A glimpse into the clinical proteome of human malaria parasites Plasmodium falciparum and Plasmodium vivax

Malaria causes a worldwide annual mortality of about a million people. Rapidly evolving drug-resistant species of the parasite have created a pressing need for the identification of new drug targets and vaccine candidates. By developing fractionation protocols to enrich parasites from low-parasitemia patient samples, we have carried out the first ever proteomics analysis of clinical isolates of early stages of Plasmodium falciparum (Pf) and P. vivax. Patient-derived malarial parasites were directly processed and analyzed using shotgun proteomics approach using high-sensitivity MS for protein identification. Our study revealed about 100 parasite-coded gene products that included many known drug targets such as Pf hypoxanthine guanine phosphoribosyl transferase, Pf L-lactate dehydrogenase, and Plasmepsins. In addition, our study reports the expression of several parasite proteins in clinical ring stages that have never been reported in the ring stages of the laboratory-cultivated parasite strain. This proof-of-principle study represents a noteworthy step forward in our understanding of pathways elaborated by the parasite within the malaria patient and will pave the way towards identification of new drug and vaccine targets that can aid malaria therapy.     

Structural modeling and docking studies of ribose 5-phosphate isomerase from Leishmania major and Homo sapiens: A comparative analysis for Leishmaniasis treatment

Leishmaniases are caused by protozoa of the genus Leishmania and are considered the second-highest cause of death worldwide by parasitic infection. The drugs available for treatment in humans are becoming ineffective mainly due to parasite resistance; therefore, it is extremely important to develop a new chemotherapy against these parasites. A crucial aspect of drug design development is the identification and characterization of novel molecular targets. In this work, through an in silico comparative analysis between the genomes of Leishmania major and Homo sapiens, the enzyme ribose 5-phosphate isomerase (R5PI) was indicated as a promising molecular target. R5PI is an important enzyme that acts in the pentose phosphate pathway and catalyzes the interconversion of d-ribose-5-phosphate (R5P) and d-ribulose-5-phosphate (5RP). R5PI activity is found in two analogous groups of enzymes called RpiA (found in H. sapiens) and RpiB (found in L. major). Here, we present the first report of the three-dimensional (3D) structures and active sites of RpiB from L. major (LmRpiB) and RpiA from H. sapiens (HsRpiA). Three-dimensional models were constructed by applying a hybrid methodology that combines comparative and ab initio modeling techniques, and the active site was characterized based on docking studies of the substrates R5P (furanose and ring-opened forms) and 5RP. Our comparative analyses show that these proteins are structural analogs and that distinct residues participate in the interconversion of R5P and 5RP. We propose two distinct reaction mechanisms for the reversible isomerization of R5P to 5RP, which is catalyzed by LmRpiB and HsRpiA. We expect that the present results will be important in guiding future molecular modeling studies to develop new drugs that are specially designed to inhibit the parasitic form of the enzyme without significant effects on the human analog.     

Phosphoproteomics for the discovery of kinases as cancer biomarkers and drug targets

Early detection and targeted therapy represent a novel regimen of cancer management. The understanding of receptor tyrosine kinases in tumorigenesis at the molecular level has led to the first generation of kinase inhibitors for anticancer therapy that targets a specific kinase or pathway. While the therapeutic advantage is obvious, targeted therapy often relapses and results in drug resistance for advanced cancers. To achieve feasible early detection and better efficacy of therapeutics targeting multiple pathways, significantly more biomarkers and drug targets are in demand, especially for individualized therapy. Recent advances in phosphoprotein enrichment and MS technologies for quantitative phosphoproteome analysis provide great opportunities in the identification and validation of kinases as drug targets. The MS-based phosphoproteomic technologies would be useful tools as well for the identification of phosphosignatures unique to a specific type or subtype of cancer and drug responsive biomarkers. This review summarizes the major kinases acting as cancer biomarkers and drug targets, the advances of MS-based phosphoproteomic technologies, and some potential values and challenges of this emerging phosphoproteomics-based biomarker and drug target discovery field. Strategies for global, targeted, and quantitative phosphoproteomics are discussed, and some recent interesting applications are also evaluated.     

