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⚗️ Metals 2492
▸ Metals — Platinum (109)
apoptosis (297)Pt (214)pt (24)ferroptosis (22)oxaliplatin (21)cisplatin (21)pyroptosis (7)necroptosis (6)transcription (6)carboplatin (5)transcription factors (5)transcriptional regulation (5)platinum (4)lead optimization (3)transcription regulation (3)metabolic adaptation (3)pt(ii) complexes (2)transcriptional regulatory interactions (2)ferroptosis induction (2)transcription initiation (2)transcription-coupled repair (2)adaptive binding (2)cellular adaptation (2)post-transcriptional regulation (2)pt(dach)methionine (1)transcription-coupled nucleotide excision repair (tc-ner) (1)triptolide (1)molecular optimization (1)pt(dach)cl4 (1)innate apoptotic immunity (1)pta (1)oligopeptides (1)transcription-coupled ner (1)ferroptosis suppressor protein 1 (fsp1) (1)apoptotic cells (1)platinumbased (1)hptab (1)signaling-transcriptional mechanisms (1)oncogene transcription inhibition (1)pt2 (1)admet optimization (1)receptor (1)pten (1)platinum(ii) (1)chain-of-thought prompt engineering (1)tetrapeptides (1)apoptotic function (1)adaptive immune response (1)gpt-2 (1)platinum drugs (1)ptii complex (1)platinum complexes (1)transcriptomics (1)cell metabolism disruption (1)peptide (1)pt(s,s-dab) (1)pt(r,r-dab) (1)pt3(hptab) (1)estrogen receptor (1)transcriptional addiction (1)transcription stress (1)septicemia (1)optical spectroscopies (1)receptors (1)selective serotonin reuptake inhibitors (ssri) (1)transcription-coupled nucleotide excision repair (1)pt(r,r-dach) (1)chiroptical response (1)diplatinum helicate (1)cyclometalated 1,3-bis(8-quinolyl) phenyl chloroplatinum(ii) (1)transcriptional activity (1)pt1 (1)disrupting a base pair (1)platinum-containing drugs (1)gpt-4 (1)transcriptional stalling (1)transcription inhibition (1)apoptotic (1)eukaryotic transcription (1)base pairing disruption (1)apoptosis-related disorders (1)coordination chemistry is not relevant, but bioinorganic and medicinal chemistry are related concepts (1)chatgpt (1)apoptosis induction (1)platinum(ii)-based (1)transcriptional activation (1)platinum-based compounds (1)inhibition of transcription factors (1)molecular descriptors (1)pt(dach)oxalato (1)polypeptide chains (1)pt(dach)cl2 (1)glp-1 receptor agonists (1)chiroptical applications (1)pt(s,s-dach) (1)cell-penetrating peptides (1)cysteine uptake (1)therapeutic optimization (1)shape description methods (1)transcription blockage (1)antiferroptotic (1)rna transcription (1)electronic absorption (1)cellular adaptation to hypoxia (1)ferroptosis suppressor protein 1 (1)apoptosis evasion (1)phosphopeptide-based kinome analysis (1)anti-apoptotic (1)gpt (1)
▸ Metals — Cobalt (185)
coordination-chemistry (102)Co (64)coordination chemistry (55)colorectal cancer (19)computational biology (7)spectroscopy (7)computational chemistry (6)computational modeling (6)pharmacology (6)co (5)pharmacovigilance (5)cryo-electron microscopy (4)glucose (4)colon cancer (4)metal complexes (4)glycolysis (4)oncology (4)pharmacokinetics (4)conformational change (3)glycocalyx (3)oncometabolite (3)complex i (3)oncosis (3)oncogenesis (2)polypharmacology (2)in-silico (2)plant secondary metabolites (2)computational approaches (2)in silico (2)convolutional neural networks (2)complex iii (2)natural compounds (2)pharmacodynamics (2)mitochondrial complex i (2)aerobic glycolysis (2)oncogene (2)covid-19 (2)microviscosity (1)pharmacometabolomics (1)complex formation (1)redox control (1)fatty alcohols (1)influence on physicochemical properties (1)fluorescence recovery after photobleaching (1)convolutional neural network (1)conditional lethality (1)picolinic acid (1)sars-cov-1 (1)metabolic control (1)pharmacological inhibition (1)pharmacokinetic (1)therapeutic controversy (1)multicolor emission (1)co2 fixation (1)protein complex (1)oncogenes (1)recombination (1)confocal microscopy (1)metal-ligand cooperation (1)cell surface recognition (1)sarcoma (1)network pharmacology (1)covalent interaction (1)escherichia coli (1)cobalamin (1)reversible compartmentalization (1)oncogene promoter regions (1)cellular compartments (1)coulometric karl fischer apparatus (1)combinatorial treatment (1)heme-containing enzymes (1)coimmunoprecipitation assay (1)glycosphingolipids (1)comorbidities (1)glycolytic activity (1)computational metabolomics (1)conformational isomerization (1)constitutive induction (1)confocal imaging (1)alcoholic hepatitis (1)knowledge discovery (1)oncogenic mutation (1)cobaltocene (1)coordination (1)computational approach (1)inorganic compounds (1)toxicology (1)conformational stability (1)connectivity mapping (1)mitochondrial uncoupling protein 2 (1)pharmacokinetic analyses (1)membrane permeability comparison (1)computer models (1)pathological conditions (1)dna condensation (1)4-octyl-itaconate (4-oi) (1)glucose dependence (1)cockayne's syndrome (1)atomic force microscope (1)complex diseases (1)dna conformational distortion (1)computational prediction (1)health economics (1)viscometry (1)conformational transitions (1)anticoagulant (1)glycome (1)oncogenic pathways (1)mitochondrial quality control (1)spin-orbit coupling (1)cytosolic ca21 concentration (1)cobamide (1)glycobiology (1)coimmunoprecipitation (1)dual protein expansion microscopy (1)brightfield microscopy (1)complexes (1)fluorescence recovery after photobleaching (frap) (1)glucose deprivation resistance (1)physicochemical properties (1)cell-like compartments (1)expansion microscopy (1)anticoagulants (1)ascorbic acid (1)oncogenic signaling (1)collective intelligence (1)cordycepin (1)genetic encoding (1)co2 (1)coupled-cluster computations (1)atp-competitive inhibitors (1)non-covalent interaction (1)computational methods (1)conformational states (1)conformational transition (1)electronic health records (1)sars-cov-2 (1)computational models (1)pharmacodynamic (1)text encoder (1)social cognition (1)sensory nerve conduction velocity (1)covalent binding (1)oncogene-mediated cellular transformation (1)fluorescence microscopy (1)glycolysis pathway (1)electronic conductometry (1)conformational landscapes (1)inductively coupled plasma mass spectrometry (1)itaconate (1)co(terpy)2+ (1)nmr spectroscopy (1)computational analysis (1)inductively coupled plasma mass spectrometer (1)coenzyme q10 (1)cell communication (1)colony formation assay (1)physico-chemical mechanisms (1)recognition (1)glycolytic enzymes (1)systems pharmacology (1)atomic force microscopy (1)computational methodologies (1)oncogenic (1)click expansion microscopy (1)glycosylation (1)n-(2-picolyl)salicylimine (1)ewing sarcoma (1)computational study (1)anticoagulation (1)confocal laser scanning microscopy (1)immuno-oncology (1)genome conformation profiling (1)somatic comorbidities (1)uv-vis spectroscopy (1)in silico analysis (1)co-immunoprecipitation (1)caco-2 cell monolayers (1)scoping review (1)conformational switch (1)damage recognition (1)entity recognition (1)energy conversion (1)noncovalent interactions (1)computer analysis (1)
▸ Metals — Iron (60)
▸ Metals — Ruthenium (86)
Ru (41)drug discovery (27)drug-delivery (23)drug resistance (11)prodrug (9)drug-drug interactions (9)drugs (7)adverse drug reactions (7)structural biology (7)drug repurposing (6)drug delivery (5)drug (5)drug development (5)g-quadruplex dna (4)ru (4)protein structure (3)drug interactions (3)structural analysis (3)drug screening (3)drug-target interaction prediction (3)g-quadruplex (3)drug design (3)drug repositioning (2)metallodrugs (2)structural data (2)drug-target interaction (2)serum (1)structure-based virtual screening (1)recruitment (1)hexammineruthenium(iii) (1)drug testing (1)spectrum diagrams (1)drug therapy (1)drug safety monitoring (1)drug sensitivity and resistance testing (1)drug safety assessment (1)structure (1)structural insights (1)adverse drug reaction detection (1)drug sensitization (1)drug target (1)truncations (1)drug-drug interaction prediction (1)protein structure-function relationship (1)pyruvate (1)drug-drug interaction identification (1)phenotypic drug screening (1)spontaneous adverse drug reaction reports (1)structural basis (1)antiviral drug discovery (1)drug tolerance (1)green rust (1)structural modeling (1)small-molecule drugs (1)structural methods (1)drug-nutrient interactions (1)adverse drug events (1)computational drug discovery (1)metal-based drugs (1)structural rearrangement (1)protein structure analysis (1)virus (1)small-molecule oral drugs (1)targeted drug delivery (1)adverse drug reaction (1)chemical drugs (1)doxorubicin (1)drug resistance reduction (1)drug-likeness (1)drug interaction prediction (1)drug target identification (1)macromolecular structure determination (1)resorufin (1)drug interaction analysis (1)drug combinations (1)non-steroidal anti-inflammatory drugs (nsaids) (1)structural bioinformatics (1)structure prediction (1)drug response (1)drug interaction screening (1)ruthenium(ii)-based (1)drug detection (1)structure-function analysis (1)metal-based drug (1)protocellular structures (1)drug interaction identification (1)
▸ Metals — Copper (63)
▸ Metals — Gold (19)
▸ Metals — Iridium (29)
▸ Metals — Others (17)
