The Bio3D packages for structural bioinformatics

Rational design of monomeric IL37 variants guided by stability and dynamical analyses of IL37 dimers

IL37 plays important roles in the regulation of innate immunity and its oligomeric status is critical to these roles. In its monomeric state, IL37 can effectively inhibit the inflammatory response of IL18 by binding to IL18Rα, a capacity lost in its dimeric form, underlining the pivotal role of the oligomeric status of IL37 in its anti-inflammatory action. Until now, two IL37 dimer structures have been deposited in PDB, reflecting a substantial difference in their dimer interfaces. Given this discrepancy, we analyzed the PDB structures of the IL37 dimer (PDB IDs: 6ncu, 5hn1) along with a AF2-multimer prediction by molecular dynamics (MD) simulations. Results showed that the 5hn1 and AF2-predicted dimers have the same interface and stably maintained their conformations throughout simulations, while the recent IL37 dimer (PDB ID: 6ncu) with a different interface did not, proposing a possible issue with the recent IL37 dimer structure (6ncu). Next, focusing on the stable dimer structures, we have identified five critical positions of V71/Y85/I86/E89/S114, three new positions compared to the literature, that would reduce dimer stability without affecting the monomer structure. Two quintuple mutants were tested by MD simulations and showed partial or complete dissociation of the dimer. Overall, the insights gained from this study reinforce the validity of the 5hn1 and AF2 multimer structures, while also advancing our understanding of the IL37 dimer interface through the generation of monomer-locked IL37 variants.

Enhanced catalytic performance and pH stability of Streptomyces Laccase Y230R and its degradation of malachite green

The escalating threat of malachite green (MG) pollution poses significant risks to ecosystems. Saturation mutation targeting Tyr230 of small laccase (SLAC) from Streptomyces coelicolor yielded Y230R, exhibiting a remarkable 104 % increase in specific activity. Notably, this mutation achieved dual enhancements in both activity and pH stability. Molecular dynamics simulation revealed higher structural stability of Y230R compared to wild-type (WT) across varying pH levels. The increased count of hydrogen bonds in Y230R compared to WT may be contribute to its stability. Y230R demonstrated superior catalytic efficiency (67.0 %) in MG decolorization, maintaining over 90 % activity after 30 min incubation in MG solution (500 mg/L), highlighting enhanced tolerance compared to WT. Molecular docking analysis attributed the differential catalytic effects on MG and ABTS to structural disparities and hydrogen bonding. Y230R stands as a promising composite mutant for future laccase engineering and industrial applications.

TIMM9 as a prognostic biomarker in multiple cancers and its associated biological processes

TIMM9 has been identified as a mediator of essential functions in mitochondria, but its association with pan-cancer is poorly understood. We herein employed bioinformatics, computational chemistry techniques and experiments to investigate the role of TIMM9 in pan-cancer. Our analysis revealed that overexpression of TIMM9 was significantly associated with tumorigenesis, pathological stage progression, and metastasis. Missense mutations (particularly the S49L variant), copy number variations (CNV) and methylation alterations in TIMM9 were found to be associated with poor cancer prognosis. Moreover, TIMM9 was positively related with cell cycle progression, mitochondrial and ribosomal function, oxidative phosphorylation, TCA cycle activity, innate and adaptive immunity. Additionally, we discovered that TIMM9 could be regulated by cancer-associated signaling pathways, such as the mTOR pathway. Using molecular simulations, we identified ITFG1 as the protein that has the strongest physical association with TIMM9, which show a promising structural complement.

Cheminformatics-based analysis identified (Z)-2-(2,5-dimethoxy benzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one as an inhibitor of Marburg replication by interacting with NP

The highly pathogenic Marburg virus (MARV) is a member of the Filoviridae family, a non-segmented negative-strand RNA virus. This article represents the computer-aided drug design (CADD) approach for identifying drug-like compounds that prevent the MARV virus disease by inhibiting nucleoprotein, which is responsible for their replication. This study used a wide range of in silico drug design techniques to identify potential drugs. Out of 368 natural compounds, 202 compounds passed ADMET, and molecular docking identified the top two molecules (CID: 1804018 and 5280520) with a high binding affinity of -6.77 and -6.672 kcal/mol, respectively. Both compounds showed interactions with the common amino acid residues SER_216, ARG_215, TYR_135, CYS_195, and ILE_108, which indicates that lead compounds and control ligands interact in the common active site/catalytic site of the protein. The negative binding free energies of CID: 1804018 and 5280520 were -66.01 and -31.29 kcal/mol, respectively. Two lead compounds were re-evaluated using MD modeling techniques, which confirmed CID: 1804018 as the most stable when complexed with the target protein. PC3 of the (Z)-2-(2,5-dimethoxybenzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one (CID: 1804018) was 8.74%, whereas PC3 of the 2'-Hydroxydaidzein (CID: 5280520) was 11.25%. In this study, (Z)-2-(2,5-dimethoxybenzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one (CID: 1804018) unveiled the significant stability of the proteins' binding site in ADMET, Molecular docking, MM-GBSA and MD simulation analysis studies, which also showed a high negative binding free energy value, confirming as the best drug candidate which is found in Angelica archangelica which may potentially inhibit the replication of MARV nucleoprotein.

Conformations of KRAS4B Affected by Its Partner Binding and G12C Mutation: Insights from GaMD Trajectory-Image Transformation-Based Deep Learning

Binding of partners and mutations highly affects the conformational dynamics of KRAS4B, which is of significance for deeply understanding its function. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) and principal component analysis (PCA) were carried out to probe the effect of G12C and binding of three partners NF1, RAF1, and SOS1 on the conformation alterations of KRAS4B. DL reveals that G12C and binding of partners result in alterations in the contacts of key structure domains, such as the switch domains SW1 and SW2 together with the loops L4, L5, and P-loop. Binding of NF1, RAF1, and SOS1 constrains the structural fluctuation of SW1, SW2, L4, and L5; on the contrary, G12C leads to the instability of these four structure domains. The analyses of free energy landscapes (FELs) and PCA also show that binding of partners maintains the stability of the conformational states of KRAS4B while G12C induces greater mobility of the switch domains SW1 and SW2, which produces significant impacts on the interactions of GTP with SW1, L4, and L5. Our findings suggest that partner binding and G12C play important roles in the activity and allosteric regulation of KRAS4B, which may theoretically aid in further understanding the function of KRAS4B.

Systematic discovery of DNA-binding tandem repeat proteins

Tandem repeat proteins (TRPs) are widely distributed and bind to a wide variety of ligands. DNA-binding TRPs such as zinc finger (ZNF) and transcription activator-like effector (TALE) play important roles in biology and biotechnology. In this study, we first conducted an extensive analysis of TRPs in public databases, and found that the enormous diversity of TRPs is largely unexplored. We then focused our efforts on identifying novel TRPs possessing DNA-binding capabilities. We established a protein language model for DNA-binding protein prediction (PLM-DBPPred), and predicted a large number of DNA-binding TRPs. A subset was then selected for experimental screening, leading to the identification of 11 novel DNA-binding TRPs, with six showing sequence specificity. Notably, members of the STAR (Short TALE-like Repeat proteins) family can be programmed to target specific 9 bp DNA sequences with high affinity. Leveraging this property, we generated artificial transcription factors using reprogrammed STAR proteins and achieved targeted activation of endogenous gene sets. Furthermore, the members of novel families such as MOON (Marine Organism-Originated DNA binding protein) and pTERF (prokaryotic mTERF-like protein) exhibit unique features and distinct DNA-binding characteristics, revealing interesting biological clues. Our study expands the diversity of DNA-binding TRPs, and demonstrates that a systematic approach greatly enhances the discovery of new biological insights and tools.

