Enhanced Protein-Protein Interaction Discovery via AlphaFold-Multimer

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Фев. 21, 2024

Abstract Accurately mapping protein-protein interactions (PPIs) is critical for elucidating cellular functions and has significant implications health disease. Conventional experimental approaches, while foundational, often fall short in capturing direct, dynamic interactions, especially those with transient or small interfaces. Our study leverages AlphaFold-Multimer (AFM) to re-evaluate high-confidence PPI datasets from Drosophila human. analysis uncovers a limitation of the AFM-derived interface pTM (ipTM) metric, which, reflective structural integrity, can miss physiologically relevant at interfaces within flexible regions. To bridge this gap, we introduce Local Interaction Score (LIS), derived AFM’s Predicted Aligned Error (PAE), focusing on areas low PAE values, indicative high confidence interaction predictions. The LIS method demonstrates enhanced sensitivity detecting PPIs, particularly among that involve By applying large-scale datasets, enhance detection direct interactions. Moreover, present FlyPredictome, an online platform integrates our AFM-based predictions additional information such as gene expression correlations subcellular localization This not only improves upon utility prediction but also highlights potential computational methods complement approaches identification networks.

Язык: Английский

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New insights into protein–protein interaction modulators in drug discovery and therapeutic advance

Signal Transduction and Targeted Therapy, Год журнала: 2024, Номер 9(1)

Опубликована: Дек. 5, 2024

Abstract Protein-protein interactions (PPIs) are fundamental to cellular signaling and transduction which marks them as attractive therapeutic drug development targets. What were once considered be undruggable targets have become increasingly feasible due the progress that has been made over last two decades rapid technological advances. This work explores influence of innovations on PPI research development. Additionally, diverse strategies for discovering, modulating, characterizing PPIs their corresponding modulators examined with aim presenting a streamlined pipeline advancing PPI-targeted therapeutics. By showcasing carefully selected case studies in modulator discovery development, we illustrate efficacy various identifying, optimizing, overcoming challenges associated design. The valuable lessons insights gained from identification, optimization, approval discussed demonstrating transitioned beyond early-stage now represent prime opportunity significant potential. examples encompass those developed cancer, inflammation immunomodulation, well antiviral applications. perspective aims establish foundation effective targeting modulation using pave way future

Язык: Английский

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Large language models in bioinformatics: applications and perspectives

arXiv (Cornell University), Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Large language models (LLMs) are a class of artificial intelligence based on deep learning, which have great performance in various tasks, especially natural processing (NLP). typically consist neural networks with numerous parameters, trained large amounts unlabeled input using self-supervised or semi-supervised learning. However, their potential for solving bioinformatics problems may even exceed proficiency modeling human language. In this review, we will present summary the prominent used processing, such as BERT and GPT, focus exploring applications at different omics levels bioinformatics, mainly including genomics, transcriptomics, proteomics, drug discovery single cell analysis. Finally, review summarizes prospects bioinformatic problems.

Язык: Английский

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Decoding Plant–Pathogen Interactions: A Comprehensive Exploration of Effector–Plant Transcription Factor Dynamics

Molecular Plant Pathology, Год журнала: 2025, Номер 26(1)

Опубликована: Янв. 1, 2025

ABSTRACT In the coevolutionary process between plant pathogens and hosts, pathogen effectors, primarily proteinaceous, engage in interactions with host proteins, such as transcription factors (TFs), during infection process. This review delves into intricate interplay TFs a key aspect prolonged complex battle plants pathogens. Effectors strategically manipulate using diverse tactics. These include modulating activity of TFs, influencing their incorporation multimeric complexes, directly changing TF expression levels, promoting degradation via ubiquitin‐proteasome system, inducing subcellular relocalization. The systematically presents documented interactions, elucidating mechanisms profound impact on host–pathogen dynamics. It emphasises central role defence investigates convergent evolution effectors targeting TFs. By providing this overview, we offer valuable insights dynamic interaction landscape suggest potential directions for future research.

Язык: Английский

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Protein Recognition Methods for Diagnostics and Therapy

BBA Advances, Год журнала: 2025, Номер 7, С. 100149 - 100149

Опубликована: Янв. 1, 2025

The fundamental biological processes involving highly specific interactions between proteins and other motifs are the pillars of protein recognition mechanisms. These crucial for systems, often having significant implications within diagnostics therapy development. Protein specificity reliant on structural compatibility, dynamic conformational changes, biochemical interactions-all which grounded in molecular forces like hydrogen bonding, ionic interactions, van der Waals forces. Advanced characterization tools have improved our understanding revealing kinetics thermodynamics these In parallel, new computing methods, including artificial intelligence, docking, dynamical simulations, increased prediction accuracy leading to well-defined interaction sites binding information. is pivotal diagnostic methods ELISAs biosensors, disease detection applications. therapeutics, plays an important role drug development, enabling design small molecules, peptides, monoclonal antibodies. Despite recent progress, there many challenges remaining fully understand recognition, particularly complex cell environment. require future work studies enhance therapeutic researchers using screening identify, assess, optimize clinical translation.