▸ Metals — Palladium (13)
▸ Metals — Zinc (5)
▸ Metals — Other (17)
🔬 Methods 1118
▸ Methods — Other experimental (213)
synthesis (246)ML (51)docking (23)natural language processing (12)in vitro (7)in vivo (6)morphological profiling (4)literature search (4)benchmarking (4)network analysis (4)image-based profiling (3)biochemical analysis (3)text analysis (3)bibliometric analysis (3)api (2)incites (2)vosviewer (2)experimental (2)theoretical studies (2)high-throughput screening (2)sequence analysis (2)information extraction (2)pubmed (2)cck-8 assay (2)statistics (2)lectin array (2)statistical approach (2)literature review (2)genetic (2)icite (2)lectin microarray (2)semantic search (2)data visualization (1)in vivo studies (1)target-based approaches (1)permeability measurement (1)gene expression profile (1)patch clamp (1)cnns (1)knockout mouse studies (1)cpg island methylator phenotype (1)in vitro models (1)immunoblot (1)bret2 (1)preclinical models (1)graph theory (1)gnns (1)passive rheology (1)nonequilibrium sensitivity analysis (1)ex vivo (1)multilayer network integration (1)inhibition assay (1)go analysis (1)experimental data analysis (1)caspase activity (1)nct (1)esm (1)web of science (1)gene expression microarray (1)uv light exposure (1)text2sql (1)decision-making (1)short tandem repeat profiling (1)in-vitro (1)analytical determination methods (1)perturbation (1)immunospecific antibodies (1)overexpression (1)mechanistic analysis (1)nuclease digestion (1)enzymatic reaction (1)excision assay (1)nuclear magnetic resonance (not explicitly mentioned but implied through study of variants) (1)pampa assay (1)experimental studies (1)null models (1)binding studies (1)clinical analysis (1)semi-supervised learning (1)efficacy analyses (1)supervised learning (1)electric field application (1)mouse model (1)estimates (1)isothermal calorimetry (1)rational design (1)learning to rank (1)gene expression analysis (1)fluorometry (1)octanol-aqueous shake-flask method (1)polypharmacy regimens (1)predictive models (1)xr-seq (1)graph learning (1)human studies (1)in vivo lung perfusion (1)merip-seq (1)uv-detection (1)atp hydrolysis (1)clinical methods (1)data processing (1)glovebox-bound apparatus (1)hoechst 33,258 staining (1)mutational analyses (1)semantic retrieval (1)solid-phase microextraction (1)immunization (1)pathscan array (1)quantitative phase behavior (1)natural bond orbital (nbo) analysis (1)ai (1)immunological analysis (1)cellular assays (1)synthetic biology tools (1)nanotherapeutic approaches (1)splicing regulation profiling (1)genome-wide screening (1)loss-of-function screens (1)histochemical staining (1)resazurin reduction assay (1)stopped-flow ph jump experiments (1)protein language model (1)experimental validation (1)matrix factorization (1)giao method (1)multi-head attention mechanism (1)rnns (1)phase ii trial (1)calorimetry (1)high throughput screening (1)trp emission (1)self-supervised learning (1)chemocentric approach (1)graph-based learning (1)tcga analysis (1)theoretical framework (1)machine-learning algorithms (1)ablation experiments (1)boolean logic (1)guanidine hydrochloride denaturation (1)ic50 index (1)statistical analysis (1)quantification (1)ensemble learning (1)in vitro study (1)relation search (1)relation extraction (1)image segmentation (1)genetic studies (1)genome-wide analysis (1)knockdown (1)ccsd(t) (1)biochemical characterization (1)performance evaluation (1)nbo 3.1 (1)rocplotter (1)mitoplast preparation (1)cryoem (1)entity annotation (1)modeling (1)systems engineering (1)database analysis (1)radiation exposure (1)prognostic tools (1)mouse models (1)nuclear magnetic resonance (1)proximity ligation assays (1)mp2(fc)/6–311 +  + (2d,2p) (1)personalized treatments (1)ncbi e-utilities (1)gradient boosting machines (1)kegg analysis (1)genetic algorithm (1)algorithms (1)experimental design (1)system-level/network analyses (1)visualized analysis (1)aimall (1)radiotherapy (1)laboratory methods (1)displacement assay (1)electrophoretic retardation measurements (1)seahorse platform (1)normoxia (1)mixture modeling (1)high-throughput (1)experimental methods (1)slot blot (1)magnetic tweezers (1)thermal denaturation (1)global genome ner (1)genetic profiling (1)mutation analysis (1)algorithm development (1)modelling (1)cell migration assay (1)methylome profiling (1)biochemical studies (1)patch clamping (1)umbrella review (1)zotero (1)immunoblotting (1)statistical methods (1)cellular models (1)miclip (1)fluorometric assay (1)enzymatic assays (1)genetic analysis (1)photophysical (1)biomedical information retrieval (1)logistic regression (1)in-vivo (1)mutational status analysis (1)
