Computational Structural Analysis Research Articles

Searching for Proton Transfer Channels in Respiratory Complex I

We have explored a strategy to identify potential proton transfer channels using computational analysis of a protein structure based on Voronoi partitioning, and applied it for the analysis of proton transfer pathways in redox-driven proton pumping respiratory complex I. The analysis results in a network of connected voids/channels which represent the dual structure of the protein; we then hydrated the identified channels using our water placement program Dowser++. Many theoretical water molecules found in the channels perfectly match the observed experimental water molecules in the structure; some other predicted water molecules have not been resolved in the experiments. The channels are of varying cross-section. Some channels are big enough to accommodate water molecules that are suitable to conduct protons; others are too narrow to hold water but require only minor conformational changes to accommodate proton transfer. We provide a preliminary analysis of proton conductivity of the network channels, classifying the proton transfer channels as open, closed, and partially open, and discuss possible conformational changes that can modulate, i.e. open and close, the channels.

Diversity and phage sensitivity to phages of porcine enterotoxigenic Escherichia coli.

Enterotoxigenic Escherichia coli (ETEC) is a diverse and poorly characterized E. coli pathotype that causes diarrhea in humans and animals. Phages have been proposed for the veterinary biocontrol of ETEC, but effective solutions require understanding of porcine ETEC diversity that affects phage infection. Here, we sequenced and analyzed the genomes of the PHAGEBio ETEC collection, gathering 79 diverse ETEC strains isolated from European pigs with post-weaning diarrhea (PWD). We identified the virulence factors characterizing the pathotype and several antibiotic resistance genes on plasmids, while phage resistance genes and other virulence factors were mostly chromosome encoded. We experienced that ETEC strains were highly resistant to Enterobacteriaceae phage infection. It was only by enrichment of numerous diverse samples with different media and conditions, using the 41 ETEC strains of our collection as hosts, that we could isolate two lytic phages that could infect a large part of our diverse ETEC collection: vB_EcoP_ETEP21B and vB_EcoS_ETEP102. Based on genome and host range analyses, we discussed the infection strategies of the two phages and identified components of lipopolysaccharides ( LPS) as receptors for the two phages. Our detailed computational structural analysis highlights several loops and pockets in the tail fibers that may allow recognition and binding of ETEC strains, also in the presence of O-antigens. Despite the importance of receptor recognition, the diversity of the ETEC strains remains a significant challenge for isolating ETEC phages and developing sustainable phage-based products to address ETEC-induced PWD.IMPORTANCEEnterotoxigenic Escherichia coli (ETEC)-induced post-weaning diarrhea is a severe disease in piglets that leads to weight loss and potentially death, with high economic and animal welfare costs worldwide. Phage-based approaches have been proposed, but available data are insufficient to ensure efficacy. Genome analysis of an extensive collection of ETEC strains revealed that phage defense mechanisms were mostly chromosome encoded, suggesting a lower chance of spread and selection by phage exposure. The difficulty in isolating lytic phages and the molecular and structural analyses of two ETEC phages point toward a multifactorial resistance of ETEC to phage infection and the importance of extensive phage screenings specifically against clinically relevant strains. The PHAGEBio ETEC collection and these two phages are valuable tools for the scientific community to expand our knowledge on the most studied, but still enigmatic, bacterial species-E. coli.

Generation of novel respiratory syncytial virus vaccine candidate antigens that can induce high levels of prefusion-specific antibodies

