Statistical coevolution analysis and molecular dynamics: identification of amino acid pairs essential for catalysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Estabrook RA
PROVIDER: S-EPMC545822 | biostudies-literature | 2005 Jan
REPOSITORIES: biostudies-literature
Publications
Statistical coevolution analysis and molecular dynamics: identification of amino acid pairs essential for catalysis.
Estabrook R August RA Luo Jia J Purdy Matthew M MM Sharma Vyas V Weakliem Paul P Bruice Thomas C TC Reich Norbert O NO
Proceedings of the National Academy of Sciences of the United States of America 20050118 4
Molecular dynamics (MD) simulations of HhaI DNA methyltransferase and statistical coupling analysis (SCA) data on the DNA cytosine methyltransferase family were combined to identify residues that are coupled by coevolution and motion. The highest ranking correlated pairs from the data matrix product (SCA.MD) are colocalized and form stabilizing interactions; the anticorrelated pairs are separated on average by 30 A and form a clear focal point centered near the active site. We suggest that these ...[more]
Similar Datasets
Project description:Enzymes are proteins that can efficiently catalyze specific biochemical reactions, and they are widely present in the human body. Developing an efficient method to identify human enzymes is vital to select enzymes from the vast number of human proteins and to investigate their functions. Nevertheless, only a limited amount of research has been conducted on the classification of human enzymes and nonenzymes. In this work, we developed a support vector machine- (SVM-) based predictor to classify human enzymes using the amino acid composition (AAC), the composition of k-spaced amino acid pairs (CKSAAP), and selected informative amino acid pairs through the use of a feature selection technique. A training dataset including 1117 human enzymes and 2099 nonenzymes and a test dataset including 684 human enzymes and 1270 nonenzymes were constructed to train and test the proposed model. The results of jackknife cross-validation showed that the overall accuracy was 76.46% for the training set and 76.21% for the test set, which are higher than the 72.6% achieved in previous research. Furthermore, various feature extraction methods and mainstream classifiers were compared in this task, and informative feature parameters of k-spaced amino acid pairs were selected and compared. The results suggest that our classifier can be used in human enzyme identification effectively and efficiently and can help to understand their functions and develop new drugs.
| S-EPMC7273372 | biostudies-literature
Project description:The process of amino acid replacement in proteins is context-dependent, with substitution rates influenced by local structure, functional role, and amino acids at other locations. Predicting how these differences affect replacement processes is difficult. To make such inference easier, it is often assumed that the acceptabilities of different amino acids at a position are constant. However, evolutionary interactions among residue positions will tend to invalidate this assumption. Here, we use simulations of purple acid phosphatase evolution to show that amino acid propensities at a position undergo predictable change after an amino acid replacement at that position. After a replacement, the new amino acid and similar amino acids tend to become gradually more acceptable over time at that position. In other words, proteins tend to equilibrate to the presence of an amino acid at a position through replacements at other positions. Such a shift is reminiscent of the spectroscopy effect known as the Stokes shift, where molecules receiving a quantum of energy and moving to a higher electronic state will adjust to the new state and emit a smaller quantum of energy whenever they shift back down to the original ground state. Predictions of changes in stability in real proteins show that mutation reversals become less favorable over time, and thus, broadly support our results. The observation of an evolutionary Stokes shift has profound implications for the study of protein evolution and the modeling of evolutionary processes.
| S-EPMC3361410 | biostudies-literature
Project description:Considering lack of validated therapeutic drugs or vaccines against contagious SARS-CoV2, various efforts have been focused on repurposing of existing drugs or identifying new agents. In an attempt to identify new and potential SARS-CoV2 inhibitors targeting specific enzyme of the pathogen, a few induced fit models of SARS-CoV2 main protease (Mpro) including N-aryl amide and aryl sulfonamide based fragments were subjected to a multi-step in silico strategy. Sub-structure query of co-crystallographic fragments provided numerous ZINC15 driven commercially available compounds that entered molecular docking stage to find binding interactions/modes inside Mpro active site. Docking results were reevaluated through time dependent stability of top-ranked ligand-protease complexes by molecular dynamics (MD) simulations within 50 ns. Relative contribution of interacted residues in binding to the most probable binding pose was estimated through amino acid decomposition analysis in B3LYP level of theory with Def2-TZVPP split basis set. In confirmation of docking results, MD simulations revealed less perceptible torsional distortions (more stable binding mode) in binding of ZINC_252512772 (ΔGb -9.18 kcal/mol) into Mpro active site. H-bond interactions and hydrophobic contacts were determinant forces in binding interactions of in silico hit. Quantum chemical calculations confirmed MD results and proved the pivotal role of a conserved residue (Glu166) in making permanent hydrogen bond (98% of MD simulations time) with ZINC_252512772. Drug-like physicochemical properties as well as desirable target binding interactions nominated ZINC_252512772 as a desirable in silico hit for further development toward SARS-CoV2 inhibitors. Highlights A few N-aryl amide/aryl sulfonamide based fragments were subjected to a multi-step in silico strategy to afford potential SARS-CoV2 Mpro inhibitors. MD simulations revealed less perceptible torsional distortions (more stable binding mode) in binding of ZINC_252512772 (ΔGb -9.18 kcal/mol) into Mpro active site. H-bond interactions and hydrophobic contacts were determinant forces in binding interactions of in silico hit. Quantum chemical calculations confirmed MD results and proved pivotal role of a conserved residue (Glu166) in making permanent hydrogen bond (98% of MD simulations time) with ZINC_252512772. Communicated by Ramaswamy H. Sarma.