Searching for potential biomarkers of cisplatin resistance in human ovarian cancer using a label-free LC/MS-based protein quantification method

Platinum-based chemotherapy, such as cisplatin, is the primary treatment for ovarian cancer. However, drug resistance has become a major impediment to the successful treatment of ovarian cancer. To date, the molecular mechanisms of resistance to platinum-based chemotherapy remain unclear. In this study, we applied an LC/MS-based protein quantification method to examine the global protein expression of two pairs of ovarian cancer cell lines, A2780/A2780-CP (cisplatin-sensitive/cisplatin-resistant) and 2008/2008-C13*5.25 (cisplatin-sensitive/cisplatin-resistant). We identified and quantified over 2000 proteins from these cell lines and 760 proteins showed significant expression changes with a false discovery rate of less than 5% between paired groups. Based on the results we obtained, we suggest several potential pathways that may be involved in cisplatin resistance in human ovarian cancer. This study provides not only a new proteomic platform for large-scale quantitative protein analysis, but also important information for discovery of potential biomarkers of cisplatin resistance in ovarian cancer. Furthermore, these results may be clinically relevant for diagnostics, prognostics, and therapeutic improvement for ovarian cancer treatment.     

A comparative proteomic study to characterize the vinblastine resistance in human ovarian cancer cells

Drug resistance is a major impediment to the successful treatment of human cancers, including ovarian cancer. Vinblastine (VLB), an antimicrotubule agent, is one of the chemotherapeutic drugs that exhibit resistance in ovarian cancer patients. To determine the protein factors that are involved in vinblastine resistance in human ovarian cancer cells, a combination of sample pre-fractionation and high-resolution 2-DE proteomic analysis was performed. Approximately 1200 proteins were detected and quantitatively compared in both nuclear/membrane and cytosolic fractions. Sixty-nine proteins from the nuclear/membrane fraction showed altered expression levels, whereas 59 were altered in the cytosolic fraction between SKOV3 (vinblastine-sensitive) and SKVLB (vinblastine-resistant) cell lines. These proteins include membrane-associated, chromatin remodeling, cytoskeletal, and microtubule-associated proteins as well as others that regulate signal transduction. This study not only demonstrates a novel understanding of the mechanism of drug resistance but also provides a valuable resource for future studies on drug resistance to vinblastine. In addition, it also represents a good example of how to increase the protein dynamic range and reduce sample complexity using currently available tools.     

De novo lead optimization of triazine derivatives identifies potent antimalarials

Malaria is a life-threatening disease caused by Plasmodium parasites among which Plasmodium falciparum is the most deadly. Due to the widespread resistance of the current antimalarial drugs, intense research efforts are focused on identification of new and potent antimalarials. We report here, a structure based drug discovery strategy for design of a series of effective and novel triazine based antimalarials. The X-ray structure of P. falciparum methyl transferase (PfPMT) is used as a target as it is unique to the parasite. The triazine molecules designed and synthesized showed low micro-molar activity against malarial parasite cell lines. Molecular dynamics simulations on the PfPMT-inhibitor complex shed light on the inhibition mechanism for further optimization of the lead compounds.     

Proteomics in rheumatology: The beginning of a fairy tale?

One of the major challenges in proteome research is to translate its applications to the setting of human diseases. Proteomics in rheumatology is an area with marked potential including applications ranging from diagnostics, over therapeutic monitoring to discovery of new potential therapeutic targets. Biomarkers will be essential to discriminate between clinical similar rheumatic diseases, to monitor disease-states or to install the best appropriate therapy. Especially in the field of rheumatology, analysis of specific genes and/or their expression products by pharmacogenetics/-genomics or pharmacoproteomics could be necessary to enable an effective, patient-tailored therapy. In rheumatology, direct examination of proteins may be of utmost importance, as it is already known that PTMs, such as citrullination of proteins or peptides, may be involved in certain rheumatic diseases. The discovery and validation of antibodies directed against citrullinated proteins/peptides in rheumatic diseases using proteome analysis approaches has been described. Gel-free methods, SELDI-approaches and classic 2-DE approaches have been deployed on body fluids as well as on target tissues in different rheumatic diseases. Proteomics in rheumatology is on the rise and pilot studies have indicated that the application of proteomics-based technologies in rheumatic diseases appears to be an exciting example of translational research.     