Язык: Английский

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High throughput methods to study protein-protein interactions during host-pathogen interactions

European Journal of Cell Biology, Год журнала: 2024, Номер 103(2), С. 151393 - 151393

Опубликована: Янв. 24, 2024

The ability of a pathogen to survive and cause an infection is often determined by specific interactions between the host proteins. Such can be both intra- extracellular may define outcome infection. There are range innovative biochemical, biophysical bioinformatic techniques currently available identify protein-protein (PPI) pathogen. However, complexity diversity host-pathogen PPIs has led development several high throughput (HT) that enable study multiple at once and/or screen samples same time, in unbiased manner. We review here major HT laboratory-based technologies employed for host-bacterial interaction studies.

Язык: Английский

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Multi-tissue characterization of the constitutive heterochromatin proteome in Drosophila identifies a link between satellite DNA organization and transposon repression

PLoS Biology, Год журнала: 2025, Номер 23(1), С. e3002984 - e3002984

Опубликована: Янв. 15, 2025

Noncoding satellite DNA repeats are abundant at the pericentromeric heterochromatin of eukaryotic chromosomes. During interphase, sequence-specific DNA-binding proteins cluster these from multiple chromosomes into nuclear foci known as chromocenters. Despite pivotal role chromocenters in cellular processes like genome encapsulation and gene repression, associated remain incompletely characterized. Here, we use 2 proteins, D1 Prod, baits to characterize chromocenter-associated proteome Drosophila embryos, ovaries, testes through quantitative mass spectrometry. We identify D1- Prod-associated including well previously unlinked or chromocenters, thereby laying foundation for a comprehensive understanding functions enabled by their proteins. Interestingly, find that components transposon-silencing piRNA pathway with Prod embryos. Using genetics, transcriptomics, small RNA profiling, show flies lacking during embryogenesis exhibit transposon expression gonadal atrophy adults. further demonstrate this can be rescued mutating checkpoint kinase, Chk2 , which mediates germ cell arrest response mobilization. Thus, reveal protein silence transposons, manner is heritable across later stages development.

Язык: Английский

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Kinase-substrate prediction using an autoregressive model

Computational and Structural Biotechnology Journal, Год журнала: 2025, Номер 27, С. 1103 - 1111

Опубликована: Янв. 1, 2025

Kinase-specific phosphorylation plays a critical role in cellular signaling and various diseases. However, even model organisms, the substrates of most kinases remain unidentified. Currently, there is no reliable method to predict kinase-substrate relationships. In this study, we introduce an innovative approach leveraging autoregressive pairs. Unlike traditional methods focused on predicting site-specific phosphorylation, our addresses kinase-specific protein substrate prediction at level. We redefine problem as special type protein-protein interaction task. Our integrates large language ESM-2 encoder employs decoder classify protein-kinase interactions binary fashion. adopted hard negative strategy, based kinase embedding distances generated from ESM-2, compel effectively distinguish positive data. conducted top‑k analysis assess how well can prioritize likely candidates. also capable zero-shot prediction, meaning it for case known substrates, which cannot be achieved by methods. model's robust generalization novel underrepresented groups showcases its versatility broad utility. Code data are available https://github.com/farz1995/substrate_kinase_prediction.

Язык: Английский

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Rational Proteolysis Targeting Chimera Design Driven by Molecular Modeling and Machine Learning

Wiley Interdisciplinary Reviews Computational Molecular Science, Год журнала: 2025, Номер 15(2)

Опубликована: Март 1, 2025

ABSTRACT Proteolysis targeting chimera (PROTAC) induces specific protein degradation through the ubiquitin–proteasome system and offers significant advantages over small molecule drugs. They are emerging as a promising avenue, particularly in previously “undruggable” targets. Traditional PROTACs have been discovered large‐scale experimental screening. Extensive research efforts focused on unraveling biological pharmacological functions of PROTACs, with strides made toward transitioning from empirical discovery to rational, structure‐based design strategies. This review provides an overview recent representative computer‐aided drug studies PROTACs. We highlight how utilization targeted database, molecular modeling techniques, machine learning algorithms, computational methods contributes facilitating PROTAC discovery. Furthermore, we conclude achievements field explore challenges future directions. aim offer insights references for rational

Язык: Английский

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The role of alpha-synuclein in synucleinopathy: Impact on lipid regulation at mitochondria–ER membranes

npj Parkinson s Disease, Год журнала: 2025, Номер 11(1)

Опубликована: Апрель 30, 2025

The protein alpha-synuclein (αSyn) plays a pivotal role in the pathogenesis of synucleinopathies, including Parkinson's disease and multiple system atrophy, with growing evidence indicating that lipid dyshomeostasis is key phenotype these neurodegenerative disorders. Previously, we identified αSyn localizes, at least part, to mitochondria-associated endoplasmic reticulum membranes (MAMs), which are transient functional domains containing proteins regulate metabolism, de novo synthesis phosphatidylserine. In present study, analyzed composition postmortem human samples, focusing on substantia nigra pars compacta controls, as well three less affected brain regions donors. To further assess synucleinopathy-related lipidome alterations, similar analyses were performed striatum atrophy cases. Our data reveal region- disease-specific changes levels species. Specifically, our revealed alterations specific phosphatidylserine species areas most disease. Some albeit lesser degree, also observed atrophy. Using induced pluripotent stem cell-derived neurons, show regulates metabolism MAM domains, dosage parallels perturbation levels. These findings support notion pathophysiology linked dysregulation homeostasis, may contribute vulnerability synucleinopathy. have significant therapeutic implications.

Язык: Английский

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