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1. OPTIMADE, an API for exchanging materials data

   https://doi.org/10.1038/s41597-021-00974-z  

   Andersen, Casper W.; Armiento, Rickard; Blokhin, Evgeny; Conduit, Gareth J.; Dwaraknath, Shyam; Evans, Matthew L.; Fekete, Ádám; Gopakumar, Abhijith; Gražulis, Saulius; Merkys, Andrius; et al (August 2021, Scientific Data)

   Abstract The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification. 

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2. Genome-wide effects of the antimicrobial peptide apidaecin on translation termination in bacteria

   https://doi.org/10.7554/eLife.62655  

   Mangano, Kyle; Florin, Tanja; Shao, Xinhao; Klepacki, Dorota; Chelysheva, Irina; Ignatova, Zoya; Gao, Yu; Mankin, Alexander S; Vázquez-Laslop, Nora (October 2020, eLife)

   null (Ed.)

   Biochemical studies suggested that the antimicrobial peptide apidaecin (Api) inhibits protein synthesis by binding in the nascent peptide exit tunnel and trapping the release factor associated with a terminating ribosome. The mode of Api action in bacterial cells had remained unknown. Here genome-wide analysis reveals that in bacteria, Api arrests translating ribosomes at stop codons and causes pronounced queuing of the trailing ribosomes. By sequestering the available release factors, Api promotes pervasive stop codon bypass, leading to the expression of proteins with C-terminal extensions. Api-mediated translation arrest leads to the futile activation of the ribosome rescue systems. Understanding the unique mechanism of Api action in living cells may facilitate the development of new medicines and research tools for genome exploration. 

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3. LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition

   Cherepanova, Valeriia; Goldblum, Micah; Foley, Harrison; Duan, Shiyuan; Dickerson, John P; Taylor, Gavin; Goldstein, Tom (April 2021, Proceedings of the International Conference on Learning Representations (ICLR))

   Facial recognition systems are increasingly deployed by private corporations, government agencies, and contractors for consumer services and mass surveillance programs alike. These systems are typically built by scraping social media profiles for user images. Adversarial perturbations have been proposed for bypassing facial recognition systems. However, existing methods fail on full-scale systems and commercial APIs. We develop our own adversarial filter that accounts for the entire image processing pipeline and is demonstrably effective against industrial-grade pipelines that include face detection and large scale databases. Additionally, we release an easy-to-use webtool that significantly degrades the accuracy of Amazon Rekognition and the Microsoft Azure Face Recognition API, reducing the accuracy of each to below 1%. 

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4. Charting the sequence-activity landscape of peptide inhibitors of translation termination

   https://doi.org/10.1073/pnas.2026465118  

   Baliga, Chetana; Brown, Tyler J.; Florin, Tanja; Colon, Sarah; Shah, Vallari; Skowron, Kornelia J.; Kefi, Amira; Szal, Teresa; Klepacki, Dorota; Moore, Terry W.; et al (March 2021, Proceedings of the National Academy of Sciences)

   Apidaecin (Api), an unmodified 18-amino-acid-long proline-rich antibacterial peptide produced by bees, has been recently described as a specific inhibitor of translation termination. It invades the nascent peptide exit tunnel of the postrelease ribosome and traps the release factors preventing their recycling. Api binds in the exit tunnel in an extended conformation that matches the placement of a nascent polypeptide and establishes multiple contacts with ribosomal RNA (rRNA) and ribosomal proteins. Which of these interactions are critical for Api’s activity is unknown. We addressed this problem by analyzing the activity of all possible single-amino-acid substitutions of the Api variants synthesized in the bacterial cell. By conditionally expressing the engineeredapigene, we generated Api directly in the bacterial cytosol, thereby bypassing the need for importing the peptide from the medium. The endogenously expressed Api, as well as its N-terminally truncated mutants, retained the antibacterial properties and the mechanism of action of the native peptide. Taking advantage of the Api expression system and next-generation sequencing, we mapped in one experiment all the single-amino-acid substitutions that preserve or alleviate the on-target activity of the Api mutants. Analysis of the inactivating mutations made it possible to define the pharmacophore of Api involved in critical interactions with the ribosome, transfer RNA (tRNA), and release factors. We also identified the Api segment that tolerates a variety of amino acid substitutions; alterations in this segment could be used to improve the pharmacological properties of the antibacterial peptide. 

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5. ChemProps: A RESTful API enabled database for composite polymer name standardization

   https://doi.org/10.1186/s13321-021-00502-6  

   Hu, Bingyin; Lin, Anqi; Brinson, L. Catherine (December 2021, Journal of Cheminformatics)

   null (Ed.)

   Abstract The inconsistency of polymer indexing caused by the lack of uniformity in expression of polymer names is a major challenge for widespread use of polymer related data resources and limits broad application of materials informatics for innovation in broad classes of polymer science and polymeric based materials. The current solution of using a variety of different chemical identifiers has proven insufficient to address the challenge and is not intuitive for researchers. This work proposes a multi-algorithm-based mapping methodology entitled ChemProps that is optimized to solve the polymer indexing issue with easy-to-update design both in depth and in width. RESTful API is enabled for lightweight data exchange and easy integration across data systems. A weight factor is assigned to each algorithm to generate scores for candidate chemical names and optimized to maximize the minimum value of the score difference between the ground truth chemical name and the other candidate chemical names. Ten-fold validation is utilized on the 160 training data points to prevent overfitting issues. The obtained set of weight factors achieves a 100% test accuracy on the 54 test data points. The weight factors will evolve as ChemProps grows. With ChemProps, other polymer databases can remove duplicate entries and enable a more accurate “search by SMILES” function by using ChemProps as a common name-to-SMILES translator through API calls. ChemProps is also an excellent tool for auto-populating polymer properties thanks to its easy-to-update design. 

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