Structural studies of protein-nucleic acid complexes: A brief overview of the selected techniques

Nucleic acids based integrated macromolecular complexes for SiRNA delivery: Recent advancements

The therapeutic potential of small interfering RNA (siRNA) is monumental, offering a pathway to silence disease-causing genes with precision. However, the delivery of siRNA to target cells in-vivo remains a formidable challenge, owing to degradation by nucleases, poor cellular uptake and immunogenicity. This overview examines recent advancements in the design and application of nucleic acid-based integrated macromolecular complexes for the efficient delivery of siRNA. We dissect the innovative delivery vectors developed in recent years, including lipid-based nanoparticles, polymeric carriers, dendrimer complexes and hybrid systems that incorporate stimuli-responsive elements for targeted and controlled release. Advancements in bioconjugation techniques, active targeting strategies and nanotechnology-enabled delivery platforms are evaluated for their contribution to enhancing siRNA delivery. It also addresses the complex interplay between delivery system design and biological barriers, highlighting the dynamic progress and remaining hurdles in translating siRNA therapies from bench to bedside. By offering a comprehensive overview of current strategies and emerging technologies, we underscore the future directions and potential impact of siRNA delivery systems in personalized medicine.

Each big journey starts with a first step: Importance of oligomerization

Protein oligomers, widely found in nature, have significant physiological and pathological functions. They are classified into three groups based on their function and toxicity. Significant advancements are being achieved in the development of functional oligomers, with a focus on various applications and their engineering. The antimicrobial peptides oligomers play roles in death of bacterial and cancer cells. The predominant pathogenic species in neurodegenerative disorders, as shown by recent results, are amyloid oligomers, which are the main subject of this chapter. They are generated throughout the aggregation process, serving as both intermediates in the subsequent aggregation pathways and ultimate products. Some of them may possess potent cytotoxic properties and through diverse mechanisms cause cellular impairment, and ultimately, the death of cells and disease progression. Information regarding their structure, formation mechanism, and toxicity is limited due to their inherent instability and structural variability. This chapter aims to provide a concise overview of the current knowledge regarding amyloid oligomers.

Structural biology of SARS-CoV-2

This chapter provides a comprehensive overview of the techniques employed to unravel the structural biology of SARS-CoV-2, facilitating a deeper understanding of the virus for developing future therapeutic strategies. Various techniques such as Electron microscopy (EM) for capturing high-resolution images of the virus and X-ray crystallography used for determining atomic-level structures of viral proteins are discussed. Cryo-electron microscopy (cryo-EM) imaging is also examined as a powerful tool for visualizing the virus's structure in its native state. Intracellular detection and tracking of SARS-CoV-2 are discussed, highlighting the techniques employed to study the virus's behavior within host cells. The chapter further explores how cryo-EM has been instrumental in delivering high-quality structural information on SARS-CoV-2, enabling researchers to better understand its mechanisms of infection and replication. The structural visualization of SARS-CoV-2 is then presented, focusing on key components such as the spike protein structure, RNA polymerase structure, and the visualization of intact and in-situ virions using cryo-electron tomography (cryo-ET). Lastly, the chapter touches upon the application of nuclear magnetic resonance (NMR) spectroscopy for studying the dynamics and interactions of viral proteins.

Evaluation of DNA-protein complex structures using the deep learning method

Biological processes such as transcription, repair, and regulation require interactions between DNA and proteins. To unravel their functions, it is imperative to determine the high-resolution structures of DNA-protein complexes. However, experimental methods for this purpose are costly and technically demanding. Consequently, there is an urgent need for computational techniques to identify the structures of DNA-protein complexes. Despite technological advancements, accurately identifying DNA-protein complexes through computational methods still poses a challenge. Our team has developed a cutting-edge deep-learning approach called DDPScore that assesses DNA-protein complex structures. DDPScore utilizes a 4D convolutional neural network to overcome limited training data. This approach effectively captures local and global features while comprehensively considering the conformational changes arising from the flexibility during the DNA-protein docking process. DDPScore consistently outperformed the available methods in comprehensive DNA-protein complex docking evaluations, even for the flexible docking challenges. DDPScore has a wide range of applications in predicting and designing structures of DNA-protein complexes.