Inter-residue Interactions Research Articles

Entropic Overcompensation of the N501Y Mutation on SARS-CoV-2 S Binding to ACE2.

Recent experimental work has shown that the N501Y mutation in the SARS-CoV-2 S glycoprotein's receptor binding domain (RBD) increases binding affinity to the angiotensin-converting enzyme 2 (ACE2), primarily by overcompensating for a less favorable enthalpy of binding by greatly reducing the entropic penalty for complex formation, but the basis for this entropic overcompensation is not clear [Prévost et al. J. Biol. Chem.2021, 297, 101151]. We use all-atom molecular dynamics simulations and free-energy calculations to qualitatively assess the impact of the N501Y mutation on the enthalpy and entropy of binding of RBD to ACE2. Our calculations correctly predict that N501Y causes a less favorable enthalpy of binding to ACE2 relative to the original strain. Furthermore, we show that this is overcompensated for by a more entropically favorable increase in large-scale quaternary flexibility and intraprotein root mean square fluctuations of residue positions upon binding in both RBD and ACE2. The enhanced quaternary flexibility stems from N501Y's ability to remodel the inter-residue interactions between the two proteins away from interactions central to the epitope and toward more peripheral interactions. These findings suggest that an important factor in determining protein-protein binding affinity is the degree to which fluctuations are distributed throughout the complex and that residue mutations that may seem to result in weaker interactions than their wild-type counterparts may yet result in increased binding affinity thanks to their ability to suppress unfavorable entropy changes upon binding.

Трехмерная структура молекулы бета-лакторфина

Opioid peptides cause pain relief, sedation and sleep, as well as a euphoric state and a number of autonomic reactions. These peptides are of animal and plant origin. A number of exogenous peptides obtained from food have opiate-like properties. This peptides were named exorphins. The discovery of the opioid activity of the peptide components of food has led to the assumption that certain types of food can act on the central nervous system like opiate drugs. A number of milk exorphins have been found that have opioid receptor antagonist properties. These include casoxins A, B, C, human casoxin D, as well as lactoferroxins A, B and C, as well as alpha and beta lactorphins. The possibility of the formation of these peptides during the hydrolysis of the corresponding proteins by peptidases of the gastrointestinal tract has been proven in vitro. Representatives of exorphins are also cytochrophins and hemorphins. It is assumed that these peptides can be formed in vivo during the proteolytic cleavage of cytochrome b and hemoglobin. The beta-lactorphine molecule is a representative of this class. The conformational possibilities of the beta-lactorphine Tyr-Leu-Leu-Phe molecule were studied by the method of theoretical conformational analysis. The potential function of the system is chosen as the sum of non-valence, electrostatic and torsion interactions and the energy of hydrogen bonds. The low-energy conformations of the alpha-lactorphine molecule, the values of the dihedral angles of the main and side chains of the amino acid residues that make up the molecules were found, and the energy of intra- and interresidual interactions was estimated. It has been shown that the spatial structure of the beta-lactorphine molecule can be represented by eight forms of the main chain. The results obtained can be used to elucidate the structural and structural-functional organization of exorphin molecules.

Трехмерная структура пентапептидной молекулы Arg-Glu-Arg-Gly-Pro

It seems relevant to carry out structural and functional studies of glyprolines and their synthetic analogues on model systems using theoretical research methods. Glyprolines are a family of short peptides whose amino acid sequences contain residues of proline and glycine. Currently their mechanisms of action are poorly understood. Great interest in their structure is caused by the possibility of creating new drugs that are the human body’s own reserve. Glyproline molecules are stable and eddicient. Using the method of molecular mechanics, the spatial structure and conformational properties of the glyproline pentapeptide molecule Arg-Glu-Arg-Gly-Pro were determined. The potential energy of the molecule was estimated as the sum of non-valent, electrostatic, torsion interactions and the energy of hydrogen bonds. 9 low-energy conformations were found for glyproline pentapeptide, the values of structure the dihedral angles of the main and side chains, and the energy of intra-and inter-residue interactions was estimated. It is revealed that low energy conformations of this molecule have the half-folded type of backbone. The side chains of the Arg and Glu amino acids in low-energy conformations carry out effective interactions and are conformationally labile amino acids, they bring together the regions of the main chain and the side chains of the amino acids included in the pentapeptide.

