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.

Engineering the defects of UiO-66 MOF for an improved catalytic detoxification of CWA simulant: methyl paraoxon.

Exigency in search of an ideal candidate for an effective detoxification of chemical warfare agents is still continuing. Zirconium-based Metal-organic Framework (MOF) UiO-66 has shown a significant detoxification of such toxic chemicals owing to its tunable physio-chemical properties and profuse catalytic sites. In this context, a series of UiO-66 MOFs synthesized by tuning the acidity constant (p ) and concentration of the modulator, synthesis temperature and water molecules was tested for their detoxification efficiency against the simulant 'methyl-paraoxon' at room temperature.

MOFabric: an effective and wearable protective garment towards CWA detoxification.

In current trends, an imminent development of self-detoxification filters is highly desirable against exposure to chemical warfare agents (CWAs). Exploiting protective materials that can be applicable in day-to-day life for instantaneous detoxification will be of immense importance. The available technologies in the current scenario are susceptible to secondary emission and pose a need for an alternate design strategy for effective degradation.

CarbDisMut: database on neutral and disease-causing mutations in human carbohydrate-binding proteins.

Protein-carbohydrate interactions are involved in several cellular and biological functions. Integrating structure and function of carbohydrate-binding proteins with disease-causing mutations help to understand the molecular basis of diseases. Although databases are available for protein-carbohydrate complexes based on structure, binding affinity and function, no specific database for mutations in human carbohydrate-binding proteins is reported in the literature.

TMKit: a Python interface for computational analysis of transmembrane proteins.

Transmembrane proteins are receptors, enzymes, transporters and ion channels that are instrumental in regulating a variety of cellular activities, such as signal transduction and cell communication. Despite tremendous progress in computational capacities to support protein research, there is still a significant gap in the availability of specialized computational analysis toolkits for transmembrane protein research. Here, we introduce TMKit, an open-source Python programming interface that is modular, scalable and specifically designed for processing transmembrane protein data.

TMH Stab-pred: Predicting the stability of α-helical membrane proteins using sequence and structural features.

The folding and stability of transmembrane proteins (TMPs) are governed by the insertion of secondary structural elements into the cell membrane followed by their assembly. Understanding the important features that dictate the stability of TMPs is important for elucidating their functions. In this work, we related sequence and structure-based parameters with free energy (ΔG) of α-helical membrane proteins.

Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications.

Membrane proteins mediate a wide spectrum of biological processes, such as signal transduction and cell communication. Due to the arduous and costly nature inherent to the experimental process, membrane proteins have long been devoid of well-resolved atomic-level tertiary structures and, consequently, the understanding of their functional roles underlying a multitude of life activities has been hampered. Currently, computational tools dedicated to furthering the structure-function understanding are primarily focused on utilizing intelligent algorithms to address a variety of site-wise prediction problems (e.

Iron Oxide Nanoparticles: A Review on the Province of Its Compounds, Properties and Biological Applications.

Materials science and technology, with the advent of nanotechnology, has brought about innumerable nanomaterials and multi-functional materials, with intriguing yet profound properties, into the scientific realm. Even a minor functionalization of a nanomaterial brings about vast changes in its properties that could be potentially utilized in various applications, particularly for biological applications, as one of the primary needs at present is for point-of-care devices that can provide swifter, accurate, reliable, and reproducible results for the detection of various physiological conditions, or as elements that could increase the resolution of current bio-imaging procedures. In this regard, iron oxide nanoparticles, a major class of metal oxide nanoparticles, have been sweepingly synthesized, characterized, and studied for their essential properties; there are 14 polymorphs that have been reported so far in the literature.

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.

Exploring Plausible Therapeutic Targets for Alzheimer's Disease using Multi-omics Approach, Machine Learning and Docking.

The progressive deterioration of neurons leads to Alzheimer's disease (AD), and developing a drug for this disorder is challenging. Substantial gene/transcriptome variability from multiple cell types leads to downstream pathophysiologic consequences that represent the heterogeneity of this disease. Identifying potential biomarkers for promising therapeutics is strenuous due to the fact that the transcriptome, epigenetic, or proteome changes detected in patients are not clear whether they are the cause or consequence of the disease, which eventually makes the drug discovery efforts intricate.

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.

Halogen-Based 17β-HSD1 Inhibitors: Insights from DFT, Docking, and Molecular Dynamics Simulation Studies.

The high expression of 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) mRNA has been found in breast cancer tissues and endometriosis. The current research focuses on preparing a range of organic molecules as 17β-HSD1 inhibitors. Among them, the derivatives of hydroxyphenyl naphthol steroidomimetics are reported as one of the potential groups of inhibitors for treating estrogen-dependent disorders.

Alz-Disc: A Tool to Discriminate Disease-causing and Neutral Mutations in Alzheimer's Disease.

Background: Alzheimer's disease (AD) is the most common neurodegenerative disorder that affects the neuronal system and leads to memory loss. Many coding gene variants are associated with this disease and it is important to characterize their annotations.

Methods: We collected the Alzheimer's disease-causing and neutral mutations from different databases.

