Yuval Inbar - home page
I am a PhD student of Prof. Haim Wolfson
and Prof Ruth Nussinov at the Bioinfo3D lab (Tel Aviv university). My main field of interest is structural
bioinformatics and drug design. I am especially interested in the development
of algorithms that involve graph theory, combinatorics
and computational geometry to practical problems in molecular biology.
Research:
- Drug Design
- Pharmacophore
Detection: A pharmacophore is a 3D
arrangement of physico-chemical features in a ligand that is responsible for the interaction with a
receptor. In the absence of a known 3D receptor structure, a pharmacophore can be identified from a multiple
structural alignment of the ligand molecules.
We have developed PharmaGist: a novel
highly efficient method for the detection of a pharmacophore
from a set of ligands/drugs which interact with
a target receptor. The key advantages of the presented algorithm are: (a)
the ability to multiply align flexible ligands,
(b) its ability to focus on subsets of the input molecules which may
share a large common substructure, resulting in the detection both of
outliers molecules and of alternative binding modes, and (c) its
computational efficiency which allows to handle in a deterministic manner
detection of pharmacophore shared by a large
number of molecules on a standard PC. The algorithm was extensively
tested on a dataset of almost 80 ligands acting
on 12 different receptors. The results, which were achieved using a
standard default parameter set, were consistent with reference pharmacophores that were derived from the bound ligand-receptor complexes. The pharmacophores
detected by the algorithm are expected to be a key component in the
discovery of new leads by screening large drug-like molecule database [2]. The PharmaGist
webserver
is available at http://bioinfo3d.cs.tau.ac.il/PharmaGist/
.
- Virtual Screening:
We have further developed the PharmaGist
method to perform a virtual screening of drug-like molecular databases.
This application gets a small set of active ligands
and a large (thousands) molecular database. The molecules in both sets
are considered flexible. Based on the active ligands
set we detect a pharmacophore, then we check each molecule in the database for its
ability to present the detected pharmacophore
upon conformational change. The molecules are then ranked according to
this ability. The preliminary results are promising, showing that the
method has a strong discrimination ability
between active and non-active ligands.
- Protein Assembly
- Prediction of
Multi-Molecular Assemblies by Multiple Docking: The majority of proteins
function when associated in multimolecular
assemblies. Yet, prediction of the structures of multimolecular
complexes has largely not been addressed, probably due to the magnitude
of the combinatorial complexity of the problem. Docking applications have
traditionally been used to predict pairwise
interactions between molecules. We have developed an algorithm that
extends the application of docking to multi-molecular assemblies. We
apply it to predict both quaternary structures of oligomers
and multi-protein complexes. The algorithm predicted well a near native
arrangement of the input subunits for all cases in our data set, where
the number of the subunits of the different target complexes varied from
3 to 10. In
order to simulate a more realistic scenario, unbound cases were also
tested. In these cases the input conformations of the subunits are either
unbound conformations of the subunits or a model obtained by homology modelling technique. The successful predictions of
the unbound cases, where the input conformations of the subunits are
different from their conformations within the target complex, suggest
that the algorithm is robust. We expect that this type of algorithm
should be particularly useful to predict the structures of large
macromolecular assemblies, difficult to solve by experimental structure
determination.[4, 8]
- Prediction of
Symmetric Assemblies by Docking: The majority of proteins within the
cell function as symmetrical oligomeric
complexes. Symmetry gives several advantages to protein function, such as
formation of large protein structures, stability against denaturation and folding efficiency. There are many
types of symmetry in nature. We developed efficient docking methods for
predicting symmetric assemblies starting from monomeric
unit for different types of symmetry: cyclic, dihedral, cubic and
helical. All the algorithms a priori restrict their transformational
search space only to symmetric transformations, and thus gain both in
efficiency and performance.[6]
The SymmDock weserver
for prediction of (cyclic) symmetric assemblies is available at http://bioinfo3d.cs.tau.ac.il/SymmDock/
.
