CHARMMing: a new, flexible web portal for CHARMM

Substrate specificity controlled by the exit site of human P4-ATPases, revealed by de novo point mutations in neurological disorders

The maintenance of lipid asymmetry on the plasma membrane is regulated by flippases, such as ATP8A2, ATP11A, and ATP11C, which translocate phosphatidylserine and phosphatidylethanolamine from the outer leaflet to the inner leaflet. We previously identified a patient-derived point mutation (Q84E) in ATP11A at the phospholipid entry site, which acquired the ability to flip phosphatidylcholine (PtdCho). This mutation led to elevated levels of sphingomyelin (SM) in the outer leaflet of the plasma membrane. We herein present two de novo ATP11A dominant mutations (E114G and S399L) in heterozygous patients exhibiting neurological and developmental disorders. These mutations, situated near the predicted phospholipid exit site, similarly confer the ability for ATP11A to recognize PtdCho as a substrate, resulting in its internalization into cells. Cells expressing these mutants had increased SM levels on their surface, attributed to the up-regulated expression of the sphingomyelin synthase-1 gene, rendering them more susceptible to SM phosphodiesterase-mediated cell lysis. Corresponding mutations in ATP11C and ATP8A2, paralogs of ATP11A, exerted similar effects on PtdCho-flipping activity and increased SM levels on the cell surface. Molecular dynamics simulations, based on the ATP11C structure, suggest that the E114G and S399L mutations enhance ATP11C's affinity toward PtdCho. These findings underscore the importance of the well-conserved exit and entry sites in determining phospholipid substrate specificity and indicate that aberrant flipping of PtdCho contributes to neurological disorders.

In Silico Deciphering of the Potential Impact of Variants of Uncertain Significance in Hereditary Colorectal Cancer Syndromes

Colorectal cancer (CRC) ranks third in terms of cancer incidence worldwide and is responsible for 8% of all deaths globally. Approximately 10% of CRC cases are caused by inherited pathogenic mutations in driver genes involved in pathways that are crucial for CRC tumorigenesis and progression. These hereditary mutations significantly increase the risk of initial benign polyps or adenomas developing into cancer. In recent years, the rapid and accurate sequencing of CRC-specific multigene panels by next-generation sequencing (NGS) technologies has enabled the identification of several recurrent pathogenic variants with established functional consequences. In parallel, rare genetic variants that are not characterized and are, therefore, called variants of uncertain significance (VUSs) have also been detected. The classification of VUSs is a challenging task because each amino acid has specific biochemical properties and uniquely contributes to the structural stability and functional activity of proteins. In this scenario, the ability to computationally predict the effect of a VUS is crucial. In particular, in silico prediction methods can provide useful insights to assess the potential impact of a VUS and support additional clinical evaluation. This approach can further benefit from recent advances in artificial intelligence-based technologies. In this review, we describe the main in silico prediction tools that can be used to evaluate the structural and functional impact of VUSs and provide examples of their application in the analysis of gene variants involved in hereditary CRC syndromes.

Using atomistic solution scattering modelling to elucidate the role of the Fc glycans in human IgG4

Human immunoglobulin G (IgG) exists as four subclasses IgG1-4, each of which has two Fab subunits joined by two hinges to a Fc subunit. IgG4 has the shortest hinge with 12 residues. The Fc subunit has two glycan chains, but the importance of glycosylation is not fully understood in IgG4. Here, to evaluate the stability and structure of non-glycosylated IgG4, we performed a multidisciplinary structural study of glycosylated and deglycosylated human IgG4 A33 for comparison with our similar study of human IgG1 A33. After deglycosylation, IgG4 was found to be monomeric by analytical ultracentrifugation; its sedimentation coefficient of 6.52 S was reduced by 0.27 S in reflection of its lower mass. X-ray and neutron solution scattering showed that the overall Guinier radius of gyration RG and its cross-sectional values after deglycosylation were almost unchanged. In the P(r) distance distribution curves, the two M1 and M2 peaks that monitor the two most common distances within IgG4 were unchanged following deglycosylation. Further insight from Monte Carlo simulations for glycosylated and deglycosylated IgG4 came from 111,382 and 117,135 possible structures respectively. Their comparison to the X-ray and neutron scattering curves identified several hundred best-fit models for both forms of IgG4. Principal component analyses showed that glycosylated and deglycosylated IgG4 exhibited different conformations from each other. Within the constraint of unchanged RG and M1-M2 values, the glycosylated IgG4 models showed more restricted Fc conformations compared to deglycosylated IgG4, but no other changes. Kratky plots supported this interpretation of greater disorder upon deglycosylation, also observed in IgG1. Overall, these more variable Fc conformations may demonstrate a generalisable impact of deglycosylation on Fc structures, but with no large conformational changes in IgG4 unlike those seen in IgG1.

MoSDeF-GOMC: Python Software for the Creation of Scientific Workflows for the Monte Carlo Simulation Engine GOMC

MoSDeF-GOMC is a python interface for the Monte Carlo software GOMC to the Molecular Simulation Design Framework (MoSDeF) ecosystem. MoSDeF-GOMC automates the process of generating initial coordinates, assigning force field parameters, and writing coordinate (PDB), connectivity (PSF), force field parameter, and simulation control files. The software lowers entry barriers for novice users while allowing advanced users to create complex workflows that encapsulate simulation setup, execution, and data analysis in a single script. All relevant simulation parameters are encoded within the workflow, ensuring reproducible simulations. MoSDeF-GOMC's capabilities are illustrated through a number of examples, including prediction of the adsorption isotherm for CO₂ in IRMOF-1, free energies of hydration for neon and radon over a broad temperature range, and the vapor-liquid coexistence curve of a four-component surrogate for the jet fuel S-8. The MoSDeF-GOMC software is available on GitHub at https://github.com/GOMC-WSU/MoSDeF-GOMC.

A De Novo-Designed Type 3 Copper Protein Tunes Catechol Substrate Recognition and Reactivity

De novo metalloprotein design is a remarkable approach to shape protein scaffolds toward specific functions. Here, we report the design and characterization of Due Rame 1 (DR1), a de novo designed protein housing a di-copper site and mimicking the Type 3 (T3) copper-containing polyphenol oxidases (PPOs). To achieve this goal, we hierarchically designed the first and the second di-metal coordination spheres to engineer the di-copper site into a simple four-helix bundle scaffold. Spectroscopic, thermodynamic, and functional characterization revealed that DR1 recapitulates the T3 copper site, supporting different copper redox states, and being active in the O₂ -dependent oxidation of catechols to o-quinones. Careful design of the residues lining the substrate access site endows DR1 with substrate recognition, as revealed by Hammet analysis and computational studies on substituted catechols. This study represents a premier example in the construction of a functional T3 copper site into a designed four-helix bundle protein.

