Block of the hERG channel by bupivacaine: Electrophysiological and modeling insights towards stereochemical optimization

The hERG voltage-gated potassium channel mediates the cardiac I(Kr) current, which is crucial for the duration of the cardiac action potential. Undesired block of the channel by certain drugs may prolong the QT interval and increase the risk of malignant ventricular arrhythmias. Although the molecular determinants of hERG block have been intensively studied, not much is known about its stereoselectivity. Levo-(S)-bupivacaine was the first drug reported to have a higher affinity to block hERG than its enantiomer. This study strives to understand the principles underlying the stereoselectivity of bupivacaine block with the help of mutagenesis analyses and molecular modeling simulations. Electrophysiological measurements of mutated hERG channels allowed for the identification of residues involved in bupivacaine binding and stereoselectivity. Docking and molecular mechanics simulations for both enantiomers of bupivacaine and terfenadine (a non-stereoselective blocker) were performed inside an open-state model of the hERG channel. The predicted binding modes enabled a clear depiction of ligand-protein interactions. Estimated binding affinities for both enantiomers were consistent with electrophysiological measurements. A similar computational procedure was applied to bupivacaine enantiomers towards two mutated hERG channels (Tyr652Ala and Phe656Ala). This study confirmed, at the molecular level, that bupivacaine stereoselectively binds the hERG channel. These results help to lay the foundation for structural guidelines to optimize the cardiotoxic profile of drug candidates in silico.

Lead discovery, chemistry optimization, and biological evaluation studies of novel biamide derivatives as CB2 receptor inverse agonists and osteoclast inhibitors

N,N'-((4-(Dimethylamino)phenyl)methylene)bis(2-phenylacetamide) was discovered by using 3D pharmacophore database searches and was biologically confirmed as a new class of CB(2) inverse agonists. Subsequently, 52 derivatives were designed and synthesized through lead chemistry optimization by modifying the rings A-C and the core structure in further SAR studies. Five compounds were developed and also confirmed as CB(2) inverse agonists with the highest CB(2) binding affinity (CB(2)K(i) of 22-85 nM, EC(50) of 4-28 nM) and best selectivity (CB(1)/CB(2) of 235- to 909-fold). Furthermore, osteoclastogenesis bioassay indicated that PAM compounds showed great inhibition of osteoclast formation. Especially, compound 26 showed 72% inhibition activity even at the low concentration of 0.1 μM. The cytotoxicity assay suggested that the inhibition of PAM compounds on osteoclastogenesis did not result from its cytotoxicity. Therefore, these PAM derivatives could be used as potential leads for the development of a new type of antiosteoporosis agent.

Sedation and weaning from mechanical ventilation: effects of process optimization outside a clinical trial

PURPOSE: We studied the effects of reorganization and changes in the care process, including use of protocols for sedation and weaning from mechanical ventilation, on the use of sedative and analgesic drugs and on length of respiratory support and stay in the intensive care unit (ICU). MATERIALS AND METHODS: Three cohorts of 100 mechanically ventilated ICU patients, admitted in 1999 (baseline), 2000 (implementation I, after a change in ICU organization and in diagnostic and therapeutic approaches), and 2001 (implementation II, after introduction of protocols for weaning from mechanical ventilation and sedation), were studied retrospectively. RESULTS: Simplified Acute Physiology Score II (SAPS II), diagnostic groups, and number of organ failures were similar in all groups. Data are reported as median (interquartile range).Time on mechanical ventilation decreased from 18 (7-41) (baseline) to 12 (7-27) hours (implementation II) (P = .046), an effect which was entirely attributable to noninvasive ventilation, and length of ICU stay decreased in survivors from 37 (21-71) to 25 (19-63) hours (P = .049). The amount of morphine (P = .001) and midazolam (P = .050) decreased, whereas the amount of propofol (P = .052) and fentanyl increased (P = .001). Total Therapeutic Intervention Scoring System-28 (TISS-28) per patient decreased from 137 (99-272) to 113 (87-256) points (P = .009). Intensive care unit mortality was 19% (baseline), 8% (implementation I), and 7% (implementation II) (P = .020). CONCLUSIONS: Changes in organizational and care processes were associated with an altered pattern of sedative and analgesic drug prescription, a decrease in length of (noninvasive) respiratory support and length of stay in survivors, and decreases in resource use as measured by TISS-28 and mortality.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Preparation and optimization of calcium fluoride particles for dental applications.