Bioinformatics and computational studies of chabamide F and chabamide G for breast cancer and their probable mechanisms of action

Globally, the prevalence of breast cancer (BC) is increasing at an alarming level, despite early detection and technological improvements. Alkaloids are diverse chemical groups, and many within this class have been reported as potential anticancer compounds. Chabamide F (F) and chabamide G (G) are two dimeric amide alkaloids found in a traditional medicinal plant, Piper chaba, and possess significant cytotoxic effects. However, their scientific rationalization in BC remains unknown. Here, we aimed to investigate their potential and molecular mechanisms for BC through in silico approaches. From network pharmacology, we identified 64 BC-related genes as targets. GO and KEGG studies showed that they were involved in various biological processes and mostly expressed in BC-related pathways such as RAS, PI3K-AKT, estrogen, MAPK, and FoxO pathways. However, PPI analysis revealed SRC and AKT1 as hub genes, which play key roles in BC tumorigenesis and metastasis. Molecular docking revealed the strong binding affinity of F (- 10.7 kcal/mol) and G (- 9.4 and - 11.7 kcal/mol) for SRC and AKT1, respectively, as well as the acquisition of vital residues to inhibit them. Their long-term stability was evaluated using 200 ns molecular dynamics simulation. The RMSD, RMSF, Rg, and SASA analyses showed that the G-SRC and G-AKT1 complexes were excellently stable compared to the control, dasatinib, and capivasertib, respectively. Additionally, the PCA and DCCM analyses revealed a significant reduction in the residual correlation and motions. By contrast, the stability of the F-SRC complex was greater than that of the control, whereas it was moderately stable in complex with AKT1. The MMPBSA analysis demonstrated higher binding energies for both compounds than the controls. In particular, the binding energy of G for SRC and AKT1 was - 120.671 ± 16.997 and - 130.437 ± 19.111 kJ/mol, respectively, which was approximately twice as high as the control molecules. Van der Waal and polar solvation energies significantly contributed to this energy. Furthermore, both of them exhibited significant interactions with the binding site residues of both proteins. In summary, this study indicates that these two molecules could be a potential ATP-competitive inhibitor of SRC and an allosteric inhibitor of AKT1.

Structural basis for allosteric regulation of human phosphofructokinase-1

Phosphofructokinase-1 (PFK1) catalyzes the rate-limiting step of glycolysis, committing glucose to conversion into cellular energy. PFK1 is highly regulated to respond to the changing energy needs of the cell. In bacteria, the structural basis of PFK1 regulation is a textbook example of allostery; molecular signals of low and high cellular energy promote transition between an active R-state and inactive T-state conformation, respectively. Little is known, however, about the structural basis for regulation of eukaryotic PFK1. Here, we determine structures of the human liver isoform of PFK1 (PFKL) in the R- and T-state by cryoEM, providing insight into eukaryotic PFK1 allosteric regulatory mechanisms. The T-state structure reveals conformational differences between the bacterial and eukaryotic enzyme, the mechanisms of allosteric inhibition by ATP binding at multiple sites, and an autoinhibitory role of the C-terminus in stabilizing the T-state. We also determine structures of PFKL filaments that define the mechanism of higher-order assembly and demonstrate that these structures are necessary for higher-order assembly of PFKL in cells.

Z. A, Alhazzani K. Insilico exploration C. koseri ATP synthase inhibitors by pharmacophore-based virtual screening, molecular docking and MD simulation

Citrobacter koseri is a gram-negative rod that causes infections in people who have significant comorbidities and are immunocompromised. Antibiotic-resistant strains are becoming more common, which complicates infection treatment and highlights the need for innovative, effective drugs to fight these resistant strains. The enzyme complex ATP synthase participates in the adenosine triphosphate (ATP) synthesis, the fundamental energy currency of cells. This study used Computer-Aided Drug Design approaches to identify potential inhibitors of C. koseri ATP synthase. SWISS-MODEL was used to predict the 3D structure of C. koseri ATP synthase. A ligand-based pharmacophore model was developed using chemical features of ampicillin. Following ligand-based virtual screening across nine databases, the 2043 screened hits were docked to the ATP synthase active site using the standard precision mode of the glide tool. Based on their binding affinities, the top ten compounds were selected for additional investigation. The binding affinities of the chosen compounds ranged from -10.021 to -8.452 kcal/mol. The top four compounds (PubChem-25230613, PubChem-74936833, CHEMBL263035, PubChem-44208924) with the best ADMET characteristics and binding modes were chosen. Thus, the feasible binding mechanisms of the selected compounds were subjected to stability analysis using the MD Simulation study, which revealed the compounds' stability as potent inhibitors within the protein binding pocket. This computational approach provides important insights into the rational design of novel therapeutics and emphasizes the importance of targeting essential metabolic pathways when combating antibiotic-resistant pathogens. Future experimental validation and optimization of the identified inhibitors is required to determine their efficacy and safety profiles for clinical use.

Deciphering the Mystery in p300 Taz2-p53 TAD2 Recognition

Intrinsically disordered proteins (IDPs) engage in various fundamental biological activities, and their behavior is of particular importance for a better understanding of the verbose but well-organized signal transduction in cells. IDPs exhibit uniquely paradoxical features with low affinity but simultaneously high specificity in recognizing their binding targets. The transcription factor p53 plays a crucial role in cancer suppression, carrying out some of its biological functions using its disordered regions, such as N-terminal transactivation domain 2 (TAD2). Exploration of the binding and unbinding processes between proteins is challenging, and the inherently disordered properties of these regions further complicate the issue. Computer simulations are a powerful tool to complement the experiments to fill gaps to explore the binding/unbinding processes between proteins. Here, we investigated the binding mechanism between p300 Taz2 and p53 TAD2 through extensive molecular dynamics (MD) simulations using the physics-based UNited RESidue (UNRES) force field with additional Go̅-like potentials. Distance restraints extracted from the NMR-resolved structures were imposed on intermolecular residue pairs to accelerate binding simulations, in which Taz2 was immobilized in a native-like conformation and disordered TAD2 was fully free. Starting from six structures with TAD2 placed at different positions around Taz2, we observed a metastable intermediate state in which the middle helical segment of TAD2 is anchored in the binding pocket, highlighting the significance of the TAD2 helix in directing protein recognition. Physics-based binding simulations show that successful binding is achieved after a series of stages, including (1) protein collisions to initiate the formation of encounter complexes, (2) partial attachment of TAD2, and finally (3) full attachment of TAD2 to the correct binding pocket of Taz2. Furthermore, machine-learning-based PathDetect-SOM was used to identify two binding pathways, the encounter complexes, and the intermediate states.

Predictive identification and design of potent inhibitors targeting resistance-inducing candidate genes from E. coli whole-genome sequences

Introduction: This work utilizes predictive modeling in drug discovery to unravel potential candidate genes from Escherichia coli that are implicated in antimicrobial resistance; we subsequently target the gidB, MacB, and KatG genes with some compounds from plants with reported antibacterial potentials. Method: The resistance genes and plasmids were identified from 10 whole-genome sequence datasets of E. coli; forty two plant compounds were selected, and their 3D structures were retrieved and optimized for docking. The 3D crystal structures of KatG, MacB, and gidB were retrieved and prepared for molecular docking, molecular dynamics simulations, and ADMET profiling. Result: Hesperidin showed the least binding energy (kcal/mol) against KatG (-9.3), MacB (-10.7), and gidB (-6.7); additionally, good pharmacokinetic profiles and structure-dynamics integrity with their respective protein complexes were observed. Conclusion: Although these findings suggest hesperidin as a potential inhibitor against MacB, gidB, and KatG in E. coli, further validations through in vitro and in vivo experiments are needed. This research is expected to provide an alternative avenue for addressing existing antimicrobial resistances associated with E. coli's MacB, gidB, and KatG.

SARS-CoV-2 Omicron XBB lineage spike structures, conformations, antigenicity, and receptor recognition

A recombinant lineage of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant, named XBB, appeared in late 2022 and evolved descendants that successively swept local and global populations. XBB lineage members were noted for their improved immune evasion and transmissibility. Here, we determine cryoelectron microscopy (cryo-EM) structures of XBB.1.5, XBB.1.16, EG.5, and EG.5.1 spike (S) ectodomains to reveal reinforced 3-receptor binding domain (RBD)-down receptor-inaccessible closed states mediated by interprotomer RBD interactions previously observed in BA.1 and BA.2. Improved XBB.1.5 and XBB.1.16 RBD stability compensated for stability loss caused by early Omicron mutations, while the F456L substitution reduced EG.5 RBD stability. S1 subunit mutations had long-range impacts on conformation and epitope presentation in the S2 subunit. Our results reveal continued S protein evolution via simultaneous optimization of multiple parameters, including stability, receptor binding, and immune evasion, and the dramatic effects of relatively few residue substitutions in altering the S protein conformational landscape.