Proteomics in Drug Development: The Dawn of a New Era?

Mass spectrometry offers the potential of acquiring high resolution data depicting the functional status of a group of healthy or diseased individuals, according to different conditions. As most of the drugs are currently targeting proteins, proteomics has a dual value, both in the discovery of new molecules as therapeutic targets, but also as a methodology to perform high throughput drug profiling. As there is an evident need for drugs to be improved in terms of efficacy, a mechanistic insight for downstream effectors can be valuable in order to predict side effects and resistance mechanisms. Recently developed assays, like thermal proteome profiling enables comprehensive drug target profiling and is, therefore, of high value in drug discovery. In this review, a systematic literature search is conducted and the most prominent proteomics studies as implicated in assisting drug discovery and development is presented. Focus is placed on investigations that are closer to implementation, therefore particular emphasis is given in studies conducted in human diseased population and further verified in vitro or in vivo.     

Relaxed complex scheme suggests novel inhibitors for the lyase activity of DNA polymerase beta

DNA polymerase beta (pol β), the error-prone polymerase of base excision repair, plays a significant role in chemotherapeutic agent resistance. Its over expression reduces the efficacy of anticancer drug therapies including ionizing radiation, bleomycin, monofunctional alkylating agents and cisplatin. Small-scale studies on different types of cancer showed that pol β is mutated in approximately 30% of tumors. These mutations further lower pol β fidelity in DNA synthesis exposing the genome to serious mutations. These findings suggested pol β as a promising therapeutic target for cancer treatment. More than 60 pol β-inhibitors have been identified so far, however, most of them are either not potent or specific enough to become a drug. Here, we applied the relaxed complex scheme virtual screening (RCSVS) to allow for the full receptor flexibility in filtering the NCI diversity set, DrugBank compounds and a library of ～ 9000 fragmental compounds for novel pol β inhibitors. In this procedure we screened the set of ～ 12,500 compounds against an ensemble of 11 dominant-receptor structures representing the essential backbone dynamics of the 8 kDa domain of pol β. Our results predicted new compounds that can bind with higher affinity to the lyase active site compared to pamoic acid (PA), a well-known inhibitor of DNA pol β.     

Proteomic analysis of high-molecular-weight protein polymers in a doxorubicin-resistant breast-cancer cell line

We recently reported that increased transglutaminase 2 (TGase 2) expression correlates with increased resistance to the cancer drug doxorubicin in breast-cancer cell lines. Interestingly, high-molecular-weight (HMW) proteins also increased with increased TGase 2 expression in the drug-resistant cell lines. TGase 2 is likely to be responsible for the formation of HMW proteins, because TGase 2 catalyzes cross-linking between proteins. Although the role of the HMW proteins is unclear, we demonstrated that TGase 2 inhibition increases drug sensitivity in breast-cancer cells. Herein we find that TGase 2 inhibition by cystamine dramatically reduces the level of HMW proteins. Identification of the HMW proteins may suggest the mechanism of cancer drug resistance associated with aberrant TGase 2 function. To explore the identities of HMW proteins, we performed in-gel tryptic digestions of unresolved HMW proteins and analyzed the resulting peptides using LC-MALDI-MS/MS. Most of the identified proteins were associated with gene regulation, such as polyadenylate-binding proteins, translation initiation factors, and ribonucleoproteins. This finding suggests that TGase 2 may participate in gene regulation, in addition to its role in cell adhesion.     