Sequence-Dependent Backbone Dynamics of Intrinsically Disordered Proteins.

For intrinsically disordered proteins (IDPs), a pressing question is how sequence codes for function. Dynamics serves as a crucial link, reminiscent of the role of structure in sequence-function relations of structured proteins. To define general rules governing sequence-dependent backbone dynamics, we carried out long molecular dynamics simulations of eight IDPs. Blocks of residues exhibiting large amplitudes in slow dynamics are rigidified by local inter-residue interactions or secondary structures. A long region or an entire IDP can be slowed down by long-range contacts or secondary-structure packing. On the other hand, glycines promote fast dynamics and either demarcate rigid blocks or facilitate multiple modes of local and long-range inter-residue interactions. The sequence-dependent backbone dynamics endows IDPs with versatile response to binding partners, with some blocks recalcitrant while others readily adapting to intermolecular interactions.

Evolution of Stronger SARS-CoV-2 Variants as Revealed Through the Lens of Molecular Dynamics Simulations.

Using molecular dynamics simulations, the protein–protein interactions of the receptor-binding domain of the wild-type and seven variants of the severe acute respiratory syndrome coronavirus 2 spike protein and the peptidase domain of human angiotensin-converting enzyme 2 were investigated. These variants are alpha, beta, gamma, delta, eta, kappa, and omicron. Using 100 ns simulation data, the residue interaction networks at the protein–protein interface were identified. Also, the impact of mutations on essential protein dynamics, backbone flexibility, and interaction energy of the simulated protein–protein complexes were studied. The protein–protein interface for the wild-type, delta, and omicron variants contained several stronger interactions, while the alpha, beta, gamma, eta, and kappa variants exhibited an opposite scenario as evident from the analysis of the inter-residue interaction distances and pair-wise interaction energies. The study reveals that two distinct residue networks at the central and right contact regions forge stronger binding affinity between the protein partners. The study provides a molecular-level insight into how enhanced transmissibility and infectivity by delta and omicron variants are most likely tied to a handful of interacting residues at the binding interface, which could potentially be utilized for future antibody constructs and structure-based antiviral drug design. Supplementary InformationThe online version contains supplementary material available at 10.1007/s10930-022-10065-6.

Stability profile of the neuronal SNARE complex reflects its potency to drive fast membrane fusion

Soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) form the SNARE complex to mediate most fusion events of the secretory pathway. The neuronal SNARE complex is featured by its high stability and half-zippered conformation required for driving robust and fast synaptic exocytosis. However, these two features seem to be thermodynamically mutually exclusive. In this study, we have employed temperature-dependent disassociation assays and single-molecule Förster resonance energy transfer (FRET) experiments to analyze the stability and conformation of the neuronal SNARE complex. We reclassified the amino acids of the SNARE motif into four sub-groups (core, core-side I and II, and non-contact). Our data showed that the core residues predominantly contribute to the complex stability to meet a basal requirement for SNARE-mediated membrane fusion, while the core-side residues exert an unbalanced effect on the N- and C-half bundle stability that determines the half-zippered conformation of the neuronal SNARE complex, which would accommodate essential regulations by complexins and synaptotagmins for fast Ca2+-triggered membrane fusion. Furthermore, our data confirmed a strong coupling of folding energy between the N- and C-half assembly of the neuronal SNARE complex, which rationalizes the strong potency of the half-zippered conformation to conduct robust and fast fusion. Overall, these results uncovered that the stability profile of the neuronal SNARE complex reflects its potency to drive fast and robust membrane fusion. Based on these results, we also developed a new parameter, the stability factor (Fs), to characterize the overall stability of the neuronal SNARE complex and resolved a linear correlation between the stability and inter-residue coulombic interactions of the neuronal SNARE complex, which would help rationally design artificial SNARE complexes and remold functional SNARE complexes with desirable stability.

