Developing a move-set for protein model refinement

Efficient rational modification of non-ribosomal peptides by adenylation domain substitution

Non-ribosomal peptide synthetase (NRPS) enzymes form modular assembly-lines, wherein each module governs the incorporation of a specific monomer into a short peptide product. Modules are comprised of one or more key domains, including adenylation (A) domains, which recognise and activate the monomer substrate; condensation (C) domains, which catalyse amide bond formation; and thiolation (T) domains, which shuttle reaction intermediates between catalytic domains. This arrangement offers prospects for rational peptide modification via substitution of substrate-specifying domains. For over 20 years, it has been considered that C domains play key roles in proof-reading the substrate; a presumption that has greatly complicated rational NRPS redesign. Here we present evidence from both directed and natural evolution studies that any substrate-specifying role for C domains is likely to be the exception rather than the rule, and that novel non-ribosomal peptides can be generated by substitution of A domains alone. We identify permissive A domain recombination boundaries and show that these allow us to efficiently generate modified pyoverdine peptides at high yields. We further demonstrate the transferability of our approach in the PheATE-ProCAT model system originally used to infer C domain substrate specificity, generating modified dipeptide products at yields that are inconsistent with the prevailing dogma.

Crystal structure of a xylulose 5-phosphate phosphoketolase. Insights into the substrate specificity for xylulose 5-phosphate

Phosphoketolases (PK) are TPP-dependent enzymes which play essential roles in carbohydrate metabolism of numerous bacteria. Depending on the substrate specificity PKs can be subdivided into xylulose 5-phosphate (X5P) specific PKs (XPKs) and PKs which accept both X5P and fructose 6-phosphate (F6P) (XFPKs). Despite their key metabolic importance, so far only the crystal structures of two XFPKs have been reported. There are no reported structures for any XPKs and for any complexes between PK and substrate. One of the major unknowns concerning PKs mechanism of action is related to the structural determinants of PKs substrate specificity for X5P or F6P. We report here the crystal structure of XPK from Lactococcus lactis (XPK-Ll) at 2.1 Å resolution. Using small angle X-ray scattering (SAXS) we proved that XPK-Ll is a dimer in solution. Towards better understanding of PKs substrate specificity, we performed flexible docking of TPP-X5P and TPP-F6P on crystal structures of XPK-Ll, two XFPKs and transketolase (TK). Calculated structure-based binding energies consistently support XPK-Ll preference for X5P. Analysis of structural models thus obtained show that substrates adopt moderately different conformation in PKs active sites following distinct networks of polar interactions. Based on the here reported structure of XPK-Ll we propose the most probable amino acid residues involved in the catalytic steps of reaction mechanism. Altogether our results suggest that PKs substrate preference for X5P or F6P is the outcome of a fine balance between specific binding network and dissimilar catalytic residues depending on the enzyme (XPK or XFPK) - substrate (X5P or F6P) couples.

Evolution-Guided Structural and Functional Analyses of the HERC Family Reveal an Ancient Marine Origin and Determinants of Antiviral Activity

In humans, homologous to the E6-AP carboxyl terminus (HECT) and regulator of chromosome condensation 1 (RCC1)-like domain-containing protein 5 (HERC5) is an interferon-induced protein that inhibits replication of evolutionarily diverse viruses, including human immunodeficiency virus type 1 (HIV-1). To better understand the origin, evolution, and function of HERC5, we performed phylogenetic, structural, and functional analyses of the entire human small-HERC family, which includes HERC3, HERC4, HERC5, and HERC6. We demonstrated that the HERC family emerged >595 million years ago and has undergone gene duplication and gene loss events throughout its evolution. The structural topology of the RCC1-like domain and HECT domains from all HERC paralogs is highly conserved among evolutionarily diverse vertebrates despite low sequence homology. Functional analyses showed that the human small HERCs exhibit different degrees of antiviral activity toward HIV-1 and that HERC5 provides the strongest inhibition. Notably, coelacanth HERC5 inhibited simian immunodeficiency virus (SIV), but not HIV-1, particle production, suggesting that the antiviral activity of HERC5 emerged over 413 million years ago and exhibits species- and virus-specific restriction. In addition, we showed that both HERC5 and HERC6 are evolving under strong positive selection, particularly blade 1 of the RCC1-like domain, which we showed is a key determinant of antiviral activity. These studies provide insight into the origin, evolution, and biological importance of the human restriction factor HERC5 and the other HERC family members.

