Use of agricultural lands by San Joaquin kit foxes

Although the current range of the endangered San Joaquin kit fox ( Vulpes macrotis mutica ) borders large areas of farmland, the ecology of this species rarely has been studied within an agricultural setting. In central California, we examined habitat use, prey availability, and diet of radio-collared kit foxes inhabiting an aqueduct right-of-way (ROW) bordered by farmland. During both years of study (1998–1999), nocturnal locations of foxes occurred more often than expected (based on habitat availability) in the ROW and less often than expected within annual crops. Orchards were used disproportionately more than their availability during 1998 and were used in proportion to availability during 1999. Kit foxes traveled up to 1.1 km into annual crops and up to 1.5 km into orchards. Among diurnal locations (den sites) of foxes, 98% were within the ROW. Live-trapping revealed higher densities and greater diversity of rodents along the ROW than within farmland. Remains of murid rodents were found in 79% of kit fox scats. Our findings indicated that kit foxes ranged into orchards and annual croplands at night, but almost never occupied these areas during the day. The lack of den sites and low prey availability within farmland probably limited the ability of kit foxes to exploit and occupy these areas. Providing artificial den sites within croplands (especially within orchards) and along canals may increase use of farmland by kit foxes and facilitate their movement between isolated patches of natural lands.     

Movements and home ranges of San Joaquin kit foxes ( Vulpes macrotis mutica ) relative to oil-field development

We examined the effect of oil-field development on movements and patterns of spatial use of San Joaquin kit foxes ( Vulpes macrotis mutica ) on the Naval Petroleum Reserves in California (NPRC) in the San Joaquin Valley. To do this, we compared movements and home ranges of kit foxes from June 1984 to September 1985 in areas developed for petroleum production (30% of native habitat lost to production facilities) and areas with little development (3%). Distances traveled nightly by kit foxes did not differ between levels of petroleum development or between sexes ( P > 0.2). Mean length of nightly movements during breeding (14.6 km) was longer than during pup-rearing (10.7 km) and pup-dispersal (9.4 km) periods ( P = 0.01). Mean size of home ranges was 4.6 ± 0.4 ( s￣x ) km 2 ( n = 21) and did not differ between levels of petroleum development and sexes ( P > 0.2). Overlap of home ranges of foxes from the same social group (78 ± 4.3%) was greater than that of same-sex foxes (35 ± 7.8%) and males and females of different social groups (32 ± 8.0%, P P > 0.4). Despite extensive overlap of home ranges, kit foxes on NPRC maintained relatively exclusive core areas, particularly adjacent foxes of the same sex. Future studies should examine which levels of habitat conversion impact spatial use of kit foxes.     

Structure and dynamics of the M3 muscarinic acetylcholine receptor

Acetylcholine, the first neurotransmitter to be identified, exerts many of its physiological actions via activation of a family of G-protein-coupled receptors (GPCRs) known as muscarinic acetylcholine receptors (mAChRs). Although the five mAChR subtypes (M1-M5) share a high degree of sequence homology, they show pronounced differences in G-protein coupling preference and the physiological responses they mediate. Unfortunately, despite decades of effort, no therapeutic agents endowed with clear mAChR subtype selectivity have been developed to exploit these differences. We describe here the structure of the G(q/11)-coupled M3 mAChR ('M3 receptor', from rat) bound to the bronchodilator drug tiotropium and identify the binding mode for this clinically important drug. This structure, together with that of the G(i/o)-coupled M2 receptor, offers possibilities for the design of mAChR subtype-selective ligands. Importantly, the M3 receptor structure allows a structural comparison between two members of a mammalian GPCR subfamily displaying different G-protein coupling selectivities. Furthermore, molecular dynamics simulations suggest that tiotropium binds transiently to an allosteric site en route to the binding pocket of both receptors. These simulations offer a structural view of an allosteric binding mode for an orthosteric GPCR ligand and provide additional opportunities for the design of ligands with different affinities or binding kinetics for different mAChR subtypes. Our findings not only offer insights into the structure and function of one of the most important GPCR families, but may also facilitate the design of improved therapeutics targeting these critical receptors.     

Large-scale prediction and testing of drug activity on side-effect targets

Discovering the unintended 'off-targets' that predict adverse drug reactions is daunting by empirical methods alone. Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects. Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended 'side-effect' targets. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method or by new experimental assays. Affinities for these new off-targets ranged from 1 nM to 30 μM. To explore relevance, we developed an association metric to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a drug-target-adverse drug reaction network. Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1. The clinical relevance of this inhibition was borne out in whole human blood platelet aggregation assays. This approach may have wide application to de-risking toxicological liabilities in drug discovery.     

Structure of the δ-opioid receptor bound to naltrindole

The opioid receptor family comprises three members, the μ-, δ- and κ-opioid receptors, which respond to classical opioid alkaloids such as morphine and heroin as well as to endogenous peptide ligands like endorphins. They belong to the G-protein-coupled receptor (GPCR) superfamily, and are excellent therapeutic targets for pain control. The δ-opioid receptor (δ-OR) has a role in analgesia, as well as in other neurological functions that remain poorly understood. The structures of the μ-OR and κ-OR have recently been solved. Here we report the crystal structure of the mouse δ-OR, bound to the subtype-selective antagonist naltrindole. Together with the structures of the μ-OR and κ-OR, the δ-OR structure provides insights into conserved elements of opioid ligand recognition while also revealing structural features associated with ligand-subtype selectivity. The binding pocket of opioid receptors can be divided into two distinct regions. Whereas the lower part of this pocket is highly conserved among opioid receptors, the upper part contains divergent residues that confer subtype selectivity. This provides a structural explanation and validation for the 'message-address' model of opioid receptor pharmacology, in which distinct 'message' (efficacy) and 'address' (selectivity) determinants are contained within a single ligand. Comparison of the address region of the δ-OR with other GPCRs reveals that this structural organization may be a more general phenomenon, extending to other GPCR families as well.     

Life choices simulation: Model and methodology

The life choices stimulation (LCS) is a computer-managed simulation which permits participants to explore the impact of decision making in an extended time frame. It is designed primarily for individuals who wish to explore a variety of possible futures and to develop an appreciation for the complexity of relationships and career planning. A general systems approach was used to design a model of complexity within the simulation. “Situation” scenarios were developed to represent common life experiences to which the participant must respond (such as single parenting, divorce, career choice, and old age). The realism of the simulation is provided by a supporting data base which includes such data points as average income of male and female workers, types of employment and their salary levels, and time unit allowances for life-style choices. These data are kept current and are used to generate the results of various choices. This paper describes the process of simulation development, outlines the LCS, and suggests research uses.