Biology subjects

Sadek, A.

Publications and source records attributed to Sadek, A..

8 recordsLinked to original sources

bioRxiv2026

De novo Design of Polymorph-Specific Binders Targeting α-Synuclein Fibrils

Alpha-synuclein (aSyn) aggregation into amyloid fibrils is a hallmark of synucleinopathies, a group of neurodegenerative disorders that includes Parkinsons disease. Beyond the central role of fibrils in disease pathology and propagation, distinct aSyn fibril polymorphs have been associated with different synucleinopathies, presenting opportunities for differential diagnosis and structure-based disease-specific phenotyping. Here, we present AmyBind, a computational pipeline for the de novo design of mini-protein binders that target polymorph-specific structural features of amyloid fibrils. Using this approach, we developed two aSyn fibril-specific binders, one of which exhibited polymorph-specificity. Neither binder interfered with fibril elongation in vitro, consistent with their designed binding mode on lateral fibril surfaces. In cell-based models, both binders showed polymorph-specific colocalization but did not affect fibril uptake or seeding, indicating their utility as fibril-selective labeling agents in cellular contexts. These findings demonstrate the feasibility of structure-guided, polymorph-specific amyloid targeting and provide a foundation for developing early-stage diagnostics and therapeutics for synucleinopathies and other amyloid-related diseases.

bioengineering↗

bioRxiv2025

Probing the energy landscape of α-Synuclein amyloid fibril formation by systematic K-to-Q mutagenesis

The aggregation of natively disordered -Synuclein (Syn) into amyloid fibrils is a hallmark of Parkinsons and other neurodegenerative diseases. Understanding Syns pathological role remains a major challenge due to its complex, context-dependent energy landscape characterized by conformational plasticity and fibril polymorphism. Here, we present a systematic mutational analysis as a quantitative probe of the Syn energy landscape, focusing on electrostatic contributions to key aggregation pathways. We engineered Syn variants with one to eight lysine-to-glutamine substitutions and analyzed their aggregation under controlled conditions to delineate their effects on nucleation, elongation, seed amplification, fibril stability, and fibril polymorphism. We find that Syn aggregation from a homogenous solution can be modelled well using global properties, including protein concentration, charge, and ionic strength. Microscopic pathways and the resulting fibril polymorphs are instead modulated by sequence-specific effects. We identify mutations of residues found in fibril cores as perturbations that significantly modify the Syn free energy landscape, creating pathways and energy minima not accessible to the WT under the same experimental conditions. In contrast, mutations outside of the fibril core affect the magnitude of the relevant energy barriers whilst overall maintaining a WT-like free energy landscape. Our work outlines a scalable, quantitative framework that increases the informational output of the mutational studies of Syn using conventional assays. The approach can be extended by incorporating additional mutational and functional data to deepen our understanding of Syns energy landscape and its role in health and disease.

biophysics↗

bioRxiv2025

Mapping the Structural Landscape of Amyloid Fibrils to Guide Polymorph-Specific Therapeutics

Amyloid fibrils are pathological hallmarks of neurodegenerative diseases and central contributors to their progression, representing promising targets for disease-modifying interventions. However, limited access to patient-derived fibrils and the inability to reproduce pathological folds in vitro hinder the development of fibril-specific ligands. Here, we present FibrilSite, a computational pipeline that identifies geometric and physicochemical similarities across fibril surfaces and demonstrate its utility to identify structural features that distinguish different fibril polymorphs. Our analysis uncovered conserved and polymorph-specific features within alpha-synuclein fibrils. Notably, one site was conserved between ex vivo multiple system atrophy and in vitro H50Q mutant fibrils, suggesting the latters potential utility in drug discovery. Druggability predictions further prioritized ligandable sites across fibrils. Together, our findings establish a structure-based framework for identifying disease-relevant features and mapping them onto suitable in vitro models, guiding the rational development of polymorph-specific diagnostics and therapeutics for amyloid-related disorders with improved translational potential.

bioinformatics↗

bioRxiv2024

Mapping targetable sites on the human surfaceome for the design of novel binders

The human cell surfaceome, integral to cell communication and disease mechanisms, presents a prime target for therapeutic intervention. De novo protein binder design against these cell surface proteins offers a promising yet underexplored strategy for drug development. However, the vast search space and limited data on natural or competitive binders have historically limited experimental success. In this study, we systematically analyzed the entire human surfaceome, identifying approximately 4,500 targetable sites and introducing high-quality binder seeds tailored for protein design applications. To validate these seeds, we implemented two experimental approaches (protein scaffolding and peptide cyclization) on three representative targets (FGFR2, IFNAR2, and HER3). Our results revealed a high success rate, emphasizing the precision and therapeutic potential of these seeds, as well as the need for constant improvements of computational protein design pipelines utilizing machine learning and physics-based methods. Additionally, we present SURFACE-Bind, an interactive database offering open access to all generated data. The high-throughput computational design methods and target-specific binder seeds established here pave the way for a new generation of targeted therapeutics for the human surfaceome.

synthetic biology↗

bioRxiv2024

β-glucan reprograms alveolar macrophages via neutrophil/IFNγ axis to promote lung injury