Edge weights in a protein elastic network reorganize collective motions and render long-range sensitivity responses.

The effects of inter-residue interactions on protein collective motions are analyzed by comparing two elastic network models (ENM)-structural contact ENM (SC-ENM) and molecular dynamics (MD)-ENM-with the edge weights computed from an all-atom MD trajectory by structure-mechanics statistical learning. A theoretical framework is devised to decompose the eigenvalues of ENM Hessian into contributions from individual springs and to compute the sensitivities of positional fluctuations and covariances to spring constant variation. Our linear perturbation approach quantifies the response mechanisms as softness modulation and orientation shift. All contacts of Cα positions in SC-ENM have an identical spring constant by fitting the profile of root-of-mean-squared-fluctuation calculated from an all-atom MD simulation, and the same trajectory data are also used to compute the specific spring constant of each contact as an MD-ENM edge weight. We illustrate that the soft-mode reorganization can be understood in terms of gaining weights along the structural contacts of low elastic strengths and loosing magnitude along those of high rigidities. With the diverse mechanical strengths encoded in protein dynamics, MD-ENM is found to have more pronounced long-range couplings and sensitivity responses with orientation shift identified as a key player in driving the specific residues to have high sensitivities. Furthermore, the responses of perturbing the springs of different residues are found to have asymmetry in the action-reaction relationship. In understanding the mutation effects on protein functional properties, such as long-range communications, our results point in the directions of collective motions as a major effector.

Molecular Dynamics Simulation Investigation of the Binding and Interaction of the EphA6-Odin Protein Complex.

Protein-protein interaction plays an important role in the development of almost all cells. Elucidating the dynamic binding and affinity of a protein-protein complex is essential for understanding the biological functions of proteins. EphA6 and Odin proteins are members of the Eph (erythropoietin-producing hepatocyte) receptor family and the Anks (ankyrin repeat and sterile α motif domain-containing) family, respectively. Odin significantly functions in regulating endocytosis, degradation, and stability of EphA receptors. In this work, the key residues of the interaction interface were determined through a hydrogen bond, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and dynamic correlation analysis of the conventional molecular dynamics (MD) simulations. The calculated standard binding free energy, -7.92 kcal/mol, between EphA6 and Odin is quite consistent with the experimental measurement value, -8.73 kcal/mol. By the combination of several MD simulation techniques, our investigation of the binding process reveals the detailed representative characteristics of the entire binding pathway at the molecular level. Based on the obtained potential of the mean force (PMF) curve, the analysis of the simulation trajectories shows that the residue Arg1013 in the receptor EphA6 is responsible for capturing Asp739 and Asp740 in the ligand Odin during the initial stage of binding. In the later stage of binding, the hydrogen bonds and salt bridges between a series of residues Lys973, Leu1007, Gly1009, His1010, and Arg1012 in the receptor and residues Leu735, Asn736, Asp739, Asp740, and Asp753 in the ligand mainly contribute to the stability of the protein complex. In addition, the specific change process of the receptor-ligand-binding mode is also clarified during the binding process. Our present simulation will promote a deep understanding of the protein-protein interaction, and the identified key interresidue interaction will be theoretical guidance for the design of protein drugs.

Bioinformatics Approaches to Predict Mutation Effects in the Binding Site of the Proangiogenic Molecule CD93.

