CD4-binding obstacles in conformational transitions and allosteric communications of HIV gp120.

As the only exposed viral protein at the membrane surface of HIV, envelope glycoprotein gp120 is responsible for recognizing host cells and mediating virus-cell membrane fusion. Available structures of gp120 indicate that it exhibits two distinct conformational states, called closed and open states. Although experimental data demonstrates that CD4 binding stabilizes open state of gp120, detailed structural dynamics and kinetics of gp120 during this process remain elusive. Here, two open-state gp120 simulation systems, one without any ligands (ligand-free) and the other complexed with CD4 (CD4-bound), were subjected to microsecond-scale molecular dynamics simulations following the conformational transitions and allosteric pathways of gp120 evaluated by using the Markov state model and a network-based method, respectively. Our results provide an atomic-resolution description of gp120 conformational transitions, suggesting that gp120 is intrinsically dynamic from the open state to closed state, whereas CD4 binding blocks these transitions. Consistent with experimental structures, five metastable conformations with different orientations of the V1/V2 region and V3 loop have been extracted. The binding of CD4 significantly enhances allosteric communications from the CD4-binding site to V3 loop and ß20-21 hairpin, resulting in high-affinity interactions with coreceptors and activation of the conformational transitions switcher, respectively. This study will facilitate the structural understanding of the CD4-binding effects on conformational transitions and allosteric pathways of gp120.

Allosteric mechanism of the circadian protein Vivid resolved through Markov state model and machine learning analysis.

The fungal circadian clock photoreceptor Vivid (VVD) contains a photosensitive allosteric light, oxygen, voltage (LOV) domain that undergoes a large N-terminal conformational change. The mechanism by which a blue-light driven covalent bond formation leads to a global conformational change remains unclear, which hinders the further development of VVD as an optogenetic tool. We answered this question through a novel computational platform integrating Markov state models, machine learning methods, and newly developed community analysis algorithms. Applying this new integrative approach, we provided a quantitative evaluation of the contribution from the covalent bond to the protein global conformational change, and proposed an atomistic allosteric mechanism leading to the discovery of the unexpected importance of A'α/Aß and previously overlooked Eα/Fα loops in the conformational change. This approach could be applicable to other allosteric proteins in general to provide interpretable atomistic representations of their otherwise elusive allosteric mechanisms.

A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation.

An index of agonism is described that can be used to quantify agonist receptor selectivity, bias, cell-based agonism, and the effects of receptor mutation on signaling. The parameter is derived from agonist concentration-response curves and comprises the maximal response to the agonist (max) and the EC50 in the form of Δlog(max/EC50). This parameter is derived from equations describing agonists as positive allosteric facilitators of receptor-signaling protein interaction. A similar index is also derived to quantify the potentiating effects of positive allosteric modulators, which can be used to quantify in situ positive allosteric modulator activity in vivo. These indices lend themselves to statistical analysis and are system-independent in that the effects of the system processing of agonist response and differences in assay sensitivity and receptor expression are cancelled. The various applications of the Δlog(max/EC50) scale are described for each pharmacologic application.

Coupling between global dynamics and signal transduction pathways: a mechanism of allostery for chaperonin GroEL.

Despite significant efforts toward understanding the molecular basis of allosteric communication, the mechanisms by which local energetic and conformational changes cooperatively diffuse from ligand-binding sites to distal regions across the 3-dimensional structure of allosteric proteins remain to be established. Recent experimental and theoretical evidence supports the view that allosteric communication is facilitated by the intrinsic ability of the biomolecules to undergo collective changes in structure, triggered by ligand binding. Two groups of studies recently proved to provide insights into such intrinsic, structure-induced effects: elastic network models that permit us to visualize the cooperative changes in conformation that are most readily accessible near native state conditions, and information-theoretic approaches that elucidate the most efficient pathways of signal transmission favored by the overall architecture. Using a combination of these two approaches, we highlight, by way of application to the bacterial chaperonin complex GroEL-GroES, how the most cooperative modes of motion play a role in mediating the propagation of allosteric signals. A functional coupling between the global dynamics sampled under equilibrium conditions and the signal transduction pathways inherently favored by network topology appears to control allosteric effects.

Positive and negative allosteric modulation of metabotropic glutamate receptors: emerging therapeutic potential.

Metabotropic glutamate receptors (mGluRs) modulate neuronal activity in the central and peripheral nervous systems, and since their discovery have attracted considerable attention as putative therapeutic targets for a range of neurological and psychiatric disorders. A number of competitive agonists and antagonists acting at the N-terminal glutamate binding site have been identified, the majority of which are conformationally constrained or substituted amino acid analogues. These ligands have greatly facilitated investigation of the physiological and pathological roles of the receptor family. However, their utility and therapeutic potential has been restricted by relatively poor bioavailability and central nervous system (CNS) penetration, as well as limited chemical tractability and, generally, a lack of selectivity for individual mGluRs. Recently, a number of non-competitive mGluR ligands have been identified which bind within the receptor transmembrane heptahelical domain. These include both positive and negative allosteric modulators. Positive allosteric modulators do not exhibit intrinsic agonism but facilitate agonist-mediated receptor activity. Negative allosteric modulators include both non-competitive antagonists and inverse agonists. Allosteric modulation offers the potential for improved selectivity, particularly for individual receptors within the mGluR family, and enhanced chemical tractability relative to competitive agonists/antagonists. In addition, positive allosteric modulation provides a distinct, and perhaps superior, profile to receptor agonism, offering the potential for facilitation of physiologically appropriate receptor activation with reduced liability for receptor desensitisation and/or tolerance. Thus, the emerging field of positive and negative allosteric modulation of the mGluR family offers considerable promise for the development of novel therapeutics.

Cumulative biological risk and socio-economic differences in mortality: MacArthur studies of successful aging.

Previous research has suggested that socio-economic status (SES) differences in mortality are only partially explained by differences in life-style, psychological and social factors. Seven year mortality data (1988-1995) from the MacArthur Study of Successful Aging, a longitudinal study of adults, aged 70-79, from New Haven, CT; East Boston, MA; and Durham, NC; were used to test the hypothesis that a cumulative measure of biological dysregulation ("allostatic load"), reflecting multiple regulatory systems, would serve as a further mediator of SES differences in mortality. Logistic regression analyses revealed that a cumulative index of biological risk explained 35.4% of the difference in mortality risk between those with higher versus lower SES (as measured by less than high school education versus high school or greater educational attainment). Importantly, the cumulative index provided independent explanatory power, over and above a measure of doctor-diagnosed disease, though the latter also contributed to education-related variation in mortality risks. The summary measure of biological risk also accounted for more variance than individual biological parameters, suggesting the potential value of a multi-systems view of biological pathways through which SES ultimately affects morbidity and mortality.