FOXP2 and PAX6 are transcription factors essential for neural development, with mutations in both linked to autism spectrum disorders (ASDs). Their DNA-binding domains include a forkhead domain (FHD) for FOXP2 and a paired domain (PD) plus homeodomain (HD) for PAX6. We investigated whether the FOXP2 FHD interacts directly with PAX6 PD or HD, and how such interactions influence DNA binding. Fluorescence anisotropy showed that all three domains bind specifically to their respective DNA targets with similar affinities. The FOXP2 FHD also interacts directly with both PAX6 PD and HD, with low micromolar binding affinities. Despite its stronger intrinsic DNA affinity, the FHD was displaced from its target DNA by both PAX6 domains, suggesting that protein-protein interactions can override DNA affinity under competitive conditions. In contrast, FOXP2 could not displace PD or HD from their DNA targets. Molecular docking supported these findings: DNA-protein interfaces were largely unchanged by the second protein, but protein-protein interfaces were strongly influenced by DNA occupancy. The H3 helix of FHD was identified as a central point for assembly, contributing to both DNA and protein interfaces. When FHD was bound to DNA, H3 was occupied, forcing PD or HD to dock at alternative, less optimal sites. HD maintained stronger contacts in these rearranged states, consistent with its greater competitive strength. This asymmetric interplay indicates competitive dominance by PAX6 and suggests mechanisms that could underlie transcriptional regulation in neurodevelopment.

Ovarian cancer remains a significant clinical challenge for women's health, making it imperative to elucidate its underlying molecular mechanisms. LncRNA CERS6-AS1 and LIN28B-binding proteins play a vital role in the development of ovarian cancer. The expression levels of CERS6-AS1 and LIN28B in ovarian cancer tissues and cell lines were evaluated using qPCR. Protein levels were analyzed through IHC. The survival rate was assessed using the Kaplan-Meier curve. LIN28B or CERS6-AS1 was silenced via RNA interference (shRNA), and the effects on proliferation, migration, and invasion were examined through cell cloning, scratch assays, and Transwell assays. RNA pull-down and RIP experiments confirmed the binding of CERS6-AS1 to IGF2BP1 and enhances on the stability of LIN28B mRNA. Finally, LIN28B overexpression was performed for functional recovery experiments. Elevated expression of CERS6-AS1 and LIN28B was observed in both clinical ovarian cancer specimens and derived cell lines. The knockdown of LIN28B suppressed ovarian cancer cell proliferation, migration and invasion. Molecular investigations revealed that CERS6-AS1 stabilized LIN28B through IGF2BP1 binding. Furthermore, CERS6-AS1 depletion similarly attenuated malignant phenotypes, effects that were rescued by LIN28B overexpression. Collectively, the CERS6-AS1-regulated IGF2BP1/LIN28B signaling axis promoted ovarian cancer progression by enhancing tumor cell proliferation, migration and invasion, highlighting this pathway as a promising therapeutic target.

Xanthomonas oryzae pv. oryzae (Xoo), the causative agent of bacterial blight in rice, secretes a suite of effectors via the Type III Secretion System (T3SS), among which harpin proteins like Hpa1 are key modulators of plant immunity. Unlike other T3SS effectors, Hpa1 lacks enzymatic activity and instead acts as a biostimulant, promoting growth and defense responses. In this study, the hpa1 gene was cloned from Xoo BXO1 strain and successfully expressed in E. coli Rosetta cells. The recombinant protein was purified using Ni-NTA chromatography, and SDS-PAGE, Western blotting, and MALDI-TOF analysis confirmed its molecular weight (∼16.5 kDa). Biophysical characterization revealed a predominance of α-helical content, with CD spectroscopy. Thermal and chemical unfolding of Hpa1 was evaluated using CD spectroscopy (with GuHCl) and ANS fluorescence (with GuHCl and urea), revealing moderate stability. pH-dependent stability assessed by fluorescence showed optimal structural retention at pH 5. TFE-induced structural modulation, studied by CD, demonstrated concentration-dependent α-helix enhancement. Thermal stability was assessed through four approaches: SDS-PAGE, CD at 222 nm, SYPRO Orange-based thermal shift assay, and HR-inducing activity in Nicotiana benthamiana. These results collectively confirmed that native Hpa1 conformation is not necessary for its function. These findings highlight its potential as a protein-based biostimulant for agricultural applications and its utility as a model for studying intrinsically disordered yet functionally stable proteins.