Respiratory syncytial virus (RSV) infection is an acute respiratory infection caused by RSV. It occurs worldwide, and for over 50 years, several attempts have been made to research and develop vaccines to prevent RSV infection; effective preventive vaccines are eagerly awaited. The RSV fusion (F) protein, which has gained attention as a vaccine antigen, causes a dynamic structural change from the preF to postF state. Therefore, the structural changes in proteins must be regulated to produce a vaccine antigen that can efficiently induce antibodies with high virus-neutralizing activity. We successfully discovered several mutations that stabilized the antigen site Ø in the preF state, trimerized it, and improved the level of protein expression through observation and computational analysis of the RSV-F protein structure and amino acid mutation analysis of RSV strains. The four RSV-F protein mutants that resulted from the combination of these effective mutations stably conserved a wide range of preF- and trimeric preF-specific epitopes with high virus-neutralizing activity. Absorption assay using human serum revealed that mutants constructed bound to antibodies with virus-neutralizing activity that were induced by natural RSV infection, whereas they hardly bound to anti-postF antibodies without virus-neutralizing activity. Furthermore, mouse immunization demonstrated that our constructed mutants induced a high percentage of antibodies that bind to the preF-specific antigen site. These characteristics suggest that the mutants constructed can be superior vaccine antigens from the viewpoint of RSV infection prevention effect and safety.

Elucidating key determinants of engineered scFv antibody in MMP-9 binding using high throughput screening and machine learning.

An imbalance in matrix metalloproteinase-9 (MMP-9) regulation can lead to numerous diseases, including neurological disorders, cancer, and pre-term labor. Engineering single-chain antibody fragments (scFvs) Targeting MMP-9 to develop novel therapeutics for such diseases is desirable. We screened a synthetic scFv antibody library displayed on the yeast surface for binding improvement to MMP-9 using FACS (fluorescent-activated cell sorting). The scFv antibody clones isolated after FACS showed improvement in binding to MMP-9 compared to the endogenous inhibitor. To understand molecular determinants of binding between engineered scFv antibody variants and MMP-9, next-generation DNA sequencing, and computational protein structure analysis were used. Additionally, a deep-learning language model was trained on the synthetic library to predict the binding of scFv variants using their CDR-H3 sequences.

Forward genetics combined with unsupervised classifications identified zebrafish mutants affecting biliary system formation

Impaired formation of the biliary network can lead to congenital cholestatic liver diseases; however, the genes responsible for proper biliary system formation and maintenance have not been fully identified. Combining computational network structure analysis algorithms with a zebrafish forward genetic screen, we identified 24 new zebrafish mutants that display impaired intrahepatic biliary network formation. Complementation tests suggested these 24 mutations affect 24 different genes. We applied unsupervised clustering algorithms to unbiasedly classify the recovered mutants into three classes. Further computational analysis revealed that each of the recovered mutations in these three classes has a unique phenotype on node-subtype composition and distribution within the intrahepatic biliary network. In addition, we found most of the recovered mutations are viable. In those mutant fish, which are already good animal models to study chronic cholestatic liver diseases, the biliary network phenotypes persist into adulthood. Altogether, this study provides unique genetic and computational toolsets that advance our understanding of the molecular pathways leading to biliary system malformation and cholestatic liver diseases.

Abstract PO3-29-03: An Emerging Class of ER mutations Enhances ER Dimerization and Promotes ER Activity

Abstract Physiological activation of estrogen receptor alpha (ERα) requires the binding of estradiol (E2) to the ligand binding domain (LBD) of the receptor. This interaction triggers a repositioning of helix 12 (H12), facilitating the recruitment of coactivator proteins to the unoccupied coactivator binding groove. However, in the context of breast cancer, point mutations of ERα at H12 lead to its repositioning and self-activation in the absence of E2. Through MSK clinical sequencing breast cancer cohort (MSK-IMPACT), we assayed 8302 samples of ER+ breast cancer patients and identified 649 mutations within the LBD of ERα. 471 of these mutations (73%) were located at H11-H12 loops (D538, Y537, L536), while the remaining 27% were located near the dimer interface of ERα (V422, G442, F461, S463P, L469). Through in vitro biochemical and cell assays, we identified that these mutations promote dimer formation and hormone-independent transcriptional activity. Tumors expressing these mutations exhibited significantly accelerated growth compared to their wild-type controls. Unlike Y537S, cells harboring mutations at the dimer interface maintain their sensitivity to Selective Estrogen Receptor Degraders (SERDs), including Fulvestrant, recently FDA-approved Elacestrant, and Camizestrant, as well as Selective Estrogen Receptor Modulators (SERMs) including Tamoxifen and Raloxifene. By utilizing machine learning and computational structural analyses, we uncovered that these mutants, unlike Y537 repositions H12, act distinctly through conformational change across the ERα dimer interface. Further cell assays proved that the dimerization leads to increased stability of the receptor and facilitates its nuclear localization, which is required for ERα activation. Collectively, our finding unveiled a new class of ER mutations that enforce receptor dimerization and activation of the ER signaling pathway. The discovery opens up a new therapeutic interventional possibility, suggesting that targeting dimerization could emerge as a new strategy to combat these malignancies. Citation Format: Seema Irani, Wuwei Tan, Qing Li, Weiyi Toy, Catherine Jones, Mayur Gadiya, Antonio Marra, John Katzenellenbogen, Kathryn Carlson, Benita S. Katzenellenbogen, Yang Shen, Sarat Chandarlapaty. An Emerging Class of ER mutations Enhances ER Dimerization and Promotes ER Activity [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-29-03.