Illustrative Tutorials for ProThermDB: Thermodynamic Database for Proteins and Mutants.

ProThermDB (https://web.iitm.ac.

Synthesis, biological-pharmacological evaluation and molecular docking studies of Schiff base analogues of transition metal (II) complexes of 4-amino-1,5-dimethyl-2-phenylpyrazol-3-one.

Novel tridentate Schiff base [CuL], [NiL], [CoL], [MnL] and [ZnL] complexes have been prepared with Schiff base resulting from acetophenylidene-4-iminoantipyrine and tyrosine. Microanalytical data, IR, UV-vis, H, C-NMR, powder XRD, SEM, cyclic voltammetry, ESR, and mass spectral techniques confirmed the structural features of the chelates. The general formula of the complexes [ML] was confirmed from elemental analysis, mass and H-NMR spectral studies.

ProNAB: database for binding affinities of protein-nucleic acid complexes and their mutants.

Protein-nucleic acid interactions are involved in various biological processes such as gene expression, replication, transcription, translation and packaging. The binding affinities of protein-DNA and protein-RNA complexes are important for elucidating the mechanism of protein-nucleic acid recognition. Although experimental data on binding affinity are reported abundantly in the literature, no well-curated database is currently available for protein-nucleic acid binding affinity.

Synthesis, structural, pharmacological and molecular docking simulations studies of Schiff base transition metal complexes procured from acetylacetonyl-4-iminoantipyrine and tyrosine.

Schiff base complexes of Cu(II), Ni(II), Co(II), VO(II) and Zn(II) ions have been synthesized by condensation of acetylaceto-4-iminoantipyrine and tyrosine. The structural characterization of compounds has been investigated using elemental analysis, molar conductance and magnetic susceptibility measurements, UV-Vis., FT-IR, ESI-mass, H-NMR, C-NMR, ESR spectroscopy, cyclic voltammetry, XRD and SEM techniques.

ProThermDB: thermodynamic database for proteins and mutants revisited after 15 years.

ProThermDB is an updated version of the thermodynamic database for proteins and mutants (ProTherm), which has ∼31 500 data on protein stability, an increase of 84% from the previous version. It contains several thermodynamic parameters such as melting temperature, free energy obtained with thermal and denaturant denaturation, enthalpy change and heat capacity change along with experimental methods and conditions, sequence, structure and literature information. Besides, the current version of the database includes about 120 000 thermodynamic data obtained for different organisms and cell lines, which are determined by recent high throughput proteomics techniques using whole-cell approaches.

A non-enzymatic electrochemical biosensor for the detection of formalin levels in fishes: Realization of a novel comparator effect based on electrolyte.

Formalin has been used as the preservative of fishes in the concentration range of 15-25 mgL. However, there have been a high frequency of violations in the optimum use of formalin levels. The consumption of fishes treated with excessive formalin levels leads to nasopharynx, leukaemia and sinonasal cancer and there is a huge demand for the development of formalin sensor.

MPTherm-pred: Analysis and Prediction of Thermal Stability Changes upon Mutations in Transmembrane Proteins.

The stability of membrane proteins differs from globular proteins due to the presence of nonpolar membrane-spanning regions. Using a dataset of 929 membrane protein mutations whose effects on thermal stability (ΔT) were experimentally determined, we found that the average ΔT due to 190 stabilizing and 232 destabilizing mutations occurring in membrane-spanning regions are 2.43(3.

Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins.

Membrane proteins are unique in that they interact with lipid bilayers, making them indispensable for transporting molecules and relaying signals between and across cells. Due to the significance of the protein's functions, mutations often have profound effects on the fitness of the host. This is apparent both from experimental studies, which implicated numerous missense variants in diseases, as well as from evolutionary signals that allow elucidating the physicochemical constraints that intermembrane and aqueous environments bring.

MPTherm: database for membrane protein thermodynamics for understanding folding and stability.

The functions of membrane proteins (MPs) are attributed to their structure and stability. Factors influencing the stability of MPs differ from globular proteins due to the presence of membrane spanning regions. Thermodynamic data of MPs aid to understand the relationship among their structure, stability and function.

Pred-MutHTP: Prediction of disease-causing and neutral mutations in human transmembrane proteins.

Membrane proteins are unique in that segments thereof concurrently reside in vastly different physicochemical environments: the extracellular space, the lipid bilayer, and the cytoplasm. Accordingly, the effects of missense variants disrupting their sequence depend greatly on the characteristics of the environment of the protein segment affected as well as the function it performs. Because membrane proteins have many crucial roles (transport, signal transduction, cell adhesion, etc.

Development of an acetone sensor using nanostructured CoO thin films for exhaled breath analysis.

In recent times, the development of breath sensors for the detection of Diabetic Keto-Acidosis (DKA) has been gaining prominent importance in the field of health care and advanced diagnostics. Acetone is one of the prominent biomarkers in the exhaled breath of persons affected by DKA. In this background, nanostructured cobalt oxide sensing elements were fabricated using a spray pyrolysis technique at different deposition temperatures (473 to 773 K in steps of 100 K) towards the fabrication of an acetone sensor.