Factors Stabilizing β-Sheets in Protein Structures from a Quantum-Chemical Perspective

Structural and functional analysis of engineered antibodies for cancer immunotherapy: insights into protein compactness and solvent accessibility

Antibodies are crucial tools in various biomedical applications, including immunotherapy. In this study, we focused on designing and engineering antibodies to enhance their structural dynamics and functional properties. By employing advanced computational techniques and experimental validation, we gained crucial insights into the impact of specific mutations on the engineered antibodies. This study investigates the design and engineering of antibodies to improve their structural dynamics and functional properties. Structural attributes, such as protein compactness and solvent accessibility, were assessed, revealing interesting trends in anti-CD3 and anti-HER2 antibodies. Mutations in CD3 antibodies resulted in a more stable conformation, while mutant HER2 antibodies exhibited altered interaction with the target. Analysis of secondary structure assignments demonstrated significant changes in the folding and stability of the mutant antibodies compared to the wild-type counterparts. The conformational landscape of the engineered antibodies was explored, providing insights into folding pathways and binding mechanisms. Overall, the current study highlights the significance of antibody design and engineering in modulating structural dynamics and functional properties. The findings contribute to developing improved immunotherapeutic strategies by optimising antibody-based therapeutics for targeted diseases with enhanced efficacy and precision.

What are the minimal folding seeds in proteins? Experimental and theoretical assessment of secondary structure propensities of small peptide fragments

Certain peptide sequences, some of them as short as amino acid triplets, are significantly overpopulated in specific secondary structure motifs in folded protein structures. For example, 74% of the EAM triplet is found in α-helices, and only 3% occurs in the extended parts of proteins (typically β-sheets). In contrast, other triplets (such as VIV and IYI) appear almost exclusively in extended parts (79% and 69%, respectively). In order to determine whether such preferences are structurally encoded in a particular peptide fragment or appear only at the level of a complex protein structure, NMR, VCD, and ECD experiments were carried out on selected tripeptides: EAM (denoted as pro-'α-helical' in proteins), KAM(α), ALA(α), DIC(α), EKF(α), IYI(pro-β-sheet or more generally, pro-extended), and VIV(β), and the reference α-helical CATWEAMEKCK undecapeptide. The experimental data were in very good agreement with extensive quantum mechanical conformational sampling. Altogether, we clearly showed that the pro-helical vs. pro-extended propensities start to emerge already at the level of tripeptides and can be fully developed at longer sequences. We postulate that certain short peptide sequences can be considered minimal "folding seeds". Admittedly, the inherent secondary structure propensity can be overruled by the large intramolecular interaction energies within the folded and compact protein structures. Still, the correlation of experimental and computational data presented herein suggests that the secondary structure propensity should be considered as one of the key factors that may lead to understanding the underlying physico-chemical principles of protein structure and folding from the first principles.

In silico protein dynamics in the human cytoplasm: Partial folding, misfolding, fold switching, and non-native interactions

We examine the influence of cellular interactions in all-atom models of a section of the Homo sapiens cytoplasm on the early folding events of the three-helix bundle protein B (PB). While genetically engineered PB is known to fold in dilute water box simulations in three microseconds, the three initially unfolded PB copies in our two cytoplasm models using a similar force field did not reach the native state during 30-microsecond simulations. We did however capture the formation of all three helices in a compact native-like topology. Folding in vivo is delayed because intramolecular contact formation within PB is in direct competition with intermolecular contacts between PB and surrounding macromolecules. In extreme cases, intermolecular beta-sheets are formed. Interactions with other macromolecules are also observed to promote structure formation, for example when a PB helix in our simulations is shielded from solvent by macromolecular crowding. Sticking and crowding in our models initiate sampling of helix/sheet structural plasticity of PB. Relatedly, in past in vitro experiments, similar GA domains were shown to switch between two different folds. Finally, we also observed that stickiness between PB and the cellular environment can be modulated in our simulations through the reduction in protein hydrophobicity when we reversed PB back to the wild-type sequence. This study demonstrates that even fast-folding proteins can get stuck in non-native states in the cell, making them useful models for protein-chaperone interactions and early stages of aggregate formation relevant to cellular disease.

