AIMC Topic: Databases, Protein

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Machine learning classification can reduce false positives in structure-based virtual screening.

Proceedings of the National Academy of Sciences of the United States of America
With the recent explosion in the size of libraries available for screening, virtual screening is positioned to assume a more prominent role in early drug discovery's search for active chemical matter. In typical virtual screens, however, only about 1...

Molecular docking and machine learning analysis of Abemaciclib in colon cancer.

BMC molecular and cell biology
BACKGROUND: The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is personalised opens the doors to the design ...

Protein-Protein Interactions Efficiently Modeled by Residue Cluster Classes.

International journal of molecular sciences
Predicting protein-protein interactions (PPI) represents an important challenge in structural bioinformatics. Current computational methods display different degrees of accuracy when predicting these interactions. Different factors were proposed to h...

Identification of ligand-binding residues using protein sequence profile alignment and query-specific support vector machine model.

Analytical biochemistry
Information embedded in ligand-binding residues (LBRs) of proteins is important for understanding protein functions. How to accurately identify the potential ligand-binding residues is still a challenging problem, especially only protein sequence is ...

IConMHC: a deep learning convolutional neural network model to predict peptide and MHC-I binding affinity.

Immunogenetics
Tumor-specific neoantigens are mutated self-peptides presented by tumor cell major histocompatibility complex (MHC) molecules and are necessary to elicit host's anti-cancer cytotoxic T cell responses. It could be specifically recognized by neoantigen...

DEEPSMP: A deep learning model for predicting the ectodomain shedding events of membrane proteins.

Journal of bioinformatics and computational biology
Membrane proteins play essential roles in modern medicine. In recent studies, some membrane proteins involved in ectodomain shedding events have been reported as the potential drug targets and biomarkers of some serious diseases. However, there are f...

CoRNeA: A Pipeline to Decrypt the Inter-Protein Interfaces from Amino Acid Sequence Information.

Biomolecules
Decrypting the interface residues of the protein complexes provides insight into the functions of the proteins and, hence, the overall cellular machinery. Computational methods have been devised in the past to predict the interface residues using ami...

Exploring the mechanism of TCM formulae in the treatment of different types of coronary heart disease by network pharmacology and machining learning.

Pharmacological research
Traditional Chinese medicine (TCM) has long been used in the clinical treatment of coronary heart disease (CHD). TCM is characterized by syndrome-based medication, which is, using different TCM formulae for different syndromes. However, the underlyin...

Prediction of Protein-Protein Interactions with Local Weight-Sharing Mechanism in Deep Learning.

BioMed research international
Protein-protein interactions (PPIs) are important for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. The experimental methods for identifying PPIs are always time-consuming and ex...