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⚗️ Metals 2487
▸ 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 1116
▸ Methods — Other experimental (213)
synthesis (244)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 659
▸ 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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2648 articles
Blotske K, Zhao X, Henry K +12 more · 2026 · medRxiv : the preprint server for health sciences · added 2026-04-20
Drug-drug interactions (DDIs) are a significant source of morbidity and adverse drug events (ADEs), particularly in situations of polypharmacy and complex medication regimens. While rules-based softwa Show more
Drug-drug interactions (DDIs) are a significant source of morbidity and adverse drug events (ADEs), particularly in situations of polypharmacy and complex medication regimens. While rules-based software integrated in electronic health records (EHRs) has demonstrated proficiency in identifying DDIs present in medication regimens, large language model (LLM) based identification requires thorough benchmarking and performance evaluation using high-quality datasets for safe use. The purpose of this study was to develop a series of performance benchmarking experiments specifically for LLM performance in identification and management of DDIs using a specifically curated clinician-annotated dataset of clinically-relevant DDIs. Show less
📄 PDF DOI: 10.64898/2025.12.03.25341549
adverse drug events benchmarking bioinformatics drug-drug interactions drugs large language models medicinal chemistry performance evaluation
Li, Da, Shi, Sanbao, Yu, Zhiyu +2 more · 2026 · Nature Publishing Group · Nature · added 2026-04-20
Artificial intelligence (AI) is being used in oncological drug development to address the high costs, low success rates, and long timelines that characterize traditional drug development pipelines. Th Show more
Artificial intelligence (AI) is being used in oncological drug development to address the high costs, low success rates, and long timelines that characterize traditional drug development pipelines. The use of machine learning (ML) and deep learning (DL) models in computer-aided drug design is constantly growing owing to their capacity to analyze large, heterogeneous datasets, their ability to capture nonlinear biological trends, and their integration of various molecular and clinical characteristics. AI applications accelerate target discovery by predicting protein structures, ranking disease-relevant genes, and assessing target drugability. AI can be used to conduct rapid searches of multiplexed chemical libraries, predict drug-target interactions, and optimize the pharmacological and physicochemical properties of drugs in virtual screening. Advanced neural network designs also aid in de novo drug design, which involves developing new molecular structures with therapeutic properties of interest. This review outlines how AI has been used for target identification, virtual screening, de novo molecular design, and, specifically, in cancer applications. It further discusses the major issues in AI-based drug development, such as data quality, model interpretation, computational constraints, and ethical and regulatory considerations, which remain essential obstacles to broader clinical translation. Show less
📄 PDF DOI: 10.1038/s41698-026-01310-7
ML amino-acid docking review
Zhao, Tianyi, Liu, Renjie, Sun, Yuzhi +8 more · 2026 · Nature Publishing Group · Nature · added 2026-04-20
DECODE is a universal deconvolution framework for both cell types and cell states that can be applied to transcriptomic, proteomic and metabolomic data.
📄 PDF DOI: 10.1038/s41592-026-03007-y
ML
2026 · European Journal of Applied Physiology · Springer · added 2026-04-21
Proteomics has matured into a discipline capable of quantifying nearly every protein encoded by the genome, yet it remains largely blind to the true operational units of physiology: proteoforms. Each Show more
Proteomics has matured into a discipline capable of quantifying nearly every protein encoded by the genome, yet it remains largely blind to the true operational units of physiology: proteoforms. Each proteoform—defined by a specific sequence and post-translationally modified state—represents a unique molecular identity with distinct chemical, functional, and structural properties. This review proposes the proteoform functor: a mathematical map between the abstract proteoform state space and the realised physiological space of biological function—and ultimately complex phenotypes. Show less
📄 PDF DOI: 10.1007/s00421-025-06096-3
bioinformatics biological function conformational states cysteine mass spectrometry neurodegenerative diseases physiological function physiology
Prabakaran, R., Bromberg, Yana · 2026 · Nature Publishing Group · Nature · added 2026-04-20
