Protein Crystal Structures Research Articles

SYNTHESIS AND BIOLOGICAL EVALUATION OF 1H-(INDOLE-5-YL)-3-SUBSTITUTED-1,2,4-OXADIAZOLES AS NOVEL 5-LOX INHIBITORS

: A series of indolyloxadiazoles were synthesized from amidoxime and indole 3-carboxaldehyde using CAN as a catalyst and PEG as a solvent. In vitro, a 5-LOX inhibitory assay has been performed for all the synthesized compounds. Among the tested compounds, 4bf showed the highest potency (IC50 18.78 µg/ml). The synthesized compound carried out docking on the 5-LOX enzyme protein crystal structure. Compound (4bf) docked snugly into the receptor site with a score of -9.1 Kcal/mol, and it showed strong hydrogen bond interactions with two key amino acids, His368 and Asn555.

Bioactive compounds from Morchella esculenta as potential inhibitors of RNA-binding protein La in ovarian cancer: a molecular modeling and quantum mechanics approach.

La protein is significantly expressed in various malignant tumors, including ovarian cancer (OC), which is related to the poor response to platinum-based chemotherapy. Thus, inhibiting La protein could control the expression of the potential downstream genes involved in promoting proliferation and chemotherapy resistance to OC, which could serve as a therapeutic intervention. Through a molecular docking approach, 12 compounds from Morchella esculenta were screened against the crystal structure of La protein and four hit compounds were identified, including beta-carotene, p-hydroxybenzoic acid, gamma-tocopherol, and alpha-tocopherol, with a binding affinity of - 10.7, - 8.1, - 7.9, and - 7.6kcal/mol, respectively, higher than pyridine-2-carboxylate (control), with a binding affinity of - 5.2kcal/mol. To explore the interaction of the hit compounds with the target receptor, they were selected for a molecular dynamic simulation and post-simulation analysis for 100ns. The result showed promising reliability of the ligands due to a stable interaction with the La protein crystal structure. Furthermore, the drug-likeness and physicochemical chemical properties of the compounds were investigated using ADMET study and density functional theory analysis, respectively, and the result shows that the hit compounds could serve as a promising starting for the development of novel LA protein inhibitors for OC therapeutics. Finally, this study compared HOMO and LUMO values from global hybrids with long-range corrected DFAs, and the result from the two followed the same qualitative pattern while calculating HOMO values; however, MO62X/cc-pVTZ could better predict LUMO values when considering a global hybrid.

A Insilico Study on Structural aspects of Caffeine by ArgusLab 4 software

In this study, the quasi-experimental molecular computational studies of the caffeine compound found in many herbal and the binding properties of the 4QHO protein to the active site were investigated by molecular docking method. For molecular docking, first of all, caffeine molecule, geometry optimization was done in ArgusLab program with semi-experimental PM3 method. The HOMO, LUMO, HOMO-LUMO energy differences and potential energy surface of all optimized molecules were calculated. The selected 4QHO protein crystal structure was obtained from the protein database in *.pdb format and optimized ligand interaction with this crystal structure was studied using ArgusLab. As a result of molecular docking studies, ligand-protein binding energies, hydrogen bond sites and number that can occur between ligand-protein were determined and evaluated.

Sonochemical synthesis of New Thiazolidin-4-one derivatives as potent anticancer and antimicrobial agents with Docking design, and Energy gap estimation

Thiazolidin-4-ones have important biological features, which has led to the development of new derivatives employing an efficient ultrasonic method. Schiff base derivatives were synthesized by condensation of 4,4′-diaminophenylmethane with various substituted benzaldehyde. These derivatives are subsequently subjected to cyclization, leading to the formation of thiazolidine-4-ones with favorable yields. The synthesized compounds were characterized using various analytical techniques such as FT-IR, 1H and 13C NMR, HRMS spectroscopy, and CHNS analysis. Thiazolidin-4-ones demonstrated anticancer potential with percentage cell viability at different concentrations (1mM, 3mM, and 5mM) and cell toxicity (1mM, 3mM, and 5mM). The IC50 values of compound 4g were found to be (72.27±1.39, 67.28±1.63, and 63.22±1.82), (36.77±0.11, 32.71±0.31, and 32.71±0.31), and 10.77±0.95, respectively. It is a good result according to the standard. The tested compounds demonstrated remarkable antimicrobial efficacy against bacterial strains like Staphylococcus aureus, Escherichia coli, and the fungal strain Candida albicans. The Minimum Inhibitory Concentrations (MIC) of compound 4g against Staphylococcus aureus, Escherichia coli, and Candida albicans were found to be 0.50±0.027, 0.70±0.040, and 0.80±0.036, respectively, which are comparable to reference medications. Docking design was conducted with the Staphylococcus aureus MurB protein (ID Code: 1HSK) and Novel CDK-5 inhibitor EFP crystal structure with CDK-2 (ID Code: 3IG7) for colon carcinoma HT29. Finally, the energy gaps were estimated by calculating HUMO and LUMO energy levels using the DFT/B3LYP method with the 6-31 G (d, p) basis set.

