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Membrane Proteins

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Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches.

International journal of molecular sciences
Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the design of compounds of therapeutic interest. However, the identification of binding sites on protei...

Efficient Generation of Paired Single-Cell Multiomics Profiles by Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Recent advances in single-cell sequencing technology have made it possible to measure multiple paired omics simultaneously in a single cell such as cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-nucleus chromatin...

Neural potentials of proteins extrapolate beyond training data.

The Journal of chemical physics
We evaluate neural network (NN) coarse-grained (CG) force fields compared to traditional CG molecular mechanics force fields. We conclude that NN force fields are able to extrapolate and sample from unseen regions of the free energy surface when trai...

Disclosing the locale of transmembrane proteins within cellular alcove by machine learning approach: systematic review and meta analysis.

Journal of biomolecular structure & dynamics
Protein subcellular localization is a promising research question in Proteomics and associated fields, including Biological Sciences, Biomedical Engineering, Computational Biology, Bioinformatics, Proteomics, Artificial Intelligence, and Biophysics. ...

PortPred: Exploiting deep learning embeddings of amino acid sequences for the identification of transporter proteins and their substrates.

Journal of cellular biochemistry
The physiology of every living cell is regulated at some level by transporter proteins which constitute a relevant portion of membrane-bound proteins and are involved in the movement of ions, small and macromolecules across bio-membranes. The importa...

Integrating Pre-Trained protein language model and multiple window scanning deep learning networks for accurate identification of secondary active transporters in membrane proteins.

Methods (San Diego, Calif.)
Secondary active transporters play pivotal roles in regulating ion and molecule transport across cell membranes, with implications in diseases like cancer. However, studying transporters via biochemical experiments poses challenges. We propose an eff...

Exploring the World of Membrane Proteins: Techniques and Methods for Understanding Structure, Function, and Dynamics.

Molecules (Basel, Switzerland)
In eukaryotic cells, membrane proteins play a crucial role. They fall into three categories: intrinsic proteins, extrinsic proteins, and proteins that are essential to the human genome (30% of which is devoted to encoding them). Hydrophobic interacti...

MPA-Pred: A machine learning approach for predicting the binding affinity of membrane protein-protein complexes.

Proteins
Membrane protein-protein interactions are essential for several functions including cell signaling, ion transport, and enzymatic activity. These interactions are mainly dictated by their binding affinities. Although several methods are available for ...

Prediction of interactions between cell surface proteins by machine learning.

Proteins
Cells detect changes in their external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions betwee...

ProteinMAE: masked autoencoder for protein surface self-supervised learning.

Bioinformatics (Oxford, England)
SUMMARY: The biological functions of proteins are determined by the chemical and geometric properties of their surfaces. Recently, with the booming progress of deep learning, a series of learning-based surface descriptors have been proposed and achie...