Comparative protein structure modeling of genes and genomes

Notoginsenoside R1 improves intestinal microvascular functioning in sepsis by targeting Drp1-mediated mitochondrial quality imbalance

CONTEXT

Sepsis can result in critical organ failure, and notoginsenoside R1 (NGR1) offers mitochondrial protection.

OBJECTIVE

To determine whether NGR1 improves organ function and prognosis after sepsis by protecting mitochondrial quality.

MATERIALS AND METHODS

A sepsis model was established in C57BL/6 mice using cecum ligation puncture (CLP) and an in vitro model with lipopolysaccharide (LPS, 10 µg/mL)-stimulated primary intestinal microvascular endothelial cells (IMVECs) and then determine NGR1's safe dosage. Groups for each model were: in vivo-a control group, a CLP-induced sepsis group, and a CLP + NGR1 treatment group (30 mg/kg/d for 3 d); in vitro-a control group, a LPS-induced sepsis group, and a LPS + NGR1 treatment group (4 μM for 30 min). NGR1's effects on survival, intestinal function, mitochondrial quality, and mitochondrial dynamic-related protein (Drp1) were evaluated.

RESULTS

Sepsis resulted in approximately 60% mortality within 7 days post-CLP, with significant reductions in intestinal microvascular perfusion and increases in vascular leakage. Severe mitochondrial quality imbalance was observed in IMVECs. NGR1 (IC50 is 854.1 μM at 30 min) targeted Drp1, inhibiting mitochondrial translocation, preventing mitochondrial fragmentation and restoring IMVEC morphology and function, thus protecting against intestinal barrier dysfunction, vascular permeability, microcirculatory flow, and improving sepsis prognosis.

DISCUSSION AND CONCLUSIONS

Drp1-mediated mitochondrial quality imbalance is a potential therapeutic target for sepsis. Small molecule natural drugs like NGR1 targeting Drp1 may offer new directions for organ protection following sepsis. Future research should focus on clinical trials to evaluate NGR1's efficacy across various patient populations, potentially leading to novel treatments for sepsis.

Bipartite binding interface recruiting HP1 to chromosomal passenger complex at inner centromeres

Maintenance of ploidy depends on the mitotic kinase Aurora B, the catalytic subunit of the chromosomal passenger complex (CPC) whose proficient activity is supported by HP1 enriched at inner centromeres. HP1 is known to associate with INCENP of the CPC in a manner that depends on the PVI motif conserved across HP1 interactors. Here, we found that the interaction of INCENP with HP1 requires not only the PVI motif but also its C-terminally juxtaposed domain. Remarkably, these domains conditionally fold the β-strand (PVI motif) and the α-helix from a disordered sequence upon HP1 binding and render INCENP with high affinity to HP1. This bipartite binding domain termed SSH domain (Structure composed of Strand and Helix) is necessary and sufficient to attain a predominant interaction of HP1 with INCENP. These results identify a unique HP1-binding module in INCENP that ensures enrichment of HP1 at inner centromeres, Aurora B activity, and thereby mitotic fidelity.

A Novel Antigen Design Strategy to Isolate Single-Domain Antibodies that Target Human Nav1.7 and Reduce Pain in Animal Models

Genetic studies have identified the voltage-gated sodium channel 1.7 (Nav1.7) as pain target. Due to the ineffectiveness of small molecules and monoclonal antibodies as therapeutics for pain, single-domain antibodies (VHHs) are developed against the human Nav1.7 (hNav1.7) using a novel antigen presentation strategy. A 70 amino-acid peptide from the hNav1.7 protein is identified as a target antigen. A recombinant version of this peptide is grafted into the complementarity determining region 3 (CDR3) loop of an inert VHH in order to maintain the native 3D conformation of the peptide. This antigen is used to isolate one VHH able to i) bind hNav1.7, ii) slow the deactivation of hNav1.7, iii) reduce the ability of eliciting action potentials in nociceptors, and iv) reverse hyperalgesia in in vivo rat and mouse models. This VHH exhibits the potential to be developed as a therapeutic capable of suppressing pain. This novel antigen presentation strategy can be applied to develop biologics against other difficult targets such as ion channels, transporters and GPCRs.

Probing the formation of a hetero-dimeric membrane transport complex with dual in vitro and in silico mutagenesis

The reversible association of transmembrane helices is a fundamental mechanism in how living cells convey information and respond to physiological events. The cardiac calcium transport regulator phospholamban (PLN) is an example of a single-span transmembrane protein that populates a variety of reversible and competing oligomeric states. PLN primarily forms monomers and pentamers in the membrane, where the PLN pentamer is a storage form and the PLN monomer forms a hetero-dimeric inhibitory complex with SERCA. The binding affinity and free-energy of formation of the SERCA-PLN complex in a membrane have not been determined. As is the case for most transmembrane protein interactions, measuring these quantities experimentally is extremely challenging. In this study, we estimated binding affinities by employing in silico alchemical free-energy calculations for all PLN transmembrane alanine substitutions in a membrane bilayer. The binding affinities were calculated separately for the SERCA-PLN complex, a PLN monomer, and a PLN pentamer and compared to in vitro functional measurements of SERCA regulation by the PLN alanine substitutions. Initially, the changes in SERCA inhibition by PLN alanine substitutions were compared to the changes in free energy for the SERCA-PLN complex formed from the PLN monomer. However, the functional data for the PLN alanine substitutions were better explained by the formation of the SERCA-PLN complex directly from the PLN pentamer. This finding points to an inhibitory mechanism favoring conformational selection of SERCA and the interaction of a PLN pentamer with SERCA for 'delivery' of a PLN monomer to the inhibitory site. The implications of these findings suggest that the energetics of helix exchange between homo- and hetero-oligomeric signaling complexes is favored over an intermediate involving a free monomeric helix in the membrane bilayer.

Olanzapine manipulates neuroactive signals and may onset metabolic disturbances

Olanzapine is one of the most prescribed atypical antipsychotics to treat psychiatric illness and is associated with weight gain and metabolic disturbance. The present study investigated the olanzapine-regulated metabolic pathways using functional enrichent analysis including binding affinity with G-protein-coupled receptors (GPCRs). Proteins modulated by olanzapine were retrieved from SwissTargetPrediction, DIGEP-Pred, and BindingDB and then enriched in Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) to assess molecular function, biological process, and cellular components including Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We used homology modeling to improve the 3D structure for GPCR synapse proteins including dopamine, serotonin, muscarinic, and histamine receptors which were then optimized using molecular dynamics (MD) simulations. The protein-olanzapine binding mechanisms for different GPCR binders were evaluated using molecular docking; later refined by MD simulations. Binding mechanism of olanzapine with D2, 5HT1A, 5HT2A, 5HT2B, 5HT2C, M1, and M2 receptors were created using homology modeling and optimized using MD simulations. In target identification, it was observed that olanzapine majority targeted G-protein coupled receptors. Further, enrichment analysis identified around 76% of the total genes regulated in molecular function, biological process, and cellular components were common including KEGG pathways. Moreover, it was observed that olanzapine had a major potency over the neurotransmitter synapse including neuroactive signals . Olanzapine-induced weight gain and metabolic alterations could be due to the deregulation of multiple synapses like dopamine, serotonin, muscarinic, and histamine at the feeding center followed by cGMP-PKG, cAMP, and PI3K-Akt signaling pathways. HIGHLIGHTSOlanzapine is used in the management of psychiatric illnesses.Olanzapine causes disturbance in lipids and glucosehomeostasis and manipulates energy expenditure.Olanzapine-induced weight gain may occur due to the deregulation of the multiple synapse and cGMP-PKG, cAMP, and PI3K-Akt signaling pathwayCommunicated by Ramaswamy H. Sarma.

BANMF-S: a blockwise accelerated non-negative matrix factorization framework with structural network constraints for single cell imputation

MOTIVATION

Single cell RNA sequencing (scRNA-seq) technique enables the transcriptome profiling of hundreds to ten thousands of cells at the unprecedented individual level and provides new insights to study cell heterogeneity. However, its advantages are hampered by dropout events. To address this problem, we propose a Blockwise Accelerated Non-negative Matrix Factorization framework with Structural network constraints (BANMF-S) to impute those technical zeros.