Fluorides are used in dental care due to their beneficial effect in tooth enamel de-/remineralization cycles. To achieve a desired constant supply of soluble fluorides in the oral cavity, different approaches have been followed. Here we present results on the preparation of CaF2 particles and their characterization with respect to a potential application as enamel associated fluoride releasing reservoirs. CaF2 particles were synthesized by precipitation from soluble NaF and CaCl2 salt solutions of defined concentrations and their morphology analyzed by scanning electron microscopy. CaF2 particles with defined sizes and shapes could be synthesized by adjusting the concentrations of the precursor salt solutions. Such particles interacted with enamel surfaces when applied at fluoride concentrations correlating to typical dental care products. Fluoride release from the synthesized CaF2 particles was observed to be largely influenced by the concentration of phosphate in the solution. Physiological solutions with phosphate concentration similar to saliva (3.5 mM) reduced the fluoride release from pure CaF2 particles by a factor of 10-20 × as compared to phosphate free buffer solutions. Fluoride release was even lower in human saliva. The fluoride release could be increased by the addition of phosphate in substoichiometric amounts during CaF2 particle synthesis. The presented results demonstrate that the morphology and fluoride release characteristics of CaF2 particles can be tuned and provide evidence of the suitability of synthetic CaF2 particles as enamel associated fluoride reservoirs.

Regulating a Benzodifuran Single Molecule Redox Switch via Electrochemical Gating and Optimization of Molecule/Electrode Coupling

We report a novel strategy for the regulation of charge transport through single molecule junctions via the combination of external stimuli of electrode potential, internal modulation of molecular structures, and optimization of anchoring groups. We have designed redox-active benzodifuran (BDF) compounds as functional electronic units to fabricate metal–molecule–metal (m–M–m) junction devices by scanning tunneling microscopy (STM) and mechanically controllable break junctions (MCBJ). The conductance of thiol-terminated BDF can be tuned by changing the electrode potentials showing clearly an off/on/off single molecule redox switching effect. To optimize the response, a BDF molecule tailored with carbodithioate (−CS2–) anchoring groups was synthesized. Our studies show that replacement of thiol by carbodithioate not only enhances the junction conductance but also substantially improves the switching effect by enhancing the on/off ratio from 2.5 to 8.

Computer assisted planning and navigation of periacetabular osteotomy with range of motion optimization

Femoroacetabular impingement (FAI) before or after Periacetabular Osteotomy (PAO) is surprisingly frequent and surgeons need to be aware of the risk preoperatively and be able to avoid it intraoperatively. In this paper we present a novel computer assisted planning and navigation system for PAO with impingement analysis and range of motion (ROM) optimization. Our system starts with a fully automatic detection of the acetabular rim, which allows for quantifying the acetabular morphology with parameters such as acetabular version, inclination and femoral head coverage ratio for a computer assisted diagnosis and planning. The planned situation was optimized with impingement simulation by balancing acetabuar coverage with ROM. Intra-operatively navigation was conducted until the optimized planning situation was achieved. Our experimental results demonstrated: 1) The fully automated acetabular rim detection was validated with accuracy 1.1 ± 0.7mm; 2) The optimized PAO planning improved ROM significantly compared to that without ROM optimization; 3) By comparing the pre-operatively planned situation and the intra-operatively achieved situation, sub-degree accuracy was achieved for all directions.

Global Optimization with Sparse and Local Gaussian Process Models

We present a novel surrogate model-based global optimization framework allowing a large number of function evaluations. The method, called SpLEGO, is based on a multi-scale expected improvement (EI) framework relying on both sparse and local Gaussian process (GP) models. First, a bi-objective approach relying on a global sparse GP model is used to determine potential next sampling regions. Local GP models are then constructed within each selected region. The method subsequently employs the standard expected improvement criterion to deal with the exploration-exploitation trade-off within selected local models, leading to a decision on where to perform the next function evaluation(s). The potential of our approach is demonstrated using the so-called Sparse Pseudo-input GP as a global model. The algorithm is tested on four benchmark problems, whose number of starting points ranges from 102 to 104. Our results show that SpLEGO is effective and capable of solving problems with large number of starting points, and it even provides significant advantages when compared with state-of-the-art EI algorithms.