Didier BarradasKing Abdullah University of Science and Technology | KAUST · KAUST Catalysis Center (KCC)
Didier Barradas
Doctor of Philosophy
About
30
Publications
3,536
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273
Citations
Citations since 2017
Introduction
Additional affiliations
February 2018 - present
Position
- PostDoc Position
Description
- o Lead and develop projects for innovative expert systems for the classification of 3D models. o Generate and integrate data to generate diverse databases to train AI/ML algorithms. o Write scientific reports and present the results at international conferences.
June 2017 - February 2018
Position
- PostDoc Position
February 2011 - December 2011
Education
October 2012 - December 2016
August 2008 - February 2011
August 2002 - January 2008
Publications
Publications (30)
Reliably scoring and ranking candidate models of protein complexes and assigning their oligomeric state from the structure of the crystal lattice represent outstanding challenges. A community-wide effort was launched to tackle these challenges. The latest resources on protein complexes and interfaces were exploited to derive a benchmark dataset con...
Motivation
Protein–protein interactions drive many relevant biological events, such as infection, replication and recognition. To control or engineer such events, we need to access the molecular details of the interaction provided by experimental 3D structures. However, such experiments take time and are expensive; moreover, the current technology...
Protein-protein interactions drive many important biological events, such as infection, replication, and recognition. We need to access the molecular details of the interaction provided by experimental 3D structures to control or engineer such events. However, such experiments take time and are expensive; moreover, the current technology cannot kee...
Herein, we present the results of a machine learning approach we developed to single out correct 3D docking models of protein–protein complexes obtained by popular docking software. To this aim, we generated 3×104 docking models for each of the 230 complexes in the protein–protein benchmark, version 5, using three different docking programs (HADDOC...
We present the results for CAPRI Round 50, the 4th joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 12 targets, including 6 dimers, 3 trimers, and 3 higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interface...
Herein, we present the results of a machine learning approach we developed to single out correct 3D docking models of protein-protein complexes obtained by popular docking software. To this aim, we generated a set of ~7xE06 docking models with three different docking programs (HADDOCK, FTDock and ZDOCK) for the 230 complexes in the protein-protein...
The haloarchaeon Halorubrum lacusprofundi is among the few polyextremophilic organisms capable of surviving in one of the most extreme aquatic environments on Earth, the Deep Lake of Antarctica (−18 • C to +11.5 • C and 21-28%, w/v salt content). Hence, H. lacusprofundi has been proposed as a model for biotechnology and astrobiology to investigate...
The haloarchaeon Halorubrum lacusprofundi is among the few polyextremophilic organisms capable of surviving in one of the most extreme aquatic environments on Earth, the Deep Lake of Antarctica (−18 °C to +11.5 °C and 21–28%, w/v salt content). Hence, H. lacusprofundi has been proposed as a model for biotechnology and astrobiology to investigate po...
Background:
Properly scoring protein-protein docking models to single out the correct ones is an open challenge, also object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), a community-wide blind docking experiment. We introduced in the field CONSRANK (CONSensus RANKing), the first pure consensus method. Also available as a...
The pandemicity & the ability of the SARS-COV-2 to reinfect a cured subject, among other damaging characteristics of it, took everybody by surprise. A global collaborative scientific effort was direly required to bring learned people from different niches of medicine & data science together. Such a platform was provided by COVID19 Virtual BioHackat...
We present the results for CAPRI Round 46, the third joint CASP‐CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo‐oligomers and 6 heterocomplexes. Eight of the homo‐oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank,...
We present the results for CAPRI Round 46, the 3rd joint CASP‐CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo‐oligomers and 6 hetero‐complexes. Eight of the homo‐oligomer targets and one hetero‐dimer comprised proteins that could be readily modeled using templates from the Protein Data Bank,...
Three different models of the game of Go are developed by establishing an analogy between this game and physical systems susceptible to analysis under the well-known Ising model in two dimensions. The Ising Hamiltonian is adapted to measure the 'energy' of the Go boards generated by the interaction of the game pieces (stones) as players make their...
This work aims for modeling and simulating the metastasis of cancer, via the analogy between the cancer process and the board game Go. In the game of Go, black stones that play first could correspond to a metaphor of the birth, growth, and metastasis of cancer. Moreover, playing white stones on the second turn could correspond the inhibition of can...
Go gaming is a struggle between adversaries, black and white simple stones, and aim to control the most Go board territory for success. Rules are simple but Go game fighting is highly intricate. Stones placement and interaction on board is random-appearance, likewise interaction phenomena among basic elements in physics thermodynamics, chemistry, b...
This work aims for modeling and simulating the metastasis of cancer, via the analogy between the cancer process and the board game Go. In the game of Go, black stones that play firstcould correspond to a metaphor of the birth, growth, and metastasis of cancer. Moreover, playing white stones on the second turn could correspond the inhibition of canc...
This work aims for modeling and simulating the metastasis of cancer, via the analogy between the cancer process and the board game Go. In the game of Go, black stones play first, could correspond to metastasis of cancer. Moreover, playing white stones on the second turn would correspond to the inhibition of cancer invasion. Mathematical modeling an...
This work aims for modeling and simulating the metastasis of cancer, via the analogy between the cancer process and the board game Go. In the game of Go, black stones play first, could correspond to metastasis of cancer. Moreover, playing white stones on the second turn would correspond to the inhibition of cancer invasion. Mathematical modeling an...
Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap betwee...
Statistical analysis of nsSNPs frequencies in the disease-related protein interaction networks.
(PDF)
Proteins contained in the first layer interaction networks of the six selected diseases.
Structural coverage according to Interactome3D (EXP: experimental structure; MDL: Homology model; NS: no structure).
(CSV)
Proteins associated to each disease according to OMIM database.
(TXT)
Proteins associated to the six selected diseases based on OMIM database.
All of them have available structure or homology-based model in Interactome3D.
(TXT)
nsSNPs associated to the protein interaction networks of the six selected diseases.
They are based on humsavar, with their location in the protein according to the real complex structures (Interactome3D) or to the docking predictions (pyDockNIP extended). Many of the nsSNPs are characterized based on both structural and docking data, because they a...
Protein complexes forming the first layer interaction networks of the six selected diseases, with their structural coverage.
Structural information according to Interactome3D (EXP: experimental structure; MDL: Homology model; MDD: Domain-domain model), or docking. NS: no structure for the subunits.
(CSV)
Protein-protein interactions play fundamental roles in biological processes including signaling, metabolism and trafficking. While the structure of a protein complex reveals crucial details about the interaction, it is often difficult to acquire this information experimentally. As the number of interactions discovered increases faster than they can...
Motivation: In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction.
Results: Atomic modeling of pro...
A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biom...
The induction of DNA synthesis in various tissues of Anopheles albimanus, in response to challenge with Saccharomyces cerevisiae, Micrococcus luteus, and Serratia marcescens, was analyzed by 5-bromo-2-deoxy-uridine (BrdU) incorporation. Microorganism-inoculated mosquitoes were fed with a sucrose solution containing BrdU and maintained alive for 5 d...
Projects
Project (1)
With Hotspot prediction using protein-protein docking we attempt to identify edgeteic mutations. These mutations are the ones that alter the interface of protein, therefore changing the interaction network leading to a pathological state. The visualization of this mutation on the 3D structures of the proteins can offer explanation to the mechanism how they yield a disease phenotype and identify new pharmacological targets
