Biomedical subjects

J Marelius

Publications and source records attributed to J Marelius.

7 recordsLinked to original sources

PubMed2001

Computational modelling of inhibitor binding to human thrombin.

Thrombin is an essential protein involved in blood clot formation and an important clinical target, since disturbances of the coagulation process cause serious cardiovascular diseases such as thrombosis. Here we evaluate the performance of a molecular dynamics based method for predicting the binding affinities of different types of human thrombin inhibitors. For a series of eight ligands the method ranks their relative affinities reasonably well. The binding free energy difference between high and low affinity representatives in the test set is quantitatively reproduced, as well as the stereospecificity for a chiral inhibitor. The original parametrisation of this linear interaction energy method requires the addition of a constant energy term in the case of thrombin. This yields a mean unsigned error of 0.68 kcal/mol for the absolute binding free energies. This type of approach is also useful for elucidating three-dimensional structure-activity relationships in terms of microscopic interactions of the ligands with the solvated enzyme.

Antithrombins↗

PubMed2001

Sensitivity of an empirical affinity scoring function to changes in receptor-ligand complex conformations.

A combination of empirical scoring and conformational sampling for ligand binding affinity prediction is examined. The behaviour of a scoring function with respect to the sensitivity to conformational changes is investigated using ensembles of structures generated by molecular dynamics simulation. The correlation between the calculated score and the coordinate deviation from the experimental structure is clear for the complex of arabinose with arabinose-binding protein, which is dominated by hydrogen bond interactions, while the score calculated for the hydrophobic complex between retinol and retinol binding protein is rather insensitive to ligand conformational changes. For typical ensembles of structures generated by molecular dynamics at 300 K, the variation of the calculated score is considerably smaller than that of the underlying molecular mechanics interaction energies.

Algorithms↗

PubMed2001

The linear interaction energy method for predicting ligand binding free energies.

An overview of the simplified linear interaction energy (LIE) method for calculation of ligand binding free energies is given. This method is based on force field estimations of the receptor-ligand interactions and thermal conformational sampling. A notable feature is that the binding energetics can be predicted by considering only the intermolecular interactions between the ligand and receptor. The approximations behind this approach are examined and different parametrizations of the model are discussed. In general, LIE type of methods appear particularly useful for computational drug lead optimization.

Humans↗

PubMed2000

Computational predictions of binding affinities to dihydrofolate reductase: synthesis and biological evaluation of methotrexate analogues.

The relative binding affinities to human dihydrofolate reductase of four new potential antifolates, containing ester linkages between the two aromatic systems, were estimated by free energy perturbation simulations. The ester analogue, predicted to exhibit the highest binding affinity to human dihydrofolate reductase, and a reference ester (more structurally related to methotrexate) were synthesized. As deduced from the measured IC(50) values, the calculated ranking of the ligands was correct although a greater difference in affinity was indicated by the experimental measurements. Among the new antifolates the most potent inhibitor exhibited a similar pharmacokinetic profile to methotrexate but lacked activity in a complex antiarthritic model in rat in vivo.

Animals↗

PubMed1998

Computation of affinity and selectivity: binding of 2,4-diaminopteridine and 2,4-diaminoquinazoline inhibitors to dihydrofolate reductases.

Binding energy calculations for complexes of mutant and wild-type human dihydrofolate reductases with 2,4-diaminopteridine and 2,4-diaminoquinazoline inhibitors are reported. Quantitative insight into binding energetics of these molecules is obtained from calculations based on force field energy evaluation and thermal sampling by molecular dynamics simulations. The calculated affinity of methotrexate for wild-type and mutant enzymes is reasonably well reproduced. Truncation of the methotrexate glutamate tail results in a loss of affinity by several orders of magnitude. No major difference in binding strength is predicted between the pteridines and the quinazolìnes, while the N-methyl group present in methotrexate appears to confer significantly stronger binding. The recent improvement, which is used here, of our linear interaction energy method for binding affinity prediction, as well as problems with treating charged and flexible ligands are discussed. This approach should be suitable in a drug discovery context for prediction of binding energies of new inhibitors prior to their synthesis, when some information about the binding mode is available.

Computer Simulation↗

PubMed1998

Ligand binding affinity prediction by linear interaction energy methods.

A recent method for estimating ligand binding affinities is extended. This method employs averages of interaction potential energy terms from molecular dynamics simulations or other thermal conformational sampling techniques. Incorporation of systematic deviations from electrostatic linear response, derived from free energy perturbation studies, into the absolute binding free energy expression significantly enhances the accuracy of the approach. This type of method may be useful for computational prediction of ligand binding strengths, e.g., in drug design applications.

Binding Sites↗

PubMedDate not supplied

Q: a molecular dynamics program for free energy calculations and empirical valence bond simulations in biomolecular systems.

A new molecular dynamics program for free energy calculations in biomolecular systems is presented. It is principally designed for free energy perturbation simulations, empirical valence bond calculations, and binding affinity estimation by linear interaction energy methods. Evaluation of ligand-binding selectivity and free energy profiles for nucleophile activation in two protein tyrosine phosphatases as well as absolute binding affinity estimation for a lysine-binding protein are given as examples.

Algorithms↗