19 resultados para Idempotent Rank
Resumo:
In this paper, we determine the lower central and derived series for the braid groups of the projective plane. We are motivated in part by the study of Fadell-Neuwirth short exact sequences, but the problem is interesting in its own right. The n-string braid groups B(n)(RP(2)) of the projective plane RP(2) were originally studied by Van Buskirk during the 1960s. and are of particular interest due to the fact that they have torsion. The group B(1)(RP(2)) (resp. B(2)(RP(2))) is isomorphic to the cyclic group Z(2) of order 2 (resp. the generalised quaternion group of order 16) and hence their lower central and derived series are known. If n > 2, we first prove that the lower central series of B(n)(RP(2)) is constant from the commutator subgroup onwards. We observe that Gamma(2)(B(3)(RP(2))) is isomorphic to (F(3) X Q(8)) X Z(3), where F(k) denotes the free group of rank k, and Q(8) denotes the quaternion group of order 8, and that Gamma(2)(B(4)(RP(2))) is an extension of an index 2 subgroup K of P(4)(RP(2)) by Z(2) circle plus Z(2). As for the derived series of B(n)(RP(2)), we show that for all n >= 5, it is constant from the derived subgroup onwards. The group B(n)(RP(2)) being finite and soluble for n <= 2, the critical cases are n = 3, 4. We are able to determine completely the derived series of B(3)(RP(2)). The subgroups (B(3)(RP(2)))((1)), (B(3)(RP(2)))((2)) and (B(3)(RP(2)))((3)) are isomorphic respectively to (F(3) x Q(8)) x Z(3), F(3) X Q(8) and F(9) X Z(2), and we compute the derived series quotients of these groups. From (B(3)(RP(2)))((4)) onwards, the derived series of B(3)(RP(2)), as well as its successive derived series quotients, coincide with those of F(9). We analyse the derived series of B(4)(RP(2)) and its quotients up to (B(4)(RP(2)))((4)), and we show that (B(4)(RP(2)))((4)) is a semi-direct product of F(129) by F(17). Finally, we give a presentation of Gamma(2)(B(n)(RP(2))). (C) 2011 Elsevier Inc. All rights reserved.
Resumo:
Using Sigma theory we show that for large classes of groups G there is a subgroup H of finite index in Aut(G) such that for phi is an element of H the Reidemeister number R(phi) is infinite. This includes all finitely generated nonpolycyclic groups G that fall into one of the following classes: nilpotent-by-abelian groups of type FP(infinity); groups G/G `` of finite Prufer rank; groups G of type FP(2) without free nonabelian subgroups and with nonpolycyclic maximal metabelian quotient; some direct products of groups; or the pure symmetric automorphism group. Using a different argument we show that the result also holds for 1-ended nonabelian nonsurface limit groups. In some cases, such as with the generalized Thompson`s groups F(n,0) and their finite direct products, H = Aut(G).
Resumo:
A myriad of methods are available for virtual screening of small organic compound databases. In this study we have successfully applied a quantitative model of consensus measurements, using a combination of 3D similarity searches (ROCS and EON), Hologram Quantitative Structure Activity Relationships (HQSAR) and docking (FRED, FlexX, Glide and AutoDock Vina), to retrieve cruzain inhibitors from collected databases. All methods were assessed individually and then combined in a Ligand-Based Virtual Screening (LBVS) and Target-Based Virtual Screening (TBVS) consensus scoring, using Receiving Operating Characteristic (ROC) curves to evaluate their performance. Three consensus strategies were used: scaled-rank-by-number, rank-by-rank and rank-by-vote, with the most thriving the scaled-rank-by-number strategy, considering that the stiff ROC curve appeared to be satisfactory in every way to indicate a higher enrichment power at early retrieval of active compounds from the database. The ligand-based method provided access to a robust and predictive HQSAR model that was developed to show superior discrimination between active and inactive compounds, which was also better than ROCS and EON procedures. Overall, the integration of fast computational techniques based on ligand and target structures resulted in a more efficient retrieval of cruzain inhibitors with desired pharmacological profiles that may be useful to advance the discovery of new trypanocidal agents.
2D QSAR and similarity studies on cruzain inhibitors aimed at improving selectivity over cathepsin L
Resumo:
Hologram quantitative structure-activity relationships (HQSAR) were applied to a data set of 41 cruzain inhibitors. The best HQSAR model (Q(2) = 0.77; R-2 = 0.90) employing Surflex-Sim, as training and test sets generator, was obtained using atoms, bonds, and connections as fragment distinctions and 4-7 as fragment size. This model was then used to predict the potencies of 12 test set compounds, giving satisfactory predictive R-2 value of 0,88. The contribution maps obtained from the best HQSAR model are in agreement with the biological activities of the study compounds. The Trypanosoma cruzi cruzain shares high similarity with the mammalian homolog cathepsin L. The selectivity toward cruzam was checked by a database of 123 compounds, which corresponds to the 41 cruzain inhibitors used in the HQSAR model development plus 82 cathepsin L inhibitors. We screened these compounds by ROCS (Rapid Overlay of Chemical Structures), a Gaussian-shape volume overlap filter that can rapidly identify shapes that match the query molecule. Remarkably, ROCS was able to rank the first 37 hits as being only cruzain inhibitors. In addition, the area under the curve (AUC) obtained with ROCS was 0.96, indicating that the method was very efficient to distinguishing between cruzain and cathepsin L inhibitors. (c) 2007 Elsevier Ltd. All rights reserved.