Guiding AlphaFold predictions with experimental knowledge to inform dynamics and interactions with VAIRO

Today there are several different experimental scales for the intrinsic alpha-helix as well as beta-strand propensities of the 20 amino acids obtained from the thermodynamic analysis of various model systems. These scales do not compare well with those extracted from statistical analysis of three-dimensional structure databases. Possible explanations for this could be the limited size of the databases used, the definitions of intrinsic propensities, or the theoretical approach. Here we report a statistical determination of alpha-helix and beta-strand propensities derived from the analysis of a database of 279 three-dimensional structures. Contrary to what has been generally done, we have considered a particular residue as in alpha-helix or beta-strand conformation by looking only at its dihedral angles (phi-psi matrices). Neither the identity nor the conformation of the surrounding residues in the amino acid sequence has been taken into consideration. Pseudoenergy empirical scales have been calculated from the statistical propensities. These scales agree very well with the experimental ones in relative and absolute terms. Moreover, its correlation with the average of the experimental scales for alpha-helix or beta-strand is as good as the correlations of the individual experimental scales with the average. These results show that by using a large enough database and a proper definition for the secondary structure propensities, it is possible to obtain a scale as good as any of experimental origin. Interestingly the phi-psi analysis of the Ramachandran plot suggests that the amino acids could have different beta-strand propensities in different subregions of the beta-strand area.

The article deals with the interdiction convergence on the example of evolutionary changes in lexical semantics of poetic language. The current study contributes to the development of the methodology for studying the language evolutionary processes. The paper describes certain trends of dynamic changes and their specifics; it gives some prediction about the further lexis convergence of different types of functional styles. The findings contribute to the development of lexicography which is going to reflect not only static but also dynamic characteristics of lexical units including stylistic ones. The subjectivity of labeling poetic vocabulary in dictionaries can be partially removed through the analysis of corpus data by comparing frequency indices in different subsections, however this method is not always accurate, moreover, it doesnt effectively trace evolutionary changes. The data from the psycholinguistic experiments can help reveal the dynamics of changes. On the one hand, the results of scaling show the extent of poetry in connotative meanings; on the other hand, the open-response associative experiment allows us to calculate the archaization index of a lexeme through summing up the numerical values of certain selected parameters. The research gives obvious evidence of active archaization of some specific poetic lexemes. The findings also prove that the dynamic changes in stylistic connotation are not synchronous with the changes in the denotative layer of a lexical unit.

A Membrane-Translocating Peptide Penetrates into Bilayers without Significant Bilayer Perturbations

Comparative cytogenetics and heterochromatic patterns in two species of the genus Acanthostracion (Ostraciidae: Tetraodontiformes)

The A2 domain of von Willebrand factor (vWF A2) acts as a mechanosensor, unfolding under shear stress to enable cleavage by ADAMTS13. Dysfunction of this process causes von Willebrand disease (VWD) and thrombotic thrombocytopenic purpura (TTP). Although we previously reported the NMR assignments for mouse vWF A2, the human ortholog shares only 79% sequence identity (38 amino acid differences). Given that VWD and TTP are human pathologies, structural characterization of the human protein is essential. Here, we present the backbone 1H, 13C, and 15N resonance assignments of human vWF A2. Secondary structure propensity (SSP) analysis confirms that the solution structure retains the canonical Rossmann fold. Comparison with the mouse ortholog reveals distinct local differences in secondary structure propensities, particularly at the boundaries of α-helices and β-strands. These local variations, arising from sequence divergence, may influence the stability and unfolding dynamics relevant to human disease mechanisms.

Humans differ from other primates by marked differences in cognitive abilities and a significantly larger brain. These differences correlate with metabolic changes, as evidenced by the relative up-regulation of energy-related genes and metabolites in human brain. While the mechanisms underlying these evolutionary changes have not been elucidated, altered activities of key transcription factors (TFs) could play a pivotal role. To assess this possibility, we analyzed microarray data from five tissues from humans and chimpanzees. We identified 90 TF genes with significantly different expression levels in human and chimpanzee brain among which the rapidly evolving KRAB-zinc finger genes are markedly over-represented. The differentially expressed TFs cluster within a robust regulatory network consisting of two distinct but interlinked modules, one strongly associated with energy metabolism functions, and the other with transcription, vesicular transport, and ubiquitination. Our results suggest that concerted changes in a relatively small number of interacting TFs may coordinate major gene expression differences in human and chimpanzee brain.