Human pathogenic streptococcal proteomics and vaccine development

Gram-positive streptococci are non-motile, chain-forming bacteria commonly found in the normal oral and bowel flora of warm-blooded animals. Over the past decade, a proteomic approach combining 2-DE and MS has been used to systematically map the cellular, surface-associated and secreted proteins of human pathogenic streptococcal species. The public availability of complete streptococcal genomic sequences and the amalgamation of proteomic, genomic and bioinformatic technologies have recently facilitated the identification of novel streptococcal vaccine candidate antigens and therapeutic agents. The objective of this review is to examine the constituents of the streptococcal cell wall and secreted proteome, the mechanisms of transport of surface and secreted proteins, and describe the current methodologies employed for the identification of novel surface-displayed proteins and potential vaccine antigens.     

A structural insight into the inhibitory mechanism of an orally active PI3K/mTOR dual inhibitor,PKI-179 using computational approaches

The PI3K/AKT/mTOR signaling pathway has been identified as an important target for cancer therapy. Attempts are increasingly made to design the inhibitors against the key proteins of this pathway for anti-cancer therapy. The PI3K/mTOR dual inhibitors have proved more effective than the inhibitors against only single protein targets. Recently discovered PKI-179, an orally effective compound, is one such dual inhibitor targeting both PI3K and mTOR. This anti-cancer compound is efficacious both in vitro and in vivo. However, the binding mechanisms and the molecular interactions of PKI-179 with PI3K and mTOR are not yet available. The current study investigated the exact binding mode and the molecular interactions of PKI-179 with PI3Kγ and mTOR using molecular docking and (un)binding simulation analyses. The study identified PKI-179 interacting residues of both the proteins and their importance in binding was ranked by the loss in accessible surface area, number of molecular interactions of the residue, and consistent appearance of the residue in (un)binding simulation analysis. The key residues involved in binding of PKI-179 were Ala-805 in PI3Kγ and Ile-2163 in mTOR as they have lost maximum accessible surface area due to binding. In addition, the residues which played a role in binding of the drug but were away from the catalytic site were also identified using (un)binding simulation analyses. Finally, comparison of the interacting residues in the respective catalytic sites was done for the difference in the binding of the drug to the two proteins. Thus, the pairs of the residues falling at the similar location with respect to the docked drug were identified. The striking similarity in the interacting residues of the catalytic site explains the concomitant inhibition of both proteins by a number of inhibitors. In conclusion, the docking and (un)binding simulation analyses of dual inhibitor PKI-179 with PI3K and mTOR will provide a suitable multi-target model for studying drug–protein interactions and thus help in designing the novel drugs with higher potency.     

The proteomics of cancer stem cells: potential clinical applications for innovative research in oncology

Cancer stem cells (CSCs) or tumour-maintaining cells are becoming an important new reality in oncology. The intriguing molecular pathophysiology of CSCs may justify some of the obscure pathogenetic, diagnostic, prognostic, and above all, therapeutic aspects of cancer and, eventually, lead to new solutions in oncology. CSC is a cell within the tumour that possesses the capacity to self-renew and, in doing so, gives rise to the heterogeneous lineages that comprise the tumour. The precise identification of this peculiar subpopulation of cancer cells, which has some intriguing similarities to normal stem cells, is becoming an important and urgent topic in oncology. In fact, some debated CSC markers have been already adopted by pharmacological research as targets of new and/or old anticancer drugs, showing an intriguing therapeutic index. These discussed identification markers include cell surface proteins, different activated signalling pathways, several molecules of the stem cell niche, various drug resistance mechanisms (ABCG2 and ALDH), telomerase, oncogenes and oncosuppressors (p16INK4 - Rb) and lastly, various microRNAs. In this new promising area of cancer research, proteomics, in general, and oncoproteomics, in particular, can and must play a significant role if the methodological approaches and the experimental protocols are correctly designed and interpreted.     

