External validation of the GRACE risk score in patients with myocardial infarction in Hungary.

Background: Literature confirms that the Global Registry of Acute Coronary Events (GRACE) risk score provides a better risk evaluation than clinical judgment in patients with acute myocardial infarction. We aimed to externally validate the GRACE risk score in unselected patients with myocardial infarction in Hungary.

Methods: Data from the comprehensive Hungarian Myocardial Infarction Registry (HUMIR), a national registry that collects data on consecutive acute myocardial infarction (AMI) patients, were used.

[Management of patients treated for myocardial infarction in different regions of Hungary and patient survival for 10 years].

Unlabelled: Összefoglaló. Előzmény: A szívinfarktus miatt kezelt betegek ellátásának regionális adataira és a betegek hosszú távú kórlefolyására vonatkozó hazai kutatás eddig nem történt. Célkitűzés: A vizsgálat célja a Magyar Infarktus Regiszter pilotidőszakában rögzített betegeknél az ellátás és a 10 éves túlélés elemzése a magyarországi nagyrégiókban.

[Quality assurance of national internet-based patient register data: Experiences during the operation of the Hungarian Myocardial Infarction Registry, 2010–2020].

Unlabelled: Összefoglaló. Bevezetés: A Nemzeti Szívinfarktus Regiszterben 111 788 beteg 122 351 infarktusos eseményéhez kapcsolódó 145 292 kezelés adatai szerepelnek. Módszer: A rögzített adatokat az üzemeltetők folyamatosan kontrollálják, bemutatják azokat a minőségbiztosítási módszereket, amelyekkel az adatbázis teljességét és megfelelőségét biztosítják.

Identification of PPARγ ligands with One-dimensional Drug Profile Matching.

Introduction: Computational molecular database screening helps to decrease the time and resources needed for drug development. Reintroduction of generic drugs by second medical use patents also contributes to cheaper and faster drug development processes. We screened, in silico, the Food and Drug Administration-approved generic drug database by means of the One-dimensional Drug Profile Matching (oDPM) method in order to find potential peroxisome proliferator-activated receptor gamma (PPARγ) agonists.

Virtual affinity fingerprints for target fishing: a new application of Drug Profile Matching.

We recently introduced Drug Profile Matching (DPM), a novel virtual affinity fingerprinting bioactivity prediction method. DPM is based on the docking profiles of ca. 1200 FDA-approved small-molecule drugs against a set of nontarget proteins and creates bioactivity predictions based on this pattern.

Contribution of 2D and 3D structural features of drug molecules in the prediction of Drug Profile Matching.

Drug Profile Matching (DPM), a novel virtual affinity fingerprinting method capable of predicting the medical effect profiles of small molecules, was introduced by our group recently. The method exploits the information content of interaction patterns generated by flexible docking to a series of rigidly kept nontarget protein active sites. We presented the ability of DPM to classify molecules excellently, and the question arose, what the contribution of 2D and 3D structural features of the small molecules is to the intriguingly high prediction power of DPM.

A novel actin binding site of myosin required for effective muscle contraction.

F-actin serves as a track for myosin's motor functions and activates its ATPase activity by several orders of magnitude, enabling actomyosin to produce effective force against load. Although actin activation is a ubiquitous property of all myosin isoforms, the molecular mechanism and physiological role of this activation are unclear. Here we describe a conserved actin-binding region of myosin named the 'activation loop', which interacts with the N-terminal segment of actin.

Drug effect prediction by polypharmacology-based interaction profiling.

Most drugs exert their effects via multitarget interactions, as hypothesized by polypharmacology. While these multitarget interactions are responsible for the clinical effect profiles of drugs, current methods have failed to uncover the complex relationships between them. Here, we introduce an approach which is able to relate complex drug-protein interaction profiles with effect profiles.

Predicting P-glycoprotein-mediated drug transport based on support vector machine and three-dimensional crystal structure of P-glycoprotein.

Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates.

Evaluation of drug-human serum albumin binding interactions with support vector machine aided online automated docking.

Human serum albumin (HSA), the most abundant plasma protein is well known for its extraordinary binding capacity for both endogenous and exogenous substances, including a wide range of drugs. Interaction with the two principal binding sites of HSA in subdomain IIA (site 1) and in subdomain IIIA (site 2) controls the free, active concentration of a drug, provides a reservoir for a long duration of action and ultimately affects the ADME (absorption, distribution, metabolism, and excretion) profile. Due to the continuous demand to investigate HSA binding properties of novel drugs, drug candidates and drug-like compounds, a support vector machine (SVM) model was developed that efficiently predicts albumin binding.

Relating the shape of protein binding sites to binding affinity profiles: is there an association?

Background: Various pattern-based methods exist that use in vitro or in silico affinity profiles for classification and functional examination of proteins. Nevertheless, the connection between the protein affinity profiles and the structural characteristics of the binding sites is still unclear. Our aim was to investigate the association between virtual drug screening results (calculated binding free energy values) and the geometry of protein binding sites.

Cyclodextrin KnowledgeBase a web-based service managing CD-ligand complexation data.

Cyclodextrins are cyclic oligosaccharides that are able to form water-soluble inclusion complexes with small molecules. Because of their complexing ability, they are widely applied in food, pharmaceutical and chemical industries. In this paper we describe the development of a free web-service, Cyclodextrin KnowledgeBase: ( http://www.

Breaking the hierarchy--a new cluster selection mechanism for hierarchical clustering methods.

Background: Hierarchical clustering methods like Ward's method have been used since decades to understand biological and chemical data sets. In order to get a partition of the data set, it is necessary to choose an optimal level of the hierarchy by a so-called level selection algorithm. In 2005, a new kind of hierarchical clustering method was introduced by Palla et al.