Multi-method computational evaluation of the inhibitors against leucine-rich repeat kinase 2 G2019S mutant for Parkinson's disease.

Leucine-rich repeat kinase 2 G2019S mutant (LRRK2 G2019S) is a potential target for Parkinson's disease therapy. In this work, the computational evaluation of the LRRK2 G2019S inhibitors was conducted via a combined approach which contains a preliminary screening of a large database of compounds via similarity and pharmacophore, a secondary selection via structure-based affinity prediction and molecular docking, and a rescoring treatment for the final selection. MD simulations and MM/GBSA calculations were performed to check the agreement between different prediction methods for these inhibitors. 331 experimental ligands were collected, and 170 were used to build the structure-activity relationship. Eight representative ligand structural models were employed in similarity searching and pharmacophore screening over 14 million compounds. The process for selecting proper molecular descriptors provides a successful sample which can be used as a general strategy in QSAR modelling. The rescoring used in this work presents an alternative useful treatment for ranking and selection.

All-Ion Monitoring-Directed Low-Abundance Protein Quantification Reveals CALB2 as a Key Promoter in Hepatocellular Carcinoma Metastasis.

Because of the wide abundance range of the proteome, achieving high-coverage quantification of low-abundance proteins is always a major challenge. In this study, a complete pipeline focused on all-ion monitoring (AIM) is first constructed with the concept of untargeted parallel-reaction monitoring, including the seamless connection of protein sample preparation, liquid chromatography mass spectrometry (LC-MS) acquisition, and algorithm development to enable the in-depth quantitative analysis of low-abundance proteins. This pipeline significantly improves the reproducibility and sensitivity of sample preparation and LC-MS acquisition for low-abundance proteins, enabling all the precursors ions fragmented and collected. Contributed by the advantages of the AIM method with all the target precursor acquisition by the data-dependent acquisition (DDA) approach, together with the ability of data-independent acquisition to fragment all precursor ions, the quantitative accuracy and precision of low-abundance proteins are greatly enhanced. As a proof of concept, this pipeline is employed to discover the key differential proteins in the mechanism of hepatocellular carcinoma (HCC) metastasis. On the basis of the superiority of AIM, an extremely low-abundance protein, CALB2, is proposed to promote HCC metastasis in vitro and in vivo. We also reveal that CALB2 activates the TRPV2-Ca2+-ERK1/2 signaling pathway to induce HCC cell metastasis. In summary, we provide a universal AIM pipeline for the high-coverage quantification of low-abundance functional proteins to seek novel insights into the mechanisms of cancer metastasis.

Ionic Liquid-Based Extraction System for In-Depth Analysis of Membrane Protein Complexes.

Limited by the rare efficient extraction system in extracting hydrophobic membrane protein complexes (MPCs) without compromising the stability of protein-protein interactions (PPIs), the in-depth functional study of MPCs has lagged far behind. In this study, the first systematic screening of ionic liquids (ILs) was performed and showed that triethylammonium acetate (TEAA) IL exhibited excellent performance in stabilizing PPIs, which was further confirmed by molecular docking simulations. By combining TEAA with the conventional detergent Nonidet P-40 (NP-40), a novel IL-based extraction system, i-TAN (TEAA IL with 1% NP-40), was proposed, which demonstrated superior performance in extracting and stabilizing MPCs, attributed to its larger size, more uniform distribution, and closer-to-neutral microenvironment of micelles. Extraction of MPCs with i-TAN allowed the confident identification of more hydrophobic EGFR-interacting proteins that are easily dissociated during the extraction process. Quantitative analysis of the difference in EGFR complexes between trastuzumab-sensitive and trastuzumab-resistant breast cancer cells provided comprehensive insights to understand the drug resistance mechanism, suggesting that i-TAN has great potential in interactomics and functional analysis of MPCs. This study provides a novel strategy for MPC extraction and downstream processing.

Discovery of inhibitors targeting protein tyrosine phosphatase 1B using a combined virtual screening approach.

