Relationship between protein folding kinetics and amino acid properties

Velocity control of protein translocation through a nanopore by tuning the fraction of benzenoid residues

Protein sequencing is essential to unveil the mechanism of cellular processes that govern the function of living organisms, and which play a crucial role in the field of drug design and molecular diagnostics. Nanopores have been proved to be effective tools in single molecule sensing, but the fast translocation speed of a peptide through a nanopore is one of the major obstacles that hinders the development of nanopore-based protein sequencing. In this work, by using molecular dynamics simulations (MDS) it is found that the peptide containing more hydrophobic residues permeates slower through a molybdenum disulfide nanopore, which originates from the strong interaction between the membrane surface and the hydrophobic residues. The binding affinity is remarkable especially for benzenoid residues as they contain a hydrophobic aromatic ring that is composed of relatively non-polar C-C and C-H bonds. By tuning the fraction of benzenoid residues of the peptide, the velocity of the protein translocation through the nanopore is well controlled. The peptide with all the hydrophobic residues being benzenoid residues is found to translocate through the nanopore almost ten times slower than the one without any benzenoid residues, which is beneficial for gathering adequate information for precise amino acid identification.

PFDB: A standardized protein folding database with temperature correction

We constructed a standardized protein folding kinetics database (PFDB) in which the logarithmic rate constants of all listed proteins are calculated at the standard temperature (25 °C). A temperature correction based on the Eyring–Kramers equation was introduced for proteins whose folding kinetics were originally measured at temperatures other than 25 °C. We verified the temperature correction by comparing the logarithmic rate constants predicted and experimentally observed at 25 °C for 14 different proteins, and the results demonstrated improvement of the quality of the database. PFDB consists of 141 (89 two-state and 52 non-two-state) single-domain globular proteins, which has the largest number among the currently available databases of protein folding kinetics. PFDB is thus intended to be used as a standard for developing and testing future predictive and theoretical studies of protein folding. PFDB can be accessed from the following link: http://lee.kias.re.kr/~bala/PFDB.

A novel model-based on FCM-LM algorithm for prediction of protein folding rate

The prediction of protein folding rates is of paramount importance in describing the protein folding mechanism, which has broad applications in fields such as enzyme engineering and protein engineering. Therefore, predicting protein folding rates using the first-order of protein sequence, secondary structure and amino acid properties has become a very active research topic in recent years. This paper presents a new fuzzy cognitive map (FCM) model based on deep learning neural networks which uses data obtained from biological experiments to predict the protein folding rate. FCM extracts the important data features from the protein sequence which then initializes the deep neural networks effectively. It was found that the Levenberg-Marquardt (LM) algorithm for deep neural networks can improve the prediction accuracy of the protein folding rates. The correlation coefficient between the predicted values and those real values obtained from experiments reached 0.94 and 0.9 in two independent numerical tests.

Network measures for protein folding state discrimination

Proteins fold using a two-state or multi-state kinetic mechanisms, but up to now there is not a first-principle model to explain this different behavior. We exploit the network properties of protein structures by introducing novel observables to address the problem of classifying the different types of folding kinetics. These observables display a plain physical meaning, in terms of vibrational modes, possible configurations compatible with the native protein structure, and folding cooperativity. The relevance of these observables is supported by a classification performance up to 90%, even with simple classifiers such as discriminant analysis.

Analysis of molecular structures and mechanisms for toxins derived from venomous animals

As predominant component in the venom of many dangerous animal species, toxins have been thoroughly investigated for drug design or as pharmacologic tools. The present study demonstrated the use of size and hydrophobicity of amino acid residues for the purposes of quantifying the valuable sequence-structure relationship and performing further analysis of interactional mechanisms in secondary structure elements (SSEs) for toxin native conformations. First, we showed that the presence of large and hydrophobic residues varying in availability in the primary sequences correspondingly affects the amount of these residues being used in the SSEs in accordance with linear behavioral patterns from empirical assessments of experimentally derived toxins and non-toxins. Subsequent derivation of prediction rules was established with the aim of analyzing molecular structures and mechanisms by means of 114 residue compositions for venom toxins. The obtained results concerning the linear behavioral patterns demonstrated the nature of the information transfer occurring from the primary to secondary structures. A dual action mechanism was established, taking into account steric and hydrophobic interactions. Finally, a new residue composition prediction method for SSEs of toxins was suggested.

