Although deep learning has transformed protein structure prediction, the controlled generation of functional and experimentally tractable protein structures remains a major challenge in structural bioinformatics. Diffusion models offer a versatile ap...
Isoflavonoid synthase (IFS) is a critical enzyme for the biosynthesis of over 2400 isoflavonoids. Isoflavonoids are an important class of plant secondary metabolites that have a range of pharmaceutical and nutraceutical properties. With growing inter...
Protein–protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning...
The interaction between proteins and polyphenols is known to modify both the bioavailability and bioactivity of dietary polyphenols. Understanding these interactions can facilitate the design of delivery systems for polyphenols in the digestive tract...
We used the PACSAB protein model, based on the implicit solvation approach, to simulate protein–protein recognition and study the effect of helical structure on the association of aggregating peptides. After optimization, the PACSAB force field...
Derived from the natural language processing (NLP) algorithms, protein language models enable the encoding of protein sequences, which are widely diverse in length and amino acid composition, in fixed-size numerical vectors (embeddings). We surveyed...
The signaling of cytokinins (CKs), classical plant hormones, is based on the interaction of proteins that constitute the multistep phosphorelay system (MSP): catalytic receptors—sensor histidine kinases (HKs), phosphotransmitters (HPts), and tr...
We study self-association of ubiquitin and the disordered protein ACTR using the most commonly used water models. We find that dissociation events are found only with TIP4P-EW and TIP4P/2005, while the widely used TIP3P water model produces straightf...
The prediction of protein–protein interactions is a key task in proteomics. Since protein sequences are easily available and understandable, they have become the primary data source for predicting protein–protein interactions. With the de...
The insulin signalling system is one of the most conserved endocrine systems of Animalia from mollusc to man. In decapod Crustacea, such as the Eastern spiny lobster, Sagmariasus verreauxi (Sv) and the red-claw crayfish, Cherax quadricarinatus (Cq),...
A downward trend in animal protein (AP) intake has been observed in western countries over the last decade and the effects of such a transition on protein adequacy remain debatable. Using the probability approach and diet modeling with data on 1678 a...
Many life activities and key functions in organisms are maintained by different types of protein–protein interactions (PPIs). In order to accelerate the discovery of PPIs for different species, many computational methods have been developed. Un...
Despite the recent advances in the prediction of protein structures by deep neutral networks, the elucidation of protein-folding mechanisms remains challenging. A promising theory for describing protein folding is a coarse-grained statistical mechani...
Diverse phylogenetic methods require a substitution model of evolution that should mimic, as accurately as possible, the real substitution process. At the protein level, empirical substitution models have traditionally been based on a large number of...
Human microsomal triglyceride transfer protein (hMTP) plays an essential role in the assembly of apoB-containing lipoproteins, and has become an important drug target for the treatment of several disease states, such as abetalipoproteinemia, fat mala...
Protein–peptide interactions (PpIs) are a subset of the overall protein–protein interaction (PPI) network in the living cell and are pivotal for the majority of cell processes and functions. High-throughput methods to detect PpIs and PPIs...
Protein function prediction plays a crucial role in uncovering the molecular mechanisms underlying life processes in the post-genomic era. However, with the widespread adoption of high-throughput sequencing technologies, the pace of protein function...
Protein–protein and protein–peptide interactions are fundamental to biological processes, making the accurate prediction of their binding affinity crucial for drug design and mutational analysis. Here, we develop HyBind-NN, a multimodal g...
Methods such as AlphaFold have revolutionized protein structure prediction, making quantitative prediction of the thermodynamic stability of individual proteins and their complexes one of the next frontiers in computational protein modeling. Here, we...
Protein and nucleic acid binding site prediction is a critical computational task that benefits a wide range of biological processes. Previous studies have shown that feature selection holds particular significance for this prediction task, making th...
6 April 2023
Transmembrane proteins (TMPs) are a class of essential proteins for biological and therapeutic purposes. Despite an increasing number of structures, the gap with the number of available sequences remains impressive. The choice of a dedicated function...
Unlike the secondary structure elements that connect in protein structures, loop fragments in protein chains are often highly mobile even in generally stable proteins. The structural variability of loops is often at the center of a protein’s stabilit...
The quality prediction of quaternary structure models of a protein complex, in the absence of its true structure, is known as the Estimation of Model Accuracy (EMA). EMA is useful for ranking predicted protein complex structures and using them approp...
In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many...
Hypergraphs, a generalisation of traditional graphs in which hyperedges may connect more than two vertices, provide a natural framework for modeling higher-order interactions in complex biological systems. In the context of protein complexes, hypergr...
