Biomedical subjects

Jonas Boström

Publications and source records attributed to Jonas Boström.

5 recordsLinked to original sources

PubMed2006

Do structurally similar ligands bind in a similar fashion?

The scope of the current work is to investigate whether structurally similar ligands bind in a similar fashion by exhaustively analyzing experimental data from the protein database (PDB). The complete PDB was searched for pairs of structurally similar ligands binding to the same biological target. The binding sites of the pairs of proteins complexing structurally similar ligands were found to differ in 83% of the cases. The most recurrent structural change among the pairs involves different water molecule architecture. Side-chain movements are observed in half of the pairs, whereas backbone movements rarely occurred. However, two structurally similar ligands generally confirm a high degree of structural conservation. That is, a majority of the ligand pairs occupy the same region in the binding sites, providing support for the use of shape matching in the drug design process. We allow ourselves to draw general conclusions because our data set consists of ligands with drug-like physicochemical properties complexed to a broad spectrum of different protein classes.

Crystallography, X-Ray↗

PubMed2006

Computational chemistry-driven decision making in lead generation.

Novel starting points for drug discovery projects are generally found either by screening large collections of compounds or smaller more-focused libraries. Ideally, hundreds or even thousands of actives are initially found, and these need to be reduced to a handful of promising lead series. In several sequential steps, many actives are dropped and only some are followed up. Computational chemistry tools are used in this context to predict properties, cluster hits, design focused libraries and search for close analogues to explore the potential of hit series. At the end of hit-to-lead, the project must commit to one, or preferably a few, lead series that will be refined during lead optimization and hopefully produce a drug candidate. Striving for the best possible decision is crucial because choosing the wrong series is a costly one-way street.

Combinatorial Chemistry Techniques↗

PubMed2003

Assessing the performance of OMEGA with respect to retrieving bioactive conformations.

OMEGA is a rule-based program which rapidly generates conformational ensembles of small molecules. We have varied the parameters which control the nature of the ensembles generated by OMEGA in a statistical fashion (D-optimal) with the aim of increasing the probability of generating bioactive conformations. Thirty-six drug-like ligands from different ligand-protein complexes determined by high-resolution (< or =2.0A) X-ray crystallography have been analyzed. Statistically significant models (Q(2)> or =0.75) confirm that one can increase the performance of OMEGA by modifying the parameters. Twenty-eight of the bioactive conformations were retrieved when using a low-energy cut-off (5 kcal/mol), a low RMSD value (0.6A) for duplicate removal, and a maximum of 1000 output conformations. All of those that were not retrieved had eight or more rotatable bonds. The duplicate removal parameter was found to have the largest impact on retrieval of bioactive conformations, and the maximum number of conformations also affected the results considerably. The input conformation was found to influence the results largely because certain bond angles can prevent the bioactive conformation from being generated as a low-energy conformation. Pre-optimizing the input structures with MMFF94s improved the results significantly. We also investigated the performance of OMEGA in connection with database searching. The shape-matching program Rapid Overlay of Chemical Structures (ROCS) was used as search tool. Two multi-conformational databases were built from the MDDR database plus the 36 compounds; one large (maximum 1000 conformations/mol) and one small (maximum 100 conformations/mol). Both databases provided satisfactory results in terms of retrieval. ROCS was able to rank 35 out of 36 X-ray structures among the top 500 hits from the large database.

Algorithms↗

PubMedDate not supplied

A 3D QSAR study on a set of dopamine D4 receptor antagonists.

The molecular alignments obtained from a previously reported pharmacophore model have been employed in a three-dimensional quantitative structure-activity relationship (3D QSAR) study, to obtain a more detailed insight into the structure-activity relationships for D(2) and D(4) receptor antagonists. The frequently applied CoMFA method and the related CoMSIA method were used. Statistically significant models have been derived with these two methods, based on a set of 32 structurally diverse D(2) and D(4) receptor antagonists. The CoMSIA and the CoMFA methods produced equally good models expressed in terms of q(2) values. The predictive power of the derived models were demonstrated to be high. Graphical interpretation of the results, provided by the CoMSIA method, brings to light important structural features of the compounds related to either low- or high-affinity D(2) or D(4) antagonism. The results of the 3D QSAR studies indicate that bulky N-substituents decrease D(2) binding, whereas D(4) binding is enhanced. Electrostatically favorable and unfavorable regions exclusive to D(2) receptor binding were identified. Likewise, certain hydrogen-bond acceptors can be used to lower D(2) affinity. These observations may be exploited for the design of novel dopamine D(4) selective antagonists.

Dopamine D2 Receptor Antagonists↗

PubMedDate not supplied

MIMUMBA revisited: torsion angle rules for conformer generation derived from X-ray structures.

A method has been developed which automatically generates SMARTS patterns for four-atomic torsional fragments, searches experimental structures in the Cambridge Crystallographic Database, and obtains rules for preferred torsion angles in drug-size molecules. These rules can be used for exhaustive conformational analysis using the popular conformer generator OMEGA. This approach results in an overall improvement of quality and coverage of conformational space when comparing conformer ensembles generated by this method with results obtained by using the default OMEGA setup. In particular, the percentage of structures with at least one conformation closer than 0.5 A to the X-ray structure improves from 84% to 92% in a test set of 11 027 experimental structures from the CSD. Moreover, the average RMS distance of the closest conformation to the X-ray structure improves from 0.30 to 0.22 A.

Chemistry↗