Identification of anti-cancer organometallic compounds by inhibition of BCL-2/Bax interactions

Apoptosis is regulated by the BCL-2 family, which includes the anti-apoptotic and pro-apoptotic proteins (Bax, Bok, Bak, etc.). These proteins often interact in dimers and act as apoptotic switches. Anti-apoptotic proteins, such as BCL-2, block the functions of these pro-apoptotic proteins. The pro-apoptotic and anti-apoptotic protein-protein interactions must be inhibited to prevent tumor cells from escaping apoptosis. This method has been used to develop anticancer drugs by inhibiting BCL-2 with both natural and synthetic compounds. Metal-containing compounds were used as pharmaceuticals for human cancer patients for a long time, and cisplatin was the first candidate of this class. Drug design, however, needs to pay more attention to metal complexes. We have studied the X-ray crystal structure of the BCL-2 protein in detail and identified the hydrophobic nature of the site with two less solvent-accessible sites. Based on the hydrophobic nature of the compounds, 74 organometallic compounds with X-ray crystallographically characterized bioactivity (including anticancer activity) were selected from the Cambridge crystallographic database. For testing, molecular docking was used to determine which compound was most effective against the BCL-2 protein. Organometallic compounds (benzene)-chloro-(1-{[(9H-fluoren-2-yl)imino]methyl}naphthalen-2-olato)-ruthenium (2), (1-((1,1′-biphenyl)-4-yl)-2,3,4,5-tetramethylcyclopentadienyl)-chloro-(4,4′-dimethyl-2,2′-bipyridine)-rhodium hexafluorophosphate (37), (μ-1,1'-(butane-1,4-diyl)bis(3-oxy-2-methylpyridin-4(1H)-one))-dichloro-bis(pentamethyl-cyclopentadienyl)-di-rhodium tetrahydrate (46), (μ-1,1'-(butane-1,4-diyl)bis(3-oxy-2-methylpyridin-4(1H)-one))-dichloro-bis(pentamethyl-cyclopentadienyl)-di-iridium (47) etc are found to be important compounds in this study. The capability of different types of complex interactions was identified using Hirshfeld surface analysis of the complexes. A NCI plot was conducted to understand the nature of the interaction between complex amino acids and active-site amino acids. A DFT study was conducted to examine the stability and chemical reactivity of the selected complexes. Using this study, one suitable hydrophobic lead anti-cancer organometallic pharmaceutical was found that binds at the less solvent-accessible hydrophobic site of BCL-2.

Modulatory effects of extract of Heinsia crinita against fructose/streptozotocin-induced oxidative stress in diabetic rat models

