Journal of Molecular Graphics and Modelling

The Na+/K+-ATPase (NKA) regulates ion balance in the kidney and influences cellular processes like proliferation and apoptosis through its signal transduction. The endogenous ligand 20-Hydroxyeicosatetraenoic acid (20-HETE) contributes to inflammation and fibrosis in chronic kidney disease (CKD) and inhibits NKA activity in renal tubules. However, the molecular mechanism of this interaction remains unclear. In this study, we used in-silico approach to investigate the potential interaction between 20-HETE and NKA. Various ligands, including known NKA ligands such as cardiotonic steroids (CTS), 20-HETE, and negative controls, were docked using rigid and Induced Fit Docking to predict the affinity of the ligands toward NKA. Binding free energy calculations with the Prime Molecular mechanics with generalized Born and surface area (Prime MM/GBSA) tools were used to confirm the involvement of key amino acids in ligand-receptor interactions. The docking analyses revealed that 20-HETE exhibited a binding affinity comparable to negative control, with some differences between rigid and induced fit docking. Binding free energy data highlighted key amino acids in the 20-HETE and NKA interaction. Interaction fingerprint and mutations such as Ala330Gly and Val329Ala significantly reduced binding free energy, while Thr804Ala showed a notable decrease, underscoring the potential importance of these amino acids in ligand stabilization. These findings provide computational evidence supporting potential direct interaction between 20-HETE and NKA and identify candidate residues for future experimental validation.

Pseudomonas aeruginosa, a Gram-negative opportunistic pathogen is well known for life-threatening acute infections among the human population. The bacterium can withstand most antibiotics by using their high levels of inherent and acquired resistance mechanisms such as Biofilm-EPS, Persistence, and Quorum sensing (QS). Owing to the importance of adaptive antibiotic multi-drug resistance of P. aeruginosa, the current investigation is aimed to explore the phytochemicals derived from mangrove plants as potential agents to control biofilm and drug resistance mechanisms through a multi-mechanistic computational approach. For identifying potential compounds and target, In-silico drug repurposing technique is implemented by docking/virtual screening of 49 phytochemical compounds against 18 proteins involved in the Persister Cell formation, QS, and EPS synthesis in P. aeruginosa which resulted the proteins RelA and SpoT (persistence), PqsA, and PqSR (QS), and PelA and PelB (EPS synthesis) and compounds Taraxerone and Taraxerol to be potential. The results of docking were well corroborated with MD simulations. These targets and compounds explored through in-silico approach, are found to target potential antimicrobial pathways involving EPS synthesis, persistence genes, and QS, aiming to enhance antibiotic efficacy. Further, this study could be reference for in-vivo and in-vitro investigations to evaluate the further effectiveness of the compounds and potentiality of the proteins for MDR therapeutics of P. aeruginosa.