The emerging field of chemo- and pharmacoproteomics

The emerging field of chemo- and pharmacoproteomics studies the mechanisms of action of bioactive molecules in a systems pharmacology context. In contrast to traditional drug discovery, pharmacoproteomics integrates the mechanism of a drug's action, its side effects including toxicity, and the discovery of new drug targets in a single approach. Thus, it determines early favorable (e.g. multiple kinase target in cancer drugs) and unfavorable (e.g. side effects) polypharmacology. Target profiling is accomplished using either active site-labeling probes or immobilized drugs. This strategy identifies direct targets and has in fact enabled even the determination of binding curves and half maximum inhibitory concentrations of these targets. In addition, the enrichment greatly reduces the complexity of the proteome to be analyzed by quantitative MS. Complementary to these approaches, global proteomics profiling studying drug treatement-induced changes in protein expression levels and/or post-translational modification status have started to become possible mostly due to significant improvements in instrumentation. Particularly, when using multidimensional separations, a considerable proteome depth of up to 10 000 proteins can be achieved with current state-of-the-art mass spectrometers and bioinformatics tools. In summary, chemo- and pharmacoproteomics has already contributed significantly to the identification of novel drug targets and their mechanisms of action(s). Aided by further technological advancements, this interdisciplinary approach will likely be used more broadly in the future.     

Binding affinity models for Falcipain inhibition based on the Linear Interaction Energy method

The high rate of drug resistance as well as the complex biochemical process of the parasite reproduction cycle makes development of new drugs for malaria a very important but challenging task. Falcipain 2 (FL2) and Falcipain 3 (FL3) are the major cysteine protease enzymes that play a central role in providing essential amino acids for the parasite’s protein biosynthesis through the hemoglobin hydrolysis process. Selective inhibition of these enzymes is considered as a promising chemotherapeutic target. In the present investigation, the highly efficient linear interaction energy (LIE) method has been parameterized for binding affinity predictions and assessed with a set of 244 compounds for FL2 and FL3 inhibition. The results revealed that the van der Waals energy is very important for ligands binding to Falcipain proteins and that, overall, the electrostatic energy contribution is minor. The best models obtained for FL2 and FL3 give root mean square errors (RMSE) of 1.82 and 1.33 kcal/mol respectively, for the test set. In this study, we also investigate how the choice of initial protein-ligand confirmation (pose) impacts the overall quality of the LIE models. Moreover, the transferability of LIE parameters is further discussed.     

An ensemble of support vector machines for predicting virulent proteins

It is important to develop a reliable system for predicting bacterial virulent proteins for finding novel drug/vaccine and for understanding virulence mechanisms in pathogens.In this work we have proposed a bacterial virulent protein prediction method based on an ensemble of classifiers where the features are extracted directly from the amino acid sequence of a given protein. It is well known in the literature that the features extracted from the evolutionary information of a given protein are better than the features extracted from the amino acid sequence. Our method tries to fill the gap between the amino acid sequence based approaches and the evolutionary information based approaches.An extensive evaluation according to a blind testing protocol, where the parameters of the system are calculated using the training set and the system is validated in three different independent datasets, has demonstrated the validity of the proposed method.     

Structural model of the Plasmodium CDK, Pfmrk, a novel target for malaria therapeutics

Malaria, with 300-500 million clinical cases resulting in 1-3 million fatalities a year, is one of the most deadly tropical diseases. As current antimalarial therapeutics become increasingly ineffective due to parasitic resistance, there exists an urgent need to develop and pursue new therapeutic strategies. Recent genome sequencing and molecular cloning projects have identified several enzymes from Plasmodium (P.) falciparum that may represent novel drug targets, including a family of proteins that are homologous to the mammalian cyclin-dependent kinases (CDKs). CDKs are essential for the control of the mammalian cell cycle and, based on the conservation of the CDKs across species, the plasmodial CDKs are expected to play a crucial role in parasitic growth. Here we present a 3D structural model of Pfmrk, a putative human CDK activating kinase (CAK) homolog in P. falciparum. Notable features of the present structural model include: (1) parameterization of the Mg2+ hexacoordination system using ab initio quantum chemical calculations to accurately represent the ATP-kinase interaction; and (2) comparison between the docking scores and measured binding affinities for a series of oxindole-based Pfmrk inhibitors of known activity. Detailed analysis of inhibitor-Pfmrk binding interactions enabled us to identify specific residues (viz. Met66, Met75, Met91, Met94 and Phe143) within the Pfmrk binding pocket that may play an important role in inhibitor binding affinity and selectivity. The availability of this Pfmrk structural model, together with insights gained from analysis of ligand-receptor interactions, should promote the rational design of potent and selective Pfmrk inhibitors as antimalarial therapeutics.     

