A5041266189- Computational Drug Discovery Methods
- Protein Structure and Dynamics
- Cystic Fibrosis Research Advances
- Machine Learning in Materials Science
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Carbohydrate Chemistry and Synthesis
- Neonatal Respiratory Health Research
- Biochemical and Molecular Research
- Lysosomal Storage Disorders Research
- Enzyme Structure and Function
- Chemical Synthesis and Analysis
- Machine Learning in Bioinformatics
- Drug Transport and Resistance Mechanisms
- Receptor Mechanisms and Signaling
- Phagocytosis and Immune Regulation
- Advanced NMR Techniques and Applications
- Legume Nitrogen Fixing Symbiosis
- Molecular spectroscopy and chirality
- Monoclonal and Polyclonal Antibodies Research
- Calcium Carbonate Crystallization and Inhibition
- Molecular Biology Techniques and Applications
- Gene Regulatory Network Analysis
- Pharmacogenetics and Drug Metabolism
- Glycogen Storage Diseases and Myoclonus
Université Paris Sciences et Lettres
2016-2025
Inserm
2015-2025
Institut Curie
2015-2025
École Nationale Supérieure des Mines de Paris
2014-2024
ParisTech
2017-2019
Cancer et génome: Bioinformatique, biostatistiques et épidémiologie des systèmes complexes
2017
Génomique Bioinformatique et Applications
2017
Kyushu University
2012
Kyoto University
2012
Kyoto University Institute for Chemical Research
2012
Abstract Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes failure in process development, and withdrawal once they reached market. Therefore, silico prediction potential side-effects early discovery process, before reaching clinical stages, great interest to improve this long expensive provide new efficient safe therapies for patients. Results In present work, we propose method predict candidate molecules based...
Abstract Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in development process. This underscores importance system–wide approaches for linking different scales actions; namely drug-protein interactions (molecular scale) (phenotypic toward effect prediction uncharacterized drugs. Results: We performed large-scale analysis to extract correlated sets targeted proteins effects, based on co-occurrence drugs protein-binding profiles...
When it becomes completely possible for one to computationally forecast the impacts of harmful substances on humans, would be easier attempt addressing shortcomings existing safety testing chemicals. In this paper, we relay outcomes a community-facing DREAM contest prognosticate nature environment-based compounds, considering their likelihood have disadvantageous health-related effects human populace. Our research quantified cytotoxicity levels in 156 compounds across 884 lymphoblastic lines...
The G-protein coupled receptor (GPCR) superfamily is currently the largest class of therapeutic targets. In silico prediction interactions between GPCRs and small molecules in transmembrane ligand-binding site therefore a crucial step drug discovery process, which remains daunting task due to difficulty characterize 3D structure most GPCRs, limited amount known ligands for some members superfamily. Chemogenomics, attempts all target simultaneously, has recently been proposed as an...
Drug effects are mainly caused by the interactions between drug molecules and their target proteins including primary targets off-targets. Identification of molecular mechanisms behind overall drug-target is crucial in design process.We develop a classifier-based approach to identify chemogenomic features (the underlying associations chemical substructures protein domains) that involved interaction networks. We propose novel algorithm for extracting informative using L(1) regularized...
Predicting which molecules can bind to a given binding site of protein with known 3D structure is important decipher the function, and useful in drug design. A classical assumption structural biology that proteins similar structures have related molecular functions, therefore may ligands. However, do not display any overall sequence or similarity also ligands if they contain sites. Quantitatively assessing between sites be propose new for pocket, based on those pockets.We method quantify...
Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment the utility SNP data for predicting efficacy RA patients was performed context a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled comparative evaluation predictions developed by...
The identification of rules governing molecular recognition between drug chemical substructures and protein functional sites is a challenging issue at many stages the development process. In this paper we develop novel method to extract sets domains that govern drug-target interactions on genome-wide scale. This made possible using sparse canonical correspondence analysis (SCCA) for analyzing substructure profiles domain simultaneously. does not depend availability 3D structures. From data...