▸ Methods — Computational (31)
▸ Methods — Crystallography / Structure (4)
▸ Methods — Cell biology (21)
▸ Methods — Spectroscopy (19)
▸ Methods — Genomics / Omics (25)
▸ Methods — Mass spec / Chromatography (6)
▸ Methods — Clinical / Epidemiology (8)
▸ Methods — Electrochemistry (5)
▸ Methods — Other (1)
🎯 Targets 980
▸ Targets — Mitochondria (15)
▸ Targets — Other (157)
protein (58)enzyme (19)heme (11)gene expression (10)nucleus (9)genome (5)cardiolipin (5)enzymes (5)are (4)nucleolus (4)genetic variants (4)tfiih (4)lipids (4)signal transduction (4)cytoplasm (4)cellular metabolism (4)cell metabolism (3)cell surface (3)ribosome (3)metalloproteins (3)cells (3)cell (3)fumarate hydratase (2)dihydroorotate dehydrogenase (2)ubiquinone (2)stress response (2)tubulin (2)cytosol (2)polysulfides (2)cytochrome c oxidase (2)xpb (2)aif (2)genes (2)ribosome biogenesis (2)chromophore (1)none (1)substrates (1)clinical notes (1)acsl4 (1)protein phosphatase 2a (1)dpscs (1)albumin (1)tissues (1)trxr (1)substrate (1)platelet aggregation (1)tbk1 (1)metabolic phenotype (1)lab results (1)intracellular ph (1)sqr (1)cellular biochemistry (1)target (1)healthy cells (1)sting (1)gene targets (1)variants (1)three-way junction (1)heme-oxygenase1 (1)ddr1 (1)cajal bodies (1)target genes (1)upr (1)mif (1)heme a3 (1)nucleic acids (1)intracellular substrates (1)hydrogen sulfide (h2s) (1)mt1-mmp (1)gene (1)plasma proteins (1)adenine (1)metabolic signatures (1)nuclear foci (1)mscs (1)caspase cascade (1)p65 (1)dna synthesis (1)ddb2 (1)nuclear factor (1)hmga2 (1)ecm (1)diseases (1)spliceosomal proteins (1)neurons (1)smn protein (1)nadh/nad(p)h (1)rtk clusters (1)reactive species (1)metal (1)translation initiation (1)ligand (1)lipid droplet (1)metabolic enzymes (1)pkcd (1)protein kinases (1)peripheral nervous system (1)stem cells (1)cellular targets (1)metalloenzyme (1)chemical reactions (1)4ebp1 (1)procaspase 3 (1)ump synthase (1)rbx1 (1)literature-based evidence (1)ras (1)metabolic biomarkers (1)guanine (1)metal centers (1)ccr7 (1)cytochrome p450 2e1 (1)cell nucleus (1)lung tissue (1)ph (1)stress granules (1)erythrocytes (1)hexokinase 2 (1)nucleic acid (1)nitrogen species (1)four-way junction (1)nucleolar protein (1)p21 (1)mek1/2 (1)membrane potential (1)polysulfides (h2sn) (1)mek (1)annexin v (1)atp production (1)actin (1)traf5 (1)tme (1)cytoskeleton (1)proteoforms (1)cell cycle (1)p47phox (1)metabolome (1)cellular (1)aldoa (1)oxidants (1)zbp1 (1)cellular machines (1)atp (1)actin filaments (1)disease network (1)lipid damage (1)focal adhesions (1)p97 (1)protein sequence (1)xpc (1)whole cell (1)p38 (1)plectin (1)plasmids (1)propidium iodide (1)nadph oxidase 1 (nox1) (1)hdac enzymes (1)
▸ Targets — Nucleic acids (44)
▸ Targets — Membrane / Transport (15)
▸ Targets — Enzymes / Kinases (18)
▸ Targets — Transcription factors (5)
🦠 Diseases 880
▸ Diseases — Cancer (69)
▸ Diseases — Other (41)
▸ Diseases — Neurodegenerative (18)
▸ Diseases — Inflammatory / Immune (6)
▸ Diseases — Metabolic (5)
▸ Diseases — Cardiovascular (6)
▸ Diseases — Hepatic / Renal (8)
⚙️ Mechanisms 800
▸ Mechanisms — ROS / Redox (65)
▸ Mechanisms — Other (96)
cell cycle arrest (16)enzyme inhibition (12)phosphorylation (5)gene expression regulation (5)cell cycle regulation (4)persulfidation (3)detoxification (3)ligand dissociation (2)sequence variants (2)mechanism of action (2)resistance (2)inactivation (2)invasion inhibition (1)er stress responses (1)hormesis (1)invasiveness (1)epithelial-to-mesenchymal transition inhibition (1)oxygen-dependent metabolism (1)aquation (1)paracellular permeability (1)translation efficiency (1)denaturation (1)sequestration (1)oxidative post-translational modification (1)lipid metabolism (1)duplex unwinding (1)unfolded protein response (1)antioxidation (1)calcium regulation (1)radical formation (1)oxidative damage (1)splicing regulation (1)cell growth arrest (1)protein destabilization (1)multivalent interactions (1)protein phosphatase 2a modulation (1)protein dislocation (1)cell growth suppression (1)proteotoxic stress (1)protein rearrangements (1)p21 translation inhibition (1)gg-ner (1)pseudohypoxia (1)hypoxic response (1)electron shuttle (1)low-barrier hydrogen bond (1)kinase inhibition (1)synthetic lethality (1)stress responses (1)mutagenesis (1)subcellular relocalization (1)weak interactions (1)proton ejection (1)metabolic fuel selection (1)posttranslational modification (1)regulatory interactions (1)proton pumps (1)genetic regulation (1)protein unfolding (1)nucleolar homeostasis (1)ligand switch (1)ribosomopathies (1)oxidation-reduction (1)induced fit (1)localization (1)genetic mutation (1)mode of action (1)nucleolar stress response (1)cell killing capacity (1)ligand exchange (1)bond breaking (1)kinase activation (1)modulation (1)diadduct formation (1)cytoskeleton modulation (1)radical-mediated reaction (1)electron self-exchange (1)protein shuttling (1)pore formation (1)cellular metabolism regulation (1)nuclear export processes (1)ion selectivity (1)cell survival suppression (1)stabilization (1)cell damage (1)mitochondrial bioenergetics (1)gene therapy (1)cytochrome p450 2e1 inhibition (1)oxidative metabolic phenotype (1)phosphorylation regulation (1)aggregation (1)downregulation (1)glutamate exchange (1)acidosis (1)dysregulated gene expression (1)glycan expression (1)
▸ Mechanisms — Signaling (51)
▸ Mechanisms — Immune modulation (21)
▸ Mechanisms — DNA damage / Repair (5)
▸ Mechanisms — Epigenetic (18)
▸ Mechanisms — Cell death (7)
▸ Mechanisms — Protein interaction (14)
▸ Mechanisms — Metabolic rewiring (8)
🔗 Ligands 646
▸ Ligands — N-donor (25)
▸ Ligands — Heterocyclic (9)
▸ Ligands — C-donor / NHC (4)
▸ Ligands — S-donor (14)
▸ Ligands — O-donor (7)
▸ Ligands — Other (8)
▸ Ligands — P-donor (2)
▸ Ligands — Peptide / Protein (4)
▸ Ligands — Macrocyclic (3)
▸ Ligands — Polydentate (5)
🧠 Concepts 612
▸ Concepts — Other biomedical (178)
medicinal chemistry (122)photoactivated (27)cell biology (13)chemotherapy (11)metabolism (10)biochemistry (9)artificial intelligence (7)large language models (7)systems biology (6)information retrieval (5)precision medicine (5)gene regulation (5)data mining (5)chemoprevention (4)cheminformatics (4)therapeutic target (4)mitophagy (4)immunology (4)genetics (4)biomedical research (3)large language model (3)biomedical literature (3)hydrogen bonding (3)post-translational modifications (3)chemotherapy resistance (3)variant interpretation (3)immunometabolism (3)physiology (2)clinical practice (2)evidence extraction (2)biotransformation (2)metabolic regulation (2)physiological relevance (2)chemical biology (2)cell cycle progression (2)immunomodulation (2)biophysics (2)protein modification (2)biopharmaceutics (2)immunity (2)in vitro modeling (2)post-translational modification (2)targeted therapy (2)predictive modeling (2)therapy resistance (2)desiccant efficiency (1)multimodal data integration (1)stereochemistry (1)variant evaluation (1)epithelial-mesenchymal transition (1)metalloprotein (1)genetic screening (1)self-assembly (1)personalized therapy (1)protein function prediction (1)cellular mechanisms (1)protein targeting (1)evidence-based medicine (1)photophysics (1)protein modifications (1)translational research (1)paracellular transport (1)helicase mechanism (1)chemiosmosis (1)polarizability (1)nonequilibrium (1)genotype characterization (1)nuclear shape (1)nutrient dependency (1)metabolic engineering (1)interactome (1)therapies (1)probing (1)multiscale analysis (1)reactive species interactome (1)tissue-specific (1)pharmaceutics (1)knowledge extraction (1)metabolic activities (1)protein function (1)chemical ontology (1)proton delocalization (1)permeability (1)biomarkers (1)prediction tool (1)mechanisms of action (1)protein-ligand binding affinity prediction (1)short hydrogen bonds (1)chemical language models (1)biomedical informatics (1)organelle function (1)microbiome (1)pathogenesis (1)mechanistic framework (1)biosignatures (1)cellular stress response (1)ion-selective electrodes (1)multimodal fusion (1)gasotransmitter (1)carbon metabolism (1)bioengineering (1)ion association (1)enzyme mechanism (1)symmetry breaking (1)micropolarity (1)genome stability (1)scaffold (1)global health (1)clinical implications (1)cellular neurobiology (1)mesh indexing (1)llm (1)therapeutic strategy (1)ner (1)dissipative behavior (1)enzymology (1)pretrained model (1)longevity (1)profiling approaches (1)multimodal information integration (1)therapeutic implications (1)astrobiology (1)protein sequence analysis (1)selective degradation (1)mechanical properties (1)biomedical literature search (1)metabolism regulation (1)extracellular vesicles (1)protein chemistry (1)foundation model (1)data science (1)low-barrier hydrogen bonds (1)variant detection (1)synthetic biology (1)therapeutic innovation (1)therapeutic targeting (1)metabolic dependencies (1)protein data bank (1)cellular biology (1)phenotypic screening (1)immunoengineering (1)database (1)thermochemistry (1)therapeutic approaches (1)medical subject heading (1)network biology (1)inorganic chemistry (1)immunoregulation (1)ageing (1)protein interaction networks (1)hormone mimics (1)therapeutics (1)chemotherapy efficacy (1)metabolite-mediated regulation (1)regulatory landscape (1)chemical informatics (1)mental well-being (1)personalized medicine (1)cell plasticity (1)protein science (1)metabolic therapy (1)cell polarity (1)bioavailability (1)biomedicine (1)cellular stress (1)network medicine (1)energy transduction (1)boron helices (1)nucleolar biology (1)sialic acid (1)organic solvent drying (1)phenotypic analysis (1)in vivo perfusion (1)polypharmacy (1)hyperglycemia (1)phenotypic screens (1)mechanobiology (1)nuclear organization (1)