| S-EPMC7441780 | biostudies-literature
Project description:Nisin is a posttranslationally-modified antimicrobial peptide that has the ability to induce its own biosynthesis. Serines and threonines in the modifiable core peptide part of precursor nisin are dehydrated to dehydroalanines and dehydrobutyrines by the dehydratase NisB, and subsequently cysteines are coupled to the dehydroamino acids by the cyclase NisC. In this study, we applied extensive site-directed mutagenesis, together with direct binding studies, to investigate the molecular mechanism of the dehydratase NisB. We use a natural nisin-producing strain as a host to probe mutant-NisB functionality. Importantly, we are able to differentiate between intracellular and secreted fully dehydrated precursor nisin, enabling investigation of the NisB properties needed for the release of dehydrated precursor nisin to its devoted secretion system NisT. We report that single amino acid substitutions of conserved residues, i.e., R83A, R83M, and R87A result in incomplete dehydration of precursor nisin and prevention of secretion. Single point NisB mutants Y80F and H961A, result in a complete lack of dehydration of precursor nisin, but do not abrogate precursor nisin binding. The data indicate that residues Y80 and H961 are directly involved in catalysis, fitting well with their position in the recently published 3D-structure of NisB. We confirm, by in vivo studies, results that were previously obtained from in vitro experiments and NisB structure elucidation and show that previous findings translate well to effects seen in the original production host.
| S-EPMC4341554 | biostudies-literature
Project description:As complete genomes accumulate and the generation of genomic biodiversity proceeds at an accelerating pace, the need to understand the interaction between sequence evolution and protein structure and function rises in prominence. The pattern and pace of substitutions in proteins can provide important clues to functional importance, functional divergence, and adaptive response. Coevolution between amino acid residues and the context dependence of the evolutionary process are often ignored, however, because of their complexity, but they are critical for the accurate interpretation of reconstructed evolutionary events. Because residues interact with one another, and because the effect of substitutions can depend on the structural and physiological environment in which they occur, an accurate science of evolutionary functional genomics and a complete understanding of selection in proteins require a better understanding of how context dependence affects protein evolution. Here, we present new evidence from vertebrate cytochrome oxidase sequences that pairwise coevolutionary interactions between protein residues are highly dependent on tertiary and secondary structure. We also discuss theoretical predictions that impinge on our expectations of how protein residues may interact over long distances because of their shared need to maintain protein stability.
| S-EPMC2943952 | biostudies-literature
Project description:Protein function arises from a poorly understood pattern of energetic interactions between amino acid residues. Sequence-based strategies for deducing this pattern have been proposed, but lack of benchmark data has limited experimental verification. Here, we extend deep-mutation technologies to enable measurement of many thousands of pairwise amino acid couplings in several homologs of a protein family - a deep coupling scan (DCS). The data show that cooperative interactions between residues are loaded in a sparse, evolutionarily conserved, spatially contiguous network of amino acids. The pattern of amino acid coupling is quantitatively captured in the coevolution of amino acid positions, especially as indicated by the statistical coupling analysis (SCA), providing experimental confirmation of the key tenets of this method. This work exposes the collective nature of physical constraints on protein function and clarifies its link with sequence analysis, enabling a general practical approach for understanding the structural basis for protein function.
