Article
Biochemistry & Molecular Biology
Keisuke Kasahara, Daisuke Kuroda, Aki Tanabe, Raiji Kawade, Satoru Nagatoishi, Kouhei Tsumoto
Summary: In protein engineering, supercharging mutations improve physicochemical properties, while antibodies recognize antigens through surface antigen-binding sites. Surface charge is crucial in assessing therapeutic antibodies.
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Markus Bursch, Jan-Michael Mewes, Andreas Hansen, Stefan Grimme
Summary: This work provides best-practice guidance on various methodological and technical aspects of DFT calculations, including how to choose computational protocols, functionals, basis sets, and achieve an optimal balance between accuracy, robustness, and efficiency through multi-level approaches.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2022)
Article
Multidisciplinary Sciences
Sara Stabile, Francesca Palermo, Inna Bukreeva, Daniela Mele, Vincenzo Formoso, Roberto Bartolino, Alessia Cedola
Summary: This study utilizes X-ray phase contrast tomography to unlock the secrets of the ancient Herculaneum papyrus scrolls, paving the way for further investigation despite challenges in the unfolding process.
SCIENTIFIC REPORTS
(2021)
Article
Biochemistry & Molecular Biology
Denis Yuen, Louise Cabansay, Andrew Duncan, Gary Luu, Gregory Hogue, Charles Overbeck, Natalie Perez, Walt Shands, David Steinberg, Chaz Reid, Nneka Olunwa, Richard Hansen, Elizabeth Sheets, Ash O'Farrell, Kim Cullion, Brian D. O'Connor, Benedict Paten, Lincoln Stein
Summary: Dockstore is an open source platform that facilitates the publishing, sharing, and finding of bioinformatics tools and workflows. It uses cloud technologies to increase the FAIRness of computational resources, promoting reproducibility in complex bioinformatics analyses. The platform supports various source repositories, analysis frameworks, and language technologies for authors to create a centralized catalogue of scientific software.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Nanoscience & Nanotechnology
Jooyeon Shin, Jong-Gu Lee, Gunhee Lee, Peter Pikhitsa, Sang Moon Kim, Mansoo Choi, Yong Whan Choi
Summary: This study presents a smart switching surface that can generate and remove wrinkles reversibly to adapt to both wet and dry environments, enabling robots to complete tasks in different conditions. The wrinkles on denser and smaller hexagonal patterns generate six times more friction than non-switching flat surfaces in wet environments, and a similar amount of friction to the flat surfaces in dry environments.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Biology
Jordan DeKraker, Roy A. M. Haast, Mohamed D. Yousif, Bradley Karat, Jonathan C. Lau, Stefan Kohler, Ali R. Khan
Summary: The article introduces an automated and robust BIDS-App tool called HippUnfold, which can be used to define and index individual-specific hippocampal folding in MRI for more detailed neuroimaging analysis.
Article
Chemistry, Multidisciplinary
Thomas Malcomson, Peter Repiscak, Stefan Erhardt, Martin J. Paterson
Summary: The suitability of single-reference density functional theory (DFT) methods for calculating the redox potentials of copper-containing macrocycle complexes was confirmed. Improvement in the cc-pVnZ basis set series had a significant effect on the calculated redox potentials, but they readily converged at the cc-pVTZ level. The all-electron Def2-TZVPP basis set was found to be a suitable choice for calculating redox potentials using a cc-pVTZ geometry. The best-performing model chemistries were determined to be the M06/polarizable continuum model (PCM), and a reliable scheme for calculating redox potentials of copper macrocycles was proposed using M06/cc-pVTZ with PCM solvation.
Article
Computer Science, Software Engineering
X. Su, Y. Hong, J. Ye, F. Xu, X. Yuan
Summary: Non-line-of-sight (NLOS) imaging technology has rapidly developed in recent years, enabling the reconstruction of hidden objects through analyzing diffuse reflection of relay surfaces. To address the limitations in handling multiple spatial-temporal resolution and multi-scene images, a novel end-to-end Multi-scale Iterative Model-guided Unfolding (MIMU) method is proposed, which shows superior performance and flexibility. The lack of real training data is overcome by training the method in simulation. Simulation and real-data experiments demonstrate that the proposed method achieves better reconstruction results in terms of quality and quantity compared to existing methods.
COMPUTER GRAPHICS FORUM
(2023)
Article
Chemistry, Physical
David Dirnberger, Georg Kresse, Cesare Franchini, Michele Reticcioli
Summary: Modern computing facilities allow for first-principles density functional theory studies of complex physical and chemical phenomena, often linked to large supercells. However, supercells in reciprocal space have small Brillouin zones with folded electronic eigenstates, making analysis challenging. An unfolding scheme embedded in the Vienna Ab initio Simulation Package (VASP) has been proposed to reconstruct electronic band structures from supercells to primitive cell Brillouin zones.
