Toward an optimal docking and free energy calculation scheme in ligand design with application to COX-1 inhibitors.

Cyclooxygenase-1 (COX-1) is one of the main targets of most pain-relieving pharmaceuticals. Although the enzyme is well characterized, it is known to be a difficult target for automated molecular docking and scoring. We collected from the literature a structurally diverse set of 45 nonsteroidal anti-inflammatory drugs (NSAIDs) and COX-2-selective inhibitors (coxibs) with a wide range of binding affinities for COX-1.

Computational prediction of alanine scanning and ligand binding energetics in G-protein coupled receptors.

Site-directed mutagenesis combined with binding affinity measurements is widely used to probe the nature of ligand interactions with GPCRs. Such experiments, as well as structure-activity relationships for series of ligands, are usually interpreted with computationally derived models of ligand binding modes. However, systematic approaches for accurate calculations of the corresponding binding free energies are still lacking.

Mutagenesis and computational modeling of human G-protein-coupled receptor Y2 for neuropeptide Y and peptide YY.

Neuropeptide Y and peptide YY receptor type 2 (Y2) is involved in appetite regulation and several other physiological processes. We have investigated the structure of the human Y2 receptor. Computational modeling of receptor-agonist interactions was used as a guide to design a series of receptor mutants, followed by binding assays using full-length and truncated peptide agonists and the Y2-specific antagonist BIIE0246.

Computer simulations of structure-activity relationships for HERG channel blockers.

The hERG potassium channel is of major pharmaceutical importance, and its blockade by various compounds, potentially causing serious cardiac side effects, is a major problem in drug development. Despite the large amounts of existing biochemical data on blockade of hERG by drugs and druglike compounds, relatively little is known regarding the structural basis of binding of blockers to the channel. Here, we have used a recently developed homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method.

Mutagenesis of human neuropeptide Y/peptide YY receptor Y2 reveals additional differences to Y1 in interactions with highly conserved ligand positions.

Neuropeptide Y (NPY) and peptide YY (PYY) share approximately 70% of their 36 amino acids and bind to the same three human receptor subtypes, Y1, Y2 and Y5, even though these receptors only share approximately 30% sequence identity. Based on our previous investigation of human Y1 we describe here a mutagenesis study of three corresponding positions in human Y2, i.e.

Toward a consensus model of the HERG potassium channel.

Malfunction of hERG potassium channels, due to inherited mutations or inhibition by drugs, can cause long QT syndrome, which can lead to life-threatening arrhythmias. A three-dimensional structure of hERG is a prerequisite to understand the molecular basis of hERG malfunction. To achieve a consensus model, we carried out an extensive analysis of hERG models based on various alignments of helix S5.

Mutagenesis and homology modeling of the Tn21 integron integrase IntI1.

Horizontal DNA transfer between bacteria is widespread and a major cause of antibiotic resistance. For logistic reasons, single or combined genes are shuttled between vectors such as plasmids and bacterial chromosomes. Special elements termed integrons operate in such shuttling and are therefore vital for horizontal gene transfer.

Combining docking, molecular dynamics and the linear interaction energy method to predict binding modes and affinities for non-nucleoside inhibitors to HIV-1 reverse transcriptase.

Docking, scoring, molecular dynamics (MD), and the linear interaction energy (LIE) method are used here to predict binding modes and affinities for a set of 43 non-nucleoside inhibitors to HIV-1 reverse transcriptase. Starting from a crystallographic structure, the binding modes of 43 inhibitors are predicted using automated docking. The Goldscore scoring function and the LIE method are then used to determine the relative binding free energies for the inhibitors.

Predicting binding modes from free energy calculations.

To produce reliable predictions of bioactive conformations is a major challenge in the field of structure-based inhibitor design and is a requirement for accurate binding free energy predictions with structure-based methods. A series of HIV-1 reverse transcriptase inhibitors was cross-docked using a non-native crystal structure that resulted in two distinct clusters of possible conformations. One of these clusters was compatible with an existing crystal structure, whereas the other displayed a flipped heterocyclic group.