The nuclear receptor superfamily is comprised of ligand-regulated transcription factors that contain an intrinsically disordered domain at the amino-terminal end, known as the N-terminal domain (NTD). While this poorly conserved domain is known to possess ligand-independent activation function (AF-1), few NTD functions are conserved between nuclear receptors (NRs). Identified roles in other receptors include androgen receptor (AR), estrogen receptor (ER) and mineralocorticoid receptor (MR). Here, we aim to define the function of the NTD of the farnesoid X receptor (FXR), a crucial regulator of lipid and bile acid metabolism. We show that the NTD engages in interdomain contact with other FXR domains. We also observe that the NTD interacts directly with coregulator proteins. Using mutagenesis, mammalian two-hybrid assays and molecular dynamics simulations, we identify and validate a novel SXXLF motif in the NTD which mediates interactions with both coregulators and the ligand binding domain. Mutation of the motif induces large changes in conformational and allosteric coupling in FXR. Our study identifies a new nuclear receptor-interacting motif that modulates the transcriptional activity of FXR. Graphical AbstractFXR-NTD regulates transcriptional activity through interdomain communication with the LBD and is also involved in co-activator recruitment. The SENLF motif is the first defined functional element within the FXR-NTD and mediates both NTD-LBD interaction and selective co-activator engagements to drive NTD-mediated transcriptional activity. O_FIG O_LINKSMALLFIG WIDTH=135 HEIGHT=200 SRC="FIGDIR/small/724725v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@5a37aorg.highwire.dtl.DTLVardef@2fa9e1org.highwire.dtl.DTLVardef@13a19daorg.highwire.dtl.DTLVardef@1775ed2_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundRising antimicrobial resistance rates, require new therapeutic approaches such as antimicrobial peptides (AMPs), which are part of the innate immune defense, as alternatives to antibiotics. In this study, we aim to unravel the antibacterial activity of human histone H1.2 peptide against Pseudomonas aeruginosa and its potential immune modulatory role. MethodsWe used a hemofiltrate peptide database for antimicrobial peptide prediction to identify novel human AMPs. Thirteen sequences of histone H1 were identified as putative AMPs, synthesized, and tested against bacterial ESKAPE pathogens in a radial diffusion assay. SYTOX green assay, electrophoretic mobility shift assay, and differential proteomics assays were conducted to determine the mode of action of H1.2 peptide fragment. A crystal violet assay was performed to evaluate the inhibition of biofilm formation. The cytotoxicity of the peptide was tested in LDH and Alamar assays. Finally, to visualize the contributions of H1.2 in NETs formation, scanning electron microscopy was performed. ResultsThe H1.2 peptide inhibited the growth of P. aeruginosa in a dose and pH-dependent manner without cytotoxicity towards mammalian THP-1 cells. It acts on intracellular targets to inhibit the growth of P. aeruginosa. STRING analysis from the differential proteomics assay showed that H1.2 targets the downregulation of proteins involved in the biogenesis of outer membrane proteins, including the folding and trafficking of outer membrane proteins across the cytoplasmic membrane. Scanning electron microscopy images showed that H1.2 forms NET-like structures capable of trapping and immobilizing P. aeruginosa. ConclusionThe characterized antimicrobial activity of H1.2 points to a role for human histone H1 fragments in innate immunity and may represent a promising approach for the development of novel antibacterial therapies. Graphical Summary O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/724237v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1778ddborg.highwire.dtl.DTLVardef@26430org.highwire.dtl.DTLVardef@ffbfa2org.highwire.dtl.DTLVardef@7e38ae_HPS_FORMAT_FIGEXP M_FIG C_FIG Sec transport and BAM complex system including chaperone proteins and quality control proteases are inhibited by H1.2 in Pseudomonas aeruginosa.Outer membrane proteins (OMPs) are synthesized in the cytoplasm and transported across the inner membrane via the Sec translocase, assisted by SecA/SecB or ribosomes. In the periplasm, they are escorted by chaperones such as SurA to the BAM complex for insertion into the outer membrane. Here, we show that H1.2, an antimicrobial peptide, targets membrane biogenesis in P. aeruginosa through downregulating Sec translocase (SecA/SecB and SecYEG), SurA, and BAM complex. Therefore, leading to improper transfer, folding and insertion of OMPs into the outer membrane. Normally, misfolded proteins are degraded by the protease MucD to prevent toxic aggregation in the bacteria. However, with H1.2 inhibiting MucD the proteotoxic stress is exacerbated, ultimately compromising bacterial homeostasis and viability. Figure created using BioRender.com.

WD40 domains share a widespread {beta}-propeller fold, and often act as versatile scaffold proteins. Despite their central role in organizing dynamic cellular complexes, the molecular and structural mechanisms of many WD40 proteins remain poorly understood. Among them, DCAF7, an ubiquitously expressed and essential gene in human, also encodes a highly conserved WD40 protein in eukaryotic organisms. It is known to interact with multiple and functionnally diverse partners to coordinates cellular activity of several protein kinases as well as transcriptional regulators, thereby modulating key cellular processes such as cell growth, differentiation, and transcriptional regulation. However, the precise mode of action of DCAF7 is unknown and its important divergence in sequence from better characterize WD40 prevent information transfer by similarity. Structural interactomic can reveal how protein-protein interactions (PPIs) occur within an organism and are essential for understanding biological functions and developing new therapeutic strategies. Using SLiMAn2, AlphaFold2/3 and PSSMsearch, we identified a conserved -helical short linear motif (SLiM) in several well known DCAF7 partners that binds to the top surface of its {beta}-propeller. This motif was subsequently used to generate a regular expression, to identify potential new direct binders across the DCAF7 meta-interactome and the human proteome. Domain-domain interactions were also predicted for some other partners. Finally, modeling of oligomeric complexes with such new hits reveals the structural basis of DCAF7 scaffolding, with links to neurodevelopmental disorders such as autism.

