ATP-Magnesium Coordination: Protein Structure-Based Force Field Evaluation and Corrections.

In the numerous molecular recognition and catalytic processes across biochemistry involving adenosine triphosphate (ATP), the common bioactive form is its magnesium chelate, ATP·Mg. In aqueous solution, two chelation geometries predominate, distinguished by bidentate and tridentate Mg-phosphate coordination. These are approximately isoenergetic but separated by a high energy barrier.

Calculation of binding free energies.

Molecular dynamics simulations enable access to free energy differences governing the driving force underlying all biological processes. In the current chapter we describe alchemical methods allowing the calculation of relative free energy differences. We concentrate on the binding free energies that can be obtained using non-equilibrium approaches based on the Crooks Fluctuation Theorem.

How do aminoadamantanes block the influenza M2 channel, and how does resistance develop?

The interactions between channels and their cognate blockers are at the heart of numerous biomedical phenomena. Herein, we unravel one particularly important example bearing direct pharmaceutical relevance: the blockage mechanism of the influenza M2 channel by the anti-flu amino-adamantyls (amantadine and rimantadine) and how the channel and, consequently, the virus develop resistance against them. Using both computational analyses and experimental verification, we find that amino-adamantyls inhibit M2's H(+) channel activity by electrostatic hindrance due to their positively charged amino group.

A model for the interaction between NF-kappa-B and ASPP2 suggests an I-kappa-B-like binding mechanism.

We used computational methods to study the interaction between two key proteins in apoptosis regulation: the transcription factor NF-kappa-B (NFkappaB) and the proapoptotic protein ASPP2. The C-terminus of ASPP2 contains ankyrin repeats and SH3 domains (ASPP2(ANK-SH3)) that mediate interactions with numerous apoptosis-related proteins, including the p65 subunit of NFkappaB (NFkappaB(p65)). Using peptide-based methods, we have recently identified the interaction sites between NFkappaB(p65) and ASPP2(ANK-SH3) (Rotem et al.

Structure and dynamics of the influenza A M2 channel: a comparison of three structures.

The M2 protein is an essential component of the Influenza virus' infectivity cycle. It is a homo-tetrameric bundle forming a pH-gated H(+) channel. The structure of M2 was solved by three different groups, using different techniques, protein sequences and pH environment.

pH-driven helix rotations in the influenza M2 H+ channel: a potential gating mechanism.

The pH activated M2 H(+) channel from influenza A has been a subject of numerous studies due to following: (1) It serves as a target for the aminoadamantane drugs that block its channel activity. (2) M2's small size makes it amenable to biophysical scrutiny. (3) A single histidine residue is thought to control the pH gating of the channel.

Gating mechanism of the influenza A M2 channel revealed by 1D and 2D IR spectroscopies.

The pH-controlled M2 protein from influenza A is a critical component of the virus and serves as a target for the aminoadamantane antiflu agents that block its H+ channel activity. To better understand its H+ gating mechanism, we investigated M2 in lipid bilayers with a new combination of IR spectroscopies and theory. Linear Fourier transform infrared (FTIR) spectroscopy was used to measure the precise orientation of the backbone carbonyl groups, and 2D infrared (IR) spectroscopy was used to identify channel-lining residues.

Modeling membrane proteins utilizing information from silent amino acid substitutions.

This unit describes predicting the structure of simple transmembrane alpha-helical bundles. The protocol is based on a global molecular dynamics search (GMDS) of the configuration space of the helical bundle, yielding several candidates structures. The correct structure amongst these candidates is selected using information from silent amino acid substitutions, employing the following premise: Only the correct structure must (by definition) accept all of the silent amino acid substitutions.

Genetic algorithm-based optimization of hydrophobicity tables.

The genomic abundance and pharmacological importance of membrane proteins have fueled efforts to identify them based solely on sequence information. Previous methods based on the physicochemical principle of a sliding window of hydrophobicity (hydropathy analysis) have been replaced by approaches based on hidden Markov models or neural networks which prevail due to their probabilistic orientation. In the current study, an optimization of the hydrophobicity tables used in hydropathy analysis is performed using a genetic algorithm.

A periodicity analysis of transmembrane helices.

Transmembrane helices and the helical bundles which they form are the major building blocks of membrane proteins. Since helices are characterized by a given periodicity, it is possible to search for patterns of traits which typify one side of the helix and not the other (e.g.

Modeling the structure of the respiratory syncytial virus small hydrophobic protein by silent-mutation analysis of global searching molecular dynamics.

Human respiratory syncytial virus (RSV) encodes a small hydrophobic (SH) protein, whose function in the life cycle of the virus is unknown. Recent channel activity measurements of the protein suggest that like other viroporins, SH may assemble into a homo-oligomeric ion channel. To further our understanding of this potentially important protein, a new strategy was implemented in order to model the transmembrane oligomeric bundle of the protein.

Syntaxin 1A modulates the voltage-gated L-type calcium channel (Ca(v)1.2) in a cooperative manner.

Syntaxin 1A (Sx1A) modifies the activity of voltage-gated Ca2+ channels acting via the cytosolic and the two vicinal cysteines (271 and 272) at the transmembrane domain. Here we show that Sx1A modulates the Lc-type Ca2+ channel, Cav1.2, in a cooperative manner, and we explore whether channel clustering or the Sx1A homodimer is responsible for this activity.

Monte Carlo estimation of the number of possible protein folds: effects of sampling bias and folds distributions.

The estimation of the number of protein folds in nature is a matter of considerable interest. In this study, a Monte Carlo method employing the broken stick model is used to assign a given number of proteins into a given number of folds. Subsequently, random, integer, non-repeating numbers are generated in order to simulate the process of fold discovery.