Identification and evaluation of antiviral activity of novel compounds targeting SARS-CoV-2 virus by enzymatic and antiviral assays, and computational analysis.

The viral genome of the SARS-CoV-2 coronavirus, the aetiologic agent of COVID-19, encodes structural, non-structural, and accessory proteins. Most of these components undergo rapid genetic variations, though to a lesser extent the essential viral proteases. Consequently, the protease and/or deubiquitinase activities of the cysteine proteases Mpro and PLpro became attractive targets for the design of antiviral agents. Here, we develop and evaluate new bis(benzylidene)cyclohexanones (BBC) and identify potential antiviral compounds. Three compounds were found to be effective in reducing the SARS-CoV-2 load, with EC50 values in the low micromolar concentration range. However, these compounds also exhibited inhibitory activity IC50 against PLpro at approximately 10-fold higher micromolar concentrations. Although originally developed as PLpro inhibitors, the comparison between IC50 and EC50 of BBC indicates that the mechanism of their in vitro antiviral activity is probably not directly related to inhibition of viral cysteine proteases. In conclusion, our study has identified new potential noncytotoxic antiviral compounds suitable for in vivo testing and further improvement.

Structure-Based Design and Pharmacophore-Based Virtual Screening of Combinatorial Library of Triclosan Analogues Active against Enoyl-Acyl Carrier Protein Reductase of Plasmodium falciparum with Favourable ADME Profiles.

Cost-effective therapy of neglected and tropical diseases such as malaria requires everlasting drug discovery efforts due to the rapidly emerging drug resistance of the plasmodium parasite. We have carried out computational design of new inhibitors of the enoyl-acyl carrier protein reductase (ENR) of Plasmodium falciparum (PfENR) using computer-aided combinatorial and pharmacophore-based molecular design. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) complexation QSAR model was developed for triclosan-based inhibitors (TCL) and a significant correlation was established between the calculated relative Gibbs free energies of complex formation (∆∆Gcom) between PfENR and TCL and the observed inhibitory potencies of the enzyme (IC50exp) for a training set of 20 known TCL analogues. Validation of the predictive power of the MM-PBSA QSAR model was carried out with the generation of 3D QSAR pharmacophore (PH4). We obtained a reasonable correlation between the relative Gibbs free energy of complex formation ∆∆Gcom and IC50exp values, which explained approximately 95% of the PfENR inhibition data: pIC50exp=-0.0544×∆∆Gcom+6.9336,R2=0.95. A similar agreement was established for the PH4 pharmacophore model of the PfENR inhibition (pIC50exp=0.9754×pIC50pre+0.1596, R2=0.98). Analysis of enzyme-inhibitor binding site interactions suggested suitable building blocks to be used in a virtual combinatorial library of 33,480 TCL analogues. Structural information derived from the complexation model and the PH4 pharmacophore guided us through in silico screening of the virtual combinatorial library of TCL analogues to finally identify potential new TCL inhibitors effective at low nanomolar concentrations. Virtual screening of the library by PfENR-PH4 led to a predicted IC50pre value for the best inhibitor candidate as low as 1.9 nM. Finally, the stability of PfENR-TCLx complexes and the flexibility of the active conformation of the inhibitor for selected top-ranking TCL analogues were checked with the help of molecular dynamics. This computational study resulted in a set of proposed new potent inhibitors with predicted antimalarial effects and favourable pharmacokinetic profiles that act on a novel pharmacological target, PfENR.

Adhesion of fibroblast cells on thin films representing surfaces of polymeric scaffolds of human urethra rationalized by molecular models of integrin binding: cell adhesion on polymeric scaffolds for regenerative medicine.