A model-agnostic empirical framework is proposed to measure the uncertainty associated with protein embeddings and to assess the biological relevance of these embeddings in order to improve model reli Show more
A model-agnostic empirical framework is proposed to measure the uncertainty associated with protein embeddings and to assess the biological relevance of these embeddings in order to improve model reliability and performance on downstream tasks. Show less
📄 PDF DOI: 10.1038/s41592-026-03028-7
amino-acid
M. V. Kashina, Kashina, M. V., M. A. Kinzhalov +1 more · 2026 · Pleiades Publishing · added 2026-04-20
Abstract This article presents the synthesis and detailed structural investigation of a new palladium(II) heteroligand complex trans-[PdCl(CNXyl)2(C{CN(H)Xyl}2)]Cl, containing an acyclic diaminocarben Show more
Abstract This article presents the synthesis and detailed structural investigation of a new palladium(II) heteroligand complex trans-[PdCl(CNXyl)2(C{CN(H)Xyl}2)]Cl, containing an acyclic diaminocarbene ligand and two isocyanide ligands. X-ray diffraction and NMR spectroscopy revealed that complex is stabilized both in the crystal and in solution by a system of N–H···Cl– hydrogen bonds formed between one chloride anion and two N–H groups of the diaminocarbene ligand (N–H···Cl–···H–N), with calculated energies of 3.8–5.4 kcal/mol. A Cambridge Structural Database search identified 22 other palladium(II) acyclic diaminocarbene complexes with similar N–H···X···H–N (X = Cl–, Br–, O=C<, O=S<, etc.) hydrogen-bonded systems. The complex demonstrated significant antiproliferative activity against the triple-negative breast cancer cell line MDA-MB-231, with an IC50 value of 5.55 ± 0.45 µM, which is four times higher than that of cisplatin. Show less
📄 PDF DOI: 10.1134/S0036023625603356
NMR Pd X-ray anticancer synthesis
2026 · Oncology Reports · added 2026-04-21
Ferroptosis is a type of programmed cell death characterized by accumulation of free iron, reactive oxygen species generation and lipid peroxidation and is distinct from other types of regulated cell Show more
Ferroptosis is a type of programmed cell death characterized by accumulation of free iron, reactive oxygen species generation and lipid peroxidation and is distinct from other types of regulated cell deaths such as apoptosis, necrosis and autophagy. Ferroptosis is distinct from other programmed cell deaths for its iron dependence and its significant role in tumor suppression. Therefore, harnessing ferroptosis may offer promising avenues for cancer therapy. In the present review, the different pathways that lead to ferroptosis, the genes and transcription factors involved in both iron and lipid metabolism, as well as the impact of small‑molecule alterations on the regulation of ferroptotic cell death, were discussed. Furthermore, the emergence of combination therapies with ferroptosis‑inducing molecules that overcome resistance to conventional chemotherapy, particularly in solid tumors, were highlighted. Show less
📄 PDF DOI: 10.3892/or.2025.9029
anticancer cancer cancer therapy cell membrane glutathione gsh iron lipid peroxidation
Chen, Yujie, Liu, Zhiyuan, Xu, Heming +8 more · 2026 · Nature Publishing Group · Nature · added 2026-04-20
Combining single-cell parallel profiling of genome conformation, histone modifications, chromatin accessibility and gene expression reveals dynamics and intranuclear spatial clustering of epigenome pr Show more
Combining single-cell parallel profiling of genome conformation, histone modifications, chromatin accessibility and gene expression reveals dynamics and intranuclear spatial clustering of epigenome profiles, enabling sophisticated analysis of the regulatory landscape across cell types and tissues. Show less
📄 PDF DOI: 10.1038/s41586-026-10322-z
chromatin chromatin accessibility analysis chromatin biology epigenome profiling epigenomics four-omics sequencing gene expression analysis gene regulation
Chengnan Wu, Nikolai F. Romashev, Veronika I. Komlyagina +9 more · 2026 · Inorganic Chemistry Frontiers · Royal Society of Chemistry · added 2026-04-20
While various metal complexes demonstrate immunogenic cell death (ICD)-inducing properties, there is a lack of studies comparing ICD properties in structurally similar complexes with different Show more
While various metal complexes demonstrate immunogenic cell death (ICD)-inducing properties, there is a lack of studies comparing ICD properties in structurally similar complexes with different metal centers. In this study, we synthesized four structurally similar Rh(I) and Ir(I) complexes with redox-active 1,2-bis(arylimino)acenaphthene (Ar-bian) ligands and assessed their anticancer and ICD-inducing properties. Analysis of damage-associated molecular patterns (DAMPs), ROS localization and dying cell populations highlighted the distinct roles of the metal center and the ligands. Specifically, only Rh(I) complexes induced the release of the three essential DAMPs and high levels of late apoptotic cells, while the Ir(I) complexes failed to trigger crucial “eat-me” signals. This work offers valuable insights into structure–activity relationships in metal complexes in the context of ICD. Show less
