Abstract

Alterations in apoptotic pathways have been implicated in many debilitating diseases such as cancer and neurodegenerative disorders.1,2 Thus, targeting cell death pathways has always been therapeutically attractive. In particular, as it is conceptually easier to kill than to sustain cells, abundant attention has been focused on anti-cancer therapies using pro-apoptotic agents such as conventional radiation and chemo-therapy. These treatments are generally believed to trigger activation of the mitochondria-mediated apoptotic pathways. However, these therapies lack molecular specificity. Over the last year or so, the discovery and structural characterization of an IAP-binding peptide motif have generated much enthusiasm in screening for an anti-cancer drug tailored for the caspase pathways.3 Apoptosis is primarily executed by activated caspases, a family of cysteine proteases with aspartate specificity in their substrates. Caspases are produced in cells as catalytically inactive zymogens and must be proteolytically processed to become active proteases during apoptosis. In normal surviving cells that have not received an apoptotic stimulus, most caspases remain inactive. Our method employs a grid-based algorithm and a knowledge-based potential derived from ligand-binding sites in the experimentally solved RNA–ligand complexes. The predictive power of LigandRNA favorably compares to five other publicly available methods. Here, in Biogenea we have for the first time discovered an in silico designed conserved motif-like tetrapeptide consisting of high free anad total binding energy mimetic pharmastructures for the potentiating apoptosis through IAP-binding as a possible future therapeutic compound using the BiogenetoligandorolTM and the LigandRNA.

Abstract

KIF20A (RAB6KIFL) belongs to the kinesin superfamilyof motor proteins, which play critical roles in the traffickingof molecules and organelles during the growth of pancreatic cancer.Immunotherapy using a previously identified epitope peptide forKIF20A is expected to improve clinical outcomes. A phase I clinicaltrial combining KIF20A-derived peptide with gemcitabine (GEM) was therefore conducted among patients with advancedpancreatic cancer who had received prior therapy such as chemotherapyand/or radiotherapy. Despite, huge importance of the field, no dedicated AVP resource is available. In the present Research Scientific Project , we have collected 1245 peptides with antiviral activity targeting important human viruses like influenza, HIV, HCV and SARS, etc. After removing redundant peptides, 1056 peptides were divided into 951 training and 105 validation data sets. We have exploited various peptides sequence features, i.e. motifs and alignment followed by amino acid composition and physicochemical properties during 5-fold cross validation using Support Vector Machine. Physiochemical properties-based model achieved maximum 85% accuracy and 0.70 Matthew’s Correlation Coefficient (MCC). Therefore, AVPpred—the first web server for predicting the highly effective AVPs would certainly be helpful to researchers working on peptide-based antiviral development. The web server is freely available at http://crdd.osdd.net/ servers/avpp. Here, in Biogenea we have discovered for the first time an in silico KIF20A-derived Peptide mimic designed poly-chemo-pharmacophoric macroscaffold as a future super-antagonist for the treatment of PatientsWith Advanced Pancreatic Cancer.

Abstract

Active immunotherapy is emerging as a potential therapeutic approach for prostate cancer. First phase I trials of an Ii-Key/HER-2/neu(776–790) hybrid peptide vaccine (AE37) with recombinant granulocyte macrophage colony-stimulating factor as adjuvant in patients with HER-2/neu+prostate cancer have shown positive resutls. The primary functionalities of ChemMine Tools fall into five major application areas: data visualization, structure comparisons, similarity searching, compound clustering and prediction of chemical properties. First, users can upload compound data sets to the online Compound Workbench. Numerous utilities are provided for compound viewing, structure drawing and format interconversion. Second, pairwise structural similarities among compounds can be quantified. Third, interfaces to ultra-fast structure similarity search algorithms are available to efficiently mine the chemical space in the public domain. These include fingerprint and embedding/ indexing algorithms. Fourth, the service includes a Clustering Toolbox that integrates cheminformatic algorithms with data mining utilities to enable systematic structure and activity based analyses of custom compound sets. Fifth, physicochemical property descriptors of custom compound sets can be calculated. These descriptors are important for assessing the bioactivity profile of compounds in silico and quantitative structure—activity relationship (QSAR) analyses. ChemMine Tools is available at: http://chemmine.ucr.ed. Here, in Biogenea we for the first time discovered a COMPUTER-assisted Identified Ii-Key/HER-2/ neu (776-790) Hybrid Peptide-mimotopic poly-mimic chemostructure with vaccine-like active pharmacophore sites as a novel inhibitor trans-activator in Prostate Cancer Patients using the ChemMine tools. An online service for analyzing and clustering small molecules.