This work combines experimental and computational study of Balb/3T3 clone A31 mouse embryo fibroblasts cell line adhesion and proliferation on fourteen different polymeric surfaces prepared from poly(dioxanone) (PDO), poly(glycolic acid) (PGA), poly(hydroxybutyrate) (PHB), and poly(L-lactic acid) (PLA), and their 1:1 mixtures. The study was done with the aim to explore the attractive interactions between various synthetic biomaterials and simple model of the cell attachment mechanism involving the trans-membrane protein integrin. The considered polymeric biodegradable biomaterials can be used as scaffolds for tissue engineering and regenerative urology. During the growth of new tissue, the polymer scaffold is replaced by the extracellular matrix (ECM) synthetized by the proliferating cells. The adhesion and proliferation experiments were done on thin polymer films produced by solvent casting. The computational approach used 3D molecular models of two layers of ordered parallel polymeric fibres, which formed quasi-planar nanosized models of the scaffold surface. Experimental data showed that PGA based polymer films promote the cell adhesion. Cell proliferation testing, performed by incubating the fibroblast cells with the studied polymer films, disclosed that PLA, PHB/PLA and PHB/PGA systems are able to support proliferation of Balb/3T3 clone A31 cells equal to the plain glass. Relative interaction energies between 3D models of polymeric films and the α2 I domain of the cell adhesion receptor integrin α2ß1 computed by molecular mechanics suggest that plain polymers PGA, PDO and mixtures PDO/PGA, PHB/PGA, and especially PGA/PLA display elevated affinity to the cell-attachment protein, which confirms the experimental observations. The combination of experimental and modelling approach can assist rational design of synthetic polymeric biomaterial for scaffolds of artificial human urethra that can be efficiently colonized by cells.

Diversity of sialidases found in the human body - A review.

Sialidases are enzymes essential for numerous organisms including humans. Hydrolytic sialidases (EC 3.2.1.18), trans-sialidases and anhydrosialidases (intramolecular trans-sialidases, EC 4.2.2.15) are glycoside hydrolase enzymes that cleave the glycosidic linkage and release sialic acid residues from sialyl substrates. The paper summarizes diverse sialidases present in the human body and their potential impact on development of antiviral compounds - inhibitors of viral neuraminidases. It includes a brief overview of catalytic mechanisms of action of sialidases and describes the origin of sialidases in the human body. This is followed by description of the structure and function of sialidase families with a special focus on the GH33 and GH34 families. Various effects of sialidases on human body are also briefly described. Modulation of sialidase activity may be considered a useful tool for effective treatment of various diseases. In some cases, it is desired to completely suppress the activity of sialidases by suitable inhibitors. Specific sialidase inhibitors are useful for the treatment of influenza, epilepsy, Alzheimer's disease, diabetes, different types of cancer, or heart defects. Challenges and future directions are shortly depicted in the final part of the paper.

Antiviral agents against COVID-19: structure-based design of specific peptidomimetic inhibitors of SARS-CoV-2 main protease.

Despite the intense development of vaccines and antiviral therapeutics, no specific treatment of coronavirus disease 2019 (COVID-19), caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently available. Recently, X-ray crystallographic structures of a validated pharmacological target of SARS-CoV-2, the main protease (Mpro also called 3CLpro) in complex with peptide-like irreversible inhibitors have been published. We have carried out computer-aided structure-based design and optimization of peptidomimetic irreversible α-ketoamide Mpro inhibitors and their analogues using MM, MD and QM/MM methodology, with the goal to propose lead compounds with improved binding affinity to SARS-CoV-2 Mpro, enhanced specificity for pathogenic coronaviruses, decreased peptidic character, and favourable drug-like properties. The best inhibitor candidates designed in this work show largely improved interaction energies towards the Mpro and enhanced specificity due to 6 additional hydrogen bonds to the active site residues. The presented results on new SARS-CoV-2 Mpro inhibitors are expected to stimulate further research towards the development of specific anti-COVID-19 drugs.

Pathogenicity of new BEST1 variants identified in Italian patients with best vitelliform macular dystrophy assessed by computational structural biology.