Terminal deoxynucleotidyl transferase (TdT) is a unique DNA polymerase that catalyzes the template-independent addition of nucleotides to the 3' terminus of single-stranded DNA. Its distinctive catalytic properties have been exploited in aptasensor design, nanomaterial synthesis, DNA mutagenesis, innovative data storage based on single-nucleotide DNA sequences, and enzymatic de novo DNA synthesis. However, the application of the enzyme is limited by its low expression yield, poor thermostability, and reduced nucleotide incorporation efficiency with substrates prone to forming secondary structures. To overcome these limitations, we engineered a bovine TdT variant truncated at the N-terminus by 148 residues (148_TrTdT), which demonstrates a twofold increase in expression yield, a 5 °C improvement in thermostability, and over 30 % enhancement in nucleotide incorporation efficiency and processivity compared to the wild-type enzyme. Moreover, we demonstrated that DNA-binding proteins enhance the nucleotide incorporation activity of native TdT (10-fold) and 148_TrTdT (2-fold) when substrates are prone to forming secondary structures. Collectively, the methodologies implemented in this study exhibit significant potential for enhancing the efficiency of enzymatic de novo DNA synthesis, thereby enabling the development of new bioengineering and biomedical applications.

Lung adenocarcinoma remains a major challenge in cancer research due to its complex molecular underpinnings. In this study, we developed an integrated machine learning framework to identify novel driver genes associated with lung adenocarcinoma by leveraging multi-omics data. We curated gene candidates from methylation, RNAseq, mutation, and miRNA levels, and mapped them onto a protein-protein interaction network from STRING to generate informative feature vectors using a node2vec method. Furthermore, they were also represented by GO and KEGG enrichment features. All features were then refined through a multi-step process, beginning with the Boruta algorithm for filtering and followed by the minimum redundancy maximum relevance method for ranking. An incremental feature selection strategy was employed to determine the optimal feature subsets, which were used to build predictive models with random forest and support vector machine classifiers. To address class imbalance, synthetic sampling was applied, and ten-fold cross-validation ensured model robustness. Consequently, we predicted 428, 105, 1039, and 1748 potential lung adenocarcinoma driver genes for RNAseq, methylation, mutation, and miRNA levels, respectively. Integrated analysis of overlapping gene sets further highlighted key candidates, including PQLC3, FAM192A, FAM83D, SPRED1, SFTPB, and TM4SF5, with high composite probability scores. Some identified genes may be the driver genes of lung adenocarcinoma and have some druggable potential. These findings provide new insights into the molecular mechanisms of lung adenocarcinoma and suggest promising targets for future diagnostic and therapeutic strategies.

The Neglected Tropical Disease (NTD) Leishmaniasis continues to pose a serious global health burden affecting millions globally. Visceral leishmaniasis, one of three clinical forms, can be fatal, if left untreated. Current treatment regimen relies mostly on re-purposed drugs and is limited by toxicity, high cost and the emergence of drug resistance, highlighting the need for safer, targeted therapies. In this study, we characterized Leishmania donovani homoserine dehydrogenase (LdHSD), a crucial enzyme in the aspartate pathway. As no human homolog exists, it represents a promising target for selective therapeutic intervention. LdHSD was purified to homogeneity, characterized biophysically and its activity biochemically assayed. Docking of the substrate (L-homoserine) and the cofactor (NADP) to the LdHSD homology model identified adjacent but discrete binding pockets. Structure-based virtual screening of the Maybridge Compound Library was subsequently performed and the top 10 substrate-site bound compounds were taken for experimental validation. Two of the three piperidine/piperazine scaffold compounds inhibited LdHSD activity by ∼90 %. These findings highlight the therapeutic potential of targeting LdHSD for the development of novel, selective anti-leishmanial agents and establish a strong foundation for future optimization of these identified inhibitors.

