A5036518257- Computational Drug Discovery Methods
- Machine Learning in Materials Science
- Protein Structure and Dynamics
- Metabolomics and Mass Spectrometry Studies
- Receptor Mechanisms and Signaling
- Microbial Natural Products and Biosynthesis
- Analytical Chemistry and Chromatography
- RNA Interference and Gene Delivery
- Advanced biosensing and bioanalysis techniques
- Molecular spectroscopy and chirality
- DNA and Nucleic Acid Chemistry
- RNA and protein synthesis mechanisms
- Chemical Synthesis and Analysis
- Statistical Methods in Clinical Trials
- Drug Transport and Resistance Mechanisms
- Cholesterol and Lipid Metabolism
- Chronic Lymphocytic Leukemia Research
- Phosphodiesterase function and regulation
- Cell death mechanisms and regulation
- vaccines and immunoinformatics approaches
- Plant biochemistry and biosynthesis
- Artificial Intelligence in Healthcare
- Neuroendocrine regulation and behavior
- Neuroscience of respiration and sleep
- Monoclonal and Polyclonal Antibodies Research
Biogen (United States)
2018-2025
Pfizer (United States)
2012-2022
Institut de Biologie de l'École Normale Supérieure
2016
Inserm
2016
École Normale Supérieure - PSL
2016
Université Paris Sciences et Lettres
2016
Centre National de la Recherche Scientifique
2016
Institute for Research in Biomedicine
2012
Universitat Politècnica de Catalunya
2012
Universitat de Barcelona
2012
A fast new algorithm (Fingerprints for Ligands And Proteins or FLAP) able to describe small molecules and protein structures using a common reference framework of four-point pharmacophore fingerprints molecular-cavity shape is described in detail. The procedure starts by the GRID force field calculate molecular interaction fields, which are then used identify particular target locations where an energetic with features would be very favorable. points thus calculated FLAP build all possible...
Absorption, distribution, metabolism, and excretion (ADME), which collectively define the concentration profile of a drug at site action, are critical importance to success candidate. Recent advances in machine learning algorithms availability larger proprietary as well public ADME data sets have generated renewed interest within academic pharmaceutical science communities predicting pharmacokinetic physicochemical endpoints early discovery. In this study, we collected 120 internal...
Through the years GRID force field has been tuned to fit experimental observations in crystal structures. This paper describes determination of hydrogen bonding pattern for organic fluorines based on an exhaustive inspection Protein Data Bank. All PDB complexes, whose protein structures have cocrystallized fluorine-containing ligands, were examined and geometrically inspected. By applying statistics, geometry was described as a distribution function angle at fluorine: new specific angular...
Fully phosphorothioate antisense oligonucleotides (ASOs) with locked nucleic acids (LNAs) improve target affinity, RNase H activation and stability. LNA modified ASOs can cause hepatotoxicity, this risk is currently not fully understood. In vitro cytotoxicity screens have been reliable predictors of hepatic toxicity in non-clinical testing; however, mice are considered to be a sensitive test species. To better understand the relationship between nucleotide sequence structure-toxicity...
Chemical space is impractically large, and conventional structure-based virtual screening techniques cannot be used to simply search through the entire discover effective bioactive molecules. To address this shortcoming, we propose a generative adversarial network generate, rather than search, diverse three-dimensional ligand shapes complementary pocket. Furthermore, show that generated molecule can decoded using shape-captioning into sequence of SMILES enabling directly de novo drug design....
A supercritical fluid chromatography method was developed for the detection of intramolecular hydrogen bonds in pharmaceutically relevant molecules. The identification compounds likely to form is an important drug design consideration given correlation bonding with increased membrane permeability. technique described here correlates chromatographic retention exposed polarity a molecule. Molecules that can bond hide their and therefore exhibit lower than similar cannot. By use pairwise...
<i>N</i>-methyl-d-aspartate receptors (NMDARs) are glutamate-gated ion channels that play key roles in brain physiology and pathology. Because numerous pathologic conditions involve NMDAR overactivation, subunit-selective antagonists hold strong therapeutic potential, although clinical successes remain limited. Among the most promising NMDAR-targeting drugs allosteric inhibitors of GluN2B-containing receptors. Since discovery ifenprodil, a range GluN2B-selective compounds with strikingly...
Deep generative models applied to the generation of novel compounds in small-molecule drug design have attracted a lot attention recent years. To that interact with specific target proteins, we propose Generative Pre-Trained Transformer (GPT)-inspired model for de novo target-specific molecular design. By implementing different keys and values multi-head conditional on specified target, proposed method can generate drug-like both without target. The results show our approach (cMolGPT) is...
A series of insertion patterns for chemically modified nucleotides [2′-O-methyl (2′-OMe), 2′-fluoro (2′-F), methoxyethyl (MOE), locked nucleic acid (LNA), and G-Clamp] within antisense gapmers is studied in vitro vivo the context glucocorticoid receptor. Correlation between lipid transfection unassisted (gymnotic—using no agent) assays seen to be dependent on chemical modification, with results corresponding assay vitro. While mRNA knockdown are typically reasonable predictors results,...
