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**Molecular Design and Process Optimization**
***Biological Applications of Quantum Chemistry*
Ab initio quantum mechanical methods are being developed for  massively parallel computing systems. Unlike empirical force field  (or molecular mechanics) or semi-empirical methods, ab initio  methodsare not parameterized and therefore can be used to describe  previously unknown chemical substanceswith a good degree of  accuracy.  Because they are computationally intensive, to date these  methodshave been applied to small chemical systems that generally  have fewer than 30 atoms.  Systems ofbiological interest usually  have more than 100 atoms and will require the gigaflops speed of massively parallel systems. 
The Hartree-Fock Self-Consistent Field (SCF) approximation to the  time-dependent Schroedingerequation has been implemented on a  MIMD distributed memory parallel system.  The computational bottleneck is in calculating a large number of integrals, saving the  large data set of results ondisk, and reading a subset of the data at  every iteration in the approximation.  The alternativedirect SCF  method that recalculates a smaller number of integrals at each  iteration and saves theresults in memory lends itself to  parallelization.  A new "mpqc" software and its underlying library written in C perform direct method calculations.  One feature of the  library is that matrices aredistributed across the processors,  eliminating the restriction on matrix size to the size of a processor's memory. 
The mpqc software and extensions and enhancements to it are the  building blocks for optimizingmolecular geometries.  Such  geometries can be used in determining other molecular properties  and theenergy of chemical reactions.  Optimization methods written  in C++ have been implemented in mpqc. This software has been used  to optimize geometries of molecules documented in the scientific literature in 10 iterations compared with other methods that took  90 iterations or in some cases werenot converging after similar  numbers of iterations. 
This is joint work involving DCRT and Sandia National Laboratories.   Future efforts involveconverting mpqc libraries to C++ and  applications in other areas of computational chemistry. 
***Biomolecular Design*
Physical models and mathematical algorithms for numerical  simulation of biomolecular systems arebeing developed at the  University of Houston with NSF support.  The research team  combines expertisein chemistry, biophysics, biochemistry, chemical  engineering, computer science, and mathematics. 
The acetylcholinesterase dimer (AChE), partly shown in the figure below, is an enzyme responsible fordegrading the  neurotransmitter acetylcholine in species from man on down to  insects.  AChE is atarget for many commonly used drugs and toxins;  among the drugs that bind to AChE are therapeuticagents for  Alzheimer's disease, myasthenia gravis, and glaucoma.  Using  numerical simulation, asecond "back door" to the active site was  recently discovered, creating the likelihood thatsubstrates can  come in one door and exit through the other.  The Intel Touchstone  Delta at Caltechand the Intel Paragon at SDSC will now be used for  more extensive simulations that should explain howthis back door  works: what makes it open and close, and what can pass through it  and what can't. 
The computations are being done using EulerGromos, the scalable  parallel molecular dynamics softwaredeveloped at the University of  Houston.  Using 256 processors on the Delta, simulations of the full solvated dimer involving 131,653 dynamical atoms take  approximately 20 seconds per time step andrequire on the order of  50,000 time steps. 
Recent work by the team and others on data parallel programming  languages and techniques has resolvedmany of the core programming  issues for multicomputers.  The programming languages that have  beendeveloped require further refinement based on experience  gained by implementing the sophisticatednumerical algorithms the  simulations require.  Software engineering techniques have been  developedto facilitate efficient porting of several codes to both  distributed-memory and shared-memoryprocessors.  Furthermore,  at least three different parallel programming paradigms are being  used asappropriate for different applications, and in most cases  automatic translation between them can beaccomplished easily. 
http://sina.tcamc.uh.edu/tcamc****