Protein tyrosine phosphatase 1B (PTP1B) acts as a therapeutic target for type 2 diabetes. However, the major challenges of PTP1B drug discovery are the poor selectivity and the weak oral bioavailability. In this study, we performed a combined virtual screening approach including multicomplex pharmacophore, molecular docking-based screening, van der Waals energy normalization, pose scaling factor, ADMET evaluation, and molecular dynamics simulation to select PTP1B inhibitors from three databases (PubChem, ChEMBL, and ZINC). We identified three potential PTP1B inhibitors, compounds 1, 4, and 5, with favorable binding energy and good oral bioavailability. The energetic and geometrical analyses show that the three compounds are stably bound to PTP1B, via occupying both the catalytic site (site A) and the proximal noncatalytic site (site B or C). Such occupancy may improve the selectivity. This work not only provided a feasible virtual screening protocol, but also suggested three potential PTP1B inhibitors for the treatment of type 2 diabetes.

Quantitative proteomics identifies FOLR1 to drive sorafenib resistance via activating autophagy in hepatocellular carcinoma cells.

Sorafenib is commonly used to treat advanced human hepatocellular carcinoma (HCC). However, clinical efficacy has been limited by drug resistance. In this study, we used label-free quantitative proteomic analysis to systematically investigate the underlying mechanisms of sorafenib resistance in HCC cells. A total of 1709 proteins were confidently quantified. Among them, 89 were differentially expressed and highly enriched in the processes of cell-cell adhesion, negative regulation of apoptosis, response to drug and metabolic processes involving in sorafenib resistance. Notably, folate receptor α (FOLR1) was found to be significantly upregulated in resistant HCC cells. In addition, in vitro studies showed that overexpression of FOLR1 decreased the sensitivity of HCC cells to sorafenib, whereas siRNA-directed knockdown of FOLR1 increased the sensitivity of HCC cells to sorafenib. Immunoprecipitation-mass spectrometry analysis suggested a strong link between FOLR1 and autophagy-related proteins. Further biological experiments found that FOLR1-related sorafenib resistance was accompanied by the activation of autophagy, whereas inhibition of autophagy significantly reduced FOLR1-induced cell resistance. These results suggest the driving role of FOLR1 in HCC resistance to sorafenib, which may be exerted through FOLR1-induced autophagy. Therefore, this study may provide new insights into understanding the mechanism of sorafenib resistance.

Divide-and-link peptide docking: a fragment-based peptide docking protocol.

Protein-peptide interactions are crucial for various important cellular regulations, and are also a basis for understanding protein-protein interactions, protein folding and peptide drug design. Due to the limited structural data obtained using experimental methods, it is necessary to predict protein-peptide interaction modes using computational methods. In the present work, we designed a fragment-based docking protocol, Divide-and-Link Peptide Docking (DLPepDock), to predict protein-peptide binding modes. This protocol contains the following steps: dividing the peptide into fragments and separately docking the fragments using a third-party small molecular docking tool, linking the docked fragmental poses to form the whole peptide conformations via fragmental coordinate transformation using our in-house program, removing unreasonable poses according to several geometrical filters, extracting representative conformations after clustering for further minimization using the steepest descent and conjugation gradient methods based on a full-atom molecular force field and finally scoring using the MM/PBSA binding energy calculation implemented in Amber. When tested on the LEADS-PEP benchmark data set of 26 diverse complexes with peptides of 6-12 residues, FlexPepDock ab initio and AutoDock CrankPep achieved superior results. DLPepDock performed better than the other 15 docking protocols implemented in nine docking programs (HPepDock, DockThor, rDock, Glide, LeDock, AutoDock, AutoDock Vina, Surflex, and GOLD). The Linux scripts to call the third-party tools and run all the calculations.

Novel LRRK2 GTP-binding inhibitors reduced degeneration in Parkinson's disease cell and mouse models.

