Computational protein design and large-scale assessment by I-TASSER structure assembly simulations

Modeling of SARS-CoV-2 Virus Proteins: Implications on Its Proteome

COronaVIrus Disease 19 (COVID-19) is a severe acute respiratory syndrome (SARS) caused by a group of beta coronaviruses, SARS-CoV-2. The SARS-CoV-2 virus is similar to previous SARS- and MERS-causing strains and has infected nearly six hundred and fifty million people all over the globe, while the death toll has crossed the six million mark (as of December, 2022). In this chapter, we look at how computational modeling approaches of the viral proteins could help us understand the various processes in the viral life cycle inside the host, an understanding of which might provide key insights in mitigating this and future threats. This understanding helps us identify key targets for the purpose of drug discovery and vaccine development.

Algorithms for protein design

Computational Protein Design has the potential to contribute to major advances in enzyme technology, vaccine design, receptor-ligand engineering, biomaterials, nanosensors, and synthetic biology. Although Protein Design is a challenging problem, proteins can be designed by experts in Protein Design, as well as by non-experts whose primary interests are in the applications of Protein Design. The increased accessibility of Protein Design technology is attributable to the accumulated knowledge and experience with Protein Design as well as to the availability of software and online resources. The objective of this review is to serve as a guide to the relevant literature with a focus on the novel methods and algorithms that have been developed or applied for Protein Design, and to assist in the selection of algorithms for Protein Design. Novel algorithms and models that have been introduced to utilize the enormous amount of experimental data and novel computational hardware have the potential for producing substantial increases in the accuracy, reliability and range of applications of designed proteins.

A sequence space search engine for computational protein design to modulate molecular functionality

De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Carlo parallel search algorithm for better sequence-structure compatibility probing in protein design. The guidance provided by the evolutionary profile, the greedy approach, and the cooling schedule adopted in the Monte Carlo simulation ensures sufficient exploration and exploitation of the search space leading to faster convergence. On evaluating the proposed algorithm, we find that a dataset of 76 target scaffolds report an average root-mean-square-deviation (RMSD) of 1.07 Å and an average TM-Score of 0.93 with the modeled designed protein sequences. High sequence recapitulation of 48.7% (59.4%) observed in the design sequences for all (hydrophobic) solvent-inaccessible residues again establish the goodness of the proposed algorithm. A high (93.4%) intra-group recapitulation of hydrophobic residues in the solvent-inaccessible region indicates that the proposed protein design algorithm preserves the core residues in the protein and provides alternative residue combinations in the solvent-accessible regions of the target protein. Furthermore, a COFACTOR-based protein functional analysis shows that the design sequences exhibit altered molecular functionality and introduce new molecular functions compared to the target scaffolds.Communicated by Ramaswamy H. Sarma.

Intestinal guard: Human CXCL17 modulates protective response against mycotoxins and CXCL17-mimetic peptides development

Mycotoxin contamination is an ongoing and growing issue that can create health risks and even cause death. Unfortunately, there is currently a lack of specific therapy against mycotoxins with few side effects. On the other hand, the strategic expression of CXCL17 in mucosal tissues suggests that it may be involved in immune response when exposed to mycotoxins, but the exact role of CXCL17 remains largely unknown. Using Caco-2 as a cell model of the intestinal epithelial barrier (the first line of defense against mycotoxins), we showed that a strong production of ROS-dependent CXCL17 was triggered by mycotoxins via p38 and JNK pathways. Under the mycotoxins stress, CXCL17 modulated enhanced immuno-protective response with a remission of inflammation and apoptosis through PI3K/AKT/mTOR. Based on our observed feedback of CXCL17 to the mycotoxins, we developed the CXCL17-mimetic peptides in silico (CX1 and CX2) that possessed the safety and the capability to ameliorate mycotoxins-inducible inflammation and apoptosis. In this study, the identification of detoxifying feature of CXCL17 is a prominent addition to the chemokine field, pointing out a new direction for curing the mycotoxins-caused damage.