Reduced alphabet for protein folding prediction

What are the key building blocks that would have been needed to construct complex protein folds? This is an important issue for understanding protein folding mechanism and guiding de novo protein design. Twenty naturally occurring amino acids and eight secondary structures consist of a 28-letter alphabet to determine folding kinetics and mechanism. Here we predict folding kinetic rates of proteins from many reduced alphabets. We find that a reduced alphabet of 10 letters achieves good correlation with folding rates, close to the one achieved by full 28-letter alphabet. Many other reduced alphabets are not significantly correlated to folding rates. The finding suggests that not all amino acids and secondary structures are equally important for protein folding. The foldable sequence of a protein could be designed using at least 10 folding units, which can either promote or inhibit protein folding. Reducing alphabet cardinality without losing key folding kinetic information opens the door to potentially faster machine learning and data mining applications in protein structure prediction, sequence alignment and protein design.

A comprehensive database of verified experimental data on protein folding kinetics

Insights into protein folding rely increasingly on the synergy between experimental and theoretical approaches. Developing successful computational models requires access to experimental data of sufficient quantity and high quality. We compiled folding rate constants for what initially appeared to be 184 proteins from 15 published collections/web databases. To generate the highest confidence in the dataset, we verified the reported lnkf value and exact experimental construct and conditions from the original experimental report(s). The resulting comprehensive database of 126 verified entries, ACPro, will serve as a freely accessible resource (https://www.ats.amherst.edu/protein/) for the protein folding community to enable confident testing of predictive models. In addition, we provide a streamlined submission form for researchers to add new folding kinetics results, requiring specification of all the relevant experimental information according to the standards proposed in 2005 by the protein folding consortium organized by Plaxco. As the number and diversity of proteins whose folding kinetics are studied expands, our curated database will enable efficient and confident incorporation of new experimental results into a standardized collection. This database will support a more robust symbiosis between experiment and theory, leading ultimately to more rapid and accurate insights into protein folding, stability, and dynamics.

Sequence analysis on the information of folding initiation segments in ferredoxin-like fold proteins

BACKGROUND

While some studies have shown that the 3D protein structures are more conservative than their amino acid sequences, other experimental studies have shown that even if two proteins share the same topology, they may have different folding pathways. There are many studies investigating this issue with molecular dynamics or Go-like model simulations, however, one should be able to obtain the same information by analyzing the proteins' amino acid sequences, if the sequences contain all the information about the 3D structures. In this study, we use information about protein sequences to predict the location of their folding segments. We focus on proteins with a ferredoxin-like fold, which has a characteristic topology. Some of these proteins have different folding segments.

RESULTS

Despite the simplicity of our methods, we are able to correctly determine the experimentally identified folding segments by predicting the location of the compact regions considered to play an important role in structural formation. We also apply our sequence analyses to some homologues of each protein and confirm that there are highly conserved folding segments despite the homologues' sequence diversity. These homologues have similar folding segments even though the homology of two proteins' sequences is not so high.

CONCLUSION

Our analyses have proven useful for investigating the common or different folding features of the proteins studied.

Phenylalanine and tyrosine methyl ester intramolecular interactions and conformational analysis by (1)H NMR and infrared spectroscopies and theoretical calculations

Amino acid conformational analysis in solution are scarce, since these compounds present a bipolar zwitterionic structure ((+)H3NCHRCOO(-)) in these media. Also, intramolecular hydrogen bonds have been classified as the sole interactions governing amino acid conformational behavior in the literature. In the present work we propose phenylalanine and tyrosine methyl ester conformational studies in different solvents by (1)H NMR and infrared spectroscopies and theoretical calculations. Both experimental and theoretical results are in agreement and suggest that the conformational behavior of the phenylalanine and tyrosine methyl esters are similar and are dictated by the interplay between steric and hyperconjugative interactions.