Improved prediction of protein side-chain conformations with SCWRL4

Finding the right fit: chiseling structures out of cryo-electron microscopy maps

Cryo-electron microscopy is a central tool for studying the architecture of macromolecular complexes at subnanometer resolution. Interpretation of an electron microscopy map requires its computational integration with data about the structure's components from all available sources, notably atomic models. Selecting a protocol for EM density-guided integrative structural modeling depends on the resolution and quality of the EM map as well as the available complimentary datasets. Here, we review rigid, flexible, and de novo integrative fitting into EM maps and provide guidelines and considerations for the design of modeling experiments. Finally, we discuss efforts towards establishing unified criteria for map and model assessment and validation.

Determinants of substrate and cation transport in the human Na+/dicarboxylate cotransporter NaDC3

Metabolic intermediates, such as succinate and citrate, regulate important processes ranging from energy metabolism to fatty acid synthesis. Cytosolic concentrations of these metabolites are controlled, in part, by members of the SLC13 gene family. The molecular mechanism underlying Na(+)-coupled di- and tricarboxylate transport by this family is understood poorly. The human Na(+)/dicarboxylate cotransporter NaDC3 (SLC13A3) is found in various tissues, including the kidney, liver, and brain. In addition to citric acid cycle intermediates such as α-ketoglutarate and succinate, NaDC3 transports other compounds into cells, including N-acetyl aspartate, mercaptosuccinate, and glutathione, in keeping with its dual roles in cell nutrition and detoxification. In this study, we construct a homology structural model of NaDC3 on the basis of the structure of the Vibrio cholerae homolog vcINDY. Our computations are followed by experimental testing of the predicted NaDC3 structure and mode of interaction with various substrates. The results of this study show that the substrate and cation binding domains of NaDC3 are composed of residues in the opposing hairpin loops and unwound portions of adjacent helices. Furthermore, these results provide a possible explanation for the differential substrate specificity among dicarboxylate transporters that underpin their diverse biological roles in metabolism and detoxification. The structural model of NaDC3 provides a framework for understanding substrate selectivity and the Na(+)-coupled anion transport mechanism by the human SLC13 family and other key solute carrier transporters.

Detecting protein conformational changes in interactions via scaling known structures

Conformational changes frequently occur when proteins interact with other proteins. How to detect such changes in silico is a major problem. Existing methods for docking with conformational changes remain time-consuming, and they solve only a small portion of protein complexes accurately. This work presents a more accurate method (FlexDoBi) for docking with conformational changes. FlexDoBi generates the possible conformational changes of the interface residues that transform the proteins from their unbound states to bound states. Based on the generated conformational changes, multidimensional scaling is performed to construct candidates for the bound structure. We develop a new energy item for determining the orientation of docking subunits and selecting of plausible conformational changes. Experimental results illustrate that FlexDoBi achieves better results. On 20 complexes, we obtained an average iRMSD of 1.55Å, which compares favorably with the average iRMSD of 1.94Å for FiberDock. Compared to ZDOCK, our results are of 0.27Å less in average iRMSD of the medium difficulty group.

Structure of sulfamidase provides insight into the molecular pathology of mucopolysaccharidosis IIIA

Mucopolysaccharidosis type IIIA (Sanfilippo A syndrome), a fatal childhood-onset neurodegenerative disease with mild facial, visceral and skeletal abnormalities, is caused by an inherited deficiency of the enzyme N-sulfoglucosamine sulfohydrolase (SGSH; sulfamidase). More than 100 mutations in the SGSH gene have been found to reduce or eliminate its enzymatic activity. However, the molecular understanding of the effect of these mutations has been confined by a lack of structural data for this enzyme. Here, the crystal structure of glycosylated SGSH is presented at 2 Å resolution. Despite the low sequence identity between this unique N-sulfatase and the group of O-sulfatases, they share a similar overall fold and active-site architecture, including a catalytic formylglycine, a divalent metal-binding site and a sulfate-binding site. However, a highly conserved lysine in O-sulfatases is replaced in SGSH by an arginine (Arg282) that is positioned to bind the N-linked sulfate substrate. The structure also provides insight into the diverse effects of pathogenic mutations on SGSH function in mucopolysaccharidosis type IIIA and convincing evidence for the molecular consequences of many missense mutations. Further, the molecular characterization of SGSH mutations will lay the groundwork for the development of structure-based drug design for this devastating neurodegenerative disorder.

Purification and identification of metabolites produced by Bacillus cereus and B. subtilis active against Meloidogyne exigua, and their in silico interaction with a putative phosphoribosyltransferase from M. incognita

To contribute to the development of products to control Meloidogyne exigua, the bacteria Bacillus cereus and B. subtilis were cultivated in liquid medium to produce metabolites active against this plant-parasitic nematode. Fractionation of the crude dichloromethane extracts obtained from the cultures afforded uracil, 9H-purine and dihydrouracil. All compounds were active against M. exigua, the latter being the most efficient. This substance presented a LC50 of 204 µg/mL against the nematode, while a LC50 of 260 µg/mL was observed for the commercial nematicide carbofuran. A search for protein-ligand complexes in which the ligands were structurally similar to dihydrouracil resulted in the selection of phosphoribosyltransferases, the sequences of which were used in an in silico search in the genome of M. incognita for a similar sequence of amino acids. The resulting sequence was modelled and dihydrouracil and 9H-purine were inserted in the active site of this putative phosphoribosyltransferase resulting in protein-ligand complexes that underwent molecular dynamics simulations. Calculation of the binding free-energies of these complexes revealed that the dissociation constant of dihydrouracil and 9H-purine to this protein is around 8.3 x 10-7 and 1.6 x 10-6 M, respectively. Consequently, these substances and the putative phosphoribosyltransferase are promising for the development of new products to control M. exigua.