Mutations in the leucine-rich repeat kinase-2 (LRRK2) gene cause autosomal-dominant Parkinson's disease (PD) and contribute to sporadic PD. LRRK2 contains Guanosine-5'-triphosphate (GTP) binding, GTPase and kinase activities that have been implicated in the neuronal degeneration of PD pathogenesis, making LRRK2, a potential drug target. To date, there is no disease-modifying drug to slow the neuronal degeneration of PD and no published LRRK2 GTP domain inhibitor. Here, the biological functions of two novel GTP-binding inhibitors of LRRK2 were examined in PD cell and mouse models. Through a combination of computer-aided drug design (CADD) and LRRK2 bio-functional screens, two novel compounds, 68: and 70: , were shown to reduce LRRK2 GTP binding and to inhibit LRRK2 kinase activity in vitro and in cultured cell assays. Moreover, these two compounds attenuated neuronal degeneration in human SH-SY5Y neuroblastoma cells and mouse primary neurons expressing mutant LRRK2 variants. Although both compounds inhibited LRRK2 kinase activity and reduced neuronal degeneration, solubility problems with 70: prevented further testing in mice. Thus, only 68: was tested in a LRRK2-based lipopolysaccharide (LPS)-induced pre-inflammatory mouse model. 68: reduced LRRK2 GTP-binding activity and kinase activity in brains of LRRK2 transgenic mice after intraperitoneal injection. Moreover, LPS induced LRRK2 upregulation and microglia activation in mouse brains. These findings suggest that disruption of GTP binding to LRRK2 represents a potential novel therapeutic approach for PD intervention and that these novel GTP-binding inhibitors provide both tools and lead compounds for future drug development.

Evaluating the covalent binding of carbapenems on BlaC using noncovalent interactions.

Carbapenems, as irreversible covalent binders and slow substrates to the class A ß-lactamase (BlaC) of Mycobacterium tuberculosis, can inhibit BlaC to hydrolyze the ß-lactam drugs which are used to control tuberculosis. Their binding on BlaC involves covalent bonding and noncovalent interaction. We introduce a hypothesis that the noncovalent interactions dominate the difference of binding free energies for covalent ligands based on the assumption that their covalent bonding energies are the same. MM/GBSA binding free energies calculated from the noncovalent interactions provided a threshold with respect to the experimental kinetic data, to select slow carbapenem substrates which were either constructed using the structural units of experimentally identified carbapenems or obtained from the similarity search over the ZINC15 database. Combining molecular docking with consensus scoring and molecular dynamics simulation with MM/GBSA binding free energy calculations, a computational protocol was developed from which several new tight-binding carbapenems were theoretically identified.

Small molecules bound to unique sites in the target protein binding cleft of calcium-bound S100B as characterized by nuclear magnetic resonance and X-ray crystallography.

Structural studies are part of a rational drug design program aimed at inhibiting the S100B-p53 interaction and restoring wild-type p53 function in malignant melanoma. To this end, structures of three compounds (SBi132, SBi1279, and SBi523) bound to Ca(2+)-S100B were determined by X-ray crystallography at 2.10 A (R(free) = 0.257), 1.98 A (R(free) = 0.281), and 1.90 A (R(free) = 0.228) resolution, respectively. Upon comparison, SBi132, SBi279, and SBi523 were found to bind in distinct locations and orientations within the hydrophobic target binding pocket of Ca(2+)-S100B with minimal structural changes observed for the protein upon complex formation with each compound. Specifically, SBi132 binds nearby residues in loop 2 (His-42, Phe-43, and Leu-44) and helix 4 (Phe-76, Met-79, Ile-80, Ala-83, Cys-84, Phe-87, and Phe-88), whereas SBi523 interacts with a separate site defined by residues within loop 2 (Ser-41, His-42, Phe-43, Leu-44, Glu-45, and Glu-46) and one residue on helix 4 (Phe-87). The SBi279 binding site on Ca(2+)-S100B overlaps the SBi132 and SBi523 sites and contacts residues in both loop 2 (Ser-41, His-42, Phe-43, Leu-44, and Glu-45) and helix 4 (Ile-80, Ala-83, Cys-84, Phe-87, and Phe-88). NMR data, including saturation transfer difference (STD) and (15)N backbone and (13)C side chain chemical shift perturbations, were consistent with the X-ray crystal structures and demonstrated the relevance of all three small molecule-S100B complexes in solution. The discovery that SBi132, SBi279, and SBi523 bind to proximal sites on Ca(2+)-S100B could be useful for the development of a new class of molecule(s) that interacts with one or more of these binding sites simultaneously, thereby yielding novel tight binding inhibitors specific for blocking protein-protein interactions involving S100B.