Structural analysis of an endogenous 4-megadalton succinyl-CoA-generating metabolon

The oxoglutarate dehydrogenase complex (OGDHc) participates in the tricarboxylic acid cycle and, in a multi-step reaction, decarboxylates α-ketoglutarate, transfers succinyl to CoA, and reduces NAD+. Due to its pivotal role in metabolism, OGDHc enzymatic components have been studied in isolation; however, their interactions within the endogenous OGDHc remain elusive. Here, we discern the organization of a thermophilic, eukaryotic, native OGDHc in its active state. By combining biochemical, biophysical, and bioinformatic methods, we resolve its composition, 3D architecture, and molecular function at 3.35 Å resolution. We further report the high-resolution cryo-EM structure of the OGDHc core (E2o), which displays various structural adaptations. These include hydrogen bonding patterns confining interactions of OGDHc participating enzymes (E1o-E2o-E3), electrostatic tunneling that drives inter-subunit communication, and the presence of a flexible subunit (E3BPo), connecting E2o and E3. This multi-scale analysis of a succinyl-CoA-producing native cell extract provides a blueprint for structure-function studies of complex mixtures of medical and biotechnological value.

Imidazole-amino acids. Conformational switch under tautomer and pH change

Replacement of the main chain peptide bond by imidazole ring seems to be a promising tool for the peptide-based drug design, due to the specific prototropic tautomeric as well as amphoteric properties. In this study, we present that both tautomer and pH change can cause a conformational switch of the studied residues of alanine (1-4) and dehydroalanine (5-8) with the C-terminal peptide group replaced by imidazole. The DFT methods are applied and an environment of increasing polarity is simulated. The conformational maps (Ramachandram diagrams) are presented and the stability of possible conformations is discussed. The neutral forms, tautomers τ (1) and π (2), adapt the conformations αRτ (φ, ψ = - 75°, - 114°) and C7eq (φ, ψ = - 75°, 66°), respectively. Their torsion angles ψ differ by about 180°, which results in a considerable impact on the peptide chain conformation. The cation form (3) adapts both these conformations, whereas the anion analogue (4) prefers the conformations C5 (φ, ψ = - 165°, - 178°) and β2 (φ, ψ ~ - 165°, - 3°). Dehydroamino acid analogues, the tautomers τ (5) and π (6) as well as the anion form (8), have a strong tendency toward the conformations β2 (φ, ψ = - 179°, 0°) and C5 (φ, ψ = - 180°, 180°). The preferences of the protonated imidazolium form (7) depend on the environment. The imidazole ring, acting as a donor or acceptor of the hydrogen bonds created within the studied residues, has a profound effect on the type of conformation.

Exhaustive Mapping of the Conformational Space of Natural Dipeptides by the DFT-D3//COSMO-RS Method

