Insights on protein thermal stability: a graph representation of molecular interactions

Machine Learning Based Predictive Model for the Analysis of Sequence Activity Relationships Using Protein Spectra and Protein Descriptors

Accurately establishing the connection between a protein sequence and its function remains a focal point within the field of protein engineering, especially in the context of predicting the effects of mutations. From this, there has been a continued drive to build accurate and reliable predictive models via machine learning that allow for the virtual screening of many protein mutant sequences, measuring the relationship between sequence and 'fitness' or 'activity', commonly known as a Sequence-Activity-Relationship (SAR). An important preliminary stage in the building of these predictive models is the encoding of the chosen sequences. Evaluated in this work is a plethora of encoding strategies using the Amino Acid Index database, where the indices are transformed into their spectral form via Digital Signal Processing (DSP) techniques, as well as numerous protein structural and physiochemical descriptors. The encoding strategies are explored on a dataset curated to measure the thermostability of various mutants from a recombination library, designed from parental cytochrome P450s. In this work it was concluded that the implementation of protein spectra in concatenation with protein descriptors, together with the Partial Least Squares Regression (PLS) algorithm, gave the most noteworthy increase in the quality of the predictive models (as described in Encoding Strategy C), highlighting their utility in identifying an SAR. The accompanying software produced for this paper is termed pySAR (Python Sequence-Activity-Relationship), which allows for a user to find the optimal arrangement of structural and or physiochemical properties to encode their specific mutant library dataset; the source code is available at: https://github.com/amckenna41/pySAR.

Inferring the stabilization effects of SARS-CoV-2 variants on the binding with ACE2 receptor

As the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic continues to spread, several variants of the virus, with mutations distributed all over the viral genome, are emerging. While most of the variants present mutations having little to no effects at the phenotypic level, some of these variants are spreading at a rate that suggests they may present a selective advantage. In particular, these rapidly spreading variants present specific mutations on the spike protein. These observations call for an urgent need to characterize the effects of these variants’ mutations on phenotype features like contagiousness and antigenicity. With this aim, we performed molecular dynamics simulations on a selected set of possible spike variants in order to assess the stabilizing effect of particular amino acid substitutions on the molecular complex. We specifically focused on the mutations that are both characteristic of the top three most worrying variants at the moment, i.e the English, South African, and Amazonian ones, and that occur at the molecular interface between SARS-CoV-2 spike protein and its human ACE2 receptor. We characterize these variants’ effect in terms of (i) residue mobility, (ii) compactness, studying the network of interactions at the interface, and (iii) variation of shape complementarity via expanding the molecular surfaces in the Zernike basis. Overall, our analyses highlighted greater stability of the three variant complexes with respect to both the wild type and two negative control systems, especially for the English and Amazonian variants. In addition, in the three variants, we investigate the effects a not-yet observed mutation in position 501 could provoke on complex stability. We found that a phenylalanine mutation behaves similarly to the English variant and may cooperate in further increasing the stability of the South African one, hinting at the need for careful surveillance for the emergence of these mutations in the population. Ultimately, we show that the proposed observables describe key features for the stability of the ACE2-spike complex and can help to monitor further possible spike variants.

Miotto et al. perform molecular dynamics simulations on a selected set of possible SARS-CoV-2 spike variants in order to assess the stabilizing effect of particular amino acid substitutions on the molecular complex. Their analysis can help to monitor further possible spike variants.

OUP accepted manuscript

Motivation

Thermal properties of proteins are of great importance for a number of theoretical and practical implications. Predicting the thermal stability of a protein is a difficult and still scarcely addressed task.

Results

Here, we introduce Thermometer, a webserver to assess the thermal stability of a protein using structural information. Thermometer is implemented as a publicly available, user-friendly interface.

Availability and implementation

Our server can be found at the following link (all major browser supported): http://service.tartaglialab.com/new_submission/thermometer_file.

Supplementary information

Supplementary data are available at Bioinformatics online.