The transmembrane glycoprotein CD93 has been identified as a potential new target to inhibit tumor angiogenesis. Recently, Multimerin-2 (MMRN2), a pan-endothelial extracellular matrix protein, has been identified as a ligand for CD93, but the interaction mechanism between these two proteins is yet to be studied. In this article, we aim to investigate the structural and functional effects of induced mutations on the binding domain of CD93 to MMRN2. Starting from experimental data, we assessed how specific mutations in the C-type lectin-like domain (CTLD) affect the binding interaction profile. We described a four-step workflow in order to predict the effects of variations on the inter-residue interaction network at the PPI, based on evolutionary information, complex network metrics, and energetic affinity. We showed that the application of computational approaches, combined with experimental data, allowed us to gain more in-depth molecular insights into the CD93-MMRN2 interaction, offering a platform for developing innovative therapeutics able to target these molecules and block their interaction. This comprehensive molecular insight might prove useful in drug design in cancer therapy.

Notch ankyrin domain: evolutionary rise of a thermodynamic sensor

Notch signalling pathway plays a key role in metazoan biology by contributing to resolution of binary decisions in the life cycle of cells during development. Outcomes such as proliferation/differentiation dichotomy are resolved by transcriptional remodelling that follows a switch from Notchon to Notchoff state, characterised by dissociation of Notch intracellular domain (NICD) from DNA-bound RBPJ. Here we provide evidence that transitioning to the Notchoff state is regulated by heat flux, a phenomenon that aligns resolution of fate dichotomies to mitochondrial activity. A combination of phylogenetic analysis and computational biochemistry was utilised to disclose structural adaptations of Notch1 ankyrin domain that enabled function as a sensor of heat flux. We then employed DNA-based micro-thermography to measure heat flux during brain development, followed by analysis in vitro of the temperature-dependent behaviour of Notch1 in mouse neural progenitor cells. The structural capacity of NICD to operate as a thermodynamic sensor in metazoans stems from characteristic enrichment of charged acidic amino acids in β-hairpins of the ankyrin domain that amplify destabilising inter-residue electrostatic interactions and render the domain thermolabile. The instability emerges upon mitochondrial activity which raises the perinuclear and nuclear temperatures to 50 °C and 39 °C, respectively, leading to destabilization of Notch1 transcriptional complex and transitioning to the Notchoff state. Notch1 functions a metazoan thermodynamic sensor that is switched on by intercellular contacts, inputs heat flux as a proxy for mitochondrial activity in the Notchon state via the ankyrin domain and is eventually switched off in a temperature-dependent manner.4Fh46PNx-YRBNHf862t6mSVideo abstract

Structural and Biophysical Mechanisms Driving Differential Hormone Response in Steroid Receptors

Steroid receptors (SRs) belong to the superfamily of ligand‐activated transcription factors that regulate a myriad of biological processes upon binding of cholesterol‐derived hormones. A poorly understood aspect of this transcriptional regulation is how diverse steroid hormones modulate the ligand binding domain (LBD) of steroid receptors to achieve selective transcriptional outcomes. Here we investigate hormone specificity in the ancestral steroid receptor 2 (ancSR2) which is transcriptionally activated by 3‐ketosteroid hormones and unresponsive to 3‐hydroxylated, A‐ring aromatized steroids (i.e., estrogens). Previous work uncovered evolutionarily conserved ligand sensing‐residues in the binding pocket of LBD which also enables hormone discrimination. Specifically, the L42 (Helix3)‐M75 (Helix5) interaction was predicted to enable discrimination between 3‐ketosteroids and estrogens. To further probe the role of these ligand sensors in mediating differential hormone responses, we mutated M75 to modulate the Helix3‐Helix5 interaction and determined how transcriptional function, protein structure and dynamics are impacted. Specifically, we have combined site‐directed mutagenesis with biophysical experiments, cell‐based assays, and molecular dynamics (MD) simulations. While our secondary structure measurements reveal minor impacts on structure, MD simulations reveal that M75 mutations modulate the status of the H3‐H5 interaction, subsequently affecting ancSR2 conformations in a hormone‐dependent manner. Additionally, hydrogen deuterium exchange‐mass spectrometry (HDX‐MS) measurements reveal conformational effects at regions distant from the mutation site that may modulate ancSR2 inter‐residue interaction networks for differential hormone response. The differential hormone response is supported in luciferase reporter assays as well as ligand binding assays. These studies will provide biophysical and structural insight into how steroid receptors achieve hormone‐specific transcriptional responses.