Abstract

The p53 and nuclear factor κB (NF-κB) pathways play crucial roles in human cancer development. Simultaneous targeting of both pathways is an attractive therapeutic strategy against cancer. The use of pharmacologically active short peptide sequences has prooven to be a better option in cancer therapeutics than the full-lengthprotein. It has been previously report ed one such 44-mer peptide sequence of SMAR1 (TAT-SMAR1 wild type, P44) that retains the tumor suppressor activity of the full-length protein.P44 peptide could efficiently activate p53 by mediating its phosphorylation at serine15, resulting in the activation of p21 and in effect regulating cell cycle checkpoint. In vitrophosphorylation assays with point-mutated P44-derived pep-tides suggested that serine 347 of SMAR1 was indispensable forits activity and represented the substrate motif for the proteinkinase C family of proteins. In this Research Scientific Project we generated an antitumor multi-targeted hyper-molecule that bears a pyrrolo[3,4-clomifene-diamizido-c]pyrazole scaffold and functions as an enantiomeric P44 peptide mimeto inhibitor against both the p53-MDM2 interaction and the NF-κB activation. This pharmacophjoric scaffold may be a first-in-class dual targeted enantiomeric inhibitor with dual efficacy for cancer therapy with potential synergistic effect in vitro and in vivo. Docking and molecular dynamics simulation studies further provided insights into the nature of stereoselectivity. Here, we have for the first time in silico discovered novel chemo-hyperstructures as a novel drug discovery incorporated strategy utilizing a mechanistic investigation of low mass stochastic genetic algorithms for the generation of an enantiomeric antitumor agent consistinc of three conserved pharmacophores dual targeting the p53 and NF-κB pathways for the activation of the p53 tumor suppressor pathway by an engineered TAT-SMAR1 wild type, P44 cyclotidomimic multicovalent pharmaco-ligand.

Abstract

A conditionally replicative adenovirus is a novel anticancer agent designed to replicate selectively in tumor cells. However, a leak of the virus into systemic circulation from the tumors often causes ectopic infection of various organs. Therefore, suppression of naive viral tropism and addition of tumor-targeting potential are necessary to secure patient safety and increase the therapeutic effect of an oncolytic adenovirus in the clinical setting. It has also recently been developed a direct selection method of targeted vector from a random peptide library displayed on an adenoviral fiber knob to overcome the limitation that many cell type-specific ligands for targeted adenovirus vectors are not known. In previous studies it has also been further examined whether the addition of a tumor-targeting ligand to a replication-competent adenovirus ablated for naive tropism enhances its therapeutic index. Structure-based drug design is an iterative process, following cycles of structural biology, computer-aided design, synthetic chemistry and bioassay. In favorable circumstances, this process can lead to the structures of hundreds of protein-ligand crystal structures. In addition, molecular dynamics simulations are increasingly being used to further explore the conformational landscape of these complexes. Currently, methods capable of the analysis of ensembles of crystal structures and MD trajectories are limited and usually rely upon least squares superposition of coordinates. Novel methodologies are described for the analysis of multiple short linear motif like peptide structures of a protein-drug active binding conserved site. Statistical approaches that rely upon residue equivalence, but not superposition, are developed as chemogenomic informatic tasks can be performed includinig the identification of hinge regions, allosteric conformational changes and transient binding sites. Here, we have for the first time discovered an in silico rational designed adenovirus library displaying random peptide-mimic pharmacophore comprising Oncolytic virus therapeutic promising properties for pancreatic cancer using a KNIME-based BiogenetoligandorolTM directed polyphony superposition independent method for ensemble-based drug discoveries.

