Chemical and structural diversity in cyclooxygenase protein active sites

Peptides Derived from a Plant Protease Inhibitor of the Coagulation Contact System Decrease Arterial Thrombus Formation in a Murine Model, without Impairing Hemostatic Parameters

Several plant protein inhibitors with anticoagulant properties have been studied and characterized, including the Delonix regia trypsin inhibitor (DrTI). This protein inhibits serine proteases (trypsin) and enzymes directly involved in coagulation, such as plasma kallikrein, factor XIIa, and factor XIa. In this study, we evaluated the effects of two new synthetic peptides derived from the primary sequence of DrTI in coagulation and thrombosis models to understand the mechanisms involved in the pathophysiology of thrombus formation as well as in the development of new antithrombotic therapies. Both peptides acted on in vitro hemostasis-related parameters, showing promising results, prolonging the Partially Activated Thromboplastin Time (aPTT) and inhibited platelet aggregation induced by adenosine diphosphate (ADP) and arachidonic acid. In murine models, for arterial thrombosis induced by photochemical injury, and platelet-endothelial interactions monitored by intravital microscopy, both peptides at doses of 0.5 mg/kg significantly extended the time of artery occlusion and modified the platelet adhesion and aggregation pattern with no changes in bleeding time, demonstrating the high biotechnological potential of both molecules.

Identification of drug combinations on the basis of machine learning to maximize anti-aging effects

Aging is a multifactorial process that involves numerous genetic changes, so identifying anti-aging agents is quite challenging. Age-associated genetic factors must be better understood to search appropriately for anti-aging agents. We utilized an aging-related gene expression pattern-trained machine learning system that can implement reversible changes in aging by linking combinatory drugs. In silico gene expression pattern-based drug repositioning strategies, such as connectivity map, have been developed as a method for unique drug discovery. However, these strategies have limitations such as lists that differ for input and drug-inducing genes or constraints to compare experimental cell lines to target diseases. To address this issue and improve the prediction success rate, we modified the original version of expression profiles with a stepwise-filtered method. We utilized a machine learning system called deep-neural network (DNN). Here we report that combinational drug pairs using differential expressed genes (DEG) had a more enhanced anti-aging effect compared with single independent treatments on leukemia cells. This study shows potential drug combinations to retard the effects of aging with higher efficacy using innovative machine learning techniques.

Genome-wide identification, evolution, expression, and alternative splicing profiles of peroxiredoxin genes in cotton

Peroxiredoxin (PRX) is a ubiquitous thioredoxin-dependent peroxidase that can eliminate excessive free radicals produced by stress and protect cells from oxidative damage. PRXs are also involved in reactive oxygen species (ROS)- and redox-dependent signaling by performing redox interactions with other proteins and modify their redox status. At present, PRX family identification, evolution and regulation research has been conducted in some plants; however, systematic research about this family is lacking in cotton. In this study, a total of 44 PRXs were identified in the cotton genome. Phylogenetic and conserved active site analyses showed that the PRXs were divided into six subfamilies according to the conserved site (PxxxTxxC…S…W/F) and conserved cysteinyl residues positions. Segmental duplication and polyploid events were the main methods for PRX family expansion, and the PRXs of diploid G. arboreum were the donors of PRXs in the D subgenomes of allotetraploid G. hirsutum and G. barbadense during the evolution of the PRX family. qRT-PCR analysis confirmed that cis-acting elements play important roles in regulating the expression of PRXs. Alternative splicing events occurred in GhPRX14-D that can increased the complexity of transcripts in G. hirsutum. Subcellular localization showed that most PRX members were located in chloroplasts, the cytoplasmic membrane and the nucleus. Our results provide systematic support for a better understanding of PRXs in cotton and a starting point for further studies of the specific functions of PRXs in cotton.