Extracellular loop 4 of the proline transporter PutP controls the periplasmic entrance to ligand binding sites

The Na(+)/proline symporter (PutP), like several other Na(+)-coupled symporters, belongs to the so-called LeuT-fold structural family, which features ten core transmembrane domains (cTMs) connected by extra- and intracellular loops. The role of these loops has been discussed in context with the gating function in the alternating access model of secondary active transport processes. Here we report the complete spin-labeling site scan of extracellular loop 4 (eL4) in PutP that reveals the presence of two α-helical segments, eL4a and eL4b. Among the eL4 residues that are directly implicated in the functional dynamics of the transporter, Phe314 in eL4b anchors the loop by means of hydrophobic contacts to cTM1 close to the ligand binding sites. We propose that ligand-induced conformational changes at the binding sites are transmitted via the anchoring residue to eL4 and through eL4 further to adjacent cTMs, leading to closure of the extracellular gate.

The c-ring ion binding site of the ATP synthase from Bacillus pseudofirmus OF4 is adapted to alkaliphilic lifestyle

In the c-ring rotor of ATP synthases ions are shuttled across the membrane during ATP synthesis by a unique rotary mechanism. We investigated characteristics of the c-ring from the alkaliphile Bacillus pseudofirmus OF4 with respect to evolutionary adaptations to operate with protons at high environmental pH. The X-ray structures of the wild-type c13 ring at pH 9.0 and a 'neutralophile-like' mutant (P51A) at pH 4.4, at 2.4 and 2.8 Å resolution, respectively, reveal a dependency of the conformation and protonation state of the proton-binding glutamate (E(54) ) on environmental hydrophobicity. Faster labelling kinetics with the inhibitor dicyclohexylcarbodiimide (DCCD) demonstrate a greater flexibility of E(54) in the mutant due to reduced water occupancy within the H(+) binding site. A second 'neutralophile-like' mutant (V21N) shows reduced growth at high pH, which is explained by restricted conformational freedom of the mutant's E(54) carboxylate. The study directly connects subtle structural adaptations of the c-ring ion binding site to in vivo effects of alkaliphile cell physiology.

Automated structure refinement for a protein heterodimer complex using limited EPR spectroscopic data and a rigid-body docking algorithm: a three-dimensional model for an ankyrin-CDB3 complex

We report here specialized functions incorporated recently in the rigid-body docking software toolkit TagDock to utilize electron paramagnetic resonance derived (EPR-derived) interresidue distance measurements and spin-label accessibility data. The TagDock package extensions include a custom methanethiosulfonate spin label rotamer library to enable explicit, all-atom spin-label side-chain modeling and scripts to evaluate spin-label surface accessibility. These software enhancements enable us to better utilize the biophysical data routinely available from various spin-labeling experiments. To illustrate the power and utility of these tools, we report the refinement of an ankyrin:CDB3 complex model that exhibits much improved agreement with the EPR distance measurements, compared to model structures published previously.

Structure-based mutational studies of substrate inhibition of betaine aldehyde dehydrogenase BetB from Staphylococcus aureus

Inhibition of enzyme activity by high concentrations of substrate and/or cofactor is a general phenomenon demonstrated in many enzymes, including aldehyde dehydrogenases. Here we show that the uncharacterized protein BetB (SA2613) from Staphylococcus aureus is a highly specific betaine aldehyde dehydrogenase, which exhibits substrate inhibition at concentrations of betaine aldehyde as low as 0.15 mM. In contrast, the aldehyde dehydrogenase YdcW from Escherichia coli, which is also active against betaine aldehyde, shows no inhibition by this substrate. Using the crystal structures of BetB and YdcW, we performed a structure-based mutational analysis of BetB and introduced the YdcW residues into the BetB active site. From a total of 32 mutations, those in five residues located in the substrate binding pocket (Val288, Ser290, His448, Tyr450, and Trp456) greatly reduced the substrate inhibition of BetB, whereas the double mutant protein H448F/Y450L demonstrated a complete loss of substrate inhibition. Substrate inhibition was also reduced by mutations of the semiconserved Gly234 (to Ser, Thr, or Ala) located in the BetB NAD(+) binding site, suggesting some cooperativity between the cofactor and substrate binding sites. Substrate docking analysis of the BetB and YdcW active sites revealed that the wild-type BetB can bind betaine aldehyde in both productive and nonproductive conformations, whereas only the productive binding mode can be modeled in the active sites of YdcW and the BetB mutant proteins with reduced substrate inhibition. Thus, our results suggest that the molecular mechanism of substrate inhibition of BetB is associated with the nonproductive binding of betaine aldehyde.

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment

BACKGROUND

Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models.

RESULTS

MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality.

CONCLUSIONS

Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy.

The Human Proteome Organization Chromosome 6 Consortium: integrating chromosome-centric and biology/disease driven strategies

The Human Proteome Project (HPP) is designed to generate a comprehensive map of the protein-based molecular architecture of the human body, to provide a resource to help elucidate biological and molecular function, and to advance diagnosis and treatment of diseases. Within this framework, the chromosome-based HPP (C-HPP) has allocated responsibility for mapping individual chromosomes by country or region, while the biology/disease HPP (B/D-HPP) coordinates these teams in cross-functional disease-based groups. Chromosome 6 (Ch6) provides an excellent model for integration of these two tasks. This metacentric chromosome has a complement of 1002-1034 genes that code for known, novel or putative proteins. Ch6 is functionally associated with more than 120 major human diseases, many with high population prevalence, devastating clinical impact and profound societal consequences. The unique combination of genomic, proteomic, metabolomic, phenomic and health services data being drawn together within the Ch6 program has enormous potential to advance personalized medicine by promoting robust biomarkers, subunit vaccines and new drug targets. The strong liaison between the clinical and laboratory teams, and the structured framework for technology transfer and health policy decisions within Canada will increase the speed and efficacy of this transition, and the value of this translational research.