📄 PDF DOI: 10.1039/D5QI00868A
Ir ROS Rh anticancer coordination-chemistry immunogenic synthesis
Mouawad N, El Jaafari N, El Sibai M +1 more · 2026 · Oncology Reports · added 2026-04-20
Ferroptosis is a type of programmed cell death characterized by accumulation of free iron, reactive oxygen species generation and lipid peroxidation and is distinct from other types of regulated cell Show more
Ferroptosis is a type of programmed cell death characterized by accumulation of free iron, reactive oxygen species generation and lipid peroxidation and is distinct from other types of regulated cell deaths such as apoptosis, necrosis and autophagy. Ferroptosis is distinct from other programmed cell deaths for its iron dependence and its significant role in tumor suppression. Therefore, harnessing ferroptosis may offer promising avenues for cancer therapy. In the present review, the different pathways that lead to ferroptosis, the genes and transcription factors involved in both iron and lipid metabolism, as well as the impact of small‑molecule alterations on the regulation of ferroptotic cell death, were discussed. Furthermore, the emergence of combination therapies with ferroptosis‑inducing molecules that overcome resistance to conventional chemotherapy, particularly in solid tumors, were highlighted. Show less
📄 PDF DOI: 10.3892/or.2025.9029
Fe ROS review
Richard Rudolf, Biprajit Sarkar · 2026 · Inorganic Chemistry Frontiers · Royal Society of Chemistry · added 2026-04-20
Mesoionic imines (MIIs) based on a 1,2,3-triazole core have been popularized in the past ca. 5 years. In this review article we discuss the synthesis, coordination ability and the structural a Show more
Mesoionic imines (MIIs) based on a 1,2,3-triazole core have been popularized in the past ca. 5 years. In this review article we discuss the synthesis, coordination ability and the structural and spectroscopic properties of this fascinating class of electronically ambivalent compounds. Apart from this, we also discuss the utility of MIIs and their compounds in directed C–H activation reactions, and in the activation and conversion of small molecules such as alkynes and CO2. Based on the current state of the art, we touch upon possible future developments of the chemistry of these classes of molecules. Show less
📄 PDF DOI: 10.1039/D5QI01569C
catalysis review synthesis
Gianluca Righetti, Georgyi Koidan, Sergiy L. Filimonchuk +3 more · 2026 · Chemical Science · Royal Society of Chemistry · added 2026-05-10
Many ligands are structurally rigid and well-defined, e.g. N-heterocyclic carbenes display a fan-like structure with a defined buried volume. Here, we break this dogma by introducing more flexibility Show more
Many ligands are structurally rigid and well-defined, e.g. N-heterocyclic carbenes display a fan-like structure with a defined buried volume. Here, we break this dogma by introducing more flexibility around the catalytically active center by using acyclic (diamino)carbene (ADC) ligands. The ADC ligand was constructed in a straightforward protocol on the ruthenium center via methyl isocyanide coordination and subsequent reaction with amines such as pyrrolidine. Ligand flexibility in the formed (pyrrolidine)(methylamine)carbene ruthenium complex Ru-2 was demonstrated both in solution (variable temperature NMR) and in the solid state through crystallographic identification with the protic NH site oriented either distal or proximal to the ruthenium center. In contrast to their cyclic analogues, the Ru-ADC complexes are highly active in base-free transfer hydrogenation, with turnover numbers >1000. The base-free conditions allowed for the transformation of substrates with base-sensitive groups such as esters, amides, acids, and amines, substrates that typically fail to undergo transfer hydrogenation under classical conditions. The absence of base also enabled late-stage hydrogenation of more complex substrates, and it avoids complications such as corrosion attributed to KOH and related strong bases. Show less
📄 PDF DOI: 10.1039/d5sc08206d
carbene
Kevlishvili, Ilia, Dorabawila, Devmin · 2026 · American Chemical Society (ACS) · added 2026-05-10
Canonical string representations have transformed organic cheminformatics, yet transition-metal complexes (TMCs) lack an equivalent that captures coordination geometry, stereochemistry, and donor t...