Chlamydia trachomatis is an obligate intracellular Gram-negative pathogen responsible for sexually transmitted infections and trachoma in humans. Although antibiotics are generally effective against acute infections, persistent chlamydial forms often exhibit reduced susceptibility during chronic infection. Chlamydia relies on its type III secretion system (T3SS) to inject effector proteins into host cells, making T3SS proteins attractive targets for antivirulence therapeutics. In this study, we employed an integrated computational pipeline to model and assemble the C. trachomatis T3SS constituent proteins. Template-based modeling using crystallographic structures of homologs from other Gram-negative bacteria revealed a highly conserved structural architecture despite low sequence identity (18-46%). Stereochemical validation confirmed high model quality, with most T3SS proteins exhibiting favorable protein-protein interactions (PPIs). Since the activity of the T3SS complex relies on extensive PPIs, we targeted these PPIs as a promising approach to attenuate bacterial virulence. CdsN, which functions as an ATPase of the T3SS, is a hexamer of which we targeted the dimerization interface. Structure-based virtual screening of compounds from the e-Drug3D and IMPPAT libraries against predicted hotspot residues and the identified druggable pocket at the CdsN dimeric interface, followed by ADMET screening, yielded three promising candidates: M Roflumilast (Drug ID: 1537), Elacestrant (Drug ID: 2081), and Tecovirimat (Drug ID: 1889). All three ligands formed thermodynamically stable complexes with the CdsN dimer, with Elacestrant demonstrating the most favourable binding free energy. This was also confirmed by 100 ns molecular dynamics simulation. This study provides new insights into the molecular architecture of C. trachomatis T3SS and identifies M Roflumilast, Elacestrant, and Tecovirimat as potential drug candidates against chlamydial infection. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/723290v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@1821599org.highwire.dtl.DTLVardef@1581baaorg.highwire.dtl.DTLVardef@1805e98org.highwire.dtl.DTLVardef@c25e56_HPS_FORMAT_FIGEXP M_FIG C_FIG

Cryptosporidium parvum is a protozoan parasite responsible for cryptosporidiosis, significantly threatening immunocompromised individuals, particularly HIV/AIDS patients, by causing severe diarrhea and potential mortality. Current treatments are largely ineffective, prompting investigations into new therapeutic options. This study evaluated two antiparasitic drugs: Mebendazole, used for helminth infections, and Artemisinin, used for malaria. The SKSR gene family encodes virulence factors in C. parvum, and Calcium-dependent protein kinase1 (CpCDPK1) regulates the life cycle of C. parvum; targeting these proteins may reduce growth and infection in hosts. In the current study, molecular docking was conducted taking Mebendazole and Artemisinin drugs as ligands, SKSR gene family and CpCDPK1 proteins as drug targets. Results with SKSR showed binding energy of -4.9 kcal/mol, -6.72 kcal/mol for Mebendazole and Artemisinin, respectively. Whereas, with CpCDPK1, the binding energies were -6.44 kcal/mol, -9.18 kcal/mol for Mebendazole and Artemisinin, respectively. Docking of Nitazoxanide (an in-use drug for C. parvum) with SKSR and CpCDPK1 revealed binding energies -4.2 kcal/mol, -4.81 kcal/mol, respectively. The stability of the proteins (targets) upon binding to the ligands was assessed by performing all-atom MD simulations for 100ns using the GROMACS package. No major variations were observed upon binding of Artemisinin and Mebendazole to SKSR and CpCDPK1. The findings of MD simulations imply that both proteins maintain their stability upon binding of Artemisinin and Mebendazole. Molecular Docking and MD simulation studies suggest that Artemisinin and Mebendazole are potential candidates for repurposing in the treatment of C. parvum infections, with recommendations for in vitro studies to validate these findings.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, can use host derived lipids as carbon and energy source for survival. Mammalian cell entry (Mce) associated membrane (Mam) proteins are important for the stability of lipid importing Mce complexes. Mtb has five homologs of Mam proteins referred as orphaned Mam (OmamA-E) proteins. A recent study suggested that OmamC (Rv1363c) is essential for the storage and utilization of lipids under starvation in Mtb. To understand the structure and interactions of OmamC, we generated a truncated soluble variant of OmamC (OmamC129-261). Here, we report on the challenges encountered during the crystallization and structure determination of OmamC129-261 and the strategies applied to overcome them. Despite the AlphaFold2 predicted model proving an initial molecular replacement solution, experimental phasing was necessary to determine the structure of OmamC129-261. Heat treatment of protein prior to crystallization setup removed partially unfolded protein present and played a critical role in enhancing the reproducibility and diffraction quality of OmamC129-261 crystals. Although reported earlier, it is not a widely used method. It is worth to try this method, especially, when faced with poor reproducibility and diffraction of crystals.