BIOLOGICAL SIGNIFICANCE

Canada has been selected to play a leading role in the international Human Proteome Project, the global counterpart of the Human Genome Project designed to understand the structure and function of the human proteome in health and disease. Canada will lead an international team focusing on chromosome 6, which is functionally associated with more than 120 major human diseases, including immune and inflammatory disorders affecting the brain, skeletal system, heart and blood vessels, lungs, kidney, liver, gastrointestinal tract and endocrine system. Many of these chronic and persistent diseases have a high population prevalence, devastating clinical impact and profound societal consequences. As a result, they impose a multi-billion dollar economic burden on Canada and on all advanced societies through direct costs of patient care, the loss of health and productivity, and extensive caregiver burden. There is no definitive treatment at the present time for any of these disorders. The manuscript outlines the research which will involve a systematic assessment of all chromosome 6 genes, development of a knowledge base, and development of assays and reagents for all chromosome 6 proteins. We feel that the informatic infrastructure and MRM assays developed will place the chromosome 6 consortium in an excellent position to be a leading player in this major international research initiative. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?

Automated procedure for contact-map-based protein structure reconstruction

Knowledge of the three-dimensional structures of ion channels allows for modeling their conductivity characteristics using biophysical models and can lead to discovering their cellular functionality. Recent studies show that quality of structure predictions can be significantly improved using protein contact site information. Therefore, a number of procedures for protein structure prediction based on their contact-map have been proposed. Their comparison is difficult due to different methodologies used for validation. In this work, a Contact Map-to-Structure pipeline (C2S_pipeline) for contact-based protein structure reconstruction is designed and validated. The C2S_pipeline can be used to reconstruct monomeric and multimeric proteins. The median RMSD of structures obtained during validation on a representative set of protein structures, equaled 5.27 Å, and the best structure was reconstructed with RMSD of 1.59 Å. The validation is followed by a detailed case study on the KcsA ion channel. Models of KcsA are reconstructed based on different portions of contact site information. Structural feature analysis of acquired KcsA models is supported by a thorough analysis of electrostatic potential distributions inside the channels. The study shows that electrostatic parameters are correlated with structural quality of models. Therefore, they can be used to discriminate between high and low quality structures. We show that 30 % of contact information is needed to obtain accurate structures of KcsA, if contacts are selected randomly. This number increases to 70 % in case of erroneous maps in which the remaining contacts or non-contacts are changed to the opposite. Furthermore, the study reveals that local reconstruction accuracy is correlated with the number of contacts in which amino acid are involved. This results in higher reconstruction accuracy in the structure core than peripheral regions.

Redistribution of flexibility in stabilizing antibody fragment mutants follows Le Châtelier's principle

Le Châtelier's principle is the cornerstone of our understanding of chemical equilibria. When a system at equilibrium undergoes a change in concentration or thermodynamic state (i.e., temperature, pressure, etc.), La Châtelier's principle states that an equilibrium shift will occur to offset the perturbation and a new equilibrium is established. We demonstrate that the effects of stabilizing mutations on the rigidity ⇔ flexibility equilibrium within the native state ensemble manifest themselves through enthalpy-entropy compensation as the protein structure adjusts to restore the global balance between the two. Specifically, we characterize the effects of mutation to single chain fragments of the anti-lymphotoxin-β receptor antibody using a computational Distance Constraint Model. Statistically significant changes in the distribution of both rigidity and flexibility within the molecular structure is typically observed, where the local perturbations often lead to distal shifts in flexibility and rigidity profiles. Nevertheless, the net gain or loss in flexibility of individual mutants can be skewed. Despite all mutants being exclusively stabilizing in this dataset, increased flexibility is slightly more common than increased rigidity. Mechanistically the redistribution of flexibility is largely controlled by changes in the H-bond network. For example, a stabilizing mutation can induce an increase in rigidity locally due to the formation of new H-bonds, and simultaneously break H-bonds elsewhere leading to increased flexibility distant from the mutation site via Le Châtelier. Increased flexibility within the VH β4/β5 loop is a noteworthy illustration of this long-range effect.

Design of a truncated cardiotoxin-I analogue with potent insulinotropic activity

Insulin secretion by pancreatic β-cells in response to glucose or other secretagogues is tightly coupled to membrane potential. Various studies have highlighted the prospect of enhancing insulin secretion in a glucose-dependent manner by blocking voltage-gated potassium channels (K(v)) and calcium-activated potassium channels (K(Ca)). Such strategy is expected to present a lower risk for hypoglycemic events compared to KATP channel blockers. Our group recently reported the discovery of a new insulinotropic agent, cardiotoxin-I (CTX-I), from the Naja kaouthia snake venom. In the present study, we report the design and synthesis of [Lys(52)]CTX-I(41-60) via structure-guided modification, a truncated, equipotent analogue of CTX-I, and demonstrate, using various pharmacological inhibitors, that this derivative probably exerts its action through Kv channels. This new analogue could represent a useful pharmacological tool to study β-cell physiology or even open a new therapeutic avenue for the treatment of type 2 diabetes.

Electrostatic charge at position 552 affects the activation and permeation of FMRFamide-gated Na+ channels

The FMRFamide-gated Na(+) channel (FaNaC) is a unique peptide-gated sodium channel and a member of the epithelial sodium channel/degenerin family. Previous studies have shown that an aspartate residue (Asp(552)) in the second transmembrane domain is involved in activation of the FaNaC. To examine the significance of a negative charge at position 552, we used a cysteine-modification method. Macroscopic currents of a cysteine mutant (D552C) were potentiated or inhibited by use of positively or negatively charged sulfhydryl reagents ([2-(trimethylammonium)ethyl]methanethiosulfonate bromide, MTSET, and sodium (2-sulfonatoethyl)methanethiosulfonate, MTSES, respectively). Dose-response analysis showed that treatment with MTSET increased the potency of the FMRFamide in the FaNaC whereas treatment with MTSES reduced the maximum response. Negative charge at position 552 was necessary for the characteristic inward rectification of the FaNaC. These results suggest that negative electric charge at position 552 is important to the activation and permeation properties of the FaNaC.