RESULTS

BANMF-S constructs a gene-gene similarity network to integrate prior information from the external PPI network by the Triadic Closure Principle and a cell-cell similarity network to capture the neighborhood structure and temporal information through a Minimum-Spanning Tree. By collaboratively employing these two networks as regularizations, BANMF-S encourages the coherence of similar gene and cell pairs in the latent space, enhancing the potential to recover the underlying features. Besides, BANMF-S adopts a blocklization strategy to solve the traditional NMF problem through distributed Stochastic Gradient Descent method in a parallel way to accelerate the optimization. Numerical experiments on simulations and real datasets verify that BANMF-S can improve the accuracy of downstream clustering and pseudo-trajectory inference, and its performance is superior to seven state-of-the-art algorithms.

AVAILABILITY

All data used in this work are downloaded from publicly available data sources, and their corresponding accession numbers or source URLs are provided in Supplementary File Section 5.1 Dataset Information. The source codes are publicly available in Github repository https://github.com/jiayingzhao/BANMF-S.

BUB1B monoallelic germline variants contribute to prostate cancer predisposition by triggering chromosomal instability

BACKGROUND

Prostate cancer (PrCa) is the most frequently diagnosed cancer in men. Variants in known moderate- to high-penetrance genes explain less than 5% of the cases arising at early-onset (< 56 years) and/or with familial aggregation of the disease. Considering that BubR1 is an essential component of the mitotic spindle assembly checkpoint, we hypothesized that monoallelic BUB1B variants could be sufficient to fuel chromosomal instability (CIN), potentially triggering (prostate) carcinogenesis.

METHODS

To unveil BUB1B as a new PrCa predisposing gene, we performed targeted next-generation sequencing in germline DNA from 462 early-onset/familial PrCa patients and 1,416 cancer patients fulfilling criteria for genetic testing for other hereditary cancer syndromes. To explore the pan-cancer role of BUB1B, we used in silico BubR1 molecular modeling, in vitro gene-editing, and ex vivo patients' tumors and peripheral blood lymphocytes.

RESULTS

Rare BUB1B variants were found in ~ 1.9% of the early-onset/familial PrCa cases and in ~ 0.6% of other cancer patients fulfilling criteria for hereditary disease. We further show that BUB1B variants lead to decreased BubR1 expression and/or stability, which promotes increased premature chromatid separation and, consequently, triggers CIN, driving resistance to Taxol-based therapies.

CONCLUSIONS

Our study shows that different BUB1B variants may uncover a trigger for CIN-driven carcinogenesis, supporting the role of BUB1B as a (pan)-cancer predisposing gene with potential impact on genetic counseling and treatment decision-making.

Enhancement of the structure and biochemical function of cyclomaltodextrinase from the Anoxybacillus flavithermus ZNU-NGA with site-directed mutagenesis

This study was conducted to examine the role of the central domain of cyclomaltodextrinase in terms of stability, substrate specificity, becoming dodecameric form, and enzyme activity. To this end, H403R/L309V double-point mutation and T280Q single-point mutation were performed at the central domain and (β/α)8-barrel. The results indicated that the activity of the H403R/L309V mutant at the optimal pH and temperature increased by about 25% and 40%, respectively. Plus, the irreversible thermal inactivation of the H403R/L309V mutant at 60 °C and 160 min was approximately twice of the enzyme without mutation. Both mutants underwent significant structural change relative to the wild enzyme and subsequently a significant catalytic activity. However, the catalytic efficiency (kcat/Km) of the H403R/L309V mutant increased in the presence of beta- and gamma-cyclomaltodextrin substrates compared to the wild enzyme and T280Q mutant. As a result, by applying the L309V mutant and given the smaller size of the valine, leucine spatial inhibition in the wild protein seems to decline, and also it facilitates the substrate access to active site amino acids. Moreover, as gamma substrate is larger, eliminating the effect of spatial inhibition on this substrate has a greater effect on improving the catalytic activity of this enzyme.

Developing phytocompound-based new drugs against multi-drug-resistant Staphylococcus aureus

Staphylococcus aureus, a prevalent component of the human microbiota, is associated with skin infections to life-threatening diseases, presenting challenges in treatment options and necessitating the development of effective treatments. This study integrated computational and in vitro approaches to identify promising phytocompounds with therapeutic potential. Staphopain B emerged as a target protein for its role in immune evasion, exhibiting stability during molecular dynamic simulation (MDS) with a root mean square deviation value of 2.376 Å. Screening 115 phytocompounds with antibacterial properties from the PubChem database identified 12 with drug-like properties, nine of which showed superior binding affinity to Staphopain B compared to a commercial antibiotic, doxycycline (-7.8 kcal mol-1). Notably, epoxyazadiradione and nimbolide displayed higher estimated free energy of binding scores (-7.91 and -7.93 kcal mol-1, respectively), indicating strong protein-ligand interactions. The root mean square fluctuation values for epoxyazadiradione and nimbolide were 1.097 and 1.034 Å, respectively, which was confirmed through MDS. Crude ethanolic extracts (100% and 70%) of neem (Azadirachta indica) leaves demonstrated narrow inhibition against the bacteria in comparison to doxycycline in the disc-diffusion assay. This study underscores the potential of phytocompounds as therapeutic agents against S. aureus; however, further in vitro experiments and testing of the phytocompounds in vivo are required.

Characterization of thiamine pyrophosphokinase of vitamin B1 biosynthetic pathway as a drug target of Leishmania donovani

Vitamin B1 is an essential cofactor for enzymes involved in the metabolism of carbohydrates, particularly Transketolases. These enzymes are amenable to therapeutic interventions because of their specificity. In the final step of the Vitamin B1 biosynthesis pathway, Thiamine Pyrophosphokinase (TPK) converts thiamin into its active form, Thiamin Pyrophosphate (TPP), allowing researchers to investigate the functional importance of this enzyme and the pathway's dispensability in Leishmania donovani, a protozoan parasite that causes visceral leishmaniasis. In this study, various in silico, biochemical, biophysical, and cellular assays-based experiments have been conducted to identify and characterize LdTPK, and to provide a sound platform for the discovery of potential LdTPK inhibitors. LdTPK structural modelling ensured high protein quality. Oxythiamine and pyrithiamine were found to bind well with LdTPK with considerable binding energies, and MD simulation-based experiments indicated the stability of the complexation. Additionally, LdTPK1 was found to activate ROS defense in amastigotes, and its inhibition using oxythiamine and pyrithiamine led to the growth inhibition of L. donovani promastigotes and intracellular amastigotes. These findings highlight LdTPK as a promising target for the development of new anti-leishmanial agents. An in-depth analysis of the enzymes involved in TPP biosynthesis in L. donovani has the potential to yield novel therapeutic strategies for Leishmaniasis.Communicated by Ramaswamy H. Sarma.

Genetic characterization of the first Deltacoronavirus from wild birds around Qinghai Lake

Deltacoronavirus, widely distributed among pigs and wild birds, pose a significant risk of cross-species transmission, including potential human epidemics. Metagenomic analysis of bird samples from Qinghai Lake, China in 2021 reported the presence of Deltacoronavirus. A specific gene fragment of Deltacoronavirus was detected in fecal samples from wild birds at a positive rate of 5.94% (6/101). Next-generation sequencing (NGS) identified a novel Deltacoronavirus strain, which was closely related to isolates from the United Arab Emirates (2018), China (2022), and Poland (2023). Subsequently the strain was named A/black-headed gull/Qinghai/2021(BHG-QH-2021) upon confirmation of the Cytochrome b gene of black-headed gull in the sample. All available genome sequences of avian Deltacoronavirus, including the newly identified BHG-QH-2021 and 5 representative strains of porcine Deltacoronavirus (PDCoV), were classified according to ICTV criteria. In contrast to Coronavirus HKU15, which infects both mammals and birds and shows the possibility of cross-species transmission from bird to mammal host, our analysis revealed that BHG-QH-2021 is classified as Putative species 4. Putative species 4 has been reported to infect 5 species of birds but not mammals, suggesting that cross-species transmission of Putative species 4 is more prevalent among birds. Recombination analysis traced BHG-QH-2021 origin to dut148cor1 and MW01_1o strains, with MW01_1o contributing the S gene. Surprisingly, SwissModle prediction showed that the optimal template for receptor-binding domain (RBD) of BHG-QH-2021 is derived from the human coronavirus 229E, a member of the Alphacoronavirus, rather than the anticipated RBD structure of PDCoV of Deltacoronavirus. Further molecular docking analysis revealed that substituting the loop 1-2 segments of HCoV-229E significantly enhanced the binding capability of BHG-QH-2021 with human Aminopeptidase N (hAPN), surpassing its native receptor-binding domain (RBD). Most importantly, this finding was further confirmed by co-immunoprecipitation experiment that loop 1-2 segments of HCoV-229E enable BHG-QH-2021 RBD binding to hAPN, indicating that the loop 1-2 segment of the RBD in Putative species 4 is a probable key determinant for the virus ability to spill over into humans. Our results summarize the phylogenetic relationships among known Deltacoronavirus, reveal an independent putative avian Deltacoronavirus species with inter-continental and inter-species transmission potential, and underscore the importance of continuous surveillance of wildlife Deltacoronavirus.

