Progress on the development of prediction tools for detecting disease causing mutations in proteins.

Proteins are involved in a variety of functions in living organisms. The mutation of amino acid residues in a protein alters its structure, stability, binding, and function, with some mutations leading to diseases. Understanding the influence of mutations on protein structure and function help to gain deep insights on the molecular mechanism of diseases and devising therapeutic strategies.

MPA-MutPred: a novel strategy for accurately predicting the binding affinity change upon mutation in membrane protein complexes.

Mutations in the interface of membrane protein (MP) complexes are key contributors to a broad spectrum of human diseases, primarily due to changes in their binding affinities. While various methods exist for predicting the mutation-induced changes in binding affinity (ΔΔG) in protein-protein complexes, none are specific to MP complexes. This study proposes a novel strategy for ΔΔG prediction in MP complexes, which combines linear and nonlinear models, to obtain a more robust model with improved prediction accuracy.

Prevalence of Voice Problems and Associated Risk Factors in Islamic Religious Orators.

Islamic leadership is a diverse profession and previous research has highlighted the increased risk of voice problems among Islamic leaders. The prevalence and risk factors for voice problems among Malayalam-speaking Islamic religious orators have not been adequately investigated. This study aimed to assess the prevalence of self-reported voice problems among Islamic religious orators who recite the Adhaan and those who do not and to examine the impact of age and associated risk factors.

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

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 predicting the binding affinity of protein-protein complexes, there exists no specific method for membrane protein-protein complexes.

MPAD: A Database for Binding Affinity of Membrane Protein-protein Complexes and their Mutants.

Membrane protein complexes are crucial for a large variety of biological functions which are mainly dictated by their binding affinity. Due to the intricate nature of their structure, however, the binding affinity of membrane proteins is less explored compared to globular proteins. Mutations in these complexes affect their binding affinity, as well as impair critical functions, and may lead to diseases.

Computational Approaches for Investigating Disease-causing Mutations in Membrane Proteins: Database Development, Analysis and Prediction.

Membrane proteins (MPs) play an essential role in a broad range of cellular functions, serving as transporters, enzymes, receptors, and communicators, and about ~60% of membrane proteins are primarily used as drug targets. These proteins adopt either α-helical or β-barrel structures in the lipid bilayer of a cell/organelle membrane. Mutations in membrane proteins alter their structure and function, and may lead to diseases.

Ab-CoV: a curated database for binding affinity and neutralization profiles of coronavirus-related antibodies.

Summary: We have developed a database, Ab-CoV, which contains manually curated experimental interaction profiles of 1780 coronavirus-related neutralizing antibodies. It contains more than 3200 datapoints on half maximal inhibitory concentration (IC50), half maximal effective concentration (EC50) and binding affinity (KD). Each data with experimentally known three-dimensional structures are complemented with predicted change in stability and affinity of all possible point mutations of interface residues.