📄 PDF DOI: 10.26434/chemrxiv-2025-7s3gx/v2
Mariia Beliaeva, Andrey Belyaev, Henna Korhonen +4 more · 2026 · Inorganic Chemistry Frontiers · Royal Society of Chemistry · added 2026-04-20
Hybrid phosphines with anionic hard donor functions can be used to create an adaptable ligand environment for soft late transition metals. Herein, we show that the change of coordination of a Show more
Hybrid phosphines with anionic hard donor functions can be used to create an adaptable ligand environment for soft late transition metals. Herein, we show that the change of coordination of a diphosphine–phosphinic acid (P3OOH) in response to acid–base interactions or hydrogen bonding results in structural transformations of a disilver complex [Ag2(P3OO)2] (1) to give solvated and protonated derivatives [Ag2(P3OOH)2]2+ (2) and [Ag3(P3OO)3H]+ (3), accompanied by the alteration of the quantum yield of the solid-state photoluminescence from 0.06 up to 0.69. The related diphosphine–phosphide oxide complexes [M2(P3O)2] (M = Ag, Au) are oxidized to phosphinate compounds 2 and non-luminescent [Au2(P3OO)2H]+ (5) in the presence of triflic acid. Alternatively, [Au2(P3O)2] readily accommodates an additional gold(I) ion to yield a trinuclear cluster [Au3(P3O)2]+ (6), which is brightly sky-blue phosphorescent in the crystalline state (Φem = 0.76). The phosphide oxide group −PO in 6 is stable towards oxidation under acidic conditions in solution but undergoes protonation that results in two orders of magnitude (>170-fold) increase of the emission intensity. Complex 6 acts as a guest in the crystalline matrix of 5 due to their structural similarity and affords solid solutions with bright luminescence at a doping content of 1–2%. Show less
📄 PDF DOI: 10.1039/D5QI01622C
Ag Au coordination-chemistry imaging phosphine
Cooper, Melissa L. · 2026 · Nature · Nature · added 2026-04-24
Communication between distant brain regions is mediated by plastic networks of gap&nbsp;junction-coupled astrocytes.
📄 PDF DOI: 10.1038/s41586-026-10426-6
astrocytes brain cell biology gap junctions networks neuroscience plasticity
James N Cobley · 2026 · European Journal of Applied Physiology · Springer · added 2026-04-20
Proteomics has matured into a discipline capable of quantifying nearly every protein encoded by the genome, yet it remains largely blind to the true operational units of physiology: proteoforms. Each Show more
Proteomics has matured into a discipline capable of quantifying nearly every protein encoded by the genome, yet it remains largely blind to the true operational units of physiology: proteoforms. Each proteoform—defined by a specific sequence and post-translationally modified state—represents a unique molecular identity with distinct chemical, functional, and structural properties. This review proposes the proteoform functor: a mathematical map between the abstract proteoform state space and the realised physiological space of biological function—and ultimately complex phenotypes. This mapping is not linear or additive. Rather, it is hierarchical, nonlinear, and context-dependent, reflecting the emergent complexity of life. Without resolving proteoforms, proteomics risks describing shadows of biology rather than its material substance. Deciphering complex phenotypes, demands a shift from bulk protein averages to revealing the precise molecular identities—proteoforms—that give rise to physiology. Show less
📄 PDF DOI: 10.1007/s00421-025-06096-3
amino-acid review
2026 · Nucleic acids research · Oxford University Press · added 2026-04-21
Biomedical research benefits from the rapid growth and diversity of experimentally detected protein–protein interactions (PPIs) by gaining important biological insights. However, increasingly dense PP Show more
Biomedical research benefits from the rapid growth and diversity of experimentally detected protein–protein interactions (PPIs) by gaining important biological insights. However, increasingly dense PPI networks can be challenging to interpret and apply. The 2025 update of the Integrated Interactions Database (IID) enhances accessibility and utility through several new features. We identify and incorporate network structural components from co-purified protein sets, as well as curated and predicted complexes, enabling users to explore network organization Show less
📄 PDF DOI: 10.1093/nar/gkaf1259
bioinformatics cancer immunology molecular docking network analysis osteoarthritis protein protein interaction networks
2026 · Apoptosis · Springer · added 2026-04-20
Fluorescein isothiocyanate-conjugated Annexin V in combination with propidium iodide (PI) labelling is a widely used flow cytometric assay for quantifying apoptotic and necrotic cells in anticancer st Show more
