Bone Marrow Cell Colonization Of, and Extracellular Matrix Expression On, Biodegradable Polymers

Poly(DL-lactide-co-glycolide)s (PLGAs) have been proposed as substrata for bone tissue engineering. In the experiments reported herein, we sought to identify the optimum lactide to glycolide ratio, from the series 85:15, 75:25, 50:50, or poly-(DL-lactide) (PLA), for the elaboration of bone matrix by cultured rat bone marrow cells (RBMC) on two-dimensional substrates. Having identified PLGA 75:25 as the optimum for bone matrix elaboration by RBMC, we produced three dimensional foams from this copolymer. For the two dimensional substrata, glass coverslips were spin-coated with one of the PLGAs, or PLA. Cultures were maintained for two weeks. We employed a new technique to label the elaborated bone matrix with the fluorescent antibiotic tetracycline. Bone matrix was present to a varying degree dependent on substrate composition: PLGA 75:25 = TCP \u3e PLGA 85:15 \u3e \u3e PLA. No bone matrix was observed on PLGA 50:50 or on uncoated glass coverslips. Cell proliferation was similar on each surface except PLA on which they did not proliferate. Cell morphology was assessed by scanning electron microscopy. Based on these results, three dimensional devices were produced from PLGA 75:25. Our results demonstrate that the copolymer ratios that maximize cell proliferation are not identical to the that optimize bone matrix elaboration. Furthermore, despite the intended use of three dimensional matrices for connective tissue engineering applications, bone marrow-derived cells produced only a superficial matrix layer that did not invade the scaffold, whether produced by either the salt leaching or freeze-drying procedures employed

Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction

The expansion of protein-ligand annotation databases has enabled large-scale networking of proteins by ligand similarity. These ligand-based protein networks, which implicitly predict the ability of neighboring proteins to bind related ligands, may complement biologically-oriented gene networks, which are used to predict functional or disease relevance. To quantify the degree to which such ligand-based protein associations might complement functional genomic associations, including sequence similarity, physical protein-protein interactions, co-expression, and disease gene annotations, we calculated a network based on the Similarity Ensemble Approach (SEA: sea.docking.org), where protein neighbors reflect the similarity of their ligands. We also measured the similarity with functional genomic networks over a common set of 1,131 genes, and found that the networks had only small overlaps, which were significant only due to the large scale of the data. Consistent with the view that the networks contain different information, combining them substantially improved Molecular Function prediction within GO (from AUROC~0.63-0.75 for the individual data modalities to AUROC~0.8 in the aggregate). We investigated the boost in guilt-by-association gene function prediction when the networks are combined and describe underlying properties that can be further exploited

Kriteria Visibilitas Hilal Rukyatul Hilal Indonesia (Rhi) (Konsep, Kriteria, dan Implementasi)

Telah dilaksanakan observasi hilal dan hilal tua selama periode Zulhijjah 1427–Zulhijjah 1430 H (Januari 2007–Desember 2009) oleh jejaring titik observasi Rukyatul Hilal Indonesia (RHI) yang merentang dari lintang 5° LU hingga 31° LS, dengan ataupun tanpa bantuan alat bantu optik. Observasi menghasilkan 174 data visibilitas yang terdiri dari 107 visibilitas positif dan 67 visibilitas negatif. Analisis korelasi linier Lag dengan Best Time Bulan menghasilkan definisi baru tentang hilal, yaitu Bulan pasca konjungsi yang memiliki Lag ≤ 24 menit hingga Lag ≤ 40 menit saat Matahari terbenam. Hubungan Best Time dan Lag memenuhi persamaan linear Yallop hanya untuk Lag ≤ 40 menit. Analisis korelasi aD dan DAz dengan metode least–square menghasilkan persamaan kriteria RHI aD ≥ 0,099 DAz2–1,490 DAz + 10,382 yang bentuknya hampir sama dengan kriteria LAPAN, namun sangat berbeda dibanding kriteria Fotheringham–Maunder maupun Bruin. Analisa komparatif menyimpulkan asumsi yang dipergunakan “kriteria” Imkanur Rukyat versi MABIMS dan konsep wujudul hilal tidak terbukti. Sebaliknya, terdapat kesesuaian antara hasil observasi dengan kriteria Odeh