Exploring the Function of Predicted T‐Cell Epitopes in Enhancing Influenza Virus Vaccine Efficacy

AbstractThis study investigates the potential utility of predicted T‐cell epitopes derived from the hemagglutinin (HA) sequences of the H1N1 and H5N1 serotypes of the influenza virus. The aim is to contribute to the improvement of a valuable influenza virus vaccine. The influenza virus, a member of the Orthomyxoviridae family, causes the contagious illness commonly known as the “flu.” It contains RNA and exhibits symptoms ranging from mild to severe, including fever, runny nose, sore throat, muscle aches, headaches, coughing, fatigue, and weakness. Each year, the flu epidemic results in a significant number of deaths and cases of severe illness worldwide. The study focuses on the HA protein, which is very useful for entry of virus and host cell strap, and the neuraminidase (NA) enzyme, which facilitates the free of the virus from the host cell. By utilizing computational tools such as Propred 1 and Propred, binding predictions for MHC class I and II are generated and conserved sequences are analyzed. The 3D structures of MHC class I and II human molecules are obtained from the Protein Data Bank (PDB) using the PATCH‐DOCK server. Through patch docking of the analyzed conserved sequences with MHC I and II human molecules, conserved epitopes that hold potential for vaccine development are identified. This research highlights the importance of utilizing predicted T‐cell epitopes in the design of effective influenza virus vaccines. By leveraging computational methods and structural analysis, this approach provides insights into the development of vaccines that target specific influenza virus serotypes. The identified conserved epitopes have the potential to enhance vaccine efficacy and contribute to the ongoing efforts to combat influenza virus infections.

Landscape of FLT3 Variations Associated with Structural and Functional Impact on Acute Myeloid Leukemia: A Computational Study.

Acute myeloid leukemia (AML) is hallmarked by the clonal proliferation of myeloid blasts. Mutations that result in the constitutive activation of the fms-like tyrosine kinase 3 (FLT3) gene, coding for a class III receptor tyrosine kinase, are significantly associated with this heterogeneous hematologic malignancy. The fms-related tyrosine kinase 3 ligand binds to the extracellular domain of the FLT3 receptor, inducing homodimer formation in the plasma membrane, leading to autophosphorylation and activation of apoptosis, proliferation, and differentiation of hematopoietic cells in bone marrow. In the present study, we evaluated the association of FLT3 as a significant biomarker for AML and tried to comprehend the effects of specific variations on the FLT3 protein's structure and function. We also examined the effects of I836 variants on binding affinity to sorafenib using molecular docking. We integrated multiple bioinformatics tools, databases, and resources such as OncoDB, UniProt, COSMIC, UALCAN, PyMOL, ProSA, Missense3D, InterProScan, SIFT, PolyPhen, and PredictSNP to annotate the structural, functional, and phenotypic impact of the known variations associated with FLT3. Twenty-nine FLT3 variants were analyzed using in silico approaches such as DynaMut, CUPSAT, AutoDock, and Discovery Studio for their impact on protein stability, flexibility, function, and binding affinity. The OncoDB and UALCAN portals confirmed the association of FLT3 gene expression and its mutational status with AML. A computational structural analysis of the deleterious variants of FLT3 revealed I863F mutants as destabilizers of the protein structure, possibly leading to functional changes. Many single-nucleotide variations in FLT3 have an impact on its structure and function. Thus, the annotation of FLT3 SNVs and the prediction of their deleterious pathogenic impact will facilitate an insight into the tumorigenesis process and guide experimental studies and clinical implications.