Structure and Thermal Stability of wtRop and RM6 Proteins through All-Atom Molecular Dynamics Simulations and Experiments

In the current work we study, via molecular simulations and experiments, the folding and stability of proteins from the tertiary motif of 4-α-helical bundles, a recurrent motif consisting of four amphipathic α-helices packed in a parallel or antiparallel fashion. The focus is on the role of the loop region in the structure and the properties of the wild-type Rop (wtRop) and RM6 proteins, exploring the key factors which can affect them, through all-atom molecular dynamics (MD) simulations and supporting by experimental findings. A detailed investigation of structural and conformational properties of wtRop and its RM6 loopless mutation is presented, which display different physical characteristics even in their native states. Then, the thermal stability of both proteins is explored showing RM6 as more thermostable than wtRop through all studied measures. Deviations from native structures are detected mostly in tails and loop regions and most flexible residues are indicated. Decrease of hydrogen bonds with the increase of temperature is observed, as well as reduction of hydrophobic contacts in both proteins. Experimental data from circular dichroism spectroscopy (CD), are also presented, highlighting the effect of temperature on the structural integrity of wtRop and RM6. The central goal of this study is to explore on the atomic level how a protein mutation can cause major changes in its physical properties, like its structural stability.

Factors deciding the assembly and thermostability of the DmrB cage

Dihydromethanopterin reductase (DmrB), is a naturally occurring cage protein found in various archaeal and a few bacterial species. It exists as 24mer with cubic geometry where 8 trimeric subunits are present at the corners of each cube. Each trimer is made up of three monomeric units and six FMN, where two molecules of FMN are present at the interface of each monomer. DmrB is involved in the conversion of dihydromethanopterin to tetrahydromethanopterin using FMN as a redox equivalent. In the present study, we have used spectroscopic and biochemical techniques along with complementary bio-informatic work to understand the assembly principles of the DmrB. Our results show a concentration dependant self-assembly of DmrB which is mediated by ionic interactions. The co-factor FMN stabilizes and preserves the secondary and quaternary structure of DmrB against thermal insult, indicating that the higher order assembly of DmrB is very thermostable. Our work provides an interesting piece of information regarding the role of the co-factors in the thermostability of these classes of cage proteins. The understanding of the assembly and disassembly of this thermostable cage would enable the downstream usage of this system in various nano-biotechnological applications.

A combined pH and temperature precipitation step facilitates the purification of tobacco-derived recombinant proteins that are sensitive to extremes of either parameter

Incubation at pH 4.0 or blanching at ∼65°C facilitates the purification of biopharmaceutical proteins from plants by precipitating most of the host cell proteins (HCPs) before chromatography. However, both methods are compatible only with pH or thermostable target proteins whereas many target proteins may irreversibly denature, e.g., at pH < 4.0. Here, we developed a combined pH/temperature treatment for clarified tobacco extracts and intact leaves. The latter were subjected to a blanching procedure, i.e., the submersion into a hot buffer. Using a design of experiments approach we identified conditions that remove ∼70% of HCPs at ∼55°C, using the thermosensitive antibody 2G12 and the pH-sensitive DsRed as model proteins. We found that pH and temperature exerted a combined effect during the precipitation of HCPs in the pH range 5.0-7.0 at 35°C-60°C. For clarified extracts, the temperature required to achieve a DsRed purity threshold of 20% total soluble protein (TSP) increased from 54°C to 63°C when the pH was increased from 6.4 to 7.3. The pH-stable antibody 2G12 was less responsive to the combined treatment, but the purity of 1% TSP was achieved at 35°C instead of 44°C when the pH was reduced from 6.3 to 5.8. When blanching intact leaves, product losses were not exacerbated at pH 4.0. Indeed, the highest DsRed purity (58% TSP) was achieved at this pH, combined with a temperature of 60°C and an incubation time of 30 min. In contrast, the highest 2G12 purity (0.7% TSP) was achieved at pH 5.1 and 40°C with an incubation time of 20 min. Our data suggest that a combined pH/temperature regime can avoid extreme values of either parameter; therefore, broadening the applicability of these simple purification techniques to other recombinant proteins.