Oxidative stress plays a crucial role in the development of type 2 diabetes and the associated microvascular and cardiovascular complications. In the study, we have investigated the effects of Heinsia crinita (H. crinita) extracts on lipid peroxidation and oxidative stress responses using diabetic rats. Type 2 diabetes was induced with 10 % fructose/40 mg/kg body weight streptozotocin (STZ). H. crinita extract was administered at 200 and 400 mg/kg body weight twice daily for 21 days, in addition to metformin (MET: 500 mg/kg body weight) control. Molecular docking analysis was performed to determine the binding affinity of H. crinita extracts to the DNA binding domains of peroxisome proliferator-activated receptor (Ppar) and retinoid x receptor (Rxr) protein crystal structures, showing different binding affinities for putative active compounds from the plant. Fasting blood glucose (FBG), body and organ weight changes were determined showing that H. crinita extract induced an anti-hyperglycemic effect in the treated animals, with changes (either decrease or increase) in liver and kidney weights. A decrease in mRNA expression of peroxisome proliferator-activated receptors (ppar), sterol regulatory element-binding protein 1 (srebp-1c), liver x-receptor (lxr), retinoid x receptors (rxr), cytochrome p45041 (cyp4a1) and acyl-CoA oxidase (acox1) in diabetic animals were observed, compared to the control. A dose-specific decrease or increase in antioxidant enzymes (superoxide dismutase: SOD, catalase: CAT, reduced glutathione: GSH, glutathione peroxidase: GPx) transcripts and activity levels were also observed. We also observed exposure-specific decrease or increase of malondialdehyde (MDA) levels. Our data suggested that H. crinita extract possesses protective effects against diabetes-induced oxidative stress. These effects might be attributed to their binding and activation of nuclear receptors, indicating their cellular mode of action that is comparable to MET.

Screening of Compounds in Temu Ireng (Curcuma aeruginosa Roxb.) as Tuberculosis drug using Bioinformatics Design

Temu ireng (C. aeruginosa Roxb.) is a rhizome plant that is well known among Indonesians as a type of herbal plant due to the presence of bioactive compounds with numerous benefits. One of them is to act as an anti-bacterial agent. Tuberculosis is a symptomatic chronic condition triggered by a bacterial infection of the lungs in humans. The goal of this study was to use a bioinformatic technique to identify probable substances from C. aeruginosa Roxb. as a TB drug. C. aeruginosa Roxb. compounds' pharmacokinetics and druglikeness function Antibacterial activity was calculated using SwissADME analysis, antibacterial activity using QSAR analysis, and interaction between compounds and the protein crystal structure of M. tuberculosis using molecular docking interpretation. The 1.8-cineole compound's analytical results reached Lipinski's rule of five and demonstrated great ADMET modeling as a future drug nominee. This is supported by QSAR analysis, which demonstrates that 1.8-cineole can act as an antituberculosic. Besides this, the docking binding energy of 1.8-cineole was -4.20 kcal/mol following the molecular identification, suggesting that the bonds formed were quite constant.

Determination of the Crystal Structure of the Cell Wall-Anchored Proteins and Pilins.

Surface proteins and pili (or pilus) anchored on the Gram-positive bacterial cell wall play a vital role in adhesion, colonization, biofilm formation, and immunomodulation. The pilus consists of building blocks called pilins or pilus subunits. The surface proteins and pilins share some common sequences and structural features. They contain an N-terminal signal sequence and the C-terminal cell wall sorting region, enabling their transportation across the membrane and covalent attachment to the bacterial cell wall, respectively. The transpeptidase enzymes called sortases facilitate the covalent links between the pilins during the pilus assembly and between surface proteins or basal subunits of pili and peptidoglycan-bridge during the cell wall anchoring. Thus, elucidating three-dimensional structures for the surface proteins and pilins at the atomic level is essential for understanding the mechanism of adhesion, pilus assembly, and host interaction. This chapter aims to provide a general protocol for crystal structure determination of surface proteins and pilins anchored on the Gram-positive bacterial cell wall and substrates for sortases. The protocol involves the production of recombinant protein, crystallization, and structure determination by X-ray crystallography technique.

Bio-activity prediction of drug candidate compounds targeting SARS-Cov-2 using machine learning approaches.

The SARS-CoV-2 3CLpro protein is one of the key therapeutic targets of interest for COVID-19 due to its critical role in viral replication, various high-quality protein crystal structures, and as a basis for computationally screening for compounds with improved inhibitory activity, bioavailability, and ADMETox properties. The ChEMBL and PubChem database contains experimental data from screening small molecules against SARS-CoV-2 3CLpro, which expands the opportunity to learn the pattern and design a computational model that can predict the potency of any drug compound against coronavirus before in-vitro and in-vivo testing. In this study, Utilizing several descriptors, we evaluated 27 machine learning classifiers. We also developed a neural network model that can correctly identify bioactive and inactive chemicals with 91% accuracy, on CheMBL data and 93% accuracy on combined data on both CheMBL and Pubchem. The F1-score for inactive and active compounds was 93% and 94%, respectively. SHAP (SHapley Additive exPlanations) on XGB classifier to find important fingerprints from the PaDEL descriptors for this task. The results indicated that the PaDEL descriptors were effective in predicting bioactivity, the proposed neural network design was efficient, and the Explanatory factor through SHAP correctly identified the important fingertips. In addition, we validated the effectiveness of our proposed model using a large dataset encompassing over 100,000 molecules. This research employed various molecular descriptors to discover the optimal one for this task. To evaluate the effectiveness of these possible medications against SARS-CoV-2, more in-vitro and in-vivo research is required.