Machine learning guided rational design of a non-heme iron-based lysine dioxygenase improves its total turnover number

Highly selective C-H functionalization remains an ongoing challenge in organic synthetic methodologies. Biocatalysts are robust tools for achieving these difficult chemical transformations. Biocatalyst engineering has often required directed evolution or structure-based rational design campaigns to improve their activities. In recent years, machine learning has been integrated into these workflows to improve the discovery of beneficial enzyme variants. In this work, we combine a structure-based machine-learning algorithm with classical molecular dynamics simulations to down select mutations for rational design of a non-heme iron-dependent lysine dioxygenase, LDO. This approach consistently resulted in functional LDO mutants and circumvents the need for extensive study of mutational activity before-hand. Our rationally designed single mutants purified with up to 2-fold higher yields than WT and displayed higher total turnover numbers (TTN). Combining five such single mutations into a pentamutant variant, LPNYI LDO, leads to a 40% improvement in the TTN (218±3) as compared to WT LDO (TTN = 160±2). Overall, this work offers a low-barrier approach for those seeking to synergize machine learning algorithms with pre-existing protein engineering strategies.

Targeting SHP2 Cryptic Allosteric Sites for Effective Cancer Therapy

SHP2, a pivotal component downstream of both receptor and non-receptor tyrosine kinases, has been underscored in the progression of various human cancers and neurodevelopmental disorders. Allosteric inhibitors have been proposed to regulate its autoinhibition. However, oncogenic mutations, such as E76K, convert SHP2 into its open state, wherein the catalytic cleft becomes fully exposed to its ligands. This study elucidates the dynamic properties of SHP2 structures across different states, with a focus on the effects of oncogenic mutation on two known binding sites of allosteric inhibitors. Through extensive modeling and simulations, we further identified an alternative allosteric binding pocket in solution structures. Additional analysis provides insights into the dynamics and stability of the potential site. In addition, multi-tier screening was deployed to identify potential binders targeting the potential site. Our efforts to identify a new allosteric site contribute to community-wide initiatives developing therapies using multiple allosteric inhibitors to target distinct pockets on SHP2, in the hope of potentially inhibiting or slowing tumor growth associated with SHP2.

Structural modeling and gene expression analysis of phosvitinless vitellogenin (vgc) in the Indian freshwater murrel, Channa punctatus (Bloch, 1793)

Vitellogenin (Vg) is a female-specific egg-yolk precursor protein, synthesized in the liver of fish in response to estrogens. In the present study, complete gene of phosvitinless vitellogenin (vgc) was sequenced, its 3D structure was predicted and validated by web-based softwares. The complete nucleotide sequence of vgc was 4126 bp which encodes for 1272 amino acids and showed the presence of three conserved domains viz. LPD_N, DUF1943 and DUF1944. The retrieved amino acid sequence of VgC protein was subjected to in silico analysis for understanding the structural and functional properties of protein. mRNA levels of multiple vg genes have also been quantified during annual reproductive cycle employing qPCR. A correlation has been observed between seasonal changes in gonadosomatic index with estradiol levels and hepatic expression of three types of vg genes (vga, vgb, vgc) during ovarian cycle of murrel. During preparatory phase, when photoperiod and temperature are low; low titre of E2 in blood induces expression of vgc gene. A rapid increase in the levels of E2 favours induction of vgb and vga genes in liver of murrel during early pre-spawning phase when photoperiod is long and temperature is high in nature. These results suggest that among three vitellogenin proteins, VgC is synthesized earlier than VgA and VgB during oogenesis.

Deciphering protein-mediated underwater adhesion in an invasive biofouling ascidian: Discovery, validation, and functional mechanism of an interfacial protein

Discovering macromolecules and understanding the associated mechanisms involved in underwater adhesion are essential for both studying the fundamental ecology of benthos in aquatic ecosystems and developing biomimetic adhesive materials in industries. Here, we employed quantitative proteomics to assess protein expression variations during the development of the distinct adhesive structure - stolon in the model fouling ascidian, Ciona robusta. We found 16 adhesive protein candidates with increased expression in the stolon, with ascidian adhesive protein 1 (AAP1) being particularly rich in adhesion-related signal peptides, amino acids, and functional domains. Western blot and immunolocalization analyses confirmed the prominent AAP1 signals in the mantle, tunic, stolon, and adhesive footprints, indicating the interfacial role of this protein. Surface coating and atomic force microscopy experiments verified AAP1's adhesion to diverse materials, likely through the specific electrostatic and hydrophobic amino acid interactions with various substrates. In addition, molecular docking calculations indicated the AAP1's potential for cross-linking via hydrogen bonds and salt bridges among Von Willebrand factor type A domains, enhancing its adhesion capability. Altogether, the newly discovered interfacial protein responsible for permanent underwater adhesion, along with the elucidated adhesion mechanisms, are expected to contribute to the development of biomimetic adhesive materials and anti-fouling strategies. STATEMENT OF SIGNIFICANCE: Discovering macromolecules and studying their associated mechanisms involved in underwater adhesion are essential for understanding the fundamental ecology of benthos in aquatic ecosystems and developing innovative bionic adhesive materials in various industries. Using multidisciplinary analytical methods, we identified an interfacial protein - Ascidian Adhesive Protein 1 (AAP1) from the model marine fouling ascidian, Ciona robusta. The interfacial functions of AAP1 are achieved by electrostatic and hydrophobic interactions, and the Von Willebrand factor type A domain-based cross-linking likely enhances AAP1's interfacial adhesion. The identification and validation of the interfacial functions of AAP1, combined with the elucidation of adhesion mechanisms, present a promising target for the development of biomimetic adhesive materials and the formulation of effective anti-fouling strategies.

Spontaneous Dimerization and Distinct Packing Modes of Transmembrane Domains in Receptor Tyrosine Kinases

The insulin receptor (IR) and the insulin-like growth factor-1 receptor (IGF1R) are homodimeric transmembrane glycoproteins that transduce signals across the membrane on binding of extracellular peptide ligands. The structures of IR/IGF1R fragments in apo and liganded states have revealed that the extracellular subunits of these receptors adopt Λ-shaped configurations to which are connected the intracellular tyrosine kinase (TK) domains. The binding of peptide ligands induces structural transitions in the extracellular subunits leading to potential dimerization of transmembrane domains (TMDs) and autophosphorylation in TKs. However, the activation mechanisms of IR/IGF1R, especially the role of TMDs in coordinating signal-inducing structural transitions, remain poorly understood, in part due to the lack of structures of full-length receptors in apo or liganded states. While atomistic simulations of IR/IGF1R TMDs showed that these domains can dimerize in single component membranes, spontaneous unbiased dimerization in a plasma membrane having physiologically representative lipid composition has not been observed. We address this limitation by employing coarse-grained (CG) molecular dynamics simulations to probe the dimerization propensity of IR/IGF1R TMDs. We observed that TMDs in both receptors spontaneously dimerized independent of their initial orientations in their dissociated states, signifying their natural propensity for dimerization. In the dimeric state, IR TMDs predominantly adopted X-shaped configurations with asymmetric helical packing and significant tilt relative to the membrane normal, while IGF1R TMDs adopted symmetric V-shaped or parallel configurations with either no tilt or a small tilt relative to the membrane normal. Our results suggest that IR/IGF1R TMDs spontaneously dimerize and adopt distinct dimerized configurations.