JOURNAL OF PHYSICAL CHEMISTRY C
(2021)
Article
Computer Science, Information Systems
Brijesh Soni, Dhaval K. Patel, Sanket B. Shah, Miguel Lopez-Benitez, Siddhartan Govindasamy
Summary: In this paper, a deep unfolding architecture called Primary User-Detection Network (PU-DetNet) is proposed, which combines the advantages of analytical and data-driven approaches, reduces computational cost, and achieves significant improvements in detection probability, accuracy, and throughput.
Article
Robotics
Ke Liu, Felix Hacker, Chiara Daraio
Summary: Continuous and controlled shape morphing for soft machines is achieved through a soft, robotic surface with large, reprogrammable, and pliable shape morphing capabilities. The surface consists of active and passive networks for muscle-like functions, allowing for smooth transformation of 2D sheets into arbitrary 3D geometries. This approach provides sufficient mechanical stiffness and stability for manipulating objects beyond shape changes.
Article
Computer Science, Artificial Intelligence
Jiechong Song, Bin Chen, Jian Zhang
Summary: In this paper, a novel Dynamic Path-Controllable Deep Unfolding Network (DPC-DUN) is proposed for compressive sensing (CS) reconstruction. DPC-DUN, with a designed path-controllable selector, can dynamically select a rapid and appropriate route for each image and is adjustable by regulating different performance-complexity tradeoffs. Experimental results demonstrate that our DPC-DUN is highly flexible, providing excellent performance and dynamic adjustment to meet the main requirements for practical applications.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2023)
Article
Multidisciplinary Sciences
Wellington Souto Ribeiro, Adriano Sant'Ana Silva, Alvaro Gustavo Ferreira da Silva, Ana Marinho do Nascimento, Marcelo Augusto Rocha Limao, Franciscleudo Bezerra da Costa, Pahlevi Augusto de Souza, Alexandre Jose de Melo Queiroz, Osvaldo Soares da Silva, Pluvia Oliveira Galdino, Rossana Maria Feitosa de Figueiredo, Silvanda de Melo Silva, Fernando Luiz Finger
Summary: The solar dryer plays an important role in reducing production costs, energy consumption, and post-harvest losses, making it suitable for small and medium producers to maintain tomato quality.
SCIENTIFIC REPORTS
(2021)
Article
Biotechnology & Applied Microbiology
Sotirios Zerveas, Evaggelos Kydonakis, Melpomeni-Sofia Mente, Vangelis Daskalakis, Kiriakos Kotzabasis
Summary: Metabolism, the total sum of chemical reactions that support life, can be completely halted in organisms from microalgae to yeast when exposed to a 100% hydrogen atmosphere, with cell growth and metabolic rate reversibly arrested. However, the addition of oxygen or air can almost fully restore these functions. Molecular dynamics simulations reveal that hydrogen interaction with proteins enhances thermostability, allowing for biological products to be preserved without energy consumption. This research paves the way for future innovative studies and advancements in biotechnology by combining biological, chemical, and computational methods.
JOURNAL OF BIOTECHNOLOGY
(2021)
Article
Cell Biology
Edgar Garza-Lopez, Zer Vue, Prasanna Katti, Kit Neikirk, Michelle Biete, Jacob Lam, Heather K. Beasley, Andrea G. Marshall, Taylor A. Rodman, Trace A. Christensen, Jeffrey L. Salisbury, Larry Vang, Margaret Mungai, Salma AshShareef, Sandra A. Murray, Jianqiang Shao, Jennifer Streeter, Brian Glancy, Renata O. Pereira, E. Dale Abel, Antentor Hinton
Summary: High-resolution 3D images of organelles are important in cellular biology. Recent technological advances enable the creation of 3D images for the ultrastructural analysis of organelles. This article describes a standardized protocol using Amira software for quantifying organelle morphologies in 3D and demonstrates its applications in quantifying mitochondria and endoplasmic reticulum structures.
Article
Chemistry, Physical
Sai Pooja Mahajan, Yashes Srinivasan, Jason W. Labonte, Matthew P. DeLisa, Jeffrey J. Gray
Summary: This study decoded the sequence and structural motifs determining peptide substrate preferences for the GalNAc-T2 isoform, revealing enzyme features that lead to finely tuned specificity for a broad range of peptide substrates. Computational scanning and experimental validation successfully discriminated glycosylatable peptides with high efficiency, providing insights for designing enzyme variants with tailored specificity in the future.
