We currently have a few open source software released to the public.
They are listed hereafter in reverse chronological order.
is an ab initio phasing method that uses a fragmentation and reassembly approach. It starts from an ensemble of low accuracy de novo models, disassembles them into fragments, places them independently in the crystallographic unit cell by molecular replacement, and then reassembles them into a whole structure that can provide sufficient phase information to enable the complete structure determination by automated model building.
allows to measure the complementarity
in electrostatics between a docked small molecule
and a protein receptor.
is a ligand-based virtual screening tool
using AutoCorrelation of Partial Charges.
The version published in the Journal of Cheminformatics was ACPC version 1.1
ACPC 1.1 was validated on this
The version shown on a poster at the Chemoinformatics Strasbourg Summer School 2014
and at JCUP V in Tokyo was ACPC 1.2 (OPAM package acpc.1.2).
ACPC 1.2 was validated on this
allows to measure the similarity of
electrostatic potentials between a docked small molecule
and a known ligand protein for the same receptor.
EleKit is intended to facilitate the design of SMPPIIs
(Small Molecule Protein-Protein Interaction Inhibitors).
is a protein fragment picker
allowing to create and query protein fragment databases.
All fragment lengths are supported and any set of PDB files can be used
to create a database.
Fragger can efficiently search a fragment database with a query
fragment and an RMSD threshold.
The query fragment can have structural gaps and the allowed
amino acid sequences matching a query can be constrained via a
regular expression of one-letter amino acid codes.
Fragger also incorporates a tool to compute the RMSD of one versus many
fragments in high throughput.
is a fragment assembly based de novo protein structure
prediction method that uses an Estimation of Distribution Algorithm for
high efficiency conformational sampling. While EdaFold, the previous
version of our software, estimates the probability mass function of
fragments based on coarse-grained models. This EdaFoldAA uses all-atom
models for the estimation of the probability mass function of fragment
with improved quality on the final predicted models.
is a tool to identify and rebuild residues in predicted
models with a large error. The error in predicted models is estimated
using the average pairwise geometric distance per residue computed among
selected lowest energy models. This error distribution among residues is
employed to guide the rebuilding process that focuses on more error-prone
residues of the coarse-grain models. MORPHEUS is implemented in C++.
It can be run either in batch mode or in parallel mode using MPI.
is a C++/MPI software prototype for fragment-based
protein structure prediction based on an Estimation of
Distribution Algorithm. Fragment-based approaches
build protein models by assembling short fragments
from known protein structures. Whereas the probability mass functions
over the fragment libraries are uniform in the
usual case, we propose an algorithm that learns from previously
generated decoys and steers the search towards native-like regions.
Durandal with QCP
We have further enhanced the performance of Durandal
a Quaternion-based Characteristic Polynomial
method to speedup RMSD calculations.
is a tool implementing entropy-accelerated exact clustering
for protein models stored in PDB files.
Clustering is commonly used to identify the best decoy
among many generated in protein structure prediction when using
energy alone is insufficient. Calculation of the pairwise distance
matrix for a large decoy set is computationally expensive. Typically,
only a reduced set of decoys using energy filtering is subjected to
clustering analysis. We propose a method using propagation of geometric
constraints to accelerate exact clustering, without compromising the
distance measure. Our method can be used with any metric distance.
Durandal became an official
Phenix tool, starting from Phenix v.1.7.2 !
is a PARallel and distributed job crusher. Bag-of-Tasks (BoT)
applications are commonly encountered in bioinformatics. They consist of a
large number of independent computation-intensive tasks. PAR is a scalable,
dynamic, parallel and distributed execution engine for Bag-of-Tasks.
PAR is aimed at multi-core architectures and small clusters.