Exploring Novel Antimalarial Compounds Targeting Plasmodium falciparum Enoyl-ACP Reductase: Computational and Experimental Insights

Malaria, caused by Plasmodium protozoa with Plasmodium falciparum as the most virulent species, continues to pose significant health challenges. Despite the availability of effective antimalarial drugs, the emergence of resistance has heightened the urgency for developing novel therapeutic compounds. In this study, we investigated the enoyl-ACP reductase enzyme of P. falciparum (PfENR) as a promising target for antimalarial drug discovery. Through a comprehensive analysis, we conducted a comparative evaluation of two lead compounds, LD1 (CID: 44405336, lead compounds 1) and LD2 (CID: 72703246, lead compounds 2), obtained from the PubChem/NCBI ligand database, to serve as reference molecules in the identification of potential derivatives using virtual screening assays. Among the newly identified candidates, Ligand 1 (LG1) and Ligand 2 (LG2) exhibited intriguing characteristics and underwent further investigation through docking and molecular dynamics simulations. Ligand 1 (LG1) demonstrated interactions similar to LD1, including hydrogen bonding with Asp218, while Ligand 2 (LG2) displayed superior binding energy comparable to LD1 and LD2, despite lacking hydrogen bonding interactions observed in the control compounds triclosan and its derivative 7-(4-chloro-2-hydroxyphenoxy)-4-methyl-2H-chromen-2-one (CHJ). Following computational validation using the MM/GBSA method to estimate binding free energy, commercially acquired LG1 and LG2 ligands were subjected to in vitro testing. Inhibition assays were performed to evaluate their potential as PfENR inhibitors alongside triclosan as a control compound. LG1 exhibited no inhibitory effects, while LG2 demonstrated inhibitory effects like triclosan. In conclusion, this study contributes valuable insights into developing novel antimalarial drugs by identifying LG2 as a potential ligand and employing a comprehensive approach integrating computational and experimental methodologies.

Exploring the activation mechanism of metabotropic glutamate receptor 2

Homomeric dimerization of metabotropic glutamate receptors (mGlus) is essential for the modulation of their functions and represents a promising avenue for the development of novel therapeutic approaches to address central nervous system diseases. Yet, the scarcity of detailed molecular and energetic data on mGlu2 impedes our in-depth comprehension of their activation process. Here, we employ computational simulation methods to elucidate the activation process and key events associated with the mGlu2, including a detailed analysis of its conformational transitions, the binding of agonists, Gi protein coupling, and the guanosine diphosphate (GDP) release. Our results demonstrate that the activation of mGlu2 is a stepwise process and several energy barriers need to be overcome. Moreover, we also identify the rate-determining step of the mGlu2's transition from the agonist-bound state to its active state. From the perspective of free-energy analysis, we find that the conformational dynamics of mGlu2's subunit follow coupled rather than discrete, independent actions. Asymmetric dimerization is critical for receptor activation. Our calculation results are consistent with the observation of cross-linking and fluorescent-labeled blot experiments, thus illustrating the reliability of our calculations. Besides, we also identify potential key residues in the Gi protein binding position on mGlu2, mGlu2 dimer's TM6-TM6 interface, and Gi α5 helix by the change of energy barriers after mutation. The implications of our findings could lead to a more comprehensive grasp of class C G protein-coupled receptor activation.

A High-Quality Data Set of Protein-Ligand Binding Interactions Via Comparative Complex Structure Modeling

High-quality protein-ligand complex structures provide the basis for understanding the nature of noncovalent binding interactions at the atomic level and enable structure-based drug design. However, experimentally determined complex structures are scarce compared with the vast chemical space. In this study, we addressed this issue by constructing the BindingNet data set via comparative complex structure modeling, which contains 69,816 modeled high-quality protein-ligand complex structures with experimental binding affinity data. BindingNet provides valuable insights into investigating protein-ligand interactions, allowing visual inspection and interpretation of structural analogues' structure-activity relationships. It can also be used for evaluating machine-learning-based scoring functions. Our results indicate that machine learning models trained on BindingNet could reduce the bias caused by buried solvent-accessible surface area, as we previously found for models trained on the PDBbind data set. We also discussed strategies to improve BindingNet and its potential utilization for benchmarking the molecular docking methods and ligand binding free energy calculation approaches. The BindingNet complements PDBbind in constructing a sufficient and unbiased protein-ligand binding data set and is freely available at http://bindingnet.huanglab.org.cn.

Structural insights into the semiquinone form of human Cytochrome P450 reductase by DEER distance measurements between a native flavin and a spin labelled non-canonical amino acid

The flavoprotein Cytochrome P450 reductase (CPR) is the unique electron pathway from NADPH to Cytochrome P450 (CYPs). The conformational dynamics of human CPR in solution, which involves transitions from a "locked/closed" to an "unlocked/open" state, is crucial for electron transfer. To date, however, the factors guiding these changes remain unknown. By Site-Directed Spin Labelling coupled to Electron Paramagnetic Resonance spectroscopy, we have incorporated a non-canonical amino acid onto the flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD) domains of soluble human CPR, and labelled it with a specific nitroxide spin probe. Taking advantage of the endogenous FMN cofactor, we successfully measured for the first time, the distance distribution by DEER between the semiquinone state FMNH• and the nitroxide. The DEER data revealed a salt concentration-dependent distance distribution, evidence of an "open" CPR conformation at high salt concentrations exceeding previous reports. We also conducted molecular dynamics simulations which unveiled a diverse ensemble of conformations for the "open" semiquinone state of the CPR at high salt concentration. This study unravels the conformational landscape of the one electron reduced state of CPR, which had never been studied before.

Molecular dynamics of the human RhD and RhAG blood group proteins

Introduction: Blood group antigens of the RH system (formerly known as "Rhesus") play an important role in transfusion medicine because of the severe haemolytic consequences of antibodies to these antigens. No crystal structure is available for RhD proteins with its partner RhAG, and the precise stoichiometry of the trimer complex remains unknown. Methods: To analyse their structural properties, the trimers formed by RhD and/or RhAG subunits were generated by protein modelling and molecular dynamics simulations were performed. Results: No major differences in structural behaviour were found between trimers of different compositions. The conformation of the subunits is relatively constant during molecular dynamics simulations, except for three large disordered loops. Discussion: This work makes it possible to propose a reasonable stoichiometry and demonstrates the potential of studying the structural behaviour of these proteins to investigate the hundreds of genetic variants relevant to transfusion medicine.

Oleic Acid Could Act as a Channel Blocker in the Inhibition of nAChR: Insights from Molecular Dynamics Simulations

The activation of the muscular nicotinic acetylcholine receptor (nAChR) produces the opening of the channel, with the consequent increase in the permeability of cations, triggering an excitatory signal. Free fatty acids (FFA) are known to modulate the activity of the receptor as noncompetitive antagonists, acting at the membrane-AChR interface. We present molecular dynamics simulations of a model of nAChR in a desensitized closed state embedded in a lipid bilayer in which distinct membrane phospholipids were replaced by two different monounsaturated FFA that differ in the position of a double bond. This allowed us to detect and describe that the cis-18:1ω-9 FFA were located at the interface between the transmembrane segments of α2 and γ subunits diffused into the channel lumen with the consequent potential ability to block the channel to the passage of ions.

Design and functional characterization of Salmo salar TLR5 agonist peptides derived from high mobility group B1 acidic tail

Toll-like receptor 5 (TLR5) responds to the monomeric form of flagellin and induces the MyD88-depending signaling pathway, activating proinflammatory transcription factors such as NF-κB and the consequent induction of cytokines. On the other hand, HMGB1 is a highly conserved non-histone chromosomal protein shown to interact with and activate TLR5. The present work aimed to design and characterize TLR5 agonist peptides derived from the acidic tail of Salmo salar HMGB1 based on the structural knowledge of the TLR5 surface using global molecular docking platforms. Peptide binding poses complexed on TLR5 ectodomain model from each algorithm were filtrated based on docking scoring functions and predicted theoretical binding affinity of the complex. Circular dichroism spectra were recorded for each peptide selected for synthesis. Only intrinsically disordered peptides (6W, 11W, and SsOri) were selected for experimental functional assay. The functional characterization of the peptides was performed by NF-κB activation assays, RT-qPCR gene expression assays, and Piscirickettsia salmonis challenge in SHK-1 cells. The 6W and 11W peptides increased the nuclear translation of p65 and phosphorylation. In addition, the peptides induced the expression of genes related to the TLR5 pathway activation, pro- and anti-inflammatory response, and differentiation and activation of T lymphocytes towards phenotypes such as TH1, TH17, and TH2. Finally, it was shown that the 11W peptide protects immune cells against infection with P. salmonis bacteria. Overall, the results indicate the usefulness of novel peptides as potential immunostimulants in salmonids.