An Evolutionary Profile Guided Greedy Parallel Replica-Exchange Monte Carlo Search Algorithm for Rapid Convergence in Protein Design

Protein design, also known as the inverse protein folding problem, is the identification of a protein sequence that folds into a target protein structure. Protein design is proved as an NP-hard problem. While researchers are working on designing heuristics with an emphasis on new scoring functions, we propose a replica-exchange Monte Carlo (REMC) search algorithm that ensures faster convergence using a greedy strategy. Using biological insights, we construct an evolutionary profile to encode the amino acid variability in different positions of the target protein from its structural homologs. The evolutionary profile guides the REMC search, and the greedy approach confirms appreciable exploration and exploitation of the sequence-structure fitness surface. We allow termination of a simulation trajectory once stagnant situation is detected. A series of sequence and structure level validations establish the goodness of our design. On a benchmark dataset, our algorithm reports an average root-mean-square deviation of 1.21Å between the target and the design proteins when modeled with an existing protein folding software. Besides, our algorithm assures 6.16 times overall speedup. In Molecular Dynamics simulations, we observe that four out of selected five design proteins report better to comparable stability to the corresponding target proteins.

FASPR: an open-source tool for fast and accurate protein side-chain packing

MOTIVATION

Protein structure and function are essentially determined by how the side-chain atoms interact with each other. Thus, accurate protein side-chain packing (PSCP) is a critical step toward protein structure prediction and protein design. Despite the importance of the problem, however, the accuracy and speed of current PSCP programs are still not satisfactory.

RESULTS

We present FASPR for fast and accurate PSCP by using an optimized scoring function in combination with a deterministic searching algorithm. The performance of FASPR was compared with four state-of-the-art PSCP methods (CISRR, RASP, SCATD and SCWRL4) on both native and non-native protein backbones. For the assessment on native backbones, FASPR achieved a good performance by correctly predicting 69.1% of all the side-chain dihedral angles using a stringent tolerance criterion of 20°, compared favorably with SCWRL4, CISRR, RASP and SCATD which successfully predicted 68.8%, 68.6%, 67.8% and 61.7%, respectively. Additionally, FASPR achieved the highest speed for packing the 379 test protein structures in only 34.3 s, which was significantly faster than the control methods. For the assessment on non-native backbones, FASPR showed an equivalent or better performance on I-TASSER predicted backbones and the backbones perturbed from experimental structures. Detailed analyses showed that the major advantage of FASPR lies in the optimal combination of the dead-end elimination and tree decomposition with a well optimized scoring function, which makes FASPR of practical use for both protein structure modeling and protein design studies.

AVAILABILITY AND IMPLEMENTATION

The web server, source code and datasets are freely available at https://zhanglab.ccmb.med.umich.edu/FASPR and https://github.com/tommyhuangthu/FASPR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

EvoEF2: accurate and fast energy function for computational protein design

MOTIVATION

The accuracy and success rate of de novo protein design remain limited, mainly due to the parameter over-fitting of current energy functions and their inability to discriminate incorrect designs from correct designs.

RESULTS

We developed an extended energy function, EvoEF2, for efficient de novo protein sequence design, based on a previously proposed physical energy function, EvoEF. Remarkably, EvoEF2 recovered 32.5%, 47.9% and 22.3% of all, core and surface residues for 148 test monomers, and was generally applicable to protein-protein interaction design, as it recapitulated 30.9%, 42.4%, 31.3% and 21.4% of all, core, interface and surface residues for 88 test dimers, significantly outperforming EvoEF on the native sequence recapitulation. We further used I-TASSER to evaluate the foldability of the 148 designed monomer sequences, where all of them were predicted to fold into structures with high fold- and atomic-level similarity to their corresponding native structures, as demonstrated by the fact that 87.8% of the predicted structures shared a root-mean-square-deviation less than 2 Å to their native counterparts. The study also demonstrated that the usefulness of physical energy functions is highly correlated with the parameter optimization processes, and EvoEF2, with parameters optimized using sequence recapitulation, is more suitable for computational protein sequence design than EvoEF, which was optimized on thermodynamic mutation data.