Neurodegenerative disorders (ND) such as Parkinson's and Alzheimer's progressively impair the nervous system, leading to cognitive deterioration and motor dysfunction. A primary factor in these diseases is the accumulation of misfolded protein aggregates, which interfere with cellular processes and ultimately result in neuronal death. Preventing the formation of these toxic aggregates has the potential to protect neurons and slow the advancement of disease. This study examined the impact of diosgenin on protein aggregation, utilizing human serum albumin (HSA) as model protein. Diosgenin reduced ThT fluorescence by 64.35 % and decreased turbidity by 62.61 %, indicating a notable suppression of protein aggregation. The % α-helix in HSA experienced a decline from 57.68 % to 8.82 %, but diosgenin treatment restored it to 43.89 %. Binding studies demonstrated that diosgenin interacts with HSA with -11.0 kcal/mol binding energy, facilitated by van der Waals, hydrophobic and hydrogen bonding interactions, and stability of HSA-diosgenin complex was also validated using molecular simulations. To further elucidate the aggregation inhibition mechanism by diosgenin, advanced molecular dynamics simulations were employed. Diosgenin increased the solvent accessibility of the HSA oligomers, reduced β-sheet formation, and prevented H-bond interactions, key factors in aggregate formation. Molecular simulation of Aβ oligomers (Aβ) also showed the diosgenin prevents oligomerization and β-sheet formation. We show that diosgenin presents a promising alternative due to its ability to stabilize protein structures and inhibit protein aggregation, making it a potential therapeutic candidate for NDs. However, further experimental validation in animal models is necessary to confirm diosgenin's anti-aggregation effects, particularly of amyloid-forming proteins.

Thioredoxins (Trxs) are small, highly conserved oxidoreductases characterized by a redox-active CXXC motif. While the structural adaptation of modern Trxs such as Escherichia coli Trx (EcTrx) has been described, the mechanisms underlying Trx adaptation to acidic environments remain unclear. In EcTrx, Asp43 stabilizes the active-site region through a water-mediated hydrogen bond with Lys57, which modulates the protonation state of Cys32 in cooperation with Asp26. Comparative sequence analysis shows that small, nonpolar amino acids-such as Gly and Ala-are frequently found at position 43 in acidophilic Trxs, indicating that structural flexibility at this position may contribute to acidic adaptation. To test how substitutions at position 43 affect Trx stability and function, we generated EcTrx mutants (D43G, D43A, D43S, D43N, D43L, and D43E). Thermal shift and guanidinium chloride-induced unfolding assays revealed that D43A and D43S markedly reduced stability, while D43G retained moderate stability, likely due to tighter N-terminal packing as observed in the acidophilic Acetobacter aceti Trx. These three mutants also displayed increased conformational flexibility, whereas D43N and D43L conferred partial stabilization through polar or hydrophobic side chains. In contrast, D43E-mimicking ancestral Glu-restored hydrogen bonding and enhanced thermal stability, resulting in the most rigid structure. Most mutants retained catalytic activity in DTNB assays, except D43S, which showed 50% of wild-type activity. Overall, our results demonstrate that Asp43 is critical for maintaining EcTrx structural stability and suggest that enhanced, but not excessive, flexibility at this position facilitates Trx adaptation to acidic environments.