Escherichia coli FtsZ molecular dynamics simulations

Earlier molecular dynamics studies of the FtsZ protein revealed that the protein has high intrinsic flexibility which the crystal structures cannot reveal. However, the input structure in these simulation studies was based on the available crystal structure data and therefore, the effect of the C-terminal Intrinsically Disordered Region (IDR) of FtsZ could not be observed in any of these studies. Recent investigations have revealed that the C-terminal IDR is crucial for FtsZ assembly in vitro and Z ring formation in vivo. Therefore, in this study, we simulated FtsZ with the IDR. Simulations of the FtsZ monomer in different nucleotide bound forms (without nucleotide, GTP, GDP) were performed. In the conformations of FtsZ monomer with GTP, GTP binds variably with the protein. Such a variable interaction with the monomer has not been observed in any previous simulation studies of FtsZ and not observed in crystal structures. We found that central helix bends towards the C-terminal domain in the GTP bound form, hence, making way for polymerization. A nucleotide dependent shift/rotation of the C-terminal domain was observed in simulation time averaged structures.Communicated by Ramaswamy H. Sarma.

Comprehensive structural and functional analysis of hVEGFR1: Insights into phosphorylation, molecular interactions, and potential inhibitors through docking and dynamics simulations

Vascular Endothelial Growth Factor Receptor 1 (VEGFR1), is an enzyme with tyrosine kinase activity that plays a pivotal role in angiogenesis, the process of new blood vessel formation. This receptor is of significant clinical importance as it is implicated in various cancers, particularly non-small cell lung cancer (NSCLC), where its dysregulation leads to uncontrolled cell growth through ligand-induced phosphorylation. While commercially available drugs target VEGFR1, their prolonged use often leads to drug resistance and the emergence of mutations in cancer patients. To address these challenges, researchers have identified the human tyrosine kinase (hTK) domain of VEGFR1 as a potential therapeutic marker for lung malignancies. The 3D crystal structure of the hTK domain, obtained from Protein Data Bank (PDB ID: 3HNG), has provided vital structural insights of hVEGFR1. This study has revealed variations within the hVEGFR1 tyrosine kinase domain, distinguishing between regions associated with phosphorylase kinase and transferase activities. We identified numerous potential phosphorylation sites within the TK domain, shedding light on the protein's regulation and signaling possible. Detailed molecular interaction analyses have elucidated the binding forces between lead molecules and hVEGFR1, including hydrogen bonds, electrostatic, hydrophobic, and π-sigma interactions. The stability observed during molecular dynamics simulations further underscores the biological relevance of these interactions. Furthermore, docked complexes has highlighted localized structural fluctuations, offering insight into potential allosteric effects and dynamic conformational changes induced by lead molecules. These findings not only provide a comprehensive characterization of hVEGFR1 but also pave the way for the development of targeted therapies. Eventually, this study has the potential in identifying drug to combat diseases associated with hVEGFR1 dysregulation, including cancer and angiogenesis-related disorders, contributing to effective treatment strategies.

Predicting Mutational Effects on Ca2+-Activated Chloride Conduction of TMEM16A Based on a Simulation Study

The dysfunction and defects of ion channels are associated with many human diseases, especially for loss-of-function mutations in ion channels such as cystic fibrosis transmembrane conductance regulator mutations in cystic fibrosis. Understanding ion channels is of great current importance for both medical and fundamental purposes. Such an understanding should include the ability to predict mutational effects and describe functional and mechanistic effects. In this work, we introduce an approach to predict mutational effects based on kinetic information (including reaction barriers and transition state locations) obtained by studying the working mechanism of target proteins. Specifically, we take the Ca2+-activated chloride channel TMEM16A as an example and utilize the computational biology model to predict the mutational effects of key residues. Encouragingly, we verified our predictions through electrophysiological experiments, demonstrating a 94% prediction accuracy regarding mutational directions. The mutational strength assessed by Pearson's correlation coefficient is -0.80 between our calculations and the experimental results. These findings suggest that the proposed methodology is reliable and can provide valuable guidance for revealing functional mechanisms and identifying key residues of the TMEM16A channel. The proposed approach can be extended to a broad scope of biophysical systems.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Antioxidant, antibacterial, and molecular docking of methyl ferulate and oleic acid produced by Aspergillus pseudodeflectus AUMC 15761 utilizing wheat bran

Secondary metabolites (SMs) are the primary source of therapeutics and lead chemicals in medicine. They have been especially important in the creation of effective cures for conditions such as cancer, malaria, bacterial and fungal infections, neurological and cardiovascular problems, and autoimmune illnesses. In the present study, Aspergillus pseudodeflectus AUMC 15761 was demonstrated to use wheat bran in solid state fermentation (SSF) at optimum conditions (pH 7.0 at 30 °C after 10 days of incubation and using sodium nitrate as a nitrogen source) to produce methyl ferulate and oleic acid with significant antioxidant and antibacterial properties. Gas chromatography-mass spectrometry (GC-MS) analysis of the crude methanol extract revealed eleven peaks that indicated the most common chemical components. Purification of methyl ferulate and oleic acid was carried out by column chromatography, and both compounds were identified by in-depth spectroscopic analysis, including 1D and 2D NMR and HR-ESI-MS. DPPH activity increased as the sample concentration increased. IC50 values of both compounds obtained were 73.213 ± 11.20 and 104.178 ± 9.53 µM, respectively. Also, the MIC value for methyl ferulate against Bacillus subtilis and Staphylococcus aureus was 0.31 mg/mL, while the corresponding MIC values for oleic acid were 1.25 mg/mL and 0.62 mg/mL for both bacterial strains, respectively. Molecular modeling calculations were carried out to reveal the binding mode of methyl ferulate and oleic acid within the binding site of the crucial proteins of Staphylococcus aureus. The docking results were found to be well correlated with the experimental data.

Molecular Dynamics Simulation of an Iron(III) Binding Site on the Fc Domain of IgG1 Relevant for Visible Light-Induced Protein Fragmentation

Molecular dynamics simulations were employed to investigate the interaction between Fe(III) and an iron-binding site composed of THR259, ASP252, and GLU261 on the Fc domain of an IgG1. The goal was to provide microscopic mechanistic information for the photochemical, iron-dependent site-specific oxidative fragmentation of IgG1 at THR259 reported in our previous paper. The distance between Fe(III) and residues of interest as well as the binding pocket size was examined for both protonated and deprotonated THR259. The Fe(III) binding free energy (ΔG) was estimated by using an umbrella sampling approach. The pKa shift of the THR259 hydroxyl group caused by the presence of nearby Fe(III) was estimated based on a thermodynamic cycle. The simulation results show that Fe(III) resides inside the proposed binding pocket and profoundly changes the pocket configuration. The ΔG values indicate that the pocket possesses a strong binding affinity for Fe(III). Furthermore, Fe(III) profoundly lowers the pKa value of the THR259 hydroxyl group by 5.4 pKa units.

Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A3 Receptor

A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.

Homology modeling, virtual screening, molecular docking, and ADME approaches to identify a potent agent targeting NK2R protein

Neurokinin/tachykinin receptors are classified as the G-protein coupled receptor superfamily. The neurokinin 2 receptor (NK2R) is widely expressed in different tissues. NK2R is associated with a range of biological events, such as inflammation, smooth muscle contraction, intestinal motor functions, and asthma. Despite these diverse activities, no approved drugs targeting NK2R have been developed yet. Our study focuses on finding potential inhibitors for NK2R using virtual screening, molecular docking, and ADME (absorption, distribution, metabolism, and excretion) approaches. We used a homology modeling approach and AlphaFold DB to obtain the three-dimensional structure of mouse and human NK2R proteins, respectively. The homology model of NK2R was predicted using MODELLER v10.3 and further refined and validated using the 3Drefine tool and RAMPAGE server, respectively. Molecular docking was performed using a library of 910 structurally similar molecules to four NK1R antagonists: aprepitant, casopitant, fosaprepitant, and rolapitant. Molecular docking revealed six small molecules that displayed high Chemscore fitness scores, and binding energies with desirable ligand-NK2R interactions. The evaluation of the in silico ADME profile, solubility, and permeability of the ligand molecules has revealed that the small molecules are potentially nontoxic and have the chance of exhibiting biological activity after oral administration. Further experimental studies (in vitro and in vivo assays) are required to evaluate the effectiveness of these inhibitors as therapeutic targets.