Computational analysis of electrode structure and configuration for efficient and localized neural stimulation

Computational analysis of electrode structure and configuration for efficient and localized neural stimulation

Computational analysis of dimer G6PD structure to elucidate pathogenicity of G6PD variants.

An inherent genetic enzyme disorder in humans, known as glucose-6-phosphate dehydrogenase (G6PD) deficiency, arises due to specific mutations. While the prevailing approach for investigating G6PD variants involves biochemical analysis, the intricate structural details remain limited, impeding a comprehensive understanding of how different G6PD variants of varying classes impact their functionality. This study 22 examined the dynamic properties of G6PD wild types and six G6PD variants from 23 different classes using molecular dynamic simulation (MDS). The wild-type and variant 24 G6PD structures unveil high fluctuations within the amino acid range of 274-515, the structural NADP+ binding site, pivotal for enzyme dimerization. Specifically, two variants, G6PDZacatecas (R257L) and G6PDDurham (K238R), demonstrate compromised structural stability at the dimer interface, attributable to the disruption of a salt bridge involving Glu 206 and Lys 407, along with the disturbance of hydrogen bonds formed by Asp 421 at the βN-βN sheets. Consequently, this impairment cascades to affect the binding affinity of crucial interactions, such as Lys 171-Glucose-6-Phosphate (G6P) and Lys 171-catalytic NADP+, leading to diminished enzyme activity. This study underscores the utility of computational in silico techniques in predicting the structural alterations and flexibility of G6PD variants. This insight holds promise for guiding future endeavors in drug development targeted at mitigating the impacts of G6PD deficiency.

In-silico structural analysis of Heterocephalus glaber amyloid beta: an anti-Alzheimer's peptide.

Heterocephalus glaber, known as the Naked mole-rat, has an extraordinary immunity to Alzheimer's disease. The pathological hallmark of Alzheimer's disease is cerebral accumulations of plaques, consisting of self-aggregated amyloid beta peptides. Homo sapiens and H. glaber amyloid beta peptides are different in only one amino acid. Herein, computational structural analyses were carried out to determine whether plaque development in H. glaber is prevented by the replacement of His13 with Arg13 in the amyloid beta peptide. AlphaFold2 was used to predict the structure of the H. glaber amyloid beta peptide. HADDOCK and Hex were used to self-dock the peptides and dock ions on peptides, respectively. Illustrations were made by PyMol and ChimeraX. Using VMD, we calculated the radius of gyration. The phylogenetic analysis was conducted by Mega. The results showed an accurate structure with two alpha helices separated by a short coil for H. glaber. Self-docking of the two amyloid beta peptides demonstrated a globular conformation in the H. glaber dimer, implying the unlikeliness of amyloid beta peptides' self-aggregation to form fibrillar structures. This conformational state resulted in lower electrostatic energy compared to H. sapiens, contributing to H. glaber's lower tendency for fibril and, ultimately, plaque formation. Phylogenetic analysis confirmed that amyloid precursor protein is highly conserved in each taxon of rodentia and primata. This study provides insight into the connection between the structure of H. glaber amyloid beta and its plaque formation properties, showing that the Arg13 in H. glaber leads to fibril instability, and might prevent senile plaque accumulation.