Structure-based discovery and in-parallel optimization of novelcompetitive inhibitors of thymidylate synthase

AbstractBackground:The substrate sites of enzymes are attractive targets for structurebased inhibitor design. Two difficulties hinder efforts to discover and elaborate new (nonsubstrate-like) inhibitors for these sites. First, novel inhibitors often bind at nonsubstrate sites. Second, a novel scaffold introduces chemistry that is frequently unfamiliar, making synthetic elaboration challenging.Results:In an effort to discover and elaborate a novel scaffold for a substrate site, we combined structure-based screening with in-parallel synthetic elaboration. These techniques were used to find new inhibitors that bound to the folate site of Lactobacillus casei thymidylate synthase (LcTS), an enzyme that is a potential target for proliferative diseases, and is highly studied. The available chemicals directory was screened, using a molecular-docking computer program, for molecules that complemented the three-dimensional structure of this site. Five high-ranking compounds were selected for testing. Activity and clocking studies led to a derivative of one of these, dansyltyrosine (Ki 65 μM. Using solid-phase in-parallel techniques 33 derivatives of this lead were synthesized and tested. These analogs are dissimilar to the substrate but bind competitively with it. The most active analog had a Ki of 1.3 μM. The tighter binding inhibitors were also the most specific for LcTS versus related enzymes.Conclusions:TS can recognize inhibitors that are dissimilar to, but that bind competitively with, the folate substrate. Combining structure-based discovery with in-parallel synthetic techniques allowed the rapid elaboration of this series of compounds. More automated versions of this approach can be envisaged

Encapsulation-free controlled release: Electrostatic adsorption eliminates the need for protein encapsulation in PLGA nanoparticles

Encapsulation of therapeutic molecules within polymer particles is a well-established method for achieving controlled release, yet challenges such as low loading, poor encapsulation efficiency, and loss of protein activity limit clinical translation. Despite this, the paradigm for the use of polymer particles in drug delivery has remained essentially unchanged for several decades. By taking advantage of the adsorption of protein therapeutics to poly(lactic-co-glycolic acid) (PLGA) nanoparticles, we demonstrate controlled release without encapsulation. In fact, we obtain identical, burst-free, extended-release profiles for three different protein therapeutics with and without encapsulation in PLGA nanoparticles embedded within a hydrogel. Using both positively and negatively charged proteins, we show that short-range electrostatic interactions between the proteins and the PLGA nanoparticles are the underlying mechanism for controlled release. Moreover, we demonstrate tunable release by modifying nanoparticle concentration, nanoparticle size, or environmental pH. These new insights obviate the need for encapsulation and offer promising, translatable strategies for a more effective delivery of therapeutic biomolecules

D 4 dopamine receptor high-resolution structures enable the discovery of selective agonists

Dopamine receptors are G protein-coupled receptors implicated in many neurological disorders. Different families of dopamine receptors are involved in different signaling pathways, so specificity is a key goal of therapeutics. Wang et al. present high-resolution crystal structures of the DRD4 dopamine receptor bound to the antipsychotic drug nemonapride. The high resolution of the structures facilitated ligand docking, and a DRD4-selective agonist was identified by computational screening of a large library, experimental testing of compounds with the best docking scores, and iterative cycles of docking and testing analogs of those compounds. The identified agonist had a high affinity for DRD4 and no measurable affinity for DRD2 or DRD3. Science , this issue p. [381][1] [1]: /lookup/doi/10.1126/science.aan546

Combinatorial Computational Approaches to Identify Tetracycline Derivatives as Flavivirus Inhibitors

