
-
- 2-Implementing your own function
-
- all you need to do is to edit this file and recompile align_pdb.
- There is no need to prototype any function.
-
- 10 functions holders exist, that correspond to the 10 dummy functions
- declared in this file:
- custom_pair_score_function1
- custom_pair_score_function2
- custom_pair_score_function3
- custom_pair_score_function4
- .....
- custom_pair_score_function10
-
- Let us imagine, you want to use custom_pair_function1.
-
- 1-In CUSTOM_evaluate_for_struc.c, modify custom_pair_function1,
- so that it computes the score you need.
-
- 2-If you need extra parameters, get them from ((CL->T[A])->pdb_param)->extra_param.
- 3-Recompile pdb_align:
- -put it in your bin
- -rehash or whatever
-
- 4-run the program as follows:
-
- align_pdb -in <struc1> <struc2> -hasch_mode=custom_pair_score_function1
- -extra_param=10, 12, 0.4, matrix...
-
- 5-My advice for a first time: make a very simple dummy function that spits
- out the content of extra_param.
-
- 6-Remember it is your responsability to control the number of extra parameters
- and their proper order, and type. Do not forget to apply atoi and atof to the parameters
-
- 7-Remember that the modifications you made to CUSTOM_evaluate_for_sytructure
- must be preserved by you!!! They may disappear if you update align_pdb, save them
- appart as your own patch.
-
-
-
-
-3-Using that function with T-Coffee (multiple Sequence Alignment).
-
- 1- setenv ALIGN_PDB_4_TCOFFEE <your version of align_pdb>
-
- 2- run t_coffee
- To do so, you will NOT NEED to recompile T-Coffee, simply type:
- t_coffee -in <struc1> <struc2> ... custom1_align_pdb_pair
-
-
-
-4-Syntax rules as defined by Philipp Bucher (19/06/00).
-
- Proposed ascii text notation for align_pdb
-
- First, let us summarize the align pdb algorithm in plain
- english:
-
- Given are two protein structures A and B.
-
- Step 1: For each residue in each structure extract
- the local structural neighbourhood. A neighbourhood
- is simply a subset of (usually non-consecutive)
- residues from one of the structures.
-
- Step 2: For all possible pairs of residues between structures
- A and B, compute the optimal neighbourhood alignment
- score. This score, which is also referred to as
- local neighbourhood similarity (LNS) score indicates
- whether two residues have similar local stuctural
- environemnts.
-
- Step 3: Generate one (or multiple) optimal structural alignment(s)
- for A and B based on LNS scores plus some gap penalty
- function.
-
- Now, some rules for ascii/email notation:
-
- - Whenever possible use a style which fits on one line (because it
- is painful to modify formulas that span over several lines). Example:
-
- Use: ( a**2 + b**2 )**0.5
- ________
- | 2 2
- instead of: \| a + b
-
- Introduce local variables/functions to split long expressions over
- several lines, e.g.
-
- Score = Sum(0<i<I+1) Match(A_i,B_i) where
-
- Match(A,B) = ..
-
- - Pseudosubscript notation for (multiply) indexed variables:
-
- A_i A_j_i
-
- As a general rule, I propose that we always use lower case
- letters for indices, and that the corresponding upper case letters
- denote the number of indexed objects.
-
- Index usage conventions: I propose that we use different indices
- for different objects:
-
- i a residue of structure A
- j a residue of structure B
- k a residue of a neighbourhood of structure A
- l a residue of a neighbourhood of structure B
- m a residue pair of a neignourhood alignment
- n a residue pair of a structure alignment
-
- Some examples, extensions, and additional conventions:
-
- I # of residues in structure A
- K_i # of residues of the neighbourhood of residue i of structure A
- A_k(i) # the kth residue of neighbourhood i.
- M_i,j # of residue pairs of an alignment of the neighbourhoods of
- residues i and j.
-
- The pseudosubscript notation may not always be optimal in terms clarity.
