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Nuclear receptors (NRs) are transcription factors that play an important role in multiple diseases, such as cancer, inflammation, and metabolic disorders. They share a common structural organization composed of five domains, of which the ligand-binding domain (LBD) can adopt different conformations in response to substrate, agonist, and antagonist binding, leading to distinct transcription effects. A key feature of NRs is, indeed, their intrinsic dynamics that make them a challenging target in drug discovery. This work aims to provide a meaningful investigation of NR structural variability to outline a dynamic profile for each of them. To do that, we propose a methodology based on the computation and comparison of protein cavities among the crystallographic structures of NR LBDs. First, pockets were detected with the FLAPsite algorithm and then an "all against all" approach was applied by comparing each pair of pockets within the same sub-family on the basis of their similarity score. The analysis concerned all the detectable cavities in NRs, with particular attention paid to the active site pockets. This approach can guide the investigation of NR intrinsic dynamics, the selection of reference structures to be used in drug design and the easy identification of alternative binding sites. [ABSTRACT FROM AUTHOR]

Structure-based virtual screening is currently an established tool in drug lead discovery projects. Although in the last years the field saw an impressive progress in terms of algorithm development, computational performance, and retrospective and prospective applications in ligand identification, there are still long-standing challenges where further improvement is needed. In this review, we consider the conceptual frame, state-of-the-art and recent developments of three critical “structural” issues in structure-based drug lead discovery: the use of homology modeling to accurately model the binding site when no experimental structures are available, the necessity of accounting for the dynamics of intrinsically flexible systems as proteins, and the importance of considering active site water molecules in lead identification and optimization campaigns. [ABSTRACT FROM AUTHOR]

Identifying cross-relationships among protein binding sites is becoming increasingly important in the chemo- and bioinformatics field; indeed, protein structural similarity might provide the right answer to a number of questions including Is a drug repurposable for another target? W hat is the molecular mechanism of a drug side-effect? How can we improve the ligand selectivity? The comparison of protein binding sites in terms of their three-dimensional structure molecular interaction fields can be a useful technique to approach all of these problems. Here, we report a semi-automated method for comparing and clustering protein pockets, called BioGPS, that combines the GRID Molecular Interactions Fields (MIFs) with FLAP pharmacophoric fingerprints. BioGPS identifies and compares protein binding sites by aligning them each other and directly comparing their MIFs. The strengths of this approach are that it is MIF-based, and therefore describes molecular interactions from a ligand perspective, and it is independent of protein superposition or sequence alignment. This approach enables protein-protein virtual screening (drug repurposing, polypharmacology, off-target effects), and also clustering to relate sequence-based similarities to structure-based differences among protein binding sites. [ABSTRACT FROM AUTHOR]

Abstract: O-acetylserine sulfhydrylase (OASS) catalyzes the synthesis of l-cysteine in the last step of the reductive sulfate assimilation pathway in microorganisms. Its activity is inhibited by the interaction with serine acetyltransferase (SAT), the preceding enzyme in the metabolic pathway. Inhibition is exerted by the insertion of SAT C-terminal peptide into the OASS active site. This action is effective only on the A isozyme, the prevalent form in enteric bacteria under aerobic conditions, but not on the B-isozyme, the form expressed under anaerobic conditions. We have investigated the active site determinants that modulate the interaction specificity by comparing the binding affinity of thirteen pentapeptides, derived from the C-terminal sequences of SAT of the closely related species Haemophilus influenzae and Salmonella typhimurium, towards the corresponding OASS-A, and towards S. typhimurium OASS-B. We have found that subtle changes in protein active sites have profound effects on protein–peptide recognition. Furthermore, affinity is strongly dependent on the pentapeptide sequence, signaling the relevance of P3–P4–P5 for the strength of binding, and P1–P2 mainly for specificity. The presence of an aromatic residue at P3 results in high affinity peptides with Kdiss in the micromolar and submicromolar range, regardless of the species. An acidic residue, like aspartate at P4, further strengthens the interaction and results in the higher affinity ligand of S. typhimurium OASS-A described to date. Since OASS knocked-out bacteria exhibit a significantly decreased fitness, this investigation provides key information for the development of selective OASS inhibitors, potentially useful as novel antibiotic agents. [Copyright &y& Elsevier]