Dynamic cross correlation analysis of Thermus thermophilus alkaline phosphatase and determinants of thermostability

BACKGROUND

Understanding the determinants of protein thermostability is very important both from the theoretical and applied perspective. One emerging view in thermostable enzymes seems to indicate that a salt bridge/charged residue network plays a fundamental role in their thermostability.

METHODS

The structure of alkaline phosphatase (AP) from Thermus thermophilus HB8 was solved by X-ray crystallography at 2.1 Å resolution. The obtained structure was further analyzed by molecular dynamics studies at different temperatures (303 K, 333 K and 363 K) and compared to homologous proteins from the cold-adapted organisms Shewanella sp. and Vibrio strain G15-21. To analyze differences in measures of dynamic variation, several data reduction techniques like principal component analysis (PCA), residue interaction network (RIN) analysis and rotamer analysis were used. Using hierarchical clustering, the obtained results were combined to determine residues showing high degree dynamical variations due to temperature jumps. Furthermore, dynamic cross correlation (DCC) analysis was carried out to characterize networks of charged residues.

RESULTS

Top clustered residues showed a higher propensity for thermostabilizing mutations, indicating evolutionary pressure acting on thermophilic organisms. The description of rotamer distributions by Gini coefficients and Kullback-Leibler (KL) divergence both revealed significant correlations with temperature. DCC analysis revealed a significant trend to de-correlation of the movement of charged residues at higher temperatures.

SIGNIFICANCE

The de-correlation of charged residues detected in Thermus thermophilus AP, highlights the importance of dynamic electrostatic network interactions for the thermostability of this enzyme.

Characterizing Hydropathy of Amino Acid Side Chain in a Protein Environment by Investigating the Structural Changes of Water Molecules Network

Assessing the hydropathy properties of molecules, like proteins and chemical compounds, has a crucial role in many fields of computational biology, such as drug design, biomolecular interaction, and folding prediction. Over the past decades, many descriptors were devised to evaluate the hydrophobicity of side chains. In this field, recently we likewise have developed a computational method, based on molecular dynamics data, for the investigation of the hydrophilicity and hydrophobicity features of the 20 natural amino acids, analyzing the changes occurring in the hydrogen bond network of water molecules surrounding each given compound. The local environment of each residue is complex and depends on the chemical nature of the side chain and the location in the protein. Here, we characterize the solvation properties of each amino acid side chain in the protein environment by considering its spatial reorganization in the protein local structure, so that the computational evaluation of differences in terms of hydropathy profiles in different structural and dynamical conditions can be brought to bear. A set of atomistic molecular dynamics simulations have been used to characterize the dynamic hydrogen bond network at the interface between protein and solvent, from which we map out the local hydrophobicity and hydrophilicity of amino acid residues.

Methods for the Modification and Evaluation of Cereal Proteins for the Substitution of Wheat Gluten in Dough Systems

The substitution of wheat gluten in the food industry is a relevant research area because the only known treatment for celiac disease is abstinence from this protein complex. The use of gluten-free cereals in dough systems has demonstrated that the viscoelastic properties of gluten cannot be achieved without the modification of the protein fraction. The quality of the final product is determined by the ability of the modification to form a matrix similar to that of gluten and to reach this, different methods have been proposed and tested. These procedures can be classified into four main types: chemical, enzymatic, physical, and genetic. This article provides a comprehensive review of the most recent research done in protein modification of cereal and pseudocereals for gluten substitution. The reported effects and methodologies for studying the changes made with each type of modification are described; also, some opportunity areas for future works regarding the study of the effect of protein modifications on gluten-free products are presented.

