Single-domain antibodies (sdAbs) or nanobodies have received widespread attention due to their small size (~ 15 kDa) and diverse applications in bio-derived therapeutics. As many modern biotechnology breakthroughs are applied to antibody engineering and design, nanobody thermostability or melting temperature (Tm) is crucial for their successful utilization. In this study, we present TEMPRO which is a predictive modeling approach for estimating the Tm of nanobodies using computational methods. Our methodology integrates various nanobody biophysical features to include Evolutionary Scale Modeling (ESM) embeddings, NetSurfP3 structural predictions, pLDDT scores per sdAb region from AlphaFold2, and each sequence\'s physicochemical characteristics. This approach is validated with our combined dataset containing 567 unique sequences with corresponding experimental Tm values from a manually curated internal data and a recently published nanobody database, NbThermo. Our results indicate the efficacy of protein embeddings in reliably predicting the Tm of sdAbs with mean absolute error (MAE) of 4.03 °C and root mean squared error (RMSE) of 5.66 °C, thus offering a valuable tool for the optimization of nanobodies for various biomedical and therapeutic applications. Moreover, we have validated the models\' performance using experimentally determined Tms from nanobodies not found in NbThermo. This predictive model not only enhances nanobody thermostability prediction, but also provides a useful perspective of using embeddings as a tool for facilitating a broader applicability of downstream protein analyses.

Recent years have witnessed rapid progress in the discovery of therapeutic proteins and peptides for the treatment of central nervous system (CNS) diseases. However, their clinical applications have been considerably hindered by challenges such as low biomembrane permeability, poor stability, short circulation time, and the formidable blood-brain barrier (BBB). Recently, substantial improvements have been made in understanding the dynamics of the BBB and developing efficient approaches for delivering proteins and peptides to the CNS, especially by using various nanoparticles. Herein, we present an overview of the up-to-date understanding of the BBB under physiological and pathological conditions, emphasizing their effects on brain drug delivery. We summarize advanced strategies and elucidate the underlying mechanisms for delivering proteins and peptides to the brain. We highlight the developments and applications of nanocarriers in treating CNS diseases via BBB crossing. We also provide critical opinions on the limitations and obstacles of the current strategies and put forward prospects for future research.

Urine, a common source of biological markers in biomedical research and clinical diagnosis, has recently generated a new wave of interest. It has recently become a focus of study due to the presence of its content of extracellular vesicles (EVs). These uEVs have been found to reflect physiological and pathological conditions in kidney, urothelial, and prostate tissue and can illustrate further molecular processes, leading to a rapid expansion of research in this field In this work, we present the advantages of an immunoaffinity-based method for uEVs\' isolation with respect to the gold standard purification approach performed by differential ultracentrifugation [in terms of purity and antigen presence. The immunoaffinity method was made feasible by combining specific antibodies with a functionalized polymethacrylate polymer. Flow cytometry indicated a significant fluorescence shift, validating the presence of the markers (CD9, CD63, CD81) and confirming the effectiveness of the isolation method. Microscopy evaluations have shown that the morphology of the vesicles remained intact and corresponded to the expected shapes and dimensions of uEVs. The described protocol is inexpensive, fast, easy to process, has good reproducibility, and can be applied to further biological samples.

Inflammatory bowel disease (IBD) is characterized by chronic intestinal inflammation with no cure and limited treatment options that often have systemic side effects. In this study, we developed a target-specific system to potentially treat IBD by engineering the probiotic bacterium Escherichia coli Nissle 1917 (EcN). Our modular system comprises three components: a transcription factor-based sensor (NorR) capable of detecting the inflammation biomarker nitric oxide (NO), a type 1 hemolysin secretion system, and a therapeutic cargo consisting of a library of humanized anti-TNFα nanobodies. Despite a reduction in sensitivity, our system demonstrated a concentration-dependent response to NO, successfully secreting functional nanobodies with binding affinities comparable to the commonly used drug Adalimumab, as confirmed by enzyme-linked immunosorbent assay and in vitro assays. This newly validated nanobody library expands EcN therapeutic capabilities. The adopted secretion system, also characterized for the first time in EcN, can be further adapted as a platform for screening and purifying proteins of interest. Additionally, we provided a mathematical framework to assess critical parameters in engineering probiotic systems, including the production and diffusion of relevant molecules, bacterial colonization rates, and particle interactions. This integrated approach expands the synthetic biology toolbox for EcN-based therapies, providing novel parts, circuits, and a model for tunable responses at inflammatory hotspots.