Coarse-grained structure-based models (CG-SBMs; or G[o] models) are simplified potential energy functions of biomolecules or biomolecular complexes that encode their structure. Molecular dynamics simulations of such SBMs have been successfully used to study long time-scale dynamics such as protein and RNA folding, and large conformational transitions of biomolecular complexes. SBMs have several advantages: (1) Their MD simulations are computationally inexpensive, making extensive sampling easily accessible to many researchers. (2) They are easy to modify and can be adapted for the specific biomolecular problem that needs to be investigated. However, the force-fields of SBMs are not usually included in commonly used biomolecular simulation packages resulting in a barrier to their use. Here, we present SuBMIT (Structure Based Models Input Toolkit; https://github.com/sglabncbs/submit), a toolkit for generating coarse-grained SBM input files for performing MD simulations with GROMACS and OpenMM/OpenSMOG. Simulations whose input files can be generated using the different flavors of CG-SBMs present in SuBMIT include the folding and conformational ensembles of proteins with intrinsically disordered regions, 3D-domain-swapping in proteins and the dynamics of RNA-protein assemblies (e.g., simple RNA viruses).

The Rho family of small GTPases plays a critical role in regulating actin cytoskeleton dynamics during endocytic processes in E. histolytica, including phagocytosis, pinocytosis, and trogocytosis. These proteins act as molecular switches, transitioning between inactive GDP-bound and active GTP-bound states, with guanine nucleotide exchange factors (GEFs) catalyzing this transition. Among the GEFs, EhFP10--a FYVE-domain-containing protein harbouring Dbl homology (DH) and pleckstrin homology (PH) domain was observed in phagocytosis along with seven functionally characterized Rho GTPases (EhRho1, EhRho2, EhRho4, EhRho5, EhRho6, EhRho8, and EhRho13). To study the specificity of FP10, a combination of GEF activity, binding affinity, and molecular dynamics simulations was used to characterize the interactions between EhFP10 and seven Rho GTPases systematically. The results revealed EhRho2 as the most specific and high-affinity interactor of EhFP10, with the highest nucleotide exchange rate and lowest dissociation constant (KD = 0.58 {micro}M). Structural modeling, sequence alignment, and interaction mapping further demonstrated that EhRho2 retains critical contact residues--such as Glu33, Arg4, and Leu69--that are variably absent in other isoforms, correlating with decreased GEF responsiveness. Molecular dynamics simulations and cross-correlation analyses supported the presence of a stable and coordinated interaction interface in the EhFP10-EhRho2 complex, distinguishing it from less active complexes. These findings indicate a highly selective GEF-GTPase module in E. histolytica, analogous to those in higher eukaryotes. The results uncover a potential regulatory mechanism specific to pathogenic amoebae and present EhFP10-EhRho2 as a novel therapeutic target for disrupting cytoskeleton-mediated processes crucial to virulence.

