Article
Genetics & Heredity
Ariel Gershman, Tatiana G. Romer, Yunfan Fan, Roham Razaghi, Wendy A. Smith, Winston Timp
Summary: Researchers introduced a new, more complete reference genome JHU_Msex_v1.0 for the tobacco hornworm, generated using modern technologies to improve genome continuity and accuracy. The assembly includes 25,256 genes and is accessible for public use, demonstrating benefits for future research on the tobacco hornworm as a model organism.
G3-GENES GENOMES GENETICS
(2021)
Article
Multidisciplinary Sciences
Ivana Daubnerova, Ladislav Roller, Honoo Satake, Chen Zhang, Young-Joon Kim, Dusan Zitnan
Summary: Insect ecdysis triggering hormones act on specific neurons in the central nervous system to activate the ecdysis sequence, with different ETH receptor subtypes showing distinct spatial and temporal expression patterns in the CNS to control various stages of the ecdysis process.
SCIENTIFIC REPORTS
(2021)
Article
Biochemistry & Molecular Biology
Anna Grandchamp, Peter Czuppon, Erich Bornberg-Bauer
Summary: Most eukaryotic genomes consist of non-coding transcripts. Newly transcribed non-coding transcripts, known as de novo transcripts, play a crucial role in genomic innovations. This study investigated the rates at which de novo transcripts are gained and lost in individuals of the same species and found a high turnover rate, suggesting frequent exploration of new genomic sequences within species.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Microbiology
Rosalina Garcia-Suarez, Luis A. Verduzco-Rosas, Jorge E. Ibarra
Summary: The recent discovery of endophytic strains of Bacillus thuringiensis has greatly enhanced understanding of its ecology and provided a potential new source of insecticidal strains. Two endophytic strains of B. thuringiensis isolated from lavender and Poinsettia sap exhibited high insecticidal activity, similar morphology, and increased toxicity compared to standard strains. Characterization of these strains indicated their relationship to existing standard serotypes and the potential of endophytic strains as a valuable resource for insecticidal applications.
FEMS MICROBIOLOGY ECOLOGY
(2021)
Review
Chemistry, Multidisciplinary
Dong Si, Andrew Nakamura, Runbang Tang, Haowen Guan, Jie Hou, Ammaar Firozi, Renzhi Cao, Kyle Hippe, Minglei Zhao
Summary: Cryo-electron microscopy (cryo-EM) is a major experimental technique for determining structures of large protein complexes. In recent years, using machine learning and deep learning for new cryo-EM modeling has emerged as a top-performing method in macromolecular structure modeling.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2022)
Article
Oncology
Ana C. Garrido-Castro, Liam F. Spurr, Melissa E. Hughes, Yvonne Y. Li, Andrew D. Cherniack, Priti Kumari, Maxwell R. Lloyd, Brittany Bychkovsky, Romualdo Barroso-Sousa, Simona Di Lascio, Esha Jain, Janet Files, Ayesha Mohammed-Abreu, Max Krevalin, Colin MacKichan, William T. Barry, Hao Guo, Daniel Xia, Ethan Cerami, Barrett J. Rollins, Laura E. MacConaill, Neal Lindeman, Ian E. Krop, Bruce E. Johnson, Nikhil Wagle, Eric P. Winer, Deborah A. Dillon, Nancy U. Lin
Summary: The study compared the genomic landscapes of de novo metastatic breast cancer (dnMBC) with recurrent metastatic breast cancer (rMBC) and found MYB amplification was enriched in triple-negative dnMBC. Mutations in specific genes were more prevalent in dnMBC, and alterations associated with shorter overall survival were identified. High tumor mutational burden correlated with better overall survival in triple-negative dnMBC, suggesting potential implications for therapeutic strategies.
CLINICAL CANCER RESEARCH
(2021)
Article
Neurosciences
Noa Bielopolski, Michal Stawarski, Ilana Roitman, Karen Fridman, Shane Wald-Altman, Simon Fruh, Bernhard Bettler, Andreea Nissenkorn
Summary: GABBR2 gene mutations are associated with various neurological and developmental disorders. This study investigated the impact of a GABBR2 gene mutation on protein structure and receptor activity in a patient with autism. The mutation was found to alter the protein conformation and affect receptor activity. These findings shed light on the pathogenic mechanisms of gene mutations and provide guidance for personalized treatment.