IMPORTANCE Intrinsic immunity plays an important role as the first line of defense against viruses. Studying the origins, evolution, and functions of proteins responsible for effecting this defense will provide key information about virus-host relationships that can be exploited for future drug development. We showed that HERC5 is one such antiviral protein that belongs to an evolutionarily conserved family of HERCs with an ancient marine origin. Not all vertebrates possess all HERC members, suggesting that different HERCs emerged at different times during evolution to provide the host with a survival advantage. Consistent with this, two of the more recently emerged HERC members, HERC5 and HERC6, displayed strong signatures of having been involved in an ancient evolutionary battle with viruses. Our findings provide new insights into the evolutionary origin and function of the HERC family in vertebrate evolution, identifying HERC5 and possibly HERC6 as important effectors of intrinsic immunity in vertebrates.

Expanding the frontiers of protein-protein modeling: from docking and scoring to binding affinity predictions and other challenges

In addition to protein-protein docking, this CAPRI edition included new challenges, like protein-water and protein-sugar interactions, or the prediction of binding affinities and ΔΔG changes upon mutation. Regarding the standard protein-protein docking cases, our approach, mostly based on the pyDock scheme, submitted correct models as predictors and as scorers for 67% and 57% of the evaluated targets, respectively. In this edition, available information on known interface residues hardly made any difference for our predictions. In one of the targets, the inclusion of available experimental small-angle X-ray scattering (SAXS) data using our pyDockSAXS approach slightly improved the predictions. In addition to the standard protein-protein docking assessment, new challenges were proposed. One of the new problems was predicting the position of the interface water molecules, for which we submitted models with 20% and 43% of the water-mediated native contacts predicted as predictors and scorers, respectively. Another new problem was the prediction of protein-carbohydrate binding, where our submitted model was very close to being acceptable. A set of targets were related to the prediction of binding affinities, in which our pyDock scheme was able to discriminate between natural and designed complexes with area under the curve = 83%. It was also proposed to estimate the effect of point mutations on binding affinity. Our approach, based on machine learning methods, showed high rates of correctly classified mutations for all cases. The overall results were highly rewarding, and show that the field is ready to move forward and face new interesting challenges in interactomics.

CONSTANT TIME CLASH DETECTION IN PROTEIN FOLDING

Applications for the manipulation of molecular structures are usually computationally intensive. Problems like protein docking or ab-initio protein folding need to frequently determine if two atoms in the structure collide. Therefore, an efficient algorithm for this problem, usually referred as clash detection, can greatly improve the application efficiency. This work focus mainly on the ab-initio protein folding problem. A naive approach for the clash problem, the most commonly-used by molecular structure programs, consists in calculating the distance between every pair of atoms. We propose an efficient data structure that uses a three-dimensional array to store the atoms' position. We compare the proposed data structure with one of the best known general data structures for this type of problems (SAT tree) and with the naive approach. While the naive approach takes linear time to the number of atoms to verify if a new atom clashes with any previously-set atoms, the proposed data structure takes constant time to perform the same verification. The SAT tree takes logarithmic time for the same task. The results show that the proposed data structure surpasses the other techniques for any protein size. The proposed data structure takes near half of the time of the SAT data structure and close to a fifth of the time of the naive approach for the larger proteins. We believe that this data structure can improve the existing molecular structure applications by decreasing the computational cost needed for clash detection. The data structure presented in this work can be used for any protein structure clash verification, as long as the atoms that need to be checked are kept in the 3D array. This data structure is particulary useful when manipulating large sets of atoms, for example, in applications like loop prediction, structure refinement of large proteins, and protein docking.

Rational engineering of L-asparaginase reveals importance of dual activity for cancer cell toxicity

Using proteins in a therapeutic context often requires engineering to modify functionality and enhance efficacy. We have previously reported that the therapeutic antileukemic protein macromolecule Escherichia coli L-asparaginase is degraded by leukemic lysosomal cysteine proteases. In the present study, we successfully engineered L-asparaginase to resist proteolytic cleavage and at the same time improve activity. We employed a novel combination of mutant sampling using a genetic algorithm in tandem with flexibility studies using molecular dynamics to investigate the impact of lid-loop and mutations on drug activity. Applying these methods, we successfully predicted the more active L-asparaginase mutants N24T and N24A. For the latter, a unique hydrogen bond network contributes to higher activity. Furthermore, interface mutations controlling secondary glutaminase activity demonstrated the importance of this enzymatic activity for drug cytotoxicity. All selected mutants were expressed, purified, and tested for activity and for their ability to form the active tetrameric form. By introducing the N24A and N24A R195S mutations to the drug L-asparaginase, we are a step closer to individualized drug design.

