27 papers · ranked by Valyu relevance
Daniel Russel, Keren Lasker, Ben Webb, Javier Velázquez-Muriel + 4 more
'Elina Tjioe' 'Dina Schneidman-Duhovny' 'Bret Peterson' 'Andrej Sali'] A set of software tools for building and distributing models of macromolecular assemblies uses an integrative structure modeling approach, which casts the building of models as a computational optimization problem where information is encoded into a…
Andrej Sali
Integrative modeling is an increasingly important tool in structural biology, providing structures by combining data from varied experimental methods and prior information. As a result, molecular architectures of large, heterogeneous, and dynamic systems, such as the ∼52-MDa Nuclear Pore Complex, can be mapped with…
Kari Gaalswyk, Mir Ishruna Muniyat, Justin L. MacCallum
Biomolecular structure determination has long relied on heuristics based on physical insight; however, recent efforts to model conformational ensembles and to make sense of sparse, ambiguous, and noisy data have revealed the value of detailed, quantitative physical models in structure determination. We review these two…
Aleeza Kazmi, Muhammad Kazim, Faisal Aslam, Syeda Mahreen-ul-Hassan Kazmi + 6 more
Protein is the building block for all organisms. Protein structure prediction is always a complicated task in the field of proteomics. DNA and protein databases can find the primary sequence of the peptide chain and even similar sequences in different proteins. Mainly, there are two methodologies based on the presence…
Giacomo Janson, Alessandro Grottesi, Marco Pietrosanto, Gabriele Ausiello + 2 more
The most frequently used approach for protein structure prediction is currently homology modeling. The 3D model building phase of this methodology is critical for obtaining an accurate and biologically useful prediction. The most widely employed tool to perform this task is MODELLER. This program implements the…
Faraz Faruqi, Amira Abdel-Rahman, Leandra Tejedor, Martin Nisser + 6 more
Figure 1: MechStyle enables creators to stylize 3D models with text prompts while preserving their structural integrity. Here, we used MechStyle to stylize five 3D models while ensuring that the printed objects do not break when accidentally dropped by the user: a) an eye-glass frame stylized with 'fish scales' while…
Isaac Joffe, Yuchen Qian, Mohammad Talebi-Kalaleh, Qipei Mei + 2 more
Structural engineers are often required to draw two-dimensional engineering sketches for quick structural analysis, either by hand calculation or using analysis software. However, calculation by hand is slow and error-prone, and the manual conversion of a hand-drawn sketch into a virtual model is tedious and…
Lim Heo, Collin Arbour, Michael Feig
Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict…
Julia Koehler Leman, Richard Bonneau
Structures of membrane proteins are challenging to determine experimentally and currently represent only about 2% of the structures in the ProteinDataBank. Because of this disparity, methods for modeling membrane proteins are fewer and of lower quality than those for modeling soluble proteins. However, better…
Jason J. Maldonis, Zhongnan Xu, Zhewen Song, Min Yu + 3 more
'Dane Morgan' 'Paul M. Voyles'] StructOpt, an open-source structure optimization suite, applies genetic algorithm and particle swarm methods to obtain atomic structures that minimize an objective function. The objective function typically consists of the energy and the error between simulated and experimental data…
Ladislav Svoboda, Jan Novák, Lukáš Kurilla, Jan Zeman
This paper presents a methodology and software tools for parametric design of complex architectural objects, called digital or algorithmic forms. In order to provide a flexible tool, the proposed design philosophy involves two open source utilities Donkey and MIDAS written in Grasshopper algorithm editor and C++…
Noah Kleinschmidt, Thomas Lemmin
In recent years computational methods for molecular modeling have become a prime focus of computational biology and cheminformatics. Many dedicated systems exist for modeling specific classes of molecules such as proteins or small drug-like ligands. These are often heavily tailored toward the automated gen- eration of…
Angelo Marcello Tarantino, Carmelo Majorana, Raimondo Luciano, Michele Bacciocchi + 1 more
'Michele Bacciocchi' 'Gabriele Milani'] The current Special Issue entitled “Advances in Structural Mechanics Modeled with FEM” aims to collect several numerical investigations and analyses focused on the use of the Finite Element Method (FEM). The undeniable spread of this methodology in the recent decades is due to…
Evaggelos Kaselouris
Advances in materials science, engineering, and computer science have created new opportunities for physicists and engineers to develop novel methods for material processing and characterization. This has led to a greater need for advanced modeling and simulation techniques that can capture multiphysics phenomena…
