RESUMEN
Accurately predicting cellular activities of proteins based on their primary amino acid sequences would greatly improve our understanding of the proteome. In this paper, we present CELL-E, a text-to-image transformer model that generates 2D probability density images describing the spatial distribution of proteins within cells. Given an amino acid sequence and a reference image for cell or nucleus morphology, CELL-E predicts a more refined representation of protein localization, as opposed to previous in silico methods that rely on pre-defined, discrete class annotations of protein localization to subcellular compartments.
RESUMEN
We present CELL-E 2, a novel bidirectional transformer that can generate images depicting protein subcellular localization from the amino acid sequences (and vice versa). Protein localization is a challenging problem that requires integrating sequence and image information, which most existing methods ignore. CELL-E 2 extends the work of CELL-E, not only capturing the spatial complexity of protein localization and produce probability estimates of localization atop a nucleus image, but also being able to generate sequences from images, enabling de novo protein design. We train and finetune CELL-E 2 on two large-scale datasets of human proteins. We also demonstrate how to use CELL-E 2 to create hundreds of novel nuclear localization signals (NLS). Results and interactive demos are featured at https://bohuanglab.github.io/CELL-E_2/.
RESUMEN
Distortion of nominally planar phthalocyanine macrocycles affects the excited state dynamics in that most of the excited-state energy decays through internal conversion. A click-type annulation reaction on a perfluorophthalocyanine platform appending a seven-membered ring to the ß-positions on one or more of the isoindoles distorts the macrocycle and modulates solubility. The distorted derivative enables photoacoustic imaging, photothermal effects, and strong surface-enhanced resonance Raman signals.
RESUMEN
Nanoparticles labeled with radiometals enable whole-body nuclear imaging and therapy. Though chelating agents are commonly used to radiolabel biomolecules, nanoparticles offer the advantage of attaching a radiometal directly to the nanoparticle itself without the need of such agents. We previously demonstrated that direct radiolabeling of silica nanoparticles with hard, oxophilic ions, such as the positron emitters zirconium-89 and gallium-68, is remarkably efficient. However, softer radiometals, such as the widely employed copper-64, do not stably bind to the silica matrix and quickly dissociate under physiological conditions. Here, we overcome this limitation through the use of silica nanoparticles functionalized with a soft electron-donating thiol group to allow stable attachment of copper-64. This approach significantly improves the stability of copper-64 labeled thiol-functionalized silica nanoparticles relative to native silica nanoparticles, thereby enabling in vivo PET imaging, and may be translated to other softer radiometals with affinity for sulfur. The presented approach expands the application of silica nanoparticles as a platform for facile radiolabeling with both hard and soft radiometal ions.
