A computational investigation of allostery in the catabolite activator protein

BioDrugScreen: a computational drug design resource for ranking molecules docked to the human proteome

BioDrugScreen is a resource for ranking molecules docked against a large number of targets in the human proteome. Nearly 1600 molecules from the freely available NCI diversity set were docked onto 1926 cavities identified on 1589 human targets resulting in >3 million receptor-ligand complexes requiring >200,000 cpu-hours on the TeraGrid. The targets in BioDrugScreen originated from Human Cancer Protein Interaction Network, which we have updated, as well as the Human Druggable Proteome, which we have created for the purpose of this effort. This makes the BioDrugScreen resource highly valuable in drug discovery. The receptor-ligand complexes within the database can be ranked using standard and well-established scoring functions like AutoDock, DockScore, ChemScore, X-Score, GoldScore, DFIRE and PMF. In addition, we have scored the complexes with more intensive GBSA and PBSA approaches requiring an additional 120,000 cpu-hours on the TeraGrid. We constructed a simple interface to enable users to view top-ranking molecules and access purchasing and other information for further experimental exploration.

A new member of the Escherichia coli fad regulon: transcriptional regulation of fadM (ybaW)

Recently, Nie and coworkers (L. Nie, Y. Ren, A. Janakiraman, S. Smith, and H. Schulz, Biochemistry 47:9618-9626, 2008) reported a new Escherichia coli thioesterase encoded by the ybaW gene that cleaves the thioester bonds of inhibitory acyl-coenzyme A (CoA) by-products generated during beta-oxidation of certain unsaturated fatty acids. These authors suggested that ybaW expression might be regulated by FadR, the repressor of the fad (fatty acid degradation) regulon. We report mapping of the ybaW promoter and show that ybaW transcription responded to FadR in vivo. Moreover, purified FadR bound to a DNA sequence similar to the canonical FadR binding site located upstream of the ybaW coding sequence and was released from the promoter upon the addition of long-chain acyl-CoA thioesters. We therefore propose the designation fadM in place of ybaW. Although FadR regulation of fadM expression had the pattern typical of fad regulon genes, its modulation by the cyclic AMP (cAMP) receptor protein-cAMP complex (CRP-cAMP) global regulator was the opposite of that normally observed. CRP-cAMP generally acts as an activator of fad gene expression, consistent with the low status of fatty acids as carbon sources. However, glucose growth stimulated fadM expression relative to acetate growth, as did inactivation of CRP-cAMP, indicating that the complex acts as a negative regulator of this gene. The stimulation of fadM expression seen upon deletion of the gene encoding adenylate cyclase (Deltacya) was reversed by supplementation of the growth medium with cAMP. Nie and coworkers also reported that growth on a conjugated linoleic acid isomer yields much higher levels of FadM thioesterase activity than does growth on oleic acid. In contrast, we found that the conjugated linoleic acid isomer was only a weak inducer of fadM expression. Although the gene is not essential for growth, the high basal level of fadM expression under diverse growth conditions suggests that the encoded thioesterase has functions in addition to beta-oxidation.

Quantifying Correlations Between Allosteric Sites in Thermodynamic Ensembles

Allostery describes altered protein function at one site due to a perturbation at another site. One mechanism of allostery involves correlated motions, which can occur even in the absence of substantial conformational change. We present a novel method, "MutInf", to identify statistically significant correlated motions from equilibrium molecular dynamics simulations. Our approach analyzes both backbone and sidechain motions using internal coordinates to account for the gear-like twists that can take place even in the absence of the large conformational changes typical of traditional allosteric proteins. We quantify correlated motions using a mutual information metric, which we extend to incorporate data from multiple short simulations and to filter out correlations that are not statistically significant. Applying our approach to uncover mechanisms of cooperative small molecule binding in human interleukin-2, we identify clusters of correlated residues from 50 ns of molecular dynamics simulations. Interestingly, two of the clusters with the strongest correlations highlight known cooperative small-molecule binding sites and show substantial correlations between these sites. These cooperative binding sites on interleukin-2 are correlated not only through the hydrophobic core of the protein but also through a dynamic polar network of hydrogen bonding and electrostatic interactions. Since this approach identifies correlated conformations in an unbiased, statistically robust manner, it should be a useful tool for finding novel or "orphan" allosteric sites in proteins of biological and therapeutic importance.

Protein allostery, signal transmission and dynamics: a classification scheme of allosteric mechanisms

Allostery has come of age; the number, breadth and functional roles of documented protein allostery cases are rising quickly. Since all dynamic proteins are potentially allosteric and allostery plays crucial roles in all cellular pathways, sorting and classifying allosteric mechanisms in proteins should be extremely useful in understanding and predicting how the signals are regulated and transmitted through the dynamic multi-molecular cellular organizations. Classification organizes the complex information thereby unraveling relationships and patterns in molecular activation and repression. In signaling, current classification schemes consider classes of molecules according to their functions; for example, epinephrine and norepinephrine secreted by the central nervous system are classified as neurotransmitters. Other schemes would account for epinephrine when secreted by the adrenal medulla to be hormone-like. Yet, such classifications account for the global function of the molecule; not for the molecular mechanism of how the signal transmission initiates and how it is transmitted. Here we provide a unified view of allostery and the first classification framework. We expect that a classification scheme would assist in comprehension of allosteric mechanisms, in prediction of signaling on the molecular level, in better comprehension of pathways and regulation of the complex signals, in translating them to the cascading events, and in allosteric drug design. We further provide a range of examples illustrating mechanisms in protein allostery and their classification from the cellular functional standpoint.

Allostery and cooperativity revisited

Although phenomenlogical models that account for cooperativity in allosteric systems date back to the early and mid-60's (e.g., the KNF and MWC models), there is resurgent interest in the topic due to the recent experimental and computational studies that attempted to reveal, at an atomistic level, how allostery actually works. In this review, using systems for which atomistic simulations have been carried out in our groups as examples, we describe the current understanding of allostery, how the mechanisms go beyond the classical MWC/Pauling-KNF descriptions, and point out that the "new view" of allostery, emphasizing "population shifts," is, in fact, an "old view." The presentation offers not only an up-to-date description of allostery from a theoretical/computational perspective, but also helps to resolve several outstanding issues concerning allostery.