- Protein Folding
- Protein Structure
Prediction via Combinatorial Assembly of Sub-structural Units:
Protein structure prediction and protein docking prediction are two
related problems in molecular biology. We suggest to
use multiple docking in the process of protein structure
prediction. Once reliable structural models are predicted to disjoint
fragments of the protein target sequence, a combinatorial assembly may be
used to predict their native arrangement. CombDockFold,
a combinatorial docking algorithm for the structural units
assembly problem, is presented here. We have tested the algorithm on
various examples using both domains and domain substructures as input.
Inaccurate models of the structural units were also used, to test the robustness
of the algorithm. The algorithm was able to predict a near-native
arrangement of the input structural units in almost all of the cases,
showing that the combinatorial approach succeeds to overcome the inexact
shape complementarity caused by the inaccuracy
of the models.[9, 10]
- Image Processing of Electron Microscopy Density Maps
- 3D Segmentation of
Low and Intermediate Resolution EM Density Maps: Electron Microscopy
is becoming a powerful tool for structural studies of multimolecular
complexes. Due to physical and technological barriers most solved
structures are obtained at medium and low resolution. We present here a
novel and efficient algorithm for 3D segmentation of low and intermediate
resolution density maps. The algorithm was tested on different maps with
structures varying in their shape, architecture, resolution, and voxel size. In most cases, the algorithm
distinguished between different chains. In some cases, even different
domains of the same chain were detected.
Publication list:
- Nabil
Miled, Ying Yan, Wai-Ching Hon, Olga Perisic, Marketa
Zvelebil, Yuval Inbar,
Dina Schneidman-Duhovny, Haim
J. Wolfson, Jonathan M. Backer and Roger L. Williams
(2007) Phosphoinositide
3-kinase p110α/p85 heterodimer: Crystal
structure and mechanism for gain-of-function of selected p110α cancer-associated
mutations. Science (submitted)
- Yuval Inbar, Dina Schneidman-Duhovny,
Oranit Dror, Ruth Nussinov and Haim J. Wolfson. (2007) Deterministic Pharmacophore
Detection via Multiple Flexible Alignment of
Drug-Like Molecules. In Proc. of RECOMB 2007. (In Press)
- Haspel
N, Wainreb G, Inbar Y,
Tsai HH, Tsai CJ, Wolfson HJ and Nussinov R. (2007) A
hierarchical protein folding scheme based on the building block folding
model. Methods Mol Biol. 350:189-204
- Inbar Y, Benyamini H, Nussinov R and Wolfson H.
(2005) Combinatorial docking approach for structure prediction of large
proteins and multi-molecular assemblies. Physical Biology, 3.
- Schneidman-Duhovny,
D., Inbar, Y., Nussinov,
R., and Wolfson, H. (2005) Patch- Dock and SymmDock: servers for rigid and symmetric docking.
Nucleic Acids Res 33 (Web Server issue), 363-7.
- Schneidman-Duhovny, D., Inbar,
Y., Nussinov, R., and Wolfson,
H. (2005) Geometry based flexible and symmetric protein docking.
Proteins, 60(2):224-31.
- Inbar,
Y., Schneidman-Duhovny, D., Halperin,
I., Oron, A., Nussinov,
R., and Wolfson, H. (2005) Approaching the CAPRI Challenge with Efficient Geometry Based
Docking. Proteins, 60(2):217-23.
- Inbar, Y., Benyamini, H., Nussinov, R. and Wolfson, H.
(2005) Prediction of multimolecular
assemblies by multiple docking. (2005) J. Mol. Biol., 349, 435- 447.
- Inbar, Y., Nussinov, R. and Wolfson, H. (2005) Multiple docking for protein
structure prediction. The Int. J. of Robotics Research, 24, 131-150.
- Yuval
Inbar, Hadar Benyamini, Ruth Nussinov, Haim J. Wolfson. (2003) Protein
structure prediction via combinatorial assembly of sub-structural units.
Bioinformatics. (19 Suppl): i158-i168.
- Schneidman-Duhovny
D, Inbar Y, Polak V, Shatsky M, Halperin I, Benyamini H, Barzilai A, Dror O, Haspel N, Nussinov R, Wolfson HJ.
(2003) Taking geometry to its edge: fast unbound rigid (and hinge-bent)
docking. Proteins. 52(1): 107-12.