BACKGROUND: Best vitelliform macular dystrophy (BVMD) is an autosomal dominant macular degeneration. The typical central yellowish yolk-like lesion usually appears in childhood and gradually worsens. Most cases are caused by variants in the BEST1 gene which encodes bestrophin-1, an integral membrane protein found primarily in the retinal pigment epithelium. METHODS: Here we describe the spectrum of BEST1 variants identified in a cohort of 57 Italian patients analyzed by Sanger sequencing. In 13 cases, the study also included segregation analysis in affected and unaffected relatives. We used molecular mechanics to calculate two quantitative parameters related to calcium-activated chloride channel (CaCC composed of 5 BEST1 subunits) stability and calcium-dependent activation and related them to the potential pathogenicity of individual missense variants detected in the probands. RESULTS: Thirty-six out of 57 probands (63% positivity) and 16 out of 18 relatives proved positive to genetic testing. Family study confirmed the variable penetrance and expressivity of the disease. Six of the 27 genetic variants discovered were novel: p.(Val9Gly), p.(Ser108Arg), p.(Asn179Asp), p.(Trp182Arg), p.(Glu292Gln) and p.(Asn296Lys). All BEST1 variants were assessed in silico for potential pathogenicity. Our computational structural biology approach based on 3D model structure of the CaCC showed that individual amino acid replacements may affect channel shape, stability, activation, gating, selectivity and throughput, and possibly also other features, depending on where the individual mutated amino acid residues are located in the tertiary structure of BEST1. Statistically significant correlations between mean logMAR best-corrected visual acuity (BCVA), age and modulus of computed BEST1 dimerization energies, which reflect variations in the in CaCC stability due to amino acid changes, permitted us to assess the pathogenicity of individual BEST1 variants. CONCLUSIONS: Using this computational approach, we designed a method for estimating BCVA progression in patients with BEST1 variants.

Structure-Based Design and in Silico Screening of Virtual Combinatorial Library of Benzamides Inhibiting 2-trans Enoyl-Acyl Carrier Protein Reductase of Mycobacterium tuberculosis with Favorable Predicted Pharmacokinetic Profiles.

BACKGROUND: During the previous decade a new class of benzamide-based inhibitors of 2-trans enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (Mt) with unusual binding mode have emerged. Here we report in silico design and evaluation of novel benzamide InhA-Mt inhibitors with favorable predicted pharmacokinetic profiles. METHODS: By using in situ modifications of the crystal structure of N-benzyl-4-((heteroaryl)methyl) benzamide (BHMB)-InhA complex (PDB entry 4QXM), 3D models of InhA-BHMBx complexes were prepared for a training set of 19 BHMBs with experimentally determined inhibitory potencies (half-maximal inhibitory concentrations IC50exp). In the search for active conformation of the BHMB1-19, linear QSAR model was prepared, which correlated computed gas phase enthalpies of formation (∆∆HMM) of InhA-BHMBx complexes with the IC50exp. Further, taking into account the solvent effect and entropy changes upon ligand, binding resulted in a superior QSAR model correlating computed complexation Gibbs free energies (∆∆Gcom). The successive pharmacophore model (PH4) generated from the active conformations of BHMBs served as a virtual screening tool of novel analogs included in a virtual combinatorial library (VCL) of compounds containing benzamide scaffolds. The VCL filtered by Lipinski's rule-of-five was screened by the PH4 model to identify new BHMB analogs. RESULTS: Gas phase QSAR model: -log10(IC50exp) = pIC50exp = -0.2465 × ∆∆HMM + 7.95503, R2 = 0.94; superior aqueous phase QSAR model: pIC50exp = -0.2370 × ∆∆Gcom + 7.8783, R2 = 0.97 and PH4 pharmacophore model: p IC 50 exp = 1.0013 × p IC 50 exp - 0.0085, R2 = 0.95. The VCL of more than 114 thousand BHMBs was filtered down to 73,565 analogs Lipinski's rule. The five-point PH4 screening retained 90 new and potent BHMBs with predicted inhibitory potencies IC50pre up to 65 times lower than that of BHMB1 (IC50exp = 20 nM). Predicted pharmacokinetic profile of the new analogs showed enhanced cell membrane permeability and high human oral absorption compared to current anti-tuberculotics. CONCLUSIONS: Combined use of QSAR models that considered binding of the BHMBs to InhA, pharmacophore model, and ADME properties helped to recognize bound active conformation of the benzamide inhibitors, permitted in silico screening of VCL of compounds sharing benzamide scaffold and identification of new analogs with predicted high inhibitory potencies and favorable pharmacokinetic profiles.

Virtual design of novel Plasmodium falciparum cysteine protease falcipain-2 hybrid lactone-chalcone and isatin-chalcone inhibitors probing the S2 active site pocket.

