The discussion is converging, but let me clarify a few points. I suspect that a new generation of crystallographers has come to the fore since the last material discussions of real-space refinement in the mid 1990's. So with apologies to the grey-haired (like me) set who may find the following condescending...
Fourier transform theory and the experience of Jack/Levitt led to the argument that real- and reciprocal- space refinements were formally equivalent. It can be true, but is only an approximation under the conditions of practical refinements. *Close to convergence*, the approximation is better - reciprocal space refinement is better without the implicit real-space restraint to the current phases. Improvements such as sigmaA, maximum likelihood etc. have extended the domain where reciprocal space is better, but the trade-offs depend on data, model quality. The term real-space refinement is commonly used for two different proceedures. In "true" real space refinement, model density is matched to experimental density directly. In what is also called real-space refinement, but should more properly be called pseudo-real-space refinement, the refinement is actually performed in reciprocal space, either by matching model and experimental structure factor vectors or by adding explicit phase restraints. As hopefully evident below, pseudo-real-space refinement has only 1/2 the advantages of true real-space refinement. The "real" value of real-space refinement is in reducing over-fitting & avoiding false minima, challenges that loom bigger earlier in refinement. Real-space refinement can do this in two ways: 1. Increased restraints from experimental phase information. Note that this is no longer an advantage at stages of refinement when experimental phase information has been (completely) discarded. Both true and pseudo real-space methods can use phase information. Pseudo real-space methods can have an advantage in that the phase information can be weighted differently from the amplitude information. 2. Localizing refinement. As Brunger's group showed, much over-fitting results from mutually compensating errors / omissions from different parts of a structure. True real-space refinement avoids this, because the optimization is against local density values, not structure factors dependent on the entire structure. Pseudo real-space refinement is just as susceptible to over-fitting errors as reciprocal-space refinement, because both are "global" refinements. One could say that we all alternate real-space and reciprocal-space refinements with our alternated rebuilds / refinements. Early in refinement or at low resolution, automated real-space improvement is a worthwhile additional step. Over-fitting on reciprocal-space refinement is much less with a starting R=0.35 model than the R>0.45 that I'm capable of by manual building. There are several programs that can be used for this real-space refinement. They differ in model parameterization: all atom and/or rigid fragment; cartesian vs. torsion angle; optimization method; objective function: true vs. pseudo; Gaussian atoms vs. resolution-dependent form factor calculation. In many cases, these distinctions may not be critical, and convenience of use may drive the decision of which to use. At lower resolution and with crude initial models it may be important to use a "full-feature" implementation, such as RSRef which can combine real-space refinement with the reduced parameter Rice/Brunger torsion angle SA/CG optimizer in CNS/X-plor. Bottom line messages: 1. Real-space refinement is usually a worthwhile prelude to reciprocal-space refinement. (Importance tends to rise with the difficulty of structure determination...) 2. "Real-space refinement" is a term used loosely. Dig deeper to understand the algorithms in use in your favorite programs, and make an appropriate selection based on your task at hand. Michael. Michael S. Chapman, R.T. Jones Professor of Structural Biology Dept. Biochemistry & Molecular Biology; School of Medicine, Mail Code L224 Oregon Health & Science University 3181 Sam Jackson Park Road; Portland, OR 97239-3098 [EMAIL PROTECTED] / (503) 494-1025; http://xtal.ohsu.edu/