AVAILABILITY AND IMPLEMENTATION

The source code of EvoEF2 and the benchmark datasets are freely available at https://zhanglab.ccmb.med.umich.edu/EvoEF.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Toward the Accuracy and Speed of Protein Side-Chain Packing: A Systematic Study on Rotamer Libraries

Protein rotamers refer to the conformational isomers taken by the side-chains of amino acids to accommodate specific structural folding environments. Since accurate modeling of atomic interactions is difficult, rotamer information collected from experimentally solved protein structures is often used to guide side-chain packing in protein folding and sequence design studies. Many rotamer libraries have been built in the literature but there is little quantitative guidance on which libraries should be chosen for different structural modeling studies. Here, we performed a comparative study of six widely used rotamer libraries and systematically examined their suitability for protein folding and sequence design in four aspects: (1) side-chain match accuracy, (2) side-chain conformation prediction, (3) de novo protein sequence design, and (4) computational time cost. We demonstrated that, compared to the backbone-dependent rotamer libraries (BBDRLs), the backbone-independent rotamer libraries (BBIRLs) generated conformations that more closely matched the native conformations due to the larger number of rotamers in the local rotamer search spaces. However, more practically, using an optimized physical energy function incorporated into a simulated annealing Monte Carlo searching scheme, we showed that utilization of the BBDRLs could result in higher accuracies in side-chain prediction and higher sequence recapitulation rates in protein design experiments. Detailed data analyses showed that the major advantage of BBDRLs lies in the energy term derived from the rotamer probabilities that are associated with the individual backbone torsion angle subspaces. This term is important for distinguishing between amino acid identities as well as the rotamer conformations of an amino acid. Meanwhile, the backbone torsion angle subspace-specific rotamer search drastically speeds up the searching time, despite the significantly larger number of total rotamers in the BBDRLs. These results should provide important guidance for the development and selection of rotamer libraries for practical protein design and structure prediction studies.

Construction of Escherichia coli BL21/A-53 producing histidine-tagged carboxymethylcellulase and comparison of its characteristics with CMCase without histidine-tag

To enhance recovery yield of carboxymethylcellulase (CMCase), E. coli BL21/A-53 producing the histidine-tagged CMCase was constructed in this study. The recovery yield of the histidine-tagged CMCase using the His-tag affinity chromatography was 39.8%. The predicted molecular weight of the histidine-tagged CMCase was determined as 56,260 Da. Its K_m and V_max were 9.3 g l^-1 and 76.3 g l^-1·min^-1, respectively. The histidine-tagged CMCase hydrolyzed avicel, carboxymethylcellulose (CMC), filter paper, pullulan, xylan, but there was no detectable activity on cellobiose, p-Nitrophenyl-β-D-glucopyranoside (pNPG). The optimal temperature and pH for the enzymatic reaction of the histidine-tagged CMCase was 50 °C and 5.0. The histidine-tagged CMCase was enhanced by CoCl₂ until the concentration of 100 mM, but inhibited by EDTA, HgCl₂, MnCl₂, NiCl₂, and RbCl₂. The characteristics of the histidine-tagged CMCase produced by E. coli BL21/A-53 were compared with those of CMCase without the histidine-tag of Bacillus subtilis subsp. subtilis A-53. The little changed characteristics of the histidine-tagged CMCase compared to the CMCase without a His-tag seemed to be the conformational change in the structure due to a His-tag.

Enhanced purification of histidine-tagged carboxymethylcellulase produced by Escherichia coli BL21/LBH-10 and comparison of its characteristics with carboxymethylcellulase without histidine-tag