A frequent, GxxxG-mediated, transmembrane association motif is optimized for the formation of interhelical Cα-H hydrogen bonds

Carbon hydrogen bonds between Cα-H donors and carbonyl acceptors are frequently observed between transmembrane helices (Cα-H···O=C). Networks of these interactions occur often at helix-helix interfaces mediated by GxxxG and similar patterns. Cα-H hydrogen bonds have been hypothesized to be important in membrane protein folding and association, but evidence that they are major determinants of helix association is still lacking. Here we present a comprehensive geometric analysis of homodimeric helices that demonstrates the existence of a single region in conformational space with high propensity for Cα-H···O=C hydrogen bond formation. This region corresponds to the most frequent motif for parallel dimers, GASright, whose best-known example is glycophorin A. The finding suggests a causal link between the high frequency of occurrence of GASright and its propensity for carbon hydrogen bond formation. Investigation of the sequence dependency of the motif determined that Gly residues are required at specific positions where only Gly can act as a donor with its "side chain" Hα. Gly also reduces the steric barrier for non-Gly amino acids at other positions to act as Cα donors, promoting the formation of cooperative hydrogen bonding networks. These findings offer a structural rationale for the occurrence of GxxxG patterns at the GASright interface. The analysis identified the conformational space and the sequence requirement of Cα-H···O=C mediated motifs; we took advantage of these results to develop a structural prediction method. The resulting program, CATM, predicts ab initio the known high-resolution structures of homodimeric GASright motifs at near-atomic level.

Incorporating post-translational modifications and unnatural amino acids into high-throughput modeling of protein structures

MOTIVATION

Accurately predicting protein side-chain conformations is an important subproblem of the broader protein structure prediction problem. Several methods exist for generating fairly accurate models for moderate-size proteins in seconds or less. However, a major limitation of these methods is their inability to model post-translational modifications (PTMs) and unnatural amino acids. In natural living systems, the chemical groups added following translation are often critical for the function of the protein. In engineered systems, unnatural amino acids are incorporated into proteins to explore structure-function relationships and create novel proteins.

RESULTS

We present a new version of SIDEpro to predict the side chains of proteins containing non-standard amino acids, including 15 of the most frequently observed PTMs in the Protein Data Bank and all types of phosphorylation. SIDEpro uses energy functions that are parameterized by neural networks trained from available data. For PTMs, the [Formula: see text] and [Formula: see text] accuracies are comparable with those obtained for the precursor amino acid, and so are the RMSD values for the atoms shared with the precursor amino acid. In addition, SIDEpro can accommodate any PTM or unnatural amino acid, thus providing a flexible prediction system for high-throughput modeling of proteins beyond the standard amino acids.

AVAILABILITY AND IMPLEMENTATION

SIDEpro programs and Web server, rotamer libraries and data are available through the SCRATCH suite of protein structure predictors at http://scratch.proteomics.ics.uci.edu/

Kinase-mediated changes in nucleosome conformation trigger chromatin decondensation via poly(ADP-ribosyl)ation

Dynamically controlled posttranslational modifications of nucleosomal histones alter chromatin condensation to regulate transcriptional activation. We report that a nuclear tandem kinase, JIL-1, controls gene expression by activating poly(ADP-ribose) polymerase-1 (PARP-1). JIL-1 phosphorylates the C terminus of the H2Av histone variant, which stimulates PARP-1 enzymatic activity in the surrounding chromatin, leading to further modification of histones and chromatin loosening. The H2Av nucleosome has a higher surface representation of PARP-1 binding patch, consisting of H3 and H4 epitopes. Phosphorylation of H2Av by JIL-1 restructures this surface patch, leading to activation of PARP-1. Exposure of Val61 and Leu23 of the H4 histone is critical for PARP-1 binding on nucleosome and PARP-1 activation following H2Av phosphorylation. We propose that chromatin loosening and associated initiation of gene expression is activated by phosphorylation of H2Av in a nucleosome positioned in promoter regions of PARP-1-dependent genes.

Dynafold: a dynamic programming approach to protein backbone structure determination from minimal sets of Residual Dipolar Couplings

Residual Dipolar Couplings (RDCs) are a source of NMR data that can provide a powerful set of constraints on the orientation of inter-nuclear vectors, and are quickly becoming a larger part of the experimental toolset for molecular biologists. However, few reliable protocols exist for the determination of protein backbone structures from small sets of RDCs. DynaFold is a new dynamic programming algorithm designed specifically for this task, using minimal sets of RDCs collected in multiple alignment media. DynaFold was first tested utilizing synthetic data generated for the N--H , C(α)--H(α), and C--N vectors of 1BRF, 1F53, 110M, and 3LAY proteins, with up to ±1 Hz error in three alignment media, and was able to produce structures with less than 1.9 Å of the original structures. DynaFold was then tested using experimental data, obtained from the Biological Magnetic Resonance Bank, for proteins PDBID:1P7E and 1D3Z using RDC data from two alignment media. This exercise yielded structures within 1.0 Å of their respective published structures in segments with high data density, and less than 1.9 Å over the entire protein. The same sets of RDC data were also used in comparisons with traditional methods for analysis of RDCs, which failed to match the accuracy of DynaFold's approach to structure determination.

GeneSV - an Approach to Help Characterize Possible Variations in Genomic and Protein Sequences

A computational approach for identification and assessment of genomic sequence variability (GeneSV) is described. For a given nucleotide sequence, GeneSV collects information about the permissible nucleotide variability (changes that potentially preserve function) observed in corresponding regions in genomic sequences, and combines it with conservation/variability results from protein sequence and structure-based analyses of evaluated protein coding regions. GeneSV was used to predict effects (functional vs. non-functional) of 37 amino acid substitutions on the NS5 polymerase (RdRp) of dengue virus type 2 (DENV-2), 36 of which are not observed in any publicly available DENV-2 sequence. 32 novel mutants with single amino acid substitutions in the RdRp were generated using a DENV-2 reverse genetics system. In 81% (26 of 32) of predictions tested, GeneSV correctly predicted viability of introduced mutations. In 4 of 5 (80%) mutants with double amino acid substitutions proximal in structure to one another GeneSV was also correct in its predictions. Predictive capabilities of the developed system were illustrated on dengue RNA virus, but described in the manuscript a general approach to characterize real or theoretically possible variations in genomic and protein sequences can be applied to any organism.