Isofunctional Clustering and Conformational Analysis of the Arsenate Reductase Superfamily Reveals Nine Distinct Clusters

Arsenate reductase (ArsC) is a superfamily of enzymes that reduce arsenate. Due to active site similarities, some ArsC can function as low-molecular weight protein tyrosine phosphatases (LMW-PTPs). Broad superfamily classifications align with redox partners (Trx- or Grx-linked). To understand this superfamily's mechanistic diversity, the ArsC superfamily is classified on the basis of active site features utilizing the tools TuLIP (two-level iterative clustering process) and autoMISST (automated multilevel iterative sequence searching technique). This approach identified nine functionally relevant (perhaps isofunctional) protein groups. Five groups exhibit distinct ArsC mechanisms. Three are Grx-linked: group 4AA (classical ArsC), group 3AAA (YffB-like), and group 5BAA. Two are Trx-linked: groups 6AAAAA and 7AAAAAAAA. One is an Spx-like transcriptional regulatory group, group 5AAA. Three are potential LMW-PTP groups: groups 7BAAAA, and 7AAAABAA, which have not been previously identified, and the well-studied LMW-PTP family group 8AAA. Molecular dynamics simulations were utilized to explore functional site details. In several families, we confirm and add detail to literature-based mechanistic information. Mechanistic roles are hypothesized for conserved active site residues in several families. In three families, simulations of the unliganded structure sample specific conformational ensembles, which are proposed to represent either a more ligand-binding-competent conformation or a pathway toward a more binding-competent state; these active sites may be designed to traverse high-energy barriers to the lower-energy conformations necessary to more readily bind ligands. This more detailed biochemical understanding of ArsC and ArsC-like PTP mechanisms opens possibilities for further understanding of arsenate bioremediation and the LMW-PTP mechanism.

"Azole" as privileged heterocycle for targeting the inducible cyclooxygenase enzyme

An over-expression of COX-2 isoenzyme belonging to the Cyclooxygenase Enzyme Family triggers the overproduction of pro-inflammatory prostaglandins that instigate the development of chronic inflammation and related disorders. Hence, the rationally designed drugs for mitigating over-activity of COX-2 isoenzyme play a regulatory role toward the alleviation of the progression of these disorders. However, a selective COX-2 inhibition chemotherapy prompts several side effects that necessitate the identification of novel molecular scaffolds for deliberating state-of-the-art drug designing strategies. The heterocyclic "azole" scaffold, being polar and hydrophilic, possesses remarkable physicochemical advantages for designing physiologically active molecules capable of interacting with a wide range of biological components, including enzymes, peptides, and metabolites. The substituted derivatives of azole nuclei enable a comprehensive SAR analysis for the appraisal of bioactive profile of the deliberated molecules for obtaining the rationally designed compounds with prominent activities. The comprehensive SAR analysis readily prompted the identification of Y-shaped molecules and the eminence of bulkier group for COX-2 selective inhibition. This review presents an epigrammatic collation of the pharmacophore-profile of the chemotherapeutics based on azole motif for a selective targeting of the COX-2 isoenzyme.

2-(4-Methylsulfonylphenyl)pyrimidines as Prospective Radioligands for Imaging Cyclooxygenase-2 with PET-Synthesis, Triage, and Radiolabeling

Cyclooxygenase 2 (COX-2) is an inducible enzyme responsible for the conversion of arachidonic acid into the prostaglandins, PGG2 and PGH2. Expression of this enzyme increases in inflammation. Therefore, the development of probes for imaging COX-2 with positron emission tomography (PET) has gained interest because they could be useful for the study of inflammation in vivo, and for aiding anti-inflammatory drug development targeting COX-2. Nonetheless, effective PET radioligands are still lacking. We synthesized eleven COX-2 inhibitors based on a 2(4-methylsulfonylphenyl)pyrimidine core from which we selected three as prospective PET radioligands based on desirable factors, such as high inhibitory potency for COX-2, very low inhibitory potency for COX-1, moderate lipophilicity, and amenability to labeling with a positron-emitter. These inhibitors, namely 6-methoxy-2-(4-(methylsulfonyl)phenyl-N-(thiophen-2ylmethyl)pyrimidin-4-amine (17), the 6-fluoromethyl analogue (20), and the 6-(2-fluoroethoxy) analogue (27), were labeled in useful yields and with high molar activities by treating the 6-hydroxy analogue (26) with [¹¹C]iodomethane, [¹⁸F]2-fluorobromoethane, and [d₂-¹⁸F]fluorobromomethane, respectively. [¹¹C]17, [¹⁸F]20, and [d₂-¹⁸F]27 were readily purified with HPLC and formulated for intravenous injection. These methods allow these radioligands to be produced for comparative evaluation as PET radioligands for measuring COX-2 in healthy rhesus monkey and for assessing their abilities to detect inflammation.