Molecular Insights into Phosphorylation-Induced Allosteric Conformational Changes in a β2-Adrenergic Receptor.

The large conformational flexibility of G protein-coupled receptors (GPCRs) has been a puzzle in structural and pharmacological studies for the past few decades. Apart from structural rearrangements induced by ligands, enzymatic phosphorylations by GPCR kinases (GRKs) at the carboxy-terminal tail (C-tail) of a GPCR also make conformational alterations to the transmembrane helices and facilitates the binding of one of its transducer proteins named β-arrestin. The phosphorylation-induced conformational transition of the receptor that causes specific binding to β-arrestin but prevents the association of other transducers such as G proteins lacks atomistic understanding and is elusive to experimental studies. Using microseconds of all-atom conventional and Gaussian accelerated molecular dynamics (GaMD) simulations, we investigate the allosteric mechanism of phosphorylation induced-conformational changes in β2-adrenergic receptor, a well-characterized GPCR model system. Free energy profiles reveal that the phosphorylated receptor samples a new conformational state in addition to the canonical active state corroborating with recent nuclear magnetic resonance experimental findings. The new state has a smaller intracellular cavity that is likely to accommodate β-arrestin better than G protein. Using contact map and inter-residue interaction energy calculations, we found the phosphorylated C-tail adheres to the cytosolic surface of the transmembrane domain of the receptor. Transfer entropy calculations show that the C-tail residues drive the correlated motions of TM residues, and the allosteric signal is relayed via several residues at the cytosolic surface. Our results also illustrate how the redistribution of inter-residue nonbonding interaction couples with the allosteric communication from the phosphorylated C-tail to the transmembrane. Atomistic insight into phosphorylation-induced β-arrestin specific conformation is therapeutically important to design drugs with higher efficacy and fewer side effects. Our results, therefore, open novel opportunities to fine-tune β-arrestin bias in GPCR signaling.

Improved inter-residue contact prediction via a hybrid generative model and dynamic loss function

Protein contact maps represent spatial pairwise inter-residue interactions, providing a protein's translationally and rotationally invariant topological representation. Accurate contact map prediction has been a critical driving force for improving protein structure determination. Contact maps can also be used as a stand-alone tool for varied applications such as prediction of protein–protein interactions, structure-aware thermal stability or physicochemical properties. We develop a novel hybrid contact map prediction model, CGAN-Cmap, that uses a generative adversarial neural network embedded with a series of modified squeeze and excitation residual networks. To exploit features of different dimensions, we introduce two parallel modules. This architecture improves the prediction by increasing receptive fields, surpassing redundant features and encouraging more meaningful ones from 1D and 2D inputs. We also introduce a new custom dynamic binary cross-entropy loss function to address the input imbalance problem for highly sparse long-range contacts in proteins with insufficient homologs. We evaluate the model’s performance on CASP 11, 12, 13, 14, and CAMEO test sets. CGAN-Cmap outperforms state-of-the-art models, improving precision of medium and long-range contacts by at least 3.5%. As a direct assessment between our model and AlphaFold2, the leading available protein structure prediction model, we compare extracted contact maps from AlphaFold2 and predicted contact maps from CGAN-Cmap. The results show that CGAN-Cmap has a mean precision higher by 1% compared to AlphaFold2 for most ranges of contacts. These results demonstrate an efficient approach for highly accurate contact map prediction toward accurate characterization of protein structure, properties and functions from sequence.