To enhance purification yield of the carboxymethylcellulase (CMCase) of P. aquimaris LBH-10, E. coli BL21/LBH-10 was constructed to produce the six histidine-tagged CMCase (CMCase with a His-tag). The purification yield of the CMCase with a His-tag produced by E. coli BL21/LBH-10 was 44.4%. The molecular weight of the CMCase with a His-tag was determined as 56 kDa. Its K_m and V_max were 7.4 g/L and 70.9 g/L min, respectively. The CMCase with a His-tag hydrolyzed avicel, carboxymethylcellulose (CMC), filter paper, pullulan, and xylan but did not hydrolyze cellobiose and p-nitrophenyl-β-D-glucopyranoside. The optimal temperature for reaction was 50 °C and more than 75% of its original activity was maintained at broad temperatures ranging from 20 to 70 °C after 24 h. The optimal pH was 4.0 and more than 60% of its original activity was maintained at pH ranging from 4.0 to 7.0. The activity of the CMCase with a His-tag was enhanced by CoCl₂, KCl, PbCl₂, RbCl₂, and SrCl₂ until the concentration of 100 mM, but inhibited by EDTA, HgCl₂, MnCl₂, and NiCl₂. The characteristics of the CMCase with a His-tag produced by E. coli BL21/LBH-10 were little different from the CMCase without a His-tag, which seemed to resulted from the conformational change in the structure due to a His-tag. The purification yield of the CMCase with a His-tag using affinity chromatography from the cell broth after cell breakdown was proven to be more economic than that from the supernatant with its low concentration of cellulase.

Changing the Apoptosis Pathway through Evolutionary Protein Design

One obstacle in de novo protein design is the vast sequence space that needs to be searched through to obtain functional proteins. We developed a new method using structural profiles created from evolutionarily related proteins to constrain the simulation search process, with functions specified by atomic-level ligand-protein binding interactions. The approach was applied to redesigning the BIR3 domain of the X-linked inhibitor of apoptosis protein (XIAP), whose primary function is to suppress the cell death by inhibiting caspase-9 activity; however, the function of the wild-type XIAP can be eliminated by the binding of Smac peptides. Isothermal calorimetry and luminescence assay reveal that the designed XIAP domains can bind strongly with the Smac peptides but do not significantly inhibit the caspase-9 proteolytic activity in vitro compared with the wild-type XIAP protein. Detailed mutation assay experiments suggest that the binding specificity in the designs is essentially determined by the interplay of structural profile and physical interactions, which demonstrates the potential to modify apoptosis pathways through computational design.

Isoform-specific domain organization determines conformation and function of the peroxisomal biogenesis factor PEX26

Peroxisomal biogenesis factor PEX26 is a membrane anchor for the multi-subunit PEX1-PEX6 protein complex that controls ubiquitination and dislocation of PEX5 cargo receptors for peroxisomal matrix protein import. PEX26 associates with the peroxisomal translocation pore via PEX14 and a splice variant (PEX26Δex5) of unknown function has been reported. Here, we demonstrate PEX26 homooligomerization mediated by two heptad repeat domains adjacent to the transmembrane domain. We show that isoform-specific domain organization determines PEX26 oligomerization and impacts peroxisomal β-oxidation and proliferation. PEX26 and PEX26Δex5 displayed different patterns of interaction with PEX2-PEX10 or PEX13-PEX14 complexes, which relate to distinct pre-peroxisomes in the de novo synthesis pathway. Our data support an alternative PEX14-dependent mechanism of peroxisomal membrane association for the splice variant, which lacks a transmembrane domain. Structure-function relationships of PEX26 isoforms explain an extended function in peroxisomal homeostasis and these findings may improve our understanding of the broad phenotype of PEX26-associated human disorders.

An Evolution-Based Approach to De Novo Protein Design

EvoDesign is a computational algorithm that allows the rapid creation of new protein sequences that are compatible with specific protein structures. As such, it can be used to optimize protein stability, to resculpt the protein surface to eliminate undesired protein-protein interactions, and to optimize protein-protein binding. A major distinguishing feature of EvoDesign in comparison to other protein design programs is the use of evolutionary information in the design process to guide the sequence search toward native-like sequences known to adopt structurally similar folds as the target. The observed frequencies of amino acids in specific positions in the structure in the form of structural profiles collected from proteins with similar folds and complexes with similar interfaces can implicitly capture many subtle effects that are essential for correct folding and protein-binding interactions. As a result of the inclusion of evolutionary information, the sequences designed by EvoDesign have native-like folding and binding properties not seen by other physics-based design methods. In this chapter, we describe how EvoDesign can be used to redesign proteins with a focus on the computational and experimental procedures that can be used to validate the designs.