Abstract: Ligands from a set of 19 protein–ligand complexes were re-docked with AutoDock, GOLD and FlexX using the scoring algorithms native to these programs supplemented by analysis using the HINT free energy force field. A HINT scoring function was calibrated for this data set using a simple linear regression of total HINT score for crystal-structure complexes vs. measured free energy of binding. This function had an r 2 of 0.84 and a standard error of ±0.42kcalmol−1. The free energies of binding were calculated for the best poses using the AutoDock, GOLD and FlexX scoring functions. The AutoDock and GoldScore algorithms estimated more than half of the binding free energies within the reported calibration standard errors for these functions, while that of FlexX did not. In contrast, the calibrated HINT scoring function identified optimized poses with standard errors near ±0.5kcalmol−1. When the metric of success is minimum RMSD (vs. crystallographic coordinates) the three docking programs were more successful, with mean RMSDs for the top-ranking poses in the 19 complexes of 3.38, 2.52 and 2.62Å for AutoDock, GOLD and FlexX, respectively. Two key observations in this study have general relevance for computational medicinal chemistry: first, while optimizing RMSD with docking score functions is clearly of value, these functions may be less well optimized for free energy of binding, which has broader applicability in virtual screening and drug discovery than RMSD; second, scoring functions uniquely calibrated for the data set or sets under study should nearly always be preferable to universal scoring functions. Due to these advantages, the poses selected by the HINT score also required less post-docking structure optimization to produce usable molecular models. Most of these features may be achievable with other scoring functions. [Copyright &y& Elsevier]

In the search for new chemical scaffolds able to afford NLRP3 inflammasome inhibitors, we used a pharmacophore-hybridization strategy by combining the structure of the acrylic acid derivative INF39 with the 1-(piperidin-4-yl)1,3-dihydro-2H-benzo[d]imidazole-2-one substructure present in HS203873, a recently identified NLRP3 binder. A series of differently modulated benzo[d]imidazole-2-one derivatives were designed and synthesised. The obtained compounds were screened in vitro to test their ability to inhibit NLRP3-dependent pyroptosis and IL-1β release in PMA-differentiated THP-1 cells stimulated with LPS/ATP. The selected compounds were evaluated for their ability to reduce the ATPase activity of human recombinant NLRP3 using a newly developed assay. From this screening, compounds 9, 13 and 18, able to concentration-dependently inhibit IL-1β release in LPS/ATP-stimulated human macrophages, emerged as the most promising NLRP3 inhibitors of the series. Computational simulations were applied for building the first complete model of the NLRP3 inactive state and for identifying possible binding sites available to the tested compounds. The analyses led us to suggest a mechanism of protein–ligand binding that might explain the activity of the compounds. [ABSTRACT FROM AUTHOR]