Collective residue interactions in trimer complexes of SARS-CoV-2 spike proteins analyzed by fragment molecular orbital method

In large biomolecular systems such as protein complexes, there are huge numbers of combinations of inter-residue interactions whose comprehensive analyses are often beyond the intuitive processing by researchers. Here we propose a computational method to allow for a systematic analysis of these interactions based on the fragment molecular orbital calculations, in which the inter-fragment interaction energies are comprehensively processed by the singular value decomposition. For a trimer complex of SARS-CoV-2 spike protein, three-body interactions among residues belonging to three chains are analyzed to elicit a small number of essential interaction modes or networks crucial for the structural stability of the complex.

When homologous sequences meet structural decoys: Accurate contact prediction by tFold in CASP14-(tFold for CASP14 contact prediction).

In this paper, we report our tFold framework's performance on the inter-residue contact prediction task in the 14th Critical Assessment of protein Structure Prediction (CASP14). Our tFold framework seamlessly combines both homologous sequences and structural decoys under an ultra-deep network architecture. Squeeze-excitation and axial attention mechanisms are employed to effectively capture inter-residue interactions. In CASP14, our best predictor achieves 41.78% in the averaged top-L precision for long-range contacts for all the 22 free-modeling (FM) targets, and ranked 1st among all the 60 participating teams. The tFold web server is now freely available at: https://drug.ai.tencent.com/console/en/tfold.

Liquid-Liquid Phase Separation of Short Histidine- and Tyrosine-Rich Peptides: Sequence Specificity and Molecular Topology.

The increasing realization of the prevalence of liquid-liquid phase separation (LLPS) across multiple length scales of biological constructs, from intracellular membraneless organelles to extracellular load-bearing tissues, has raised intriguing questions about intermolecular interactions regulating LLPS at the atomic level. Squid-beak derived histidine (His)- and tyrosine (Tyr)-rich peptides (HBpeps) have recently emerged as suitable short model peptides to precisely assess the roles of peptide motifs and single residues on the phase behavior and material properties of microdroplets obtained by LLPS. In this study, by systematically introducing single mutations in an HBpep, we have identified specific sticker residues that attract peptide chains together. We find that His and Tyr residues located near the sequence termini drive phase separation, forming interaction nodes that stabilize microdroplets. Combining quantum chemistry simulations with NMR studies, we predict atomic-level bond geometries and uncover inter-residue supramolecular interactions governing LLPS. These results are subsequently used to propose possible topological arrangements of the peptide chains, which upon expansion can help explain the three-dimensional network of microdroplets. The stability of the proposed topologies carried out through all-atom molecular dynamics simulations predicts chain topologies that are more likely to stabilize the microdroplets. Overall, this study provides useful guidelines for the de novo design of peptide coacervates with tunable phase behavior and material properties. In addition, the analysis of nanoscale topologies may pave the way to understand how client molecules can be trapped within microdroplets, with direct implications for the encapsulation and controlled release of therapeutics for drug delivery applications.

Recent Advances in Protein Homology Detection Propelled by Inter-Residue Interaction Map Threading.

Sequence-based protein homology detection has emerged as one of the most sensitive and accurate approaches to protein structure prediction. Despite the success, homology detection remains very challenging for weakly homologous proteins with divergent evolutionary profile. Very recently, deep neural network architectures have shown promising progress in mining the coevolutionary signal encoded in multiple sequence alignments, leading to reasonably accurate estimation of inter-residue interaction maps, which serve as a rich source of additional information for improved homology detection. Here, we summarize the latest developments in protein homology detection driven by inter-residue interaction map threading. We highlight the emerging trends in distant-homology protein threading through the alignment of predicted interaction maps at various granularities ranging from binary contact maps to finer-grained distance and orientation maps as well as their combination. We also discuss some of the current limitations and possible future avenues to further enhance the sensitivity of protein homology detection.