Residue-Specific Side-Chain Polymorphisms via Particle Belief Propagation

Protein side chains populate diverse conformational ensembles in crystals. Despite much evidence that there is widespread conformational polymorphism in protein side chains, most of the X-ray crystallography data are modeled by single conformations in the Protein Data Bank. The ability to extract or to predict these conformational polymorphisms is of crucial importance, as it facilitates deeper understanding of protein dynamics and functionality. In this paper, we describe a computational strategy capable of predicting side-chain polymorphisms. Our approach extends a particular class of algorithms for side-chain prediction by modeling the side-chain dihedral angles more appropriately as continuous rather than discrete variables. Employing a new inferential technique known as particle belief propagation, we predict residue-specific distributions that encode information about side-chain polymorphisms. Our predicted polymorphisms are in relatively close agreement with results from a state-of-the-art approach based on X-ray crystallography data, which characterizes the conformational polymorphisms of side chains using electron density information, and has successfully discovered previously unmodeled conformations.

Modeling of protein side-chain conformations with RASP

Modeling of side-chain conformations on a fixed protein backbone, also called side-chain packing, plays an important role in protein structure prediction, protein design, molecular docking, and functional analysis. RASP, or RApid Side-chain Predictor, is a recently developed program that can model protein side-chain conformations with both high accuracy and high speed. Moreover, it can generate structures with few atomic clashes. This chapter first provides a brief introduction to the principle and performances of the RASP package. Then details on how to use RASP programs to predict protein side-chain conformations are elaborated. Finally, it describes case studies for structure refinement in homology modeling and residue substitution.

Predicting the structure of protein-protein complexes using the SwarmDock Web Server

Protein-protein interactions drive many of the biological functions of the cell. Any two proteins have the potential to interact; however, whether the interactions are of biological significance is dependent on a number of complicated factors. Thus, modelling the three-dimensional structure of protein-protein complexes is still considered to be a complex endeavor. Nevertheless, many experimentalists now wish to boost their knowledge of protein-protein interactions, well beyond complexes resolved experimentally, and for them to be able to do so it is important they are able to effectively and confidently predict protein-protein interactions. The main aim of this chapter is to acquaint the reader, particularly one from a non-computational background, how to use a state-of-the-art protein docking tool. In particular, we describe here the SwarmDock Server (SDS), a web service for the flexible modelling of protein-protein complexes; this server is freely available at: http://bmm.cancerresearchuk.org/~SwarmDock/. Supplementary files for Case Studies are provided with the chapter and available at extras.springer.com.

Distinct Orai-coupling domains in STIM1 and STIM2 define the Orai-activating site

STIM1 and STIM2 are widely expressed endoplasmic reticulum (ER) Ca(2+) sensor proteins able to translocate within the ER membrane to physically couple with and gate plasma membrane Orai Ca(2+) channels. Although they are structurally similar, we reveal critical differences in the function of the short STIM-Orai-activating regions (SOAR) of STIM1 and STIM2. We narrow these differences in Orai1 gating to a strategically exposed phenylalanine residue (Phe-394) in SOAR1, which in SOAR2 is substituted by a leucine residue. Remarkably, in full-length STIM1, replacement of Phe-394 with the dimensionally similar but polar histidine head group prevents both Orai1 binding and gating, creating an Orai1 non-agonist. Thus, this residue is critical in tuning the efficacy of Orai activation. While STIM1 is a full Orai1-agonist, leucine-replacement of this crucial residue in STIM2 endows it with partial agonist properties, which may be critical for limiting Orai1 activation stemming from its enhanced sensitivity to store-depletion.

Constitutive activities and inverse agonism in dopamine receptors

The concept of activation in the absence of agonists has been demonstrated for many GPCRs and is now solidified as one of the principal aspects of GPCR signaling. In this chapter, we review how dopamine receptors demonstrate this ability. Although difficult to prove in vivo due to the presence of endogenous dopamine and lack of subtype-selective inverse agonists and "pure" antagonists (neutral ligands), in vitro assays such as measuring intracellular cAMP, [(35)S]GTPγS binding, and [(3)H]thymidine incorporation have uncovered the constitutive activation of D1- and D2-class receptors. Nevertheless, because of limited and inconsistent findings, the existence of constitutive activity for D2-class receptors is currently not well established. Mutagenesis studies have shown that basal signaling, notably by D1-class receptors, is governed by the collective contributions of transmembrane domains and extracellular/intracellular loops, such as the third extracellular loop, the third intracellular loop, and C-terminal tail. Furthermore, constitutive activities of D1-class receptors are subjected to regulation by kinases. Among the dopamine receptor family, the D5 receptor subtype exhibits a higher basal signaling and bears resemblance to constitutively active mutant forms of GPCRs. The presence of its constitutive activity in vivo and its pathophysiological relevance, with a brief mention of other subtypes, are also discussed.

DOCK/PIERR: web server for structure prediction of protein-protein complexes

In protein docking we aim to find the structure of the complex formed when two proteins interact. Protein-protein interactions are crucial for cell function. Here we discuss the usage of DOCK/PIERR. In DOCK/PIERR, a uniformly discrete sampling of orientations of one protein with respect to the other, are scored, followed by clustering, refinement, and reranking of structures. The novelty of this method lies in the scoring functions used. These are obtained by examining hundreds of millions of correctly and incorrectly docked structures, using an algorithm based on mathematical programming, with provable convergence properties.

Protocols for efficient simulations of long-time protein dynamics using coarse-grained CABS model

Coarse-grained (CG) modeling is a well-acknowledged simulation approach for getting insight into long-time scale protein folding events at reasonable computational cost. Depending on the design of a CG model, the simulation protocols vary from highly case-specific-requiring user-defined assumptions about the folding scenario-to more sophisticated blind prediction methods for which only a protein sequence is required. Here we describe the framework protocol for the simulations of long-term dynamics of globular proteins, with the use of the CABS CG protein model and sequence data. The simulations can start from a random or a selected (e.g., native) structure. The described protocol has been validated using experimental data for protein folding model systems-the prediction results agreed well with the experimental results.