We report computer-aided design of new lactone-chalcone and isatin-chalcone (HLCIC) inhibitors of the falcipain-2 (PfFP-2). 3D models of 15 FP-2:HLCIC1-15 complexes with known observed activity (IC50exp) were prepared to establish a quantitative structure-activity (QSAR) model and linear correlation between relative Gibbs free energy of enzyme:inhibitor complex formation (ΔΔGcom) and IC50exp: pIC50exp = -0.0236 × ΔΔGcom+5.082(#); R2 = 0.93. A 3D pharmacophore model (PH4) derived from the QSAR directed our effort to design novel HLCIC analogues. During the design, an initial virtual library of 2621440 HLCIC was focused down to 18288 drug-like compounds and finally, PH4 screened to identify 81 promising compounds. Thirty-three others were added from an intuitive substitution approach intended to fill better the enzyme S2 pocket. One hundred and fourteen theoretical IC50 (IC50pre) values were predicted by means of (#) and their pharmacokinetics (ADME) profiles. More than 30 putative HLCICs display IC50pre 100 times superior to that of the published most active training set inhibitor HLCIC1.

Oguchi type I caused by a homozygous missense variation in the SAG gene.

Oguchi disease, is a very rare form of night blindness caused by biallelic variations in the SAG or GRK1 genes, both involved in rod restoration after light stimuli. Here we report the clinical and genetic findings of an 8-year old boy with a history of reduced visual acuity, nyctalpia and hemeralopia. Clinical findings, in particular the Mizuo-Nakamura phenomenon, were compatible with a diagnosis of Oguchi disease. Genetic testing revealed a novel missense homozygous variation in the SAG gene. This is the first evidence that the disease can be caused by missense variations in this gene.

Diarylcyclopropane hydroxamic acid inhibitors of histone deacetylase 4 designed by combinatorial approach and QM/MM calculations.

Inhibitors of histone deacetylase superfamily (HDAC), which induce cell cycle arrest, trigger cell death and reduce angiogenesis appear as promising anti-cancer drugs targeting the epigenetic regulation of gene expression. Approved HDAC inhibitors were found effective against haematological and solid malignancies, other HDACIs are currently in clinical trials for the treatment of neurological diseases or immune disorders. Among those, diarylcyclopropane hydroxamic acids (DCHA) were found to be potent and selective inhibitors of the class IIa HDACs, specifically HDAC4, a pharmacological target for the treatment of Huntington's disease and muscular atrophy. Crystallographic analysis revealed that one of the aryl groups of the DCHA fills the lower specificity pocket of the HDAC4 catalytic site that is specific for the class IIa HDACs. We have used computer-assisted combinatorial chemistry, hybrid quantum mechanics/molecular mechanics (QM/MM) with implicit solvation and QSAR models to optimize DCHA inhibitors and propose more potent DCHA analogues. The QM/MM approach has been selected since the process of inhibitor binding to the catalytic zinc and polar amino acid residues of the deacetylase active site induces considerable rearrangement of electron density of the inhibitor. Virtual combinatorial library consisting of 12180 DCHA analogues was focused by means of structure-based evaluation to form a small combinatorial subset enriched in potentially interesting inhibitor candidates. Two validated QSAR models making use of computed relative binding affinities of the DCHA inhibitors to the HDAC4 (ΔΔGcomQM/MM) were utilized to estimate the inhibitory potencies of the new analogues. The predicted half-maximal inhibitory concentrations (IC50pre) of the designed analogues fall into the low nanomolar concentration range and their predicted ADME properties are also favourable. The best designed DCHA analogues contain indazole, phenylpiperidine, phenyloxazole or hydroxypyridine moieties and stabilize bound inhibitors by hydrogen bonds to the catalytic water molecule and backbone carbonyl groups of the deacetylase active site residues. This makes them more potent and more specific inhibitors towards the HDAC4 isoform than the known diarylcyclopropane hydroxamic acids. The analogues are recommended for synthesis and experimental verification of inhibitory potencies in medicinal chemistry laboratories.

Development of a novel diagnostic algorithm to predict NASH in HCV-positive patients.