A conformational study of the double‐stranded decanucleotide d(GCCG * G ATCGC) · d(GCGATCCGGC), with guanines chelating a cis ‐Pt(NH 3 ) 2 moiety, has been accomplished using 1 H and 31 P NMR, molecular mechanics. Correlation NMR data models disclosed an equilibrium between several kinked conformations ruled out unkinked structure. The deformation is localized at CG CCG trinucleotide where helix by approximately 60° towards major groove unwound 12–19°. revealed unexpected mobility cytosine...
Cystic fibrosis is characterized by chronic inflammation and an imbalance in the concentrations of alveolar lung oxidants antioxidants, which result cell damage. Modifications glutathione are recognized as a salient feature inflammatory diseases such cystic fibrosis, plays major role protection against oxidative stress important modulation apoptosis. The transmembrane conductance regulator (CFTR) permeable to Cl<sup>−</sup>, larger organic ions, reduced oxidized forms glutathione, ΔF508 CFTR...
We introduce a family of positive definite kernels specifically optimized for the manipulation 3D structures molecules with kernel methods. The are based on comparison three-point pharmacophores present in molecules, set molecular features known to be particularly relevant virtual screening applications. computationally demanding exact implementation these kernels, as well fast approximations related classical fingerprint-based approaches. Experimental results suggest that this new approach...
Cancer driver genes, i.e., oncogenes and tumor suppressor are involved in the acquisition of important functions tumors, providing a selective growth advantage, allowing uncontrolled proliferation avoiding apoptosis. It is therefore to identify these both for fundamental understanding cancer help finding new therapeutic targets or biomarkers. Although most frequently mutated genes have been identified, it believed that many more remain be discovered, particularly specific some types. In this...
Abstract Chemogenomics, also called proteochemometrics, covers a range of computational methods that can be used to predict protein–ligand interactions at large scales in the protein and chemical spaces. They differ from more classical ligand-based (also QSAR) ligands for given receptor. In context drug discovery process, chemogenomics allows tackle question predicting off-target proteins candidates, one main causes undesirable side-effects failure within drugs development processes. The...
Abstract The challenges of drug discovery from hit identification to clinical development sometimes involves addressing scaffold hopping issues, in order optimise molecular biological activity or ADME properties, mitigate toxicology concerns a candidate. Docking is usually viewed as the method choice for isofunctional molecules, i. e. highly dissimilar molecules that share common binding modes with protein target. However, structure may not be suitable docking because low resolution, even...
Abstract Identification of novel chemotypes with biological activity similar to a known active molecule is an important challenge in drug discovery called ‘scaffold hopping’. Small‐, medium‐, and large‐step scaffold hopping efforts may lead increasing degrees chemical structure novelty respect the parent compound. In present paper, we focus on problem hopping. We assembled high quality well characterized dataset examples comprising pairs molecules including variety protein targets. This was...
Lithostathine (pancreatic stone protein, Reg protein) is, in addition to albumin, the major nonenzymatic protein of pancreatic juice. It has been assumed inhibit calcium carbonate precipitation and therefore prevent formation ducts. This function however, debatable. The assumption is based on inhibition <i>in vitro</i> crystal nucleation growth by lithostathine. Considering that these phenomena occur only under certain critical conditions, we re-examined question using a preparation where...
Cystic fibrosis is caused by mutations in the cystic transmembrane conductance regulator (CFTR) gene. The most frequent mutation deletion of F508 first nucleotide binding fold (NBF1). It induces a perturbation folding NBF1, which impedes posttranslational maturation CFTR. Determination three‐dimensional structure NBF1 would help to understand this defect. We present novel model for built from crystal bovine mitochondrial F 1 ‐ATPase protein. This gives reasonable interpretation effect on...
Identification of the protein targets hit molecules is essential in drug discovery process. Target prediction with machine learning algorithms can help accelerate this search, limiting number required experiments. However, Drug-Target Interactions databases used for training present high statistical bias, leading to a false positives, thus increasing time and cost experimental validation campaigns. To minimize positives among predicted targets, we propose new scheme choosing negative...