Fluorescein isothiocyanate-conjugated Annexin V in combination with propidium iodide (PI) labelling is a widely used flow cytometric assay for quantifying apoptotic and necrotic cells in anticancer studies. However, increasing evidence suggests that double-positive cells, or the Annexin V⁺/PI⁺ fraction, may represent not only late apoptosis but also different modalities of regulated cell death, including necroptosis, pyroptosis, ferroptosis, and cuproptosis. By collating findings from preclinical studies across different cancer cells, this review highlights the need for consensus in interpreting Annexin V⁺/PI⁺ populations. In the absence of molecular and/or microscopy data, this fraction is more appropriately classified as undergoing 'late-stage cell death'. In short, establishing standardised interpretive criteria is crucial to enhance understanding, facilitate cross-study comparability, and improve the translational relevance of anticancer research. Show less
📄 PDF DOI: 10.1007/s10495-026-02261-x
annexin v anticancer cancer flow cytometry medicinal chemistry propidium iodide
Kotlyar M, Pastrello C, Abovsky M +5 more · 2026 · Nucleic acids research · Oxford University Press · added 2026-04-20
Biomedical research benefits from the rapid growth and diversity of experimentally detected protein-protein interactions (PPIs) by gaining important biological insights. However, increasingly dense PP Show more
Biomedical research benefits from the rapid growth and diversity of experimentally detected protein-protein interactions (PPIs) by gaining important biological insights. However, increasingly dense PPI networks can be challenging to interpret and apply. The 2025 update of the Integrated Interactions Database (IID) enhances accessibility and utility through several new features. We identify and incorporate network structural components from co-purified protein sets, as well as curated and predicted complexes, enabling users to explore network organization beyond binary interactions. Functional, pathway, and disease associations of these components can be analyzed, enabling interactions to be grouped into higher-order structures with known or provisional biological roles. Users can now filter interactions by five detection types: pairwise, co-purification, colocalization, proximity, and other evidence. To extend the value and information of predicted interactions, we include interaction interface predictions for 53 647 PPIs, generated using the MEGADOCK docking algorithm, adding molecular detail for structural biology and variant impact studies. Finally, we map PPIs to 15 immune cell types and 12 additional normal tissues, offering tissue-specific views of interaction networks increasingly relevant in disease and immunology research. IID 2025 now includes over 1 million experimentally detected human PPIs, representing an 83% increase from the previous release, alongside expanded non-human networks. The portal remains publicly available at https://ophid.utoronto.ca/iid. Show less
📄 PDF DOI: 10.1093/nar/gkaf1259
Co amino-acid docking
Danil P. Zarezin, Alexander A. Shtil, Valentin G. Nenajdenko +1 more · 2026 · RSC Medicinal Chemistry · Royal Society of Chemistry · added 2026-04-20
This study investigates the application of machine learning techniques to predict the toxicity of tetrazole derivatives, aiding in the identification of environmental risks from chemical expos Show more
This study investigates the application of machine learning techniques to predict the toxicity of tetrazole derivatives, aiding in the identification of environmental risks from chemical exposure. Utilizing LD50 data sourced from the scientific literature and the ChemIDplus database, regression models were developed to forecast acute intraperitoneal toxicity in mice. A machine learning regression model for acute intraperitoneal toxicity in mice was constructed and validated on a test dataset, achieving high accuracy (R2 = 0.76 and MSE below 10−4) and surpassing most of the comparable literature models. Molecular descriptors were computed via Mordred software to explore quantitative structure–activity relationships, and additionally, the model's robustness was demonstrated by measuring the acute toxicity of tetrazole derivatives synthesized through the azido-Ugi reaction. Show less
📄 PDF DOI: 10.1039/D5MD00757G
ML synthesis tetrazole
Zabala-Letona, Amaia, Pujana-Vaquerizo, Mikel, Martinez-Laosa, Belen +49 more · 2026 · Nature Publishing Group · Nature · added 2026-04-20
Polyamines prevent the action of kinases on acidic phosphorylatable motifs in spliceosomal proteins, thus providing a mechanism for metabolite-mediated regulation of alternative splicing in cells.
