The investigation of the reduction mechanism of the 5a-reductase enzyme of Penicillium decumbens /

The 5a-reductase of Penicillium decumbens ATCC 10436 was used as a model for the mammalian enzyme to investigate the mechanism of reduction of testosterone to 5adihydrotestosterone . The purpose of this study was to search for specific 5a-reductase inhibitors which antagonize prostate cancer . In a whole-cell biotransformation mode, this organism reduced testosterone (1) to 5a-dihydrosteroids (8) and 5aandrostane- 3, 17-dione (9) in yields of 28% and 37% respectively. Control experiments have shown that 5aandrostane- 3, 17-dione (9) can be produced from the corresponding alcohol (8) in a subsequent reaction separate from that catalysed by the 5a-reductase enzyme . Androst-4- ene-3, 17-dione (2) is reduced to give only (9) with a recovery of 80% The stereochemistry of the reduction was determined by 500 MHz ^H NMR analysis of the products resulting from the deuterium labelled substrates. The results were obtained by an analysis of the NOE difference spectra, double-quantum filtered phase sensitive COSY 2-D spectra, and ^^c-Ir 2-D shift correlation spectra of deuterium labelled products. According to the unambiguous assignment of the signals due to H-4a and H-4Ii in 5a-dihydro steroids, the NMR data show clearly that addition of hydrogen to the 4{5)K bond has occurred in a trans manner at positions 413 and 5a. To Study the reduction mechanism of this enzyme, several substrates were prepared as following; 3-methyleneandrost-4-en- 17fi-ol(3), androst-4-en-17i5-ol(5) , androst-4-en-3ii, 17fi-diol (6) and 4, 5ii-epoxyandrostane-3, 17-dione (7) . Results suggest that this enzyme system requires an oxygen atom at the 3-position of the steroid in order to bind the substrate. Furthermore, the mechanism of this 5a-reductase may proceed via direct addition of hydrogen at the 4,5 position without involvement of a carbonyl group as an intermediate.

Extracting Ramachandran torsional angle distributions from 2D NMR data using Tikhonov regularization /

Solid state nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for studying structural and dynamical properties of disordered and partially ordered materials, such as glasses, polymers, liquid crystals, and biological materials. In particular, twodimensional( 2D) NMR methods such as ^^C-^^C correlation spectroscopy under the magicangle- spinning (MAS) conditions have been used to measure structural constraints on the secondary structure of proteins and polypeptides. Amyloid fibrils implicated in a broad class of diseases such as Alzheimer's are known to contain a particular repeating structural motif, called a /5-sheet. However, the details of such structures are poorly understood, primarily because the structural constraints extracted from the 2D NMR data in the form of the so-called Ramachandran (backbone torsion) angle distributions, g{^,'4)), are strongly model-dependent. Inverse theory methods are used to extract Ramachandran angle distributions from a set of 2D MAS and constant-time double-quantum-filtered dipolar recoupling (CTDQFD) data. This is a vastly underdetermined problem, and the stability of the inverse mapping is problematic. Tikhonov regularization is a well-known method of improving the stability of the inverse; in this work it is extended to use a new regularization functional based on the Laplacian rather than on the norm of the function itself. In this way, one makes use of the inherently two-dimensional nature of the underlying Ramachandran maps. In addition, a modification of the existing numerical procedure is performed, as appropriate for an underdetermined inverse problem. Stability of the algorithm with respect to the signal-to-noise (S/N) ratio is examined using a simulated data set. The results show excellent convergence to the true angle distribution function g{(j),ii) for the S/N ratio above 100.

Optimization of trial wave functions for use in quantum Monte Carlo with application to LiH

Methods for both partial and full optimization of wavefunction parameters are explored, and these are applied to the LiH molecule. A partial optimization can be easily performed with little difficulty. But to perform a full optimization we must avoid a wrong minimum, and deal with linear-dependency, time step-dependency and ensemble-dependency problems. Five basis sets are examined. The optimized wavefunction with a 3-function set gives a variational energy of -7.998 + 0.005 a.u., which is comparable to that (-7.990 + 0.003) 1 of Reynold's unoptimized \fin ( a double-~ set of eight functions). The optimized wavefunction with a double~ plus 3dz2 set gives ari energy of -8.052 + 0.003 a.u., which is comparable with the fixed-node energy (-8.059 + 0.004)1 of the \fin. The optimized double-~ function itself gives an energy of -8.049 + 0.002 a.u. Each number above was obtained on a Bourrghs 7900 mainframe computer with 14 -15 hrs CPU time.