Defining the nature of thermal intermediate in 3 state folding proteins: apoflavodoxin, a study case

Assessing Target Specificity of the Small Molecule Inhibitor MARIMASTAT to Snake Venom Toxins: A Novel Application of Thermal Proteome Profiling

New treatments that circumvent the pitfalls of traditional antivenom therapies are critical to address the problem of snakebite globally. Numerous snake venom toxin inhibitors have shown promising cross-species neutralization of medically significant venom toxins in vivo and in vitro. The development of high-throughput approaches for the screening of such inhibitors could accelerate their identification, testing, and implementation and thus holds exciting potential for improving the treatments and outcomes of snakebite envenomation worldwide. Energetics-based proteomic approaches, including thermal proteome profiling and proteome integral solubility alteration (PISA) assays, represent "deep proteomics" methods for high throughput, proteome-wide identification of drug targets and ligands. In the following study, we apply thermal proteome profiling and PISA methods to characterize the interactions between venom toxin proteoforms in Crotalus atrox (Western Diamondback Rattlesnake) and the snake venom metalloprotease (SVMP) inhibitor marimastat. We investigate its venom proteome-wide effects and characterize its interactions with specific SVMP proteoforms, as well as its potential targeting of non-SVMP venom toxin families. We also compare the performance of PISA thermal window and soluble supernatant with insoluble precipitate using two inhibitor concentrations, providing the first demonstration of the utility of a sensitive high-throughput PISA-based approach to assess the direct targets of small molecule inhibitors for snake venom.

Calculation of Protein Folding Thermodynamics Using Molecular Dynamics Simulations

Despite advances in artificial intelligence methods, protein folding remains in many ways an enigma to be solved. Accurate computation of protein folding energetics could help drive fields such as protein and drug design and genetic interpretation. However, the challenge of calculating the state functions governing protein folding from first-principles remains unaddressed. We present here a simple approach that allows us to accurately calculate the energetics of protein folding. It is based on computing the energy of the folded and unfolded states at different temperatures using molecular dynamics simulations. From this, two essential quantities (ΔH and ΔCp) are obtained and used to calculate the conformational stability of the protein (ΔG). With this approach, we have successfully calculated the energetics of two- and three-state proteins, representatives of the major structural classes, as well as small stability differences (ΔΔG) due to changes in solution conditions or variations in an amino acid residue.

Pre-Molten, Wet, and Dry Molten Globules en Route to the Functional State of Proteins

Transitions between the unfolded and native states of the ordered globular proteins are accompanied by the accumulation of several intermediates, such as pre-molten globules, wet molten globules, and dry molten globules. Structurally equivalent conformations can serve as native functional states of intrinsically disordered proteins. This overview captures the characteristics and importance of these molten globules in both structured and intrinsically disordered proteins. It also discusses examples of engineered molten globules. The formation of these intermediates under conditions of macromolecular crowding and their interactions with nanomaterials are also reviewed.

Protein conformation stabilized by newly formed turns for thermal resilience

Thermally stable or resilient proteins are usually stabilized at intermediate states during thermal stress to prevent irreversible denaturation. However, the mechanism by which their conformations are stabilized to resist high temperature remains elusive. Herein, we investigate the conformational and thermal stability of transforming growth factor-β1 (TGF-β1), a key signaling molecule in numerous biological pathways. We report that the TGF-β1 molecule is thermally resilient as it gradually denatures during thermal treatment when the temperature increases to 90°C-100°C but recovers native folding when the temperature decreases. Using this protein as a model, further studies show the maintenance of its bioactive functional properties after thermal stress, as demonstrated by differentiation induction of NIH/3T3 fibroblasts and human mesenchymal stem cells into myofibroblasts and chondrocytes, respectively. Molecular dynamic simulations revealed that although the protein's secondary structure is unstable under thermal stress, its conformation is partially stabilized by newly formed turns. Given the importance and/or prevalence of TGF-β1 in biological processes, potential therapeutics, and the human diet, our findings encourage consideration of its thermostability for biomedical applications and nutrition.