From Proteome to Potential Drugs: Integration of Subtractive Proteomics and Ensemble Docking for Drug Repurposing against Pseudomonas aeruginosa RND Superfamily Proteins

Pseudomonas aeruginosa (P. aeruginosa) poses a significant threat as a nosocomial pathogen due to its robust resistance mechanisms and virulence factors. This study integrates subtractive proteomics and ensemble docking to identify and characterize essential proteins in P. aeruginosa, aiming to discover therapeutic targets and repurpose commercial existing drugs. Using subtractive proteomics, we refined the dataset to discard redundant proteins and minimize potential cross-interactions with human proteins and the microbiome proteins. We identified 12 key proteins, including a histidine kinase and members of the RND efflux pump family, known for their roles in antibiotic resistance, virulence, and antigenicity. Predictive modeling of the three-dimensional structures of these RND proteins and subsequent molecular ensemble-docking simulations led to the identification of MK-3207, R-428, and Suramin as promising inhibitor candidates. These compounds demonstrated high binding affinities and effective inhibition across multiple metrics. Further refinement using non-covalent interaction index methods provided deeper insights into the electronic effects in protein-ligand interactions, with Suramin exhibiting superior binding energies, suggesting its broad-spectrum inhibitory potential. Our findings confirm the critical role of RND efflux pumps in antibiotic resistance and suggest that MK-3207, R-428, and Suramin could be effectively repurposed to target these proteins. This approach highlights the potential of drug repurposing as a viable strategy to combat P. aeruginosa infections.

Prognostic role of TEAD4 in TNBC: in-silico inhibition of the TEAD4-YAP interaction by flufenamic acid analogs

Triple-negative breast cancer (TNBC) poses a significant global health challenge due to its highly aggressive nature and invasive characteristics. Dysregulation of the Hippo pathway, a key regulator of various biological processes, is observed in TNBC, and its inhibition holds promise for impeding cancer growth. This in-silico analysis investigates the role of Transcriptional Enhanced Associate Domain 4 (TEAD4) in TNBC and its interaction with Yes Associated Protein (YAP) in cancer progression. Our results demonstrate that TEAD4 upregulation is linked to poor prognosis in TNBC, emphasizing its critical role in the disease. Moreover, we identify CID44521006, an analog of Flufenamic acid, as a potential therapeutic compound capable of disrupting the TEAD4-YAP interaction by binding to the YAP-binding domain of TEAD4. These findings underscore the significance of TEAD4 in TNBC and propose CID44521006 as a promising candidate for therapeutic intervention. The study contributes valuable insights to advance treatment options for TNBC, offering a potential avenue for the development of targeted therapies against this aggressive form of breast cancer.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00239-8.

Elucidating bis-pyrimidines as new and efficient mushroom tyrosinase inhibitors: synthesis, SAR, kinetics and computational studies

In this study, a series of novel bis-pyrimidine derivatives (1P-8P) were designed, synthesized, characterized, and investigated for their in vitro inhibitory activity against mushroom tyrosinase, an enzyme critical in melanin biosynthesis and implicated in various hyperpigmentation disorders. To the best of our knowledge, the bispyrimidine scaffold has been evaluated for the first time for its tyrosinase inhibitory activity. Their inhibitory activities were assessed, revealing inhibition with IC50 values in the micromolar range. Additionally, this series of compounds were found to inhibit tyrosinase activity in a mixed-type manner, with IC50 values ranging from 12.36 ± 1.24 to 86.67 ± 3.08 μM. To further elucidate the binding interactions, molecular docking simulations were performed, identifying key residues in the active site responsible for binding affinity. Furthermore, molecular dynamics (MD) simulations were conducted to assess the dynamic behavior, stability, and binding affinity of the most potent inhibitor, compound 6P. Quantitative Structure-Activity Relationship (QSAR) models were developed to correlate the structural features of the bis-pyrimidines with their inhibitory activity, providing insights into the structure-activity relationships (SAR) that govern their potency. The experimental and theoretical findings demonstrated excellent agreement. These findings pave the way for the development of novel bis-pyrimidine-based therapeutic agents for treating hyperpigmentation and related conditions.

Pharmacophore-based virtual screening of commercial databases against β-secretase 1 for drug development against Alzheimer's disease

β-secretase 1, one of the most important proteins, is an aspartate protease. This membrane-associated protein is used for treating Alzheimer's disease (AD). Several inhibitors have been pursued against β-secretase 1, but they still have not resulted effectively. Virtual screening based on pharmacophores has been shown to be useful for lead optimization and hit identification in the preliminary phase of developing a new drug. Here, we screen the commercially available databases to find the hits against β-secretase 1 for drug discovery against AD. Virtual screening for 200,000 compounds was done using the database from the Vitas-M Laboratory. The phase screen score was utilized to assess the screened hits. Molecular docking was performed on compounds with phase scores >1.9. According to the study, the 66H ligand of the crystal structure has the maximum performance against β-secretase 1. The redocking of the co-crystal ligand showed that the docked ligand was seamlessly united with the crystal structure. The reference complex had three hydrogen bonds with Asp93, Asp289, and Gly291; one van der Waals interaction with Gly74; and three hydrophobic interactions. After equilibration, the RMSD of the reference compound sustained a value of ∼1.5 Å until 30 ns and then boosted to 2.5 Å. On comparison, the RMSD of the S1 complex steadily increased to ∼2.5 Å at 15 ns, displayed slight aberrations at approximately ∼2.5-3 Å until 80 ns, and then achieved steadiness toward the end of the simulation. The arrangements of proteins stayed condensed during the mockup when bonded to these complexes as stable Rg values showed. Furthermore, the MM/GBSA technique was employed to analyze both compounds' total binding free energies (ΔGtotal). Our research study provides a new understanding of using 66H as anti-β-secretase 1 for drug development against AD.

Comprehensive analysis of resorcinyl-imidazole Hsp90 inhibitor design

Human Hsp90 chaperones are implicated in various aspects of cancer. Due to this, Hsp90 has been explored as potential target in cancer treatment. Initial attempts to use Hsp90 inhibitors in drug trials failed due to toxicity and inefficacy. The next generation of drugs were less toxic but still insufficiently effective in a clinical setting. Recently, a lot of effort is being put into understanding the consequences of Hsp90 isoform selective inhibition, expecting that this might hold the key in targeting Hsp90 for disease treatment. Here we investigate a series of compounds containing the aryl-resorcinol scaffold with a 5-membered ring as a promising class of new human Hsp90 inhibitors, reaching nanomolar affinity. We compare how the replacement of 5-membered ring, from thiadiazole to imidazole, as well as a variety of their substituents, influences the potency of these inhibitors for Hsp90 alpha and beta isoforms. To further elucidate the dissimilarity in ligand selectivity between the isoforms, a mutant protein was constructed and tested against the ligand library. In addition, we performed a series of molecular dynamics (MD) and docking simulations to further explain our experimental findings as well as evaluated key compounds in cell assays. Our results deepen the understanding of Hsp90 isoform ligand selectivity and serve as an informative base for further Hsp90 inhibitor optimization.

Self-assembling viral histones are evolutionary intermediates between archaeal and eukaryotic nucleosomes

Nucleosomes are DNA-protein complexes composed of histone proteins that form the basis of eukaryotic chromatin. The nucleosome was a key innovation during eukaryotic evolution, but its origin from histone homologues in Archaea remains unclear. Viral histone repeats, consisting of multiple histone paralogues within a single protein, may reflect an intermediate state. Here we examine the diversity of histones encoded by Nucleocytoviricota viruses. We identified 258 histones from 168 viral metagenomes with variable domain configurations including histone singlets, doublets, triplets and quadruplets, the latter comprising the four core histones arranged in series. Viral histone repeats branch phylogenetically between Archaea and eukaryotes and display intermediate functions in Escherichia coli, self-assembling into eukaryotic-like nucleosomes that stack into archaeal-like oligomers capable of impacting genomic activity and condensing DNA. Histone linkage also facilitates nucleosome formation, promoting eukaryotic histone assembly in E. coli. These data support the hypothesis that viral histone repeats originated in stem-eukaryotes and that nucleosome evolution proceeded through histone repeat intermediates.

Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR

Recent advances in molecular modeling using deep learning can revolutionize our understanding of dynamic protein structures. NMR is particularly well-suited for determining dynamic features of biomolecular structures. The conventional process for determining biomolecular structures from experimental NMR data involves its representation as conformation-dependent restraints, followed by generation of structural models guided by these spatial restraints. Here we describe an alternative approach: generating a distribution of realistic protein conformational models using artificial intelligence-(AI-) based methods and then selecting the sets of conformers that best explain the experimental data. We applied this conformational selection approach to redetermine the solution NMR structure of the enzyme Gaussia luciferase. First, we generated a diverse set of conformer models using AlphaFold2 (AF2) with an enhanced sampling protocol. The models that best-fit NOESY and chemical shift data were then selected with a Bayesian scoring metric. The resulting models include features of both the published NMR structure and the standard AF2 model generated without enhanced sampling. This "AlphaFold-NMR" protocol also generated an alternative "open" conformational state that fits nearly as well to the overall NMR data but accounts for some NOESY data that is not consistent with first "closed" conformational state; while other NOESY data consistent with this second state are not consistent with the first conformational state. The structure of this "open" structural state differs from that of the "closed" state primarily by the position of a thumb-shaped loop between α-helices H5 and H6, revealing a cryptic surface pocket. These alternative conformational states of Gluc are supported by "double recall" analysis of NOESY data and AF2 models. Additional structural states are also indicated by backbone chemical shift data indicating partially-disordered conformations for the C-terminal segment. Considered as a multistate ensemble, these multiple states of Gluc together fit the NOESY and chemical shift data better than the "restraint-based" NMR structure and provide novel insights into its structure-dynamic-function relationships. This study demonstrates the potential of AI-based modeling with enhanced sampling to generate conformational ensembles followed by conformer selection with experimental data as an alternative to conventional restraint satisfaction protocols for protein NMR structure determination.

