| Title |
A fast and efficient method to generate biologically relevant conformations
|
|---|---|
| Published in |
Perspectives in Drug Discovery and Design, October 1994
|
| DOI | 10.1007/bf00123667 |
| Pubmed ID | |
| Authors |
Gerhard Klebe, Thomas Mietzner |
| Abstract |
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. |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Finland | 1 | 1% |
| Unknown | 65 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 29% |
| Student > Ph. D. Student | 10 | 15% |
| Student > Master | 8 | 12% |
| Student > Bachelor | 5 | 7% |
| Professor | 3 | 4% |
| Other | 11 | 16% |
| Unknown | 11 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 27 | 40% |
| Biochemistry, Genetics and Molecular Biology | 6 | 9% |
| Agricultural and Biological Sciences | 5 | 7% |
| Computer Science | 5 | 7% |
| Physics and Astronomy | 3 | 4% |
| Other | 9 | 13% |
| Unknown | 13 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 July 2020.
All research outputs
#8,571,053
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#420
of 949 outputs
Outputs of similar age
#6,408
of 20,479 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#2
of 5 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 949 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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