Simvastatin is a primary cholesterol-lowering medication, but it has also been reported to possess anti-inflammatory properties. Notably, the CD18 integrins are targets for simvastatin antagonism of ligand binding, which may affect leukocyte adhesion and diapedesis. Lymphocyte-associated antigen (LFA)-1 is inhibited through an allosteric mechanism by binding the lactone form of simvastatin (simvastatin-lac) to a hydrophobic pocket in the major ligand binding domain, the alpha chain I domain. By contrast, crystallographic evidence showed that complement receptor 3 (CR3) is inhibited by simvastatin in its carboxylate form (simvastatin-carbox) chelated by an Mg ion in the αI metal ion-dependent adhesion site (MIDAS). We now report that the affinity (K) of simvastatin-carbox for the αI is ∼650 μM, which is significantly weaker than the 50 %-inhibitory concentration of simvastatin-lac at 50 μM. The simvastatin-carbox was incapable of inhibiting CR3 binding to iC3b, nor did it exert any neuroprotective or anti-inflammatory effects in the middle cerebral artery occlusion animal model of stroke, unlike what has been reported for simvastatin-lac. From available structural data on the CR3 ligand binding domain in complex with C3d, we suggest that simvastatin-lac makes a critical ternary complex with the ligand binding domain and its ligand before engaging, in its carboxylate form, the MIDAS. In this way, both the LFA-1 and CR3 are antagonized by simvastatin-lac but through fundamentally different mechanisms.

cis-Regulatory elements (CREs) in multicellular genomes play a significant role in precise regulation of the genes. Increasing evidence has shown that alterations in CREs have had a drastic effect on the human brain evolution, neuronal cell adaptation and physiology. The human-specific sequence acceleration in CREs has not only changed the overall cognitive function of the human brain, but also seems to have strongly increased the risk of developing psychiatric disorders. Mapping the human-specific neuronal mutations within CREs remains to be a challenge and can largely impact the way DNA binding domain of the transcription factors interact with the CREs. In this study, we have identified human-specific neuronal mutations within transcription factor binding sites in neuropsychiatric enhancers of three major psychiatric disorders i.e. autism spectrum disorder, schizophrenia and bipolar disorder and studied the impact of human-specific neuronal mutations on binding affinities with the respective transcription factors via molecular dynamic simulation. Moreover, we have also identified signals of positive selection in the same set of empirically confirmed neuropsychiatric enhancers and correlated it with the way transcription factors bind with the human-specific and their counterpart ancestral allele harboring transcription factor binding sites.

NLRP3 is one of the central players in innate immune signaling. Upon stimulation, NLRP3 could oligomerize and recruit ASC, NEK7, and caspase 1 (CASP1), then assemble into inflammasome, triggering downstream inflammation and pyroptosis. Recently, it was reported that both potassium efflux dependent and independent signaling, could lead to the formation of dispersed TGN (dTGN), where NLRP3 was initially recruited. Interestingly, the phosphatidylinositol-4-phosphate (PI4P) enriched on dTGN is indispensable for NLRP3 recruitment. In this study, we found that Phafin2, which can bind PI4P and PI3P via its PH and FYVE domains respectively, could modulate the NLRP3 aggregation on dTGN, thus regulating the cell pyroptosis. Phafin2 affects NLRP3 aggregation indirectly by influencing the constitution of dTGN. Our study unravels Phafin2 might act as a critical regulator of NLRP3-mediated pyroptosis, thus providing a new therapeutic target for human diseases associated with NLRP3-involved inflammation.