Antibody pairs-based immunoassay platforms served as essential and effective tools in the field of pathogen detection. However, the cumbersome preparation and limited detection sensitivity of antibody pairs challenge in establishment of a highly sensitive detection platform. In this study, using COVID-19 testing as a case, we utilized readily accessible nanobodies as detection antibodies and further proposed an accurate design concept with a more scientific and efficient screening strategy to obtain ultrasensitive antibody pairs. We employed nanobodies capable of binding different antigenic epitopes of the nucleocapsid (NP) or receptor-binding domain (RBD) antigens sandwich as substitutes for monoclonal antibodies (mAbs) sandwich in fast detection formats and utilized time-resolved fluorescence (TRF) microspheres as the signal probe. Consequently, we developed a multi-epitope nanobody sandwich-based fluorescence lateral flow immunoassay (FLFA) strip. Our results suggest that the NP antigen had a detection limit of 12.01pg/mL, while the RBD antigen had a limit of 6.51 pg/mL using our FLFA strip. Based on double mAb sandwiches, the values presented herein demonstrated 4 to 32-fold enhancements in sensitivity, and 32 to 256-fold enhancements compared to commercially available antigen lateral flow assay kits. Furthermore, we demonstrated the excellent characteristics of the proposed test strip, including its specificity, stability, accuracy, and repeatability, which underscores its the prospective utility. Indeed, these findings indicate that our established screening strategy along with the multi-epitope nanobody sandwich mode provides an optimized strategy in the field of pathogen detection.

Nanobodies, derived from camelids and sharks, offer compact, single-variable heavy-chain antibodies with diverse biomedical potential. This review explores their generation methods, including display techniques on phages, yeast, or bacteria, and computational methodologies. Integrating experimental and computational approaches enhances understanding of nanobody structure and function. Future trends involve leveraging next-generation sequencing, machine learning, and artificial intelligence for efficient candidate selection and predictive modeling. The convergence of traditional and computational methods promises revolutionary advancements in precision biomedical applications such as targeted drug delivery and diagnostics. Embracing these technologies accelerates nanobody development, driving transformative breakthroughs in biomedicine and paving the way for precision medicine and biomedical innovation.

Naja atra, the Chinese cobra, is a major cause of snake envenomation in Asia, causing hundreds of thousands of clinical incidents annually. The current treatment, horse serum-derived antivenom, has unpredictable side effects and presents manufacturing challenges. This study focused on developing new-generation snake venom antidotes by using microbial phage display technology to derive nanobodies from an alpaca immunized with attenuated N. atra venom. Following confirmation of the immune response in the alpaca, we amplified VHH genes from isolated peripheral blood mononuclear cells and constructed a phage display VHH library of 1.0 × 107 transformants. After four rounds of biopanning, the enriched phages exhibited increased binding activity to N. atra venom. Four nanobody clones with high binding affinities were selected: aNAH1, aNAH6, aNAH7, and aNAH9. Specificity testing against venom from various snake species, including two Southeast Asian cobra species, revealed nanobodies specific to the genus Naja. An in vivo mouse venom neutralization assay demonstrated that all nanobodies prolonged mouse survival and aNAH6 protected 66.6% of the mice from the lethal dosage. These findings highlight the potential of phage display-derived nanobodies as valuable antidotes for N. atra venom, laying the groundwork for future applications in snakebite treatment.IMPORTANCEChinese cobra venom bites present a formidable medical challenge, and current serum treatments face unresolved issues. Our research applied microbial phage display technology to obtain a new, effective, and cost-efficient treatment approach. Despite interest among scientists in utilizing this technology to screen alpaca antibodies against toxins, the available literature is limited. This study makes a significant contribution by introducing neutralizing antibodies that are specifically tailored to Chinese cobra venom. We provide a comprehensive and unbiased account of the antibody construction process, accompanied by thorough testing of various nanobodies and an assessment of cross-reactivity with diverse snake venoms. These nanobodies represent a promising avenue for targeted antivenom development that bridges microbiology and biotechnology to address critical health needs.