The capability to rank different potential drug molecules against a protein target for potency has always been fundamental challenge in computational chemistry due its importance design. While several simulation-based methodologies exist, they are hard use prospectively and thus predicting lead optimization campaigns remains an open challenge. Here we present the first machine learning approach specifically tailored ranking congeneric series based on deep 3D-convolutional neural networks....
Virtual screening of large compound libraries to identify potential hit candidates is one the earliest steps in drug discovery. As size commercially available collections grows exponentially scale billions, active learning and Bayesian optimization have recently been proven as effective methods narrowing down search space. An essential component those a surrogate machine model that predicts desired properties compounds. accurate can achieve high sample efficiency by finding hits with only...
Multiple sclerosis (MS) is a chronic disease with an underlying pathology characterized by inflammation-driven neuronal loss, axonal injury, and demyelination. Bruton's tyrosine kinase (BTK), nonreceptor member of the TEC family kinases, involved in regulation, migration, functional activation B cells myeloid periphery central nervous system (CNS), cell types which are deemed to contributing progression MS patients. Herein, we describe discovery BIIB129 (25), structurally distinct...
A new computational algorithm for protein binding sites characterization and comparison has been developed, which uses a common reference framework of the projected ligand-space four-point pharmacophore fingerprints, includes cavity shape, can be used with diverse proteins as no structural alignment is required. Protein are first described using GRID molecular interaction fields (GRID-MIFs), FLAP (fingerprints ligands proteins) method then to encode compare this information. The...
PFRED a software application for the design, analysis, and visualization of antisense oligonucleotides siRNA is described. The provides an intuitive user-interface scientists to design library or that target specific gene interest. Moreover, tool facilitates incorporation various criteria have been shown be important stability potency. has made available as open-source project so code can easily modified address future needs oligonucleotide research community. A compiled version downloading...
Abstract The recent increase in the number of X-ray crystal structures G-protein coupled receptors (GPCRs) has been enabling for structure-based drug design (SBDD) efforts. These have revealed that GPCRs are highly dynamic macromolecules whose function is dependent on their intrinsic flexibility. Unfortunately, use static to understand ligand binding can potentially be misleading, especially systems with an inherently high degree conformational Here, we show docking a set dopamine D3...
Phosphorothioates (PS) have proven their effectiveness in the area of therapeutic oligonucleotides with applications spanning from cancer treatment to neurodegenerative disorders. Initially, PS substitution was introduced for antisense (PS ASOs) because it confers an increased nuclease resistance meanwhile ameliorates cellular uptake and in-vivo bioavailability. Thus, been elevated a fundamental asset realm gene silencing methodologies. But, despite wide use, little is known on possibly...
Covalent BTK-inhibitor drugs often contain reactive acrylamide warheads designed to irreversibly bind their protein targets at free thiol cysteines in the kinase active site. This reactivity also makes covalent inhibitors susceptible conjugation endogenous tripeptide glutathione (GSH), leading clearance. During lead optimization efforts for drug discovery of BTK inhibitor BIIB129, some expected GSH adducts resulted an unexpected and highly abundant rearrangement fragment ion LC-MS/MS. By...
In recent years, reinforcement learning (RL) has emerged as a valuable tool in drug design, offering the potential to propose and optimize molecules with desired properties. However, striking balance between capabilities, flexibility, reliability, efficiency remains challenging due complexity of advanced RL algorithms significant reliance on specialized code. this work, we introduce ACEGEN, comprehensive streamlined toolkit tailored for generative built using TorchRL, modern library that...
As part of our effort in identifying phosphodiesterase (PDE) 4B-preferring inhibitors for the treatment central nervous system (CNS) disorders, we sought to identify a positron emission tomography (PET) ligand enable target occupancy measurement vivo. Through systematic and cost-effective PET discovery process, involving expression level (Bmax) biodistribution determination, PET-specific structure-activity relationship (SAR) effort, specific binding assessment using LC-MS/MS "cold tracer"...
Ligand- (GRIND) and structure-based (GLUE/GRIND) 3D-QSAR approaches were compared for 55 (aryl-)bridged 2-aminobenzonitriles inhibiting HIV-1 reverse transcriptase (HIV-1 RT). The ligand-based model was built from conformers selected by in vacuo minimization. available X-ray structure of 3v complex with RT allowed comparative calculations using the new docking software GLUE conformer selection. Both models validated via statistics virtual receptor sites (VRS) considering pharmacophoric...
Kinases are involved in a variety of diseases such as cancer, diabetes, and arthritis. In recent years, many kinase small molecule inhibitors have been developed potential disease treatments. Despite the advances, selectivity remains one most challenging aspects inhibitor design. To interrogate selectivity, panel 45 assays has in-house at Pfizer. Here we present an application silico quantitative structure activity relationship (QSAR) models to extract rules from this experimental screening...
Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, rational design of effective sequences still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved discrimination between active and inactive small interfering RNAs (siRNAs) statistical model. Five descriptor types were used: (i) nucleotide position along siRNA sequence, (ii) composition terms presence/absence specific...