Antimalarial drugs have thus far been chiefly derived from two sources—natural products and synthetic drug-like compounds. Here we investigate whether antimalarial agents with novel mechanisms of action could be discovered using a diverse collection of synthetic compounds that have three-dimensional features reminiscent of natural products and are underrepresented in typical screening collections. We report the identification of such compounds with both previously reported and undescribed mechanisms of action, including a series of bicyclic azetidines that inhibit a new antimalarial target, phenylalanyl-tRNA synthetase. These molecules are curative in mice at a single, low dose and show activity against all parasite life stages in multiple in vivo efficacy models. Our findings identify bicyclic azetidines with the potential to both cure and prevent transmission of the disease as well as protect at-risk populations with a single oral dose, highlighting the strength of diversity-oriented synthesis in revealing promising therapeutic targets.

Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone.

Limited neuromuscular input results in muscle weakness in neuromuscular disease either because of a reduction in the density of muscle innervation, the rate of neuromuscular junction activation or the efficiency of synaptic transmission1. We developed a small molecule fast skeletal troponin activator, CK-2017357, as a means to increase muscle strength by amplifying the response of muscle when neuromuscular input is diminished secondary to a neuromuscular disease. Binding selectively to the fast skeletal troponin complex, CK-2017357 slows the rate of calcium release from troponin C and sensitizes muscle to calcium. As a consequence, the force-calcium relationship of muscle fibers shifts leftwards as does the force-frequency relationship of a nerve-muscle pair. In vitro and in vivo, CK-2017357 increases the production of force at sub-maximal stimulation rates. Importantly, we show that sensitization of the fast skeletal troponin complex to calcium improves muscle force and grip strength immediately after single doses of CK-2017357 in a model of neuromuscular disease, myasthenia gravis. Troponin activation may provide a new therapeutic approach to improve physical activity in diseases where neuromuscular function is compromised.

The kinetics of W' recovery in single-leg-extensor exercise is comparable to that observed in whole-body exercise, suggesting a conserved mechanism. The extent to which the recovery of the W' can be directly attributed to the recovery of [PCr] is unclear. The relationship of the W' to muscle carnosine content suggests novel future avenues of investigation.

The W'BAL model provided a generally robust prediction of CWR W'. There may exist a physiological optimum formulation of work and recovery intervals such that baseline VO2 can be minimized, leading to an enhancement of subsequent exercise tolerance. These results may have important implications for athletic training and racing.

Fatty acid translocase (FAT/CD36) is a key fatty acid transporter in skeletal muscle. However, the effects on fatty acid transport by another putative fatty acid transporter, plasma membrane-associated fatty acid binding protein (FABPpm), have not been determined in mammalian tissue. We examined the functional effects of overexpressing FABPpm on the rates of 1) palmitate transport across the sarcolemma and 2) palmitate metabolism in skeletal muscle. One muscle (soleus) was transfected with pTracer containing FABPpm cDNA. The contralateral muscle served as control. After injecting the FABPpm cDNA, muscles were electroporated. FABPpm overexpression was directly related to the quantity of DNA administered. Electrotransfection (200 microg/muscle) rapidly induced FABPpm protein overexpression (day 1, +92%, P < 0.05), which was further increased during the next few days (days 3-7; range +142% to +160%, P < 0.05). Sarcolemmal FABPpm was comparably increased (day 7, +173%, P < 0.05). Neither FAT/CD36 expression nor sarcolemmal FAT/CD36 content was altered. FABPpm overexpression increased the rates of palmitate transport (+79%, P < 0.05). Rates of palmitate incorporation into phospholipids were also increased +36%, as were the rates of palmitate oxidation (+20%). Rates of palmitate incorporation into triacylglycerol depots were not altered. These studies demonstrate that in mammalian tissue FABPpm overexpression increased the rates of palmitate transport across the sarcolemma, an effect that is independent of any changes in FAT/CD36. However, since the overexpression of plasmalemmal FABPpm (+173%) exceeded the effects on the rates of palmitate transport and metabolism, it appears that the overexpression of FABPpm alone is not sufficient to induce completely parallel increments in palmitate transport and metabolism. This suggests that other mechanisms are required to realize the full potential offered by FABPpm overexpression.