▸ Concepts — Bioinorganic (7)
▸ Concepts — Thermodynamics / Kinetics (10)
▸ Concepts — Evolution / Origin of life (9)
▸ Concepts — Nanomedicine / Delivery (2)
▸ Concepts — Cancer biology (1)
📦 Other 583
▸ Other (169)
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9 articles with selected tags
Galymzhan Moldagulov, Kisung Lee, Sanzhar Nurgaliyev +3 more · 2026 · Angewandte Chemie International Edition · Wiley · added 2026-04-20
ABSTRACT Understanding how metals coordinate to organic ligands is a precondition for the rational design of metal complexes and catalysts. Whereas certain types of ligands are capable of just one eas Show more
ABSTRACT Understanding how metals coordinate to organic ligands is a precondition for the rational design of metal complexes and catalysts. Whereas certain types of ligands are capable of just one easy‐to‐predict coordination modality, others may present tens and sometimes even hundreds of coordination options (mono‐, bi‐, or polydentate), and predicting the correct one may be a challenge even to seasoned chemists. The current paper describes a “hybrid” computational approach in which a Machine Learning, ML, algorithm learns to predict complex coordination patterns using knowledge‐based “rules” derived from the Cambridge Structural Database, CSD. This model is applicable to a broad scope of ligands (including hemilabile and haptic ones as well as those with denticity > 6) and different metals at different oxidation states. The algorithm's code is disclosed and can be readily deployed in RDKit via our RDMetallics python‐wrapper. It is also deployed as a publicly accessible web portal for demonstration and use. Show less
no PDF DOI: 10.1002/anie.202524655 📎 SI
Bi ML catalysis coordination-chemistry
2025 · Journal of inorganic biochemistry · Elsevier · added 2026-04-20
The series of bismuth(III) tris(8-hydroxyquinolinates); [Bi(Q")3] (1), [Bi(Q'Cl)3] (2), [Bi(QCl2)3] (3), [Bi(QBr2)3] (4), and [Bi(QIShow more
The series of bismuth(III) tris(8-hydroxyquinolinates); [Bi(Q")3] (1), [Bi(Q'Cl)3] (2), [Bi(QCl2)3] (3), [Bi(QBr2)3] (4), and [Bi(QI2)3] (5) (where Q"-H = C9H7NO; Q'Cl-H = C9H6NOCl, QCl2-H = C9H5NOCl2; QBr2-H = C9H5NOBr2; and QI2-H = C9H5NOI2) were synthesised, fully characterised, and evaluated for their antibacterial activity towards three Gram-positive bacteria (vancomycin-resistant E. faecalis, S. aureus, methicillin-resistant S. aureus), and four Gram-negative bacteria (A. baumannii, P. aeruginosa, K. pneumoniae, and E. coli) and also their cytotoxicity towards mammalian cells. New crystallographic data on 4 indicates it is dimeric in the solid state through 'Bi2O2' bridging which is consistent with data previously reported for 5. The five complexes (1-5) all exhibited good but variable antibacterial activity and selectivity. Complexes 2 and 5 showed significant activity towards Gram-positive bacteria with MIC (minimum inhibitory concentration) values ranging from 0.78 μM - 3.13 μM and selectivity indices of 6.2 - ≥16.0. For Gram-negative species, complexes 3 and 4 exhibited highly selective activity towards multi-drug resistant strains of A. baumannii with a range of MIC values 0.39-1.56 μM and selectivity indices of 3.14-7.23 respectively. While some of the 8-hydroxyquinolines themselves show reasonable antibacterial activity this is generally enhanced through complexation to bismuth(III). Show less
no PDF DOI: 10.1016/j.jinorgbio.2025.112836
Bi antibacterial
Ekaterina A. Ermakova, Yuliya A. Golubeva, Ksenia S. Smirnova +7 more · 2023 · New Journal of Chemistry · Royal Society of Chemistry · added 2026-04-20
Herein, we present the synthesis, characterization, and in vitro investigation of cytotoxic activity against cancer (HepG-2, MCF-7) and non-cancerous (Hek-293, MRC-5) cell lines of six copper( Show more