Alveolar macrophages (AMs) reside in the lower airways and play a crucial role in lung health and response to sterile inflammation and infections. AMs possess remarkable adaptability to different environmental challenges that can persist through their memory capacity (trained immunity). {beta}-glucan has been characterized as a potent inducer of central trained immunity by reprogramming hematopoietic stem cells (HSCs) in the bone marrow. In the present study, we show that systemic administration of {beta}-glucan induces peripheral trained immunity by reprogramming alveolar macrophages (AMs) in the lungs, in a Dectin1-independent manner. We furthermore demonstrate that AM reprogramming at both the transcriptional and metabolic levels exacerbate lung injury following bacterial (LPS) or viral (polyI:C) challenges via a neutrophil/IFN-{gamma} dependent manner. These findings identify an additional facet of {beta}-glucan in trained immunity involving AM reprogramming and shed light on the potential detrimental effects of trained immunity.

immunology↗

bioRxiv2022

Decoding Surface Fingerprints for Protein-Ligand Interactions

AO_SCPLOWBSTRACTC_SCPLOWSmall molecules have been the preferred modality for drug development and therapeutic interventions. This molecular format presents a number of advantages, e.g. long half-lives and cell permeability, making it possible to access a wide range of therapeutic targets. However, finding small molecules that engage "hard-to-drug" protein targets specifically and potently remains an arduous process, requiring experimental screening of extensive compound libraries to identify candidate leads. The search continues with further optimization of compound leads to meet the required potency and toxicity thresholds for clinical applications. Here, we propose a new computational workflow for high-throughput fragment-based screening and binding affinity prediction where we leverage the available protein-ligand complex structures using a state-of-the-art protein surface embedding framework (dMaSIF). We developed a tool capable of finding suitable ligands and fragments for a given protein pocket solely based on protein surface descriptors, that capture chemical and geometric features of the target pocket. The identified fragments can be further combined into novel ligands. Using the structural data, our ligand discovery pipeline learns the signatures of interactions between surface patches and small pharmacophores. On a query target pocket, the algorithm matches known target pockets and returns either potential ligands or identifies multiple ligand fragments in the binding site. Our binding affinity predictor is capable of predicting the affinity of a given protein-ligand pair, requiring only limited information about the ligand pose. This enables screening without the costly step of first docking candidate molecules. Our framework will facilitate the design of ligands based on the targets surface information. It may significantly reduce the experimental screening load and ultimately reveal novel chemical compounds for targeting challenging proteins.

bioinformatics↗

bioRxiv2022

Neighbouring modifications interfere with the detection of phosphorylated alpha-synuclein at Serine 129: Revisiting the specificity of pS129 antibodies

Alpha-synuclein (aSyn) within Lewy bodies, Lewy neurites, and other pathological hallmarks of Parkinsons disease and synucleinopathies have consistently been shown to accumulate in aggregated and phosphorylated forms of the protein, predominantly at Serine 129 (S129). Antibodies against phosphorylated S129 (pS129) have emerged as the primary tools to investigate, monitor, and quantify aSyn pathology in the brain and peripheral tissues. However, most of the antibodies and immunoassays aimed at detecting pS129-aSyn were developed based on the assumption that neighbouring post-translational modifications (PTMs) either do not co-occur with pS129 or do not influence its detection. Herein, we demonstrate that the co-occurrence of multiple pathology-associated C-terminal PTMs (e.g., phosphorylation at Tyrosine 125 or truncation at residue 133 or 135) differentially influences the detection of pS129-aSyn species by pS129-aSyn antibodies. These observations prompted us to systematically reassess the specificity of the most commonly used pS129 antibodies against monomeric and aggregated forms of pS129-aSyn in mouse brain slices, primary neurons, mammalian cells and seeding models of aSyn pathology formation. We identified two antibodies that are insensitive to pS129 neighbouring PTMs. However, consistent with previous reports, most pS129 antibodies showed cross-reactivity towards other proteins and often detected low and high molecular weight bands in aSyn knock-out samples that could be easily mistaken for monomeric or High Molecular Weight aggregates of aSyn. Our observations suggest that the pS129 antibodies do not capture the biochemical and morphological diversity of aSyn pathology. They also underscore the need for more specific pS129 antibodies, more thorough characterization and validation of existing antibodies, and the use of the appropriate protein standards and controls in future studies.

neuroscience↗

bioRxiv2021

Structural Insights of SARS-CoV-2 Spike Protein from Delta and Omicron Variants

Given the continuing heavy toll of the COVID-19 pandemic and the emergence of the Delta (B.1.617.2) and Omicron (B.1.1.529) variants, the WHO declared both as variants of concern (VOC). There are valid concerns that the latest Omicron variant might have increased infectivity and pathogenicity. In addition, the sheer number of S protein mutations in the Omicron variant raise concerns of potential immune evasion and resistance to therapeutics such as monoclonal antibodies. However, structural insights that underpin the potential increased pathogenicity are unknown. Here we adopted an artificial intelligence (AI)-based approach to predict the structural changes induced by mutations of the Delta and Omicron variants in the spike (S) protein using Alphafold. This was followed by docking the human angiotensin-converting enzyme 2 (ACE2) with the predicted S proteins for Wuhan-Hu-1, Delta, and Omicron variants. Our in-silico structural analysis indicates that S protein for Omicron variant has a higher binding affinity to ACE-2 receptor, compared to Wuhan-Hu-1 and Delta variants. In addition, the recognition sites of the receptor binding domains for Delta and Omicron variants showed lower electronegativity compared to Wuhan-Hu-1. Importantly, further molecular insights revealed significant changes induced at fusion protein (FP) site, which may mediate enhanced viral entry. These results represent the first computational analysis of structural changes associated with Omicron variant using Alphafold, Collectively, our results highlight potential structural basis for enhanced pathogenicity of the Omicron variant, however further validation using X-ray crystallography and cryo-EM are warranted.

biophysics↗