We extensively mapped energy landscapes and conformations of 22 (including three His protonation states) proteinogenic α-amino acids in trans configuration and the corresponding 484 (22²) dipeptides. To mimic the environment in a protein chain, the N- and C-termini of the studied systems were capped with acetyl and N-methylamide groups, respectively. We systematically varied the main chain dihedral angles (ϕ, ψ) by 40° steps and all side chain angles by 90° or 120° steps. We optimized the molecular geometries with the GFN2-xTB semiempirical (SQM) method and performed single point density functional theory calculations at the BP86-D3/DGauss-DZVP//COSMO-RS level in water, 1-octanol, N,N-dimethylformamide, and n-hexane. For each restrained (nonequilibrium) structure, we also calculated energy gradients (in water) and natural atomic charges. The exhaustive and unprecedented QM-based sampling enabled us to construct Ramachandran plots of quantum mechanical (QM(BP86-D3)//COSMO-RS) energies calculated on SQM structures, for all 506 (484 dipeptides and 22 amino acids) studied systems. We showed how the character of an amino acid side chain influences the conformational space of single amino acids and dipeptides. With clustering techniques, we were able to identify unique minima of amino acids and dipeptides (i.e., minima on the GFN2-xTB potential energy surfaces) and analyze the distribution of their BP86-D3//COSMO-RS conformational energies in all four solvents. We also derived an empirical formula for the number of unique minima based on the overall number of rotatable bonds within each peptide. The final peptide conformer data set (PeptideCs) comprises over 400 million structures, all of them annotated with QM(BP86-D3)//COSMO-RS energies. Thanks to its completeness and unbiased nature, the PeptideCs can serve, inter alia, as a data set for the validation of new methods for predicting the energy landscapes of protein structures. This data set may also prove to be useful in the development and reparameterization of biomolecular force fields. The data set is deposited at Figshare (10.25452/figshare.plus.19607172) and can be accessed using a simple web interface at http://peptidecs.uochb.cas.cz.

Fast and Accurate Quantum Mechanical Modeling of Large Molecular Systems Using Small Basis Set Hartree-Fock Methods Corrected with Atom-Centered Potentials

There has been significant interest in developing fast and accurate quantum mechanical methods for modeling large molecular systems. In this work, by utilizing a machine learning regression technique, we have developed new low-cost quantum mechanical approaches to model large molecular systems. The developed approaches rely on using one-electron Gaussian-type functions called atom-centered potentials (ACPs) to correct for the basis set incompleteness and the lack of correlation effects in the underlying minimal or small basis set Hartree-Fock (HF) methods. In particular, ACPs are proposed for ten elements common in organic and bioorganic chemistry (H, B, C, N, O, F, Si, P, S, and Cl) and four different base methods: two minimal basis sets (MINIs and MINIX) plus a double-ζ basis set (6-31G*) in combination with dispersion-corrected HF (HF-D3/MINIs, HF-D3/MINIX, HF-D3/6-31G*) and the HF-3c method. The new ACPs are trained on a very large set (73 832 data points) of noncovalent properties (interaction and conformational energies) and validated additionally on a set of 32 048 data points. All reference data are of complete basis set coupled-cluster quality, mostly CCSD(T)/CBS. The proposed ACP-corrected methods are shown to give errors in the tenths of a kcal/mol range for noncovalent interaction energies and up to 2 kcal/mol for molecular conformational energies. More importantly, the average errors are similar in the training and validation sets, confirming the robustness and applicability of these methods outside the boundaries of the training set. In addition, the performance of the new ACP-corrected methods is similar to complete basis set density functional theory (DFT) but at a cost that is orders of magnitude lower, and the proposed ACPs can be used in any computational chemistry program that supports effective-core potentials without modification. It is also shown that ACPs improve the description of covalent and noncovalent bond geometries of the underlying methods and that the improvement brought about by the application of the ACPs is directly related to the number of atoms to which they are applied, allowing the treatment of systems containing some atoms for which ACPs are not available. Overall, the ACP-corrected methods proposed in this work constitute an alternative accurate, economical, and reliable quantum mechanical approach to describe the geometries, interaction energies, and conformational energies of systems with hundreds to thousands of atoms.

Residue Folding Degree-Relationship to Secondary Structure Categories and Use as Collective Variable

Recently, we have shown that the residue folding degree, a network-based measure of folded content in proteins, is able to capture backbone conformational transitions related to the formation of secondary structures in molecular dynamics (MD) simulations. In this work, we focus primarily on developing a collective variable (CV) for MD based on this residue-bound parameter to be able to trace the evolution of secondary structure in segments of the protein. We show that this CV can do just that and that the related energy profiles (potentials of mean force, PMF) and transition barriers are comparable to those found by others for particular events in the folding process of the model mini protein Trp-cage. Hence, we conclude that the relative segment folding degree (the newly proposed CV) is a computationally viable option to gain insight into the formation of secondary structures in protein dynamics. We also show that this CV can be directly used as a measure of the amount of α-helical content in a selected segment.