Authors not listed
Heterogeneous and electrocatalysts play a crucial role in enabling various industrial chemical transformations, with quantum chemistry calculations serving as a fundamental tool for investigating their atomic-scale properties. Advances in computational power have facilitated the study of increasingly complex catalytic…
Ondřej Červinek, Benjamin Werner, Daniel Koutný, Ondřej Vaverka + 3 more
'Libor Pantělejev' 'David Paloušek' 'Aniello Riccio'] Additive manufacturing methods (AM) allow the production of complex-shaped lattice structures from a wide range of materials with enhanced mechanical properties, e.g., high strength to relative density ratio. These structures can be modified for various applications…
Mathias Peirlinck, Kevin Linka, Juan A. Hurtado, Gerhard A. Holzapfel + 1 more
Personalized computational simulations have emerged as a vital tool to understand the biomechanical factors of a disease, predict disease progression, and design personalized intervention. Material modeling is critical for realistic biomedical simulations, and poor model selection can have life-threatening consequences…
Yu Deng, Chufeng Xiao, Manfred Lau, Hongbo Fu
—In the process of product design and digital fabrication, the structural analysis of a designed prototype is a fundamental and essential step. However, such a step is usually invisible or inaccessible to designers at the early sketching phase. This limits the user's ability to consider a shape's physical properties…
Arthur Hardiagon, François-Xavier Coudert
Nanoporous frameworks are a large and diverse family of materials, with a key role in various industrial processes and applications such as energy production and conversion, fluid separation, gas storage, water harvesting, and many more. The performance and suitability of nanoporous materials for each specific…
Shun-Peng Zhu, Abílio M. P. De Jesus, Filippo Berto, John G. Michopoulos + 2 more
'John G. Michopoulos' 'Francesco Iacoviello' 'Qingyuan Wang'] The issue focuses on physics-informed machine learning and its applications for structural integrity and safety assessment of engineering systems/facilities. Data science and data mining are fields in fast development with a high potential in several…
Authors not listed
Cellular metamaterials offer a vast design space for tailoring nonlinear mechanical responses, yet exploring this space with conventional modeling approaches is often infeasible or not scalable. To fully exploit their nonlinear behavior for inverse design, it is essential to learn the full stress–strain response rather…
Bruna Silva, Marco Domingos, Sandra Amado, Juliana R. Dias + 4 more
'Paula Pascoal-Faria' 'Ana C. Maurício' 'Nuno Alves' 'Dimitrios Kouroupis'] Understanding the complex mechanical behavior of osteochondral tissues in silico is essential for improving experimental models and advancing research in joint health and degeneration. This review provides a comprehensive analysis of the…
Marius Tacke, Matthias Busch, Kian Abdolazizi, Jonas Eichinger + 3 more
Developing constitutive models that capture how materials deform under load traditionally requires years of specialized expertise in continuum mechanics, machine learning, and scientific programming. Large language models (LLMs) have recently been shown to lower this barrier by generating constitutive models on demand…
Suraj Reddy
Materials with special geometrically designed microstructures, referred to as metamaterials, have gained significant attention in the world due to their unique properties of toughness and failureresistance. The ability to simply alter the internal geometry of almost any material to exponentially increase strength is…
Authors not listed
The discovery of radiation-resistant polymers is vital for aerospace, medical, and energy applications, where ionizing radiation rapidly degrades conventional materials. Inspired by the impact of Google DeepMind’s AlphaFold in structural biology, this study presents a closed-loop generative AI framework for polymer…
Jack D. Evans, François-Xavier Coudert
We show here that machine learning is a powerful new tool for predicting the elastic response of zeolites. We built our machine learning approach relying on geometric features only, which are related to local geometry, structure and porosity of a zeolite, to predict bulk and shear moduli of zeolites with an accuracy…
Christopher Schölzel, Valeria Blesius, Gernot Ernst, Andreas Dominik
Reproducible, understandable models that can be reused and combined to true multi-scale systems are required to solve the present and future challenges of systems biology. However, many mathematical models are still built for a single purpose and reusing them in a different context can be challenging due to an…