Computational analysis of electronic structure and optical properties of monocrystalline silicon-vacancy defect system based on density functional theory

Monocrystalline silicon is an important substrate or base material for manufacturing integrated circuit chips, mirrors, etc. However, it is a typical hard and brittle material, which is very prone to produce defects during processing. This paper investigates the electronic structure and optical properties of sphalerite monocrystalline silicon with vacancy concentrations of 1.5625%, 3.125%, 4.6875%, and 6.25% using the first principles method based on density functional theory. The results demonstrate that the introduction of impurities results in the formation of impurity bands (IB) within the band structure, thereby facilitating electronic transitions. However, vacancy defects do not alter the properties of monocrystalline silicon as an indirect semiconductor. Regarding optical properties, an increase in defect concentration leads to a decrease in the macroscopic symmetry of the system, resulting in noticeable anisotropy in each property. Also found that the main spectral peaks of the defect system are red-shifted, and the vacancy defects introduce new peaks in the near-infrared region and the visible region with increasing intensity, but the peaks in the ultraviolet region gradually decrease with the increase of the defect concentration. The refractive index peak gradually decreases with the increase of defect concentration, and the calculated average refractive index is around 1.2. In the high-energy region, the refractive index takes a very small value, and the reflection of electromagnetic waves from the doped system is also weak at this time, which indicates that the system has a high transmittance property. Importantly, there is a higher intensity of energy loss at photon energies around 16.5 eV. Consequently, these calculations are deemed valuable for advancing research and applications involving monocrystalline silicon optical mirrors.

Computational and AI-driven 3D structural analysis of human papillomavirus (HPV) oncoproteins E5, E6, and E7 reveal significant divergence of HPV E5 between low-risk and high-risk genotypes

There are over 220 identified genotypes of Human papillomavirus (HPV), and the HPV genome encodes 3 major oncogenes, E5, E6, and E7. Conservation and divergence in protein sequence and function between low-risk versus high-risk oncogenic HPV genotypes has not been fully characterized. Here, we used modern computational and structural folding algorithms to perform a comparative analysis of HPV E5, E6, and E7 between multiple low risk and high risk genotypes. We first identified significantly greater sequence divergence in E5 between low- and high-risk genotypes compared to E6 and E7. Next, we used AlphaFold to model the structure of papillomavirus proteins and complexes with high confidence, including some with no established consensus structure. We observed that HPV E5, but not E6 or E7, had a dramatically different 3D structure between low-risk and high-risk genotypes. To our knowledge, this is the first comparative analysis of HPV proteins using Alphafold artificial intelligence (AI) system. The marked differences in E5 sequence and structure in high-risk HPVs may contribute in important and underappreciated ways to the development of HPV-associated cancers.

Searching for novel MDM2/MDMX dual inhibitors through a drug repurposing approach

Disruption of p53-MDM2/MDMX interaction by smaller inhibitors is a promising therapeutic intervention gaining tremendous interest. However, no MDM2/MDMX inhibitors have been marketed so far. Drug repurposing is a validated, practical approach to drug discovery. In this regard, we employed structure-based virtual screening in a reservoir of marketed drugs and identified nintedanib as a new MDM2/MDMX dual inhibitor. The computational structure analysis and biochemical experiments uncover that nintedanib binds MDM2/MDMX similarly to RO2443, a dual MDM2/MDMX inhibitor. Furthermore, the mechanistic study reveals that nintedanib disrupts the physical interaction of p53-MDM2/MDMX, enabling the transcriptional activation of p53 and the subsequent cell cycle arrest and growth inhibition in p53+/+ cancer cells. Lastly, structural minimisation of nintedanib yields H3 with the equivalent potency. In summary, this work provides a solid foundation for reshaping nintedanib as a valuable lead compound for the further design of MDM2/MDMX dual inhibitors.

