Protein structure prediction: challenging targets for CASP10

Role of environmental specificity in CASP results

BACKGROUND

Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Prediction) competition. However, the question of the mechanism behind the protein folding process itself remains unanswered. Correctly predicting the structure also does not solve the problem of, for example, amyloid proteins, where a polypeptide chain with an unaltered sequence adopts a different 3D structure.

RESULTS

This work was an attempt at explaining the structural variation by considering the contribution of the environment to protein structuring. The application of the fuzzy oil drop (FOD) model to assess the validity of the selected models provided in the CASP13, CASP14 and CASP15 projects reveals the need for an environmental factor to determine the 3D structure of proteins. Consideration of the external force field in the form of polar water (Fuzzy Oil Drop) and a version modified by the presence of the hydrophobic compounds, FOD-M (FOD-Modified) reveals that the protein folding process is environmentally dependent. An analysis of selected models from the CASP competitions indicates the need for structure prediction as dependent on the consideration of the protein folding environment.

CONCLUSIONS

The conditions governed by the environment direct the protein folding process occurring in a certain environment. Therefore, the variation of the external force field should be taken into account in the models used in protein structure prediction.

Engineering a multi epitope vaccine against SARS-CoV-2 by exploiting its non structural and structural proteins

SARS-CoV-2, the causative agent behind the ongoing pandemic exhibits an enhanced potential for infection when compared to its related family members- the SARS-CoV and MERS-CoV; which have caused similar disease outbreaks in the past. The severity of the global health burden, increasing mortality rate and the emergent economic crisis urgently demands the development of next generation vaccines. Amongst such emergent next generation vaccines are the multi-epitope subunit vaccines, which hold promise in combating deadly pathogens. In this study we have exploited immunoinformatics applications to delineate a vaccine candidate possessing multiple B and T cells epitopes by utilizing the SARS-CoV-2 non structural and structural proteins. The antigenicity potential, safety, structural stability and the production feasibility of the designed construct was evaluated computationally. Furthermore, due to the known role of human TLR-3 immune receptor in viral sensing, which facilitates host cells activation for an immune response, the vaccine construct was examined for its binding efficiency using molecular docking and molecular dynamics simulation studies, which resulted in strong and stable interactions. Finally, the immune simulation studies suggested an effective immune response on vaccine administration. Overall, the immunoinformatics analysis advocates that the proposed vaccine candidate is safe and immunogenic and therefore can be pushed as a lead for in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

Probabilistic divergence of a template-based modelling methodology from the ideal protocol

Protein structural information is essential for the detailed mapping of a functional protein network. For a higher modelling accuracy and quicker implementation, template-based algorithms have been extensively deployed and redefined. The methods only assess the predicted structure against its native state/template and do not estimate the accuracy for each modelling step. A divergence measure is therefore postulated to estimate the modelling accuracy against its theoretical optimal benchmark. By freezing the domain boundaries, the divergence measures are predicted for the most crucial steps of a modelling algorithm. To precisely refine the score using weighting constants, big data analysis could further be deployed.

Excavating the functionally crucial active-site residues of the DXS protein of Bacillus subtilis by exploring its closest homologues

Background

To achieve a high yield of terpenoid-based therapeutics, 1-deoxy-d-xylulose-5-phosphate (DXP) pathway has been significantly exploited for the production of downstream enzymes. The DXP synthase (DXS) enzyme, the initiator of this pathway, is pivotal for the convergence of carbon flux, and is computationally studied well for the industrially utilized generally regarded as safe (GRAS) bacterium Bacillus subtilis to decode its vital regions for aiding the construction of a functionally improved mutant library.

Results

For the 546 sequence dataset of DXS sequences, a representative set of 108 sequences is created, and it shows a significant evolutionary divergence across different species clubbed into 37 clades, whereas three clades are observed for the 76 sequence dataset of Bacillus subtilis. The DXS enzyme, sharing a statistically significant homology to transketolase, is shown to be evolutionarily too distant. By the mutual information-based co-evolutionary network and hotspot analysis, the most crucial loci within the active site are deciphered. The 650-residue representative structure displays a complete conservation of 114 loci, and only two co-evolving residues ASP154 and ILE371 are found to be the conserved ones. Lastly, P318D is predicted to be the top-ranked mutation causing the increase in the thermodynamic stability of 6OUW.

Conclusion

The study excavates the vital functional, phylogenetic, and conserved residues across the active site of the DXS protein, the key rate-limiting controller of the entire pathway. It would aid to computationally understand the evolutionary landscape of this industrially useful enzyme and would allow us to widen its substrate repertoire to increase the enzymatic yield of unnatural molecules for in vivo and in vitro applications.

Refined template selection and combination algorithm significantly improves template-based modeling accuracy

In contrast to ab-initio protein modeling methodologies, comparative modeling is considered as the most popular and reliable algorithm to model protein structure. However, the selection of the best set of templates is still a major challenge. An effective template-ranking algorithm is developed to efficiently select only the reliable hits for predicting the protein structures. The algorithm employs the pairwise as well as multiple sequence alignments of template hits to rank and select the best possible set of templates. It captures several key sequences and structural information of template hits and converts into scores to effectively rank them. This selected set of templates is used to model a target. Modeling accuracy of the algorithm is tested and evaluated on TBM-HA domain containing CASP8, CASP9 and CASP10 targets. On an average, this template ranking and selection algorithm improves GDT-TS, GDT-HA and TM_Score by 3.531, 4.814 and 0.022, respectively. Further, it has been shown that the inclusion of structurally similar templates with ample conformational diversity is crucial for the modeling algorithm to maximally as well as reliably span the target sequence and construct its near-native model. The optimal model sampling also holds the key to predict the best possible target structure.