Uniformly convergent n-tuple-zeta augmented polarized (nZaP) basis sets for complete basis set extrapolations. I. Self-consistent field energies.

We present a sequence of n-tuple-zeta augmented polarized (nZaP) basis sets designed for extrapolations of both self-consistent field (SCF) and correlation energies to the complete basis set (CBS) limit. These nZaP basis sets (n=2-6) are formulated to give consistent errors throughout the Periodic Table (e.g., a consistent of approximately 1 mhartree/electron error for the 2ZaP SCF energy and a consistent of approximately 1.4 muhartree/electron error for the 6ZaP SCF energy). The SCF energy exhibits systematic convergence to the CBS limit: E(SCF)(nZaP) approximately E(SCF)(CBS)+Ae(-an). A single parameter, a=6.30, describes the 2ZaP through 6ZaP errors of H through Xe within 10%. The SCF rms basis set truncation errors of H through Xe are 33.5mE(h), 4.58mE(h), 0.82mE(h), 0.18mE(h), and 0.047mE(h) for 2ZaP, 3ZaP, 4ZaP, 5ZaP, and 6ZaP, respectively. Linear extrapolations of the (2,3)ZaP, (3,4)ZaP, (4,5)ZaP, and (5,6)ZaP calculations (all with a=6.30) reduce these errors by an order of magnitude to 0.24mE(h), 0.056mE(h), 0.020mE(h), and 0.005mE(h), respectively. A test set of 34 atoms, ions, and molecules gives similar results, and the associated test set of 25 chemical energy differences also gives comparable absolute accuracy. However, the cancellation of errors between reactant and product is lost by extrapolation. As a result, these chemical energy differences show a more modest two-to-fourfold improvement with extrapolation.

Inhibition of the bacterial heme oxygenases from Pseudomonas aeruginosa and Neisseria meningitidis: novel antimicrobial targets.

The final step in heme utilization and iron acquisition in many pathogens is the oxidative cleavage of heme by heme oxygenase (HO), yielding iron, biliverdin, and carbon monoxide. Thus, the essential requirement for iron suggests that HO may provide a potential therapeutic target for antimicrobial drug development. Computer-aided drug design (CADD) combined with experimental assays identified small-molecule inhibitors of the Neisseria meningitidis HO (nm-HO). CADD virtual screening applied to 800 000 compounds identified 153 for biological assay. Several of the compounds were shown to have KD values in the micromolar range for nm-HO and the Pseudomonas aeruginosa HO (pa-HO). The compounds also inhibited the growth of P. aeruginosa as well as biliverdin formation in E. coli cells overexpressing nm-HO. Thus, CADD combined with experimental analysis has been used to identify novel inhibitors of the bacterial heme oxygenases that can cross the cell membrane and specifically inhibit HO activity.

Enhanced fermentative performance under stresses of multiple lignocellulose-derived inhibitors by overexpression of a typical 2-Cys peroxiredoxin from Kluyveromyces marxianus.

