An investigation into the construction of molecular models by the template joining method

163

122

Mutual binding between a ligand of low molecular weight and its macromolecular receptor demands structural complementarity of both species at the recognition site. To predict binding properties of new molecules before synthesis, information about possible conformations of drug molecules at the active site is required, especially if the 3D structure of the receptor is not known. The statistical analysis of small-molecule crystal data allows one to elucidate conformational preferences of molecular fragments and accordingly to compile libraries of putative ligand conformations. A comparison of geometries adopted by corresponding fragments in ligands bound to proteins shows similar distributions in conformations space. We have developed an automatic procedure that generates different conformers of a given ligand. The entire molecule is decomposed into its individual ring and open-chain torsional fragments, each used in a variety of favorable conformations. The latter ones are produced according to the library information about conformational preferences. During this building process, an extensive energy ranking is applied. Conformers ranked as energetically favorable are subjected to an optimization in torsion angle space. During minimization, unfavorable van der Waals interactions are removed while keeping the open-chain torsion angles as close as possible to the experimentally most frequently observed values. In order to assess how well the generated conformers map conformation space, a comparison with experimental data has been performed. This comparison gives some confidence in the efficiency and completeness of this approach. For some ligands that had been structurally characterized by protein crystallography the program was used to generate sets of some 10 to 100 conformers. Among these, geometries are found that fall convincingly close to the conformations actually adopted by these ligands at the binding site.

Section: Discussionmentioning

confidence: 99%

A fast and efficient method to generate biologically relevant conformations

Klebe

Mietzner

1994

163

122

“…For example, in the entity connectivity graph in Fig. 9 the order in which the entities are joined would be [1,2,5,9,10,3,6,4,7,11,8]. The entity sequence is then converted into the equivalent unit join-order list, ensuring that each unit always adjoins at least one previous unit in the list.…”

Section: Resultsmentioning

confidence: 99%

“…The goal-generati'on algorithm is used to produce successive high-level suggestions in which each unit is assigned a symbolic subconformation. The construction algorithm takes a high-level suggestion and uses the joining algorithms [2] to build the 3-dimensional conformation it represents.…”

Section: The Initial Algorithms Used To Search Conformational Spacementioning

confidence: 99%

Automated conformational analysis: Algorithms for the efficient construction of low-energy conformations

Leach¹,

Prout²,

Dolata³

1990

Self Cite

The method of constructing low-energy conformations using template joining can provide an efficient means of searching the conformational space of molecules. The simplest algorithm to perform this task would construct each potential conformation from scratch. However, new algorithms, some of which use techniques from Artificial Intelligence, have been developed which can greatly improve the efficiency of this approach.

“…The ring-generation algorithm currently used by BUILDER v.2 is straightforward. More sophisticated algorithms [45] have been developed that can generate complicated multi-ring systems. However, since the goal of BUILDER is to try to keep the connecting groups reasonably accessible to synthesis, a simpler plan was employed.…”

Section: Final Adjustmentsmentioning

confidence: 99%

BUILDER v.2: Improving the chemistry of a de novo design strategy

Roe

Kuntz

1995

Significant improvements have been made to the de novo drug design program BUILDER. The BUILDER strategy is to find molecule templates that bind tightly to 'hot spots' in the target receptor, and then generate bridges to join these templates. In this paper, the bridging algorithm has been further developed to improve the chemical sense and diversity of the bridges, as well as the robustness of the technique. The improved algorithm is then applied to rebuild known bridges in methotrexate and HIV protease. Finally, the entire BUILDER approach is tested by rebuilding methotrexate de novo.