📄 PDF DOI: 10.1038/s41586-025-09965-1
alternative splicing bioinorganic kinase inhibition metabolite-mediated regulation polyamines protein spliceosomal proteins
Zhi-Yuan Li, Long-Bo Yu, Qing-Hua Shen +5 more · 2026 · Chemical Science · Royal Society of Chemistry · added 2026-04-20
Zinc is a crucial element in cellular processes, and its homeostasis has intricate relationships with the initiation, progression, and therapeutic intervention of cancer. Activation of the cyc Show more
Zinc is a crucial element in cellular processes, and its homeostasis has intricate relationships with the initiation, progression, and therapeutic intervention of cancer. Activation of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway has been proven to be an effective strategy for cancer immunotherapy. Herein, we report four phosphorescent iridium complexes (Ir1–Ir4) with zinc chelating ligands. Among them, Ir1 can bind and image mitochondrial chelatable zinc ions via phosphorescence-lifetime responses, consequently modulating the expression of zinc-regulatory proteins. Furthermore, the in situ formed heteronuclear metal complex Ir1-Zn2 shows nuclease mimetic activities, capable of hydrolyzing mitochondrial DNA (mtDNA) to release mtDNA fragments for the activation of the cGAS-STING pathway. In conclusion, we designed a mitochondria-targeting phosphorescent Ir(III) complex with dual functions in dysregulation of zinc homeostasis and generation of nuclease in situ, which provides an innovative approach to stimulate the cGAS-STING pathway. Show less
📄 PDF DOI: 10.1039/D5SC07181J
Ir Zn coordination-chemistry imaging mitochondria
2025 · Therapeutic advances in drug safety · SAGE Publications · added 2026-04-21
Background: Adverse drug reactions (ADRs) are harmful side effects of medications. Social media provides real-time, patient-generated data, though its unstructured format presents challenges. Natural Show more
Background: Adverse drug reactions (ADRs) are harmful side effects of medications. Social media provides real-time, patient-generated data, though its unstructured format presents challenges. Natural language processing and transfer learning offer promising solutions. Objective: This study aimed to evaluate whether transformer-based models fine-tuned on a general ADR dataset can effectively classify ADRs from tweets related to glucagon-like peptide-1 (GLP-1) receptor agonists and to benchmark their performance against state-ofthe-art large language models (LLMs). Show less
📄 PDF DOI: 10.1177/20420986251405082
adr detection adverse drug reactions artificial intelligence bert bioinformatics fine-tuning glp-1 receptor agonists gpt-2
Behrooznia S, Hooshmand M · 2025 · ACS Omega · ACS Publications · added 2026-04-20
Computational drug discovery is essential for screening potential treatments and reducing the costs and time associated with proposing or combining drugs for disease management. Despite the extensive Show more
Computational drug discovery is essential for screening potential treatments and reducing the costs and time associated with proposing or combining drugs for disease management. Despite the extensive research conducted in this field, it remains an emerging area, particularly with the advent of machine learning, deep learning, and large language models (LLMs). This systematic review examines the integration of machine learning and deep learning techniques in drug discovery, concentrating on three critical areas: drug-drug interactions (DDIs), drug-target interactions (DTIs), and adverse drug reactions (ADRs). The review analyzes over 100 papers published between 2020 and 2025, categorizing the methods into deep learning, machine learning, graph learning, and hybrid models. It highlights the transformative impact of natural language processing (NLP) and LLMs in extracting meaningful insights from biomedical literature and chemical data. Furthermore, this work introduces key databases and data sets widely utilized in drug discovery. Additionally, this review identifies gaps in the existing research, such as the lack of comprehensive studies that simultaneously address DDI, DTI, and ADR extraction, and it proposes a more holistic approach to fill these gaps. The paper concludes by thoroughly evaluating various models, underscoring their performance metrics. Show less
📄 PDF DOI: 10.1021/acsomega.5c04997
ML review
2025 · Bioinformatics · Oxford University Press · added 2026-04-21
Motivation: Proteins are of great significance in living organisms. However, understanding their functions encounters numerous challenges, such as insufficient integration of multimodal information, a Show more
Motivation: Proteins are of great significance in living organisms. However, understanding their functions encounters numerous challenges, such as insufficient integration of multimodal information, a large number of training parameters, limited flexibility of classification-based methods, and the lack of systematic evaluation metrics for protein question answering systems. To tackle these issues, we propose the Prot2Chat framework. Results: We modified ProteinMPNN to encode protein sequence and structural information in a unified way. We used a large language model Show less