Protein binding sites for drug design

Drug development is a lengthy and challenging process that can be accelerated at early stages by new mathematical approaches and modern computers. To address this important issue, we are developing new mathematical solutions for the detection and characterization of protein binding sites that are important for new drug development. In this review, we present algorithms based on graph theory combined with molecular dynamics simulations that we have developed for studying biological target proteins to provide important data for optimizing the early stages of new drug development. A particular focus is the development of new protein binding site prediction algorithms (ProBiS) and new web tools for modeling pharmaceutically interesting molecules-ProBiS Tools (algorithm, database, web server), which have evolved into a full-fledged graphical tool for studying proteins in the proteome. ProBiS differs from other structural algorithms in that it can align proteins with different folds without prior knowledge of the binding sites. It allows detection of similar binding sites and can predict molecular ligands of various types of pharmaceutical interest that could be advanced to drugs to treat a disease, based on the entire Protein Data Bank (PDB) and AlphaFold database, including proteins not yet in the PDB. All ProBiS Tools are freely available to the academic community at http://insilab.org and https://probis.nih.gov.

Structure Prediction, Evaluation, and Validation of GPR18 Lipid Receptor Using Free Programs

The GPR18 receptor, often referred to as the N-arachidonylglycine receptor, although assigned (along with GPR55 and GPR119) to the new class A GPCR subfamily-lipid receptors, officially still has the status of a class A GPCR orphan. While its signaling pathways and biological significance have not yet been fully elucidated, increasing evidence points to the therapeutic potential of GPR18 in relation to immune, neurodegenerative, and cancer processes to name a few. Therefore, it is necessary to understand the interactions of potential ligands with the receptor and the influence of particular structural elements on their activity. Thus, given the lack of an experimentally solved structure, the goal of the present study was to obtain a homology model of the GPR18 receptor in the inactive state, meeting all requirements in terms of protein structure quality and recognition of active ligands. To increase the reliability and precision of the predictions, different contemporary protein structure prediction methods and software were used and compared herein. To test the usability of the resulting models, we optimized and compared the selected structures followed by the assessment of the ability to recognize known, active ligands. The stability of the predicted poses was then evaluated by means of molecular dynamics simulations. On the other hand, most of the best-ranking contemporary CADD software/platforms for its full usability require rather expensive licenses. To overcome this down-to-earth obstacle, the overarching goal of these studies was to test whether it is possible to perform the thorough CADD experiments with high scientific confidence while using only license-free/academic software and online platforms. The obtained results indicate that a wide range of freely available software and/or academic licenses allow us to carry out meaningful molecular modelling/docking studies.

Engineering and screening of novel β-1,3-xylanases with desired hydrolysate type by optimized ancestor sequence reconstruction and data mining

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A novel integrative strategy for engineering β-1,3-xylanases with desired products.

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AncXyl10 is the first successful example of ASR to shift the hydrolysate types.

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The hydrolysates of AncXyl10 was only β-1,3-xylobiose and β-1,3-xylotriose.

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The underlying mechanism laid a new groundwork towards hydrolase engineering.

Engineering of hydrolases to shift their hydrolysate types has not been attempted so far, though computer-assisted enzyme design has been successful. A novel integrative strategy for engineering and screening the β-1,3-xylanase with desired hydrolysate types was proposed, with the purpose to solve problems that the separation and preparation of β-1,3-xylo-oligosaccharides was in high cost yet in low yield as monosaccharides existed in the hydrolysates. By classifying the hydrolysate types and coding them into numerical values, two robust mathematical models with five selected attributes from molecular docking were established based on LogitBoost and partial least squares regression with overall accuracy of 83.3% and 100%, respectively. Then, they were adopted for efficient screening the potential mutagenesis library of β-1,3-xylanases that only product oligosaccharides. The virtually designed AncXyl10 was selected and experimentally verified to produce only β-1,3-xylobiose (60.38%) and β-1,3-xylotriose (39.62%), which facilitated the preparation of oligosaccharides with high purity. The underlying mechanism of AncXyl10 may associated with the gap processing and ancestral amino acid substitution in the process of ancestral sequence reconstruction. Since many carbohydrate-active enzymes have highly conserved active sites, the strategy and their biomolecular basis will shield a new light for engineering carbohydrates hydrolase to produce specific oligosaccharides.

Tuaimenal A, a Meroterpene from the Irish Deep-Sea Soft Coral Duva florida, Displays Inhibition of the SARS-CoV-2 3CLpro Enzyme

Cold water benthic environments are a prolific source of structurally diverse molecules with a range of bioactivities against human disease. Specimens of a previously chemically unexplored soft coral, Duva florida, were collected during a deep-sea cruise that sampled marine invertebrates along the Irish continental margin in 2018. Tuaimenal A (1), a cyclized merosesquiterpenoid representing a new carbon scaffold with a highly substituted chromene core, was discovered through exploration of the soft coral secondary metabolome via NMR-guided fractionation. The absolute configuration was determined through vibrational circular dichroism. Functional biochemical assays and in silico docking experiments found tuaimenal A selectively inhibits the viral main protease (3CLpro) of SARS-CoV-2.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

Effect of FKBP12-Derived Intracellular Peptides on Rapamycin-Induced FKBP-FRB Interaction and Autophagy