Article
Nanoscience & Nanotechnology
Kimberly L. Berk, Steven M. Blum, Vanessa L. Funk, Yuhua Sun, In-Young Yang, Mark Gostomski, Pierce A. Roth, Alvin T. Liem, Peter A. Emanuel, Michael E. Hogan, Aleksandr E. Miklos, Matthew W. Lux
Summary: The use of DNA nanotechnology to create DNA taggants allows for quick and efficient field validation with simple equipment, ensuring high security and reliability for tracking and verifying high-value or high-security items.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Biochemistry & Molecular Biology
Ameya Harmalkar, Jeffrey J. Gray
Summary: Computational docking methods can provide structural models of protein-protein complexes, but protein backbone flexibility can hinder accurate predictions. Recent advances include enhanced sampling techniques and internal coordinate formulations to address the issue of protein backbone flexibility.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Jeliazko R. Jeliazkov, Rahel Frick, Jing Zhou, Jeffrey J. Gray
Summary: In recent years, advances in high-throughput sequencing have led to exponential growth in the observed antibody sequence space, but not in the number of structures. Computational modeling has the potential to bridge this gap, but further improvements are needed, particularly in accuracy and speed, especially in modeling CDR-H3 loops.
Article
Biochemical Research Methods
Steven M. Blum, Marilyn S. Lee, Glory E. Mgboji, Vanessa L. Funk, Kathryn Beabout, Svetlana Harbaugh, Pierce A. Roth, Alvin T. Liem, Aleksandr E. Miklos, Peter A. Emanuel, Scott A. Walper, Jorge Luis Chavez, Matthew W. Lux
Summary: The performance of cell-free expression systems varies significantly under different matrix materials, highlighting the importance of selecting suitable matrices. Adjusting the rehydration volume of lyophilized reactions can enhance reaction speed, with minimal impact of different matrices. The application of cell-free expression systems holds great potential for on-site practice.
ACS SYNTHETIC BIOLOGY
(2021)
Article
Chemistry, Physical
Rebecca F. Alford, Rituparna Samanta, Jeffrey J. Gray
Summary: Energy functions are crucial for biomolecular modeling, with membrane protein energy functions lagging behind soluble protein ones due to sparse data and overfitting issues. To address this challenge, a suite of 12 tests on diverse independent data sets was conducted, evaluating the ability of energy functions to capture membrane protein orientation, stability, sequence, and structure. Findings point out areas for improvement in energy functions and potential integration with machine-learning-based optimization methods in the future.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2021)
Article
Chemistry, Physical
Morgan L. Nance, Jason W. Labonte, Jared Adolf-Bryfogle, Jeffrey J. Gray
Summary: Carbohydrate chains play a crucial role in regulating biological functions through interactions with protein receptors. The GlycanDock algorithm developed for protein-glycoligand docking refinement shows potential in high-resolution structural studies and can address experimental challenges. This algorithm has the ability to sample and discriminate among protein-glycoligand models with statistical reliability, making it a valuable tool in glycosciences research acceleration.
JOURNAL OF PHYSICAL CHEMISTRY B
(2021)
Article
Chemistry, Multidisciplinary
E. Randal Hofmann, Charles Davidson, Hsiu Chen, Melody Zacharko, Jay E. Dorton, Gary K. Kilper, Carcie Graves, Aleksandr E. Miklos, Katherine Rhea, Joe Ma, Bruce G. Goodwin, Shanmuga Sozhamannan
Summary: Lateral flow immunoassays are simple diagnostic devices used for detecting biological agents or other analytes of interest. There is a need for multiplex LFI devices that can differentiate between pathogens, especially in situations where reducing assay time and costs is critical. Developing a sensor-based multiplex LFI device could improve accuracy in interpreting ambiguous test results, especially at lower antigen concentrations and when there are imperfections in the strips.
Article
Multidisciplinary Sciences
Julia Koehler Leman, Sergey Lyskov, Steven M. Lewis, Jared Adolf-Bryfogle, Rebecca F. Alford, Kyle Barlow, Ziv Ben-Aharon, Daniel Farrell, Jason Fell, William A. Hansen, Ameya Harmalkar, Jeliazko Jeliazkov, Georg Kuenze, Justyna D. Krys, Ajasja Ljubetic, Amanda L. Loshbaugh, Jack Maguire, Rocco Moretti, Vikram Khipple Mulligan, Morgan L. Nance, Phuong T. Nguyen, Shane O. Conchuir, Shourya S. Roy Burman, Rituparna Samanta, Shannon T. Smith, Frank Teets, Johanna K. S. Tiemann, Andrew Watkins, Hope Woods, Brahm J. Yachnin, Christopher D. Bahl, Chris Bailey-Kellogg, David Baker, Rhiju Das, Frank DiMaio, Sagar D. Khare, Tanja Kortemme, Jason W. Labonte, Kresten Lindorff-Larsen, Jens Meiler, William Schief, Ora Schueler-Furman, Justin B. Siegel, Amelie Stein, Vladimir Yarov-Yarovoy, Brian Kuhlman, Andrew Leaver-Fay, Dominik Gront, Jeffrey J. Gray, Richard Bonneau
Summary: Vast international resources are wasted on irreproducible research each year, but reproducible scientific software applications can be created by meeting simple design goals. This reproducible design framework is valuable for developers and users of any scientific software, helping the scientific community create reproducible methods.