📄 PDF DOI: 10.1093/bioinformatics/btaf396
amino acid bioinformatics large language model multimodal information integration protein protein function prediction protein sequence protein sequence analysis
2025 · Discover Oncology · Springer · added 2026-04-21
Introduction Mitochondria are essential organelles for many aspects of cellular homeostasis. They play an indispensable role in the development and progression of diseases, particularly cancer which i Show more
Introduction Mitochondria are essential organelles for many aspects of cellular homeostasis. They play an indispensable role in the development and progression of diseases, particularly cancer which is a major cause of death worldwide. We analyzed the scientific research output on mitochondria and cancer via PubMed and Web of Science over the period 1990–2023. Methods Bibliometric analysis was performed by extracting data linking mitochondria to cancer pathogenesis over the period 1990–2023 from the PubMed database which has a precise and specific search engine. Only articles and reviews were considered. Since PubMed does not support analyses by countries or institutions, we utilized InCites, an analytical tool developed and marketed by Clarivate Analytics. We also used the VOSviewer software developed by the Centre for Science and Technology Studies (Bibliometric Department of Leiden University, Leiden, Netherlands), which enables us to graphically represent links between countries, authors or keywords in cluster form. Finally, we used iCite, a tool developed by the NIH (USA) to access a dashboard of bibliometrics for papers associated with a portfolio. This module can therefore be used to measure whether the research carried out is still basic, translational or clinical. Results In total, 169,555 publications were identified in PubMed relating to ‘mitochondria’, of which 34,949 (20.61%) concerned ‘mitochondria’ and ‘dysfunction’ and 22,406 (13.21%) regarded ‘mitochondria’ and ‘cancer’. Hence, not all mitochondrial dysfunctions may lead to cancer or enhance its progression. Qualitatively, the disciplines of journals were classified into 166 categories among which cancer specialty accounts for only 4.7% of publications. Quantitatively, our analysis showed that cancer/neoplasms in the liver (2569 articles) were placed in the first position. USA occupied the first position among countries contributing the highest number of publications (5695 articles), whereas Egypt came in the thirty-eight position with 84 publications (0.46%). Importantly, USA is the first-ranked country having both the top 1% and 10% impact indicators with 207 and 1459 articles, respectively. By crossing the query ‘liver neoplasms’ (155,678) with the query ‘mitochondria’ (169,555), we identified 1336 articles in PubMed over the study period. Among these publications, research areas were classified into 65 categories with the highest percentage of documents included in biochemistry and molecular biology (28.92%), followed by oncology (23.31%). Conclusions This study underscores the crucial yet underrepresented role of mitochondria in cancer research. Despite their significance in cancer pathogenesis, the proportion of related publications remains relatively low. Our findings Supplementary Information The online version contains supplementary material available at https://​doi.​org/​10.​1007/​s12672-​025-​ 02139-5. * Abeer El Wakil, abeer_elwakil@alexu.edu.eg; Patrick Devos, patrick.devos@univ-lille.fr; Heba Abdelmegeed, hn.abdelmegeed@ nrc.sci.eg; Alaa Kamel, alaa.kamel_pg@alexu.edu.eg | 1Department of Biological and Geological Sciences, Faculty of Education, Alexandria University, Alexandria 21526, Egypt. 2Université Lille, Lillometrics, 59000 Lille, France. 3CHU Lille, Direction de la Recherche et de l’Innovation, 59000 Lille, France. 4Department of Chemistry of Natural Compounds, National Research Centre, Giza, Egypt. 5Department of Zoology, Faulty of Science, Alexandria University, Alexandria, Egypt. Discover Oncology (2025) 16:517 | https://doi.org/10.1007/s12672-025-02139-5 Vol.:(0123456789) Research Discover Oncology (2025) 16:517 | https://doi.org/10.1007/s12672-025-02139-5 highlight the need for further research to deepen our understanding of mitochondrial mechanisms in cancer, which could pave the way for new therapeutic strategies. Graphical Abstract Show less
📄 PDF DOI: 10.1007/s12672-025-02139-5
bibliometric analysis bioinorganic cancer cancer pathogenesis icite incites medicinal chemistry mitochondria
Passi I, Sugantharam K, Sumithaa C +3 more · 2025 · Journal of Materials Chemistry B · Royal Society of Chemistry · added 2026-05-01
The clinical success of metal-based anticancer agents can be achieved by developing not only an efficient metallodrug but also a suitable drug delivery system (DDS). Although spatiotemporal delivery, Show more