- We may occasionally use parenthesis, comma-separated susbscripts, etc.
- instead, e.g. M(i,j) or M_ij.
-
- The residues of the structures will be denoted:
-
- A_1, A_2 ... A_I
- B_1, B_2 ... B_J
-
- This is for expressing general concepts only. It is of little practical
- importance for the moment since we do not use all residue-related
- structural information from pdb. Instead we use the C-alpha coordinates
-
- C_1, C_2 ... C_I (for protein C)
- D_1, D_2 ... D_J (for protein B)
-
- for all compututations. The D_1 ... is admittedly not very intuitive
- and I'm open for other suggestions. For the scalar components of the
- C-alpha coordinates I propose that we use
-
- C_1 = CX_1, CY_1, CZ_1 = (for example) 7.51, 1.24, 3.01
-
- For the distance between two C-alpha atoms we write
-
- |C_1-C_2|
-
- which equals
-
- [ (CX_1-CX_2)**2 + (CY_1-CY_2)**2 + (CZ_1-CZ_2)**2 ]**0.5
-
- if I remember correctly from high school.
-
- Back to the algorithm:
-
- > Step 1: For each residue in each structure, extract
- > the local structural neighbourhood. A neighbourhood
- > is simply a subset of (usually non-consecutive)
- > residues from the same structure.
-
- The result is something like:
-
- P(i) = P_1(i) .. P_k(i) .. P_K_i(i)
- Q(i) = Q_1(j) .. Q_l(j) .. Q_L_j(j)
-
- These are all ordered integer arrays. The P's and Q's indicate
- residue positions in sequence space. For the C-alpha coordinates,
- we use:
-
- C(i) = C_1(i) .. C_k(i) .. C_K_i(i)
- D(i) = D_1(j) .. D_l(j) .. D_L_i(j)
-
- > Step 2: For all possible pairs of residues between structures
- > A and B, compute the optimal neighbourhood alignment
- > score. This score, which is also referred to as
- > local neighbourhood similarity (NSL) score indicates
- > whether two residues have similar local stuctural
- > environemnts.
-
- We have to define a similarity score:
-
- S(i,j) = function[A,B,P(i),Q(j)]
-
- More specifically, S(i,j) is the score of an opimal alignment between
- two subsets of C-alpha coordinates from A and B, defined by P(i) and Q(j).
- We use the following notation for an alignment between two neighbourhoods.
-
- R = (k_1,l_1) .. (k_m,l_m) .. (k_M, l_M)
-
- This is pretty abstract and requires some explanation.
-
- The alignment consists of M pairs of residues from two neighbourhoods.
- The paired residues are numbered 1,2...K and 1,2...L, respectively.
- Obviously M <= K,L. For K=9 and L=7, a possible alignment would
- look as follows:
-
- R = (1,2) , (2,3) , (5,4) , (6,5) , (9,7)
-
- This alignment consists of five paired residues, the first
- residue of neighbourhood P(i) is aligned with with the second residue
- of Q(j), etc.
-
- The score of an alignment Z(R) is a function that can be
- defined in many different ways. But independently of its
- definition:
-
- S(i,j) = Z(R*,A,B,P(i),Q(j))
- R* = argmax Z(R,A,B,P(i),Q(j))
-
- This is just a complicated way of saying that the LNS score
- S(i,j) is an optimal alignment score. A simple alignment
- scoring function would be:
-
- Z = Sum(m=1..M) [ 2 - |C_(k_m) - D_l_m)| ]
-
- A more complex function could be the sum of the sums of "pair-weights",
- "pair-connection-weights", and unpaired-residue-weights":
-
- Z = Sum(m=1 .. M) [ PW (i,P_k_m,Q_l_m,C_k_m, D_l_m) ]
- + Sum(m=2 .. M ) [ PCW(j,P_k_m,P_l_m,Q_k_m-1,Q_l_m-1,C_k_m,D_l_m,C_k_m-1,D_j_m-1 ]
- + Sum(over k for all C_i(k) unpaired) UPRW [P_k, C_k ]
- + Sum(over l for all C_i(l) unpaired) UPRW [Q_l, D_l)) ]
-
- Here, the terms P_k_m ... denote sequence positions, the terms C_k_m ...