Diiron centre mutations in Ciona intestinalis alternative oxidase abolish enzymatic activity and prevent rescue of cytochrome oxidase deficiency in flies

The mitochondrial alternative oxidase, AOX, carries out the non proton-motive re-oxidation of ubiquinol by oxygen in lower eukaryotes, plants and some animals. Here we created a modified version of AOX from Ciona instestinalis, carrying mutations at conserved residues predicted to be required for chelation of the diiron prosthetic group. The modified protein was stably expressed in mammalian cells or flies, but lacked enzymatic activity and was unable to rescue the phenotypes of flies knocked down for a subunit of cytochrome oxidase. The mutated AOX transgene is thus a potentially useful tool in studies of the physiological effects of AOX expression.

Structure, function and evolution of the animal mitochondrial replicative DNA helicase

The mitochondrial replicative DNA helicase is essential for animal mitochondrial DNA (mtDNA) maintenance. Deleterious mutations in the gene that encodes it cause mitochondrial dysfunction manifested in developmental delays, defects and arrest, limited life span, and a number of human pathogenic phenotypes that are recapitulated in animals across taxa. In fact, the replicative mtDNA helicase was discovered with the identification of human disease mutations in its nuclear gene, and based upon its deduced amino acid sequence homology with bacteriophage T7 gene 4 protein (T7 gp4), a bi-functional primase-helicase. Since that time, numerous investigations of its structure, mechanism, and physiological relevance have been reported, and human disease alleles have been modeled in the human, mouse, and Drosophila systems. Here, we review this literature and draw evolutionary comparisons that serve to shed light on its divergent features.

Staying green postharvest: how three mutations in the Arabidopsis chlorophyll b reductase gene NYC1 delay degreening by distinct mechanisms

Stresses such as energy deprivation, wounding and water-supply disruption often contribute to rapid deterioration of harvested tissues. To uncover the genetic regulation behind such stresses, a simple assessment system was used to detect senescence mutants in conjunction with two rapid mapping techniques to identify the causal mutations. To demonstrate the power of this approach, immature inflorescences of Arabidopsis plants that contained ethyl methanesulfonate-induced lesions were detached and screened for altered timing of dark-induced senescence. Numerous mutant lines displaying accelerated or delayed timing of senescence relative to wild type were discovered. The underlying mutations in three of these were identified using High Resolution Melting analysis to map to a chromosomal arm followed by a whole-genome sequencing-based mapping method, termed 'Needle in the K-Stack', to identify the causal lesions. All three mutations were single base pair changes and occurred in the same gene, NON-YELLOW COLORING1 (NYC1), a chlorophyll b reductase of the short-chain dehydrogenase/reductase (SDR) superfamily. This was consistent with the mutants preferentially retaining chlorophyll b, although substantial amounts of chlorophyll b were still lost. The single base pair mutations disrupted NYC1 function by three distinct mechanisms, one by producing a termination codon, the second by interfering with correct intron splicing and the third by replacing a highly conserved proline with a non-equivalent serine residue. This non-synonymous amino acid change, which occurred in the NADPH binding domain of NYC1, is the first example of such a mutation in an SDR protein inhibiting a physiological response in plants.

Crystal structure of designed PX domain from cytokine-independent survival kinase and implications on evolution-based protein engineering

The Phox homology domain (PX domain) is a phosphoinositide-binding structural domain that is critical in mediating protein and cell membrane association and has been found in more than 100 eukaryotic proteins. The abundance of PX domains in nature offers an opportunity to redesign the protein using EvoDesign, a computational approach to design new sequences based on structure profiles of multiple evolutionarily related proteins. In this study, we report the X-ray crystallographic structure of a designed PX domain from the cytokine-independent survival kinase (CISK), which has been implicated as functioning in parallel with PKB/Akt in cell survival and insulin responses. Detailed data analysis of the designed CISK-PX protein demonstrates positive impacts of knowledge-based secondary structure and solvation predictions and structure-based sequence profiles on the efficiency of the evolutionary-based protein design method. The structure of the designed CISK-PX domain is close to the wild-type (1.54 Å in Cα RMSD), which was accurately predicted by I-TASSER based fragment assembly simulations (1.32 Å in Cα RMSD). This study represents the first successfully designed conditional peripheral membrane protein fold and has important implications in the examination and experimental validation of the evolution-based protein design approaches.