Decoding the vital segments in human ATP-dependent RNA helicase

An analysis of the ATP-dependent RNA helicase using known functionally close analogs helps disclose the structural and functional information of the enzyme. The enzyme plays several interlinked biological functions and there is an urgent need to interpret its key active-site residues to infer function and establish role. The human protein q96c10.1 is annotated using tools such as interpro, go and cdd. The physicochemical properties are estimated using the tool protparam. We describe the enzyme protein model developed using modeller to identify active site residues. We used consurf to estimate the structural conservation and is evolutionary relationship is inferred using known close sequence homologs. The active site is predicted using castp and its topological flexibility is estimated through cabs-flex. The protein is annotated as a hydrolase using available data and ddx58 is found as its top-ranked interacting protein partner. We show that about 124 residues are found to be highly conserved among 259 homologs, clustered in 7 clades with the active-site showing low sequence conservation. It is further shown that only 9 loci among the 42 active-site residues are conserved with limited structural fluctuation from the wild type structure. Thus, we document various useful information linked to function, sequence similarity and phylogeny of the enzyme for annotation as potential helicase as designated by uniprot. Data shows limited degree of conserved sequence segments with topological flexibility unlike in other subfamily members of the protein.

Structure prediction of polyglutamine disease proteins: comparison of methods

Background

The expansion of polyglutamine (poly-Q) repeats in several unrelated proteins is associated with at least ten neurodegenerative diseases. The length of the poly-Q regions plays an important role in the progression of the diseases. The number of glutamines (Q) is inversely related to the onset age of these polyglutamine diseases, and the expansion of poly-Q repeats has been associated with protein misfolding. However, very little is known about the structural changes induced by the expansion of the repeats. Computational methods can provide an alternative to determine the structure of these poly-Q proteins, but it is important to evaluate their performance before large scale prediction work is done.

Results

In this paper, two popular protein structure prediction programs, I-TASSER and Rosetta, have been used to predict the structure of the N-terminal fragment of a protein associated with Huntington's disease with 17 glutamines. Results show that both programs have the ability to find the native structures, but I-TASSER performs better for the overall task.

Conclusions

Both I-TASSER and Rosetta can be used for structure prediction of proteins with poly-Q repeats. Knowledge of poly-Q structure may significantly contribute to development of therapeutic strategies for poly-Q diseases.

Ultrafast hydrogen exchange reveals specific structural events during the initial stages of folding of cytochrome c

Many proteins undergo a sharp decrease in chain dimensions during early stages of folding, prior to the rate-limiting step in folding. However, it remains unclear whether compact states are the result of specific folding events or a general hydrophobic collapse of the poly peptide chain driven by the change in solvent conditions. To address this fundamental question, we extended the temporal resolution of NMR-detected H/D exchange labeling experiments into the microsecond regime by adopting a microfluidics approach. By observing the competition between H/D exchange and folding as a function of labeling pH, coupled with direct measurement of exchange rates in the unfolded state, we were able to monitor hydrogen-bond formation for over 50 individual backbone NH groups within the initial 140 microseconds of folding of horse cytochrome c. Clusters of solvent-shielded amide protons were observed in two α-helical segments in the C-terminal half of the protein, while the N-terminal helix remained largely unstructured, suggesting that proximity in the primary structure is a major factor in promoting helix formation and association at early stages of folding, while the entropically more costly long-range contacts between the N- and C-terminal helices are established only during later stages. Our findings clearly indicate that the initial chain condensation in cytochrome c is driven by specific interactions among a subset of α-helical segments rather than a general hydrophobic collapse.

Uncovering the determinants of a highly perturbed tyrosine pKa in the active site of ketosteroid isomerase

Within the idiosyncratic enzyme active-site environment, side chain and ligand pKa values can be profoundly perturbed relative to their values in aqueous solution. Whereas structural inspection of systems has often attributed perturbed pKa values to dominant contributions from placement near charged groups or within hydrophobic pockets, Tyr57 of a Pseudomonas putida ketosteroid isomerase (KSI) mutant, suggested to have a pKa perturbed by nearly 4 units to 6.3, is situated within a solvent-exposed active site devoid of cationic side chains, metal ions, or cofactors. Extensive comparisons among 45 variants with mutations in and around the KSI active site, along with protein semisynthesis, (13)C NMR spectroscopy, absorbance spectroscopy, and X-ray crystallography, was used to unravel the basis for this perturbed Tyr pKa. The results suggest that the origin of large energetic perturbations are more complex than suggested by visual inspection. For example, the introduction of positively charged residues near Tyr57 raises its pKa rather than lowers it; this effect, and part of the increase in the Tyr pKa from the introduction of nearby anionic groups, arises from accompanying active-site structural rearrangements. Other mutations with large effects also cause structural perturbations or appear to displace a structured water molecule that is part of a stabilizing hydrogen-bond network. Our results lead to a model in which three hydrogen bonds are donated to the stabilized ionized Tyr, with these hydrogen-bond donors, two Tyr side chains, and a water molecule positioned by other side chains and by a water-mediated hydrogen-bond network. These results support the notion that large energetic effects are often the consequence of multiple stabilizing interactions rather than a single dominant interaction. Most generally, this work provides a case study for how extensive and comprehensive comparisons via site-directed mutagenesis in a tight feedback loop with structural analysis can greatly facilitate our understanding of enzyme active-site energetics. The extensive data set provided may also be a valuable resource for those wishing to extensively test computational approaches for determining enzymatic pKa values and energetic effects.