Modeling of enzyme–substrate complexes for the metalloproteases MMP-3, ADAM-9 and ADAM-10

The matrix metalloproteases (MMPs) and the ADAMs (A Disintegrin And Metalloprotease domain) are proteolytic enzyme families containing a catalytic zinc ion, that are implicated in a variety of normal and pathological processes involving tissue remodeling and cancer. Synthetic MMP inhibitors have been designed for applications in pathological situations. However, a greater understanding of substrate binding and the catalytic mechanism is required so that more effective and selective inhibitors may be developed for both experimental and clinical purposes. By modeling a natural substrate spanning P4-P4‘ in complex with the catalytic domains, we aim to compare substrate-specificities between Stromelysin-1 (MMP-3), ADAM-9 and ADAM–10, with the aid of molecular dynamics simulations. Our results show that the substrate retains a favourable antiparallel beta-sheet conformation on the P-side in addition to the well-known orientation of the P'-region of the scissile bond, and that the primary substrate selectivity is dominated by the sidechains in the S1' pocket and the S2/S3 region. ADAM-9 has a hydrophobic residue as the central determinant in the S1' pocket, while ADAM-10 has an amphiphilic residue, which suggests a different primary specificity. The S2/S3 pocket is largely hydrophobic in all three enzymes. Inspired by our molecular dynamics calculations and supported by a large body of literature, we propose a novel, hypothetical, catalytic mechanism where the Zn-ion polarizes the oxygens from the catalytic glutamate to form a nucleophile, leading to a tetrahedral oxyanion anhydride transition state.

Expression of the disintegrin metalloprotease ADAM-10 in prostate cancer and its regulation by dihydrotestosterone, insulin like growth factor -1 and epidermal growth factor in the prostate cell model LNCaP

Purpose: The disintegrin metalloprotease ADAM-10 is a multidomain metalloprotease that is potentially significant in tumor progression due to its extracellular matrix-degrading properties. Previously, ADAM-10 mRNA was detected in prostate cancer (PCa) cell lines; however, the presence of ADAM-10 protein and its cellular localization, regulation, and role have yet to be described. We hypothesized that ADAM-10 mRNA and protein may be regulated by growth factors such as 5α-dihydrotestosterone, insulin-like growth factor I, and epidermal growth factor, known modulators of PCa cell growth and invasion.

Experimental Design: ADAM-10 expression was analyzed by in situ hybridization and immunohistochemistry in prostate tissues obtained from 23 patients with prostate disease. ADAM-10 regulation was assessed using quantitative reverse transcription-PCR and Western blot analysis in the PCa cell line LNCaP.

Results: ADAM-10 expression was localized to the secretory cells of prostate glands, with additional basal cell expression in benign glands. ADAM-10 protein was predominantly membrane bound in benign glands but showed marked nuclear localization in cancer glands. By Western blot, the 100-kDa proform and the 60-kDa active form of ADAM-10 were synergistically up-regulated in LNCaP cells treated with insulin-like growth factor I plus 5α-dihydrotestosterone. Epidermal growth factor also up-regulated both ADAM-10 mRNA and protein.

Conclusions: This study describes for the first time the expression, regulation, and cellular localization of ADAM-10 protein in PCa. The regulation and membrane localization of ADAM-10 support our hypothesis that ADAM-10 has a role in extracellular matrix maintenance and cell invasion, although the potential role of nuclear ADAM-10 is not yet known.

AdaM : adaptive-maximum imputation for neighborhood-based collaborative filtering

In the context of collaborative filtering, the well known data sparsity issue makes two like-minded users have little similarity, and consequently renders the k nearest neighbour rule inapplicable. In this paper, we address the data sparsity problem in the neighbourhood-based CF methods by proposing an Adaptive-Maximum imputation method (AdaM). The basic idea is to identify an imputation area that can maximize the imputation benefit for recommendation purposes, while minimizing the imputation error brought in. To achieve the maximum imputation benefit, the imputation area is determined from both the user and the item perspectives; to minimize the imputation error, there is at least one real rating preserved for each item in the identified imputation area. A theoretical analysis is provided to prove that the proposed imputation method outperforms the conventional neighbourhood-based CF methods through more accurate neighbour identification. Experiment results on benchmark datasets show that the proposed method significantly outperforms the other related state-of-the-art imputation-based methods in terms of accuracy.

Adam Richards: diverse comedy with some mishits

Review of Adam Richard's Gayapocalypse for the 2014 Maelbourne Comedy Festival.