FRONTIERS IN MOLECULAR NEUROSCIENCE
(2023)
Review
Pharmacology & Pharmacy
Joshua Meyers, Benedek Fabian, Nathan Brown
Summary: This review discusses the application of computational methods in drug discovery, focusing on molecular design strategies and de novo approaches. The methods of molecular design are categorized based on the coarseness of molecular representation, such as atom-based, fragment-based, or reaction-based paradigms. The importance of strong benchmarks, challenges in practical application, and potential opportunities for exploration and growth in the field are highlighted.
DRUG DISCOVERY TODAY
(2021)
Article
Immunology
Patrick O. Sakyi, Emmanuel Broni, Richard K. Amewu, Whelton A. Miller, Michael D. Wilson, Samuel Kojo Kwofie
Summary: This study explores a novel approach to address the therapeutic challenges of leishmaniasis by identifying potential inhibitory molecules. Through homology modeling and virtual screening, six potential inhibitors were identified, with one predicted to possess antileishmanial properties.
FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY
(2022)
Article
Chemistry, Medicinal
Sara Romeo Atance, Juan Viguera Diez, Ola Engkvist, Simon Olsson, Rocio Mercado
Summary: This research proposes a new reinforcement learning scheme to fine-tune graph-based deep generative models for de novo molecular design. The proposed approach can successfully guide a pretrained generative model to generate molecules with specific properties, even if these molecules are not present in the training set.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Biochemistry & Molecular Biology
Dong Si, Jason Chen, Andrew Nakamura, Luca Chang, Haowen Guan
Summary: The study of macromolecular structures has revolutionized the pharmaceutical industry's development of new vaccines. While X-ray crystallography has been the traditional method, cryo-EM is gaining popularity due to recent advancements. Automated software is desired for labor-intensive de novo macromolecular complex modeling. This paper presents deep learning-based methods for macromolecule modeling applications.
JOURNAL OF MOLECULAR BIOLOGY
(2023)
Article
Biochemical Research Methods
Tim Kucera, Matteo Togninalli, Laetitia Meng-Papaxanthos
Summary: Motivation: Protein design is crucial for medical and biotechnological applications. However, creating novel proteins is laborious and time-consuming due to the complex mechanisms involved. Machine learning has shown promise in solving complex problems, particularly in generative modeling. In this study, the authors address the problem of general protein design by developing a conditional generative adversarial network called ProteoGAN. They evaluate the model using biologically and statistically inspired metrics and demonstrate its superiority over other deep-learning baselines.
Article
Chemistry, Multidisciplinary
Zheng Tan, Yan Li, Xin Wu, Ziying Zhang, Weimei Shi, Shiqing Yang, Wanli Zhang
Summary: This article introduces a new AI method for fluorescent materials design using a generative adversarial network to generate samples and accurately forecast fluorescent properties, demonstrating its potential.
Article
Biochemistry & Molecular Biology
Sina Kordes, Sergio Romero-Romero, Leonie Lutz, Birte Hoecker
Summary: This study investigates the effects of introducing salt bridge clusters into different protein structures on their stability and conformational stability, revealing that salt bridge clusters can have varying impacts on the conformational stability of proteins.
Article
Multidisciplinary Sciences
Amir Pandi, David Adam, Amir Zare, Van Tuan Trinh, Stefan L. Schaefer, Marie Burt, Bjorn Klabunde, Elizaveta Bobkova, Manish Kushwaha, Yeganeh Foroughijabbari, Peter Braun, Christoph Spahn, Christian Preusser, Elke Pogge von Strandmann, Helge B. Bode, Heiner von Buttlar, Wilhelm Bertrams, Anna Lena Jung, Frank Abendroth, Bernd Schmeck, Gerhard Hummer, Olalla Vazquez, Tobias J. Erb
Summary: This study demonstrates the potential of using deep learning and cell-free protein synthesis for the rapid and cost-effective production and testing of bioactive peptides. Through computational methods and experimental validation, the authors identified 30 functional peptides, including six with broad-spectrum activity against drug-resistant pathogens.
NATURE COMMUNICATIONS
(2023)