Molecular basis of reduced glucosylceramidase activity in the most common Gaucher disease mutant, N370S

Gaucher disease is caused by the defective activity of the lysosomal hydrolase, glucosylceramidase. Although the x-ray structure of wild type glucosylceramidase has been resolved, little is known about the structural features of any of the >200 mutations. Various treatments for Gaucher disease are available, including enzyme replacement and chaperone therapies. The latter involves binding of competitive inhibitors at the active site to enable correct folding and transport of the mutant enzyme to the lysosome. We now use molecular dynamics, a set of structural analysis tools, and several statistical methods to determine the flexible behavior of the N370S Gaucher mutant at various pH values, with and without binding the chaperone, N-butyl-deoxynojirimycin. We focus on the effect of the chaperone on the whole protein, on the active site, and on three important structural loops, and we demonstrate how the chaperone modifies the behavior of N370S in such a way that it becomes more active at lysosomal pH. Our results suggest a mechanism whereby the binding of N-butyl-deoxynojirimycin helps target correctly folded glucosylceramidase to the lysosome, contributes to binding with saposin C, and explains the initiation of the substrate-enzyme complex. Such analysis provides a new framework for determination of the structure of other Gaucher disease mutants and suggests new approaches for rational drug design.

Alternating evolutionary pressure in a genetic algorithm facilitates protein model selection

Background

Automatic protein modelling pipelines are becoming ever more accurate; this has come hand in hand with an increasingly complicated interplay between all components involved. Nevertheless, there are still potential improvements to be made in template selection, refinement and protein model selection.

Results

In the context of an automatic modelling pipeline, we analysed each step separately, revealing several non-intuitive trends and explored a new strategy for protein conformation sampling using Genetic Algorithms (GA). We apply the concept of alternating evolutionary pressure (AEP), i.e. intermediate rounds within the GA runs where unrestrained, linear growth of the model populations is allowed.

Conclusion

This approach improves the overall performance of the GA by allowing models to overcome local energy barriers. AEP enabled the selection of the best models in 40% of all targets; compared to 25% for a normal GA.

Automated server predictions in CASP7

With each round of CASP (Critical Assessment of Techniques for Protein Structure Prediction), automated prediction servers have played an increasingly important role. Today, most protein structure prediction approaches in some way depend on automated methods for fold recognition or model building. The accuracy of server predictions has significantly increased over the last years, and, in CASP7, we observed a continuation of this trend. In the template-based modeling category, the best prediction server was ranked third overall, i.e. it outperformed all but two of the human participating groups. This server also ranked among the very best predictors in the free modeling category as well, being clearly beaten by only one human group. In the high accuracy (HA) subset of TBM, two of the top five groups were servers. This article summarizes the contribution of automated structure prediction servers in the CASP7 experiment, with emphasis on 3D structure prediction, as well as information on their prediction scope and public availability.

Analysis of TASSER-based CASP7 protein structure prediction results

An improved TASSER (Threading/ASSEmbly/Refinement) methodology is applied to predict the tertiary structure for all CASP7 targets. TASSER employs template identification by threading, followed by tertiary structure assembly by rearranging continuous template fragments, where conformational space is searched via Parallel Hyperbolic Monte Carlo sampling with an optimized force-field that includes knowledge-based statistical potentials and restraints derived from threading templates. The final models are selected by clustering structures from the low temperature replicas. Improvements in TASSER over CASP6 involve use of better templates from 3D-jury applied to three threading programs, PROSPECTOR_3, SP(3), and SPARKS, and a fragment comparison method for better model ranking. For targets with no reliable templates, a variant of TASSER (chunk-TASSER) is also applied with potentials and restraints extracted from ab initio folded supersecondary chunks of the target to build full-length models. For all 124 CASP targets/domains, the average root-mean-square-deviation (RMSD) from native and alignment coverage of the best initial threading models from 3D-jury are 6.2 A and 93%, respectively. Following TASSER reassembly, the average RMSD of the best model in the template aligned region decreases to 4.9 A and the average TM-score increases from 0.617 for the template to 0.678 for the best full-length model. Based on target difficulty, the average TM-scores of the final model to native are 0.904, 0.671, and 0.307 for high-accuracy template-based modeling, template-based modeling, and free modeling targets/domains, respectively. For the more difficult targets, TASSER with modest human intervention performed better in comparison to its server counterpart, MetaTASSER, which used a limited time simulation.

Stochastic pairwise alignments and scoring methods for comparative protein structure modeling

Despite recent advances in fold recognition algorithms that identify template structures with distant homology to the target sequence, the quality of the target-template alignment can be a major problem for distantly related proteins in comparative modeling. Here we report for the first time on the use of ensembles of pairwise alignments obtained by stochastic backtracking as a means to improve three-dimensional comparative protein models. In every one of the 35 cases, the ensemble produced by the program probA resulted in alignments that were closer to the structural alignment than those obtained from the optimal alignment. In addition, we examined the lowest energy structure among these ensembles from four different structural assessment methods and compared these with the optimal and structural alignment model. The structural assessment methods consisted of the DFIRE, DOPE, and ProsaII statistical potential energies and the potential energy from the CHARMM protein force field coupled to a Generalized Born implicit solvent model. The results demonstrate that the generation of alignment ensembles through stochastic backtracking using probA combined with one of the statistical potentials for assessing three-dimensional structures can be used to improve comparative models.