Intracellular peptides (InPeps) generated by proteasomes were previously suggested as putative natural regulators of protein-protein interactions (PPI). Here, the main aim was to investigate the intracellular effects of intracellular peptide VFDVELL (VFD7) and related peptides on PPI. The internalization of the peptides was achieved using a C-terminus covalently bound cell-penetrating peptide (cpp; YGRKKRRQRRR). The possible inhibition of PPI was investigated using a NanoBiT^® luciferase structural complementation reporter system, with a pair of plasmids vectors each encoding, simultaneously, either FK506-binding protein (FKBP) or FKBP-binding domain (FRB) of mechanistic target of rapamycin complex 1 (mTORC1). The interaction of FKBP-FRB within cells occurs under rapamycin induction. Results shown that rapamycin-induced interaction between FKBP-FRB within human embryonic kidney 293 (HEK293) cells was inhibited by VFD7-cpp (10-500 nM) and FDVELLYGRKKRRQRRR (VFD6-cpp; 1-500 nM); additional VFD7-cpp derivatives were either less or not effective in inhibiting FKBP-FRB interaction induced by rapamycin. Molecular dynamics simulations suggested that selected peptides, such as VFD7-cpp, VFD6-cpp, VFAVELLYGRKKKRRQRRR (VFA7-cpp), and VFEVELLYGRKKKRRQRRR (VFA7-cpp), bind to FKBP and to FRB protein surfaces. However, only VFD7-cpp and VFD6-cpp induced changes on FKBP structure, which could help with understanding their mechanism of PPI inhibition. InPeps extracted from HEK293 cells were found mainly associated with macromolecular components (i.e., proteins and/or nucleic acids), contributing to understanding InPeps' intracellular proteolytic stability and mechanism of action-inhibiting PPI within cells. In a model of cell death induced by hypoxia-reoxygenation, VFD6-cpp (1 µM) increased the viability of mouse embryonic fibroblasts cells (MEF) expressing mTORC1-regulated autophagy-related gene 5 (Atg5), but not in autophagy-deficient MEF cells lacking the expression of Atg5. These data suggest that VFD6-cpp could have therapeutic applications reducing undesired side effects of rapamycin long-term treatments. In summary, the present report provides further evidence that InPeps have biological significance and could be valuable tools for the rational design of therapeutic molecules targeting intracellular PPI.

CIFDock: A novel CHARMM-based flexible receptor-flexible ligand docking protocol

Docking studies play a critical role in the current workflow of drug discovery. However, limitations may often arise through factors including inadequate ligand sampling, a lack of protein flexibility, scoring function inadequacies (e.g., due to metals, co-factors, etc.), and difficulty in retaining explicit water molecules. Herein, we present a novel CHARMM-based induced fit docking (CIFDock) workflow that can circumvent these limitations by employing all-atom force fields coupled to enhanced sampling molecular dynamics procedures. Self-guided Langevin dynamics simulations are used to effectively sample relevant ligand conformations, side chain orientations, crystal water positions, and active site residue motion. Protein flexibility is further enhanced by dynamic sampling of side chain orientations using an expandable rotamer library. Steps in the procedure consisting of fixing individual components (e.g., the ligand) while sampling the other components (e.g., the residues in the active site of the protein) allow for the complex to adapt to conformational changes. Ultimately, all components of the complex-the protein, ligand, and waters-are sampled simultaneously and unrestrained with SGLD to capture any induced fit effects. This modular flexible docking procedure is automated using CHARMM scripting, interfaced with SLURM array processing, and parallelized to use the desired number of processors. We validated the CIFDock procedure by performing cross-docking studies using a data set comprised of 21 pharmaceutically relevant proteins. Five variants of the CHARMM-based SWISSDOCK scoring functions were created to quantify the results of the final generated poses. Results obtained were comparable to, or in some cases improved upon, commercial docking program data.

Highly thermostable and promiscuous β-1,3-xylanasen designed by optimized ancestral sequence reconstruction

The ancestor of β-1,3-xylanases (AncXyl09) were reconstructed by the optimized ancestral sequences reconstruction strategy to solve the poor catalytic performances of existing β-1,3-xylanases. The results showed that the half-life at 50 °C was 65.08 h, indicating good thermostability. The large number of hydrogen bonds and the disulfide bonds were the major attributes related with the thermal stability of Anxyl09. Interestingly, AncXyl09 could hydrolyze lichen besides the original substrate of β-1, 3-xylan, which is the first reported β-1,3-xylanase with substrate promiscuity. Moreover, the hydrolytic products are mainly disaccharides, the content of β-1,3-xylobiose and lichoridiose more than 70% as determined by high performance liquid chromatography (HPLC), which could significantly facilitate the separation and purification of oligosaccharides. The successful design of AncXyl09 was the representative of the semi-rationally engineered β-1, 3-xylanase, which will shield a new light on the β-1,3-xylanase engineering, active oligosaccharide preparation and marine algae resource utilization.

Structural basis for high selectivity of a rice silicon channel Lsi1

Silicon (Si), the most abundant mineral element in the earth’s crust, is taken up by plant roots in the form of silicic acid through Low silicon rice 1 (Lsi1). Lsi1 belongs to the Nodulin 26-like intrinsic protein subfamily in aquaporin and shows high selectivity for silicic acid. To uncover the structural basis for this high selectivity, here we show the crystal structure of the rice Lsi1 at a resolution of 1.8 Å. The structure reveals transmembrane helical orientations different from other aquaporins, characterized by a unique, widely opened, and hydrophilic selectivity filter (SF) composed of five residues. Our structural, functional, and theoretical investigations provide a solid structural basis for the Si uptake mechanism in plants, which will contribute to secure and sustainable rice production by manipulating Lsi1 selectivity for different metalloids.

The rice Lsi1 aquaporin mediates uptake of silicic acid via the roots. Here the authors show the crystal structure of rice Lsi1 and characterize a unique five residue hydrophilic selectivity filter providing a structural basis for the highly selective activity of Lsi1 in Si uptake.

A sublethal ATP11A mutation associated with neurological deterioration causes aberrant phosphatidylcholine flipping in plasma membranes

ATP11A translocates phosphatidylserine (PtdSer), but not phosphatidylcholine (PtdCho), from the outer to the inner leaflet of plasma membranes, thereby maintaining the asymmetric distribution of PtdSer. Here, we detected a de novo heterozygous point mutation of ATP11A in a patient with developmental delays and neurological deterioration. Mice carrying the corresponding mutation died perinatally of neurological disorders. This mutation caused an amino acid substitution (Q84E) in the first transmembrane segment of ATP11A, and mutant ATP11A flipped PtdCho. Molecular dynamics simulations revealed that the mutation allowed PtdCho binding at the substrate entry site. Aberrant PtdCho flipping markedly decreased the concentration of PtdCho in the outer leaflet of plasma membranes, whereas sphingomyelin (SM) concentrations in the outer leaflet increased. This change in the distribution of phospholipids altered cell characteristics, including cell growth, cholesterol homeostasis, and sensitivity to sphingomyelinase. Matrix-assisted laser desorption ionization-imaging mass spectrometry (MALDI-IMS) showed a marked increase of SM levels in the brains of Q84E-knockin mouse embryos. These results provide insights into the physiological importance of the substrate specificity of plasma membrane flippases for the proper distribution of PtdCho and SM.

