New surface contacts formed upon reductive lysine methylation: Improving the probability of protein crystallization

Surface lysine methylation (SLM) is a technique for improving the rate of success of protein crystallization by chemically methylating lysine residues. The exact mechanism by which SLM enhances crystallization is still not clear. To study these mechanisms, and to analyze the conditions where SLM will provide the optimal benefits for rescuing failed crystallization experiments, we compared 40 protein structures containing N,N-dimethyl-lysine (dmLys) to a nonredundant set of 18,972 nonmethylated structures from the PDB. By measuring the relative frequency of intermolecular contacts (where contacts are defined as interactions between the residues in proximity with a distance of 3.5 Å or less) of basic residues in the methylated versus nonmethylated sets, dmLys-Glu contacts are seen more frequently than Lys-Glu contacts. Based on observation of the 10 proteins with both native and methylated structures, we propose that the increased rate of contact for dmLys-Glu is due to both a slight increase in the number of amine-carboxyl H-bonds and to the formation of methyl C–H···O interactions. By comparing the relative contact frequencies of dmLys with other residues, the mechanism by which methylation of lysines improves the formation of crystal contacts appears to be similar to that of Lys to Arg mutation. Moreover, analysis of methylated structures with the surface entropy reduction (SER) prediction server suggests that in many cases SLM of predicted SER sites may contribute to improved crystallization. Thus, tools that analyze protein sequences and mark residues for SER mutation may identify proteins with good candidate sites for SLM.     

Sharing natural resources: mountain gorillas and people in the Parc National des Volcans,Rwanda

The compatibility of natural resource use by people and mountain gorillas (Gorilla beringei beringei) within the Parc National des Volcans was studied. The distribution of gorillas was modelled using a Maximum Entropy algorithm. Biophysical predictor variables were trained with daily GPS locations of gorillas during 2006. Elevation, as a climate surrogate, was the best predictor (58%) of the occurrence of gorillas. The mid‐altitudes (2500–3500 m a.s.l.) contained the bulk of the gorilla groups. Incoming solar radiation, as proxy for comfortable nesting sites, was the second best predictor (17%). Vegetation types, as foliage provider, (13%) and slope steepness for providing security (12%) were contributing predictors. The modelled and actual gorilla distributions were together overlaid with people’s resource use in the park. Both people and gorillas were congregated in the areas identified as most suitable for gorillas. However, within these areas spatial segregation was found between human natural resource‐users and gorillas. Therefore, the number of gorillas is likely to be limited by the human natural resource use within the park. A perimeter fence, the introduction of community‐based natural resource management, and a buffer zone are discussed as short‐, medium‐ and long‐term mitigation measures.     

The conformational and property space of acetylcholine bound to muscarinic receptors: an entropy component accounts for the subtype selectivity of acetylcholine

The conformational behavior of receptor-bound acetylcholine (ACh) was investigated by molecular dynamics simulations. Based on the great similarity among muscarinic receptors, the study was focused on the human M(1), M(2), and M(5) receptors as previously modeled by us. The results showed that receptor-bound ACh was not frozen in a single preferred conformation but preserved an unexpected fraction of its conformational space. However, there were marked differences between the three receptors since the ligand was mostly trans in the M(1) receptor, equally distributed among trans and gauche conformers in M(2), and exclusively gauche in the M(5); the greater flexibility of M(2)-bound ACh was paralleled by the greater flexibility of the occupied M(2) binding site. By contrast, the property space of receptor-bound ACh, and particularly its virtual (computed, conformation-dependent) lipophilicity, was restricted to relatively narrow ranges optimal for successful interaction. Experimental binding investigations to the individual human M(1), M(2), and M(5) muscarinic receptors showed ACh to have a 10-fold higher affinity for the M(2) compared to the M(1) and M(5) receptors. This selectivity was not confirmed by the calculated binding scores, a fact postulated to be caused by the absence of an entropy component in such binding scores. Indeed, the Shannon entropy of all geometric and physicochemical properties monitored were markedly higher in M(2)-bound ACh compared to M(1)-bound and M(5)-bound ACh. This finding suggests that the selectivity profile of acetylcholine for the M(2) receptor is largely entropy-driven, a fact that might explain the intrinsic difficulty to design subtype-selective muscarinic agonists.     