Non-alcoholic steato-hepatitis (NASH) is a severe disease characterised by liver inflammation and progressive hepatic fibrosis, which may progress to cirrhosis and hepatocellular carcinoma. Clinical evidence suggests that in hepatitis C virus patients steatosis and NASH are associated with faster fibrosis progression and hepatocellular carcinoma. A safe and reliable non-invasive diagnostic method to detect NASH at its early stages is still needed to prevent progression of the disease. We prospectively enrolled 91 hepatitis C virus-positive patients with histologically proven chronic liver disease: 77 patients were included in our study; of these, 10 had NASH. For each patient, various clinical and serological variables were collected. Different algorithms combining squamous cell carcinoma antigen-immunoglobulin-M (SCCA-IgM) levels with other common clinical data were created to provide the probability of having NASH. Our analysis revealed a statistically significant correlation between the histological presence of NASH and SCCA-IgM, insulin, homeostasis model assessment, haemoglobin, high-density lipoprotein and ferritin levels, and smoke. Compared to the use of a single marker, algorithms that combined four, six or seven variables identified NASH with higher accuracy. The best diagnostic performance was obtained with the logistic regression combination, which included all seven variables correlated with NASH. The combination of SCCA-IgM with common clinical data shows promising diagnostic performance for the detection of NASH in hepatitis C virus patients.

How accurate is the description of ligand-protein interactions by a hybrid QM/MM approach?

During the last decades, the application of hybrid quantum mechanical/molecular mechanical (QM/MM) methods has been extended to the field of drug design. In principle, the approximate QM/MM approach offers a more complete description of drug-receptor non-covalent interactions. This is especially true when charge or proton transfer, chelation of metal ions or strong polarization of ligand and protein or surface chemical groups are involved. The aim of this work was to assess the accuracy of calculated non-covalent ligand-protein interaction energies ([Formula: see text]) obtained by the hybrid QM/MM approach employed in QSite/Jaguar of Schrödinger's Small-Molecule Drug Discovery Suite on a set of small-molecule model systems when compared to rigorous QM calculations. The QM/MM approach was used at the density functional theory (DFT) level of theory with 6-31G* basis set, hybrid B3LYP functional and OPLS-2005 force field (DFT-B3LYP/6-31G*//OPLS-2005), a popular combination frequently used in studies on larger and complex biological systems such as drug-receptor complexes. In this work, we did not attempt to compute the most precise interaction energies of the model systems. We rather tried to assess the performance of the approximate QM/MM vs. full QM approach at the same computationally accessible level. For effective use of the QM/MM approach it is essential to select an appropriate QM region of the studied systems. To aid the selection of specific protein residues or functional groups to be included in the QM region, we evaluated the effect of its size, composition and symmetry on the accuracy of the QM/MM calculated [Formula: see text]. This was performed by means of a set of model clusters with well-defined configurations, which mimic the basic types of non-covalent interactions in proteins. Based on these systematic quantitative comparisons, recommendations for the addition of chemical groups or protein residues into the QM region are proposed for the popular DFT-B3LYP/6-31G*//OPLS-2005 QM/MM approach, leading to a more realistic description of ligand-protein interactions. These guidelines can have a significant bearing on computational drug or material research employing hybrid QM/MM methods by providing an estimate of the accuracy that can be expected from QM/MM studies. Graphical abstract An approximate hybrid QM/MM approach at the DFT-B3LYP/6-31G*//OPLS-2005 level was systematically assessed for the accuracy of description of non-covalent interactions on a series of six small-molecule model systems using the QSite and Jaguar modules of Schrödinger. Guidelines for rational selection of receptor residues or function groups to be included in the QM region around the ligand were proposed based on the achieved accuracy of computed ligand-protein interaction energies obtained by QM/MM vs. the full QM approach.

Stereoisomers of oseltamivir - synthesis, in silico prediction and biological evaluation.

Oseltamivir is an important antiviral drug, which possess three chirality centers in its structure. From eight possible stereoisomers, only two have been synthesized and evaluated so far. We describe herein the stereoselective synthesis, computational activity prediction and biological testing of another three diastereoisomers of oseltamivir. These isomers have been synthesized using stereoselective organocatalytic Michael addition, cyclization and reduction. Their binding to viral neuraminidase N1 of influenza A virus was evaluated by quantum-chemical calculations and their anti-influenza activities were tested by an in vitro virus-inhibition assay. All three isomers displayed antiviral activity lower than that of oseltamivir, however, one of the stereoisomers, (3S,4R,5S)-isomer, of oseltamivir showed in vitro potency towards the Tamiflu-sensitive influenza viral strain A/Perth/265/2009(H5N1) comparable to Tamiflu.