Solution structures of human myeloma IgG3 antibody reveal extended Fab and Fc regions relative to the other IgG subclasses

Human immunoglobulin G subclass 3 (IgG3) possesses a uniquely long hinge region that separates its Fab antigen-binding and Fc receptor-binding regions. Owing to this hinge length, the molecular structure of full-length IgG3 remains elusive, and the role of the two conserved Fc glycosylation sites are unknown. To address these issues, we subjected glycosylated and deglycosylated human myeloma IgG3 to multidisciplinary solution structure studies. Using analytical ultracentrifugation, the elongated structure of IgG3 was determined from the reduced sedimentation coefficients s020,w of 5.82 to 6.29 S for both glycosylated and deglycosylated IgG3. X-ray and neutron scattering showed that the Guinier RG values were 6.95 nm for glycosylated IgG3 and were unchanged after deglycosylation, again indicating an elongated structure. The distance distribution function P(r) showed a maximum length of 25 to 28 nm and three distinct maxima. The molecular structure of IgG3 was determined using atomistic modeling based on molecular dynamics simulations of the IgG3 hinge and Monte Carlo simulations to identify physically realistic arrangements of the Fab and Fc regions. This resulted in libraries containing 135,135 and 73,905 glycosylated and deglycosylated IgG3 structures, respectively. Comparisons with the X-ray and neutron scattering curves gave 100 best-fit models for each form of IgG3 that accounted for the experimental scattering curves. These models revealed the first molecular structures for full-length IgG3. The structures exhibited relatively restricted Fab and Fc conformations joined by an extended semirigid hinge, which explains the potent effector functions of IgG3 relative to the other subclasses IgG1, IgG2, and IgG4.

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.

ProBiS-Dock Database: A Web Server and Interactive Web Repository of Small Ligand-Protein Binding Sites for Drug Design

We have developed a new system, ProBiS-Dock, which can be used to determine the different types of protein binding sites for small ligands. The binding sites identified this way are then used to construct a new binding site database, the ProBiS-Dock Database, that allows for the ranking of binding sites according to their utility for drug development. The newly constructed database currently has more than 1.4 million binding sites and offers the possibility to investigate potential drug targets originating from different biological species. The interactive ProBiS-Dock Database, a web server and repository that consists of all small-molecule ligand binding sites in all of the protein structures in the Protein Data Bank, is freely available at http://probis-dock-database.insilab.org. The ProBiS-Dock Database will be regularly updated to keep pace with the growth of the Protein Data Bank, and our anticipation is that it will be useful in drug discovery.

From genomes to molecular dynamics - A bottom up approach in extrication of SARS CoV-2 main protease inhibitors

The recent pandemic Coronavirus disease-19 outbreak had traumatized global countries since its origin in late December 2019. Though the virus originated in China, it has spread rapidly across the world due its firmly established community transmission. To successfully tackle the spread and further infection, there needs a clear multidimensional understanding of the molecular mechanisms. Henceforth, 942 viral genome sequences were analysed to predict the core genomes crucial in virus life cycle. Additionally, 35 small interfering RNA transcripts were predicted that can target specifically the viral core proteins and reduce pathogenesis. The crystal structure of Covid-19 main protease-6LU7 was chosen as an attractive target due to the factors that there were fewer mutations and whose structure had significant identity to the annotated protein sequence of the core genome. Drug repurposing of both recruiting and non recruiting drugs was carried out through molecular docking procedures to recognize bitolterol as a good inhibitor of Covid-19 protease. The study was extended further to screen antiviral phytocompounds through quantitative structure activity relationship and molecular docking to identify davidigenin, from licorice as the best novel lead with good interactions and binding energy. The docking of the best compounds in all three categories was validated with molecular dynamics simulations which implied stable binding of the drug and lead molecule. Though the studies need clinical evaluations, the results are suggestive of curbing the pandemic.

Solution structure of deglycosylated human IgG1 shows the role of CH2 glycans in its conformation

The human immunoglobulin G (IgG) class is the most prevalent antibody in serum, with the IgG1 subclass being the most abundant. IgG1 is composed of two Fab regions connected to a Fc region through a 15-residue hinge peptide. Two glycan chains are conserved in the Fc region in IgG; however, their importance for the structure of intact IgG1 has remained unclear. Here, we subjected glycosylated and deglycosylated monoclonal human IgG1 (designated as A33) to a comparative multidisciplinary structural study of both forms. After deglycosylation using peptide:N-glycosidase F, analytical ultracentrifugation showed that IgG1 remained monomeric and the sedimentation coefficients s⁰_20,w of IgG1 decreased from 6.45 S by 0.16-0.27 S. This change was attributed to the reduction in mass after glycan removal. X-ray and neutron scattering revealed changes in the Guinier structural parameters after deglycosylation. Although the radius of gyration (R_G) was unchanged, the cross-sectional radius of gyration (R_XS-1) increased by 0.1 nm, and the commonly occurring distance peak M2 of the distance distribution curve P(r) increased by 0.4 nm. These changes revealed that the Fab-Fc separation in IgG1 was perturbed after deglycosylation. To explain these changes, atomistic scattering modeling based on Monte Carlo simulations resulted in 123,284 and 119,191 trial structures for glycosylated and deglycosylated IgG1 respectively. From these, 100 x-ray and neutron best-fit models were determined. For these, principal component analyses identified five groups of structural conformations that were different for glycosylated and deglycosylated IgG1. The Fc region in glycosylated IgG1 showed a restricted range of conformations relative to the Fab regions, whereas the Fc region in deglycosylated IgG1 showed a broader conformational spectrum. These more variable Fc conformations account for the loss of binding to the Fcγ receptor in deglycosylated IgG1.