S. C, Gangadhar S, A. S, Murali M, Shivamallu C, Achar RR, Silina E, Stupin V, Manturova N, Shati AA, Alfaifi MY, Elbehairi SEI, Kollur SP, Amruthesh KN. Exploration of Type III effector Xanthomonas outer protein Q (XopQ) inhibitor from Picrasma quassioides as an antibacterial agent using chemoinformatics analysis

The present study was focused on exploring the efficient inhibitors of closed state (form) of type III effector Xanthomonas outer protein Q (XopQ) (PDB: 4P5F) from the 44 phytochemicals of Picrasma quassioides using cutting-edge computational analysis. Among them, Kumudine B showed excellent binding energy (-11.0 kcal/mol), followed by Picrasamide A, Quassidine I and Quassidine J with the targeted closed state of XopQ protein compared to the reference standard drug (Streptomycin). The molecular dynamics (MD) simulations performed at 300 ns validated the stability of top lead ligands (Kumudine B, Picrasamide A, and Quassidine I)-bound XopQ protein complex with slightly lower fluctuation than Streptomycin. The MM-PBSA calculation confirmed the strong interactions of top lead ligands (Kumudine B and QuassidineI) with XopQ protein, as they offered the least binding energy. The results of absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis confirmed that Quassidine I, Kumudine B and Picrasamide A were found to qualify most of the drug-likeness rules with excellent bioavailability scores compared to Streptomycin. Results of the computational studies suggested that Kumudine B, Picrasamide A, and Quassidine I could be considered potential compounds to design novel antibacterial drugs against X. oryzae infection. Further in vitro and in vivo antibacterial activities of Kumudine B, Picrasamide A, and Quassidine I are required to confirm their therapeutic potentiality in controlling the X. oryzae infection.

Modeling allosteric mechanisms of eukaryotic type II topoisomerases

Type II topoisomerases (TopoIIs) are ubiquitous enzymes that are involved in crucial nuclear processes such as genome organization, chromosome segregation, and other DNA metabolic processes. These enzymes function as large, homodimeric complexes that undergo a complex cycle of binding and hydrolysis of two ATP molecules in their ATPase domains, which regulates the capture and passage of one DNA double-helix through a second, cleaved DNA molecule. This process requires the transmission of information about the state of the bound nucleotide over vast ranges in the TopoII complex. How this information is transmitted at the molecular level to regulate TopoII functions and how protein substitutions disrupt these mechanisms remains largely unknown. Here, we employed extensive microsecond-scale molecular dynamics simulations of the yeast TopoII enzyme in multiple nucleotide-bound states and with amino acid substitutions near both the N and C termini of the complex. Simulation results indicate that the ATPase domains are remarkably flexible on the sub-microsecond timescale and that these dynamics are modulated by the identity of the bound nucleotides and both local and distant amino acid substitutions. Network analyses point toward specific allosteric networks that transmit information about the hydrolysis cycle throughout the complex, which include residues in both the protein and the bound DNA molecule. Amino acid substitutions weaken many of these pathways. Together, our results provide molecular level details on how the TopoII catalytic cycle is controlled through nucleotide binding and hydrolysis and how mutations may disrupt this process.

Normal Mode Analysis Elicits Conformational Shifts in Proteins at Both Proximal and Distal Regions to the Phosphosite Stemming from Single-Site Phosphorylation

Phosphorylation, a fundamental biochemical switch, intricately regulates protein function and signaling pathways. Our study employs extensive computational structural analyses on a curated data set of phosphorylated and unphosphorylated protein pairs to explore the multifaceted impact of phosphorylation on protein conformation. Using normal mode analysis (NMA), we investigated changes in protein flexibility post-phosphorylation, highlighting an enhanced level of structural dynamism. Our findings reveal that phosphorylation induces not only local changes at the phosphorylation site but also extensive alterations in distant regions, showcasing its far-reaching influence on protein structure-dynamics. Through in-depth case studies on polyubiquitin B and glycogen synthase kinase-3 beta, we elucidate how phosphorylation at distinct sites leads to variable structural and dynamic modifications, potentially dictating functional outcomes. While phosphorylation largely preserves the residue motion correlation, it significantly disrupts low-frequency global modes, presenting a dualistic impact on protein dynamics. We also explored alterations in the total accessible surface area (ASA), emphasizing region-specific changes around phosphorylation sites. This study sheds light on phosphorylation-induced conformational changes, dynamic modulation, and surface accessibility alterations, leveraging an integrated computational approach with RMSD, NMA, and ASA, thereby contributing to a comprehensive understanding of cellular regulation and suggesting promising avenues for therapeutic interventions.

Phylogenetic insight into ABCE gene subfamily in plants

ATP-BINDING CASSETTE SUBFAMILY E MEMBER (ABCE) proteins are one of the most conserved proteins across eukaryotes and archaea. Yeast and most animals possess a single ABCE gene encoding the critical translational factor ABCE1. In several plant species, including Arabidopsis thaliana and Oryza sativa, two or more ABCE gene copies have been identified, however information related to plant ABCE gene family is still missing. In this study we retrieved ABCE gene sequences of 76 plant species from public genome databases and comprehensively analyzed them with the reference to A. thaliana ABCE2 gene (AtABCE2). Using bioinformatic approach we assessed the conservation and phylogeny of plant ABCEs. In addition, we performed haplotype analysis of AtABCE2 and its paralogue AtABCE1 using genomic sequences of 1,135 A. thaliana ecotypes. Plant ABCE proteins showed overall high sequence conservation, sharing at least 78% of amino acid sequence identity with AtABCE2. We found that over half of the selected species have two to eight ABCE genes, suggesting that in plants ABCE genes can be classified as a low-copy gene family, rather than a single-copy gene family. The phylogenetic trees of ABCE protein sequences and the corresponding coding sequences demonstrated that Brassicaceae and Poaceae families have independently undergone lineage-specific split of the ancestral ABCE gene. Other plant species have gained ABCE gene copies through more recent duplication events. We also noticed that ploidy level but not ancient whole genome duplications experienced by a species impacts ABCE gene family size. Deeper analysis of AtABCE2 and AtABCE1 from 1,135 A. thaliana ecotypes revealed four and 35 non-synonymous SNPs, respectively. The lower natural variation in AtABCE2 compared to AtABCE1 is in consistence with its crucial role for plant viability. Overall, while the sequence of the ABCE protein family is highly conserved in the plant kingdom, many plants have evolved to have more than one copy of this essential translational factor.

Mapping Conformational Changes in the Saliva Proteome Potentially Associated with Oral Cancer Aggressiveness

Diverse proteomics-based strategies have been applied to saliva to quantitatively identify diagnostic and prognostic targets for oral cancer. Considering that these targets may be regulated by events that do not imply variation in protein abundance levels, we hypothesized that changes in protein conformation can be associated with diagnosis and prognosis, revealing biological processes and novel targets of clinical relevance. For this, we employed limited proteolysis-mass spectrometry in saliva samples to explore structural alterations, comparing the proteome of healthy control and oral squamous cell carcinoma (OSCC) patients with and without lymph node metastasis. Thirty-six proteins with potential structural rearrangements were associated with clinical patient features including transketolase and its interacting partners. Moreover, N-glycosylated peptides contribute to structural rearrangements of potential diagnostic and prognostic markers. Altogether, this approach utilizes saliva proteins to search for targets for diagnosing and prognosing oral cancer and can guide the discovery of potential regulated sites beyond protein-level abundance.