A residue-focused protein crystal structure evaluation method based on electron density

A residue-focused protein crystal structure evaluation method based on electron density

Homomeric interactions of the MPZ Ig domain and their relation to Charcot-Marie-Tooth disease.

Mutations in MPZ (myelin protein zero) can cause demyelinating early-onset Charcot-Marie-Tooth type 1B disease or later onset type 2I/J disease characterized by axonal degeneration, reflecting the diverse roles of MPZ in Schwann cells. MPZ holds apposing membranes of the myelin sheath together, with the adhesion role fulfilled by its extracellular immunoglobulin-like domain (IgMPZ), which oligomerizes. Models for how the IgMPZ might form oligomeric assemblies has been extrapolated from a protein crystal structure in which individual rat IgMPZ subunits are packed together under artificial conditions, forming three weak interfaces. One interface organizes the IgMPZ into tetramers, a second 'dimer' interface links tetramers together across the intraperiod line, and a third hydrophobic interface that mediates binding to lipid bilayers or the same hydrophobic surface on another IgMPZ domain. Presently, there are no data confirming whether the proposed IgMPZ interfaces actually mediate oligomerization in solution, whether they are required for the adhesion activity of MPZ, whether they are important for myelination, or whether their loss results in disease. We performed nuclear magnetic resonance spectroscopy and small angle X-ray scattering analysis of wild-type IgMPZ as well as mutant forms with amino acid substitutions designed to interrupt its presumptive oligomerization interfaces. Here, we confirm the interface that mediates IgMPZ tetramerization, but find that dimerization is mediated by a distinct interface that has yet to be identified. We next correlated different types of Charcot-Marie-Tooth disease symptoms to subregions within IgMPZ tetramers. Variants causing axonal late-onset disease (CMT2I/J) map to surface residues of IgMPZ proximal to the transmembrane domain. Variants causing early-onset demyelinating disease (CMT1B) segregate into two groups: one is described by variants that disrupt the stability of the Ig-fold itself and are largely located within the core of the IgMPZ domain; whereas another describes a region on the surface of IgMPZ tetramers, accessible to protein interactions. Computational docking studies predict that this latter disease-relevant subregion may potentially mediate dimerization of IgMPZ tetramers.

More than just pattern recognition: Prediction of uncommon protein structure features by AI methods

The CASP14 experiment demonstrated the extraordinary structure modeling capabilities of artificial intelligence (AI) methods. That result has ignited a fierce debate about what these methods are actually doing. One of the criticisms has been that the AI does not have any sense of the underlying physics but is merely performing pattern recognition. Here, we address that issue by analyzing the extent to which the methods identify rare structural motifs. The rationale underlying the approach is that a pattern recognition machine tends to choose the more frequently occurring motifs, whereas some sense of subtle energetic factors is required to choose infrequently occurring ones. To reduce the possibility of bias from related experimental structures and to minimize the effect of experimental errors, we examined only CASP14 target protein crystal structures determined to a resolution limit better than 2 Å, which lacked significant amino acid sequence homology to proteins of known structure. In those experimental structures and in the corresponding models, we track cis peptides, π-helices, 310-helices, and other small 3D motifs that occur in the PDB database at a frequency of lower than 1% of total amino acid residues. The best-performing AI method, AlphaFold2, captured these uncommon structural elements exquisitely well. All discrepancies appeared to be a consequence of crystal environment effects. We propose that the neural network learned a protein structure potential of mean force, enabling it to correctly identify situations where unusual structural features represent the lowest local free energy because of subtle influences from the atomic environment.

Discriminating physiological from non-physiological interfaces in structures of protein complexes: A community-wide study.