Acinetobacter baumannii is a leading multidrug-resistant critical priority pathogen in healthcare settings, where biofilm formation confers survival and antibiotic tolerance. Targeting virulence associated proteins offers an alternative to conventional bactericidal strategies. Here, the inner membrane anchored lipoprotein NLPA, implicated in biofilm associated adaptation, was studied as a putative anti-virulence target using an integrated in silico pipeline and complementing the computational findings. The Alpha fold-derived structure of NLPA served as the basis for virtual screening of approximately 1.6 million compounds, with subsequent prioritization guided by MM/GBSA calculated binding free energies to highlight the top promising candidates. Molecular dynamics simulations demonstrated stable NLPA ligand complexes, as indicated by equilibrated RMSD, low residue fluctuations in the binding region, and persistent interaction networks over time. Pharmacokinetic evaluation indicated that the compounds satisfied Lipinskis Rule of Five and had overall acceptable ADMET characteristics. Two compounds, NLPA-6 and NLPA-3, showed the most favourable predicted binding free energies, suggesting strong and stable interactions within the NLPA binding site. NLPA-3 was evaluated in vitro against A. baumannii to validate the computational outcomes. The compound displayed moderate antibacterial activity with a MIC of 125 g/mL and demonstrated 55.75% inhibition of biofilm formation at 4x MIC. In addition, in macrophage infection studies, NLPA-3 decreased intracellular bacterial survival to 19.25% at 50 g/mL, suggesting that it may disrupt virulence pathways linked to persistence. In whole, these findings identify promising NLPA targeting compounds and support the feasibility of NLPA as an anti-virulence target.

In any field, unquestioningly accepting artificial intelligence (AI) results should be considered bad practise. Here, we devised a comparative modelling-based strategy for validating protein structures that exploits the well-known observation that protein folds are far more conserved than protein sequences. We identify proteins with a similar fold to the AlphaFold-generated query protein and determine their structural alignment to the query. The hypothesis is that if the sequence alignment coincides with the structural alignment, then the structure is validated. The strategy is implemented on a helix-by-helix and strand-by-strand basis using a multi-template pairwise local profile alignment method that works well into the twilight zone. The method is illustrated by application to the transmembrane transporter PEPT1, for which the structure is known, and the S-deacylases ABHD13 and ABHD16A, for which only AI-generated models exist. ABHD16A is particularly challenging because a sequence alignment search with BLASTp does not reveal any structural homologues and therefore requires work with extremely remote homologues; however, both models are validated through this strategy and are stable during classical molecular dynamics simulations. The ability of the strategy to identify errors is assessed with reference to misaligned ABHD13 models and misfolded decoy proteins.

Precise site-specific drug design remains a challenge in structure-based drug discovery. Most existing approaches screen for ligands to target binding pockets on a protein surface based on static structures obtained from techniques such as X-ray, NMR, cryo-EM, and AlphaFold. However, the structure-function paradigm is, in reality, a structure-dynamics-function relationship that determines a proteins binding and activity. As such, drug screening or design without evaluating binding competition across the protein surface or considering the receptors dynamic, substrate-dependent conformational states is incomplete. Substrate-specific unique protein conformations are underexplored and offer novel opportunities for selective therapeutic targeting, though systematic workflows for identifying and exploiting such sites remain limited. Previously, we showed that collagen alters matrix metalloprotease-1 (MMP1) dynamics and that R405 is an allosteric residue on the MMP1 surface that exhibits strong dynamic correlations with its active site. Here, we present a substrate-specific allosteric drug-design framework that targets specific sites on a protein, using collagen-bound MMP1 as a model system. We determined the conformational dynamics of free and collagen-bound MMP1 using all-atom molecular dynamics (MD) simulations and categorized conformations into clusters of similar conformations. We then compared and identified unique conformations that occur only in collagen-bound MMP1 to design drugs against them using a machine-learning approach. The top three unique clusters were used to generate approximately 150,000 candidate compounds that were then screened against both the R405-centered region and all detectable binding pockets across the MMP1 surface. We have found several compounds that bind preferentially around R405 by at least 0.3 kcal/mol relative to competing sites across the surface. This strategy establishes a generalizable framework for designing ligands that preferentially target substrate-specific allosteric sites, providing new opportunities for precision therapeutics that modulate proteins in their biologically relevant functional states. Simple SummaryIn this paper, we establish a substrate-specific allosteric drug-design strategy that integrates all-atom molecular dynamics simulations, conformational clustering, machine-learning-based ligand design, and surface-wide binding-selectivity screening, using collagen-bound MMP1 as a model system. We show that collagen binding reshapes the conformational ensemble of MMP1, creating unique conformational states that are absent or inaccessible in the free enzyme. By identifying these substrate-specific conformations, generating ligands based on the corresponding dynamic fingerprints around the collagen-specific allosteric residue R405, and screening compounds across all binding pockets on the MMP1 surface, we demonstrate preferential targeting of the collagen-specific site relative to competing pockets. These results establish a generalizable framework for designing ligands that selectively recognize biologically relevant substrate-bound conformations rather than static protein structures alone. Substrate-specific allosteric targeting may enable selective modulation of individual protein functions while minimizing off-target interactions, providing new opportunities for precision therapeutics against dynamic protein systems.

