stuck a bit

After discussion with Prof. Tan, I found the clustering method is not a good method to predict protein structure, because clustering is based on matrices derived from 3-d structures, and the primary sequences are simply ignored. Unless after clustering analyisis, we could find substantial similarites among members' primary sequence, there is no conclusion of the correlation between the primary sequence and 3-d structrue. In other words, we cannot predict the struture given the clustering information.

So now, I am going to change my goal of predicting protein. The work flow should be as follows:
1.
Rerun Zeyar's program to get a correct output.
Meanwhile, analyze the clusters from the clusters directory.

2.Try split the matrices into 10x10 matrices and use one clustering, and see if can get a better clustering. CM--split-->sub matrices->clusters of sub matrices->bit vectors->clusters of bit vectors->clusters of CM->cluster analysis->the applicatioin mentioned in Zeyar's paper/thesis.

Subsequent work

1. Talk to Zeyar and find the problem with his code
2. Continue to develop the rest of the matrix comparison program; make it automatically load the files in the matrix directory, read the matrix and compare.
3. When clustering is done, analysize the clusters with methods that are similar to emerging patterns. Identify the substructures (domains) that are unique in the cluster under analysis. If not found, try to use the most often occured substructure in a domain. This method has to be compared with the BLAST-Homology methods and show that my method is superior in terms of accuracy.

Xquery--An XML Query Language

Kosmix--A new searching tool

Kosmix exists quietly in the internet until recently I am doing a survey in database integration. Compared with google, it has the advantages of pre-organizing the searching results without compromising the speed. (At least in end-user level) Categories like trusted souces and advanced readings might be helpful. However, the limited results in each category may obscure many uses. Need to investigate more.

check for matalign, singular value decomposition and contact map overlap

They may be useful in comparing two matrices

Topology of a protein structure

The topology of a protein structure is a highly simplified description of tis fold including only the sequence of a secondary structure elements, and their relative spatial positions and approximate orientations.

Structural comparison methods are sometimes applicable for interface comparisons because structural comparison involves many more residues, which is deemed to be a harder problem than interfaces.

Prediction of protein–protein interactions by combining structure and sequence conservation in protein interfaces

Authors: A. Selim Aytuna, Attila Gursoy∗ and Ozlem Keskin∗ 2005
Basic idea: If A interacts with B and a's interface resembles A's and b's resembles B's, then predict a interacts with b.
Input: "template dataset" with known interacting interfaces; "target dataset" with interfaces we want to predict.

"The template dataset handles structure
and sequence conservation by combining two previously generated datasets:
the structurally non-redundant dataset of protein–protein interfaces extracted
from the PDB and the set of conserved residues on these interfaces (computational
hotspots). The target dataset is a sequentially non-redundant set of
all protein complexes and chains in the PDB."

"Proteins associate through binding sites. These sites are believed to
contribute to the biomolecular recognition and binding of proteins
by providing specific chemical and physical properties necessary
for these processes. "