The clinical success of metal-based anticancer agents can be achieved by developing not only an efficient metallodrug but also a suitable drug delivery system (DDS). Although spatiotemporal delivery, enhancing the efficacy, and alleviating toxicity are achievable, modifying the mechanism of action of metallodrugs using a nano DDS remains scarce. With all this in mind, a series of cyclometalated ruthenium(II) half-sandwich complexes of the type [(η6-p-cymene)Ru(L)Cl] Ru(1)-Ru(4), where L is 2-phenylquinoline (L1), 2-(thiophen-2-yl)quinoline (L2), 4-methyl-2-phenylquinoline (L3), or 2,4-diphenylquinoline (L4), have been isolated and characterized by analytical and spectroscopic methods. Ru(1) and Ru(2) have been structurally characterized, and their coordination geometries around the ruthenium(II) are described as pseudo-octahedral geometry. Only the Ru(1) complex, which exhibited substantial cytotoxicity in non-cancerous cells and low cytotoxicity in breast cancer cells, is encapsulated into a hybrid nanosystem comprising phospholipid and polydiacetylene. The Ru(1)-entrapped nanoassembly (PDL-Ru(1)) is found to show pH-induced emission and higher release of the complex in a simulated tumor environment than in a physiological environment. Even though such a halochromic character failed to benefit cell imaging, the nanocarrier-mediated delivery has been proven to improve the cytotoxicity of Ru(1) in breast cancer cells, modulate the mode of cell death, and reduce toxicity in normal cells. Zebrafish embryo toxicity studies revealed that polydiacetylene-lipid nanoassembly could be useful for in vivo biocompatibility applications of ruthenodrug candidates. Show less
📄 PDF DOI: 10.1039/d4tb02559h
Biometal
Hua W, Li F, Yang P +4 more · 2025 · Journal of Inorganic Biochemistry · Elsevier · added 2026-05-01
The diversification of ligands provides more opportunities to adjust the photophysical performance as well as the bio-function of Ru(II) complexes as novel photosensitizers. Herein, a kind of Ru(II) c Show more
The diversification of ligands provides more opportunities to adjust the photophysical performance as well as the bio-function of Ru(II) complexes as novel photosensitizers. Herein, a kind of Ru(II) complexes carrying resveratrol derivative, amino-Res, as ligand was designed and synthesized. The representative complex (named Ru4) showed potent anticancer activity under the trigger of 520 nm-light. Lipophilicity and cellular accumulation experiments indicated that Ru4 possessed higher LogPO/W value and cell up-take than Ru1-Ru3 and [Ru(bpy)3]2+. Mechanism study revealed that Ru4 could inhibit cancer cell migration, invasion and cancer stemness. The bio-function of Ru4 was mainly inherited from the amino-Res ligand. The in vivo study demonstrated that Ru4 could inhibit the tumor growth without significant system toxicity. Show less
📄 PDF DOI: 10.1016/j.jinorgbio.2025.112873
Biometal
Bao L, Yang S, Zhao W +1 more · 2025 · Amino Acids · Springer · added 2026-04-20
Bao L, Yang S, Zhao W, Zuo Y Show less
Claudin (CLDN) proteins are extensively studied due to their critical role in maintaining tissue barriers and cell polarity. However, significant gaps remain in understanding the functional mechanisms Show more
Claudin (CLDN) proteins are extensively studied due to their critical role in maintaining tissue barriers and cell polarity. However, significant gaps remain in understanding the functional mechanisms of their sequence motifs and the molecular mechanisms of their interactions with other tight junction proteins. This review systematically examines the multifunctional properties of the CLDN protein family from the perspectives of sequence and structure. During evolution, CLDN family members have developed highly conserved structural features, particularly key conserved sites within the first extracellular loop (ECL1) and the C-terminal PDZ-binding domain, which play a central role in regulating the barrier function of tight junctions, ion selectivity, and protein-protein interactions. Furthermore, the distribution pattern of acidic and basic amino acids in ECL1 has been shown to directly determine ion selectivity and paracellular permeability. Meanwhile, the assembly and functional stability of tight junctions are precisely regulated by the C-terminal PDZ-binding domain through its interactions with the ZO protein family. Additionally, the study further elucidates how CLDN proteins modulate critical signaling pathways governing cellular proliferation, survival, and permeability, thereby participating in diverse physiological and pathological processes. These insights have deepened the understanding of the functional diversity of CLDN proteins and provided a new theoretical basis for developing disease diagnostic markers and designing targeted treatment strategies based on CLDN proteins. Show less
📄 PDF DOI: 10.1007/s00726-025-03479-w
amino-acid review
Anushka Verma, Arabinda Muley, Vuppaladadium Shanmuga Sharan Rathnam +4 more · 2025 · European Journal of Inorganic Chemistry · Wiley · added 2026-05-01
📄 PDF DOI: 10.1002/ejic.202500300
Biometal