LARP1 (La-related protein 1) is an important mediator of translation regulation that stabilizes terminal oligopyrimidine motif-containing mRNAs. LARP1, being a direct target of mechanistic Target of Rapamycin Complex 1 (mTORC1), undergoes phosphorylation in the presence of growth factors. Phosphorylation-dependent conformational changes in LARP1 dictate its ability to stabilize or repress mRNAs with 5' terminal oligopyrimidine (TOP), which code for key proteins in ribosome biogenesis and translation. Due to this important role, LARP1 is involved in cancer cell survival, facilitating selective translation of oncogenic proteins with a tradeoff in cap-dependent translation. As the function of LARP1 is governed by phosphorylation, this review provides phosphoproteomics-based regulatory network of LARP1, identifying major phosphorylation sites, upstream kinases, and interactors, with mutual co-differential regulation events. Extensive literature synthesis identified 11 major phosphorylation sites of LARP1, and an understanding of interaction dynamics that contribute to functional plasticity of LARP1. Specially, this article synthesizes the co-regulatory network of LARP1 with other proteins, and the interactions central to mTOR signaling, phosphorylation of LARP1, and its functional role in disease manifestation. This approach focusing on the LARP1-kinase regulatory network is crucial in untangling its miscellaneous role in cancer, which provides novel therapeutic paths for malignancies.

Protofibrils are key intermediates to explore effective therapeutic strategies for amyloid-related diseases; however, their structural features remain largely ambiguous. Here, we report a direct visualization of the intermolecular β-sheet structure of amyloid protofibrils using cryo-electron microscopy. We analyzed the protofibrils formed by an insulin-derived peptide and observed 4.7 Å regularly spaced lines at their centers surrounded by fuzzy regions, consistent with the hydrogen-bonded β-strand structure. We propose a model in which short β-strands form a β-sheet core in the center, whereas the outer fuzzy regions are composed of random coiled structures. This structure is different from that of mature amyloid fibrils, where β-sheets span the entire structure, suggesting that the partial β-sheet formation in protofibrils is responsible for their curvy noodle-like appearance. Overall, this study highlights cryo-electron microscopy as a powerful tool for visualizing seemingly flexible structures, such as protofibrils, and establishes a conceptual framework for the rational design of diagnostic and therapeutic agents targeting the protofibril β-sheet structure.

PPAR-γ and SIRT1 are the emerging targets that are vital in diabetes and diabetic complications. So, the development of dual activators for PPAR-γ and SIRT1 can be a good strategy in the treatment of diabetes and diabetic complications and in order to reduce the adverse effects that occur from the activation of these targets. The network analysis was applied to study the protein-protein interactions. Similarity-based virtual screening was done to screen Fisetin-based molecules, and docking analysis was performed for both targets. In addition, an ADME study and electrostatic complementarity analysis were conducted to study the role of binding energies between the ligands and the targets. The Molecular Dynamics (MD) simulation was performed to study the stable binding conformation. Different validation metrics from MD analysis, such as RMSD, RMSF, R, PCA and free energy landscape (FEL), were analysed to evaluate the stability of the compounds with the target proteins. Moreover, the WaterSwap and MMPBSA analyses were also done to calculate the binding free energy of the compounds. The findings from this extensive evaluation depicted that the selected three molecules can be used as potent and safe dual activators of PPAR-γ and SIRT1 to combat diabetes and several diabetic complications.

Listeria monocytogenes is the causative agent of Listeriosis, a serious foodborne illness that primarily affects pregnant women, new-borns, the elderly, and immunocompromised individuals. L. monocytogenes secretes proteins that bind and degrade chitin, a linear polysaccharide formed of β1,4-linked N-acetylglucosamine residues, and although humans do not produce chitin, these enzymes act as virulence factors that promote bacterial growth during host infection. The chitinase ChiA is a major contributor to virulence, and it can modulate host immunity through downregulating the expression of host inducible nitric oxide synthase (iNOS), although this precise mechanism has yet to be determined. Here we present the X-ray crystal structure of L. monocytogenes ChiA at 1.95 Å resolution, complemented by solution small angle X-ray scattering analysis and molecular dynamics simulations. Our comparative analyses reveal structural conservation with homologous bacterial chitinases and highlight potential alternative ligand-binding sites beyond the canonical chitin-binding channel. Molecular dynamics simulations of an N-glycopeptide model demonstrate stable interactions between LmChiA and the mannose-rich N-glycan core near these putative sites. These findings suggest that LmChiA may interact with branched host glycans rather than exclusively processing chitin-derived substrates, and this provides a potential explanation for its role in modulating host immune responses.