Applications of evolutionary SVM to prediction of membrane alpha-helices

This paper is in the area of membrane proteins. Membrane proteins make up about 75% of possible targets for novel drugs discovery. However, membrane proteins are one of the most understudied groups of proteins in biochemical research because of technical difficulties of attaining structural information about transmembrane regions or domains. Structural determination of TM regions is an important priority in pharmaceutical industry, as it paves the way for structure based drug design.This research presents a novel evolutionary support vector machine (SVM) based alpha-helix transmembrane region prediction algorithm to solve the membrane helices in amino acid sequences. The SVM-genetic algorithm (GA) methodology is based on the optimisation of sliding window size, evolutionary encoding selection and SVM parameter optimisation. In this research average hydrophobicity and propensity based on skew statistics are used to encode the one letter representation of amino acid sequences datasets.The computer simulation results demonstrate that the proposed SVM-GA methodology performs better than most conventional techniques producing an accuracy of 86.71% for cross-validation and 86.43% for jack-knife for randomly selected proteins containing single and multiple transmembrane regions. Furthermore, for the amino acid sequence 3LVG, the proposed SVM-GA produces better alpha-helix region identification than PRED-TMR2, MEMSATSVM/MEMSAT3 and PSIPRED V3.0.     

Identification of Mycobacterium tuberculosis enoyl-acyl carrier protein reductase inhibitors: A combined in-silico and in-vitro analysis

Mycobacterium tuberculosis (Mtb), had developed evolutionary changes in its genome to adapt for survival and thereby generated multi-drug resistant strains. However, novel drug targets that remained unchanged for their biochemical role has impressed the research community to target such proteins. The comprehensive analysis of multiple protein targets has influenced us to make a consensus structural rule exploited by pharmacophore and other allied techniques from a large repository of protein structures. In this pursuit, we made a retrospective analysis of pharmacophores mapped from the tuberculosis structural proteome and identified unique patterns that can be employed for the novel molecules design. The current work on NADH–dependent enoyl–acyl carrier protein reductase (InhA) has yielded top scored pharmacophore models which were searched over SPECS natural product database to prioritize the molecules that can be targeted against Mtb. With efforts on rigorous validation and expertise, we have identified such pharmacophoric patterns from natural compounds that can be used as initial hits. Subsequently, these hits were subjected to in-vitro antitubercular evaluation to ensure the inhibitory activity against the mycobacterium culture growth (MtbH37Rv). Furthermore, docking simulations were carried out to provide an insight on the possible modes of interaction between the experimentally explored compounds and InhA.     

Comparative proteomic analysis to discover potential therapeutic targets in human multiple myeloma

To clarify the molecular mechanisms that participate in the formation of multiple myeloma (MM) and to detect any tumor-related biomarkers, we performed proteomic analysis of cellular protein extracts from MM cells and normal plasma cells. Plasma cells from nine patients with newly diagnosed MM and nine healthy donors were purified by using anti-CD138 based immunomagnetic bead-positive selection. The protein profiles of purified MM and normal plasma cells were compared using 2-DE. We identified a total of 43 differentially expressed proteins, and confirmed with Western blotting six proteins. The altered proteins were analyzed using the software program Pathway Studio and the biological network can be accessed via (http://life-health.jnu.edu.cn/pathway/pathway.html). Further functional studies showed that annexin A1 knock down modestly induces lethality alone and potentiates the effects of dexamethasone on both dexamethasone-sensitive and dexamethasone-resistant MM cells. By correlating the proteomic data with these functional studies, the current results provide not only new insights into the pathogenesis of MM but also direct implications for the development of novel anti-MM therapeutic strategies and could lead to the discovery of potential therapeutic targets. Future molecular and functional studies would provide novel insights into the roles of these dysregulated proteins in the molecular etiology of MM.