MEMSAT - Transmembrane Prediction Program

jones at bsm.bioc.ucl.ac.uk jones at bsm.bioc.ucl.ac.uk
Thu Mar 31 16:10:57 EST 1994


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MEMSAT - MEMbrane protein Structure And Topology
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(Reposted due to news failure at our site)

To cut down on my email load, I am making the PC implementation of the
new membrane protein structure prediction method described in

Jones,  D.T., Taylor,  W.R. & Thornton,  J.M. (1994)  A Model Recognition
Approach to the  Prediction of All-Helical Membrane Protein Structure and
Topology. Biochemistry (USA) 33:3038-3049.

available by anonymous FTP.

The software is available free if you intend to use the program for purely
academic research or teaching. Those wishing to use the program
commercially must contact me for further details. Operators of biosoftware
FTP sites please feel free to make the files available at your own site,
as long as the files are not altered.

The program runs on a 386 PC or better with 4 Mb of RAM. Source code (again
free to academics) may be obtained by contacting me by email (the source
will compile on just about any system with a C compiler).

To obtain the file (a self-extracting archive) ftp to the address
ftp.biochem.ucl.ac.uk (128.40.46.11), username "anonymous", password
"your-email-address", and obtain the files /pub/MEMSAT/README and
/pub/MEMSAT/memsatpc.exe

Also...

Copies of the data and programs for creating PAM matrices for general,
and transmembrane proteins are also available in the directory
/pub/PAM_matrices - see the README file for details, along with the
following reference:

Jones D.T., Taylor W.R. and Thornton J.M. (1994) A mutation data matrix
for transmembrane proteins. FEBS Letters 339:269-275.

The PAM matrix files are entirely in the public domain.

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A brief description of the MEMSAT program follows:

The  MEMSAT  program  implements a new method  for the prediction of  the
secondary structure and topology of all-helix  integral membrane proteins
based  on the recognition of topological models. The method employs a set
of statistical tables (log likelihood ratios) compiled from  well-charac-
terized membrane protein data, and a novel dynamic programming  algorithm
to recognize membrane topology models  by expectation  maximization.  The
statistical  tables encode definite biases  towards  certain  amino  acid
species being on the inside, middle and outside of a cellular membrane.


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This message was written, produced and executively directed by Dr David Jones
Email: jones at bioc.bsm.ucl.ac.uk         |     JANET: jones at uk.ac.ucl.bioc.bsm
Address: Dept. of Biochemistry          |       Tel: +44 71 387 7050 x3879
and Molecular Biology, University       |       Fax: +44 71 380 7193
College, London WC1E 6BT, U.K.          |
Disclaimer: STANDARD > KEYWORDS : OPINIONS MY OWN NOBODY ELSE'S WHATSOEVER




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