rFold

rFold is a set of Lua (LuaJIT) classes and submodules to build, manipulate and analyse three-dimensional protein structures.

Overview

rFold is intended to be a library of functions to assist in protein structure analysis and prediction. The predictive methodology will be largely based on kinematic and artificial intelligence approaches, but hopefully interested users can pick and choose utilities from the project to meet their own needs.

The intended development roadmap is to create functionality in roughly the following order: Build (generate 3D structure coordinates from internal phi, psi, omega and chi dihedral angles); Collect (catalogue internal coordinate and other data from known protein structures); Move (perturb structures to explore local regions of conformational space); and Evaluate (assess three dimensional residue environments based on data from known structures).

As of March 2017, both the Build and Collect modules are working. The Build module can accurately interconvert between PDB files and fully specified internal coordinates (phi, psi, omega and chi dihedral angles, plus all bond lengths and angles). The Collect module generates a database of protein internal coordinates from input protein structures.

External Dependencies

numlua -- Numeric Libraries for Lua for matrix support. I needed to pull the lua_number2int fix for this repository; possibly this should be switched to use Torch.

deque -- Queue implementation used to assemble residues for Build module.

ldoc -- Lua documentation generator.

Build

Accurate creation of 3D coordinate data from protein structure internal coordinates (phi and psi dihedral angles) requires explicit specification of all structure details: bond lengths, angles and dihedral angles. rFold defines a '.pic' ('protein internal coordinates') datafile format in which each standalone line specifies 3 atoms and their length, angle, length relationship, or 4 atoms with their dihedral angle relationship. For example:

1MUD A 1MN:1MCA:1MC 1.45628 114.95350 1.53294

1MUD A 1MN:1MCA:1MC:2QN 144.22629

In addition the coordinates for the first three atoms (usually N, CA and C) of each chain are required from the original PDB file in order to place the chain in the correct coordinate space, if the coordinates are to be compared to the PDB data.

While there is an inevitable buildup of error as residues are assembled along a protein chain, the current implementation with five decimal point precision for the internal coordinates is sufficient to exactly regenerate backbone and sidechain coordinates for PDB chains of over 1200 residues.

Using a May, 2016 cullpdb_pc20_res2.2_R1.0.curr file from the Dunbrack Lab PISCES server, 97.5% of 5,825 protein chains are regenerated exactly according to a line-by-line comparison test (see buildProtein.lua). As of June, 2016, the 143 chains generating differences have not yet been investigated.

Collect

Defines and loads a PostgreSQL database of protein internal coordinate data. Schema defined in rFold.dbm, a datafile for PgModeler - which is a PostgreSQL schema editor and design tool available at http://pgmodeler.com.br/ .
Source tree contains modified DSSP program, changed to output internal coordinate records matching PIC data above and more atom coordinates.

Executable rFoldLoadDB.lua reads PDB or PIC files, generates internal or 3D coordinates, regenerates 3D or internal coordinates and compares against input, processses with modified DSSP and compares again, loads into database and finally extracts from database and confirms that internal coordinates still match throughout. Only entries passing all tests are committed to database, others are rolled back.

Of 6389 chains in the 30 March, 2017 PISCES 'cullpdbpc20res2.0R0.25d170330_chains6389', 5941 chains (93%) are successfully loaded; this completes in about 8 hours on the development PC.

Move

Not implented.

Evaluate

Not implemented. See Miller, Douthart and Dunker 1994 for early work.

Why Lua / LuaJIT?

In addition to speed and its connection with the Torch7 Neural Nets / Scientific Computing Framework, I find Lua code remarkably easy to understand and modify long after initial development work.

License

Copyright 2016, 2017 Robert T. Miller

Licensed under the Apache License, Version 2.0 (the "License"); you may not use these files except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

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