Genomic surveillance of omicron B.1.1.529 SARS-CoV-2 and its variants between December 2021 and March 2023 in Tamil Nadu, India-A state-wide prospective longitudinal study

A state-wide prospective longitudinal investigation of the genomic surveillance of the omicron B.1.1.529 SARS-CoV-2 variant and its sublineages in Tamil Nadu, India, was conducted between December 2021 and March 2023. The study aimed to elucidate their mutational patterns and their genetic interrelationship in the Indian population. The study identified several unique mutations at different time-points, which likely could attribute to the changing disease characteristics, transmission, and pathogenicity attributes of omicron variants. The study found that the omicron variant is highly competent in its mutating potentials, and that it continues to evolve in the general population, likely escaping from natural as well as vaccine-induced immune responses. Our findings suggest that continuous surveillance of viral variants at the global scenario is warranted to undertake intervention measures against potentially precarious SARS-CoV-2 variants and their evolution.

Characterization, modeling, and anticancer activity of L.arginase production from marine Bacillus licheniformis OF2

BACKGROUND

L-arginase, is a powerful anticancer that hydrolyzes L-arginine to L-ornithine and urea. This enzyme is widely distributed and expressed in organisms like plants, fungi, however very scarce from bacteria. Our study is based on isolating, purifying, and screening the marine bacteria that can produce arginase.

RESULTS

The highest arginase producing bacteria will be identified by using microbiological and molecular biology methods as Bacillus licheniformis OF2. Characterization of arginase is the objective of this study. The activity of enzyme was screened, and estimated beside partial sequencing of arginase gene was analyzed. In silico homology modeling was applied to generate the protein's 3D structure, and COACH and COFACTOR were applied to determine the protein's binding sites and biological annotations based on the I-TASSER structure prediction. The purified enzyme was undergone an in vitro anticancer test.

CONCLUSIONS

L-arginase demonstrated more strong anti-cancer cells with an IC50 of 21.4 ug/ml in a dose-dependent manner. L-arginase underwent another investigation for its impact on the caspase 7 and BCL2 family of proteins (BCL2, Bax, and Bax/Bcl2). Through cell arrest in the G1/S phase, L-arginase signals the apoptotic cascade, which is supported by a flow cytometry analysis of cell cycle phases.

Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method

Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named "Deep Learning-Ramachandran Plot-Molecular Dynamics Simulation (DL-RP-MDS)" to evaluate the deleteriousness of MLH1 missense VUS. The method extracts protein structural information by using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, then combines the variation data with an unsupervised learning model composed of auto-encoder and neural network classifier to identify the variants causing significant change in protein structure. In this report, we applied the method to classify 447 MLH1 missense VUS. We predicted 126/447 (28.2%) MLH1 missense VUS were deleterious. Our study demonstrates that DL-RP-MDS is able to classify the missense VUS based solely on their impact on protein structure.

HTLV-1 reverse transcriptase homology model provides structural basis for sensitivity to existing nucleoside/nucleotide reverse transcriptase inhibitors

The human T-lymphotropic virus type 1 (HTLV-1) infects millions of people globally and is endemic to various resource-limited regions. Infections persist for life and are associated with increased susceptibility to opportunistic infections and severe diseases including adult T cell leukemia/lymphoma and HTLV-1-associated myelopathy-tropical spastic paraparesis. No HTLV-1-specific anti-retrovirals have been developed and it is unclear whether existing anti-retrovirals developed for treatment of human immunodeficiency virus (HIV) have efficacy against HTLV-1. To understand the structural basis for therapeutic binding, homology modelling and machine learning were used to develop a structural model of the HTLV-1 reverse transcriptase. With this, molecular docking experiments using a panel of FDA-approved inhibitors of viral reverse transcriptases to assess their capacity for binding, and in turn, inhibition. Importantly, nucleoside/nucleotide reverse transcriptase inhibitor but not non-nucleoside reverse transcriptase inhibitors were predicted to bind the HTLV-1 reverse transcriptase, with similar affinity to HIV-1 reverse transcriptase. By strengthening the rationale for clinical testing of therapies such as tenofovir alafenamide, zidovudine, lamivudine, and azvudine for treatment of HTLV-1, this study has demonstrated the power of in silico structural biology approaches in drug design and therapeutic testing.

Molecular Modeling Techniques and In-Silico Drug Discovery

Molecular modeling is the technique to determine the overall structure of an unknown molecule, be it a small one or a macromolecule. The technique encompasses the method of screening ligand libraries for the development of new candidate drug molecules. All these aspects have become an essential topic of research. This field is truly interdisciplinary and finds its applications in almost all fields of life science research. In this chapter, an overview of the protocol associated with molecular modeling techniques will be discussed.

Amalgamated Pharmacoinformatics Study to Investigate the Mechanism of Xiao Jianzhong Tang against Chronic Atrophic Gastritis

BACKGROUND

Traditional Chinese medicine (TCM) Xiao Jianzhong Tang (XJZ) has a favorable efficacy in the treatment of chronic atrophic gastritis (CAG). However, its pharmacological mechanism has not been fully explained.

OBJECTIVE

The purpose of this study was to find the potential mechanism of XJZ in the treatment of CAG using pharmacocoinformatics approaches.

METHODS

Network pharmacology was used to screen out the key compounds and key targets, MODELLER and GNNRefine were used to repair and refine proteins, Autodock vina was employed to perform molecular docking, Δ Lin_F9XGB was used to score the docking results, and Gromacs was used to perform molecular dynamics simulations (MD).

RESULTS

Kaempferol, licochalcone A, and naringenin, were obtained as key compounds, while AKT1, MAPK1, MAPK14, RELA, STAT1, and STAT3 were acquired as key targets. Among docking results, 12 complexes scored greater than five. They were run for 50ns MD. The free binding energy of AKT1-licochalcone A and MAPK1-licochalcone A was less than -15 kcal/mol and AKT1-naringenin and STAT3-licochalcone A was less than -9 kcal/mol. These complexes were crucial in XJZ treating CAG.

CONCLUSION

Our findings suggest that licochalcone A could act on AKT1, MAPK1, and STAT3, and naringenin could act on AKT1 to play the potential therapeutic effect on CAG. The work also provides a powerful approach to interpreting the complex mechanism of TCM through the amalgamation of network pharmacology, deep learning-based protein refinement, molecular docking, machine learning-based binding affinity estimation, MD simulations, and MM-PBSA-based estimation of binding free energy.

Exploring molecular determinants and pharmacokinetic properties of IgG1-scFv bispecific antibodies

Bispecific antibodies (BsAbs) capable of recognizing two distinct epitopes or antigens offer promising therapeutic options for various diseases by targeting multiple pathways. The favorable pharmacokinetic (PK) properties of monoclonal antibodies (mAbs) are crucial, as they directly influence patient safety and therapeutic efficacy. For numerous mAb therapeutics, optimization of neonatal Fc receptor (FcRn) interactions and elimination of unfavorable molecular properties have led to improved PK properties. However, many BsAbs exhibit unfavorable PK, which has precluded their development as drugs. In this report, we present studies on the molecular determinants underlying the distinct PK profiles of three IgG1-scFv BsAbs. Our study indicated that high levels of nonspecific interactions, elevated isoelectric point (pI), and increased number of positively charged patches contributed to the fast clearance of IgG1-scFv. FcRn chromatography results revealed specific scFv-FcRn interactions that are unique to the IgG1-scFv, which was further supported by molecular dynamics (MD) simulation. These interactions likely stabilize the BsAb FcRn interaction at physiological pH, which in turn could disrupt FcRn-mediated BsAb recycling. In addition to the empirical observations, we also evaluated the impact of in silico properties, including pI differential between the Fab and scFv and the ratio of dipole moment to hydrophobic moment (RM) and their correlation with the observed clearance. These findings highlight that the PK properties of BsAbs may be governed by novel determinants, owing to their increased structural complexity compared to immunoglobulin G (IgG) 1 antibodies.