Computer-Aided Design of Orally Bioavailable Pyrrolidine Carboxamide Inhibitors of Enoyl-Acyl Carrier Protein Reductase of Mycobacterium tuberculosis with Favorable Pharmacokinetic Profiles.

We have carried out a computational structure-based design of new potent pyrrolidine carboxamide (PCAMs) inhibitors of enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (MTb). Three-dimensional (3D) models of InhA-PCAMx complexes were prepared by in situ modification of the crystal structure of InhA-PCAM1 (Protein Data Bank (PDB) entry code: 4U0J), the reference compound of a training set of 20 PCAMs with known experimental inhibitory potencies (IC50(exp)). First, we built a gas phase quantitative structure-activity relationships (QSAR) model, linearly correlating the computed enthalpy of the InhA-PCAM complex formation and the IC50(exp). Further, taking into account the solvent effect and loss of inhibitor entropy upon enzyme binding led to a QSAR model with a superior linear correlation between computed Gibbs free energies (ΔΔGcom) of InhA-PCAM complex formation and IC50(exp) (pIC50(exp) = -0.1552·ΔΔGcom + 5.0448, R² = 0.94), which was further validated with a 3D-QSAR pharmacophore model generation (PH4). Structural information from the models guided us in designing of a virtual combinatorial library (VL) of more than 17 million PCAMs. The VL was adsorption, distribution, metabolism and excretion (ADME) focused and reduced down to 1.6 million drug like orally bioavailable analogues and PH4 in silico screened to identify new potent PCAMs with predicted IC50(pre) reaching up to 5 nM. Combining molecular modeling and PH4 in silico screening of the VL resulted in the proposed novel potent antituberculotic agent candidates with favorable pharmacokinetic profiles.

Virtually Designed Triclosan-Based Inhibitors of Enoyl-Acyl Carrier Protein Reductase of Mycobacterium tuberculosis and of Plasmodium falciparum.

We report here new chemical structures of predicted nanomolar triclosan-based inhibitors (TCLs) of Mycobacterium tuberculosis enoyl-acyl carrier protein reductase (InhA) virtually proposed by computer-assisted molecular design. 3D models of InhA-TCL complexes were prepared by in situ modifications of the reference crystal structure (PDB entry 1P45) for a training set of 15 TCLs with known InhA inhibitory activities. A QSAR model was built leading to linear correlation between the calculated free energies of complexation (ΔΔGcom ) and experimental values IC50 (exp) : pIC50 =-0.0657×ΔΔGcom +3.0502, R(2) =0.96. In addition, ligand-based quantitative pharmacophore model (PH4) was built from bound conformations of the training set compounds and confirmed the correlation between molecular models and observed activities: pIC50 (exp=) 0.8929×pIC50 (pre) -0.441, R(2) =0.95. Structural information from both models helped us to propose new TCL analogues. A virtual library of TCLs with known predicted activities against enoyl-acyl carrier protein reductase of Plasmodium falciparum (PfENR) was evaluated, revealing dual target TCLs. Moreover, analysis of binding site interactions suggested enriching substitutions, which led to more potent TCLs with predicted pIC50 (pre) as low as 7 nM. The computational approach, which used both free energy estimated from molecular modeling and 3D-QSAR pharmacophore model, was helpful in virtually proposing the dual-targeted drugs and provided valuable information for the design of novel potential antituberculotic agents.

Ultraviolet A radiation potentiates the cytotoxic and genotoxic effects of 7 H-dibenzo[c,g]carbazole and its methyl derivatives.

