The PUXANO technology platforms aim to accelerate structure-based protein research, from sequence to structure
Given that we are classifying individual protein graphs with different number of residues, we use several layers,Nl = 3, of graph convolutions. The final protein representation is obtained by first concatenating features from all layers into a single feature matrix, i.e.,\({\bf{H}}=[{...
Naveed H., Han J. J. Structure-based protein-protein interaction networks and drug design. Quantitative Biology . 2013; 1 (3):183–191.Naveed H, Han J J. Structure-based protein-protein interaction networks and drug design. Quantitative Biology , 2013, 1(3): 183–191....
Predicting the functional sites of a protein from its structure, such as the binding sites of small molecules, other proteins or antibodies, sheds light on its function in vivo. Currently, two classes of methods prevail: machine learning models built on top of handcrafted features and comparative...
protein structure comparisonfold classificationA reduced representation in the format of a barcode has been developed to provide an overview of the topological nature of a given protein structure from 3D coordinate file. The molecular structure of a protein coordinate file from Protein Data Bank is ...
Recent developments in protein design rely on large neural networks with up to 100s of millions of parameters, yet it is unclear which residue dependencies are critical for determining protein function. Here, we show that amino acid preferences at indivi
论文地址: Enhancing Protein Language Models with Structure-based Encoder and Pre-training 看完GearNet再看这篇文章,其实就是加了一个语言模型在结构编码器前面,并且做预训练的时候fix语言模型。 GearNet记录:nlinp:《Protein Representation Learning by Geometric Structure Pretraining》阅读记录 摘要 蛋白质语言模...
Protein engineering based on structure homology holds the potential to engineer steroid-transforming enzymes on demand. Based on the genome sequencing analysis of industrial Mycobacterium strain HGMS2 to produce 4-androstene-3,17-dione (4-AD), three hypothetical proteins were predicted as putative Δ...
A two-stage neural network has been used to predict protein secondary structure based on the position specific scoring matrices generated by PSI-BLAST. Despite the simplicity and convenience of the approach used, the results are found to be superior to those produced by other methods, including th...
Introduction to structural bioinformatics, protein structure, sequence alignment and homology modeling & structure-based drug design (SBDD)