Computational Methods for Protein Structures

Computational methods employing machine learning algorithms are powerful tools that can be used to predict the effect of mutations on protein structure. This is important in neurodegenerative disorders, where some mutations can cause the formation of toxic protein aggregations. This feed follows the latests insights into the relationships between mutation and protein structure leading to better understanding of disease.

January 13, 2022

Predicting and interpreting large-scale mutagenesis data using analyses of protein stability and conservation.

Cell Reports
Magnus Haraldson HøieKresten Lindorff-Larsen
January 7, 2022
Preprint
Open Access

Resolving Protein Conformational Plasticity and Substrate Binding Through the Lens of Machine-Learning

BioRxiv : the Preprint Server for Biology
Navjeet Ahalawat, J. Mondal
January 3, 2022
Preprint

Biased Hypothesis Formation From Projection Pursuit

ArXiv
John PattersonDonald J. Jacobs
January 5, 2022
Preprint
Open Access

Machine learning guided design of high affinity ACE2 decoys for SARS-CoV-2 neutralization.

BioRxiv : the Preprint Server for Biology
Matthew C ChanDiwakar Shukla
December 28, 2021
Preprint
Open Access

Network-guided supervised learning on gene expression using a graph convolutional neural network

BioRxiv : the Preprint Server for Biology
Chayaporn Suphavilai, H. Yingtaweesittikul
December 28, 2021
Preprint
Open Access

Structural Evolution of the Ancient Enzyme, Dissimilatory Sulfite Reductase

BioRxiv : the Preprint Server for Biology
D. R. ColmanC. A. Royer
December 29, 2021

Pathogenicity Prediction of Single Amino Acid Variants with Machine Learning Model Based on Protein Structural Energies.

IEEE/ACM Transactions on Computational Biology and Bioinformatics
Tzu-Hsuan WuSun-Yuan Hsieh
December 28, 2021

Generating novel molecule for target protein (SARS-CoV-2) using drug-target interaction based on graph neural network.

Network Modeling and Analysis in Health Informatics and Bioinformatics
Amit RanjanRajiv Misra
December 23, 2021
Preprint
Open Access

Machine learning guided design of high affinity ACE2 decoys for SARS-CoV-2 neutralization

BioRxiv : the Preprint Server for Biology
M. ChanDiwakar Shukla
December 20, 2021
Review

Forty years of directed evolution and its continuously evolving technology toolbox: A review of the patent landscape.

Biotechnology and Bioengineering
Zarina Iqbal, Saima Sadaf
December 14, 2021

MUfoldQA_G: High-accuracy protein model QA via retraining and transformation.

Computational and Structural Biotechnology Journal
Wenbo WangYi Shang
December 11, 2021
Open Access

Predicting deleterious missense genetic variants via integrative supervised nonnegative matrix tri-factorization.

Scientific Reports
Asieh Amousoltani AraniMohammad Amin Tabatabaiefar
December 9, 2021

Updated Prediction of Aggregators and Assay-Interfering Substructures in Food Compounds.

Journal of Agricultural and Food Chemistry
Andres Sanchez-Ruiz, Gonzalo Colmenarejo
December 9, 2021
Preprint
Open Access

Heterogeneity of the GFP fitness landscape and data-driven protein design

BioRxiv : the Preprint Server for Biology
L. Gonzalez SomermeyerFyodor Kondrashov
December 1, 2021

Molecular Simulations of Intrinsically Disordered Proteins and Their Binding Mechanisms.

Methods in Molecular Biology
Xiakun ChuVictor Muñoz
December 1, 2021

An effective model for predicting serum albumin level in hemodialysis patients.

Computers in Biology and Medicine
Jiao HuHamza Turabieh
November 25, 2021
Preprint
Open Access

Updated Prediction of Aggregators and Assay Interfering Substructures in Food Compounds

ChemRxiv
Andres Sanchez-Ruiz, Gonzalo Colmenarejo
November 25, 2021

Protein-ligand binding affinity prediction model based on graph attention network.

Mathematical Biosciences and Engineering : MBE
Hong YuanJin Li

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