BACKGROUND: Bioethanol from lignocellulosic materials is of great significance to the production of renewable fuels due to its wide sources. However, multiple inhibitors generated from pretreatments represent great challenges for its industrial-scale fermentation. Despite the complex toxicity mechanisms, lignocellulose-derived inhibitors have been reported to be related to the levels of intracellular reactive oxygen species (ROS), which makes oxidoreductase a potential target for the enhancement of the tolerance of yeasts to these inhibitors. RESULTS: A typical 2-Cys peroxiredoxin from Kluyveromyces marxianus Y179 (KmTPX1) was identified, and its overexpression was achieved in Saccharomyces cerevisiae 280. Strain TPX1 with overexpressed KmTPX1 gene showed an enhanced tolerance to oxidative stresses. Serial dilution assay indicated that KmTPX1 gene contributed to a better cellular growth behavior, when the cells were exposed to multiple lignocellulose-derived inhibitors, such as formic acid, acetic acid, furfural, ethanol, and salt. In particular, KmTPX1 expression also possessed enhanced tolerance to a mixture of formic acid, acetic acid, and furfural (FAF) with a shorter lag period. The maximum glucose consumption rate and ethanol generation rate in KmTPX1-expressing strain were significantly improved, compared with the control. The mechanism of improved tolerance to FAF depends on the lower level of intracellular ROS for cell survival under stress. CONCLUSION: A new functional gene KmTPX1 from K. marxianus is firstly associated with the enhanced tolerance to multiple lignocellulose-derived inhibitors in S. cerevisiae. We provided a possible detoxification mechanism of the KmTPX1 for further theoretical research; meanwhile, we provided a powerful potential for application of the KmTPX1 overexpressing strain in ethanol production from lignocellulosic materials.

How Y357F, Y276F mutants affect the methylation activity of PRDM9: QM/MM MD and free energy simulations.

Histone methyltransferase PRDM9 catalyzes the methylation of H3K4me2 (histone 3 dimethylated lysine 4) to H3K4me3 (histone 3 trimethylated lysine 4) by transferring the methyl group from S-adenosyl methionine (AdoMet). PRDM9 is the major determinant of the meiotic recombination hotspot and the enrichment of H3K4me3 at the hotspot defines the initiation site of meiotic recombination. In PRDM9, two conserved tyrosine residues Tyr357 and Tyr276 surrounding the amino group of the substrate lysine may influence the methylation activity through hydrogen bond interactions with AdoMet or the substrate lysine. In this study, quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) and free energy simulations were performed to reveal the methylation processes catalyzed by wild type PRDM9, its Y357F, and Y276F mutants, respectively. The different roles of Tyr357 and Tyr276 in the methylation activity of PRDM9 were also investigated and compared. The calculated free energy barriers of the methyl transfers suggest that the Y276F mutation decreases the catalytic activity of the methyl transfer, while the Y357F mutation does not change the catalytic activity of the methyl transfer. The reactant complex conformations generated in the QM/MM MD simulations show that the reactive configuration can be formed in the Y357F mutant but not in the Y276F mutant.

Transcriptional analysis of Kluyveromyces marxianus for ethanol production from inulin using consolidated bioprocessing technology.

BACKGROUND: Ethanol production from non-crop materials, such as Jerusalem artichokes, would make a great contribution to the energy industry. The non-conventional yeast, Kluyveromyces marxianus, is able to carry out ethanol fermentation of sugar molecules obtained from inulin-containing materials by consolidated bioprocessing. Lower inulin concentrations and micro-aeration can lead to a relatively fast and ideal fermentation process; however, it is unclear what causes the inhibition of higher concentrations of inulin and the promotion effect of aeration. RESULTS: Next-generation sequencing technology was used to study the global transcriptional response of K. marxianus Y179 under three fermentation conditions, including 120 g/L inulin without aeration (120-N), 230 g/L inulin without aeration (230-N), 230 g/L inulin with aeration by ORP controlling at -130 mV (230-130mV). A total of 35.55 million clean reads were generated from three samples, of which 4,820 predicted that open reading frames were annotated. For differential expression analysis, 950 and 1,452 differentially expressed genes were discovered under the conditions of 230-130mV and 120-N, respectively, and the sample 230-N was used as the control. These genes are mainly associated with the pathways of central carbon metabolism and ethanol formation. Increased expression of inulinase and the low activity of the autophagy-related gene, ATG8, ensured fast and ideal fermentation processes. CONCLUSIONS: Despite being reported as the "crabtree-negative" species, K. marxianus Y179 could achieve favorable ethanol fermentation profiles under micro-aeration and high inulin concentrations. K. marxianus Y179 cells responded to inulin concentrations and micro-aeration that is involved in the whole ethanol metabolism network. These results will serve as an important foundation for further exploration of the regulatory mechanisms involved in ethanol fermentation from inulin by consolidated bioprocessing and also provide a valuable reference for future studies on optimization and reconstruction of the metabolism network in K. marxianus.