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.

DASP3: identification of protein sequences belonging to functionally relevant groups

Background

Development of automatable processes for clustering proteins into functionally relevant groups is a critical hurdle as an increasing number of sequences are deposited into databases. Experimental function determination is exceptionally time-consuming and can’t keep pace with the identification of protein sequences. A tool, DASP (Deacon Active Site Profiler), was previously developed to identify protein sequences with active site similarity to a query set. Development of two iterative, automatable methods for clustering proteins into functionally relevant groups exposed algorithmic limitations to DASP.

Results

The accuracy and efficiency of DASP was significantly improved through six algorithmic enhancements implemented in two stages: DASP2 and DASP3. Validation demonstrated DASP3 provides greater score separation between true positives and false positives than earlier versions. In addition, DASP3 shows similar performance to previous versions in clustering protein structures into isofunctional groups (validated against manual curation), but DASP3 gathers and clusters protein sequences into isofunctional groups more efficiently than DASP and DASP2.

Conclusions

DASP algorithmic enhancements resulted in improved efficiency and accuracy of identifying proteins that contain active site features similar to those of the query set. These enhancements provide incremental improvement in structure database searches and initial sequence database searches; however, the enhancements show significant improvement in iterative sequence searches, suggesting DASP3 is an appropriate tool for the iterative processes required for clustering proteins into isofunctional groups.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1295-z) contains supplementary material, which is available to authorized users.

Mutating a Highly Conserved Residue in Diverse Cytochrome P450s Facilitates Diastereoselective Olefin Cyclopropanation

Cytochrome P450s and other heme-containing proteins have recently been shown to have promiscuous activity for the cyclopropanation of olefins using diazoacetate reagents. Despite the progress made thus far, engineering selective catalysts for all possible stereoisomers for the cyclopropanation reaction remains a considerable challenge. Previous investigations of a model P450 (P450BM3 ) revealed that mutation of a conserved active site threonine (Thr268) to alanine transformed the enzyme into a highly active and selective cyclopropanation catalyst. By incorporating this mutation into a diverse panel of P450 scaffolds, we were able to quickly identify enantioselective catalysts for all possible diastereomers in the model reaction of styrene with ethyl diazoacetate. Some alanine variants exhibited selectivities that were markedly different from the wild-type enzyme, with a few possessing moderate to high diastereoselectivity and enantioselectivities up to 97 % for synthetically challenging cis-cyclopropane diastereomers.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods.

Analysis of the peroxiredoxin family: using active-site structure and sequence information for global classification and residue analysis

Peroxiredoxins (Prxs) are a widespread and highly expressed family of cysteine-based peroxidases that react very rapidly with H₂O₂, organic peroxides, and peroxynitrite. Correct subfamily classification has been problematic because Prx subfamilies are frequently not correlated with phylogenetic distribution and diverge in their preferred reductant, oligomerization state, and tendency toward overoxidation. We have developed a method that uses the Deacon Active Site Profiler (DASP) tool to extract functional-site profiles from structurally characterized proteins to computationally define subfamilies and to identify new Prx subfamily members from GenBank(nr). For the 58 literature-defined Prx test proteins, 57 were correctly assigned, and none were assigned to the incorrect subfamily. The >3500 putative Prx sequences identified were then used to analyze residue conservation in the active site of each Prx subfamily. Our results indicate that the existence and location of the resolving cysteine vary in some subfamilies (e.g., Prx5) to a greater degree than previously appreciated and that interactions at the A interface (common to Prx5, Tpx, and higher order AhpC/Prx1 structures) are important for stabilization of the correct active-site geometry. Interestingly, this method also allows us to further divide the AhpC/Prx1 into four groups that are correlated with functional characteristics. The DASP method provides more accurate subfamily classification than PSI-BLAST for members of the Prx family and can now readily be applied to other large protein families.