Toward rational protein crystallization: A Web server for the design of crystallizable protein variants

Growing well-diffracting crystals constitutes a serious bottleneck in structural biology. A recently proposed crystallization methodology for "stubborn crystallizers" is to engineer surface sequence variants designed to form intermolecular contacts that could support a crystal lattice. This approach relies on the concept of surface entropy reduction (SER), i.e., the replacement of clusters of flexible, solvent-exposed residues with residues with lower conformational entropy. This strategy minimizes the loss of conformational entropy upon crystallization and renders crystallization thermodynamically favorable. The method has been successfully used to crystallize more than 15 novel proteins, all stubborn crystallizers. But the choice of suitable sites for mutagenesis is not trivial. Herein, we announce a Web server, the surface entropy reduction prediction server (SERp server), designed to identify mutations that may facilitate crystallization. Suggested mutations are predicted based on an algorithm incorporating a conformational entropy profile, a secondary structure prediction, and sequence conservation. Minor considerations include the nature of flanking residues and gaps between mutation candidates. While designed to be used with default values, the server has many user-controlled parameters allowing for considerable flexibility. Within, we discuss (1) the methodology of the server, (2) how to interpret the results, and (3) factors that must be considered when selecting mutations. We also attempt to benchmark the server by comparing the server's predictions with successful SER structures. In most cases, the structure yielding mutations were easily identified by the SERp server. The server can be accessed at http://www.doe-mbi.ucla.edu/Services/SER.     

Quantitative delineation of how breathing motions open ligand migration channels in myoglobin and its mutants

Ligand migration and binding are central to the biological functions of many proteins such as myoglobin (Mb) and it is widely thought that protein breathing motions open up ligand channels dynamically. However, how a protein exerts its control over the opening and closing of these channels through its intrinsic dynamics is not fully understood. Specifically, a quantitative delineation of the breathing motions that are needed to open ligand channels is lacking. In this work, we present and apply a novel normal mode‐based method to quantitatively delineate what and how breathing motions open ligand migration channels in Mb and its mutants. The motivation behind this work springs from the observation that normal mode motions are closely linked to the breathing motions that are thought to open ligand migration channels. In addition, the method provides a direct and detailed depiction of the motions of each and every residue that lines a channel and can identify key residues that play a dominating role in regulating the channel. The all‐atom model and the full force‐field employed in the method provide a realistic energetics on the work cost required to open a channel, and as a result, the method can be used to efficiently study the effects of mutations on ligand migration channels and on ligand entry rates. Our results on Mb and its mutants are in excellent agreement with MD simulation results and experimentally determined ligand entry rates. Proteins 2015; 83:757–770. © 2015 Wiley Periodicals, Inc.     

Vibrational entropy differences between mesophile and thermophile proteins and their use in protein engineering

We recently introduced ENCoM, an elastic network atomic contact model, as the first coarse-grained normal mode analysis method that accounts for the nature of amino acids and can predict the effect of mutations on thermostability based on changes vibrational entropy. In this proof-of-concept article, we use pairs of mesophile and thermophile homolog proteins with identical structures to determine if a measure of vibrational entropy based on normal mode analysis can discriminate thermophile from mesophile proteins. We observe that in around 60% of cases, thermophile proteins are more rigid at equivalent temperatures than their mesophile counterpart and this difference can guide the design of proteins to increase their thermostability through series of mutations. We observe that mutations separating thermophile proteins from their mesophile orthologs contribute independently to a decrease in vibrational entropy and discuss the application and implications of this methodology to protein engineering.