Hybridized distance- and contact-based hierarchical structure modeling for folding soluble and membrane proteins.

Crystallography and NMR system (CNS) is currently a widely used method for fragment-free ab initio protein folding from inter-residue distance or contact maps. Despite its widespread use in protein structure prediction, CNS is a decade-old macromolecular structure determination system that was originally developed for solving macromolecular geometry from experimental restraints as opposed to predictive modeling driven by interaction map data. As such, the adaptation of the CNS experimental structure determination protocol for ab initio protein folding is intrinsically anomalous that may undermine the folding accuracy of computational protein structure prediction. In this paper, we propose a new CNS-free hierarchical structure modeling method called DConStruct for folding both soluble and membrane proteins driven by distance and contact information. Rigorous experimental validation shows that DConStruct attains much better reconstruction accuracy than CNS when tested with the same input contact map at varying contact thresholds. The hierarchical modeling with iterative self-correction employed in DConStruct scales at a much higher degree of folding accuracy than CNS with the increase in contact thresholds, ultimately approaching near-optimal reconstruction accuracy at higher-thresholded contact maps. The folding accuracy of DConStruct can be further improved by exploiting distance-based hybrid interaction maps at tri-level thresholding, as demonstrated by the better performance of our method in folding free modeling targets from the 12th and 13th rounds of the Critical Assessment of techniques for protein Structure Prediction (CASP) experiments compared to popular CNS- and fragment-based approaches and energy-minimization protocols, some of which even using much finer-grained distance maps than ours. Additional large-scale benchmarking shows that DConStruct can significantly improve the folding accuracy of membrane proteins compared to a CNS-based approach. These results collectively demonstrate the feasibility of greatly improving the accuracy of ab initio protein folding by optimally exploiting the information encoded in inter-residue interaction maps beyond what is possible by CNS.

Spatial Structure of the Acth-(6-9)-PGP Molecule

The spatial structure of ACTH-(6-9)-PGP molecule has been investigated using theoretical conformational analysis method. Amino acid sequence of the N-terminal pentapeptide fragment of His-Phe-Arg-Trp-Pro of this molecule conforms to the fragment 6-9 of ACTH hormone. Calculations of conformational states of this molecule are carried out regarding nonvalent, electrostatic and torsional interactions and the energy of hydrogen bonds. The spatial structure of the His-Phe-Arg-Trp-Pro-Gly-Pro molecule was estimated on the low–energy conformations of the N-terminal tetrapeptide fragment His-Phe-Arg-Trp and C-terminal tripeptide fragment Pro-Gly-Pro of this molecule. It is shown that the spatial structure of heptapeptide molecule can be presented by 11 low-energy forms of the main chain. The low–energy conformations of this molecule, the values of dihedral angles of the backbone and side chains of the amino acid residues were founded and the energies of intra- and inter-residual interactions were determined.

Spatial Structure of the Acth-(6-9)-PGP Molecule

The spatial structure of ACTH-(6-9)-PGP molecule has been investigated using theoretical conformational analysis method. Amino acid sequence of the N-terminal pentapeptide fragment of His-Phe-Arg-Trp-Pro of this molecule conforms to the fragment 6-9 of ACTH hormone. Calculations of conformational states of this molecule are carried out regarding nonvalent, electrostatic and torsional interactions and the energy of hydrogen bonds. The spatial structure of the His-Phe-Arg-Trp-Pro-Gly-Pro molecule was estimated on the low–energy conformations of the N-terminal tetrapeptide fragment His-Phe-Arg-Trp and C-terminal tripeptide fragment Pro-Gly-Pro of this molecule. It is shown that the spatial structure of heptapeptide molecule can be presented by 11 low-energy forms of the main chain. The low–energy conformations of this molecule, the values of dihedral angles of the backbone and side chains of the amino acid residues were founded and the energies of intra- and inter-residual interactions were determined.