The discovery of drug-like molecules that bind pockets in proteins that are not present in crystallographic structures yet exert allosteric control over activity has generated great interest in designing pharmaceuticals that exploit allosteric effects. However, there have only been a small number of successes, so the therapeutic potential of these pockets-called hidden allosteric sites-remains unclear. One challenge for assessing their utility is that rational drug design approaches require foreknowledge of the target site, but most hidden allosteric sites are only discovered when a small molecule is found to stabilize them. We present a means of decoupling the identification of hidden allosteric sites from the discovery of drugs that bind them by drawing on new developments in Markov state modeling that provide unprecedented access to microsecond-to millisecond-timescale fluctuations of a protein's structure. Visualizing these fluctuations allows us to identify potential hidden allosteric sites, which we then test via thiol labeling experiments. Application of these methods reveals multiple hidden allosteric sites in an important antibiotic target-TEM-1 β-lactamase. This result supports the hypothesis that there are many as yet undiscovered hidden allosteric sites and suggests our methodology can identify such sites, providing a starting point for future drug design efforts. More generally, our results demonstrate the power of using Markov state models to guide experiments.thiol labeling | antibiotic resistance | molecular dynamics

Recent findings associate the control of stereochemistry in lipoxygenase (LOX) catalysis with a conserved active site alanine for S configuration hydroperoxide products, or a corresponding glycine for R stereoconfiguration. To further elucidate the mechanistic basis for this stereocontrol we compared the stereoselectivity of the initiating hydrogen abstraction in soybean LOX-1 and an Ala542Gly mutant that converts linoleic acid to both 13S and 9R configuration hydroperoxide products. Using 11R-3 Hand 11S-3 H-labeled linoleic acid substrates to examine the initial hydrogen abstraction, we found that all the primary hydroperoxide products were formed with an identical and highly stereoselective pro-S hydrogen abstraction from C-11 of the substrate (97-99% pro-S-selective). This strongly suggests that 9R and 13S oxygenations occur with the same binding orientation of substrate in the active site, and as the equivalent 9R and 13S products were formed from a bulky ester derivative (1-palmitoyl-2-linoleoylphosphatidylcholine), one can infer that the orientation is tail-first. Both the EPR spectrum and the reaction kinetics were altered by the R product-inducing Ala-Gly mutation, indicating a substantial influence of this Ala-Gly substitution extending to the environment of the active site iron. To examine also the reversed orientation of substrate binding, we studied oxygenation of the 15S-hydroperoxide of arachidonic acid by the Ala542Gly mutant soybean LOX-1. In addition to the usual 5S,15S-and 8S,15S-dihydroperoxides, a new product was formed and identified by high-performance liquid chromatography, UV, gas chromatography-mass spectrometry, and NMR as 9R,15S-dihydroperoxyeicosa-5Z,7E,11Z,13E-tetraenoic acid, the R configuration "partner" of the normal 5S,15S product. This provides evidence that both tail-first and carboxylate end-first binding of substrate can be associated with S or R partnerships in product formation in the same active site.

No abstract

High-frequency EMR of metalloprotein samples offers considerable potential for providing improvements in characterization of metal centers. For those metal ions that are studied at low temperature, line widths may be frequency-dependent, depending on the terms that limit the widths. Here we examine apparent EMR line widths and line shapes in some representative metalloprotein samples at two frequencies: -9.2 GHz (X-band) and -94 GHz (W-band). Samples of the same size were measured at both frequencies. The samples include cupric ion in lactoferrin, high-spin ferric ion in diferric transferrin and high-spin ferric heme in catalase. For the approximately tenfold increase in EMR frequency, the observed line widths increased tenfold or less for the samples chosen. Distributions in one or more spin Hamiltonian parameters can account for these line width dependences on EMR frequency in the lactoferrin and transferrin samples, while molecular heterogeneity is a likely contributor to the catalase frequency-dependent line width. These measurements over frequencies differing by a factor of ten also contributed new insight for simulation of the EMR spectra of diferric transferrin.