Reliably scoring and ranking candidate models of protein complexes and assigning their oligomeric state from the structure of the crystal lattice represent outstanding challenges. A community-wide effort was launched to tackle these challenges. The latest resources on protein complexes and interfaces were exploited to derive a benchmark dataset consisting of 1677 homodimer protein crystal structures, including a balanced mix of physiological and non-physiological complexes. The non-physiological complexes in the benchmark were selected to bury a similar or larger interface area than their physiological counterparts, making it more difficult for scoring functions to differentiate between them. Next, 252 functions for scoring protein-protein interfaces previously developed by 13 groups were collected and evaluated for their ability to discriminate between physiological and non-physiological complexes. A simple consensus score generated using the best performing score of each of the 13 groups, and a cross-validated Random Forest (RF) classifier were created. Both approaches showed excellent performance, with an area under the Receiver Operating Characteristic (ROC) curve of 0.93 and 0.94, respectively, outperforming individual scores developed by different groups. Additionally, AlphaFold2 engines recalled the physiological dimers with significantly higher accuracy than the non-physiological set, lending support to the reliability of our benchmark dataset annotations. Optimizing the combined power of interface scoring functions and evaluating it on challenging benchmark datasets appears to be a promising strategy.

AI-based protein models enhance the accuracy of experimentally determined protein crystal structures.

AI-based protein models enhance the accuracy of experimentally determined protein crystal structures.

High-pressure single-crystal diffraction at the Australian Synchrotron.

A new high-pressure single-crystal diffraction setup has been designed and implemented at the Australian Synchrotron for collecting molecular and protein crystal structures. The setup incorporates a modified micro-Merrill-Bassett cell and holder designed specifically to fit onto the horizontal air-bearing goniometer, allowing high-pressure diffraction measurements to be collected with little to no modification of the beamline setup compared with ambient data collections. Compression data for the amino acid, L-threonine, and the protein, hen egg-white lysozyme, were collected, showcasing the capabilities of the setup.

Sequence-assignment validation in protein crystal structure models with checkMySequence.

Sequence-register shifts remain one of the most elusive errors in experimental macromolecular models. They may affect model interpretation and propagate to newly built models from older structures. In a recent publication, it was shown that register shifts in cryo-EM models of proteins can be detected using a systematic reassignment of short model fragments to the target sequence. Here, it is shown that the same approach can be used to detect register shifts in crystal structure models using standard, model-bias-corrected electron-density maps (2mFo - DFc). Five register-shift errors in models deposited in the PDB detected using this method are described in detail.

Tight basis cycle representatives for persistent homology of large biological data sets.

Persistent homology (PH) is a popular tool for topological data analysis that has found applications across diverse areas of research. It provides a rigorous method to compute robust topological features in discrete experimental observations that often contain various sources of uncertainties. Although powerful in theory, PH suffers from high computation cost that precludes its application to large data sets. Additionally, most analyses using PH are limited to computing the existence of nontrivial features. Precise localization of these features is not generally attempted because, by definition, localized representations are not unique and because of even higher computation cost. Such a precise location is a sine qua non for determining functional significance, especially in biological applications. Here, we provide a strategy and algorithms to compute tight representative boundaries around nontrivial robust features in large data sets. To showcase the efficiency of our algorithms and the precision of computed boundaries, we analyze the human genome and protein crystal structures. In the human genome, we found a surprising effect of the impairment of chromatin loop formation on loops through chromosome 13 and the sex chromosomes. We also found loops with long-range interactions between functionally related genes. In protein homologs with significantly different topology, we found voids attributable to ligand-interaction, mutation, and differences between species.

DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries.

DNA-encoded library (DEL) technology has enabled significant advances in hit identification by enabling efficient testing of combinatorially generated molecular libraries. DEL screens measure protein binding affinity though sequencing reads of molecules tagged with unique DNA barcodes that survive a series of selection experiments. Computational models have been deployed to learn the latent binding affinities that are correlated to the sequenced count data; however, this correlation is often obfuscated by various sources of noise introduced in its complicated data-generation process. In order to denoise DEL count data and screen for molecules with good binding affinity, computational models require the correct assumptions in their modeling structure to capture the correct signals underlying the data. Recent advances in DEL models have focused on probabilistic formulations of count data, but existing approaches have thus far been limited to only utilizing 2-D molecule-level representations. We introduce a new paradigm, DEL-Dock, that combines ligand-based descriptors with 3-D spatial information from docked protein-ligand complexes. 3-D spatial information allows our model to learn over the actual binding modality rather than using only structure-based information of the ligand. We show that our model is capable of effectively denoising DEL count data to predict molecule enrichment scores that are better correlated with experimental binding affinity measurements compared to prior works. Moreover, by learning over a collection of docked poses we demonstrate that our model, trained only on DEL data, implicitly learns to perform good docking pose selection without requiring external supervision from expensive-to-source protein crystal structures.