Site-Specific Backbone and Side-Chain Contributions to Thermodynamic Stabilizing Forces of the WW Domain

The native structure of a protein is stabilized by a number of interactions such as main-chain hydrogen bonds and side-chain hydrophobic contacts. However, it has been challenging to determine how these interactions contribute to protein stability at single amino acid resolution. Here, we quantified site-specific thermodynamic stability at the molecular level to extend our understanding of the stabilizing forces in protein folding. We derived the free energy components of individual amino acid residues separately for the folding of the human Pin WW domain based on simulated structures. A further decomposition of the thermodynamic properties into contributions from backbone and side-chain groups enabled us to identify the critical residues in the secondary structure and hydrophobic core formation, without introducing physical modifications to the system as in site-directed mutagenesis methods. By relating the structural and thermodynamic changes upon folding for each residue, we find that the simultaneous formation of the backbone hydrogen bonds and side-chain contacts cooperatively stabilizes the folded structure. The identification of stabilizing interactions in a folding protein at atomic resolution will provide molecular insights into understanding the origin of the protein structure and into engineering a more stable protein.

Thiazole-amino acids: influence of thiazole ring on conformational properties of amino acid residues

Post-translational modified thiazole-amino acid (Xaa-Tzl) residues have been found in macrocyclic peptides (e.g., thiopeptides and cyanobactins), which mostly inhibit protein synthesis in Gram + bacteria. Conformational study of the series of model compounds containing this structural motif with alanine, dehydroalanine, dehydrobutyrine and dehydrophenylalanine were performed using DFT method in various environments. The solid-state crystal structure conformations of thiazole-amino acid residues retrieved from the Cambridge Structural Database were also analysed. The studied structural units tend to adopt the unique semi-extended β2 conformation; which is stabilised mainly by N-H⋯NTzl hydrogen bond, and for dehydroamino acids also by π-electron conjugation. The conformational preferences of amino acids with a thiazole ring were compared with oxazole analogues and the role of the sulfur atom in stabilising the conformations of studied peptides was discussed.

Conformational Strain Indicated by Ramachandran Angles for the Protein Backbone Is Only Weakly Related to the Flexibility

Studies on energy associated with free dipeptides have shown that conformers with unfavorable (ϕ,ψ) torsion angles have higher energy compared to conformers with favorable (ϕ,ψ) angles. It is expected that higher energy confers higher dynamics and flexibility to that part of the protein. Here, we explore a potential relationship between conformational strain in a residue due to unfavorable (ϕ,ψ) angles and its flexibility and dynamics in the context of protein structures. We compared flexibility of strained and relaxed residues, which are recognized based on outlier/allowed and favorable (ϕ,ψ) angles respectively, using normal-mode analysis (NMA). We also performed in-depth analysis on flexibility and dynamics at catalytic residues in protein kinases, which exhibit different strain status in different kinase structures using NMA and molecular dynamics simulations. We underline that strain of a residue, as defined by backbone torsion angles, is almost unrelated to the flexibility and dynamics associated with it. Even the overall trend observed among all high-resolution structures in which relaxed residues tend to have slightly higher flexibility than strained residues is counterintuitive. Consequently, we propose that identifying strained residues based on (ϕ,ψ) values is not an effective way to recognize energetic strain in protein structures.

Mapping Conformational Space of All 8000 Tripeptides by Quantum Chemical Methods: What Strain Is Affordable within Folded Protein Chains?