Recently, an adaptation to the critical-power (CP) model was published, which permits the calculation of the balance of the work capacity available above the CP remaining (W'bal) at any time during intermittent exercise. As the model is now in use in both amateur and elite sport, the purpose of this investigation was to assess the validity of the W'bal model in the field. Data were collected from the bicycle power meters of 8 trained triathletes. W'bal was calculated and compared between files where subjects reported becoming prematurely exhausted during training or competition and files where the athletes successfully completed a difficult assigned task or race without becoming exhausted. Calculated W'bal was significantly different between the 2 conditions (P < .0001). The mean W'bal at exhaustion was 0.5 ± 1.3 kJ (95% CI = 0-0.9 kJ), whereas the minimum W'bal in the nonexhausted condition was 3.6 ± 2.0 kJ (95% CI = 2.1-4.0 kJ). Receiver-operator-characteristic (ROC) curve analysis indicated that the W'bal model is useful for identifying the point at which athletes are in danger of becoming exhausted (area under the ROC curve = .914, SE .05, 95% CI .82-1.0, P < .0001). The W'bal model may therefore represent a useful new development in assessing athlete fatigue state during training and racing.

How transforming growth factor-β (TGF-β) signaling elicits diverse cell responses remains elusive, despite the major molecular components of the pathway being known. We contend that understanding TGF-β biology requires mathematical models to decipher the quantitative nature of TGF-β/Smad signaling and to account for its complexity. Here, we review mathematical models of TGF-β superfamily signaling that predict how robustness is achieved in bone-morphogenetic-protein signaling in the Drosophila embryo, how changes in receptor-trafficking dynamics can be exploited by cancer cells and how the basic mechanisms of TGF-β/Smad signaling conspire to promote Smad accumulation in the nucleus. These studies demonstrate the power of mathematical modeling for understanding TGF-β biology. Towards a systems biology understanding of TGF-β signalingTransforming growth factor-β (TGF-β) is the prototypical molecule of a superfamily of ligands that regulate diverse aspects of cellular homeostasis, including proliferation, differentiation, migration and death. The superfamily includes several ligands such as TGF-β itself, activin and the bone morphogenetic proteins (BMPs). In almost three decades of research, the principal components and the major molecular events that comprise TGF-β signal transduction have been characterized. Owing to the complexity and quantitative nature of TGF-β signaling, a systems biology understanding of TGF-β signaling is now desired. Mathematical modeling is an important tool in this regard, and several models of TGF-β superfamily signaling have recently been published. In this review, we describe the motivation for mathematical modeling studies of TGF-β signaling and discuss how first-generation models have contributed to the understanding of TGF-β biology. The dynamics of the TGF-β/Smad signaling module: the numbers matterA simplified overview of canonical TGF-β signaling is depicted in Figure 1a. Briefly, TGF-β binds two receptor types, the TGF-β type I and type II receptors (TβRI and TβRII, respectively) to form the active signaling complex. The TβRII activates TβRI kinase activity by phosphorylating the TβRI, which then transmits the signal intracellularly by phosphorylating the Smad transcription factors. There are eight Smad isoforms, which are functionally classified as receptor-regulated Smads (R-Smads; isoforms 1, 2, 3, 5 and 8), common-mediator Smad (Co-Smad; isoform 4) and inhibitory Smads (I-Smads; isoforms 6 and 7). In TGF-β signaling proper, the active TβRI phosphorylates Smads 2 and 3, which facilitates complex formation with Smad4. The Smads constitutively shuttle between the © 2008 Elsevier Ltd. All rights reserved.Corresponding author: Liu, X. (Xuedong.Liu@Colorado.edu).. Canonical signaling through the TβRI and the Smads is necessary [3-6], but not sufficient, for most cellular responses to TGF-β. TGF-β signaling is embedded in the cellular signaling network, such that it regulates non-canonical signaling pathways and engages in crosstalk [7][8][9] (Figure 1b). In particular, in...