Abstract

Glycoprotein-96, a non-polymorphic heat-shock protein, associates with intracellular peptides. Autologous tumor-derived heat shock protein-peptide complex 96 (HSPPC-96) can elicit potent tumor-specific T cell responses and protective immunity in animal models. Chemokines were described originally in the context of providing migrational cues for leukocytes. They are now known to have broader activities, including those that favor tumor growth. Treatment with autologous tumor-derived HSPPC-96 was feasible and safe at all doses tested. Observed immunological effects and antitumor activity were modest, precluding selection of a biologically active dose. Coevolution between proteins is crucial for understanding protein-protein interaction. Simultaneous changes allow a protein complex to maintain its overall structural-functional integrity. In this Research Scientific Project, we combined statistical coupling analysis (SCA) and molecular dynamics simulations on thecomplex-96 (HSPPC-96) protein complex to evaluate coevolution between conserved binding protein domain regions. We reconstructed an inter-protein residue coevolution network, consisting of 37 residues and 37complex-96 (HSPPC-96) binding domains conserved peptide derived residues and its fitness scoring reverse ligand docking interactions. It shows that most of the coevolved residue pairs are spatially proximal. When the mutations happened, the stable local structures were broken up and thus the protein interaction was decreased or inhibited, with a following increased risk of melanoma. The identification of inter-protein coevolved residues in thecomplex-96 (HSPPC-96) complex can be helpful for designing protein drug target and in silico discovery of engineering novel nanomolecule experiments. In this scientific study we have in silico discovered a Unique Small Molecule Modulator of CXCR4 tumor-derived heat-shock protein peptide complex-96 (HSPPC-96) by identifying Hits of a High-Throughput Screen Identify the Hydrophobic Pocket of Autotaxin/Lysophospholipase D as an Inhibitory Surface Molecular dynamic simulation and statistical coupling analysis via a KNIME-based BiogenetoligandorolTM generated of a functional coevolution network of oncogenic mutations in the (HSPPC-96) hyper-interactive multicovalent annotated pharmacophore construct complexes.

Abstract

Glutamate is the primary excitatory neurotransmitter in the mammalian central nervous system (CNS) and activates metabotropic glutamate receptors (mGluRs), which are coupled to downstream effector systems through guanine nucleotide binding proteins (G proteins). The mGluRs provide a mechanism by which glutamate can modulate or fine-tune activity at the same synapses on which it elicits fast synaptic responses. Because of the wide diversity, heterogeneous distribution, and diverse physiological roles of mGluR subtypes, the opportunity exists for developing therapeutic agents that selectively interact with mGluRs involved in only one or a limited number of CNS functions. Such drugs could have a dramatic impact on the development of novel treatment strategies for a variety of psychiatric disorders including depression, anxiety disorders, schizophrenia and Parkinson’s disease. The mGluR5 receptor subtype is a closely associated signaling partner of the ionotropic NMDA receptor (NMDAR) and may play a significant role in setting the tone of NMDAR function in the forebrain regions containing neuronal circuits important for cognitive behavior and for reporting on the efficacy of antipsychotic agents. The conantokins are structurally unique. It has been established that the conantokins have N-methyl-D-aspartate (NMDA) antagonist activity, and consequently target the NMDA receptor. In this study we performed a systematic analysis, with the classic kinetic models of enzyme-substrate-inhibitor interactions with different number of substrates, different reaction mechanisms, and different types or mechanisms of inhibition by modeling this situation through Monte Carlo error propagation, in which a distribution of free energy estimates is constructed by repeatedly evaluating the free energy after perturbing the microstate energies according to probability density functions describing their inherent imprecision resulting in the generation of a multi-conserved pharmaco-scaffold consisting of five key active pharmacophores peptide mimicking to the NMDA and Glutamate Receptor Subtype 5 conantokin activated pathway. Here, finally we provided for the first time a conditional probability solution computer-aided molecular strategy for the in silico identification of the ionotropic NMDA receptor and Metabotropic Glutamate Receptor Subtype 5 conantokin X6GQDDSX1X1X1DSQX2VMX2HGQRRERR peptidomimetic formula as an advanced binding site promising future drug potentiator.