To gain more insight into the physicochemical aspects of a protein structure from the first principles, conformational space of all 8000 "capped" tripeptides (i.e., N-Ac-X₁X₂X₃-NH-CH₃, where X_i is one of the 20 natural amino acids) was investigated computationally. An enormous dataset (denoted P-CONF_1.6M and containing close to 1 600 000 conformers in total) has been obtained by employing a composite protocol combining density functional theory, semiempirical quantum mechanics (SQM), and state-of-the-art solvation methods with 1000 K molecular dynamics (MD) used to generate initial structures (200 snapshots for each tripeptide). This allowed us to present the first rigorous QM-based glimpse at the vast conformational space spanned by small protein fragments. The same computational procedure was repeated for tripeptide fragments taken from the SCOPe database of three-dimensional protein folds, by restraining them to their geometry in a protein. Such complementary data allowed us to compare the distribution of conformational strain energies of unrestrained tripeptidic fragments "in solvent" with those in existing protein chains. Besides providing a rigorous (ab initio) proof of a few well-known concepts and hypotheses concerning protein structures, such as the distribution of (φ, ψ) angles in Ramachandran plots, we have made several observations that came as a certain surprise: (1) distribution of conformational energies does not significantly differ between the "unbiased/unrestrained" conformers obtained from MD sampling in solvent and the biased conformers, i.e., those of a given tripeptide obtained from protein structures; (2) conformational (strain) energy window up to ∼20 to 25 kcal·mol^-1 is readily available to tripeptide fragments within the context of a protein chain; (3) overpopulation in certain regions of Ramachandran plot was observed for the unbiased conformers. Last but not least, the massive dataset of accurate (DFT-D3//COSMO-RS) conformational (free) energies of ∼1.6 M peptide conformers, P-CONF_1.6M, obtained throughout this work may serve as excellent dataset for calibrating and benchmarking of popular force fields.

Interplay between Conformational Strain and Intramolecular Interaction in Protein Structures: Which of Them Is Evolutionarily Conserved?

By computing strain energies of peptide fragments within protein structures and their intramolecular interaction energies, we attempt to reveal general biophysical trends behind the secondary structure formation in the context of protein evolution. Our "protein basis set" consisted of 1143 representatives of different folds obtained from curated SCOPe database, and for each member of the set, the strain and intramolecular energy was calculated on the "rolling tripeptide" basis, employing the DFT-D3/COSMO-RS method for the former and the QM-calibrated force field method (MM) for the latter. The calculated data, strain and interactions, were correlated with the conservation of amino acid residues in secondary structure elements and also with the level of the residue burial within the protein three-dimensional structure. It allowed us to formulate several observations concerning fundamental differences between two main secondary structure motifs: α-helices and β-strands. We have shown that a strong interaction is one of the determining characteristics of the β-sheet formation, at least at the level of tripeptides (and likely penta- or heptapeptides, too), and that the β-strand is a prevailing secondary structure in the strongly-interacting regions of the protein folds conserved by evolution. On the other hand, low strain was neither proven to be an important physicochemical property conserved by evolution nor does it correlate with the propensity for the α-helix and β-strand. Finally, it has been demonstrated that the strong interaction has a certain level of connection with residue burial; however, we demonstrate that these two characteristics should be rather regarded as two complementary factors. These findings represent an important contribution to understanding protein folding from first principles, which is a complementary approach to ongoing efforts to solve the protein folding problem by knowledge-based approaches and machine-learning.

Protein Dynamics and the Folding Degree

The analysis of folding trajectories for proteins is an open challenge. One of the problems is how to describe the amount of folded secondary structure in a protein. We extend the use of Estradas' folding degree (Bioinformatics 2002, 18, 697) for the analysis of the evolution of the folding stage during molecular dynamics (MD) simulation. It is shown that residue contribution to the total folding degree is a predominantly local property, well-defined by the backbone dihedral angles at the given residue, without significant contribution from the backbone conformation of other residues. Moreover, the magnitude of this residue contribution can be quite easily associated with characteristic motifs of secondary protein structures such as the α-helix, β-sheet (hairpin), and so on by means of a Ramachandran-like plot as a function of backbone dihedral angles φ,ψ. Additionally, the understanding of the free energy profile associated with the folding process becomes much simpler. Often a 1D profile is sufficient to locate global minima and the corresponding structure for short peptides.