Local positioning with sensor-enabled passive multistandard RFID transponders

RFID is used today in many fields of every day life like access control, anti-theft protection or logistics. Within this article a short overview of the basic RFID principles and the EPC protocol flow is given at first. Afterwards new design approaches for RFID systems within the scope of the research project RFID-S are presented

Carbonic anhydrase activity of dinuclear CuII complexes with patellamide model ligands

The dicopper(ii) complexes of six pseudo-octapeptides, synthetic analogues of ascidiacyclamide and the patellamides, found in ascidians of the Pacific and Indian Oceans, are shown to be efficient carbonic anhydrase model complexes with k up to 7.3 × 10 s (uncatalyzed: 3.7 × 10 s; enzyme-catalyzed: 2 × 10 -1.4 × 10 s) and a turnover number (TON) of at least 1700, limited only by the experimental conditions used. So far, no copper-based natural carbonic anhydrases are known, no faster model systems have been described and the biological role of the patellamide macrocycles is so far unknown. The observed CO hydration rates depend on the configuration of the isopropyl side chains of the pseudo-octapeptide scaffold, and the naturally observed R*,S*, R*,S* geometry is shown to lead to more efficient catalysts than the S*,S*,S*,S* isomers. The catalytic efficiency also depends on the heterocyclic donor groups of the pseudo-octapeptides. Interestingly, the dicopper(ii) complex of the ligand with four imidazole groups is a more efficient catalyst than that of the close analogue of ascidiacyclamide with two thiazole and two oxazoline rings. The experimental observations indicate that the nucleophilic attack of a Cu- coordinated hydroxide at the CO carbon center is rate determining, i.e. formation of the catalyst-CO adduct and release of carbonate/bicarbonate are relatively fast processes

One Scaffold, Three Binding Modes: Novel and Selective Pteridine Reductase 1 Inhibitors Derived from Fragment Hits Discovered by Virtual Screening†

The enzyme pteridine reductase 1 (PTR1) is a potential target for new compounds to treat human African trypanosomiasis. A virtual screening campaign for fragments inhibiting PTR1 was carried out. Two novel chemical series were identified containing aminobenzothiazole and aminobenzimidazole scaffolds, respectively. One of the hits (2-amino-6-chloro-benzimidazole) was subjected to crystal structure analysis and a high resolution crystal structure in complex with PTR1 was obtained, confirming the predicted binding mode. However, the crystal structures of two analogues (2-amino-benzimidazole and 1-(3,4-dichloro-benzyl)-2-amino-benzimidazole) in complex with PTR1 revealed two alternative binding modes. In these complexes, previously unobserved protein movements and water-mediated protein-ligand contacts occurred, which prohibited a correct prediction of the binding modes. On the basis of the alternative bindingmode of 1-(3,4-dichloro-benzyl)-2-amino-benzimidazole, derivatives were designed and selective PTR1 inhibitors with low nanomolar potency and favorable physicochemical properties were obtained

Predictive Power of Molecular Dynamics Receptor Structures in Virtual Screening

Molecular dynamics (MD) simulation is a well-established method for understanding protein dynamics. Conformations from unrestrained MD simulations have yet to be assessed for blind virtual screening (VS) by docking. This study presents a critical analysis of the predictive power of MD snapshots to this regard, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations. Results from such VS predictions are discussed with respect to experimentally determined structures. In all cases, MD simulations provide snapshots that improve VS predictive power over known crystal structures, possibly due to sampling more relevant receptor conformations. Additionally, MD can move conformations previously not amenable to docking into the predictive range

Lead optimization of a pyrazole sulfonamide series of trypanosoma brucei N -myristoyltransferase inhibitors:Identification and evaluation of CNS penetrant compounds as potential treatments for stage 2 human african trypanosomiasis

[Image: see text] Trypanosoma bruceiN-myristoyltransferase (TbNMT) is an attractive therapeutic target for the treatment of human African trypanosomiasis (HAT). From previous studies, we identified pyrazole sulfonamide, DDD85646 (1), a potent inhibitor of TbNMT. Although this compound represents an excellent lead, poor central nervous system (CNS) exposure restricts its use to the hemolymphatic form (stage 1) of the disease. With a clear clinical need for new drug treatments for HAT that address both the hemolymphatic and CNS stages of the disease, a chemistry campaign was initiated to address the shortfalls of this series. This paper describes modifications to the pyrazole sulfonamides which markedly improved blood–brain barrier permeability, achieved by reducing polar surface area and capping the sulfonamide. Moreover, replacing the core aromatic with a flexible linker significantly improved selectivity. This led to the discovery of DDD100097 (40) which demonstrated partial efficacy in a stage 2 (CNS) mouse model of HAT

Shaping a screening file for maximal lead discovery efficiency and effectiveness: elimination of molecular redundancy

High Throughput Screening (HTS) is a successful strategy for finding hits and leads that have the opportunity to be converted into drugs. In this paper we highlight novel computational methods used to select compounds to build a new screening file at Pfizer and the analytical methods we used to assess their quality. We also introduce the novel concept of molecular redundancy to help decide on the density of compounds required in any region of chemical space in order to be confident of running successful HTS campaigns

A statistical framework to evaluate virtual screening

<p>Abstract</p> <p>Background</p> <p>Receiver operating characteristic (ROC) curve is widely used to evaluate virtual screening (VS) studies. However, the method fails to address the "early recognition" problem specific to VS. Although many other metrics, such as RIE, BEDROC, and pROC that emphasize "early recognition" have been proposed, there are no rigorous statistical guidelines for determining the thresholds and performing significance tests. Also no comparisons have been made between these metrics under a statistical framework to better understand their performances.</p> <p>Results</p> <p>We have proposed a statistical framework to evaluate VS studies by which the threshold to determine whether a ranking method is better than random ranking can be derived by bootstrap simulations and 2 ranking methods can be compared by permutation test. We found that different metrics emphasize "early recognition" differently. BEDROC and RIE are 2 statistically equivalent metrics. Our newly proposed metric SLR is superior to pROC. Through extensive simulations, we observed a "seesaw effect" – overemphasizing early recognition reduces the statistical power of a metric to detect true early recognitions.</p> <p>Conclusion</p> <p>The statistical framework developed and tested by us is applicable to any other metric as well, even if their exact distribution is unknown. Under this framework, a threshold can be easily selected according to a pre-specified type I error rate and statistical comparisons between 2 ranking methods becomes possible. The theoretical null distribution of SLR metric is available so that the threshold of SLR can be exactly determined without resorting to bootstrap simulations, which makes it easy to use in practical virtual screening studies.</p