AI Medical Compendium Topic:
Amino Acid Sequence

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MoRFPred-plus: Computational Identification of MoRFs in Protein Sequences using Physicochemical Properties and HMM profiles.

Journal of theoretical biology
MOTIVATION: Intrinsically Disordered Proteins (IDPs) lack stable tertiary structure and they actively participate in performing various biological functions. These IDPs expose short binding regions called Molecular Recognition Features (MoRFs) that p...

SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides.

BMC genomics
BACKGROUND: Cell-penetrating peptides (CPPs) are short peptides (5-30 amino acids) that can enter almost any cell without significant damage. On account of their high delivery efficiency, CPPs are promising candidates for gene therapy and cancer trea...

The Thermodynamic Basis of the Fuzzy Interaction of an Intrinsically Disordered Protein.

Angewandte Chemie (International ed. in English)
Many intrinsically disordered proteins (IDP) that fold upon binding retain conformational heterogeneity in IDP-target complexes. The thermodynamics of such fuzzy interactions is poorly understood. Herein we introduce a thermodynamic framework, based ...

DRREP: deep ridge regressed epitope predictor.

BMC genomics
INTRODUCTION: The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been nume...

Bi-PSSM: Position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins.

Journal of theoretical biology
Mycobacterium is a pathogenic bacterium, which is a causative agent of tuberculosis (TB) and leprosy. These diseases are very crucial and become the cause of death of millions of people every year in the world. So, the characterize structure of membr...

Predicting the helix-helix interactions from correlated residue mutations.

Proteins
Helix-helix interactions are crucial in the structure assembly, stability and function of helix-rich proteins including many membrane proteins. In spite of remarkable progresses over the past decades, the accuracy of predicting protein structures fro...

Prediction of N-linked glycosylation sites using position relative features and statistical moments.

PloS one
Glycosylation is one of the most complex post translation modification in eukaryotic cells. Almost 50% of the human proteome is glycosylated as glycosylation plays a vital role in various biological functions such as antigen's recognition, cell-cell ...

Machine Learning on Signal-to-Noise Ratios Improves Peptide Array Design in SAMDI Mass Spectrometry.

Analytical chemistry
Emerging peptide array technologies are able to profile molecular activities within cell lysates. However, the structural diversity of peptides leads to inherent differences in peptide signal-to-noise ratios (S/N). These complex effects can lead to p...

Prediction of lysine propionylation sites using biased SVM and incorporating four different sequence features into Chou's PseAAC.

Journal of molecular graphics & modelling
Lysine propionylation is an important and common protein acylation modification in both prokaryotes and eukaryotes. To better understand the molecular mechanism of propionylation, it is important to identify propionylated substrates and their corresp...

Knowledge-transfer learning for prediction of matrix metalloprotease substrate-cleavage sites.

Scientific reports
Matrix Metalloproteases (MMPs) are an important family of proteases that play crucial roles in key cellular and disease processes. Therefore, MMPs constitute important targets for drug design, development and delivery. Advanced proteomic technologies...