Evolution of the metazoan mitochondrial replicase

The large number of complete mitochondrial DNA (mtDNA) sequences available for metazoan species makes it a good system for studying genome diversity, although little is known about the mechanisms that promote and/or are correlated with the evolution of this organellar genome. By investigating the molecular evolutionary history of the catalytic and accessory subunits of the mtDNA polymerase, pol γ, we sought to develop mechanistic insight into its function that might impact genome structure by exploring the relationships between DNA replication and animal mitochondrial genome diversity. We identified three evolutionary patterns among metazoan pol γs. First, a trend toward stabilization of both sequence and structure occurred in vertebrates, with both subunits evolving distinctly from those of other animal groups, and acquiring at least four novel structural elements, the most important of which is the HLH-3β (helix-loop-helix, 3 β-sheets) domain that allows the accessory subunit to homodimerize. Second, both subunits of arthropods and tunicates have become shorter and evolved approximately twice as rapidly as their vertebrate homologs. And third, nematodes have lost the gene for the accessory subunit, which was accompanied by the loss of its interacting domain in the catalytic subunit of pol γ, and they show the highest rate of molecular evolution among all animal taxa. These findings correlate well with the mtDNA genomic features of each group described above, and with their modes of DNA replication, although a substantive amount of biochemical work is needed to draw conclusive links regarding the latter. Describing the parallels between evolution of pol γ and metazoan mtDNA architecture may also help in understanding the processes that lead to mitochondrial dysfunction and to human disease-related phenotypes.

Physics-based protein structure refinement through multiple molecular dynamics trajectories and structure averaging

We used molecular dynamics (MD) simulations for structure refinement of Critical Assessment of Techniques for Protein Structure Prediction 10 (CASP10) targets. Refinement was achieved by selecting structures from the MD-based ensembles followed by structural averaging. The overall performance of this method in CASP10 is described, and specific aspects are analyzed in detail to provide insight into key components. In particular, the use of different restraint types, sampling from multiple short simulations versus a single long simulation, the success of a quality assessment criterion, the application of scoring versus averaging, and the impact of a final refinement step are discussed in detail.

Recent advances in functional region prediction by using structural and evolutionary information - Remaining problems and future extensions

Structural genomics projects have solved many new structures with unknown functions. One strategy to investigate the function of a structure is to computationally find the functionally important residues or regions on it. Therefore, the development of functional region prediction methods has become an important research subject. An effective approach is to use a method employing structural and evolutionary information, such as the evolutionary trace (ET) method. ET ranks the residues of a protein structure by calculating the scores for relative evolutionary importance, and locates functionally important sites by identifying spatial clusters of highly ranked residues. After ET was developed, numerous ET-like methods were subsequently reported, and many of them are in practical use, although they require certain conditions. In this mini review, we first introduce the remaining problems and the recent improvements in the methods using structural and evolutionary information. We then summarize the recent developments of the methods. Finally, we conclude by describing possible extensions of the evolution- and structure-based methods.

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.

Intramolecular clasp of the cellulosomal Ruminococcus flavefaciens ScaA dockerin module confers structural stability

The cellulosome is a large extracellular multi-enzyme complex that facilitates the efficient hydrolysis and degradation of crystalline cellulosic substrates. During the course of our studies on the cellulosome of the rumen bacterium Ruminococcus flavefaciens, we focused on the critical ScaA dockerin (ScaADoc), the unique dockerin that incorporates the primary enzyme-integrating ScaA scaffoldin into the cohesin-bearing ScaB adaptor scaffoldin. In the absence of a high-resolution structure of the ScaADoc module, we generated a computational model, and, upon its analysis, we were surprised to discover a putative stacking interaction between an N-terminal Trp and a C-terminal Pro, which we termed intramolecular clasp. In order to verify the existence of such an interaction, these residues were mutated to alanine. Circular dichroism spectroscopy, intrinsic tryptophan and ANS fluorescence, and NMR spectroscopy indicated that mutation of these residues has a destabilizing effect on the functional integrity of the Ca²⁺-bound form of ScaADoc. Analysis of recently determined dockerin structures from other species revealed the presence of other well-defined intramolecular clasps, which consist of different types of interactions between selected residues at the dockerin termini. We propose that this thematic interaction may represent a major distinctive structural feature of the dockerin module.

