Membrane proteinKurtosisHydrophobicityPredictionTransmembrane helixPrediction of the transmembrane (TM) helices is important in the study of membrane proteins. A novel method to predict the location and length of both single and multiple TM helices in human proteins is presented. The proposed method is ...
Transmembrane (TM) proteins comprise 20–30% of the genome but, because of experimental difficulties, they represent less than 1% of the Protein Data Bank. The dearth of membrane protein structures makes computational prediction a potentially important means of obtaining novel structures. Recent advance...
Motivated by the success of intra-protein contact predictions in monomer structure prediction26,27,28, various advanced deep learning methods have been developed to predict the inter-chain contacts for protein complexes29,30,31,32,33,34,35,36,37,38,39,40. Our previous work, DeepHomo29, utiliz...
Here, we present a database of the human α-helical transmembrane proteome, including the predicted and/or experimentally established topology of each transmembrane protein, together with the reliability of the prediction. In order to distinguish transmembrane proteins in the proteome as well as for t...
We show that reliable identification of extracellular protein segments increases the accuracy and reliability of existing topology prediction algorithms. Using the experimental topology data as constraints, our improved prediction tool provides accurate and reliable topology models for hundreds of human ...
Those in our eyes are not negatively affect- ing AF2 predictions and were thus not considered as an issue, since the localization of disordered regions also can- not be trusted in the case of AF2-predicted soluble protein structures. Prediction of challenging and novel transmembrane folds ...
The crystal and cryogenic electron microscopy structures of the designer protein–ligand complexes were very close to the structures of the design models. We showed that the interactions between ligands and transmembrane proteins within the membrane can be accurately designed. Our work paves the way ...
Further, the paper introduces a novel method of extracting features from protein sequence, namely that of latent semantic analysis model. Most methods for transmembrane helix prediction capture amino acid propensities through single numbers (as in hydrophobicity scales) or probability distributions (as in...
3. Elofsson A, vonHeijne G: Membrane Protein Structure: Prediction vs Reality. Annu Rev Biochem 2007, 76:125-140. 4. Filipek S, Teller DC, Palczewski K, Stenkamp R: The crystallographic model of rhodopsin and its use in studies of other G protein-coupled receptors. Annu Rev Biophys ...
The alpha transmembrane region prediction tool is a data-driven model based on a counter-propagation neural network (CPNN) classifier built using transmembrane and non-transmembrane protein segments, which are characterized mathematically using amino acid adjacency matrix. The developed classifier shows ...