Synthesis, Spectroscopic, Computational Structure Analysis, Molecular Docking, in vitro Antibacterial and in vivo Antipyretic Investigations of Transition Metal(II) Complexes

Unsymmetrical Schiff base hydrazone complexes of cobalt(II), nickel(II) and zinc(II) were synthesized from oxalic dihydrazide, salicylaldehyde and ethyl acetoacetate. The ligand and its metal(II) complexes were characterized by elemental analysis, UV-visible, FT-IR, molar conductivity. To determine the biological activity, in vivo antipyretic as well as in vitro antibacterial activities were conducted along with molecular docking simulation, HOMO-LUMO and MEP calculations. The findings from the experimental and molecular docking investigations demonstrated that the ligand and all the metal(II) complexes has an ability to interact with E. coli 24kDa domain protein (PDB: 1KZN). Furthermore, these interactions were accompanied by favourable docking score values, indicating potential therapeutic implications. The quantum parameters and geometric optimization of the ligand and complexes were performed using DFT simulations.

Structural Elucidation, In vitro and In silico Biological Evaluations of New Fluorinated Chalcone Derivatives for Potential Antioxidant Activity

Abstract: The newly synthesized fluorinated chalcone derivatives are observed to possess antioxidant potential. Two new fluorinated chalcone compounds were effectively synthesized using the Claisen- Schmidt condensation reaction and were recrystallized using the slow evaporation method. The single crystal structure of the compounds was determined and refined through the X-ray single crystal diffraction method. All compounds were subjected to computational structural characterization and Hirshfeld surface analysis. The compounds were then further characterized through the Ultravioletvisible (UV-Vis) spectroscopic study. The chalcone derivatives were further analysed with biological experimentation and simulation such as in vitro antioxidant (DPPH) assay, molecular docking and in silico ADMET study. The crystal packing revealed that the molecules in the compounds were linked together through the intermolecular C—H···O and C—H···π interactions. Hirshfeld surface analysis validated the presence of intermolecular interactions in crystal packing. The UV-Vis spectroscopic study revealed that the absorption wavelength of the compounds that range from 421.79 to 428.98 nm was within the visible region with the energy gap value of 2.58 to 2.62 eV. The DPPH assay disclosed weak antioxidant activity of both compounds (-31 to 20 %, 10000 μg/mL) compared to the standard ascorbic acid (94.5 %, 50 μg/mL). The binding energy of the docked complex inside the target protein, 2CAG was within the range of -7.3 to -7.5 kcal/mol. In the silico model, SwissADME predicted that the two compounds have overall good drug-like properties. Different substituents, more planar configuration and high intramolecular interactions in the crystal packing played their role in increasing the antioxidant activities, binding energy and drug likeliness of the synthesized compounds.

Sensitivity analysis on mechanical parameters of continuum models for simulating in-plane tests on existing masonry panels

Understanding and modeling the structural behavior of existing masonry buildings is a fundamental task in view of their management and conservation, especially in seismic-prone areas. Among the different modeling approaches for the computational analysis of unreinforced masonry structures, this work investigates the ability of two material continuum models, the modified masonry-like material and Mazars’ material, to simulate real in-plane failure modes of masonry panels, considering the influence of the variability of mechanical parameters on the results. As the first part of a broader benchmark, this work focuses on the study of two recurring test patterns for masonry panels subject to both horizontal and vertical loads, given the availability of experimental data. To account for the parameter variability that typically affects masonry materials, uncertainty propagation is performed in a probabilistic framework, and a gPCE-based proxy model makes it possible to turn time-consuming numerical runs into significantly faster analytical evaluations. Sensitivity analyses are carried out in terms of Sobol’ indices to evaluate the influence of input variability on the ultimate horizontal load. The most relevant masonry parameters for each model are thus highlighted and the issue of model calibration is finally addressed by relying on Bayesian inverse methods. This work also underlines the pros and cons of the different hypotheses, which underlie the two nonlinear constitutive laws.