Abstract

Cancer is still a major cause of death in the world at the beginning of the- 21st century and remains a major focus for ongoing research and development. In recent years a promising approach to the therapeutic intervention of cancer has focused on antiangiogenesis therapies. This approach to intervening in cancer progression takes advantage of the idea that inhibiting or otherwise limiting the blood supply to tumors will deplete the tumor of oxygen and nutrients and will cause arrest of tumor cell growth and proliferation. This approach has been found to be effective and there are presently over 20 anti-angiogenic drugs undergoing various stages of evaluation in phase I, II or III clinical trials and numerous others in preclinical development. Vascular endothelial growth factor receptor 3 (VEGFR-3) supports tumor lymph angiogenesis. It was originally identified as a lymphangiogenic factor expressed in lymphatic endothelial cells. VEGFR-3 was detected in advanced human malignancies and correlated with poor prognosis. Previous studies show that activation of the VEGF-C/VEGFR-3 axis promotes cancer metastasis and is associated with clinical progression in patients with lung cancer, indicating that VEGFR-3 is a potential target for cancer therapy. By using a fast path planning approach, we then rapidly generated large amounts of flexible peptide conformations, allowing backbone and side chain flexibility. A newly introduced binding energy funnel ‘steepness score’ was applied for the evaluation of the protein–peptide-multi-ligand complexes binding affinity. KNIME-based BiogenetoligandorolTM – Pepcrawler simulations predicted high binding affinity for native protein–peptide-hyper-ligand complexes benchmark and low affinity for low-energy decoy complexes. As a result we managed finally to introduce an algorithm for high-resolution refinement and binding affinity estimation of novel designed inhibitors consisting of CGQMCTVWCSSGC conserved peptide substitution mimetic linked pharmaco-structures with potential antagonizing VEGFR-3-mediated oncogenic effects.

Abstract

Mitochondria-derived oxidative stress is believed to be centrally involved in cardiac ischemia-reperfusion (I/R) injury, although currently no therapies exist that specifically target mitochondrial reactive oxygen species (ROS) production. The potential effects of the structural analogues of apelin-12, an adipocyte-derived peptide, on mitochondrial ROS generation, cardiomyocyte apoptosis, metabolic and functional recovery to myocardial I/R injury have succesfully previously been reported. Treatment of cardiomyocytes with AI and AII significantly decreased cell apoptosis in a dose-dependent manner. In the chemical informatic field, ALOHA is demonstrated to discriminate between members of the same chemical series with strong statistical significance, suggesting that ALOHA can be used effectively to select compound candidates for synthesis and progression at the lead optimization stage of drug discovery. Here, in Biogenea Pharmaceuticals Ltd we discovered for the first time the GENEA-Sapemitor-45345. An In silico Structure-based designed of an apelin-analogue pharmacophoric agent for the mitochondrial ROS inhibition and cardiometabolic protection in myocardial ischemia-reperfusion injury using the BiogenetoligandorolTM and the ALOHA: a novel probability fusion approach for scoring multi-parameter drug-likeness during the lead optimization stage of drug discovery.

Abstract

The prognosis of patients with advanced biliary tract cancer (BTC) is extremely poor and thereare only a few standard treatments. We conducted a phase I trial to investigate the safety, immune response,and antitumor effect of vaccination with four peptides derived from cancer-testis antigens, with a focus ontheir fluctuations during long-term vaccination until the disease had progressed. A unified statistical model to support local sequence order independent similarity searching for ligand-binding sites and its application to genome-based drug discovery. Bioinformatics, 25, i305–i312.]. These algorithms have been extensively benchmarked and shown to outperform most existing algorithms. Moreover, several predictions resulting from SMAP-WS have been validated experimentally. Thus far SMAP-WS has been applied to predict drug side effects, and to repurpose existing drugs for new indications. SMAP-WS provides both a user-friendly web interface and programming API for scientists to address a wide range of compute intense questions in biology and drug discovery. Here, we have for the first time discovered a multi-epitope mimic poly-pharmacophore to Multiple Peptides Derived from Cancer-Testis Antigens for the maintance of a Specific T-cell Response in Long-term Vaccinated patients with Advanced Biliary Tract Cancer using the BiogenetoligandorolTM based SMAP-WS chemical informatic parallel web service for structural proteome-wide ligand-binding site comparison.