Blind protein structure prediction using accelerated free-energy simulations. [PDF]
We report a key proof of principle of a new acceleration method [Modeling Employing Limited Data (MELD)] for predicting protein structures by molecular dynamics simulation.
Brini, Emiliano+4 more
core +1 more source
Advances in protein tertiary structure prediction
Proteins are composed of linear chains of amino acids that form a unique three-dimensional structure in their native environment. Such native structure favors the proteins to perform their biochemical activity.
Tayebeh Farhadi
doaj +1 more source
FLORA: a novel method to predict protein function from structure in diverse superfamilies [PDF]
Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation.
A Bairoch+52 more
core +4 more sources
PS4: a next-generation dataset for protein single-sequence secondary structure prediction
Protein secondary structure prediction is a subproblem of protein folding. A light-weight algorithm capable of accurately predicting secondary structure from only the protein residue sequence could provide useful input for tertiary structure prediction ...
Omar Peracha
doaj +1 more source
RosettaBackrub--a web server for flexible backbone protein structure modeling and design. [PDF]
The RosettaBackrub server (http://kortemmelab.ucsf.edu/backrub) implements the Backrub method, derived from observations of alternative conformations in high-resolution protein crystal structures, for flexible backbone protein modeling.
Friedland, Gregory F+4 more
core +2 more sources
Naive Prediction of Protein Backbone Phi and Psi Dihedral Angles Using Deep Learning
Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network ...
Matic Broz, Marko Jukič, Urban Bren
doaj +1 more source
Improved protein structure prediction using predicted interresidue orientations
Significance Protein structure prediction is a longstanding challenge in computational biology. Through extension of deep learning-based prediction to interresidue orientations in addition to distances, and the development of a constrained optimization ...
Jianyi Yang+5 more
semanticscholar +1 more source
Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction. [PDF]
BackgroundOne of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models.
Bourne, Philip E, Scheeff, Eric D
core +3 more sources
Performance Analysis of Deep Learning Methods for Protein Contact Prediction in CASP13
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+3 more
doaj +1 more source
Accurate structure prediction of biomolecular interactions with AlphaFold 3
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 design2–6. Here we describe our AlphaFold 3 model with a substantially
Josh Abramson+47 more
semanticscholar +1 more source