Identification of lead compound screened from the natural products atlas to treat renal inflammasomes using molecular docking and dynamics simulation

One of the most prevalent ailments is kidney disease. Effective therapies for chronic renal disease are hard to come by. As a result, there is significant clinical and social interest to predict and develop novel compounds to treat renal disorders. So, specific natural products have been employed in this study because they have protective effects against kidney diseases. When taken orally, natural products can help protect against or lessen the severity of the kidney damage caused by high fructose intake, a high-fat diet, and both Type I and Type 2 diabetes. Reduced podocyte injury, a contributor to albuminuria in diabetic nephropathy, reduces renal endothelial barrier function disruption due to hyperglycemia, as well as urinary microalbumin excretion and glomerular hyperfiltration. Multiple natural products have been shown to protect the kidneys from nephrotoxic chemicals such as LPS, gentamycin, alcohol, nicotine, lead, and cadmium, all of which can persuade acute kidney injury (AKI) or chronic kidney disease (CKD). Natural compounds inhibit regulatory enzymes for controlling inflammation-related diseases. For this, use computational methods such as drug design to identify novel flavonoid compounds against kidney diseases. Drug design via computational methods gaining admiration as a swift and effective technique to identify lead compounds in a shorter time at a low cost. In this in-silico study, we screened The Natural Product Atlas based on a structure-based pharmacophore query. Top hits were analyzed for ADMET analysis followed by molecular docking and docking validation. Finally, the lead compound was simulated for a period of 200 ns and trajectories were studied for stability. We found that NPA024823 showed promising binding and stability with the AIM2. This research work aims to predict novel anti-inflammatory compounds against kidney diseases to inhibit kidney inflammasome by targeting the AIM2 protein. So, in initial preclinical research, there will be lower failure rates that demonstrate safety profiles against predicted compounds.Communicated by Ramaswamy H. Sarma.

Binding selectivity analysis of new delhi metallo-beta-lactamase-1 inhibitors using molecular dynamics simulations: Exploring possibilities for decoding antimicrobial drug resistance

BACKGROUND

New Delhi metallo-beta-lactamase-1 (NDM1) confers resistance to several bacterial species against a broad range of beta-lactam antibiotics and turning them into superbugs that pose a significant threat to healthcare systems worldwide. As such, it is a potentially relevant biological target for counteracting bacterial infections. Given the lack of effective treatment options against NDM1 producing bacteria, finding a reliable inhibitor for the NDM1 enzyme is crucial.

METHODS

Using molecular dynamics simulations, the binding selectivities and affinities of three ligands, viz. PNK, 3S0, and N1G were investigated against NDM1.

RESULTS

The results indicate that N1G binds with more affinity to NDM1 than PNK and 3S0. The binding energy decomposition analysis revealed that residues I35, W93, H189, K211, and N220 showed significant binding energies with PNK, 3S0, and N1G, and hence are crucially involved in the binding of the ligands to NDM1. Molecular dynamics trajectory analysis further elicited that the ligands influence dynamic flexibility of NDM1 morphology, which contributes to the partial selectivities of PNK, 3S0, and N1G.

CONCLUSIONS

This in silico study offers a vital information for developing potential NDM1 inhibitors with high selectivity. Nevertheless, in vitro and in vivo experimental validation is mandated to extend the possible applications of these ligands as NDM1 inhibitors that succor in combating antimicrobial resistance.

Comprehensive structural overview of the C-terminal ligand-binding domains of the TetR family regulators

TetR family regulators (TFRs) represent a large group of one-component bacterial signal transduction systems which recognize environmental signals, like the presence of antibiotics or other bactericidal compounds, and trigger the cell response by regulating the expression of genes that secure bacterial survival in harsh environmental conditions. TFRs act as homodimers, each protomer is composed of a conserved DNA-binding N-terminal domain (NTD) and a variable ligand-binding C-terminal domain (CTD). Currently, there are about 500 structures of TFRs available in the Protein Data Bank and one-fourth of them represent the structures of TFR-ligand complexes. In this review, we summarized information on the ligands interacting with TFRs and based on structural data, we compared the CTDs of the TFR family members, as well as their ligand-binding cavities. Additionally, we divided the whole TFR family, including more than half of a million sequences, into subfamilies according to calculated multiple sequence alignment and phylogenetic tree. We also highlighted structural elements characteristic of some of the subfamilies. The presented comprehensive overview of the TFR CTDs provides good bases and future directions for further studies on TFRs that are not only important targets for battling multidrug resistance but also good candidates for many biotechnological approaches, like TFR-based biosensors.

Complete genome assembly provides a high-quality skeleton for pan-NLRome construction in melon

Melon (Cucumis melo L.), being under intensive domestication and selective breeding, displays an abundant phenotypic diversity. Wild germplasm with tolerance to stress represents an untapped genetic resource for discovery of disease-resistance genes. To comprehensively characterize resistance genes in melon, we generate a telomere-to-telomere (T2T) and gap-free genome of wild melon accession PI511890 (C. melo var. chito) with a total length of 375.0 Mb and a contig N50 of 31.24 Mb. The complete genome allows us to dissect genome architecture and identify resistance gene analogs. We construct a pan-NLRome using seven melon genomes, which include 208 variable and 18 core nucleotide-binding leucine-rich repeat receptors (NLRs). Multiple disease-related transcriptome analyses indicate that most up-regulated NLRs induced by pathogens are shell or cloud NLRs. The T2T gap-free assembly and the pan-NLRome not only serve as essential resources for genomic studies and molecular breeding of melon but also provide insights into the genome architecture and NLR diversity.

Effect of Free Cysteine Residues to Serine Mutation on Cellodextrin Phosphorylase

Cellodextrin phosphorylase (CDP) plays a key role in energy-efficient cellulose metabolism of anaerobic bacteria by catalyzing phosphorolysis of cellodextrin to produce cellobiose and glucose 1-phosphate, which can be utilized for glycolysis without consumption of additional ATP. As the enzymatic phosphorolysis reaction is reversible, CDP is also employed to produce cellulosic materials in vitro. However, the enzyme is rapidly inactivated by oxidation, which hinders in vitro utilization in aerobic environments. It has been suggested that the cysteine residues of CDP, which do not form disulfide bonds, are responsible for the loss of activity, and the aim of the present work was to test this idea. For this purpose, we replaced all 11 free cysteine residues of CDP from Acetivibrio thermocellus (formerly known as Clostridium thermocellum) with serine, which structurally resembles cysteine in our previous work. Herein, we show that the resulting CDP variant, named CDP-CS, has comparable activity to the wild-type enzyme, but shows increased stability to oxidation during long-term storage. X-Ray crystallography indicated that the mutations did not markedly alter the overall structure of the enzyme. Ensemble refinement of the crystal structures of CDP and CDP-CS indicated that the C372S and C625S mutations reduce structural fluctuations in the protein main chain, which may contribute to the increased stability of CDP-CS to oxidation.

The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics

Mutations in transporters can impact an individual's response to drugs and cause many diseases. Few variants in transporters have been evaluated for their functional impact. Here, we combine saturation mutagenesis and multi-phenotypic screening to dissect the impact of 11,213 missense single-amino-acid deletions, and synonymous variants across the 554 residues of OCT1, a key liver xenobiotic transporter. By quantifying in parallel expression and substrate uptake, we find that most variants exert their primary effect on protein abundance, a phenotype not commonly measured alongside function. Using our mutagenesis results combined with structure prediction and molecular dynamic simulations, we develop accurate structure-function models of the entire transport cycle, providing biophysical characterization of all known and possible human OCT1 polymorphisms. This work provides a complete functional map of OCT1 variants along with a framework for integrating functional genomics, biophysical modeling, and human genetics to predict variant effects on disease and drug efficacy.

AlphaFold2 modeling and molecular dynamics simulations of an intrinsically disordered protein

We use AlphaFold2 (AF2) to model the monomer and dimer structures of an intrinsically disordered protein (IDP), Nvjp-1, assisted by molecular dynamics (MD) simulations. We observe relatively rigid dimeric structures of Nvjp-1 when compared with the monomer structures. We suggest that protein conformations from multiple AF2 models and those from MD trajectories exhibit a coherent trend: the conformations of an IDP are deviated from each other and the conformations of a well-folded protein are consistent with each other. We use a residue-residue interaction network (RIN) derived from the contact map which show that the residue-residue interactions in Nvjp-1 are mainly transient; however, those in a well-folded protein are mainly persistent. Despite the variation in 3D shapes, we show that the AF2 models of both disordered and ordered proteins exhibit highly consistent profiles of the pLDDT (predicted local distance difference test) scores. These results indicate a potential protocol to justify the IDPs based on multiple AF2 models and MD simulations.