A Bis(imidazole)-based cysteine labeling tool for metalloprotein assembly

Precise metal-protein coordination by design remains a considerable challenge. Polydentate, high-metal-affinity protein modifications, both chemical and recombinant, can enable metal localization. However, these constructs are often bulky, conformationally and stereochemically ill-defined, or coordinately saturated. Here, we expand the biomolecular metal-coordination toolbox with the irreversible attachment to cysteine of bis(1-methylimidazol-2-yl)ethene (“BMIE”), which generates a compact imidazole-based metal-coordinating ligand. Conjugate additions of small-molecule thiols (thiocresol and N-Boc-Cys) with BMIE confirm general thiol reactivity. The BMIE adducts are shown to complex the divalent metal ions Cu++ and Zn++ in bidentate (N2) and tridentate (N2S*) coordination geometries. Cysteine-targeted BMIE modification (>90% yield at pH 8.0) of a model protein, the S203C variant of carboxypeptidase G2 (CPG2), measured with ESI-MS, confirms its utility as a site-selective bioconjugation method. ICP-MS analysis confirms mono-metallation of the BMIE-modified CPG2 protein with Zn++, Cu++, and Co++. EPR characterization of the BMIE-modified CPG2 protein reveals the structural details of the site selective 1:1 BMIE-Cu++ coordination and symmetric tetragonal geometry under physiological conditions and in the presence of various competing and exchangeable ligands (H2O/HO−, tris, and phenanthroline). An X-ray protein crystal structure of BMIE-modified CPG2-S203C demonstrates that the BMIE modification is minimally disruptive to the overall protein structure, including the carboxypeptidase active sites, although Zn++ metalation could not be conclusively discerned at the resolution obtained. The carboxypeptidase catalytic activity of BMIE-modified CPG2-S203C was also assayed and found to be minimally affected. These features, combined with ease of attachment, define the new BMIE-based ligation as a versatile metalloprotein design tool, and enable future catalytic and structural applications.

Determinants of subtype-selectivity of the anthelmintic paraherquamide A on Caenorhabditis elegans nicotinic acetylcholine receptors.

The anthelmintic paraherquamide A acts selectively on the nematode L-type nicotinic acetylcholine receptors (nAChRs) but the mechanism of its selectivity is unknown. This study targeted the basis of paraherquamide A selectivity by determining an X-ray crystal structure of the acetylcholine binding protein (AChBP), a surrogate nAChR ligand-binding domain, complexed with the compound and by measuring its actions on wild-type and mutant Caenorhabditis elegans nematodes and functionally expressed C. elegans nAChRs. Paraherquamide A showed a higher efficacy for the levamisole-sensitive (L-type (UNC-38/UNC-29/UNC-63/LEV8/LEV-1)) nAChR than the nicotine-sensitive (N-type (ACR-16)) nAChR, a result consistent with in vivo studies on wild type worms and worms with mutations in subunits of these two classes of receptors. The X-ray crystal structure of the Ls-AChBP-paraherquamide A complex and site-directed amino acid mutation studies showed for the first time that loop C, loop E and loop F of the orthosteric receptor binding site play critical roles in the observed L-type nAChR selective actions of paraherquamide A. Significance Statement Paraherquamide A, an oxindole alkaloid, has been shown to act selectively on the L-type over N-type nAChRs in nematodes, but the mechanism of selectivity is unknown. We have co-crystallized paraherquamide A with the acetylcholine binding protein, a surrogate of nAChRs, and found that structural features of loop C, loop E and loop F contribute to the L-type nAChR selectivity of the alkaloid. The results create a new platform for the design of anthelmintic drugs targeting cholinergic neurotransmission in parasitic nematodes.