Accurate prediction of protein function is fundamental to progress in biotechnology and biomedicine, yet progress remains severely hampered by the widening chasm between exponentially growing genomic data and the limited capacity for functional annot...
Autophagy critically regulates cellular development while maintaining pathophysiological homeostasis. Since the autophagic process is tightly regulated by the coordination of autophagy-related proteins (ATGs), precise identification of these proteins...
The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great appl...
O-linked β-N-acetylglucosamine (O-GlcNAc) is a distinct monosaccharide modification of serine (S) or threonine (T) residues of nucleocytoplasmic and mitochondrial proteins. O-GlcNAc modification (i.e., O-GlcNAcylation) is involved in the regulat...
Proteins are dynamic macromolecules whose functions are intricately linked to their structural flexibility. Recent breakthroughs in deep learning have enabled accurate prediction of static protein structures. However, understanding protein function i...
Ranking protein structure models is an elusive problem in bioinformatics. These models are evaluated on both the degree of similarity to the native structure and the folding pathway. Here, we simulated the use of the coarse-grained UNited RESidue (UN...
The fusion of viral and cell membranes is one of the basic processes in the life cycles of viruses. A number of enveloped viruses confer fusion of the viral envelope and the cell membrane using surface viral fusion proteins. Their conformational rear...
The description of protein disordered states is important for understanding protein folding mechanisms and their functions. In this short review, we briefly describe a simulation approach to modeling protein interactions, which involve disordered pep...
The human immunodeficiency virus (HIV) remains a major global health challenge. A promising therapeutic strategy involves identifying human proteins capable of physically blocking viral entry by interacting with key components of the HIV attachment s...
Proteins are the foundation of life, and designing functional proteins remains a key challenge in biotechnology. Before the development of AlphaFold2, the focus of design was primarily on structure-centric approaches such as using the well-known open...
The factors that determine the relative rates of amino acid substitution during protein evolution are complex and known to vary among taxa. We estimated relative exchangeabilities for pairs of amino acids from clades spread across the tree of life an...
Currently, protein–protein interaction (PPI) networks have become an essential data source for protein function prediction. However, methods utilizing graph neural networks (GNNs) face significant challenges in modeling PPI networks. A primary...
Oomycete and fungal interactions with plants can be neutral, symbiotic or pathogenic with different impact on plant health and fitness. Both fungi and oomycetes can generate so-called effector proteins in order to successfully colonize the host plant...
Proteins are found in all living organisms and constitute a large group of macromolecules with many functions. Proteins achieve their operations by adopting distinct three-dimensional structures encoded within the sequence of the constituent amino ac...
Nanobodies have emerged as highly valuable biotherapeutic and diagnostic reagents due to their high specificity, low immunogenicity, and superior tissue penetration. However, traditional nanobody discovery methods rely on camelid immunization and pha...
Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore mole...
Systematic modeling of the enzymatic hydrolysis of milk proteins is needed to assist the study and production of partially hydrolyzed milk. The enzymatic hydrolysis of milk proteins was characterized and evaluated as a function of the temperature and...
Inhibition of fibril formation is considered a possible treatment strategy for amyloid-related diseases. Understanding the molecular nature of inhibitor action is crucial for the design of drug candidates. In the present review, we describe the commo...
To alter and adjust the shape of the plasma membrane, cells harness various mechanisms of curvature generation. Many of these curvature generation mechanisms rely on the interactions between peripheral membrane proteins, integral membrane proteins, a...
[Background] Cotton seed protein is an important seed quality trait with considerable utilization potential; however, the genetic mechanisms governing its developmental dynamics remain incompletely understood. [Methods] Field trials were conducted du...
Antioxidant proteins are involved importantly in many aspects of cellular life activities. They protect the cell and DNA from oxidative substances (such as peroxide, nitric oxide, oxygen-free radicals, etc.) which are known as reactive oxygen species...
The identification of druggable proteins has always been the core of drug development. Traditional structure-based identification methods are time-consuming and costly. As a result, more and more researchers have shifted their attention to sequence-b...
Hydration plays an essential role in protein–protein interactions. Coarse-grained modeling provides an efficient way to treat hydrated protein complexes without the use of extra-large computational resources. To enhance the capabilities of coar...
A probabilistic discrete model for 2D protein crystal growth is presented. This model takes into account the available space and can describe growing processes of a different nature due to the versatility of its parameters, which gives the model grea...
Differential Scanning Calorimetry (DSC) is a regular and powerful tool to measure the specific heat profile of various materials. In order to connect the measured profile to the properties of a particular protein, a model is required to fit. We discu...
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