Active Bayesian Optimization: Minimizing Minimizer Entropy

The ultimate goal of optimization is to find the minimizer of a target function.However, typical criteria for active optimization often ignore the uncertainty about the minimizer. We propose a novel criterion for global optimization and an associated sequential active learning strategy using Gaussian processes.Our criterion is the reduction of uncertainty in the posterior distribution of the function minimizer. It can also flexibly incorporate multiple global minimizers. We implement a tractable approximation of the criterion and demonstrate that it obtains the global minimizer accurately compared to conventional Bayesian optimization criteria

Binding of dipyridamole to phospholipid vesicles: a fluorescence study

AbstractBinding and localization of the vasodilator and antitumor drug coactivator dipyridamole (DIP) and one of its derivatives, RA25, to phospholipid vesicles of DMPC (dimyristoylphosphatidylcholine) and DPPC (dipalmitoylphosphatidylcholine) was studied using fluorescence spectroscopy as well as quenching of fluorescence. The analysis of fluorescence data indicates that neutral dipyridamole binds to the phospholipids in their liquid crystalline phase with an association constant of 950 M−1 and 1150 M−1 to DMPC and DPPC, respectively. Protonation of DIP leads to a 3-fold reduction of the association constant. For the gel phospholipid phase, the binding is smaller (a factor of 2), independently of pH, suggesting that the more flexible lipid packing in the liquid crystalline phase facilitates the binding of the drug. The association constant of RA25 neutral form is considerably lower than for DIP, being around 295 M−1. Fluorescence quenching with nitroxides TEMPO and stearic acid doxyl derivatives suggests the localization of DIP to be closer to the 5th carbon of alkyl chain. The quenching effect of 5-DSA below the lipid phase transition suggests that a strong static quenching may be operative. The quenching effect of 16-DSA is almost as great as that for 5-DSA below the phase transition, being even higher above the phase transition. This effect is probably due to the trans-gauche isomerization of the stearic acid nitroxide, making the encounter of its paramagnetic fragment with the DIP chromophore possible. Our data are consistent with DIP location close to the bilayer surface in the border of hydrophobic-polar heads interface which is similar to the data in micellar systems. In the case of RA25, the drug is in the outer part of the head group interface being much exposed to the aqueous phase and being significantly less accessible to the membrane nitroxide quenchers

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science

We present the Open MatSci ML Toolkit: a flexible, self-contained, and scalable Python-based framework to apply deep learning models and methods on scientific data with a specific focus on materials science and the OpenCatalyst Dataset. Our toolkit provides: 1. A scalable machine learning workflow for materials science leveraging PyTorch Lightning, which enables seamless scaling across different computation capabilities (laptop, server, cluster) and hardware platforms (CPU, GPU, XPU). 2. Deep Graph Library (DGL) support for rapid graph neural network prototyping and development. By publishing and sharing this toolkit with the research community via open-source release, we hope to: 1. Lower the entry barrier for new machine learning researchers and practitioners that want to get started with the OpenCatalyst dataset, which presently comprises the largest computational materials science dataset. 2. Enable the scientific community to apply advanced machine learning tools to high-impact scientific challenges, such as modeling of materials behavior for clean energy applications. We demonstrate the capabilities of our framework by enabling three new equivariant neural network models for multiple OpenCatalyst tasks and arrive at promising results for compute scaling and model performance.Comment: Paper accompanying Open-Source Software from https://github.com/IntelLabs/matscim

BREAST CANCER-ASSOCIATED MISSENSE MUTANTS OF THE PALB2 WD40 DOMAIN, WHICH DIRECTLY BINDS RAD51C, RAD51 AND BRCA2, DISRUPT DNA REPAIR

Heterozygous carriers of germ-line mutations in the BRCA2/FANCD1, PALB2/FANCN, and RAD51C/FANCO DNA repair genes have an increased life-time risk to develop breast, ovarian and other cancers; bi-allelic mutations in these genes clinically manifest as Fanconi anemia (FA). Here, we demonstrate that RAD51C is part of a novel protein complex that contains PALB2 and BRCA2. Further, the PALB2 WD40 domain can directly and independently bind RAD51C and BRCA2. To understand the role of these homologous recombination (HR) proteins in DNA repair, we functionally characterize effects of missense mutations of the PALB2 WD40 domain that have been reported in breast cancer patients. In contrast to large truncations of PALB2, which display a complete loss of interaction, the L939W, T1030I, and L1143P missense mutants/variants of PALB2 WD40 domain are associated with altered direct binding patterns to the RAD51C, RAD51 and BRCA2 HR proteins in biochemical assays. Further, the T1030I missense mutant is unstable, while the L939W and L1143P proteins are stable but partially disrupt the PALB2-RAD51C-BRCA2 complex in cells. Functionally, the L939W and L1143P mutants display a decreased capacity for DNA double-strand break-induced HR and an increased cellular sensitivity to ionizing radiation. As further evidence for the functional importance of the HR complex, RAD51C mutants that are associated with cancer susceptibility and FA also display decreased complex formation with PALB2. Together, our results suggest that three different cancer susceptibility and FA proteins function in a DNA repair pathway based upon the PALB2 WD40 domain binding to RAD51C and BRCA2