Orthoflavivirus, such as West Nile Virus (WNV), dengue virus (DENV) and ZIKA virus (ZIKV), are globally distributed pathogens that pose substantial threats to human health. Currently, there are still no effective antiviral drugs for WNV or ZIKV. Despite the availability of two licensed DENV vaccines, their use remains limited due to potential risks, highlighting an urgent need for antiviral drug development. The highly conserved orthoflavivirus protease NS2B/NS3 is required for viral replication, making it a promising anti-flavivirus target. A major challenge, however, is the highly charged active site of this enzyme, which requires charged chemical matters with low bioavailability. An alternative and more attractive strategy is to target potential allosteric sites or folding intermediate states of the protease. In this work, we employ the topology-based coarse-grained G[o] modeling to explore the coupled binding and folding pathways of WNV NS2B/NS3 protease and study the effects of the widely used experimental construct with a G4SG4 linker between NS2B and NS3 on stability and folding. Our results provide a holistic conformational landscape of the protease binding and folding, including several key intermediate states. We find that the presence of the G4SG4 linker alters the folding pathways and destabilizes the NS2B C-terminus. The latter is consistent with experimental observations that the G4SG4 linked protease has lower activity and adopts an open state without the substrate in crystal structures. Together, these findings provide for the first time a complete picture of the binding and folding of the NS2B/NS3 protease and identify important folding intermediate states that could be targeted for allosteric antiviral drug development. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/722635v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@163c356org.highwire.dtl.DTLVardef@ad7b35org.highwire.dtl.DTLVardef@173ed8aorg.highwire.dtl.DTLVardef@1f026bf_HPS_FORMAT_FIGEXP M_FIG C_FIG

IntroductionMalaria is still a pressing global health challenge, especially in sub-Saharan Africa, where behavioral factors such as alcohol consumption may exacerbate its impact. The present study is aimed at investigating the pathogenesis of alcohol-exacerbated malaria in Plasmodium berghei-infected an animal model (mice). MethodsMale mice were separated into four treatment groups: control, alcohol control, P. berghei and P. berghei plus acute alcohol treatment groups. Animals were infected with malaria through intraperitoneal injection of P. berghei and an acute dose of ethanol (20% v/v) was introduced 48 hours post-infection. Parasitaemia was monitored using the Giemsa-stained thin blood smears. Haematological parameters were assessed using automated blood analyser. Liver function was evaluated by measuring serum levels of AST and ALT and cytokine profiles (TNF-, INF-{gamma}, IL-6, IL-1{beta}) were quantified using ELISA kits. ResultsResults show that acute alcohol intake led to a significant increase in parasitaemia in the P. berghei group (p<0.01). Haematological analysis revealed a significant (p<0.001) reduction in RBC count, haemoglobin levels, haematocrit percentage, platelet count and others in the P. berghei plus acute alcohol group. Liver enzyme assays revealed an elevated AST and ALT levels (p<0.001) in the P. berghei group. Cytokine analysis revealed a significant (p<0.01) upregulation of pro-inflammatory cytokines (TNF- INF-{gamma}, IL-1{beta} and IL-6), due to acute alcohol. These results suggest that alcohol exacerbates malaria pathogenesis by increasing parasitaemia, promoting immune dysregulation and liver injury, mediated by a shift toward a pro-inflammatory cytokine profile.