Elucidating the Interactions Between Heparin/Heparan Sulfate and SARS-CoV-2-Related Proteins-An Important Strategy for Developing Novel Therapeutics for the COVID-19 Pandemic

Owing to the high mortality and the spread rate, the infectious disease caused by SARS-CoV-2 has become a major threat to public health and social economy, leading to over 70 million infections and 1. 6 million deaths to date. Since there are currently no effective therapeutic or widely available vaccines, it is of urgent need to look for new strategies for the treatment of SARS-CoV-2 infection diseases. Binding of a viral protein onto cell surface heparan sulfate (HS) is generally the first step in a cascade of interaction that is required for viral entry and the initiation of infection. Meanwhile, interactions of selectins and cytokines (e.g., IL-6 and TNF-α) with HS expressed on endothelial cells are crucial in controlling the recruitment of immune cells during inflammation. Thus, structurally defined heparin/HS and their mimetics might serve as potential drugs by competing with cell surface HS for the prevention of viral adhesion and modulation of inflammatory reaction. In this review, we will elaborate coronavirus invasion mechanisms and summarize the latest advances in HS-protein interactions, especially proteins relevant to the process of coronavirus infection and subsequent inflammation. Experimental and computational techniques involved will be emphasized.

The fine art of preparing membrane transport proteins for biomolecular simulations: Concepts and practical considerations

Molecular dynamics (MD) simulations have developed into an invaluable tool in bimolecular research, due to the capability of the method in capturing molecular events and structural transitions that describe the function as well as the physiochemical properties of biomolecular systems. Due to the progressive development of more efficient algorithms, expansion of the available computational resources, as well as the emergence of more advanced methodologies, the scope of computational studies has increased vastly over time. We now have access to a multitude of online databases, software packages, larger molecular systems and novel ligands due to the phenomenon of emerging novel psychoactive substances (NPS). With so many advances in the field, it is understandable that novices will no doubt find it challenging setting up a protein-ligand system even before they run their first MD simulation. These initial steps, such as homology modelling, ligand docking, parameterization, protein preparation and membrane setup have become a fundamental part of the drug discovery pipeline, and many areas of biomolecular sciences benefit from the applications provided by these technologies. However, there still remains no standard on their usage. Therefore, our aim within this review is to provide a clear overview of a variety of concepts and methodologies to consider, providing a workflow for a case study of a membrane transport protein, the full-length human dopamine transporter (hDAT) in complex with different stimulants, where MD simulations have recently been applied successfully.

In Silico Strategies in Tuberculosis Drug Discovery

Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field.

In Silico Laboratory: Tools for Similarity-Based Drug Discovery

Computational methods that predict and evaluate binding of ligands to receptors implicated in different pathologies have become crucial in modern drug design and discovery. Here, we describe protocols for using the recently developed package of computational tools for similarity-based drug discovery. The ProBiS stand-alone program and web server allow superimposition of protein structures against large protein databases and predict ligands based on detected binding site similarities. GenProBiS allows mapping of human somatic missense mutations related to cancer and non-synonymous single nucleotide polymorphisms and subsequent visual exploration of specific interactions in connection to these mutations. We describe protocols for using LiSiCA, a fast ligand-based virtual screening software that enables easy screening of large databases containing billions of small molecules. Finally, we show the use of BoBER, a web interface that enables user-friendly access to a large database of bioisosteric and scaffold hopping replacements.

Molecular Modeling of an Orphan GPR18 Receptor

Background: :

One of the best known to date GPCR class A (Rhodopsin) includes more than 100 orphan receptors for which the endogenous ligand is not known or is unclear. One of them is N-arachidonyl glycine receptor, named GPR18, a receptor that has been reported to be activated by Δ9-THC, endogenous cannabinoid receptors agonist anandamide and other cannabinoid receptor ligands suggesting it could be considered as third cannabinoid receptor. GPR18 activity, as well as its distribution might suggest usage of GPR18 ligands in treatment of endometriosis, cancer, and neurodegenerative disorders. Yet, so far only few GPR18 antagonists have been described, thus only ligand-based design approaches appear to be most useful to identify new ligands for this orphan receptor.

Methods: :

Main goal of this study, GPR18 inactive form homology model was built on the basis of the evolutionary closest homologous template: Human P2Y1 Receptor crystal structure.

Results: :

Obtained model was further evaluated and showed active/nonactive ligands differentiating properties with acceptable confidence. Moreover, it allowed for preliminary assessment of proteinligand interactions for a set of previously described ligands.

Conclusion::

Thus collected data might serve as a starting point for a discovery of novel, active GPR18 blocking ligands.

BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows

In the recent years, the improvement of software and hardware performance has made biomolecular simulations a mature tool for the study of biological processes. Simulation length and the size and complexity of the analyzed systems make simulations both complementary and compatible with other bioinformatics disciplines. However, the characteristics of the software packages used for simulation have prevented the adoption of the technologies accepted in other bioinformatics fields like automated deployment systems, workflow orchestration, or the use of software containers. We present here a comprehensive exercise to bring biomolecular simulations to the “bioinformatics way of working”. The exercise has led to the development of the BioExcel Building Blocks (BioBB) library. BioBB’s are built as Python wrappers to provide an interoperable architecture. BioBB’s have been integrated in a chain of usual software management tools to generate data ontologies, documentation, installation packages, software containers and ways of integration with workflow managers, that make them usable in most computational environments.

An extracellular cation coordination site influences ion conduction of OsHKT2;2

BACKGROUND

HKT channels mediate sodium uniport or sodium and potassium symport in plants. Monocotyledons express a higher number of HKT proteins than dicotyledons, and it is only within this clade of HKT channels that cation symport mechanisms are found. The prevailing ion composition in the extracellular medium affects the transport abilities of various HKT channels by changing their selectivity or ion transport rates. How this mutual effect is achieved at the molecular level is still unknown. Here, we built a homology model of the monocotyledonous OsHKT2;2, which shows sodium and potassium symport activity. We performed molecular dynamics simulations in the presence of sodium and potassium ions to investigate the mutual effect of cation species.

RESULTS

By analyzing ion-protein interactions, we identified a cation coordination site on the extracellular protein surface, which is formed by residues P71, D75, D501 and K504. Proline and the two aspartate residues coordinate cations, while K504 forms salt bridges with D75 and D501 and may be involved in the forwarding of cations towards the pore entrance. Functional validation via electrophysiological experiments confirmed the biological relevance of the predicted ion coordination site and identified K504 as a central key residue. Mutation of the cation coordinating residues affected the functionality of HKT only slightly. Additional in silico mutants and simulations of K504 supported experimental results.

CONCLUSION

We identified an extracellular cation coordination site, which is involved in ion coordination and influences the conduction of OsHKT2;2. This finding proposes a new viewpoint in the discussion of how the mutual effect of variable ion species may be achieved in HKT channels.

LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands

The accurate calculation of protein/nucleic acid–ligand interactions or condensed phase properties by force field-based methods require a precise description of the energetics of intermolecular interactions. Despite the progress made in force fields, small molecule parameterization remains an open problem due to the magnitude of the chemical space; the most critical issue is the estimation of a balanced set of atomic charges with the ability to reproduce experimental properties. The LigParGen web server provides an intuitive interface for generating OPLS-AA/1.14*CM1A(-LBCC) force field parameters for organic ligands, in the formats of commonly used molecular dynamics and Monte Carlo simulation packages. This server has high value for researchers interested in studying any phenomena based on intermolecular interactions with ligands via molecular mechanics simulations. It is free and open to all at jorgensenresearch.com/ligpargen, and has no login requirements.

CherryPicker: An Algorithm for the Automated Parametrization of Large Biomolecules for Molecular Simulation

Molecular simulations allow investigation of the structure, dynamics and thermodynamics of molecules at an atomic level of detail, and as such, are becoming increasingly important across many areas of science. As the range of applications increases, so does the variety of molecules. Simulation of a new type of molecule requires generation of parameters that result in accurate representation of the behavior of that molecule, and, in most cases, are compatible with existing parameter sets. While many automated parametrization methods exist, they are in general not well suited to large and conformationally dynamic molecules. We present here a method for automated assignment of parameters for large, novel biomolecules, and demonstrate its usage for peptides of varying degrees of complexity. Our method uses a graph theoretic representation to facilitate matching of the target molecule to molecular fragments for which reliable parameters are available. It requires minimal user input and creates parameter files compatible with the widely-used GROMACS simulation software.

Leishmania donovani adenylate kinase 2a prevents ATP-mediated cell cytolysis in macrophages

In Leishmania spp. ATP utilizing enzymes serves as a key role in preserving integrity of host cells for survival of parasite. Earlier reports suggested that Adenylate kinase (AK) a phosphotransferase enzyme released by Leishmania donovani secretome, involved in modulating levels of NTPs. In the present study, we cloned, expressed and characterized recombinant putative AK. Based on a sequence and phylogeny analysis, we identified the prominent features of the seven AK isoforms of Leishmania donovani and assigned our putative AK as LdAK2a. The K_m value of LdAK2a for ATP and AMP substrate were 204 μM and 184 μM, respectively and V_max was calculated as 1.6 μmol min^-1 mg^-1 protein. Ap5A, a known inhibitor of AK inhibited LdAK2a with estimated K_i values of 280 nM and 230 nM for ATP and AMP respectively. CD spectral studies were carried out to estimate its structural stability. Recombinant LdAK2a was found to prevent ATP mediated cell cytolysis of Raw 264.7 macrophages in vitro, which was determined by LDH assay and MMP assay. This is the first report which validates that Leishmanial AK2a can prevent ATP mediated cytolysis of macrophage cells and thereby probably play a role in preserving integrity of host cells for survival of parasite.

Effects of Pressure and Temperature on the Atomic Fluctuations of Dihydrofolate Reductase from a Psychropiezophile and a Mesophile

Determining the effects of extreme conditions on proteins from "extremophilic" and mesophilic microbes is important for understanding how life adapts to living at extremes as well as how extreme conditions can be used for sterilization and food preservation. Previous molecular dynamics simulations of dihydrofolate reductase (DHFR) from a psychropiezophile (cold- and pressure-loving), Moritella profunda (Mp), and a mesophile, Escherichia coli (Ec), at various pressures and temperatures indicate that atomic fluctuations, which are important for enzyme function, increase with both temperature and pressure. Here, the factors that cause increases in atomic fluctuations in the simulations are examined. The fluctuations increase with temperature not only because of greater thermal energy and thermal expansion of the protein but also because hydrogen bonds between protein atoms are weakened. However, the increase in fluctuations with pressure cannot be due to thermal energy, which remains constant, nor the compressive effects of pressure, but instead, the hydrogen bonds are also weakened. In addition, increased temperature causes larger increases in fluctuations of the loop regions of MpDHFR than EcDHFR, and increased pressure causes both increases and decreases in fluctuations of the loops, which differ between the two.

Adaptations for Pressure and Temperature Effects on Loop Motion in Escherichia coli and Moritella profunda Dihydrofolate Reductase

Determining how enzymes in piezophilic microbes function at high pressure can give insights into how life adapts to living at high pressure. Here, the effects of pressure and temperature on loop motions are compared Escherichia coli (Ec) and Moritella profunda (Mp) dihydrofolate reductase (DHFR) via molecular dynamics simulations at combinations of the growth temperature and pressure of the two organisms. Analysis indicates that a flexible CD loop in MpDHFR is an adaptation for cold because it makes the adenosine binding subdomain more flexible. Also, analysis indicates that the Thr113-Glu27 hydrogen bond in MpDHFR is an adaptation for high pressure because it provides flexibility within the loop subdomain compared to the very strong Thr113-Asp27 hydrogen bond in EcDHFR, and affects the correlation of the Met20 and GH loops. In addition, the results suggest that temperature might affect external loops more strongly while pressure might affect motion between elements within the protein.

Reservoir pH replica exchange

We present the reservoir pH replica exchange (R-pH-REM) method for constant pH simulations. The R-pH-REM method consists of a two-step procedure; the first step involves generation of one or more reservoirs of conformations. Each reservoir is obtained from a standard or enhanced molecular dynamics simulation with a constrained (fixed) protonation state. In the second step, fixed charge constraints are relaxed, as the structures from one or more reservoirs are periodically injected into a constant pH or a pH-replica exchange (pH-REM) simulation. The benefit of this two-step process is that the computationally intensive part of conformational search can be decoupled from constant pH simulations, and various techniques for enhanced conformational sampling can be applied without the need to integrate such techniques into the pH-REM framework. Simulations on blocked Lys, KK, and KAAE peptides were used to demonstrate an agreement between pH-REM and R-pH-REM simulations. While the reservoir simulations are not needed for these small test systems, the real need arises in cases when ionizable molecules can sample two or more conformations separated by a large energy barrier, such that adequate sampling is not achieved on a time scale of standard constant pH simulations. Such problems might be encountered in protein systems that exploit conformational transitions for function. A hypothetical case is studied, a small molecule with a large torsional barrier; while results of pH-REM simulations depend on the starting structure, R-pH-REM calculations on this model system are in excellent agreement with a theoretical model.

