Computational drug development for membrane protein targets

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Cyclic peptides are attractive for drug discovery due to their excellent binding properties and the potential to cross cell membranes. However, by far not all cyclic peptides are cell permeable, and measuring or predicting their membrane permeability is no ...

Proteins are the molecular machines of life, driving essential biological processes such as enzymatic catalysis, cellular signaling, and immune responses. The ability to design entirely new proteins with desired structures and functions has immense implica ...

The process of protein aggregation, central to neurodegenerative diseases like Huntington’s, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in disease ...

Data augmentation is vital in deep learning for enhancing model robustness by artificially expanding training datasets. However, advanced methods like CutMix blend images and assign labels based on pixel ratios, often introducing label noise by neglecting ...

Apoptosis controls cell fate, ensuring tissue homeostasis and promoting disease when dysregulated. The rate-limiting step in apoptosis is mitochondrial poration by the effector B cell lymphoma 2 (BCL-2) family proteins BAK and BAX, which are activated by i ...

Motivation Many machine learning (ML) models developed to classify phenotype from gene expression data provide interpretations for their decisions, with the aim of understanding biological processes. For many models, including neural networks, interpretati ...

Living photovoltaics are microbial electrochemical devices that use whole cell–electrode interactions to convert solar energy to electricity. The bottleneck in these technologies is the limited electron transfer between the microbe and the electrode surfac ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

Endoplasmic reticulum (ER) retention of misfolded glycoproteins is mediated by the ER-localized eukaryotic glycoprotein secretion checkpoint, UDP-glucose glycoprotein glucosyl-transferase (UGGT). The enzyme recognizes a misfolded glycoprotein and flags it ...

Over the past two decades, protein S-acylation (often referred to as S-palmitoylation) has emerged as an important regulator of vital signalling pathways. S-Acylation is a reversible post-translational modification that involves the attachment of a fatty a ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

Cyclic peptides are fascinating molecules abundantly found in nature and exploited as molecular format for drug development as well as other applications, ranging from research tools to food additives. Advances in peptide technologies made over many years ...

Post-translational modifications (PTMs) play a pivotal role in regulating protein structure, interaction, and function. Aberrant PTM patterns are associated with diseases. Moreover, individual PTMs have a complex interaction with each other, known as PTM c ...

The remarkable adaptability observed in marine ecosystems has often inspired researchers when developing new soft materials. The research undertaken in this thesis explores how ion chelator pair interactions influence the mechanical properties of bioinspir ...

The phenomenon of allostery, a general property in proteins that has been heralded as "the second secret of life" remains elusive to our understanding and even more challenging to incorporate into protein design. One example of allosteric proteins with gre ...

This study combined protein modeling methods to generate the prolamins' fractions as precise as possible. Hence, gliadins, zeins, kafirins, hordeins, secalins, avenins and oryzins were generated based on their characteristics and disulfide mapping. Finding ...

Atomic force microscopy (AFM) is a widely used imaging tool for obtaining a variety of information for a range of samples. Although it was initially intended to serve as a method of observing very flat solid surfaces, its use expanded into several other fi ...

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Networks of tryptophan (Trp)& horbar;an aromatic amino acid with strong fluorescence response & horbar;are ubiquitous in biological systems, forming diverse architectures in transmembrane proteins, cytoskeletal filaments, subneuronal elements, photorecepto ...

Computational drug development for membrane protein targets

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Bulk measurement of membrane permeability for random cyclic peptides in living cells to guide drug development

Computational design of complex protein folds and soluble analogs of membrane proteins

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging

SaliencyMix plus : Noise-Minimized Image Mixing Method With Saliency Map in Data Augmentation

Structural basis of BAK sequestration by MCL-1 in apoptosis

A comparative analysis of gene expression profiling by statistical and machine learning approaches

Polydopamine-coated photoautotrophic bacteria for improving extracellular electron transfer in living photovoltaics

Machine learning-aided generative molecular design

Live-cell imaging powered by computation

Rescue of secretion of rare-disease-associated misfolded mutant glycoproteins in UGGT1 knock-out mammalian cells

Mechanisms and functions of protein S-acylation

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Cyclic Peptides for Drug Development

Investigating the intra-molecular and inter-molecular effects of post-translational modifications on intrinsically disordered protein regions and structured protein regions

From Surfactants to 3D Printing: How Ion-Chelator Pair Interactions Affect the Mechanical Properties of Bioinspired Materials

From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Prolamins' 3D structure: A new insight into protein modeling using the language of numbers and shapes

Advancements in Nanomechanical Characterization and Biomolecular Imaging with Atomic force Microscopy

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Ultraviolet Superradiance from Mega-Networks of Tryptophan in Biological Architectures