NATURE COMMUNICATIONS
(2021)
Article
Education, Scientific Disciplines
Olivia A. Erickson, Rebecca B. Cole, Jared M. Isaacs, Silvia Alvarez-Clare, Jonathan Arnold, Allison Augustus-Wallace, Joseph C. Ayoob, Alan Berkowitz, Janet Branchaw, Kevin R. Burgio, Charles H. Cannon, Ruben Michael Ceballos, C. Sarah Cohen, Hilary Coller, Jane Disney, Van A. Doze, Margaret J. Eggers, Stacy Farina, Edwin L. Ferguson, Jeffrey J. Gray, Jean T. Greenberg, Alexander Hoffmann, Danielle Jensen-Ryan, Robert M. Kao, Alex C. Keene, Johanna E. Kowalko, Steven A. Lopez, Camille Mathis, Mona Minkara, Courtney J. Murren, Mary Jo Ondrechen, Patricia Ordonez, Anne Osano, Elizabeth Padilla-Crespo, Soubantika Palchoudhury, Hong Qin, Juan Ramirez-Lugo, Jennifer Reithel, Colin A. Shaw, Amber Smith, Rosemary Smith, Adam P. Summers, Fern Tsien, Erin L. Dolan
Summary: This paragraph describes the impact of the COVID-19 pandemic on undergraduate research programs in the United States and the implementation of remote undergraduate research programs in the life sciences. Through surveys and discussions, the strengths, weaknesses, and recommendations for improvement of these programs were identified. Despite coinciding with a peak in awareness of racial inequities and structural racism, students reported lower focus on these topics.
CBE-LIFE SCIENCES EDUCATION
(2022)
Article
Multidisciplinary Sciences
Deniz Akpinaroglu, Jeffrey A. Ruffolo, Sai Pooja Mahajan, Jeffrey J. Gray
Summary: Antibody engineering is widely used in medicine and accurate modeling of antibody structures is crucial for effective engineering and design. We developed DeepSCAb, a deep learning method that predicts both backbone and side-chain conformations of antibodies, improving the accuracy of antibody structure prediction. This method is particularly useful for antibodies without known backbone structures.
Article
Biochemical Research Methods
Ameya Harmalkar, Sai Pooja Mahajan, Jeffrey J. Gray
Summary: We developed a new sampling method, ReplicaDock 2.0, for protein complex structure prediction that successfully captures binding-induced conformational changes. Our method mimics the induced-fit mechanism of protein binding and is significantly faster than Molecular Dynamics based approaches. It achieves high success rates for moderately and highly flexible targets.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Veda Sheersh Boorla, Ratul Chowdhury, Ranjani Ramasubramanian, Brandon Ameglio, Rahel Frick, Jeffrey J. Gray, Costas D. Maranas
Summary: This study focuses on the computational design of neutralizing antibodies for emerging SARS-CoV-2 variants. By recombining VDJ genes and optimizing amino acid substitutions, high-affinity antibody variable regions were designed. Computational evaluation identified a promising candidate for experimental testing.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
(2023)
Article
Materials Science, Biomaterials
Kathryn Beabout, Amy M. Ehrenworth Breedon, Steven M. Blum, Aleksandr E. Miklos, Matthew W. Lux, Jorge L. Chavez, Michael S. Goodson
Summary: Bile acids play a crucial role in digestion and human health and can serve as biomarkers for monitoring health and detecting fecal contamination in water sources. By optimizing and transferring the expression of the sensor, its sensitivity and utility have been significantly improved.
ACS BIOMATERIALS SCIENCE & ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Jeffrey A. Ruffolo, Jeremias Sulam, Jeffrey J. Gray
Summary: DeepAb is a deep learning method that accurately predicts antibody FV structures from sequences. It outperforms alternative methods on diverse and therapeutically relevant antibodies and offers interpretable predictions by introducing an attention mechanism. Additionally, a mutant scoring metric derived from network confidence improves binding affinity for a specific antibody.