| S-EPMC6117156 | biostudies-literature
Project description:The pattern of amino acid residue replacement in the components of the bursicon signaling system (involving the BURS?/BURS? heterodimer and its receptor BURSrec) was reconstructed across a phylogeny of 17 insect species, in order to test for the co-occurrence of replacements at sets of individual sites. Sets of three or more branches with perfectly concordant changes occurred to a greater extent than expected by chance, given the observed level of amino acid change. The latter sites (SPC sites) were found to have distinctive characteristics: (1) the mean number of changes was significantly lower at SPC sites than that at other sites with multiple changes; (2) SPC sites had a significantly greater tendency toward parallel amino acid changes than other sites with multiple changes, but no greater tendency toward convergent changes; and (3) parallel changes tended to involve relatively similar amino acids, as indicated by relatively low mean chemical distances. The results implicated functional constraint, permitting only a limited subset of amino acids in a given site, as a major factor in causing both parallel amino acid replacement and coordinated amino acid changes in different sites of the same protein and of interacting proteins in this system.
| S-EPMC3427790 | biostudies-literature
Project description:BACKGROUND: One of the key forces shaping proteins is coevolution of amino acid residues. Knowing which residues coevolve in a particular protein may facilitate our understanding of protein evolution, structure and function, and help to identify substitutions that may lead to desired changes in enzyme kinetics. Rubisco, the most abundant enzyme in biosphere, plays an essential role in the process of carbon fixation through photosynthesis, thus facilitating life on Earth. This makes Rubisco an important model system for studying the dynamics of protein fitness optimization on the evolutionary landscape. In this study we investigated the selective and coevolutionary forces acting on large subunit of land plants Rubisco using Markov models of codon substitution and clustering approaches applied to amino acid substitution histories. RESULTS: We found that both selection and coevolution shape Rubisco, and that positively selected and coevolving residues have their specifically favored amino acid composition and pairing preference. The mapping of these residues on the known Rubisco tertiary structures showed that the coevolving residues tend to be in closer proximity with each other compared to the background, while positively selected residues tend to be further away from each other. This study also reveals that the residues under positive selection or coevolutionary force are located within functionally important regions and that some residues are targets of both positive selection and coevolution at the same time. CONCLUSION: Our results demonstrate that coevolution of residues is common in Rubisco of land plants and that there is an overlap between coevolving and positively selected residues. Knowledge of which Rubisco residues are coevolving and positively selected could be used for further work on structural modeling and identification of substitutions that may be changed in order to improve efficiency of this important enzyme in crops.
| S-EPMC3190394 | biostudies-literature
Project description:Prokaryotic proteins are regulated by pupylation, a type of post-translational modification that contributes to cellular function in bacterial organisms. In pupylation process, the prokaryotic ubiquitin-like protein (Pup) tagging is functionally analogous to ubiquitination in order to tag target proteins for proteasomal degradation. To date, several experimental methods have been developed to identify pupylated proteins and their pupylation sites, but these experimental methods are generally laborious and costly. Therefore, computational methods that can accurately predict potential pupylation sites based on protein sequence information are highly desirable. In this paper, a novel predictor termed as pbPUP has been developed for accurate prediction of pupylation sites. In particular, a sophisticated sequence encoding scheme [i.e. the profile-based composition of k-spaced amino acid pairs (pbCKSAAP)] is used to represent the sequence patterns and evolutionary information of the sequence fragments surrounding pupylation sites. Then, a Support Vector Machine (SVM) classifier is trained using the pbCKSAAP encoding scheme. The final pbPUP predictor achieves an AUC value of 0.849 in 10-fold cross-validation tests and outperforms other existing predictors on a comprehensive independent test dataset. The proposed method is anticipated to be a helpful computational resource for the prediction of pupylation sites. The web server and curated datasets in this study are freely available at http://protein.cau.edu.cn/pbPUP/.
| S-EPMC4469302 | biostudies-literature
Project description:Class I terpene synthases generate the structural core of bioactive terpenoids. Deciphering structure-function relationships in the reactive closed complex and targeted engineering is hampered by highly dynamic carbocation rearrangements during catalysis. Available crystal structures, however, represent the open, catalytically inactive form or harbor nonproductive substrate analogs. Here, we present a catalytically relevant, closed conformation of taxadiene synthase (TXS), the model class I terpene synthase, which simulates the initial catalytic time point. In silico modeling of subsequent catalytic steps allowed unprecedented insights into the dynamic reaction cascades and promiscuity mechanisms of class I terpene synthases. This generally applicable methodology enables the active-site localization of carbocations and demonstrates the presence of an active-site base motif and its dominating role during catalysis. It additionally allowed in silico-designed targeted protein engineering that unlocked the path to alternate monocyclic and bicyclic synthons representing the basis of a myriad of bioactive terpenoids.
| S-EPMC4776449 | biostudies-literature