7H-Dibenzo[c,g]carbazole (DBC) is a heterocyclic aromatic hydrocarbon that is carcinogenic in many species and tissues. DBC is a common environmental pollutant, and is therefore constantly exposed to sunlight. However, there are limited data exploring the toxicity of DBC photoexcitation products. Here, we investigated the impact of ultraviolet (UV) A radiation on the biological activity of DBC and its methyl derivatives, 5,9-dibenzo[c,g]carbazole and N-methyl dibenzo[c,g]carbazole, on human skin HaCaT keratinocytes. Co-exposure of HaCaT cells to UVA and DBC derivatives resulted in a sharp dose-dependent decrease in cell survival and apparent changes in cell morphology. Under the same treatment conditions, significant increases in DNA strand breaks, intracellular reactive oxygen species, and oxidative damage to DNA were observed in HaCaT cells. Consistent with these results, an apparent inhibition in superoxide dismutase, but not glutathione peroxidase activity, was detected in cells treated with DBC and its derivatives under UVA irradiation. The photoactivation-induced toxicity of individual DBC derivatives correlated with the electron excitation energies approximately expressed as the energy difference between the highest occupied and the lowest vacant molecular orbital. Our data provide the first evidence that UVA can enhance the toxicity of DBC and its derivatives. Photoactivation-induced conversion of harmless chemical compounds to toxic photoproducts associated with reactive oxygen species generation may substantially amplify the adverse health effects of UVA radiation and contribute to increased incidence of skin cancer.

Selective inhibitors of zinc-dependent histone deacetylases. Therapeutic targets relevant to cancer.

Histone deacetylases (HDACs), which act on acetylated histones and/or other non-histone protein substrates, represent validated epigenetic targets for the treatment of cancer and other human diseases. The inhibition of HDAC activity was shown to induce cell cycle arrest, differentiation, apoptosis as well as a decrease in proliferation, angiogenesis, migration, and cell resistance to chemotherapy. Targeting single HDAC isoforms with selective inhibitors will help to reveal the role of individual HDACs in cancer development or uncover further biological consequences of protein acetylation. This review focuses on conventional zinc-containing HDACs. In its first part, the biological role of individual HDACs in various types of cancer is summarized. In the second part, promising HDAC inhibitors showing activity both in enzymatic and cell-based assays are surveyed with an emphasis on the inhibitors selective to the individual HDACs.

Drugs against avian influenza a virus: design of novel sulfonate inhibitors of neuraminidase N1.

The outbreak of avian influenza A (H5N1) virus has raised a global concern for both the animal as well as human health. Besides vaccination, that may not achieve full protection in certain groups of patients, inhibiting neuraminidase or the transmembrane protein M2 represents the main measure of controlling the disease. Due to alarming emergence of influenza virus strains resistant to the currently available drugs, development of new neuraminidase N1 inhibitors is of utmost importance. The present paper provides an overview of the recent advances in the design of new antiviral drugs against avian influenza. It also reports findings in binding free energy calculations for nine neuraminidase N1 inhibitors (oseltamivir, zanamivir, and peramivir -carboxylate, -phosphonate, and -sulfonate) using the Linear Interaction Energy method. Molecular dynamics simulations of these inhibitors were performed in a free and two bound states - the so called open and closed conformations of neuraminidase N1. Obtained results successfully reproduce the experimental binding affinities of the already known neuraminidase N1 inhibitors, i.e. peramivir being a stronger binder than zanamivir that is in turn stronger binder than oseltamivir, or phosphonate inhibitors being stronger binders than their carboxylate analogues. In addition, the newly proposed sulfonate inhibitors are predicted to be the strongest binders - a fact to be confirmed by their chemical synthesis and a subsequent test of their biological activity. Finally, contributions of individual inhibitor moieties to the overall binding affinity are explicitly evaluated to assist further drug development towards inhibition of the H5N1 avian influenza A virus.

Inhibitors of HIV-protease from computational design. A history of theory and synthesis still to be fully appreciated.

Despite the fact that HIV-Protease is an over 20 years old target, computational approaches to rational design of its inhibitors still have a great potential to stimulate the synthesis of new compounds and the discovery of new, potent derivatives, ever capable to overcome the problem of drug resistance. This review deals with successful examples of inhibitors identified by computational approaches, rather than by knowledge-based design. Such methodologies include the development of energy and scoring functions, docking protocols, statistical models, virtual combinatorial chemistry. Computations addressing drug resistance, and the development of related models as the substrate envelope hypothesis are also reviewed. In some cases, the identified structures required the development of synthetic approaches in order to obtain the desired target molecules; several examples are reported.