A novel GTP-binding inhibitor, FX2149, attenuates LRRK2 toxicity in Parkinson's disease models.

Leucine-rich repeat kinase-2 (LRRK2), a cytoplasmic protein containing both GTP binding and kinase activities, has emerged as a highly promising drug target for Parkinson's disease (PD). The majority of PD-linked mutations in LRRK2 dysregulate its GTP binding and kinase activities, which may contribute to neurodegeneration. While most known LRRK2 inhibitors are developed to target the kinase domain, we have recently identified the first LRRK2 GTP binding inhibitor, 68, which not only inhibits LRRK2 GTP binding and kinase activities with high potency in vitro, but also reduces neurodegeneration. However, the in vivo effects of 68 are low due to its limited brain penetration. To address this problem, we reported herein the design and synthesis of a novel analog of 68, FX2149, aimed at increasing the in vivo efficacy. Pharmacological characterization of FX2149 exhibited inhibition of LRRK2 GTP binding activity by ~90% at a concentration of 10 nM using in vitro assays. Furthermore, FX2149 protected against mutant LRRK2-induced neurodegeneration in SH-SY5Y cells at 50-200 nM concentrations. Importantly, FX2149 at 10 mg/kg (i.p.) showed significant brain inhibition efficacy equivalent to that of 68 at 20 mg/kg (i.p.), determined by mouse brain LRRK2 GTP binding and phosphorylation assays. Furthermore, FX2149 at 10 mg/kg (i.p.) attenuated lipopolysaccharide (LPS)-induced microglia activation and LRRK2 upregulation in a mouse neuroinflammation model comparable to 68 at 20 mg/kg (i.p.). Our results highlight a novel GTP binding inhibitor with better brain efficacy, which represents a new lead compound for further understanding PD pathogenesis and therapeutic studies.

Novel Cathelicidins from Pigeon Highlights Evolutionary Convergence in Avain Cathelicidins and Functions in Modulation of Innate Immunity.

Cathelicidins are short cationic host defense peptides and play a central role in host innate immune system. Here we identified two novel cathelicidins, Cl-CATH2 and 3, from Columba livia. Evolutionary analysis of avian cathelicidins via phylogenetic tree and Ka/Ks calculations supported the positive selection that prompted evolution of CATH2 to CATH1 and 3, which originate from common ancestor and could belong to one superfamily. Cl-CATH2 and 3 both adopt amphipathic α-helical comformations identified by circular dichroism and the 3D structures built by Rosetta. Cl-CATH2 of CATH2 family with the most expression abundance in bird, exhibited relatively weak antimicrobial activity, but acted instead on the innate immune response without showing undesirable toxicities. In macrophages primed by LPS, Cl-CATH2 significantly down-regulated the gene and protein expressions of inducible nitric oxide synthase and pro-inflammatory cytokines while enhancing the anti-inflammatory cytokine, acting through MAPK and NF-κB signaling pathways. Molecular docking shows for the first time that cathelicidin binds to the opening region of LPS-binding pocket on myeloid differentiation factor 2 (MD-2) of toll-like receptor (TLR)4-MD-2 complex, which in turn inhibits the TLR4 pathway. Our results, therefore, provide new insight into the mechanism underlying the blockade of TLR4 signaling by cathelicidins.