- denote coordinates. i and j, the sequence position of the center residues
- of the neighbourhoods under consideration) are included in the argument
- lists of the functions because they are necessary to decide whether
- a residue A_k_m occurs before or after the residue A_i in sequence space.
- We don not want to align a residue A_k_m that occurs before A_i with
- a residue B_j_l that occurs after B_j and vice-versa.
-
- The LNS score could also be defined by a recursive equation system
- defining a dynamic programming algorithm. However, I find the
- above formulation more helpful for designing appropriate alignment
- scoring functions.
-
- > Step 3: Generate one (or multiple) optimal structural alignment(s)r
- > for A and B based on NLS scores plus some gap penalty
- > function.
-
- This is now pretty simple. We use essentially the same notation as
- for the neighbourhood alignments.
-
- R = (i_1,j_1) .. (i_n,j_n) .. (i_N, j_N)
-
- X* = X(R*,A,B)
- R* = argmax X(R,A,B)
-
- The alignment scoring functing X is the sum of the LNS scores
- of the pairs minus some gap penalties.
-
-
-5-Current Shortcomings
-
- At present, it is impossible to use the extra_param flag with T-Coffee. This means that
- the actual values of your parameters must be HARD-CODED within the custom_pair_score_function
- you are using.
-
- On request, I will implement a solution to solve that problem.
-
-6-Contact
- For any enquiry, please send a mail to:
- cedric.notredame@europe.com
- */
-
-
-
-
-
-
-
-
-int custom_pair_score_function1 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
- int a;
- FILE *fp;
-
- fp=vfopen ( "test_file", "w");
- for ( a=0; a< ((CL->T[0])->pdb_param)->n_extra_param; a++)
- fprintf (fp, "\n\t%s", ((CL->T[0])->pdb_param)->extra_param[a]);
-
- fprintf ( fp, "\nTEST OK");
- vfclose ( fp);
- exit (1);
-
- return score;
-
- }
-int custom_pair_score_function2 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-int custom_pair_score_function3 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-int custom_pair_score_function4 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-int custom_pair_score_function5 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-int custom_pair_score_function6 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-int custom_pair_score_function7 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-int custom_pair_score_function8 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-
-int custom_pair_score_function9 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-int custom_pair_score_function10 (Constraint_list *CL, int s1, int r1, int s2, int r2)
- {
- int score=0;
-
- return score;
-
- }
-/******************************COPYRIGHT NOTICE*******************************/
-/*© Centro de Regulacio Genomica */
-/*and */
-/*Cedric Notredame */
-/*Fri Feb 18 08:27:45 CET 2011 - Revision 596. */
-/*All rights reserved.*/
-/*This file is part of T-COFFEE.*/
-/**/
-/* T-COFFEE is free software; you can redistribute it and/or modify*/
-/* it under the terms of the GNU General Public License as published by*/
-/* the Free Software Foundation; either version 2 of the License, or*/
-/* (at your option) any later version.*/
-/**/
-/* T-COFFEE is distributed in the hope that it will be useful,*/
-/* but WITHOUT ANY WARRANTY; without even the implied warranty of*/
-/* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the*/
-/* GNU General Public License for more details.*/
-/**/
-/* You should have received a copy of the GNU General Public License*/
-/* along with Foobar; if not, write to the Free Software*/
-/* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA*/
-/*............................................... |*/
-/* If you need some more information*/
-/* cedric.notredame@europe.com*/
-/*............................................... |*/
-/**/
-/**/
-/* */
-/******************************COPYRIGHT NOTICE*******************************/
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