Insights into Fluctuations of Structure of Proteins: Significance of Intermediary States in Regulating Biological Functions

Proteins are indispensable to cellular communication and metabolism. The structure on which cells and tissues are developed is deciphered from proteins. To perform functions, proteins fold into a three-dimensional structural design, which is specific and fundamentally determined by their characteristic sequence of amino acids. Few of them have structural versatility, allowing them to adapt their shape to the task at hand. The intermediate states appear momentarily, while protein folds from denatured (D) ⇔ native (N), which plays significant roles in cellular functions. Prolific effort needs to be taken in characterizing these intermediate species if detected during the folding process. Protein folds into its native structure through definite pathways, which involve a limited number of transitory intermediates. Intermediates may be essential in protein folding pathways and assembly in some cases, as well as misfolding and aggregation folding pathways. These intermediate states help to understand the machinery of proper folding in proteins. In this review article, we highlight the various intermediate states observed and characterized so far under in vitro conditions. Moreover, the role and significance of intermediates in regulating the biological function of cells are discussed clearly.

Parallel Versus Antiparallel β-Sheet Structure in Cyclic Peptide Hybrids Containing γ- or δ-Cyclic Amino Acids

Cyclic peptides with disc-shaped structures have emerged as potent building blocks for the preparation of new biomaterials in fields ranging from biological to material science. In this work, we analyze in depth the self-assembling properties of a new type of cyclic peptides based on the alternation of α-residues and cyclic δ-amino acids (α,δ-CPs). To examine the preferred stacking properties adopted by cyclic peptides bearing this type of amino acids, we carried out a synergistic in vitro/in silico approximation by using simple dimeric models and then extended to nanotubes. Although these new cyclic peptides (α,δ-CPs) can interact either in a parallel or antiparallel fashion, our results confirm that although the parallel β-sheet is more stable, it can be switched to the antiparallel stacking by choosing residues that can establish favorable cross-strand interactions. Moreover, the subsequent comparison by using the same methodology but applied to α,γ-CPs models, up to the moment assumed as antiparallel-like d,l-α-CPs, led to unforeseen conclusions that put into question preliminary conjectures about these systems. Surprisingly, they tend to adopt a parallel β-sheet directed by the skeleton interactions. These results imply a change of paradigm with respect to cyclic peptide designs that should be considered for dimers and nanotubes.

Molecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when

The increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical-chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80-85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore's law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.

Exploring the complete mutational space of the LDL receptor LA5 domain using molecular dynamics: linking SNPs with disease phenotypes in familial hypercholesterolemia

Familial hypercholesterolemia (FH), a genetic disorder with a prevalence of 0.2%, represents a high-risk factor to develop cardiovascular and cerebrovascular diseases. The majority and most severe FH cases are associated to mutations in the receptor for low-density lipoproteins receptor (LDL-r), but the molecular basis explaining the connection between mutation and phenotype is often unknown, which hinders early diagnosis and treatment of the disease. We have used atomistic simulations to explore the complete SNP mutational space (227 mutants) of the LA5 repeat, the key domain for interacting with LDL that is coded in the exon concentrating the highest number of mutations. Four clusters of mutants of different stability have been identified. The majority of the 50 FH known mutations (33) appear distributed in the unstable clusters, i.e. loss of conformational stability explains two-third of FH phenotypes. However, one-third of FH phenotypes (17 mutations) do not destabilize the LR5 repeat. Combining our simulations with available structural data from different laboratories, we have defined a consensus-binding site for the interaction of the LA5 repeat with LDL-r partner proteins and have found that most (16) of the 17 stable FH mutations occur at binding site residues. Thus, LA5-associated FH arises from mutations that cause either the loss of stability or a decrease in domain's-binding affinity. Based on this finding, we propose the likely phenotype of each possible SNP in the LA5 repeat and outline a procedure to make a full computational diagnosis for FH.

Decoding Structural Properties of a Partially Unfolded Protein Substrate: En Route to Chaperone Binding

Many proteins comprising of complex topologies require molecular chaperones to achieve their unique three-dimensional folded structure. The E.coli chaperone, GroEL binds with a large number of unfolded and partially folded proteins, to facilitate proper folding and prevent misfolding and aggregation. Although the major structural components of GroEL are well defined, scaffolds of the non-native substrates that determine chaperone-mediated folding have been difficult to recognize. Here we performed all-atomistic and replica-exchange molecular dynamics simulations to dissect non-native ensemble of an obligate GroEL folder, DapA. Thermodynamics analyses of unfolding simulations revealed populated intermediates with distinct structural characteristics. We found that surface exposed hydrophobic patches are significantly increased, primarily contributed from native and non-native β-sheet elements. We validate the structural properties of these conformers using experimental data, including circular dichroism (CD), 1-anilinonaphthalene-8-sulfonic acid (ANS) binding measurements and previously reported hydrogen-deutrium exchange coupled to mass spectrometry (HDX-MS). Further, we constructed network graphs to elucidate long-range intra-protein connectivity of native and intermediate topologies, demonstrating regions that serve as central “hubs”. Overall, our results implicate that genomic variations (or mutations) in the distinct regions of protein structures might disrupt these topological signatures disabling chaperone-mediated folding, leading to formation of aggregates.