Interaction of Tau with G-Protein-Coupled Purinergic P2Y12 Receptor by Molecular Docking and Molecular Dynamic Simulation

Alzheimer's disease, a progressive neurological disorder, is characterized by the accumulation of neurofibrillary tangles and senile plaques by Tau and amyloid-β, respectively, in the brain microenvironment. The misfolded protein aggregates interact with several components of neuronal and glial cells such as membrane lipids, receptors, transporters, enzymes, cytoskeletal proteins, etc. Under pathological conditions, Tau interacts with several G-protein-coupled receptors (GPCRs), which undergoes either receptor signaling or desensitization followed by internalization of the protein complex. The purinergic GPCR, P2Y12 which is expressed in microglial cells, plays a key role in its activation and migration. Microglial cells sense and migrate to the site of injury aided by P2Y12 receptor that interacts with ADP released from damaged cells. P2Y12 receptor also interacts with misfolded Tau accumulated at the extracellular space and promotes receptor-mediated internalization. Immunocolocalization and co-immunoprecipitation studies demonstrated the interaction of Tau species with the P2Y12 receptor. Later, in-silico analyses were carried out with the repeat domain of Tau (TauRD), which has been identified as the interacting partner of P2Y12 receptor by in-vitro studies. Molecular docking and molecular dynamics simulation studies show the stability and the type of interaction in TauRD-receptor complex. Tau interaction with P2Y12 receptor plays a significant role in maintaining the active state of microglia which could lead to neuroinflammation and neuronal damage in AD brain. Hence, blocking P2Y12-Tau interaction and P2Y12-mediated Tau internalization in microglial cells could be possible therapeutic strategies in downregulating the severity of neuroinflammation in AD.

Machine Learning Methods in Protein-Protein Docking

An exponential increase in the number of publications that address artificial intelligence (AI) usage in life sciences has been noticed in recent years, while new modeling techniques are constantly being reported. The potential of these methods is vast-from understanding fundamental cellular processes to discovering new drugs and breakthrough therapies. Computational studies of protein-protein interactions, crucial for understanding the operation of biological systems, are no exception in this field. However, despite the rapid development of technology and the progress in developing new approaches, many aspects remain challenging to solve, such as predicting conformational changes in proteins, or more "trivial" issues as high-quality data in huge quantities.Therefore, this chapter focuses on a short introduction to various AI approaches to study protein-protein interactions, followed by a description of the most up-to-date algorithms and programs used for this purpose. Yet, given the considerable pace of development in this hot area of computational science, at the time you read this chapter, the development of the algorithms described, or the emergence of new (and better) ones should come as no surprise.

Insights into unique features of Drosophila CYP4G enzymes

The cytochrome P450 enzymes of the CYP4G subfamily are some of the most intriguing insect P450s in terms of structure and function. In Drosophila, CYP4G1 is highly expressed in the oenocytes and is the last enzyme in the biosynthesis of cuticular hydrocarbons, while CYP4G15 is expressed in the brain and is of unknown function. Both proteins have a CYP4G-specific and characteristic amino acid sequence insertion corresponding to a loop between the G and H helices whose function is unclear. Here we address these enigmatic structural and functional features of Drosophila CYP4Gs. First, we used reverse genetics to generate D. melanogaster strains in which all or part of the CYP4G-specific loop was removed from CYP4G1. We showed that the full loop was not needed for proper folding of the P450, but it is essential for function, and that just a short stretch of six amino acids is required for the enzyme's ability to make hydrocarbons. Second, we confirmed by immunocytochemistry that CYP4G15 is expressed in the brain and showed that it is specifically associated with the cortex glia cell subtype. We then expressed CYP4G15 ectopically in oenocytes, revealing that it can produce of a blend of hydrocarbons, albeit to quantitatively lower levels resulting in only a partial rescue of CYP4G1 knockdown flies. The CYP4G1 structural variants studied here should facilitate the biochemical characterization of CYP4G enzymes. Our results also raise the question of the putative role of hydrocarbons and their synthesis by cortex glial cells.

Synthesis of a tetranitrosyl iron complex with unique structure and properties as an inhibitor of phosphodiesterases

A novel neutral tetranitrosyl iron complex {[Fe(H2O)4]2+[FeR2(NO)2]22-}·4H2O (1) with R = 5-(3-pyridyl)-4H-1,2,4-triazole-3-thiolyls (C7H5N4S), which is a supramolecular ensemble, has been synthesized and studied. As follows from X-ray diffraction analysis, this is an octahedral Fe2+complex (Lewis acid) with two monoanionic dinitrosyl groups [FeR2(NO)2]- (Lewis base) and 4 water molecules as the ligands. As follows from Mössbauer spectra, the coordinating Fe2+ ion is in a low-spin state S = 0, and the dinitrosyl Fe+ ion is in a low-spin state S = 1/2. According to the data of EPR spectroscopy, mass-spectrometry and amperometry, complex 1 in solution forms dinitrosyl particles of [Fe(C7H6N4S-H)2(NO)2]- composition, which are responsible for NO generation. In addition, complex 1 was shown to be a 5-6 times more efficient phosphodiesterase (PDE) inhibitor at 5 × 10-5 M and 10-4 M concentrations than its thioligand. Probable binding sites of the [FeR2(NO)2]- ligand for the bovine PDE1B model have been determined by molecular docking and quantum-chemical calculations.

Structural and Dynamic Changes of Nucleosome upon GATA3 Binding

Pioneer factors, which can directly bind to nucleosomes, have been considered to change chromatin conformations. However, the binding impact on the nucleosome is little known. Here, we show how the pioneer factor GATA3 binds to nucleosomal DNA and affects the conformation and dynamics of nucleosomes by using a combination of SAXS, molecular modeling, and molecular dynamics simulations. Our structural models, consistent with the SAXS data, indicate that only one of the two DNA binding domains, N- and C-fingers, of GATA3 binds to an end of the DNA in solution. Our MD simulations further showed that the other unbound end of the DNA increases the fluctuation and enhances the DNA dissociation from the histone core when the N-finger binds to a DNA end, a site near the entry or exit of the nucleosome. However, this was not true for the binding of the C-finger that binds to a location about 15 base pairs distant from the DNA end. In this case, DNA dissociation occurred on the bound end. Taken together, we suggest that the N-finger and C-finger bindings of GATA3 commonly enhance DNA dissociation at one of the two DNA ends (the bound end for the C-finger binding and the unbound end for the N-finger binding), leading to triggering a conformational change in the chromatin.

Characterization of the RofA regulon in the pandemic M1global and emergent M1UK lineages of Streptococcus pyogenes

The standalone regulator RofA is a positive regulator of the pilus locus in Streptococcus pyogenes. Found in only certain emm genotypes, RofA has been reported to regulate other virulence factors, although its role in the globally dominant emm1 S. pyogenes is unclear. Given the recent emergence of a new emm1 (M1UK) toxigenic lineage that is distinguished by three non-synonymous SNPs in rofA, we characterized the rofA regulon in six emm1 strains that are representative of the two contemporary major emm1 lineages (M1global and M1UK) using RNAseq analysis, and then determined the specific role of the M1UK-specific rofA SNPs. Deletion of rofA in three M1global strains led to altered expression of 14 genes, including six non-pilus locus genes. In M1UK strains, deletion of rofA led to altered expression of 16 genes, including nine genes that were unique to M1UK. Only the pilus locus genes were common to the RofA regulons of both lineages, while transcriptomic changes varied between strains even within the same lineage. Although introduction of the three SNPs into rofA did not impact gene expression in an M1global strain, reversal of three SNPs in an M1UK strain led to an unexpected number of transcriptomic changes that in part recapitulated transcriptomic changes seen when deleting RofA in the same strain. Computational analysis predicted that interactions with a key histidine residue in the PRD domain of RofA would differ between M1UK and M1global. RofA is a positive regulator of the pilus locus in all emm1 strains but effects on other genes are strain- and lineage-specific, with no clear, common DNA binding motif. The SNPs in rofA that characterize M1UK may impact regulation of RofA; whether they alter phosphorylation of the RofA PRD domain requires further investigation.