PREX: PeroxiRedoxin classification indEX, a database of subfamily assignments across the diverse peroxiredoxin family

PREX (http://www.csb.wfu.edu/prex/) is a database of currently 3516 peroxiredoxin (Prx or PRDX) protein sequences unambiguously classified into one of six distinct subfamilies. Peroxiredoxins are a diverse and ubiquitous family of highly expressed, cysteine-dependent peroxidases that are important for antioxidant defense and for the regulation of cell signaling pathways in eukaryotes. Subfamily members were identified using the Deacon Active Site Profiler (DASP) bioinformatics tool to focus in on functionally relevant sequence fragments surrounding key residues required for protein activity. Searches of this database can be conducted by protein annotation, accession number, PDB ID, organism name or protein sequence. Output includes the subfamily to which each classified Prx belongs, accession and GI numbers, genus and species and the functional site signature used for classification. The query sequence is also presented aligned with a select group of Prxs for manual evaluation and interpretation by the user. A synopsis of the characteristics of members of each subfamily is also provided along with pertinent references.

Active site profiling to identify protein functional sites in sequences and structures using the Deacon Active Site Profiler (DASP)

Methods for the annotation and analysis of functional sites in proteins are an area of active research, and those methods that allow detailed characterization of functional site features are much needed. A Web site application, DASP, which implements a previously described method (Cammer, et al., 2003) to allow users to create an active site profile for any protein family, is described. Two protocols for functional site analysis of protein families using DASP are presented: 1) creation of functional site signatures and a profile from proteins of known structure and 2) utilization of the active site profile to search sequences that contain fragments similar to those found in the functional site signatures. The active site profile produced by Basic Protocol 1 allows the user to analyze the features of the functional site, i.e., those characteristics that are common across the family and those that are unique to one or several members of the family. The characteristics that are unique to a subfamily might be described as specificity determinants i.e., features that impart specificity to a particular function. Basic Protocol 2 provides instructions for searching for sequences that might contain a similar functional site.

Functional site profiling and electrostatic analysis of cysteines modifiable to cysteine sulfenic acid

Cysteine sulfenic acid (Cys-SOH), a reversible modification, is a catalytic intermediate at enzyme active sites, a sensor for oxidative stress, a regulator of some transcription factors, and a redox-signaling intermediate. This post-translational modification is not random: specific features near the cysteine control its reactivity. To identify features responsible for the propensity of cysteines to be modified to sulfenic acid, a list of 47 proteins (containing 49 known Cys-SOH sites) was compiled. Modifiable cysteines are found in proteins from most structural classes and many functional classes, but have no propensity for any one type of protein secondary structure. To identify features affecting cysteine reactivity, these sites were analyzed using both functional site profiling and electrostatic analysis. Overall, the solvent exposure of modifiable cysteines is not different from the average cysteine. The combined sequence, structure, and electrostatic approaches reveal mechanistic determinants not obvious from overall sequence comparison, including: (1) pKaS of some modifiable cysteines are affected by backbone features only; (2) charged residues are underrepresented in the structure near modifiable sites; (3) threonine and other polar residues can exert a large influence on the cysteine pKa; and (4) hydrogen bonding patterns are suggested to be important. This compilation of Cys-SOH modification sites and their features provides a quantitative assessment of previous observations and a basis for further analysis and prediction of these sites. Agreement with known experimental data indicates the utility of this combined approach for identifying mechanistic determinants at protein functional sites.