Modeling chemical bonding effects for protein electron crystallography: the transferable fragmental electrostatic potential (TFESP) method.

This paper addresses the problem of determining the electrostatic potential of large proteins by the superposition of potentials calculated for small fragments. The use of different atomic and molecular fragments is considered for reproducing the molecular electrostatic potential of different conformations of N-acetylalanine methylamide (NAAMA) with an acceptable degree of error as measured by conventional R factors used in crystallographic structure refinement. Three different divisions of NAAMA are tested, producing fragments that incorporate increasingly more complete descriptions of molecular bonding with diminishing accuracy in geometric fit to the parent molecule: single atoms in molecules, bonded atoms in molecules and selected functional groups, such as the backbone peptide moiety, or the alpha-carbon, beta-carbon and their associated H atoms. In the resolution range 2.5-25A, the fairly straightforward use of single atoms in molecules reduces the calculated R factors by 5-15% over a free-atom superposition. No significant further improvement was found at the lowest resolutions with a superposition of single bonds in molecules and R factors were found to degrade with larger fragments at higher resolutions because of poor geometry fits to the atoms of the parent molecule. Because the potential distribution even for single atoms depends on the environment, the best accuracy will be obtained by using a library of fragment potentials calculated for each type of atom as a function of important protein conformations.

Rescoring ligand docking poses.

The ranking of ligand docking poses according to certain scoring systems to identify the best fit is the most important step in virtual database screening for drug discovery. By focusing on method development strategy, this review provides possibilities for constructing rescoring approaches based on an overview of recent developments in the field. These developments can be classified into three categories. The first category involves a scaling approach that employs a factor to scale the primary scoring function. These scaling factors are defined with respect to the geometrical match between the location of a ligand and the target binding site, or defined according to a molecular weight distribution consistent with the empirical range of molecular weights of drug-like compounds. The second category involves consensus scoring approaches that use multiple scoring functions to rank the ligand poses retained in a docking procedure, based on the preliminary ranking according to a primary scoring function. The final category involves the addition of selected accuracy-oriented energy terms, such as the solvent effect and quantum mechanics/molecular mechanics treatments.

A small-molecule inhibitor of BCL6 kills DLBCL cells in vitro and in vivo.

The BCL6 transcriptional repressor is the most frequently involved oncogene in diffuse large B cell lymphoma (DLBCL). We combined computer-aided drug design with functional assays to identify low-molecular-weight compounds that bind to the corepressor binding groove of the BCL6 BTB domain. One such compound disrupted BCL6/corepressor complexes in vitro and in vivo, and was observed by X-ray crystallography and NMR to bind the critical site within the BTB groove. This compound could induce expression of BCL6 target genes and kill BCL6-positive DLBCL cell lines. In xenotransplantation experiments, the compound was nontoxic and potently suppressed DLBCL tumors in vivo. The compound also killed primary DLBCLs from human patients.

Targeting NAD biosynthesis in bacterial pathogens: Structure-based development of inhibitors of nicotinate mononucleotide adenylyltransferase NadD.

The emergence of multidrug-resistant pathogens necessitates the search for new antibiotics acting on previously unexplored targets. Nicotinate mononucleotide adenylyltransferase of the NadD family, an essential enzyme of NAD biosynthesis in most bacteria, was selected as a target for structure-based inhibitor development. Using iterative in silico and in vitro screens, we identified small molecule compounds that efficiently inhibited target enzymes from Escherichia coli (ecNadD) and Bacillus anthracis (baNadD) but had no effect on functionally equivalent human enzymes. On-target antibacterial activity was demonstrated for some of the selected inhibitors. A 3D structure of baNadD was solved in complex with one of these inhibitors (3_02), providing mechanistic insights and guidelines for further improvement. Most importantly, the results of this study help validate NadD as a target for the development of antibacterial agents with potential broad-spectrum activity.