The standard set of 20 genetically-encoded amino acids (C20) exhibits a statistically non-random distribution in primarily two structurally-relevant physicochemical properties: hydrophobicity and molecular volume, and to a lesser extent charge. It remains an open question, however, whether evolutionary pressures similarly optimized the same alphabet for the distribution of functionally-relevant properties, such as reactivity. In this study, we used semi-empirical quantum chemistry simulations to calculate the highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO-LUMO) gaps for 84 xeno amino acids and constructed 10 million random 20-mer amino acid alphabets to determine where C20 fit amongst this background. The HOMO-LUMO gap measurements demonstrated that C20, similar to hydrophobicity and volume, also exhibits a non-random distribution. However, unlike hydrophobicity and volume, this distribution is non-random across an unevenly broad range. The results expand upon previous theory and suggest HOMO-LUMO gap energies as one synthetic biologists may consider when developing novel protein design tools or designing functional xeno amino acid alphabets. HighlightsO_LILifes amino acid alphabet is non-randomly distributed within an expanded computationally-generated chemistry space generated from large-scale quantum chemistry simulations. C_LIO_LIAmino acid alphabet coverage theory applies beyond structurally-relevant physicochemical descriptors to include functionally-relevant properties like reactivity as measured by frontier molecular orbitals C_LIO_LIFindings here provide a theoretical framework to guide the design of novel proteins and development of synthetic amino acid alphabets. C_LI

Bovine tuberculosis (TB), caused by Mycobacterium bovis, has become a global concern over the last two decades. Bovine TB primarily affects cattle, but other domestic livestock are also affected and it is more common in less developed and developing countries. The significant loss of livestock leads to trade restrictions and economic crises. Zoonotic potential of bovine TB raises health concerns for the public. Currently, no effective treatment is available and animal slaughtering is usually undertaken to reduce the burden of it in the environment. Antibiotic therapy can be used on animals living in captivity, but it is not reliable for herd or free-grazing animals. The BCG vaccine is another option available for treating the disease, but it shows limited efficacy in cattle. The prevention of bovine TB is a long-term goal that can only be accomplished by developing a more effective vaccine than BCG and designing new drugs. In this research, we propose therapeutic drug targets and vaccine for treating bovine TB. The conceptual framework for vaccine developed in this study uses a number of bioinformatics approaches to identify potential vaccine candidates and construct an in-silico epitope-based vaccine. Our holistic framework identified potential therapeutic candidates by directly analysing the proteome of TB bacterial strains. Specifically, we performed a comparative proteomic analysis of 11 Mycobacterium bovis strains to cover the diversity and identify conserved proteins among those strains for developing the bovine TB vaccine. An extensive reverse vaccinology and immunoinformatics analysis provided 26 highly immunogenic, non-toxic and non-allergenic epitopes (CTL epitopes-8, HTL epitopes-2 and B-cell epitopes-16) for Mycobacterium bovis required for three-dimensional structure construction of TB vaccine. The constructed epitope-based vaccine showed a potent interaction inside the host, thus generating efficient cell-mediated and humoral immune responses. Next, a framework based on a novel subtractive proteomic approach was developed for identifying bovine TB drug targets. We performed this approach on the 11 Mycobacterium bovis strains and identified nine drug targets that are conserved, essential, antigenic and have unique metabolic pathways in Mycobacterium bovis. These drug targets could further help investigate therapeutic drugs for the treatment of bovine TB. Several bioinformatics prediction tools were used together to ensure checks and balances, aiming to reduce the chance of errors and provide accurate results. The vaccine and drug targets developed in this study can be tested experimentally with confidence for further validation as therapeutics with the potential to eradicate bovine TB globally. The strategies implemented in the study are generic and can be used for other zoonotic infectious diseases. This study would be a game changer in the field of bovine tuberculosis treatment.