Cellular process relies on specific binding of drug molecules with desired biological receptors. Biomolecular receptors and drugs exhibit their biological functions upon their interactions. Understanding the binding parameters and energetics of the binding provides a plethora of information that may be helpful in drug design and discovery. Further, drug interaction with carrier proteins affects the pharmacokinetics and dynamics of other exogenous and endogenous drugs. In this work, we report the binding behavior of esomeprazole with human serum albumin using several biophysical techniques. Qualitative and quantitative aspects of the binding along with the binding energetics has been focused in extracting the thermodynamics parameters and key interaction force. The binding constants (K)obtained from Scatchard analysis are-1.17 × 10, 7.49 × 10, and 3.23 × 10 M at 298, 303, 308 K respectively. Esomeprazole binds preferentially at site 1 in subdomain IIA of human serum albumin and was confirmed, supported by site-specific marker displacement studies and docking simulations. Negative value of change in free energy (∆G) -32 kJ/mol at 298 K showed thermodynamically favourable interaction and outweigh of entropic factor (T∆S = 230.76 ± 3 kJ for T = 298 K) over the enthalpic contribution (∆H = -261.99 kJ/mol) revealed an entropy-driven process. Binding of esomeprazole affected the helical structure of human serum albumin. Molecular docking studies (theoretical) shows the binding pocket of ESM at site1(IIA), which is in accordance with the experimental result. Further, the interface residues involved in the binding were analysed from the 2D diagram and ligplot of the docked complex.

Study of protein-protein interaction (PPI) network is fundamental to all cellular processes in living organisms. PPI study based on experimental techniques such as high-throughput assays, mass spectrometry is time-consuming and expensive. Computational techniques like molecular docking are restricted to availability of 3D protein structures and not suitable for large numbers of proteins. On the contrary Sequence-based PPI study is advantageous over the limitations of above techniques. Sequence-based PPI study has gained a broader scope with the help of deep learning techniques and large language model (LLM). In this study, we proposed AttnSeq-PPI, a deep learning framework based on two channels of hybrid attention mechanism. The protein sequences are embedded in high dimensional space using ProtT5 language model. In our model hybrid attention mechanism is designed by combining self-attention and cross-attention which enable the model to extract features from each protein with respect to the contextual features of both the proteins. The hybrid attention mechanism effectively captures long-range dependencies within protein sequences as well as interacting features of both proteins. The model was trained and evaluated based on 5-fold cross validation on intra-species and multi-species datasets. Additionally, four datasets of independent species and true PPI network datasets were used for validation. AttnSeq-PPI demonstrates superior generalization and outperforms existing models, achieving 99 % accuracy for both human and multi-species datasets. It can provide prediction of novel PPIs with fewer false negatives and higher precision. Additionally, we developed a web-based tool on AttnSeq-PPI accessible at https://compbiosysnbu.in/attnseqppi/ to provide PPI prediction based on protein sequences.

American tegumentary leishmaniasis (ATL) is primarily caused by Leishmania (Viannia) species such as Leishmania braziliensis, Leishmania panamensis, and Leishmania guyanensis, which show complex genomic organisation and stage-specific adaptations underlying their pathogenicity. Despite the availability of its reference genome, limitations in gene annotation persist due to the presence of hypothetical proteins, pseudogenes, and unrecognised coding regions. In this study, we used a proteogenomic approach integrating publicly available high-resolution mass spectrometry data with a custom six-frame translated genome database to refine the genome annotation of L. braziliensis strain MHOM/BR/75/M2904. Utilising stringent database-dependent searches with a 1 % false discovery rate, we identified many unique peptides, of which 1034 were genome search-specific peptides (GSSPs) mapping exclusively to unannotated genomic regions. These GSSPs facilitated the discovery of 56 novel protein-coding genes and the correction of 228 existing gene models, including N- and C-terminal extensions. Notably, several novel genes encode proteins with conserved domains such as membrane attack complex/perforin (MACPF), kinesin K39, and peptidase S9/S15, suggesting functional relevance in parasite biology. Our findings demonstrate the power of proteogenomics to uncover cryptic protein-coding regions and improve genome annotations beyond conventional predictions. This refined annotation enhances our understanding of L.braziliensis biology, providing a more accurate proteomic landscape that can inform studies on parasite virulence, host interaction, and potential therapeutic targets. The study underscores the importance of integrating proteomic evidence with genomic data to capture the full coding potential of kinetoplastid parasites, paving the way for improved diagnostics and interventions against leishmaniasis.