Comparative Modeling of Drug Target Proteins☆

In this perspective, we begin by describing the comparative protein structure modeling technique and the accuracy of the corresponding models. We then discuss the significant role that comparative prediction plays in drug discovery. We focus on virtual ligand screening against comparative models and illustrate the state-of-the-art by a number of specific examples.

Computational methods in drug discovery

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

Assessment of homology templates and an anesthetic binding site within the γ-aminobutyric acid receptor

BACKGROUND

Anesthetics mediate portions of their activity via modulation of the γ-aminobutyric acid receptor (GABAaR). Although its molecular structure remains unknown, significant progress has been made toward understanding its interactions with anesthetics via molecular modeling.

METHODS

The structure of the torpedo acetylcholine receptor (nAChRα), the structures of the α4 and β2 subunits of the human nAChR, the structures of the eukaryotic glutamate-gated chloride channel (GluCl), and the prokaryotic pH-sensing channels, from Gloeobacter violaceus and Erwinia chrysanthemi, were aligned with the SAlign and 3DMA algorithms. A multiple sequence alignment from these structures and those of the GABAaR was performed with ClustalW. The Modeler and Rosetta algorithms independently created three-dimensional constructs of the GABAaR from the GluCl template. The CDocker algorithm docked a congeneric series of propofol derivatives into the binding pocket and scored calculated binding affinities for correlation with known GABAaR potentiation EC50s.

RESULTS

Multiple structure alignments of templates revealed a clear consensus of residue locations relevant to anesthetic effects except for torpedo nAChR. Within the GABAaR models generated from GluCl, the residues notable for modulating anesthetic action within transmembrane segments 1, 2, and 3 converged on the intersubunit interface between α and β subunits. Docking scores of a propofol derivative series into this binding site showed strong linear correlation with GABAaR potentiation EC50.

CONCLUSION

Consensus structural alignment based on homologous templates revealed an intersubunit anesthetic binding cavity within the transmembrane domain of the GABAaR, which showed a correlation of ligand docking scores with experimentally measured GABAaR potentiation.

Improving computational efficiency and tractability of protein design using a piecemeal approach. A strategy for parallel and distributed protein design

MOTIVATION

Accuracy in protein design requires a fine-grained rotamer search, multiple backbone conformations, and a detailed energy function, creating a burden in runtime and memory requirements. A design task may be split into manageable pieces in both three-dimensional space and in the rotamer search space to produce small, fast jobs that are easily distributed. However, these jobs must overlap, presenting a problem in resolving conflicting solutions in the overlap regions.

RESULTS

Piecemeal design, in which the design space is split into overlapping regions and rotamer search spaces, accelerates the design process whether jobs are run in series or in parallel. Large jobs that cannot fit in memory were made possible by splitting. Accepting the consensus amino acid selection in conflict regions led to non-optimal choices. Instead, conflicts were resolved using a second pass, in which the split regions were re-combined and designed as one, producing results that were closer to optimal with a minimal increase in runtime over the consensus strategy. Splitting the search space at the rotamer level instead of at the amino acid level further improved the efficiency by reducing the search space in the second pass.

AVAILABILITY AND IMPLEMENTATION

Programs for splitting protein design expressions are available at www.bioinfo.rpi.edu/tools/piecemeal.html CONTACT: bystrc@rpi.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Energetic and molecular water permeation mechanisms of the human red blood cell urea transporter B

Urea transporter B (UT-B) is a passive membrane channel that facilitates highly efficient permeation of urea. In red blood cells (RBC), while the major function of UT-B is to transport urea, it is assumed that this protein is able to conduct water. Here, we have revisited this last issue by studying RBCs and ghosts from human variants with defects of aquaporin 1 (AQP1) or UT-B. We found that UT-B's osmotic water unit permeability (pfunit) is similar to that of AQP1. The determination of diffusional permeability coefficient (Pd) allowed the calculation of the Pf/Pd ratio, which is consistent with a single-file water transport. Molecular dynamic simulations of water conduction through human UT-B confirmed the experimental finding. From these results, we propose an atomistic description of water-protein interactions involved in this permeation. Inside the UT-B pore, five water molecules were found to form a single-file and move rapidly along a channel by hydrogen bond exchange involving two critical threonines. We further show that the energy barrier for water located in the central region coincides with a water dipole reorientation, which can be related to the proton exclusion observed experimentally. In conclusion, our results indicate that UT-B should be considered as a new member of the water channel family.

OPTIMIZATION BIAS IN ENERGY-BASED STRUCTURE PREDICTION

Physics-based computational approaches to predicting the structure of macromolecules such as proteins are gaining increased use, but there are remaining challenges. In the current work, it is demonstrated that in energy-based prediction methods, the degree of optimization of the sampled structures can influence the prediction results. In particular, discrepancies in the degree of local sampling can bias the predictions in favor of the oversampled structures by shifting the local probability distributions of the minimum sampled energies. In simple systems, it is shown that the magnitude of the errors can be calculated from the energy surface, and for certain model systems, derived analytically. Further, it is shown that for energy wells whose forms differ only by a randomly assigned energy shift, the optimal accuracy of prediction is achieved when the sampling around each structure is equal. Energy correction terms can be used in cases of unequal sampling to reproduce the total probabilities that would occur under equal sampling, but optimal corrections only partially restore the prediction accuracy lost to unequal sampling. For multiwell systems, the determination of the correction terms is a multibody problem; it is shown that the involved cross-correlation multiple integrals can be reduced to simpler integrals. The possible implications of the current analysis for macromolecular structure prediction are discussed.