Herein, we present the synthesis, characterization, and in vitro investigation of cytotoxic activity against cancer (HepG-2, MCF-7) and non-cancerous (Hek-293, MRC-5) cell lines of six copper(II) complexes with 1H-tetrazole-5-acetic acid (H2L) and secondary ligands, such as olygopyridines (dmphen – 4,7-dimethyl-1,10-phenanthroline, phendione – 1,10 phenanthroline-5,6-dione, 5-Cl-phen – 5-chloro-1,10-phenanthroline, phen – 1,10 phenanthroline, dmbipy – 2,2′-bi-4-picoline, bipy – 2,2′-bipyridine). These compounds were characterized by powder X-ray diffraction, IR spectroscopy, elemental, and thermogravimetric analysis. The behavior of the complexes in solution was studied by optical spectroscopy, conductometry, and EPR. The DNA binding constant has been obtained for complex 5 using UV–vis spectroscopy. The antimicrobial activity of the complexes has been investigated against E. coli, S. aureus, P. italicum, and C. steinii. In addition, eight new crystal structures were obtained: [Cu(5-Cl-phen)L]n·0.5DMSO·1.5H2O (3a), [Cu(phen)L]n·2.5nH2O (4·2.5nH2O), [Cu3(phen)2(H2O)(HL)2L2]n·6nH2O (4a), [Cu(dmbipy)L]n (5), [Cu(dmbipy)(HL)2] (5a), [Cu3(dmpiby)2(HL)2L2]n·2nH2O·2nC2H5OH (5b), [Cu(bipy)L]n (6), and [Cu(bipy)(H2O)L] (6a). Show less
📄 PDF DOI: 10.1039/D3NJ00568B
Bi Cu DNA-binding Ir MCF-7 X-ray antibacterial anticancer
2020 · Journal of Molecular Liquids · Elsevier · added 2026-04-20
no PDF DOI: 10.1016/j.molliq.2019.111980
Bi tetrazole
Devjanee Bardhan, Dillip Kumar Chand · 2019 · Chemistry – A European Journal · Wiley · added 2026-04-20
AbstractMetal‐driven self‐assembly is one of the most effective approaches to lucidly design a large range of discrete 2D and 3D coordination architectures/complexes. Palladium(II)‐based self‐assemble Show more
AbstractMetal‐driven self‐assembly is one of the most effective approaches to lucidly design a large range of discrete 2D and 3D coordination architectures/complexes. Palladium(II)‐based self‐assembled coordination architectures are usually prepared by using suitable metal components, in either a partially protected form (PdL′) or typical form (Pd; charges are not shown), and designed ligand components. The self‐assembled molecules prepared by using a metal component and only one type of bi‐ or polydentate ligand (L) can be classified in the homoleptic series of complexes. On the other hand, the less explored heteroleptic series of complexes are obtained by using a metal component and at least two different types of non‐chelating bi‐ or polydentate ligands (such as La and Lb). Methods that allow the controlled generation of single, discrete heteroleptic complexes are less understood. A survey of palladium(II)‐based self‐assembled coordination cages that are heteroleptic has been made. This review article illustrates a systematic collection of such architectures and credible justification of their formation, along with reported functional aspects of the complexes. The collected heteroleptic assemblies are classified here into three sections: 1) [(PdL′)m(La)x(Lb)y]‐type complexes, in which the denticity of La and Lb is equal; 2) [(PdL′)m(La)x(Lb)y]‐type complexes, in which the denticity of La and Lb is different; and 3) [Pdm(La)x(Lb)y]‐type complexes, in which the denticity of La and Lb is equal. Representative examples of some important homoleptic architectures are also provided, wherever possible, to set a background for a better understanding of the related heteroleptic versions. The purpose of this review is to pave the way for the construction of several unique heteroleptic coordination assemblies that might exhibit emergent supramolecular functions. Show less
no PDF DOI: 10.1002/chem.201900831
Bi La Pd coordination-chemistry review
Ahmad Luqman, Victoria L. Blair, Rajini Brammananth +3 more · 2016 · European Journal of Inorganic Chemistry · Wiley · added 2026-04-20
Five mixed thiolatobismuth(III) complexes [BiPh(5‐MMTD)2{4‐MMT(H)}] (1), [Bi(1‐MMTZ)2{(PYM)(PYM(H))2}] (2), [Bi(MBT)2(5‐MMTD)] (3), [Bi(4‐BrMTD)3{2‐MMI(H)}] (4) and [Bi(1‐MMTZ)2{1‐MMTZ(H)}(2‐MMI){2‐MM Show more