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A structural model for the Ruminococcus flavefaciens ScaA dockerin is proposed.

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A stacking interaction between N- and C-terminal residues was derived from the model.

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Mutations of putative interacting residues resulted in reduced stability and binding.

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Similar intramodular “clasp” interactions were observed in other dockerin structures.

EvoDesign: De novo protein design based on structural and evolutionary profiles

Protein design aims to identify new protein sequences of desirable structure and biological function. Most current de novo protein design methods rely on physics-based force fields to search for low free-energy states following Anfinsen’s thermodynamic hypothesis. A major obstacle of such approaches is the inaccuracy of the force field design, which cannot accurately describe the atomic interactions or distinguish correct folds. We developed a new web server, EvoDesign, to design optimal protein sequences of given scaffolds along with multiple sequence and structure-based features to assess the foldability and goodness of the designs. EvoDesign uses an evolution-profile–based Monte Carlo search with the profiles constructed from homologous structure families in the Protein Data Bank. A set of local structure features, including secondary structure, torsion angle and solvation, are predicted by single-sequence neural-network training and used to smooth the sequence motif and accommodate the physicochemical packing. The EvoDesign algorithm has been extensively tested in large-scale protein design experiments, which demonstrate enhanced foldability and structural stability of designed sequences compared with the physics-based designing methods. The EvoDesign server is freely available at http://zhanglab.ccmb.med.umich.edu/EvoDesign.

Energy functions in de novo protein design: current challenges and future prospects

In the past decade, a concerted effort to successfully capture specific tertiary packing interactions produced specific three-dimensional structures for many de novo designed proteins that are validated by nuclear magnetic resonance and/or X-ray crystallographic techniques. However, the success rate of computational design remains low. In this review, we provide an overview of experimentally validated, de novo designed proteins and compare four available programs, RosettaDesign, EGAD, Liang-Grishin, and RosettaDesign-SR, by assessing designed sequences computationally. Computational assessment includes the recovery of native sequences, the calculation of sizes of hydrophobic patches and total solvent-accessible surface area, and the prediction of structural properties such as intrinsic disorder, secondary structures, and three-dimensional structures. This computational assessment, together with a recent community-wide experiment in assessing scoring functions for interface design, suggests that the next-generation protein-design scoring function will come from the right balance of complementary interaction terms. Such balance may be found when more negative experimental data become available as part of a training set.

A computational prediction of structure and function of novel homologue of Arabidopsis thaliana Vps51/Vps67 subunit in Corchorus olitorius

Vps mediated vesicular transport is important for transferring macromolecules trapped inside a vesicle. Although highly abundant, Vps shows tremendous sequence variation among diverse array of species. However, this difference in sequence, which seems to also translate into substantial functional variation, is hardly characterized in Corchorus spp. Here, our computational study investigates structural and functional features of one of the Vps subunit namely Vps51/Vps67 in C. olitorius. Broad scale structural characterization revealed novel information about the overall Vps structure and binding sites. Moreover, functional analyses indicate interaction partners which were unexplored to date. Since membrane trafficking is essentially associated with nutrient uptake and chemical de-toxification, characterization of the Vps subunit can well provide us with better insight into important agronomic traits such as stress response, immune response and phytoremediation capacity.

In silico and in vivo studies of an Arabidopsis thaliana gene, ACR2, putatively involved in arsenic accumulation in plants