Effect of AQP4 and its palmitoylation on the permeability of exogenous reactive oxygen species: Insights from computational study

Aquaporin 4 (AQP4) facilitates the transport of reactive oxygen species (ROS). Both cancer cells and the ionizing radiation microenvironment can induce posttranslational modifications (PTMs) in AQP4, which may affect its permeability to ROS. Because this ROS diffusion process is rapid, microscopic, and instantaneous within and outside cells, conventional experimental methods are inadequate for elucidating the molecular mechanisms involved. In this study, computational methods were employed to investigate the permeability of exogenous ROS mediated by radiation in AQP4 at a molecular scale. We constructed a simulation system incorporating AQP4 and AQP4-Cysp13 in a complex lipid environment with ROS. Long-timescale molecular dynamics simulations were conducted to assess the structural stability of both AQP4 and AQP4-Cysp13. Free energy calculations were utilized to determine the ROS transport capability of the two AQP4 proteins. Computational electrophysiology and channel structural analysis quantitatively evaluated changes in ROS transport capacity under various radiation-induced transmembrane voltage microenvironments. Our findings demonstrate the distinct transport capabilities of AQP4 channels for water molecules and various types of ROS and reveal a decrease in transport efficiency when AQP4 undergoes palmitoylation modification. In addition, we have simulated the radiation-induced alteration of cell membrane voltage, which significantly affected the ROS transport capacity. We propose that this research will enhance the understanding of the molecular mechanisms governing the transport of exogenous ROS by AQP4 and elucidate the influence of palmitoylation on ROS transport. This study will also help clarify how different structural features of AQP4 affect the transport of exogenous ROS mediated by radiotherapy, thereby providing a theoretical molecular basis for the development of new treatment strategies that combine with radiotherapy.

Serine/threonine kinase of Mpox virus: computational modeling and structural analysis

Kinases catalyze phosphoryl transfer from a nucleoside triphosphate (usually ATP) to an amino acid on a protein for activation purposes. Although kinases are well-appreciated drug targets in different viruses and cancers, these enzymes in poxviruses received limited attention from the research community. In poxvirus, the production of infectious particles in the infected cells depends on a serine/threonine protein kinase (STK) that activates proteins implicated in the assembly of new virions. This work aimed to elucidate the structure and dynamics of the major kinase STK from Mpox virus (Orthopoxvirus). A state-of-the-art computational approach was employed to decipher the structure and dynamics of the STK using AlphaFold2 and molecular dynamics (MD) simulations. Although the predicted structure showed an atypical kinase, the overall structural fold is conserved. Binding free energy calculations via Molecular Mechanics/Generalized Born and Surface Area (MM/GBSA) determined the hotspot residues contributing to binding of ATP. The structural analysis in this work provides insights into the structure and behavior of STK in Mpox virus and possibly its closest members of Poxviridae. These findings also set the basis for setting up a thorough experimental investigation to understand the enzymatic mechanism, peptide substrate binding, and the development of small-molecule inhibitors against this kinase. Communicated by Ramaswamy H. Sarma

Towards multi-target glioblastoma therapy: Structural, distribution, and functional insights into protein target candidates

Glioblastoma is the most commonly occurring and most lethal primary brain tumor. Treatment options are limited in number and therapeutic development remains a major challenge. However, substantial progress has been made in better understanding the underlying biology of the disease. A recent proteomic meta-analysis revealed that 270 proteins were commonly dysregulated in glioblastoma, highlighting the complexity of the disease. This motivated us to explore potential protein targets which may be collectively inhibited, based on common upregulation, as part of a multi-target therapeutic strategy. Herein, we identify and characterize structural attributes relevant to the druggability of six protein target candidates. Computational analysis of crystal structures revealed druggable cavities in each of these proteins, and various parameters of these cavities were determined. For proteins with inhibitor-bound structures available, inhibitor compounds were found to overlap with the computationally determined cavities upon structural alignment. We also performed bioinformatic analysis for normal transcriptional expression distribution of these proteins across various brain regions and various tissues, as well as gene ontology curation to gain functional insights, as this information is useful for understanding the potential for off-target adverse effects. Our findings represent initial steps towards the development of multi-target glioblastoma therapy and may aid future work exploring similar therapeutic strategies.