A new CPMG-based multiple quantum relaxation dispersion experiment is presented for measuring millisecond dynamic processes at side-chain methyl positions in high molecular weight proteins. The experiment benefits from a methyl-TROSY effect in which cancellation of intramethyl dipole fields occurs, leading to methyl (13)C-(1)H correlation spectra of high sensitivity and resolution (Tugarinov, V.; Hwang, P. M.; Ollerenshaw, J. E.; Kay, L. E. J. Am. Chem. Soc. 2003, 125, 10420-10428). The utility of the methodology is illustrated with an application to a highly deuterated, methyl-protonated sample of malate synthase G, an 82 kDa enzyme consisting of a single polypeptide chain. A comparison of the sensitivity obtained using the present approach relative to existing HSQC-type (13)C single quantum dispersion experiments shows a gain of a factor of 5.4 on average, significantly increasing the range of applications for this methodology.

We present Scaden, a deep neural network for cell deconvolution that uses gene expression information to infer the cellular composition of tissues. Scaden is trained on single-cell RNA sequencing (RNA-seq) data to engineer discriminative features that confer robustness to bias and noise, making complex data preprocessing and feature selection unnecessary. We demonstrate that Scaden outperforms existing deconvolution algorithms in both precision and robustness. A single trained network reliably deconvolves bulk RNA-seq and microarray, human and mouse tissue expression data and leverages the combined information of multiple datasets. Because of this stability and flexibility, we surmise that deep learning will become an algorithmic mainstay for cell deconvolution of various data types. Scaden’s software package and web application are easy to use on new as well as diverse existing expression datasets available in public resources, deepening the molecular and cellular understanding of developmental and disease processes.

Allosteric regulation is an effective mechanism of control in biological processes. In allosteric proteins a signal originating at one site in the molecule is communicated through the protein structure to trigger a specific response at a remote site. Using NMR relaxation dispersion techniques we directly observe the dynamic process through which the KIX domain of CREB binding protein communicates allosteric information between binding sites. KIX mediates cooperativity between pairs of transcription factors through binding to two distinct interaction surfaces in an allosteric manner. We show that binding the activation domain of the mixed lineage leukemia (MLL) transcription factor to KIX induces a redistribution of the relative populations of KIX conformations toward a high-energy state in which the allosterically activated second binding site is already preformed, consistent with the Monod-Wyman-Changeux (WMC) model of allostery. The structural rearrangement process that links the two conformers and by which allosteric information is communicated occurs with a time constant of 3 ms at 27 degrees C. Our dynamic NMR data reveal that an evolutionarily conserved network of hydrophobic amino acids constitutes the pathway through which information is transmitted.