Potential anti-obesity effect of saponin metabolites from adzuki beans: A computational approach

In contrast to its widespread traditional and popular culinary use to reduce weight, Vigna angularis (adzuki beans) was not subjected to sufficient scientific scrutiny. Particularly, its saponins whose role was never investigated before to unveil the beans' antidiabetic and anti-obesity effects. Four vital pancreatic and intestinal carbohydrate enzymes were selected to assess the potency of the triterpenoidal saponins of V. angularis to bind and activate these proteins through high-precision molecular modeling and dynamics mechanisms with accurate molecular mechanics Generalized Born Surface Area (MMGBSA) energy calculations; thus, recognizing their anti-obesity potential. Our results showed that adzukisaponin VI and adzukisaponin IV were the best compounds in the α-amylase and α-glucosidase enzymatic grooves, respectively. Adzukisaponin VI and angulasaponin C were the best fitting in the N-termini of sucrase-isomaltose (SI) enzyme, and angulasaponin C was the best scoring compound in maltase-glucoamylase C-termini. All of them outperformed the standard drug acarbose. These compounds in their protein complexes were selected to undergo molecular simulations of the drug-bound protein compared to the apo-protein through 100 ns, which confirmed the consistency of binding to the key amino acid residues in the four enzyme pockets with the least propensity of unfolding. Detailed analysis is given of the different polar and hydrophobic binding interactions of docked compounds. While maltase-adzukisaponin VI complex scored the lowest MMGBSA free energy of -67.77 Kcal/mol, α-amylase complex with angulasaponin B revealed the free binding energy of -74.18 Kcal/mol with a dominance of van der Waals energy (ΔEVDW) and the least change from the start to the end of the simulation time. This study will direct researchers to the significance of isolating the pure adzuki saponin components to conduct future in vitro and in vivo experimental works and even clinical trials.

An in-silico approach to unravel the structure of 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase (DAHPS): a critical enzyme for sennoside biosynthesis in Cassia angustifolia Vahl

The laxative properties of senna are attributed to the presence of sennosides produced in the plant. The low production level of sennosides in the plant is an important impediment to their growing demand and utilization. Understanding biosynthetic pathways helps to engineer them in terms of enhanced production. The biosynthetic pathways of sennoside production in plants are not completely known yet. However, attempts to get information on genes and proteins engaged in it have been made which decode involvement of various pathways including shikimate pathway. 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase (DAHPS) is a key enzyme involved in sennosides production through the shikimate pathway. Unfortunately, there is no information available on proteomic characterization of DAHPS enzyme of senna (caDAHPS) resulting in lack of knowledge about its role. We for the first time characterized DAHPS enzyme of senna using in-silico analysis. To the best of our knowledge this is the first attempt to identify the coding sequence of caDAHPS by cloning and sequencing. We found Gln179, Arg175, Glu462, Glu302, Lys357 and His420 amino acids in the active site of caDAHPS through molecular docking. followed by molecular dynamic simulation. The amino acid residues, Lys182, Cys136, His460, Leu304, Gly333, Glu334, Pro183, Asp492 and Arg433 at the surface interact with PEP by van der Waals bonds imparting stability to the enzyme-substrate complex. Docking results were further validated by molecular dynamics. The presented in-silico analysis of caDAHPS will generate opportunities to engineer the sennoside biosynthesis in plants.Communicated by Ramaswamy H. Sarma.

Investigation of the insecticidal potential of curcumin derivatives that target the Helicoverpa armigera sterol carrier protein-2

Cotton bollworm (Helicoverpa armigera) is a highly polyphagous, widely prevalent, and persistent Old World insect pest that affects numerous important crops that are directly consumed by people, including tomato, cotton, pigeon pea, chickpea, rice, sorghum, and cowpea. Insects do not synthesize steroids but obtain them from their diet. Inhibition of dietary uptake of steroids by insects is a potentially effective insecticidal mechanism that should not be toxic to humans and other mammals, who synthesize their steroids. Ten curcumin derivatives were tested against H. armigera sterol carrier protein-2 (HaSCP-2) for their potential as insecticidal agents. Curcumin derivatives were initially docked at the binding site of HaSCP-2 to determine their binding affinities and plausible binding modes. The binding modes predominantly show hydrophobic interactions of derivatives with Phe53, Phe110, and Phe89 as core interacting residues in the active site. Validation of in silico results was carried out by performing a fluorescence binding and displacement assay to determine the binding affinities of curcumin derivatives. Among a collection of curcumin derivatives tested, Cur10 showed the lowest IC50 value of 9.64 μM, while Cur07 was 19.86 μM, and Cur06 was 20.79 μM. There was a significant negative correlation between the ability of the curcumin derivatives tested to displace the fluorescent probe from the sterol binding site of HaSCP-2 and to inhibit Sf9 insect cell growth in culture, which is consistent with the curcumin derivatives acting by the novel mechanism of blocking sterol uptake. Then molecular dynamics simulation studies validated the predicted binding modes and the interactions of curcumin derivatives with HaSCP-2 protein. In conclusion, these studies support the potential use of curcumin derivatives as insecticidal agents.

A complete map of specificity encoding for a partially fuzzy protein interaction

Thousands of human proteins function by binding short linear motifs embedded in intrinsically disordered regions. How affinity and specificity are encoded in these binding domains and the motifs themselves is not well understood. The evolvability of binding specificity - how rapidly and extensively it can change upon mutation - is also largely unexplored, as is the contribution of 'fuzzy' dynamic residues to affinity and specificity in protein-protein interactions. Here we report the first complete map of specificity encoding for a globular protein domain. Quantifying >200,000 energetic interactions between a PDZ domain and its ligand identifies 20 major energetically coupled pairs of sites that control specificity. These are organized into six modules, with most mutations in each module reprogramming specificity for a single position in the ligand. Nine of the major energetic couplings controlling specificity are between structural contacts and 11 have an allosteric mechanism of action. The dynamic tail of the ligand is more robust to mutation than the structured residues but contributes additively to binding affinity and communicates with structured residues to enable changes in specificity. Our results quantify the binding specificities of >1,800 globular proteins to reveal how specificity is encoded and provide a direct comparison of the encoding of affinity and specificity in structured and dynamic molecular recognition.

Community analysis of large-scale molecular dynamics simulations elucidated dynamics-driven allostery in tyrosine kinase 2

TYK2 is a nonreceptor tyrosine kinase, member of the Janus kinases (JAK), with a central role in several diseases, including cancer. The JAKs' catalytic domains (KD) are highly conserved, yet the isolated TYK2-KD exhibits unique specificities. In a previous work, using molecular dynamics (MD) simulations of a catalytically impaired TYK2-KD variant (P1104A) we found that this amino acid change of its JAK-characteristic insert (αFG), acts at the dynamics level. Given that structural dynamics is key to the allosteric activation of protein kinases, in this study we applied a long-scale MD simulation and investigated an active TYK2-KD form in the presence of adenosine 5'-triphosphate and one magnesium ion that represents a dynamic and crucial step of the catalytic cycle, in other protein kinases. Community analysis of the MD trajectory shed light, for the first time, on the dynamic profile and dynamics-driven allosteric communications within the TYK2-KD during activation and revealed that αFG and amino acids P1104, P1105, and I1112 in particular, hold a pivotal role and act synergistically with a dynamically coupled communication network of amino acids serving intra-KD signaling for allosteric regulation of TYK2 activity. Corroborating our findings, most of the identified amino acids are associated with cancer-related missense/splice-site mutations of the Tyk2 gene. We propose that the conformational dynamics at this step of the catalytic cycle, coordinated by αFG, underlie TYK2-unique substrate recognition and account for its distinct specificity. In total, this work adds to knowledge towards an in-depth understanding of TYK2 activation and may be valuable towards a rational design of allosteric TYK2-specific inhibitors.

3Dmapper: a command line tool for BioBank-scale mapping of variants to protein structures

MOTIVATION

The interpretation of genomic data is crucial to understand the molecular mechanisms of biological processes. Protein structures play a vital role in facilitating this interpretation by providing functional context to genetic coding variants. However, mapping genes to proteins is a tedious and error-prone task due to inconsistencies in data formats. Over the past two decades, numerous tools and databases have been developed to automatically map annotated positions and variants to protein structures. However, most of these tools are web-based and not well-suited for large-scale genomic data analysis.

RESULTS

To address this issue, we introduce 3Dmapper, a stand-alone command-line tool developed in Python and R. It systematically maps annotated protein positions and variants to protein structures, providing a solution that is both efficient and reliable.

AVAILABILITY AND IMPLEMENTATION

https://github.com/vicruiser/3Dmapper.