Flavonoids are plant bioactives that are recognized as hormone-like polyphenols because of their similarity to the endogenous sex steroids 17β-estradiol and testosterone, and to their estrogen- and androgen-like activity. Most efforts to verify flavonoid binding to nuclear receptors (NRs) and explain their action have been focused on ERα, while less attention has been paid to other nuclear and non-nuclear membrane androgen and estrogen receptors. Here, we investigate six flavonoids (apigenin, genistein, luteolin, naringenin, quercetin, and resveratrol) that are widely present in fruits and vegetables, and often used as replacement therapy in menopause. We performed comparative computational docking simulations to predict their capability of binding nuclear receptors ERα, ERβ, ERRβ, ERRγ, androgen receptor (AR), and its variant ART877A and membrane receptors for androgens, i.e., ZIP9, GPRC6A, OXER1, TRPM8, and estrogens, i.e., G Protein-Coupled Estrogen Receptor (GPER). In agreement with data reported in literature, our results suggest that these flavonoids show a relevant degree of complementarity with both estrogen and androgen NR binding sites, likely triggering genomic-mediated effects. It is noteworthy that reliable protein–ligand complexes and estimated interaction energies were also obtained for some suggested estrogen and androgen membrane receptors, indicating that flavonoids could also exert non-genomic actions. Further investigations are needed to clarify flavonoid multiple genomic and non-genomic effects. Caution in their administration could be necessary, until the safe assumption of these natural molecules that are largely present in food is assured. [ABSTRACT FROM AUTHOR]

β-lactamases (BLs) represent the most frequent cause of antimicrobial resistance in Gram-negative bacteria. Despite the continuous efforts in the development of BL inhibitors (BLIs), new BLs able to hydrolyze the last developed antibiotics rapidly emerge. Moreover, the insurgence rate of effective mutations is far higher than the release of BLIs able to counteract them. This results in a shortage of antibiotics that is menacing the effective treating of infectious diseases. The situation is made even worse by the co-expression in bacteria of BLs with different mechanisms and hydrolysis spectra, and by the lack of inhibitors able to hit them all. Differently from other targets, BL flexibility has not been deeply exploited for drug design, possibly because of the small protein size, for their apparent rigidity and their high fold conservation. In this mini-review, we discuss the evidence for BL binding site dynamics being crucial for catalytic efficiency, mutation effect, and for the design of new inhibitors. Then, we report on identified allosteric sites in BLs and on possible allosteric inhibitors, as a strategy to overcome the frequent occurrence of mutations in BLs and the difficulty of competing efficaciously with substrates. Nevertheless, allosteric inhibitors could work synergistically with traditional inhibitors, increasing the chances of restoring bacterial susceptibility towards available antibiotics. [ABSTRACT FROM AUTHOR]

Cholesterol biosynthesis is a multistep process in mammals that includes the aerobic removal of three methyl groups from the intermediate lanosterol, one from position 14 and two from position 4. During the demethylations at position 4, a 3-ketosteroid reductase catalyses the conversion of both 4-methylzymosterone and zymosterone to 4-methylzymosterol and zymosterol, respectively, restoring the alcoholic function of lanosterol, which is also maintained in cholesterol. Unlike other eukaryotes, mammals also use the same enzyme as an estrone reductase that can transform estrone (E1) into estradiol (E2). This enzyme, named 17β-hydroxysteroid dehydrogenase type 7 (HSD17B7), is therefore a multifunctional protein in mammals, and one that belongs to both the HSD17B family, which is involved in steroid-hormone metabolism, and to the family of post-squalene cholesterol biosynthesis enzymes. In the present study, a series of known inhibitors of human HSD17B7's E1-reductase activity have been assayed for potential inhibition against 3-ketosteroid reductase activity. Surprisingly, the assayed compounds lost their inhibition activity when tested in HepG2 cells that were incubated with radiolabelled acetate and against the recombinant overexpressed human enzyme incubated with 4-methylzymosterone (both radiolabelled and not). Preliminary kinetic analyses suggest a mixed or non-competitive inhibition on the E1-reductase activity, which is in agreement with Molecular Dynamics simulations. These results raise questions about the mechanism(s) of action of these possible inhibitors, the enzyme dynamic regulation and the interplay between the two activities. Image 1 • Two functionally separate, enzymatic activities in human HSD17B7 are present. • Estrone-reductase inhibitors were assayed against zymosterone-reductase activity. • Different inhibitor effects were observed on both enzymatic activities. • The inhibitor binding could affect the intrinsic dynamics of the enzyme active site. [ABSTRACT FROM AUTHOR]