Intrinsically disordered proteins play a central role in dynamic regulatory and assembly processes in the cell. Recently, a human κ-casein proteolytic fragment called lactaptin (8.6 kDa) was found to induce apoptosis of human breast adenocarcinoma MCF-7 and MDA-MB-231 cells with no cytotoxic activity toward normal cells. Earlier, we had designed some recombinant analogs of lactaptin and compared their biological activity. Among these analogs, RL2 has the highest antitumor activity, but the amino acid residues and secondary structures that are responsible for RL2′s activity remain unclear. To elucidate the structure–activity relations of RL2, we studied the structural and aggregation features of this fairly large intrinsically disordered fragment of human milk κ-casein by a combination of physicochemical methods: NMR, paramagnetic relaxation enhancement (PRE), Electron Paramagnetic Resonance (EPR), circular dichroism, dynamic light scattering, atomic force microscopy, and a cytotoxic activity assay. It was found that in solution, RL2 exists as stand-alone monomeric particles and large aggregates. Whereas the disulfide-bonded homodimer turned out to be more prone to assembly into large aggregates, the monomer predominantly forms single particles. NMR relaxation analysis of spin-labeled RL2 showed that the RL2 N-terminal region, which is essential not only for multimerization of the peptide but also for its proapoptotic action on cancer cells, is more ordered than its C-terminal counterpart and contains a site with a propensity for α-helical secondary structure.

The Life of an Insect Endosymbiont from the Cradle to the Grave

The usefulness of molecular dynamics to assess the structural integrity of mutants containing several mutations has been investigated. Our goal was to determine whether molecular dynamics would be able to discriminate mutants of a protein having a close-to-wild-type fold, from those that are not folded under the same conditions. We used as a model the B1 domain of protein G in which we replaced the unique central alpha-helix by the sequence of the second beta-hairpin, which has a strong intrinsic propensity to form this secondary structure in solution. In the resulting protein, one-third of the secondary structure has been replaced by a non-native one. Models of the mutants were built based on the three-dimensional structure of the wild-type GB1 domain. During 2 ns of molecular dynamics simulations on these models, mutants containing up to 10 mutations in the helix retained the native fold, while another mutant with an additional mutation unfolded. This result is in agreement with our circular dichroism and NMR experiments, which indicated that the former mutants fold into a structure similar to the wild-type, as opposed to the latter mutant which is partly unfolded. Additionally, a mutant containing six mutations scattered through the surface of the domain, and which is unfolded, was also detected by the simulation. This study suggests that molecular dynamics calculations could be performed on molecular models of mutants of a protein to evaluate their foldability, prior to a mutagenesis experiment.

The evolution of protein conformational dynamics contains important information about protein function and regulation. Here, we describe an approach to dynamical-evolution analysis based on multiple microsecond molecular dynamics simulations and residue–residue contact analysis. We illustrate our approach by comparing three human cyclophilin isoforms, cyclophilin A, D, and E, which belong to a family of enzymes catalyzing peptidyl-prolyl cis–trans isomerization. Our results reveal that despite distinct overall equilibrium conformations between cyclophilins under substrate-free conditions, functional dynamical changes resembling substrate-binding and catalytic processes tend to be conserved. Key residues displaying either concerted or specific dynamical changes among isoforms during the reactions are identified, which delineate two distinct allosteric pathways for cyclophilin function consistent with recent nuclear magnetic resonance experiments. A sequence-based coevolution analysis is also employed for f...