Diffusion of aqueous solutions of ionic, zwitterionic, and polar solutes

The properties of aqueous solutions of ionic, zwitterionic, and polar solutes are of interest to many fields. For instance, one of the many anomalous properties of aqueous solutions is the behavior of water diffusion in different monovalent salt solutions. In addition, solutes can affect the stabilities of macromolecules such as proteins in aqueous solution. Here, the diffusivities of aqueous solutions of sodium chloride, potassium chloride, tri-methylamine oxide (TMAO), urea, and TMAO-urea are examined in molecular dynamics simulations. The decrease in the diffusivity of water with the concentration of simple ions and urea can be described by a simple model in which the water molecules hydrogen bonded to the solutes are considered to diffuse at the same rate as the solutes, while the remainder of the water molecules are considered to be bulk and diffuse at almost the same rate as pure water. On the other hand, the decrease in the diffusivity of water with the concentration of TMAO is apparently affected by a decrease in the diffusion rate of the bulk water molecules in addition to the decrease due to the water molecules hydrogen bonded to TMAO. In other words, TMAO enhances the viscosity of water, while urea barely affects it. Overall, this separation of water molecules into those that are hydrogen bonded to solute and those that are bulk can provide a useful means of understanding the short- and long-range effects of solutes on water.

Quasiharmonic Analysis of the Energy Landscapes of Dihydrofolate Reductase from Piezophiles and Mesophiles

A quasiharmonic analysis (QHA) method is used to compare the potential energy landscapes of dihydrofolate reductase (DHFR) from a piezophile (pressure-loving organism), Moritella profunda (Mp), and a mesophile, Escherichia coli (Ec). The QHA method considers atomic fluctuations of the protein as motions of an atom in a local effective potential created by neighboring atoms and quantitates it in terms of effective force constants, isothermal compressibilities, and thermal expansivities. The analysis indicates that the underlying potential energy surface of MpDHFR is inherently softer than that of EcDHFR. In addition, on picosecond time scales, the energy surfaces become more similar under the growth conditions of Mp and Ec. On these time scales, DHFR behaves as expected; namely, increasing temperature makes the effective energy minimum less steep because thermal fluctuations increase the available volume, whereas increasing pressure steepens it because compression reduces the available volume. Our longer simulations show that, on nanosecond time scales, increasing temperature has a similar effect as on picosecond time scales because thermal fluctuations increase the volume even more on a longer time scale. However, these simulations also indicate that, on nanosecond time scales, pressure makes the local potential less steep, contrary to picosecond time scales. Further examination of the QHA indicates the nanosecond pressure response may originate at picosecond time scales at the exterior of the protein, which suggests that protein-water interactions may be involved. The results may lead to understanding adaptations in enzymes made by piezophiles that enable them to function at higher pressures.

Oxidative stress-triggered interactions between the succinyl- and acetyl-proteomes of rice leaves

Protein lysine acylations, such as succinylation and acetylation, are important post-translational modification (PTM) mechanisms, with key roles in cellular regulation. Antibody-based affinity enrichment, high-resolution liquid chromatography mass spectrometry analysis, and integrated bioinformatics analysis were used to characterize the lysine succinylome (K_suc ) and acetylome (K_ace ) of rice leaves. In total, 2,593 succinylated and 1,024 acetylated proteins were identified, of which 723 were simultaneously acetylated and succinylated. Proteins involved in photosynthetic carbon metabolism such as the large and small subunits of RuBisCO, ribosomal functions, and other key processes were subject to both PTMs. Preliminary insights into oxidant-induced changes to the rice acetylome and succinylome were gained from treatments with hydrogen peroxide. Exposure to oxidative stress did not regulate global changes in the rice acetylome or succinylome but rather led to modifications on a specific subset of the identified sites. De-succinylation of recombinant catalase (CATA) and glutathione S-transferase (OsGSTU6) altered the activities of these enzymes showing that this PTM may have a regulatory function. These findings not only greatly extend the list of acetylated and/or succinylated proteins but they also demonstrate the close cooperation between these PTMs in leaf proteins with key metabolic functions.

Interaction of anthraquinones of Cassia occidentalis seeds with DNA and Glutathione

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Emodin has the maximum binding affinity to calf thymus DNA.

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Anthraquinones form GSH conjugates.

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Anthraquinones oxidizes GSH to GSSG.

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Cytotoxicity of anthraquinones are linked to their DNA binding affinity.

Consumption of Cassia occidentalis (CO) seeds has been associated with the hepatomyoencephalopathy (HME) in children. Recently, we have characterized the toxic anthraquinones (AQs) such as Emodin, Rhein, Aloe-emodin, Chrysophanol and Physcion in CO seeds and detected these moieties in the bio fluids of CO poisoning cases. As AQs were detected in the serum of HME patients, their interaction with key biomolecules including protein, DNA and glutathione (GSH) is imperative. In this regard, we have previously reported the interaction of these AQs with serum albumin protein and their subsequent biological effects. However, the interaction of these AQs with DNA and GSH remained unexplored. In the present work, we have studied the binding of these AQs of CO seeds with DNA and GSH by fluorescence spectroscopy, UV–vis spectral analysis, molecular docking, and biochemical studies. Results indicated a higher binding affinity for Emodin (K_a = 3.854 × 10⁴ L mol⁻¹ S⁻¹), Aloe-emodin (K_a = 0.961 × 10⁴ L mol⁻¹ S⁻¹) and Rhein (K_a = 0.034 × 10⁴ L mol⁻¹ S⁻¹) towards calf thymus DNA may be associated with their higher cytotoxicity. Alternatively, Physcion and Chrysophanol which showed less cytotoxicity in our earlier studies exhibited very low DNA binding. The binding pattern of all these AQs is consistent with the in-silico data. Absorption spectroscopy studies indicated the possible formation of GSH conjugate with Aloe-emodin and Physcion. Further biochemical measurement of GSH and GSSG (Glutathione disulfide) following incubation with AQs indicated that Aloe-emodin (28%) and Rhein (30%) oxidizes GSH to GSSG more as compared to other AQs. Taken together, these results suggest that the higher cytotoxicity of Rhein, Emodin and Aloe-emodin may be attributed to their potent DNA and GSH binding affinity.