Five mixed thiolatobismuth(III) complexes [BiPh(5‐MMTD)2{4‐MMT(H)}] (1), [Bi(1‐MMTZ)2{(PYM)(PYM(H))2}] (2), [Bi(MBT)2(5‐MMTD)] (3), [Bi(4‐BrMTD)3{2‐MMI(H)}] (4) and [Bi(1‐MMTZ)2{1‐MMTZ(H)}(2‐MMI){2‐MMI(H)2}] (5) were synthesised from imidazole‐, thiazole‐, thiadiazole‐, triazole‐, tetrazole‐ and pyrimidine‐based heterocyclic thiones. Four of these complexes 1–4 were synthesized from BiPh3, while complex 5 was obtained from Bi[4‐(MeO)Ph]3. Complexes 1–5 were structurally characterised by XRD. Evaluation of the antibacterial properties against Mycobacterium smegmatis, Staphylococcus aureus, Methicillin‐resistant S. aureus (MRSA), Vancomycin‐resistant Enterococcus (VRE), Enterococcus faecalis and Escherichia coli showed that mixed thiolato complexes containing the anionic thiazole‐based ligands MBT and 4‐BrMTD are most effective. The mixed thiolato complexes [Bi(MBT)2(5‐MMTD)] (3) having thiazole‐ and thiadiazole‐ and [Bi(4‐BrMBT)3{2‐MMI(H)}] (4) containing thiazole‐ and imidazole‐based ligands proved to be more efficient, with low minimum inhibitory concentrations of 1.73 and 3.45 µm for 3 against VRE and E. faecalis, respectively, and 2.20 µm for 4 against M. smegmatis and E. faecalis. All complexes showed little or no toxicity towards mammalian COS‐7 cell lines at 20 µg mL–1. Show less
no PDF DOI: 10.1002/ejic.201600076
Bi antibacterial synthesis tetrazole thiolate
Ahmad Luqman, Victoria L. Blair, Rajini Brammananth +3 more · 2014 · Chemistry – A European Journal · Wiley · added 2026-04-20
AbstractHomo‐ and heteroleptic bismuth thiolato complexes have been synthesised and characterised from biologically relevant tetrazole‐, imidazole‐, thiadiazole‐ and thiazole‐based heterocyclic thione Show more
AbstractHomo‐ and heteroleptic bismuth thiolato complexes have been synthesised and characterised from biologically relevant tetrazole‐, imidazole‐, thiadiazole‐ and thiazole‐based heterocyclic thiones (thiols): 1‐methyl‐1H‐tetrazole‐5‐thiol (1‐MMTZ(H)); 4‐methyl‐4H‐1,2,4‐triazole‐3‐thiol (4‐MTT(H)); 1‐methyl‐1H‐imidazole‐2‐thiol (2‐MMI(H)); 5‐methyl‐1,3,4‐thiadiazole‐2‐thiol (5‐MMTD(H)); 1,3,4‐thiadiazole‐2‐dithiol (2,5‐DMTD(H)2); and 4‐(4‐bromophenyl)thiazole‐2‐thiol (4‐BrMTD(H)). Reaction of BiPh3 with 1‐MMTZ(H) produced the rare BiV thiolato complex [BiPh(1‐MMTZ)4], which undergoes reduction in DMSO to give [BiPh(1‐MMTZ)2{(1‐MMTZ(H)}2]. Reactions with PhBiCl2 or BiPh3 generally produced monophenylbismuth thiolates, [BiPh(SR)2]. The crystal structures of [BiPh(1‐MMTZ)2{1‐MMTZ(H)}2], [BiPh(5‐MMTD)2], [BiPh{2,5‐DMTD(H)}2(Me2CO)] and [Bi(4‐BrMTD)3] were obtained. Evaluation of the bactericidal properties against M. smegmatis, S. aureus, MRSA, VRE, E. faecalis and E. coli showed complexes containing the anionic ligands 1‐ MMTZ, 4‐MTT and 4‐BrMTD to be most effective. The dithiolato dithione complexes [BiPh(4‐MTT)2{4‐MTT(H)}2] and [BiPh(1‐MMTZ)2{1‐MMTZ(H)}2] were most effective against all the bacteria: MICs 0.34 μM for [BiPh(4‐MTT)2{4‐MTT(H)}2] against VRE, and 1.33 μM for [BiPh(1‐MMTZ)2{1‐MMTZ(H)}2] against M. smegmatis and S. aureus. Tris‐thiolato BiIII complexes were least effective overall. All complexes showed little or no toxicity towards mammalian COS‐7 cells at 20 μg mL−1. Show less
no PDF DOI: 10.1002/chem.201404109
Bi X-ray synthesis tetrazole thiolate
Ahmad Luqman, Victoria L. Blair, Alan M. Bond +1 more · 2013 · Angewandte Chemie International Edition · Wiley · added 2026-04-20
no PDF DOI: 10.1002/anie.201301200
Bi thiolate
Martin Steegmaier, Matthias Hoffmann, Anke Baum +12 more · 2007 · Current biology : CB · Elsevier · added 2026-04-20
Fine-mapping of the cell-division cycle, notably the identification of mitotic kinase signaling pathways, provides novel opportunities for cancer-drug discovery. As a key regulator of multiple steps d Show more
Fine-mapping of the cell-division cycle, notably the identification of mitotic kinase signaling pathways, provides novel opportunities for cancer-drug discovery. As a key regulator of multiple steps during mitotic progression across eukaryotic species, the serine/threonine-specific Polo-like kinase 1 (Plk1) is highly expressed in malignant cells and serves as a negative prognostic marker in specific human cancer types . Here, we report the discovery of a potent small-molecule inhibitor of mammalian Plk1, BI 2536, which inhibits Plk1 enzyme activity at low nanomolar concentrations. The compound potently causes a mitotic arrest and induces apoptosis in human cancer cell lines of diverse tissue origin and oncogenome signature. BI 2536 inhibits growth of human tumor xenografts in nude mice and induces regression of large tumors with well-tolerated intravenous dose regimens. In treated tumors, cells arrest in prometaphase, accumulate phosphohistone H3, and contain aberrant mitotic spindles. This mitotic arrest is followed by a surge in apoptosis, detectable by immunohistochemistry and noninvasive optical and magnetic resonance imaging. For addressing the therapeutic potential of Plk1 inhibition, BI 2536 has progressed into clinical studies in patients with locally advanced or metastatic cancers. Show less
no PDF DOI: 10.1016/j.cub.2006.12.037
Bi imaging