Modeling Allosteric Mechanisms of Eukaryotic Type II Topoisomerases

Type II topoisomerases (TopoIIs) are ubiquitous enzymes that are involved in crucial nuclear processes such as genome organization, chromosome segregation, and other DNA metabolic processes. These enzymes function as large, homodimeric complexes that undergo a complex cycle of binding and hydrolysis of two ATP molecules in their ATPase domains, which regulates the capture and passage of one DNA double-helix through a second, cleaved DNA molecule. This process requires the transmission of information about the state of the bound nucleotide over vast ranges in the TopoII complex. How this information is transmitted at the molecular level to regulate TopoII functions and how protein substitutions disrupt these mechanisms remains largely unknown. Here, we employed extensive microsecond scale molecular dynamics simulations of the yeast TopoII enzyme in multiple nucleotide-bound states and with amino acid substitutions near both the N- and C-terminals of the complex. Simulation results indicate that the ATPase domains are remarkably flexible on the sub-microsecond timescale and that these dynamics are modulated by the identity of the bound nucleotides and both local and distant amino acid substitutions. Network analyses point towards specific allosteric networks that transmit information about the hydrolysis cycle throughout the complex, which include residues in both the protein and the bound DNA molecule. Amino acid substitutions weaken many of these pathways. Together, our results provide molecular-level details on how the TopoII catalytic cycle is controlled through nucleotide binding and hydrolysis and how mutations may disrupt this process.

SARS-CoV-2 Omicron XBB lineage spike structures, conformations, antigenicity, and receptor recognition

A recombinant lineage of the SARS-CoV-2 Omicron variant, named XBB, appeared in late 2022 and evolved descendants that successively swept local and global populations. XBB lineage members were noted for their improved immune evasion and transmissibility. Here, we determine cryo-EM structures of XBB.1.5, XBB.1.16, EG.5 and EG.5.1 spike (S) ectodomains to reveal reinforced 3-RBD-down receptor inaccessible closed states mediated by interprotomer receptor binding domain (RBD) interactions previously observed in BA.1 and BA.2. Improved XBB.1.5 and XBB.1.16 RBD stability compensated for stability loss caused by early Omicron mutations, while the F456L substitution reduced EG.5 RBD stability. S1 subunit mutations had long-range impacts on conformation and epitope presentation in the S2 subunit. Our results reveal continued S protein evolution via simultaneous optimization of multiple parameters including stability, receptor binding and immune evasion, and the dramatic effects of relatively few residue substitutions in altering the S protein conformational landscape.

Dissecting the Allosteric Fine-Tuning of Enzyme Catalysis

Fully understanding the mechanism of allosteric regulation in biomolecules requires separating and examining all of the involved factors. In enzyme catalysis, allosteric effector binding shifts the structure and dynamics of the active site, leading to modified energetic (e.g., energy barrier) and dynamical (e.g., diffusion coefficient) factors underlying the catalyzed reaction rate. Such modifications can be subtle and dependent on the type of allosteric effector, representing a fine-tuning of protein function. The microscopic description of allosteric regulation at the level of function-dictating factors has prospective applications in fundamental and pharmaceutical sciences, which is, however, largely missing so far. Here, we characterize the allosteric fine-tuning of enzyme catalysis, using human Pin1 as an example, by performing more than half-millisecond all-atom molecular dynamics simulations. Changes of reaction kinetics and the dictating factors, including the free energy surface along the reaction coordinate and the diffusion coefficient of the reaction dynamics, under various enzyme and allosteric effector binding conditions are examined. Our results suggest equal importance of the energetic and dynamical factors, both of which can be modulated allosterically, and the combined effect determines the final allosteric output. We also reveal the potential dynamic basis for allosteric modulation using an advanced statistical technique to detect function-related conformational dynamics. Methods developed in this work can be applied to other allosteric systems.

In Silico Insights into the Arsenic Binding Mechanism Deploying Application of Computational Biology-Based Toolsets

An assortment of environmental matrices includes arsenic (As) in its different oxidation states, which is often linked to concerns that pose a threat to public health worldwide. The current difficulty lies in addressing toxicological concerns and achieving sustained detoxification of As. Multiple conventional degradation methods are accessible; however, they are indeed labor-intensive, expensive, and reliant on prolonged laboratory evaluations. Molecular interaction and atomic level degradation mechanisms for enzyme-As exploration are, however, underexplored in those approaches. A feasible approach in this case for tackling this accompanying concern of As might be to cope with undertaking multivalent computational methodologies and tools. This work aimed to provide molecular-level insight into the enzyme-aided As degradation mechanism. AutoDock Vina, CABS-flex 2.0, and Desmond high-performance molecular dynamics simulation (MDS) were utilized in the current investigation to simulate multivalent molecular processes on two protein sets: arsenate reductase (ArsC) and laccase (LAC) corresponding arsenate (ART) and arsenite (AST), which served as model ligands to comprehend binding, conformational, and energy attributes. The structural configurations of both proteins exhibited variability in flexibility and structure framework within the range of 3.5-4.5 Å. The LAC-ART complex exhibited the lowest calculated binding affinity, measuring -5.82 ± 0.01 kcal/mol. Meanwhile, active site residues ILE-200 and HIS-206 were demonstrated to engage in H-bonding with the ART ligand. In contrast to ArsC, the ligand binding affinity of this bound complex was considerably greater. Additional validation of docked complexes was carried out by deploying Desmond MDS of 100 ns to capture protein and ligand conformation behavior. The system achieved stability during the 100 ns simulation run, as confirmed by the average P-L RMSD, which was ∼1 Å. As a preliminary test of the enzyme's ability to catalyze As species, corresponding computational insights might be advantageous for bridging gaps and regulatory consideration.

Selective Bias Virtual Screening for Discovery of Promising Antimalarial Candidates targeting Plasmodium N-Myristoyltransferase

Malaria remains a significant public health challenge, with Plasmodium vivax being the species responsible for the most prevalent form of the disease. Given the limited therapeutic options available, the search for new antimalarials against P. vivax is urgent. This study aims to identify new inhibitors for P. vivax N-myristoyltransferase (PvNMT), an essential drug target against malaria. Through a validated virtual screening campaign, we prioritized 23 candidates for further testing. In the yeast NMT system, seven compounds exhibit a potential inhibitor phenotype. In vitro antimalarial phenotypic assays confirmed the activity of four candidates while demonstrating an absence of cytotoxicity. Enzymatic assays reveal LabMol-394 as the most promising inhibitor, displaying selectivity against the parasite and a strong correlation within the yeast system. Furthermore, molecular dynamics simulations shed some light into its binding mode. This study constitutes a substantial contribution to the exploration of a selective quinoline scaffold and provides valuable insights into the development of new antimalarial candidates.

Designer high-density lipoprotein particles enhance endothelial barrier function and suppress inflammation

High-density lipoprotein (HDL) nanoparticles promote endothelial cell (EC) function and suppress inflammation, but their utility in treating EC dysfunction has not been fully explored. Here, we describe a fusion protein named ApoA1-ApoM (A1M) consisting of apolipoprotein A1 (ApoA1), the principal structural protein of HDL that forms lipid nanoparticles, and ApoM, a chaperone for the bioactive lipid sphingosine 1-phosphate (S1P). A1M forms HDL-like particles, binds to S1P, and is signaling competent. Molecular dynamics simulations showed that the S1P-bound ApoM moiety in A1M efficiently activated EC surface receptors. Treatment of human umbilical vein ECs with A1M-S1P stimulated barrier function either alone or cooperatively with other barrier-enhancing molecules, including the stable prostacyclin analog iloprost, and suppressed cytokine-induced inflammation. A1M-S1P injection into mice during sterile inflammation suppressed neutrophil influx and inflammatory mediator secretion. Moreover, systemic A1M administration led to a sustained increase in circulating HDL-bound S1P and suppressed inflammation in a murine model of LPS-induced endotoxemia. We propose that A1M administration may enhance vascular endothelial barrier function, suppress cytokine storm, and promote resilience of the vascular endothelium.

Association of epilepsy and neurological impairments with homozygous recessive missense mutations found in the genes responsible for ganglioside biosynthesis (ST3GAL5) and calcium voltage-gated channels (CACNA1H) - insights through molecular dynamic simulations

With over 2.2 million cases, the incidence rate of epilepsy in Pakistan is far higher than the rest of the world due primarily to the frequent, traditionally imposed cousin marriages. In the present study, comprehensive whole exome sequencing (WES) analyses of a three-generation family with four affected members presenting 'unexplained' childhood absence epilepsy (CAE), seizures and dementia, was performed in a quest to identify heritable, epilepsy-causal gene variants to better aid in carrier screening and genetic counselling. The WES data was generated, analyzed, and validated through Sanger's sequencing, molecular dynamic simulation (MDS) analysis, and molecular mechanics with generalized Born and surface area solvation (MM/GBSA) studies. Two homozygous recessive, missense mutations in ST3GAL5 (c.311A > G, p. His104Arg) and CACNA1H (c.6230G > A, p. Arg2077His) genes, earlier regarded as benign or of uncertain significance, have been identified as a potential etiology. Comparative MDS and free binding energy calculations revealed substantial structural perturbations in mutant forms of ST3GAL5 leading to decreased binding and reduced catalytic activity of the p.His104Arg and two other functional variants (p.Val74Glu and p.Arg288Ter) when compared with wild type. Our findings reinforce that WES analyses may uncover 'hidden', heritable variants and together with MDS and MM/GBSA may provide plausible clues to answer the unexplained causes of epilepsy for an effective management and better patient outcome. Further, revisit of epilepsy-associated mutational landscape in population context is imperative as the variants with 'benign' tags may turn out to be 'non-benign', when exist in combination with other benign.Communicated by Ramaswamy H. Sarma.