Previously, our in silico analyses identified four candidate genes that might be involved in uptake and/or accumulation of arsenics in plants: arsenate reductase 2 (ACR2), phytochelatin synthase 1 (PCS1) and two multi-drug resistant proteins (MRP1 and MRP2) [Lund et al. (2010) J Biol Syst 18:223-224]. We also postulated that one of these four genes, ACR2, seems to play a central role in this process. To investigate further, we have constructed a 3D structure of the Arabidopsis thaliana ACR2 protein using the iterative implementation of the threading assembly refinement (I-TASSER) server. These analyses revealed that, for catalytic metabolism of arsenate, the arsenate binding-loop (AB-loop) and residues Phe-53, Phe-54, Cys-134, Cys-136, Cys-141, Cys-145, and Lys-135 are essential for reducing arsenate to arsenic intermediates (arsenylated enzyme-substrate intermediates) and arsenite in plants. Thus, functional predictions suggest that the ACR2 protein is involved in the conversion of arsenate to arsenite in plant cells. To validate the in silico results, we exposed a transfer-DNA (T-DNA)-tagged mutant of A. thaliana (mutation in the ACR2 gene) to various amounts of arsenic. Reverse transcriptase PCR revealed that the mutant exhibits significantly reduced expression of the ACR2 gene. Spectrophotometric analyses revealed that the amount of accumulated arsenic compounds in this mutant was approximately six times higher than that observed in control plants. The results obtained from in silico analyses are in complete agreement with those obtained in laboratory experiments.

Coarse-grain Protein Models

Coarse-graining is a powerful approach for modeling biomolecules that, over the last few decades, has been extensively applied to proteins. Coarse-grain models offer access to large systems and to slow processes without becoming computationally unmanageable. In addition, they are very versatile, enabling both the protein representation and the energy function to be adapted to the biological problem in hand. This review concentrates on modeling soluble proteins and their assemblies. It presents an overview of the coarse-grain representations, of the associated interaction potentials, and of the optimization procedures used to define them. It then shows how coarse-grain models have been used to understand processes involving proteins, from their initial folding to their functional properties, their binary interactions, and the assembly of large complexes.

Further evidence for the likely completeness of the library of solved single domain protein structures

Recent studies questioned whether the Protein Data Bank (PDB) contains all compact, single domain protein structures. Here, we show that all quasi-spherical, QS, random protein structures devoid of secondary structure are in the PDB and are excellent templates for all native PDB proteins up to 250 residues. Because QS templates have a similar global contour as native, TASSER can refine 98% (90%) of those whose TM-score is 0.4 (0.35) to structures greater than or equal to the 0.5 TM-score threshold (0.74 (0.64) mean TM-score) for CATH/SCOP assignment. On the basis of this and the fact that, at a TM-score of 0.4, 83% (90%) of all (internal) core secondary structure elements are recovered, a 0.40 TM-score is an appropriate fold similarity assignment threshold. Despite the claims of Taylor, Trovato, and Zhou that many of their structures lack a PDB counterpart, using fr-TM-align, at a 0.45 (0.5) TM-score threshold, essentially all (most) are found in the PDB. Thus, the conclusion that the PDB is likely complete is further supported.

Why not consider a spherical protein? Implications of backbone hydrogen bonding for protein structure and function

The intrinsic ability of protein structures to exhibit the geometric features required for molecular function in the absence of evolution is examined in the context of three systems: the reference set of real, single domain protein structures, a library of computationally generated, compact homopolypeptides, artificial structures with protein-like secondary structural elements, and quasi-spherical random proteins packed at the same density as proteins but lacking backbone secondary structure and hydrogen bonding. Without any evolutionary selection, the library of artificial structures has similar backbone hydrogen bonding, global shape, surface to volume ratio and statistically significant structural matches to real protein global structures. Moreover, these artificial structures have native like ligand binding cavities, and a tiny subset has interfacial geometries consistent with native-like protein-protein interactions and DNA binding. In contrast, the quasi-spherical random proteins, being devoid of secondary structure, have a lower surface to volume ratio and lack ligand binding pockets and intermolecular interaction interfaces. Surprisingly, these quasi-spherical random proteins exhibit protein like distributions of virtual bond angles and almost all have a statistically significant structural match to real protein structures. This implies that it is local chain stiffness, even without backbone hydrogen bonding, and compactness that give rise to the likely completeness of the library solved single domain protein structures. These studies also suggest that the packing of secondary structural elements generates the requisite geometry for intermolecular binding. Thus, backbone hydrogen bonding plays an important role not only in protein structure but also in protein function. Such ability to bind biological molecules is an inherent feature of protein structure; if combined with appropriate protein sequences, it could provide the non-zero background probability for low-level function that evolution requires for selection to occur.