A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction

Protein-protein interactions regulate almost all cellular functions and rely on a fine tune of surface amino acids properties involved on both molecular partners. The disruption of a molecular association can be caused even by a single residue mutation, often leading to a pathological modification of a biochemical pathway. Therefore the evaluation of the effects of amino acid substitutions on binding, and the ad hoc design of protein-protein interfaces, is one of the biggest challenges in computational biology. Here, we present a novel strategy for computational mutation and optimization of protein-protein interfaces. Modeling the interaction surface properties using the Zernike polynomials, we describe the shape and electrostatics of binding sites with an ordered set of descriptors, making possible the evaluation of complementarity between interacting surfaces. With a Monte Carlo approach, we obtain protein mutants with controlled molecular complementarities. Applying this strategy to the relevant case of the interaction between Ferritin and Transferrin Receptor, we obtain a set of Ferritin mutants with increased or decreased complementarity. The extensive molecular dynamics validation of the method results confirms its efficacy, showing that this strategy represents a very promising approach in designing correct molecular interfaces.

Crystal structure of Thermus thermophilus methylenetetrahydrofolate dehydrogenase and determinants of thermostability

The elucidation of mechanisms behind the thermostability of proteins is extremely important both from the theoretical and applied perspective. Here we report the crystal structure of methylenetetrahydrofolate dehydrogenase (MTHFD) from Thermus thermophilus HB8, a thermophilic model organism. Molecular dynamics trajectory analysis of this protein at different temperatures (303 K, 333 K and 363 K) was compared with homologous proteins from the less temperature resistant organism Thermoplasma acidophilum and the mesophilic organism Acinetobacter baumannii using several data reduction techniques like principal component analysis (PCA), residue interaction network (RIN) analysis and rotamer analysis. These methods enabled the determination of important residues for the thermostability of this enzyme. The description of rotamer distributions by Gini coefficients and Kullback–Leibler (KL) divergence both revealed significant correlations with temperature. The emerging view seems to indicate that a static salt bridge/charged residue network plays a fundamental role in the temperature resistance of Thermus thermophilus MTHFD by enhancing both electrostatic interactions and entropic energy dispersion. Furthermore, this analysis uncovered a relationship between residue mutations and evolutionary pressure acting on thermophilic organisms and thus could be of use for the design of future thermostable enzymes.

Simulated Epidemics in 3D Protein Structures to Detect Functional Properties

The outcome of an epidemic is closely related to the network of interactions between individuals. Likewise, protein functions depend on the 3D arrangement of their residues and the underlying energetic interaction network. Borrowing ideas from the theoretical framework that has been developed to address the spreading of real diseases, we study for the first time the diffusion of a fictitious epidemic inside the protein nonbonded interaction network, aiming to study network features and properties. Our approach allows us to probe the overall stability and the capability of propagating information in complex 3D structures, proving to be very efficient in addressing different problems, from the assessment of thermal stability to the identification of functional sites.

Protein stability governed by its structural plasticity is inferred by physicochemical factors and salt bridges

Several organisms, specifically microorganisms survive in a wide range of harsh environments including extreme temperature, pH, and salt concentration. We analyzed systematically a large number of protein sequences with their structures to understand their stability and to discriminate extremophilic proteins from their non-extremophilic orthologs. Our results highlighted that the strategy for the packing of the protein core was influenced by the environmental stresses through substitutive structural events through better ionic interaction. Statistical analysis showed that a significant difference in number and composition of amino acid exist among them. The negative correlation of pairwise sequence alignments and structural alignments indicated that most of the extremophile and non-extremophile proteins didn’t contain any association for maintaining their functional stability. A significant numbers of salt bridges were noticed on the surface of the extremostable proteins. The Ramachandran plot data represented more occurrences of amino acids being present in helix and sheet regions of extremostable proteins. We also found that a significant number of small nonpolar amino acids and moderate number of charged amino acids like Arginine and Aspartic acid represented more nonplanar Omega angles in their peptide bond. Thus, extreme conditions may predispose amino acid composition including geometric variability for molecular adaptation of extremostable proteins against atmospheric variations and associated changes under natural selection pressure. The variation of amino acid composition and structural diversifications in proteins play a major role in evolutionary adaptation to mitigate climate change.