Packing interface energetics in different crystal forms of the λ Cro dimer

Variation among crystal structures of the λ Cro dimer highlights conformational flexibility. The structures range from a wild type closed to a mutant fully open conformation, but it is unclear if each represents a stable solution state or if one may be the result of crystal packing. Here we use molecular dynamics (MD) simulation to investigate the energetics of crystal packing interfaces and the influence of site-directed mutagenesis on them in order to examine the effect of crystal packing on wild type and mutant Cro dimer conformation. Replica exchange MD of mutant Cro in solution shows that the observed conformational differences between the wild type and mutant protein are not the direct consequence of mutation. Instead, simulation of Cro in different crystal environments reveals that mutation affects the stability of crystal forms. Molecular Mechanics Poisson-Boltzmann Surface Area binding energy calculations reveal the detailed energetics of packing interfaces. Packing interfaces can have diverse properties in strength, energetic components, and some are stronger than the biological dimer interface. Further analysis shows that mutation can strengthen packing interfaces by as much as ∼5 kcal/mol in either crystal environment. Thus, in the case of Cro, mutation provides an additional energetic contribution during crystal formation that may stabilize a fully open higher energy state. Moreover, the effect of mutation in the lattice can extend to packing interfaces not involving mutation sites. Our results provide insight into possible models for the effect of crystallization on Cro conformational dynamics and emphasize careful consideration of protein crystal structures.

Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method

Background

Many proteins tune their biological function by transitioning between different functional states, effectively acting as dynamic molecular machines. Detailed structural characterization of transition trajectories is central to understanding the relationship between protein dynamics and function. Computational approaches that build on the Molecular Dynamics framework are in principle able to model transition trajectories at great detail but also at considerable computational cost. Methods that delay consideration of dynamics and focus instead on elucidating energetically-credible conformational paths connecting two functionally-relevant structures provide a complementary approach. Effective sampling-based path planning methods originating in robotics have been recently proposed to produce conformational paths. These methods largely model short peptides or address large proteins by simplifying conformational space.

Methods

We propose a robotics-inspired method that connects two given structures of a protein by sampling conformational paths. The method focuses on small- to medium-size proteins, efficiently modeling structural deformations through the use of the molecular fragment replacement technique. In particular, the method grows a tree in conformational space rooted at the start structure, steering the tree to a goal region defined around the goal structure. We investigate various bias schemes over a progress coordinate for balance between coverage of conformational space and progress towards the goal. A geometric projection layer promotes path diversity. A reactive temperature scheme allows sampling of rare paths that cross energy barriers.

Results and conclusions

Experiments are conducted on small- to medium-size proteins of length up to 214 amino acids and with multiple known functionally-relevant states, some of which are more than 13Å apart of each-other. Analysis reveals that the method effectively obtains conformational paths connecting structural states that are significantly different. A detailed analysis on the depth and breadth of the tree suggests that a soft global bias over the progress coordinate enhances sampling and results in higher path diversity. The explicit geometric projection layer that biases the exploration away from over-sampled regions further increases coverage, often improving proximity to the goal by forcing the exploration to find new paths. The reactive temperature scheme is shown effective in increasing path diversity, particularly in difficult structural transitions with known high-energy barriers.

A population-based evolutionary search approach to the multiple minima problem in de novo protein structure prediction

Background

Elucidating the native structure of a protein molecule from its sequence of amino acids, a problem known as de novo structure prediction, is a long standing challenge in computational structural biology. Difficulties in silico arise due to the high dimensionality of the protein conformational space and the ruggedness of the associated energy surface. The issue of multiple minima is a particularly troublesome hallmark of energy surfaces probed with current energy functions. In contrast to the true energy surface, these surfaces are weakly-funneled and rich in comparably deep minima populated by non-native structures. For this reason, many algorithms seek to be inclusive and obtain a broad view of the low-energy regions through an ensemble of low-energy (decoy) conformations. Conformational diversity in this ensemble is key to increasing the likelihood that the native structure has been captured.

Methods

We propose an evolutionary search approach to address the multiple-minima problem in decoy sampling for de novo structure prediction. Two population-based evolutionary search algorithms are presented that follow the basic approach of treating conformations as individuals in an evolving population. Coarse graining and molecular fragment replacement are used to efficiently obtain protein-like child conformations from parents. Potential energy is used both to bias parent selection and determine which subset of parents and children will be retained in the evolving population. The effect on the decoy ensemble of sampling minima directly is measured by additionally mapping a conformation to its nearest local minimum before considering it for retainment. The resulting memetic algorithm thus evolves not just a population of conformations but a population of local minima.

Results and conclusions

Results show that both algorithms are effective in terms of sampling conformations in proximity of the known native structure. The additional minimization is shown to be key to enhancing sampling capability and obtaining a diverse ensemble of decoy conformations, circumventing premature convergence to sub-optimal regions in the conformational space, and approaching the native structure with proximity that is comparable to state-of-the-art decoy sampling methods. The results are shown to be robust and valid when using two representative state-of-the-art coarse-grained energy functions.

Rapid sampling of local minima in protein energy surface and effective reduction through a multi-objective filter

BACKGROUND

Many problems in protein modeling require obtaining a discrete representation of the protein conformational space as an ensemble of conformations. In ab-initio structure prediction, in particular, where the goal is to predict the native structure of a protein chain given its amino-acid sequence, the ensemble needs to satisfy energetic constraints. Given the thermodynamic hypothesis, an effective ensemble contains low-energy conformations which are similar to the native structure. The high-dimensionality of the conformational space and the ruggedness of the underlying energy surface currently make it very difficult to obtain such an ensemble. Recent studies have proposed that Basin Hopping is a promising probabilistic search framework to obtain a discrete representation of the protein energy surface in terms of local minima. Basin Hopping performs a series of structural perturbations followed by energy minimizations with the goal of hopping between nearby energy minima. This approach has been shown to be effective in obtaining conformations near the native structure for small systems. Recent work by us has extended this framework to larger systems through employment of the molecular fragment replacement technique, resulting in rapid sampling of large ensembles.

METHODS

This paper investigates the algorithmic components in Basin Hopping to both understand and control their effect on the sampling of near-native minima. Realizing that such an ensemble is reduced before further refinement in full ab-initio protocols, we take an additional step and analyze the quality of the ensemble retained by ensemble reduction techniques. We propose a novel multi-objective technique based on the Pareto front to filter the ensemble of sampled local minima.

