Results 51 to 60 of about 1,386,749 (339)

Accurate protein structure prediction with hydroxyl radical protein footprinting data

Nature Communications, 2021
Mass spectrometry-based covalent labeling techniques such as hydroxyl radical protein footprinting (HRPF) provide information about protein tertiary structures.
Sarah E. Biehn, Steffen Lindert
doaj   +1 more source

Performance Analysis of Deep Learning Methods for Protein Contact Prediction in CASP13

CLEI Electronic Journal, 2021
Protein structure prediction is one of the most important problems in Computational Biology; and consists of determining the 3D structure of a protein given its amino acid sequence.
Romina Valdez, Khevin Roig, Diego P. Pinto-Roa, Jose Colbes   +3 more
doaj   +1 more source

Accurate structure prediction of biomolecular interactions with AlphaFold 3

Nature
The introduction of AlphaFold 21 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design2, 3, 4, 5–6.
Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green, A. Pritzel, Olaf Ronneberger, Lindsay Willmore, Andrew J Ballard, Joshua Bambrick, Sebastian Bodenstein, David A Evans, Chia-Chun Hung, Michael O’Neill, D. Reiman, Kathryn Tunyasuvunakool, Zachary Wu, Akvile Zemgulyte, Eirini Arvaniti, Charles Beattie, Ottavia Bertolli, Alex Bridgland, Alexey Cherepanov, Miles Congreve, A. Cowen-Rivers, Andrew Cowie, Michael Figurnov, Fabian B Fuchs, Hannah Gladman, Rishub Jain, Yousuf A. Khan, Caroline M R Low, Kuba Perlin, Anna Potapenko, Pascal Savy, Sukhdeep Singh, A. Stecula, Ashok Thillaisundaram, Catherine Tong, Sergei Yakneen, Ellen D. Zhong, Michal Zielinski, Augustin Žídek, V. Bapst, Pushmeet Kohli, Max Jaderberg, D. Hassabis, J. Jumper   +47 more
semanticscholar   +1 more source

ClusterEmbed: Lightweight Protein Structure Prediction on PCs [PDF]

BIO Web of Conferences
Biological sequence design seeks to generate novel sequences, such as proteins, with optimized functional properties, a task complicated by vast combinatorial spaces and complex sequence-function relationships.
Yuan Chuxin
doaj   +1 more source

Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models

bioRxiv, 2022
There has been considerable recent progress in designing new proteins using deep learning methods1–9. Despite this progress, a general deep learning framework for protein design that enables solution of a wide range of design challenges, including de ...
Joseph L. Watson, David Juergens, N. Bennett, Brian L. Trippe, Jason Yim, Helen E. Eisenach, Woody Ahern, Andrew J. Borst, R. Ragotte, L. Milles, B. Wicky, Nikita Hanikel, S. Pellock, A. Courbet, W. Sheffler, Jue Wang, Preetham Venkatesh, Isaac Sappington, Susana Vázquez Torres, A. Lauko, Valentin De Bortoli, Emile Mathieu, R. Barzilay, T. Jaakkola, F. DiMaio, M. Baek, D. Baker   +26 more
semanticscholar   +1 more source

Mapping the evolution of mitochondrial complex I through structural variation

FEBS Letters, EarlyView.
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin, Tingting Chen, James A. Letts   +2 more
wiley   +1 more source

DeepComplex: A Web Server of Predicting Protein Complex Structures by Deep Learning Inter-chain Contact Prediction and Distance-Based Modelling

Frontiers in Molecular Biosciences, 2021
Proteins interact to form complexes. Predicting the quaternary structure of protein complexes is useful for protein function analysis, protein engineering, and drug design.
Farhan Quadir, Raj S. Roy, Elham Soltanikazemi, Jianlin Cheng   +3 more
doaj   +1 more source

Improved Protein Structure Prediction Using a New Multi‐Scale Network and Homologous Templates

Advancement of science, 2021
The accuracy of de novo protein structure prediction has been improved considerably in recent years, mostly due to the introduction of deep learning techniques.
Hong Su, Wenkai Wang, Zongyang Du, Zhenling Peng, Shanghua Gao, Mingg-Ming Cheng, Jianyi Yang   +6 more
semanticscholar   +1 more source

Enteropathogenic E. coli shows delayed attachment and host response in human jejunum organoid‐derived monolayers compared to HeLa cells

FEBS Letters, EarlyView.
Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi, Pilar Samperio Ventayol, Natalie Burkard, Nicolas Schlegel, Carmen Aguilar, Sina Bartfeld   +5 more
wiley   +1 more source

Protein language model embeddings for fast, accurate, alignment-free protein structure prediction

bioRxiv, 2021
All state-of-the-art (SOTA) protein structure predictions rely on evolutionary information captured in multiple sequence alignments (MSAs), primarily on evolutionary couplings (co-evolution).
Konstantin Weissenow, M. Heinzinger, B. Rost   +2 more
semanticscholar   +1 more source