Identification of potential inhibitor against Leishmania donovani mitochondrial DNA primase through in-silico and in vitro drug repurposing approaches

Leishmania donovani is the causal organism of leishmaniasis with critical health implications affecting about 12 million people around the globe. Due to less efficacy, adverse side effects, and resistance, the available therapeutic molecules fail to control leishmaniasis. The mitochondrial primase of Leishmania donovani (LdmtPRI1) is a vital cog in the DNA replication mechanism, as the enzyme initiates the replication of the mitochondrial genome of Leishmania donovani. Hence, we target this protein as a probable drug target against leishmaniasis. The de-novo approach enabled computational prediction of the three-dimensional structure of LdmtPRI1, and its active sites were identified. Ligands from commercially available drug compounds were selected and docked against LdmtPRI1. The compounds were chosen for pharmacokinetic study and molecular dynamics simulation based on their binding energies and protein interactions. The LdmtPRI1 gene was cloned, overexpressed, and purified, and a primase activity assay was performed. The selected compounds were verified experimentally by the parasite and primase inhibition assay. Capecitabine was observed to be effective against the promastigote form of Leishmania donovani, as well as inhibiting primase activity. This study's findings suggest capecitabine might be a potential anti-leishmanial drug candidate after adequate further studies.

Identification and mechanistic exploration of structural and conformational dynamics of NF-kB inhibitors: rationale insights from in silico and in vitro studies

Increased expression of target genes that code for proinflammatory chemical mediators results from a series of intracellular cascades triggered by activation of dysregulated NF-κB signaling pathway. Dysfunctional NF-kB signaling amplifies and perpetuates autoimmune responses in inflammatory diseases, including psoriasis. This study aimed to identify therapeutically relevant NF-kB inhibitors and elucidate the mechanistic aspects behind NF-kB inhibition. After virtual screening and molecular docking, five hit NF-kB inhibitors opted, and their therapeutic efficacy was examined using cell-based assays in TNF-α stimulated human keratinocyte cells. To investigate the conformational changes of target protein and inhibitor-protein interaction mechanisms, molecular dynamics (MD) simulations, binding free energy calculations together with principal component (PC) analysis, dynamics cross-correlation matrix analysis (DCCM), free energy landscape (FEL) analysis and quantum mechanical calculations were carried out. Among identified NF-kB inhibitors, myricetin and hesperidin significantly scavenged intracellular ROS and inhibited NF-kB activation. Analysis of the MD simulation trajectories of ligand-protein complexes revealed that myricetin and hesperidin formed energetically stabilized complexes with the target protein and were able to lock NF-kB in a closed conformation. Myricetin and hesperidin binding to the target protein significantly impacted conformational changes and internal dynamics of amino acid residues in protein domains. Tyr57, Glu60, Lys144 and Asp239 residues majorly contributed to locking the NF-kB in a closed conformation. The combinatorial approach employing in silico tools integrated with cell-based approaches substantiated the binding mechanism and NF-kB active site inhibition by the lead molecule myricetin, which can be explored as a viable antipsoriatic drug candidate associated with dysregulated NF-kB.Communicated by Ramaswamy H. Sarma.

Emerging role of carbonyl-carbonyl interactions in the classification of beta turns

Carbonyl-carbonyl interactions in peptides and proteins attracted considerable interest in recent years. Here, we report a survey of carbonyl-carbonyl interactions in cyclic peptides, depsipeptides, peptoids and discuss the relationship between backbone torsion angles and CO∙∙∙CO distances. In general, φ values in the range between -40° and -90° and between 40° and 90° correspond to CO∙∙∙CO distances below 3.22 Å. By extending the analysis of carbonyl-carbonyl interactions in different types of beta turns in proteins, we also highlight the role of direct or reciprocal carbonyl-carbonyl interactions in stabilizing the beta turn conformation for each specific type. We confirmed the new type II beta turn, detected by Dunbrack and coworkers, and named Pa, and detect the presence of a direct carbonyl-carbonyl interaction between the second and third residues of the turn. We also evidenced the existence of another new type II beta turn, named pA (following Dunbrack's notation), which represents the alternative conformation of Pa with opposite φ and ψ values and is characterized by a direct carbonyl-carbonyl interaction between the second and third residues of the turn. Finally, we show that the occurrence of CO∙∙∙CO interactions could be also advocated to explain from a chemical point of view the diversity of turn types.

Uncovering New Conformational States of the Substrate Binding Pocket of LSD1 Potential for Inhibitor Design via Funnel Metadynamics

Lysine-specific demethylase 1 (LSD1) is a promising therapeutic target for cancer therapy. So far, over 80 crystal structures of LSD1 in different complex states have been deposited in the Protein Data Bank, which are valuable resources for performing structure-based drug design. However, among all of the crystal structures of LSD1, the substrate binding pocket, which is the most efficient druggable site for designing LSD1 inhibitors at present, is very similar no matter whether LSD1 is in the apo or any holo forms, which is inconsistent with its versatile demethylase functions. To investigate whether the substrate binding pocket is rigid or exhibits other representative conformations different from the crystal conformations that are feasible for designing new LSD1 inhibitors, we performed funnel metadynamics simulations to study the conformation dynamics of LSD1 in the binding process of two effective LSD1 inhibitors (CC-90011 and 6X0, CC-90011 undergoing clinical trials). Our results showed that the entrance of the substrate binding pocket is very flexible. Two representative entrance conformations of LSD1 counting against binding with the substrate of histone H3 were detected, which may be used for structure-based LSD1 inhibitor design. Besides, alternative optimal binding modes and prebinding modes for both inhibitors were also detected, which depicted that the key interactions changed along with the binding process. Our results should provide great help for LSD1 inhibitor design.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.

Design and synthesis of 2-amino-4,6-diarylpyrimidine derivatives as potent α-glucosidase and α-amylase inhibitors: structure-activity relationship, in vitro, QSAR, molecular docking, MD simulations and drug-likeness studies

In the present study, a series of 2-amino-4,6-diarylpyrimidine derivatives was designed, synthesized, characterized and evaluated for their in vitro α-glucosidase and α-amylase enzyme inhibition assays. The outcomes proved that this class of compounds exhibit considerable inhibitory activity against both enzymes. Among the target compounds, compounds 4p and 6p demonstrated the most potent dual inhibition with IC50 = 0.087 ± 0.01 μM for α-glucosidase; 0.189 ± 0.02 μM for α-amylase and IC50 = 0.095 ± 0.03 μM for α-glucosidase; 0.214 ± 0.03 μM for α-amylase, respectively as compared to the standard rutin (IC50 = 0.192 ± 0.02 μM for α-glucosidase and 0.224 ± 0.02 μM for α-amylase). Remarkably, the enzyme inhibition results indicate that test compounds have stronger inhibitory effect on the target enzymes than the positive control, with a significantly lower IC50 value. Moreover, these series of compounds were found to inhibit α-glucosidase activity in a reversible mixed-type manner with IC50 between 0.087 ± 0.01 μM to 1.952 ± 0.26 μM. Furthermore, molecular docking studies were performed to affirm the binding interactions of this scaffold to the active sites of α-glucosidase and α-amylase enzymes. The quantitative structure-activity relationship (QSAR) investigations showed a strong association between 1p-15p structures and their inhibitory actions (IC50) with a correlation value (R2) of 0.999916. Finally, molecular dynamic (MD) simulations were carried out to assess the dynamic behavior, stability of the protein-ligand complex, and binding affinity of the most active inhibitor 4p. The experimental and theoretical results therefore exposed a very good compatibility. Additionally, the drug-likeness assay revealed that some compounds exhibit a linear association with Lipinski's rule of five, indicating good drug-likeness and bioactivity scores for pharmacological targets.Communicated by Ramaswamy H. Sarma.