Scenedesmus quadricauda, a freshwater microalga, has gained attention for its high lipid accumulation potential. However, information on fatty acid (FA) biosynthesis pathways in Scenedesmus species remains limited. Biomass (1.010 gL) and lipid content (404 mgL) in S. quadricauda were found to be higher compared to other microalgal isolates under autotrophic nutrition. All biodiesel indices were found within the defined range of biodiesel (EN14214) and petro-diesel (EN590:2013) standards. The predominant fatty acid was palmitic acid (16:0), accounting for 33.201 % of the total. Further, homology study and 3D models of all subunits of S. quadricauda enzymes acetyl-CoA carboxylase (ACC) - the key enzyme of the FA biosynthetic pathway - identified distinct structural features. The biotin carboxylase (BC), biotin carboxyl carrier protein (BCCP), β-carboxyltransferases (β-CT) subunits of the heteromeric ACC of S. quadricauda showed homology with its eukaryotic counterparts, whereas the α -carboxyltransferases (α-CT) subunit showed homology with prokaryotic carboxyltransferase. In contrast, homologous enzymes in other Scenedesmus species were found to resemble prokaryotic forms exclusively. Conserved motifs such as the glycine-rich loop, ERYV motif, and AAAP motif were identified in the BC and BCCP enzymes. Malonyl-CoA:ACP transacylase (MAT) enzyme of S. quadricauda was of prokaryotic origin but showed structural divergence from its homologs in other Scenedesmus species. Fatty-acyl thioesterases (FAT) enzyme contained a duplication of two 4-hydroxybenzoyl-CoA thioesterase-like domains (4HBT). These unique sequences and binding sites in the fatty acid biosynthesis enzymes of S. quadricauda may contribute to the distinct regulation of carbon flux and lipid assembly compared to other species.

Protein aggregation plays a crucial role in various neurodegenerative diseases, including Huntington's disease. Understanding the factors influencing aggregation kinetics is essential for deciphering disease mechanisms. This research paper investigates the aggregation of a mutant Huntingtin protein (HD39Q) under various conditions, focusing on the impact of macromolecular crowding agents. The study employs multiple techniques, including fluorescence spectroscopy, circular dichroism, and nanoparticle tracking analysis, to characterize the aggregation kinetics and morphology. The results demonstrate that crowding agents significantly accelerate aggregation, with different agents exhibiting varying effects depending on their physicochemical properties. Fluorescence correlation spectroscopy provides insights into early-stage oligomerization. Confocal and scanning electron microscopy help visualize the resulting aggregates and fibrils. These findings contribute to a better understanding of how intracellular-like environments influence protein aggregation and provide valuable insights into the biophysical properties of aggregation-prone proteins.

De novo proteins represent a challenging frontier at the intersection of evolutionary biology and synthetic biology. Broadly, the term encompasses two distinct categories: naturally evolved de novo proteins, which arise from previously non-coding DNA, and synthetically designed de novo proteins, which are created from scratch through computational and experimental methods. This review provides an overview of the definitions, history, functional significance, and investigation methods for both categories. By examining potential challenges in current de novo protein research, this review highlights the growing convergence between natural evolutionary processes and rational protein engineering, reflecting their importance in biological discovery and human innovations.