Fucoidans have been widely reported to show SARS-CoV-2 antiviral activity. In this study, we observed a striking difference in the inhibitory potency between two commercially available fucoidans: Fucus vesiculosus crude (Fvc) and pure (Fvp). SEC-MALS analysis revealed two molecular weight populations for Fvc (1098 kDa, 58.58 kDa) and one for Fvp (40.48 kDa). At micromolar concentrations of fucoidans, the binding affinities (KDs) of Fvc_1098 (223 nM) and Fvc_58 (4.27 {micro}M) for the amine-biotinylated SARS-CoV-2 receptor binding domain (RBD) were higher than that of Fvp (76.5 {micro}M). At nanomolar concentrations, binding was observed only to the Avi-tag-, but not amine-biotinylated RBDs, suggesting better accessibility of their binding sites. The association rates (kon) were faster for Fvc than for Fvp. Similarly, affinities of Fvc_1098 (23.4 nM) and Fvc_58 (4.48 M) for ACE2 were greater than that of Fvp (66.8 M), indicating that Fvc can bind directly to both RBD and ACE2. Fvc demonstrated enhanced inhibitory potency (IC50 = 58 g/mL) compared to Fvp (IC50 > 239 g/mL) in the pseudovirus entry assay and did not induce cytotoxicity in HEK293T cells. In conclusion, crude fucoidan with high fucose content and high molecular weight shows promising antiviral activity.

Structure Integration with Function, Taxonomy and Sequences (SIFTS) provides residue-level mappings between UniProt Knowledgebase sequences and Protein Data Bank structures and has historically been generated through internal Protein Data Bank in Europe (PDBe) pipelines. Here, PDBe-SIFTS is presented as a fully open-source, locally deployable implementation of this mapping framework. The pipeline combines fast, scalable sequence search using MMseqs2, an improved bounded scoring scheme for ranking candidate mappings, and residue-level mapping refinement based on backbone connectivity. PDBe-SIFTS is distributed as a Python package with command-line tools for 1) building a sequence search database, 2) identifying the best sequence-structure match, 3) one-to-one mapping at the residue level, and 4) generating SIFTS annotations in PDBx/mmCIF format. Benchmarking on the complete Protein Data Bank archive showed that MMseqs2 reduced archive-scale UniProtKB searches from hours with BLASTP to minutes, approximately 22-36 times faster, while curated mappings were recovered at top rank in 93.1% of cases. The remaining discrepancies mainly involved biologically ambiguous cases such as highly conserved proteins, chimeric constructs, or closely related orthologs. These results show that PDBe-SIFTS enables fast mapping, improving structural coherence in residue-level alignments while delivering the most up-to-date and accurate mappings, comparable to expert curation. Tool: https://github.com/PDBeurope/SIFTS Quick start notebook with example: https://github.com/PDBeurope/SIFTS/tree/master/notebooks Broader audience statementMatching protein sequences to their three-dimensional structures, and mapping annotations across both, is essential for understanding protein function, interactions, and molecular mechanisms. This integrated view enables richer interpretation of biological data and underpins advances in drug discovery, disease research, and protein engineering. PDBe-SIFTS provides an open and functional framework for structure-sequence mapping, allowing researchers and databases to run, inspect, and extend these mappings locally, while benefiting from faster searches, transparent scoring, and structurally informed residue-level alignments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/721839v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@5e6ea6org.highwire.dtl.DTLVardef@1b2754dorg.highwire.dtl.DTLVardef@1334f9forg.highwire.dtl.DTLVardef@1b083a1_HPS_FORMAT_FIGEXP M_FIG C_FIG

Orthohantaviruses cause severe human diseases including hemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS), with case fatality rates up to 40%. No FDA-approved therapeutics are currently available, highlighting urgent need for drug development following recent outbreak events. We systematically examined host protease dependencies in hantavirus replication, focusing on Signal Peptidase (SP) and Signal Peptide Peptidase (SPP) essential for viral glycoprotein maturation. Through comprehensive database mining and molecular docking analysis, we identified six potential protease inhibitors, with Compound E achieving the highest binding confidence score (-0.28) against SPP. Our analysis reveals that targeting host ER proteases represents a viable antiviral strategy, providing a systematic framework for protease-targeted antihantavirus drug development and identifying specific lead compounds for experimental validation.