Improved Small Molecule Identification through Learning Combinations of Kernel Regression Models

In small molecule identification from tandem mass (MS/MS) spectra, input–output kernel regression (IOKR) currently provides the state-of-the-art combination of fast training and prediction and high identification rates. The IOKR approach can be simply understood as predicting a fingerprint vector from the MS/MS spectrum of the unknown molecule, and solving a pre-image problem to find the molecule with the most similar fingerprint. In this paper, we bring forward the following improvements to the IOKR framework: firstly, we formulate the IOKRreverse model that can be understood as mapping molecular structures into the MS/MS feature space and solving a pre-image problem to find the molecule whose predicted spectrum is the closest to the input MS/MS spectrum. Secondly, we introduce an approach to combine several IOKR and IOKRreverse models computed from different input and output kernels, called IOKRfusion. The method is based on minimizing structured Hinge loss of the combined model using a mini-batch stochastic subgradient optimization. Our experiments show a consistent improvement of top-k accuracy both in positive and negative ionization mode dat

Calcium-dependent phospholipid scramblase activity of TMEM16 protein family members.

Asymmetrical distribution of phospholipids between the inner and outer plasma membrane leaflets is disrupted in various biological processes. We recently identified TMEM16F, an eight-transmembrane protein, as a Ca2+-dependent phospholipid scramblase that exposes phosphatidylserine (PS) to the cell surface. In this study, we established a mouse lymphocyte cell line with a floxed allele in the TMEM16F gene. When TMEM16F was deleted, these cells failed to expose PS in response to Ca2+ ionophore, but PS exposure was elicited by Fas ligand treatment. We expressed other TMEM16 proteins in the TMEM16F−/− cells and found that not only TMEM16F, but also 16C, 16D, 16G, and 16J work as lipid scramblases with different preference to lipid substrates. On the other hand, a patch clamp analysis in 293T cells indicated that TMEM16A and 16B, but not other family members, acted as Ca2+-dependent Cl− channels. These results indicated that among 10 TMEM16 family members, 7 members could be divided into two subfamilies, Ca2+-dependent Cl− channels (16A and 16B) and Ca2+-dependent lipid scramblases (16C, 16D, 16F, 16G, and 16J)