PlayMolecule ProteinPrepare: A Web Application for Protein Preparation for Molecular Dynamics Simulations

Protein preparation is a critical step in molecular simulations that consists of refining a Protein Data Bank (PDB) structure by assigning titration states and optimizing the hydrogen-bonding network. In this application note, we describe ProteinPrepare, a web application designed to interactively support the preparation of protein structures. Users can upload a PDB file, choose the solvent pH value, and inspect the resulting protonated residues and hydrogen-bonding network within a 3D web interface. Protonation states are suggested automatically but can be manually changed using the visual aid of the hydrogen-bonding network. Tables and diagrams provide estimated pK_a values and charge states, with visual indication for cases where review is required. We expect the graphical interface to be a useful instrument to assess the validity of the preparation, but nevertheless, a script to execute the preparation offline with the High-Throughput Molecular Dynamics (HTMD) environment is also provided for noninteractive operations.

CHARMM-GUI 10 years for biomolecular modeling and simulation

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. © 2016 Wiley Periodicals, Inc.

ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins

ProBiS (Protein Binding Sites) Tools consist of algorithm, database, and web servers for prediction of binding sites and protein ligands based on the detection of structurally similar binding sites in the Protein Data Bank. In this article, we review the operations that ProBiS Tools perform, provide comments on the evolution of the tools, and give some implementation details. We review some of its applications to biologically interesting proteins. ProBiS Tools are freely available at http://probis.cmm.ki.si and http://probis.nih.gov.

Elucidating a chemical defense mechanism of Antarctic sponges: A computational study

In 2000, a novel secondary metabolite (erebusinone, Ereb) was isolated from the Antarctic sea sponge, Isodictya erinacea. The bioactivity of Ereb was investigated, and it was found to inhibit molting when fed to the arthropod species Orchomene plebs. Xanthurenic acid (XA) is a known endogenous molt regulator present in arthropods. Experimental studies have confirmed that XA inhibits molting by binding to either (or both) of two P450 enzymes (CYP315a1 or CYP314a1) that are responsible for the final two hydroxylations in the production of the molt-inducing hormone, 20-hydroxyecdysone (20E). The lack of crystal structures and biochemical assays for CYP315a1 or CYP314a1, has prevented further experimental exploration of XA and Ereb's molt inhibition mechanisms. Herein, a wide array of computational techniques - homology modeling, molecular dynamics simulations, binding site bioinformatics, flexible receptor-flexible ligand docking, and molecular mechanics-generalized Born surface area calculations - have been employed to elucidate the structure-function relationships between the aforementioned P450s and the two described small molecule inhibitors (Ereb and XA). Results indicate that Ereb likely targets CYP315a1 by interacting with a network of aromatic residues in the binding site, while XA may inhibit both CYP315a1 and CYP314a1 because of its aromatic, as well as charged nature.

Thiamin Diphosphate Activation in 1-Deoxy-d-xylulose 5-Phosphate Synthase: Insights into the Mechanism and Underlying Intermolecular Interactions

1-Deoxy-d-xylulose 5-phosphate synthase (DXS) is a thiamin diphosphate (TDP) dependent enzyme that marks the beginning of the methylerythritol 4-phosphate isoprenoid biosynthesis pathway. The mechanism of action for DXS is still poorly understood and begins with the formation of a thiazolium ylide. This TDP activation step is thought to proceed through an intramolecular deprotonation by the 4'-aminopyrimidine ring of TDP; however, this step would occur only after an initial deprotonation of its own 4'-amino group. The mechanism of the initial deprotonation has been hypothesized, by analogy to transketolases, to occur via a histidine or an active site water molecule. Results from hybrid quantum mechanical/molecular mechanical (QM/MM) reaction path calculations reveal an ∼10 kcal/mol difference in transition state energies, favoring a water mediated mechanism over direct deprotonation by histidine. This difference was determined to be largely governed by electrostatic changes induced by conformational variations in the active site. Additionally, mutagenesis studies reveal DXS to be an evolutionarily resilient enzyme. Particularly, we hypothesize that residues H82 and H304 may act in a compensatory fashion if the other is lost due to mutation. Further, nucleus-independent chemical shifts (NICSs) and aromatic stabilization energy (ASE) calculations suggest that reduction in TDP aromaticity also serves as a factor for regulating ylide formation and controlling reactivity.

A Simple and Resource-efficient Setup for the Computer-aided Drug Design Laboratory

Undertaking modelling investigations for Computer-Aided Drug Design (CADD) requires a proper environment. In principle, this could be done on a single computer, but the reality of a drug discovery program requires robustness and high-throughput computing (HTC) to efficiently support the research. Therefore, a more capable alternative is needed but its implementation has no widespread solution. Here, the realization of such a computing facility is discussed, from general layout to technical details all aspects are covered.

The conserved active site histidine-glutamate pair of ferrochelatase coordinately catalyzes porphyrin metalation

Ferrochelatase catalyzes the insertion of ferrous iron into protoporphyrin IX to generate heme. Despite recent research on the reaction mechanism of ferrochelatase, the precise roles and localization of individual active site residues in catalysis, particularly those involved in the insertion of the ferrous iron into the protoporphyrin IX substrate, remain controversial. One outstanding question is from which side of the macrocycle of the bound porphyin substrate is the ferrous iron substrate inserted. Pre-steady state kinetic experiments done under single-turnover conditions conclusively demonstrate that metal ion insertion is pH-dependent, and that the conserved active site His-Glu pair coordinately catalyzes the metal ion insertion reaction. Further, p[Formula: see text] calculations and molecular dynamic simulations indicate that the active site His is deprotonated and the protonation state of the Glu relates to the conformational state of ferrochelatase. Specifically, the conserved Glu in the open conformation of ferrochelatase is deprotonated, while it remains protonated in the closed conformation. These findings support not only the role of the His-Glu pair in catalyzing metal ion insertion, as these residues need to be deprotonated to bind the incoming metal ion, but also the importance of the relationship between the protonation state of the Glu residue and the conformation of ferrochelatase. Finally, the results of this study are consistent with our previous proposal that the unwinding of the [Formula: see text]-helix, the major structural determinant of the closed to open conformational transition in ferrochelatase, is associated with the Glu residue binding the Fe[Formula: see text] substrate from a mitochondrial Fe[Formula: see text] donor.

Why should biochemistry students be introduced to molecular dynamics simulations--and how can we introduce them?

Molecular dynamics (MD) simulations play an increasingly important role in many aspects of biochemical research but are often not part of the biochemistry curricula at the undergraduate level. This article discusses the pedagogical value of exposing students to MD simulations and provides information to help instructors consider what software and hardware resources are necessary to successfully introduce these simulations into their courses. In addition, a brief review of the MD-based activities in this issue and other sources are provided.