Gating topology of the proton-coupled oligopeptide symporters.

Proton-coupled oligopeptide transporters belong to the major facilitator superfamily (MFS) of membrane transporters. Recent crystal structures suggest the MFS fold facilitates transport through rearrangement of their two six-helix bundles around a central ligand binding site; how this is achieved, however, is poorly understood. Using modeling, molecular dynamics, crystallography, functional assays, and site-directed spin labeling combined with double electron-electron resonance (DEER) spectroscopy, we present a detailed study of the transport dynamics of two bacterial oligopeptide transporters, PepTSo and PepTSt.

Identification of molecular hinge points mediating alternating access in the vesicular monoamine transporter VMAT2.

Vesicular monoamine transporter 2 (VMAT2) catalyzes transport of monoamines into storage vesicles in a process that involves exchange of the charged monoamine with two protons. VMAT2 is a member of the DHA12 family of multidrug transporters that belongs to the major facilitator superfamily (MFS) of secondary transporters. Here we present a homology model of VMAT2, which has the standard MFS fold, that is, with two domains of six transmembrane helices each which are related by twofold pseudosymmetry and whose axis runs normal to the membrane and between the two halves.

Constraint Network Analysis (CNA): a Python software package for efficiently linking biomacromolecular structure, flexibility, (thermo-)stability, and function.

For deriving maximal advantage from information on biomacromolecular flexibility and rigidity, results from rigidity analyses must be linked to biologically relevant characteristics of a structure. Here, we describe the Python-based software package Constraint Network Analysis (CNA) developed for this task. CNA functions as a front- and backend to the graph-based rigidity analysis software FIRST.

Global and local indices for characterizing biomolecular flexibility and rigidity.

Understanding flexibility and rigidity characteristics of biomolecules is a prerequisite for understanding biomolecular structural stability and function. Computational methods have been implemented that directly characterize biomolecular flexibility and rigidity by constraint network analysis. For deriving maximal advantage from these analyses, their results need to be linked to biologically relevant characteristics of a structure.

Thermostabilizing mutations preferentially occur at structural weak spots with a high mutation ratio.

We apply Constraint Network Analysis (CNA) to investigate the relationship between structural rigidity and thermostability of five citrate synthase (CS) structures over a temperature range from 37 °C to 100 °C. For the first time, we introduce an ensemble-based variant of CNA and model the temperature-dependence of hydrophobic interactions in the constraint network. A very good correlation between the predicted thermostabilities of CS and optimal growth temperatures of their source organisms (R²=0.

The alternating-access mechanism of MFS transporters arises from inverted-topology repeats.

Lactose permease (LacY) is the prototype of the major facilitator superfamily (MFS) of secondary transporters. Available structures of LacY reveal a state in which the substrate is exposed to the cytoplasm but is occluded from the periplasm. However, the alternating-access transport mechanism requires the existence of a periplasm-facing state.

Protein rigidity and thermophilic adaptation.

We probe the hypothesis of corresponding states, according to which homologues from mesophilic and thermophilic organisms are in corresponding states of similar rigidity and flexibility at their respective optimal temperatures. For this, the local distribution of flexible and rigid regions in 19 pairs of homologous proteins from meso- and thermophilic organisms is analyzed and related to activity characteristics of the enzymes by constraint network analysis (CNA). Two pairs of enzymes are considered in more detail: 3-isopropylmalate dehydrogenase and thermolysin-like protease.

Homology model-based virtual screening for GPCR ligands using docking and target-biased scoring.

The current study investigates the combination of two recently reported techniques for the improvement of homology model-based virtual screening for G-protein coupled receptor (GPCR) ligands. First, ligand-supported homology modeling was used to generate receptor models that were in agreement with mutagenesis data and structure-activity relationship information of the ligands. Second, interaction patterns from known ligands to the receptor were applied for scoring and rank ordering compounds from a virtual library using ligand-receptor interaction fingerprint-based similarity (IFS).

Maximum common binding modes (MCBM): consensus docking scoring using multiple ligand information and interaction fingerprints.

Improving the scoring functions for small molecule-protein docking is a highly challenging task in current computational drug design. Here we present a novel consensus scoring concept for the prediction of binding modes for multiple known active ligands. Similar ligands are generally believed to bind to their receptor in a similar fashion.

Improving binding mode predictions by docking into protein-specifically adapted potential fields.

The development of a protein-specifically adapted objective function for docking is described. Structural and energetic information about known protein-ligand complexes is exploited to tailor knowledge-based potentials using a "reverse", protein-based CoMFA-type (=AFMoC) approach. That way, effects due to protein flexibility and information about multiple solvation schemes can be implicitly incorporated.