Lucy Forrest - Prototype 01

Forrest Lab

National Institute of Neurological Disorders & Stroke

Software

1. AlignMe

Align sequences or profiles of membrane proteins, at www.bioinfo.mpg.de/AlignMe where you can:
  • Access the AlignMe Server, hosted by the Max Planck Society Bioinformatics Facility
  • Download standalone version and examples
Version 1.1
  • Position Specific Subsititution Matrices (PSSMs) supported as input
  • Support for ClustalW and fasta format outputs
  • Extract two sequences from the alignment of two averaged MSAs
  • Gaps are now "?0" in profiles - avoids conflation of gaps with zero profile values
  • Scripts for running with optimal parameters for alpha-helical proteins

 Manual for the standalone version of AlignMe 1.1

Cite these:
Stamm M, Staritzbichler R, Khafizov K, Forrest LR, 2013, PLoS ONE
Khafizov K, Staritzbichler R, Stamm M, Forrest LR, 2010, Biochemistry


2. Consensus Structure Alignments

Combines several structure alignment outputs and produces confidence scores for each position.

  scripts for computing consensus information from structure alignment programs.

Cite this:
Stamm M, Forrest LR, 2015, Proteins


3. GRIFFIN

Grid-based Force-Field Input: for setting up of membrane protein systems, by treating the protein as an implicit object (on a grid) and expelling the lipids from the region overlapping the protein. Can be run in combination with the standard molecular dynamics packages NAMD or Gromacs.

GRIFFIN pages may be accessed at faraldolab.org
Read the paper: Staritzbichler R, Anslemi C, Forrest LR, Faraldo-Gómez JD, 2011, J Chem Theor Comp 7:1167–1176


Data

1. EncoMPASS

The EncoMPASS (The Encyclopedia of Membrane Proteins Analyzed by Structure and Symmetry) database encodes structural relationships between membrane proteins, plus every structure is analyzed for symmetry. The website provides a visual interface for the symmetries and other analysis. 
The code for generating the database is on GitHub at https://github.com/EncomPASS-code/EncoMPASS


2. MemSTATS

MemSTATS (Membrane protein Structures And Their Symmetries) is a dataset designed for testing symmetry detection algorithms.
It is available on GitHub. DOI: 10.5281/zenodo.1345122


3. HOMEP3 - 2013

A dataset of families of HOmologous MEmbrane Proteins; version from 2013. Membrane proteins of known structure are classified into families with related transmembrane topologies. These can be used as a reference dataset for a range of sequence alignment and structure prediction methodologies specific to membrane proteins. Includes both alpha-helical and beta-barrel proteins.

 list of protein structures included, organized by family.

 pdb files including only the transmembrane chains.

 pairs of alpha-helical protein structures.

 pairs of beta-barrel protein structures.

Cite this:
Stamm M, Forrest LR, 2015, Proteins


4. HOMEP2 - 2010

HOmologous MEmbrane Proteins dataset from 2010. Includes only alpha-helical proteins.

 list of alpha helical proteins included.

 pdb files of alpha helical proteins including only the transmembrane chains.

 fasta files of alpha helical proteins including only the transmembrane chains.

Cite this:
Stamm M, Staritzbichler R, Khafizov K, Forrest LR, 2013, PLoS ONE 


5. Original HOMEP - (version 1.0)

HOmologous MEmbrane Proteins dataset compiled from protein structures available in 2006
HOMEP pages at the Honig Lab
(http://bhapp.c2b2.columbia.edu/software/Data_sets/homep/)
Original citation:
Forrest LR et al, 2006, Biophys J

Lab News

New team member! 

We welcome Suhwan (Paul) Lee, a new postbaccalaureate student from Ole Miss!

New insights into coupling during symport

A recent collaboration with Gary Rudnick has just been accepted for publication. We identify a key molecular interaction responsible for responding to bound ligands and required for the major transport-related conformational change. See it in the bioRxiv here.

Neurotransmitter sequestration reviewed

A review of our structure-function studies with the Schulinder lab has just been published in the Journal of General Physiology. Learn how molecular modeling has driven biochemical studies to identify key regions of the vesicular monoamine transporter, VMAT2.

 

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