Alzheimer\'s disease (AD) remains a significant challenge in the field of neurodegenerative disorders, even nearly a century after its discovery, due to the elusive nature of its causes. The development of drugs that target multiple aspects of the disease has emerged as a promising strategy to address the complexities of AD and related conditions. The immune system\'s role, particularly in AD, has gained considerable interest, with nanobodies representing a new frontier in biomedical research. Advances in targeting antibodies against amyloid-β (Aβ) and using messenger RNA for genetic translation have revolutionized the production of antibodies and drug development, opening new possibilities for treatment. Despite these advancements, conventional therapies for AD, such as Cognex, Exelon, Razadyne, and Aricept, often have limited long-term effectiveness, underscoring the need for innovative solutions. This necessity has led to the incorporation advanced technologies like artificial intelligence and machine learning into the drug discovery process for neurodegenerative diseases. These technologies help identify therapeutic targets and optimize lead compounds, offering a more effective approach to addressing the challenges of AD and similar conditions.

Antibodies that can selectively remove rogue proteins in the brain are an obvious choice to treat neurodegenerative disorders (NDs), but after decades of efforts, only two antibodies to treat Alzheimer\'s disease are approved, dozens are in the testing phase, and one was withdrawn, and the other halted, likely due to efficacy issues. However, these outcomes should have been evident since these antibodies cannot enter the brain sufficiently due to the blood-brain barrier (BBB) protectant. However, all products can be rejuvenated by binding them with transferrin, preferably as smaller fragments. This model can be tested quickly and at a low cost and should be applied to bapineuzumab, solanezumab, crenezumab, gantenerumab, aducanumab, lecanemab, donanemab, cinpanemab, and gantenerumab, and their fragments. This paper demonstrates that conjugating with transferrin does not alter the binding to brain proteins such as amyloid-β (Aβ) and α-synuclein. We also present a selection of conjugate designs that will allow cleavage upon entering the brain to prevent their exocytosis while keeping the fragments connected to enable optimal binding to proteins. The identified products can be readily tested and returned to patients with the lowest regulatory cost and delays. These engineered antibodies can be manufactured by recombinant engineering, preferably by mRNA technology, as a more affordable solution to meet the dire need to treat neurodegenerative disorders effectively.

Non-small cell lung cancer (NSCLC) presents a complex and diverse disease, exhibiting variations at individuals\' cellular and histological levels. This complexity gives rise to different subtypes and genetic mutations, posing challenges for accurate diagnosis and effective treatment. Nevertheless, continuous progress in medical research and therapies is continually shaping the landscape of NSCLC diagnosis and management. The treatment of NSCLC has undergone significant advancements in recent years, especially with the emergence of targeted therapies that have shown remarkable efficacy in patients with actionable mutations. This has ushered in the era of personalized medicine in NSCLC treatment, with improvements in molecular and immunohistochemical techniques contributing to enhanced progression-free survival. This review focuses on the latest progress, challenges, and future directions in developing targeted therapies for NSCLC, including tyrosine kinase inhibitors (TKIs), DNA-damaging agents, immunotherapy regimens, natural drug therapy, and nanobodies. Furthermore, recent randomized studies have demonstrated enhanced overall survival in patients receiving different targeted and natural drug therapies.