Directed tweak

An important extension to rigid-body fitting is the so-called directed tweak technique [105]. Directed tweak allows for an RMS fit, simultaneously considering the molecular flexibility. By the use of local coordinates for the handling of rotatable bonds, it is possible to formulate analytical derivatives of the objective function. With a gradient-based local optimizer flexible RMS fits are obtained extremely fast. However, no torsional preferences may be introduced. Therefore, directed tweak may result in energetically unfavorable conformations. 

Hurst, T. Flexible 3D searching the directed tweak technique. /. Chem. Inf. Comput. Sci. 1994, 34, 190-196. 

Another optimization method, related to the least-squares fitting used in point-based algorithms, is the directed tweak method [31]. This is a torsional space optimizer, in which the rotatable bonds of the ligands are adjusted at search time to produce a conformation which matches the 3D query as closely as possible. As directed tweak involves the use of analytical derivatives, it is very fast and allows for an RMS fit to consider ligand flexibility. 

Alignment methods are also known to combine different optimization methods, such as a genetic algorithm and a directed tweak method [36]. 

Hurst, T. 1994. Flexible 3D searching The Directed Tweak technique. J Chem Inf Comput Sci 34 190-6. 

Clark et al. - also compared the GA with distance geometry, directed tweak, and random search methods on the problem of finding good phar-macaphoric matches in databases df thousands of molecules. Their final conclusion is that GA and directed tweak outperform all of the methods, and that the directed tweak may in fact be preferable to GA, as mentioned earlier in this chapter. 

ChemDBS-3D uses rule-based systematic conformational analysis (single = 3, alpha 4, double/conjugated = 2 points) or random rule-based (max. time 2 min), or flexifit (no VDW bump check) ISIS/3D and UNITY use torsional minimization (conformationally flexible searching and directed tweak, respectively. 

Methods that combine a search technique with other optimization approaches include distance geometry, random search, and genetic algorithms. A comparison of these methods with derivative-based optimization concluded that all were inferior in performance to directed tweak, with the most favorable of the three being the genetic algorithm. ... 

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