Several non-native proteins require molecular chaperones for proper folding. Many unfolded proteins if not folded accurately, become causal factors in various types of misfolding or aggregation induced diseases such as Alzheimer′s, Huntington′s and several other neurodegenerative disorders. However, structural information of non-folded proteins especially chaperone-dependent proteins is difficult to probe experimentally due to their inherent aggregation propensities. In this work, we study DapA protein, which exhibits obligate requirement on GroEL chaperonin machinery for its folding. We use molecular dynamics simulations to reveal populated intermediate structures of DapA in atomic details. The most plausible intermediate was found to be in agreement with recently reported hydrogen-exchange experimental data. Significant increase in surface exposed hydrophobicity was observed in intermediates compared to native, which was further validated using ANS binding experiments. We also constructed network model of these intermediates that provides remarkable insights into stable hubs (or important residues) underlying diverse states of unfolded proteins. In summary, our work provides a molecular picture of an unfolded protein that is en route to chaperone binding, and these underlying structural properties might act as a molecular signal for their productive folding.

Rational stabilization of complex proteins: a divide and combine approach

Increasing the thermostability of proteins is often crucial for their successful use as analytic, synthetic or therapeutic tools. Most rational thermostabilization strategies were developed on small two-state proteins and, unsurprisingly, they tend to fail when applied to the much more abundant, larger, non-fully cooperative proteins. We show that the key to stabilize the latter is to know the regions of lower stability. To prove it, we have engineered apoflavodoxin, a non-fully cooperative protein on which previous thermostabilizing attempts had failed. We use a step-wise combination of structure-based, rationally-designed, stabilizing mutations confined to the less stable structural region, and obtain variants that, according to their van't Hoff to calorimetric enthalpy ratios, exhibit fully-cooperative thermal unfolding with a melting temperature of 75°C, 32 degrees above the lower melting temperature of the non-cooperative wild type protein. The ideas introduced here may also be useful for the thermostabilization of complex proteins through formulation or using specific stabilizing ligands (e.g. pharmacological chaperones).

Quantifying the Sources of Kinetic Frustration in Folding Simulations of Small Proteins

Experiments and atomistic simulations of polypeptides have revealed structural intermediates that promote or inhibit conformational transitions to the native state during folding. We invoke a concept of “kinetic frustration” to quantify the prevalence and impact of these behaviors on folding rates within a large set of atomistic simulation data for 10 fast-folding proteins, where each protein’s conformational space is represented as a Markov state model of conformational transitions. Our graph theoretic approach addresses what conformational features correlate with folding inhibition and therefore permits comparison among features within a single protein network and also more generally between proteins. Nonnative contacts and nonnative secondary structure formation can thus be quantitatively implicated in inhibiting folding for several of the tested peptides.

Understanding the relevance of local conformational stability and dynamics to the aggregation propensity of an IgG1 and IgG2 monoclonal antibodies

Aggregation of monoclonal antibodies is often a multi-step process involving structural alterations in monomeric proteins and subsequent formation of soluble or insoluble oligomers. The role of local conformational stability and dynamics of native and/or partially altered structures in determining the aggregation propensity of monoclonal antibodies, however, is not well understood. Here, we investigate the role of conformational stability and dynamics of regions with distinct solvent exposure in determining the aggregation propensity of an IgG1 and IgG2 monoclonal antibody. The temperatures employed span the pre-unfolding range (10-40°C) and the onset temperatures (T onset ) for exposure of apolar residues (≈ 50°C), alterations in secondary structures (≈ 60°C) and initiation of visible aggregate formation (≈ 60°C). Solvent-exposed regions were found to precede solvent-shielded regions in an initiation of aggregation for both proteins. Such a process was observed upon alterations in overall tertiary structure while retaining the secondary structures in both the proteins. In addition, a greater dynamic nature of solvent-shielded regions in potential intermediates of IgG1 and the improved conformational stability increased its resistance to aggregation when compared to IgG2. These results suggest that local conformational stability and fluctuations of partially altered structures can influence the aggregation propensity of immunoglobulins.