One enzyme, many faces: urease is also canatoxin

Ureases catalyze the hydrolysis of urea into carbamate and ammonia. Well-conserved proteins, most plant ureases are hexamers of a single chain subunit, like the most abundant isoform of the jack bean (Canavalia ensiformis) urease (JBU). Canatoxin (CNTX) was originally isolated from these seeds as a neurotoxic protein, and later characterized as an isoform of JBU with lower molecular mass and enzyme activity. Inactive CNTX oligomers form upon storage and stabilization of CNTX was achieved by treatment with low concentration of formaldehyde, avoiding its oligomerization. Here, nano-LC-MS/MS-based peptide analysis of CNTX revealed 804 amino acids identical to those of JBU's sequence (840 amino acids). De novo sequencing of CNTX revealed 15 different peptides containing substitution of amino acid residues, denoting CNTX as a product of a paralog gene of JBU. The MS/MS analysis of formaldehyde-treated CNTX showed that amino acid residues located at the trimer-trimer interface of JBU's hexamer were modified. The data confirmed that CNTX is an isoform of JBU and elucidated that stabilization by formaldehyde treatment occurs by modification of amino acids at the protein's surface that prevents the formation of the hexamer and of higher molecular mass inactive aggregates. HIGHLIGHTSCanatoxin (CNTX) is an isoform of jack bean urease (JBU, hexamer of 90 kDa chains)MS/MS sequencing of CNTX showed 804 amino acids identical in JBU (840 residues)Formaldehyde treatment of CNTX stabilizes its toxicity and avoids oligomerizationModified amino acid residues in CNTX are at the trimer-trimer interface of JBUCommunicated by Ramaswamy H. Sarma.

Comprehensive assessment of protein loop modeling programs on large-scale datasets: prediction accuracy and efficiency

Protein loops play a critical role in the dynamics of proteins and are essential for numerous biological functions, and various computational approaches to loop modeling have been proposed over the past decades. However, a comprehensive understanding of the strengths and weaknesses of each method is lacking. In this work, we constructed two high-quality datasets (i.e. the General dataset and the CASP dataset) and systematically evaluated the accuracy and efficiency of 13 commonly used loop modeling approaches from the perspective of loop lengths, protein classes and residue types. The results indicate that the knowledge-based method FREAD generally outperforms the other tested programs in most cases, but encountered challenges when predicting loops longer than 15 and 30 residues on the CASP and General datasets, respectively. The ab initio method Rosetta NGK demonstrated exceptional modeling accuracy for short loops with four to eight residues and achieved the highest success rate on the CASP dataset. The well-known AlphaFold2 and RoseTTAFold require more resources for better performance, but they exhibit promise for predicting loops longer than 16 and 30 residues in the CASP and General datasets. These observations can provide valuable insights for selecting suitable methods for specific loop modeling tasks and contribute to future advancements in the field.

Designer Adaptor Proteins for Functional Conversion of Peptides to Small-Molecule Ligands toward In-Cell Catalytic Protein Modification

Peptides are privileged ligands for diverse biomacromolecules, including proteins; however, their utility is often limited due to low membrane permeability and in-cell instability. Here, we report peptide ligand-inserted eDHFR (PLIED) fusion protein as a universal adaptor for targeting proteins of interest (POI) with cell-permeable and stable synthetic functional small molecules (SFSM). PLIED binds to POI through the peptide moiety, properly orienting its eDHFR moiety, which then recruits trimethoprim (TMP)-conjugated SFSM to POI. Using a lysine-acylating BAHA catalyst as SFSM, we demonstrate that POI (MDM2 and chromatin histone) are post-translationally and synthetically acetylated at specific lysine residues. The residue-selectivity is predictable in an atomic resolution from molecular dynamics simulations of the POI/PLIED/TMP-BAHA (MTX was used as a TMP model) ternary complex. This designer adaptor approach universally enables functional conversion of impermeable peptide ligands to permeable small-molecule ligands, thus expanding the in-cell toolbox of chemical biology.

Characterization on the oncogenic effect of the missense mutations of p53 via machine learning

Dysfunctions caused by missense mutations in the tumour suppressor p53 have been extensively shown to be a leading driver of many cancers. Unfortunately, it is time-consuming and labour-intensive to experimentally elucidate the effects of all possible missense variants. Recent works presented a comprehensive dataset and machine learning model to predict the functional outcome of mutations in p53. Despite the well-established dataset and precise predictions, this tool was trained on a complicated model with limited predictions on p53 mutations. In this work, we first used computational biophysical tools to investigate the functional consequences of missense mutations in p53, informing a bias of deleterious mutations with destabilizing effects. Combining these insights with experimental assays, we present two interpretable machine learning models leveraging both experimental assays and in silico biophysical measurements to accurately predict the functional consequences on p53 and validate their robustness on clinical data. Our final model based on nine features obtained comparable predictive performance with the state-of-the-art p53 specific method and outperformed other generalized, widely used predictors. Interpreting our models revealed that information on residue p53 activity, polar atom distances and changes in p53 stability were instrumental in the decisions, consistent with a bias of the properties of deleterious mutations. Our predictions have been computed for all possible missense mutations in p53, offering clinical diagnostic utility, which is crucial for patient monitoring and the development of personalized cancer treatment.

Binding Modes of Carnostatine, Homocarnosine, and Ophidine to Human Carnosinase 1

Carnosine (CAR), anserine (ANS), homocarnosine (H-CAR), and ophidine (OPH) are histidine-containing dipeptides that show a wide range of therapeutic properties. With their potential physiological effects, these bioactive dipeptides are considered as bioactive food components. However, such dipeptides display low stability due to their rapid degradation by human serum carnosinase 1 (CN1). A dimeric CN1 hydrolyzes such histidine-containing compounds with different degrees of reactivities. A selective CN inhibitor, carnostatine (CARN), was reported to effectively inhibit CN's activity. To date, the binding mechanisms of CAR and ANS have been recently reported, while no clear information about H-CAR, OPH, and CARN binding is available. Thus, in this work, molecular dynamics simulations were employed to elucidate the binding mechanism of H-CAR, OPH, and CARN. Among all, the amine end and imidazole ring are the main players for trapping all of the ligands in a pocket. OPH shows the poorest binding affinity, while CARN displays the tightest binding. Such firm binding is due to the longer amine chain and the additional hydroxyl (-OH) group of CARN. H-CAR and CARN are analogous, but the absence of the -OH moiety in H-CAR significantly enhances its mobility, resulting in the reduction in binding affinity. For OPH which is an ANS analogue, the methylated imidazole ring destroys the OPH-CN1 interaction network at this region, consequentially leading to the poor binding ability. An insight into how CN recognizes and binds its substrates obtained here will be useful for designing an effective strategy to prolong the lifetime of CAR and its analogues after ingestion.

Structure-Based In Silico Screening of Marine Phlorotannins for Potential Walrus Calicivirus Inhibitor

A new calicivirus isolated from a walrus was reported in 2004. Since unknown marine mammalian zoonotic viruses could pose great risks to human health, this study aimed to develop therapeutic countermeasures to quell any potential outbreak of a pandemic caused by this virus. We first generated a 3D model of the walrus calicivirus capsid protein and identified compounds from marine natural products, especially phlorotannins, as potential walrus calicivirus inhibitors. A 3D model of the target protein was generated using homology modeling based on two publicly available template sequences. The sequence of the capsid protein exhibited 31.3% identity and 42.7% similarity with the reference templates. The accuracy and reliability of the predicted residues were validated via Ramachandran plotting. Molecular docking simulations were performed between the capsid protein 3D model and 17 phlorotannins. Among them, five phlorotannins demonstrated markedly stable docking profiles; in particular, 2,7-phloroglucinol-6,6-bieckol showed favorable structural integrity and stability during molecular dynamics simulations. The results indicate that the phlorotannins are promising walrus calicivirus inhibitors. Overall, the study findings showcase the rapid turnaround of in silico-based drug discovery approaches, providing useful insights for developing potential therapies against novel pathogenic viruses, especially when the 3D structures of the viruses remain experimentally unknown.