Experimental Polyproline II Propensities Describe Sequence-Dependent Variability in the Hydrodynamic Size of Intrinsically Disordered Proteins

Protein structure prediction is pivotal for understanding the structure-function relationship of proteins, advancing biological research, and facilitating pharmaceutical development and experimental design. While deep learning methods and the expanded availability of experimental 3D protein structures have accelerated structure prediction, the dynamic nature of protein structures has received limited attention. This study introduces an innovative 4D diffusion model incorporating molecular dynamics (MD) simulation data to learn dynamic protein structures. Our approach is distinguished by the following components: (1) a unified diffusion model capable of generating dynamic protein structures, including both the backbone and side chains, utilizing atomic grouping and side-chain dihedral angle predictions; (2) a reference network that enhances structural consistency by integrating the latent embeddings of the initial 3D protein structures; and (3) a motion alignment module aimed at improving temporal structural coherence across multiple time steps. To our knowledge, this is the first diffusion-based model aimed at predicting protein trajectories across multiple time steps simultaneously. Validation on benchmark datasets demonstrates that our model exhibits high accuracy in predicting dynamic 3D structures of proteins containing up to 256 amino acids over 32 time steps, effectively capturing both local flexibility in stable states and significant conformational changes.

The dynamics of monomeric Alzheimer Abeta1-40 in aqueous solution was studied using heteronuclear NMR experiments. 15N NMR relaxation rates of amide groups report on the dynamics in the peptide chain and make it possible to estimate structural propensities from temperature-dependent relaxation data and chemical shifts change analysis. The persistence length of the polypeptide chain was determined using a model in which the influence of neighboring residue relaxation is assumed to decay exponentially as a function of distance. The persistence length of the Abeta1-40 monomer was found to decrease from eight to three residues when temperature was increased from 3 to 18 degrees C. At 3 degrees C the peptide shows structural propensities that correlate well with the suggested secondary structure regions of the peptide to be present in the fibrils, and with the alpha-helical structure in membrane-mimicking systems. Our data leads to a structural model for the monomeric soluble beta-peptide with six different regions of secondary structure propensities. The peptide has two regions with beta-strand propensity (residues 16-24 and 31-40), two regions with high PII-helix propensity (residues 1-4 and 11-15) and two unstructured regions with higher mobility (residues 5-10 and 25-30) connecting the structural elements.

The study comprehensively analyzed the women’s wrestling qualification system across Olympic cycles using key parameters. The main research results reveal the evolution of selection criteria for female athletes in the Olympic Games, demonstrating dynamic changes in qualification mechanisms. The research methodology includes a comprehensive approach combining historical, statistical, and comparative analysis. A wide range of archival materials, statistical data from international sports organizations, and direct results of qualification tournaments were processed. This allowed not only tracing the historical dynamics of changes in the Olympic selection system but also identifying key trends and patterns in the development of women's wrestling on the international sports arena. Results include: a detailed characterization of athlete selection criteria across different Olympic cycles; a comprehensive analysis of the transformation in the quantitative composition of participants in Olympic weight categories; a historiography of world qualification tournaments for women’s wrestling; a comparative analysis of Olympic quota distribution across continents. The theoretical significance of the work lies in systematizing scientific knowledge about qualification processes in women’s wrestling, while its practical value is in the possibility of using the results to improve sports selection and predict Olympic perspectives. The study expands the scientific understanding of mechanisms for forming Olympic teams in women’s wrestling and can serve as a methodological basis for further scientific research in sports analytics. Particular attention is paid to analyzing evolutionary changes in the system of athlete selection, specifically the transformation of qualification requirements and criteria at different stages of women’s wrestling development. The obtained results are of significant importance for understanding the complex processes of forming Olympic teams, improving sports selection methodologies, and predicting the development prospects of women's wrestling in the context of the international sports movement.

Evolutionary changes that occur within the maize genome can be divided into two classes: In the protein-coding regions, mutations that survive selective pressure primarily consist of single nucleotide polymorphisms which evolve at a relatively slow rate (10-9 mutations/ bp/generation), and functionally detrimental insertions are strongly selected against. In intergenic regions rapidly evolving (10-4 10-8 mutations/bp/generation) transposon insertions and deletions predominate. While genic single nucleotide changes are expected in part to result in amino acid sequence variants leading to the modification of protein properties (catalytic properties of enzymes, binding constants, etc.), transposable elements and other large insertions and deletions, when functionally relevant, are predicted to be regulatory in nature and may affect gene expression at distances of up to 100 kb away. Here, we discuss recent experimental evidence for massive dynamic changes of maize intergenic regions and the predicted functional consequences of genome diversity within this species.