Limited structural information of drug targets, cellular toxicity possessed by lead compounds, and large amounts of potential leads are the major issues facing the design-oriented approach of discovering new leads. In an attempt to tackle these issues, we have developed a process of virtual screening based on the observation that conformational rearrangements of the dengue virus envelope protein are essential for the mediation of viral entry into host cells via membrane fusion. Screening was based solely on the structural information of the Dengue virus envelope protein and was focused on a target site that is presumably important for the conformational rearrangements necessary for viral entry. To circumvent the issue of lead compound toxicity, we performed screening based on molecular docking using structural databases of medical compounds. To enhance the identification of hits, we further categorized and selected candidates according to their novel structural characteristics. Finally, the selected candidates were subjected to a biological validation assay to assess inhibition of Dengue virus propagation in mammalian host cells using a plaque formation assay. Among the 10 compounds examined, rolitetracycline and doxycycline significantly inhibited plaque formation, demonstrating their inhibitory effect on dengue virus propagation. Both compounds were tetracycline derivatives with IC(50)s estimated to be 67.1 µM and 55.6 µM, respectively. Their docked conformations displayed common hydrophobic interactions with critical residues that affected membrane fusion during viral entry. These interactions will therefore position the tetracyclic ring moieties of both inhibitors to bind firmly to the target and, subsequently, disrupt conformational rearrangement and block viral entry. This process can be applied to other drug targets in which conformational rearrangement is critical to function

Crystal Structure of an LSD-Bound Human Serotonin Receptor

SummaryThe prototypical hallucinogen LSD acts via serotonin receptors, and here we describe the crystal structure of LSD in complex with the human serotonin receptor 5-HT2B. The complex reveals conformational rearrangements to accommodate LSD, providing a structural explanation for the conformational selectivity of LSD's key diethylamide moiety. LSD dissociates exceptionally slow from both 5-HT2BR and 5-HT2AR—a major target for its psychoactivity. Molecular dynamics (MD) simulations suggest that LSD's slow binding kinetics may be due to a "lid" formed by extracellular loop 2 (EL2) at the entrance to the binding pocket. A mutation predicted to increase the mobility of this lid greatly accelerates LSD's binding kinetics and selectively dampens LSD-mediated β-arrestin2 recruitment. This study thus reveals an unexpected binding mode of LSD; illuminates key features of its kinetics, stereochemistry, and signaling; and provides a molecular explanation for LSD's actions at human serotonin receptors.PaperCli

Structure-Based Discovery of A2A Adenosine Receptor Ligands

The recent determination of X-ray structures of pharmacologically relevant GPCRs has made these targets accessible to structure-based ligand discovery. Here we explore whether novel chemotypes may be discovered for the A(2A) adenosine receptor, based on complementarity to its recently determined structure. The A(2A) adenosine receptor signals in the periphery and the CNS, with agonists explored as anti-inflammatory drugs and antagonists explored for neurodegenerative diseases. We used molecular docking to screen a 1.4 million compound database against the X-ray structure computationally and tested 20 high-ranking, previously unknown molecules experimentally. Of these 35% showed substantial activity with affinities between 200 nM and 9 microM. For the most potent of these new inhibitors, over 50-fold specificity was observed for the A(2A) versus the related A(1) and A(3) subtypes. These high hit rates and affinities at least partly reflect the bias of commercial libraries toward GPCR-like chemotypes, an issue that we attempt to investigate quantitatively. Despite this bias, many of the most potent new ligands were novel, dissimilar from known ligands, providing new lead structures for modulation of this medically important target

Automated Docking Screens: A Feasibility Study

Molecular docking is themost practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCKBlaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCKBlaster recapitulates the crystal ligand pose within 2 A ̊ rmsd 50-60 % of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5 % of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5 % of 100 property-matched decoys while also posing within 2 A ̊ rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available a