RESULTS AND CONCLUSIONS

We show that controlling the magnitude of the perturbation allows directly controlling the distance between consecutively-sampled local minima and, in turn, steering the exploration towards conformations near the native structure. For the minimization step, we show that the addition of Metropolis Monte Carlo-based minimization is no more effective than a simple greedy search. Finally, we show that the size of the ensemble of sampled local minima can be effectively and efficiently reduced by a multi-objective filter to obtain a simpler representation of the probed energy surface.

Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement

AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

The binding of TAPBPR and Tapasin to MHC class I is mutually exclusive

The loading of peptide Ags onto MHC class I molecules is a highly controlled process in which the MHC class I-dedicated chaperone tapasin is a key player. We recently identified a tapasin-related molecule, TAPBPR, as an additional component in the MHC class I Ag-presentation pathway. In this study, we show that the amino acid residues important for tapasin to interact with MHC class I are highly conserved on TAPBPR. We identify specific residues in the N-terminal and C-terminal domains of TAPBPR involved in associating with MHC class I. Furthermore, we demonstrate that residues on MHC class I crucial for its association with tapasin, such as T134, are also essential for its interaction with TAPBPR. Taken together, the data indicate that TAPBPR and tapasin bind in a similar orientation to the same face of MHC class I. In the absence of tapasin, the association of MHC class I with TAPBPR is increased. However, in the absence of TAPBPR, the interaction between MHC class I and tapasin does not increase. In light of our findings, previous data determining the function of tapasin in the MHC class I Ag-processing and presentation pathway must be re-evaluated.

An evolution-based approach to De Novo protein design and case study on Mycobacterium tuberculosis

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality.

The goal of computational protein design is to create new protein sequences of desirable structure and biological function. Most protein design methods are developed to search for sequences with the lowest free-energy based on physics-based force fields following Anfinsen's thermodynamic hypothesis. A major obstacle of such approaches is the inaccuracy of the force-field design, which cannot accurately describe atomic interactions or correctly recognize protein folds. We propose a novel method which uses evolutionary information, in the form of sequence profiles from structure families, to guide the sequence design. Since sequence profiles are generally more accurate than physics-based potentials in protein fold recognition, a unique advantage lies on that it targets the design procedure to a family of protein sequence profiles to enhance the robustness of designed sequences. The method was tested on 87 proteins and the designed sequences can be folded by I-TASSER to models with an average RMSD 2.1 Å. As a case study of large-scale application, the method is extended to redesign all structurally resolved proteins in the human pathogenic bacteria, Mycobacterium tuberculosis. Five sequences varying in fold and sizes were characterized by circular dichroism and NMR spectroscopy experiments and three were shown to have ordered tertiary structure.

Bindings of hMRP1 transmembrane peptides with dodecylphosphocholine and dodecyl-β-d-maltoside micelles: a molecular dynamics simulation study

In this paper, we describe molecular dynamics simulation results of the interactions between four peptides (mTM10, mTM16, TM17 and KTM17) with micelles of dodecylphosphocholine (DPC) and dodecyl-β-d-maltoside (DDM). These peptides represent three transmembrane fragments (TM10, 16 and 17) from the MSD1 and MSD2 membrane-spanning domains of an ABC membrane protein (hMRP1), which play roles in the protein functions. The peptide-micelle complex structures, including the tryptophan accessibility and dynamics were compared to circular dichroism and fluorescence studies obtained in water, trifluoroethanol and with micelles. Our work provides additional results not directly accessible by experiments that give further support to the fact that these peptides adopt an interfacial conformation within the micelles. We also show that the peptides are more buried in DDM than in DPC, and consequently, that they have a larger surface exposure to water in DPC than in DDM. As noted previously by simulations and experiments we have also observed formation of cation-π bonds between the phosphocholine DPC headgroup and Trp peptide residue. Concerning the peptide secondary structures (SS), we find that in TFE their initial helical conformations are maintained during the simulation, whereas in water their initial SS are lost after few nanoseconds of simulation. An intermediate situation is observed with micelles, where the peptides remain partially folded and more structured in DDM than in DPC. Finally, our results show no sign of β-strand structure formation as invoked by far-UV CD experiments even when three identical peptides are simulated either in water or with micelles.

Designing cooperativity into the designed protein Top7

The topology of the designed protein Top7 is not found in natural proteins. Top7 shows signatures of non-cooperative folding in both experimental studies and computer simulations. In particular, molecular dynamics of coarse-grained structure-based models of Top7 show a well-populated C-terminal folding-intermediate. Since most similarly sized globular proteins are cooperative folders, the non-natural topology of Top7 has been suggested as a reason for its non-cooperative folding. Here, we computationally examine the folding of Top7 with the intent of making it cooperative. We find that its folding cooperativity can be increased in two ways: (a) Optimization of packing interactions in the N-terminal half of the protein enables further folding of the C-terminal intermediate. (b) Reduction in the packing density of the C-terminal region destabilizes the intermediate. In practice, these strategies are implemented in our Top7 model through modifications to the contact-map. These modifications do not alter the topology of Top7 but result in cooperative folding. Amino-acid mutations that mimic these modifications also lead to a significant increase in folding cooperativity. Finally, we devise a method to randomize the sizes of amino-acids within the same topology, and confirm that the structure of Top7 makes its folding sensitive to packing interactions. In contrast, the ribosomal protein S6, which has secondary structure similar to Top7, has folding which is much less sensitive to packing perturbations. Thus, it should be possible to make a sequence fold cooperatively to the structure of Top7, but to do so its side-chain packing needs to be carefully designed.

Flexible docking and refinement with a coarse-grained protein model using ATTRACT

A coarse-grained (CG) protein model implemented in the ATTRACT protein-protein docking program has been employed to predict protein-protein complex structures in CAPRI Rounds 22-27. For six targets, acceptable or better quality solutions have been submitted corresponding to ~60% of all targets. For one target, promising results on the prediction of the hydration structure at the protein-protein interface have been achieved. New approaches for the rapid flexible refinement have been developed based on a combination of atomistic representation of the bonded geometry and a CG description of nonbonded interactions. Possible further improvements of the docking approach in particular at the scoring and the flexible refinement steps are discussed.