Abstract

In silico Drug discovery and development of novel multi-target molecules is an interdisciplinary, expensive and time-consuming procedure. Computer aided drug discovery advancements during the past decades have improved the way of pharmaceutical research design of novel bioactive huper-structured drug-gable molecules. Computer aided drug design helps in reducing the cost and time for drug discovery process which otherwise takes many years. Virtual screening and docking studies helped to obtain ligand molecules that can inhibit the important Proteins involved in the pathogenesis of Ebola virus. It is noticed that the chemical compounds might be the promising candidates drug-like small targeted compounds for further pre-clinical and clinical investigation, and that the NP and the octapeptides ATLQAIAS and ATLQAENV, as well as AVLQSGFR, might be pre-clinically translated and antisense converted to effective direct inhibitors against the Ebola Virus Fusion Conserved Proteoma. Meanwhile, we in silico generated conserved octapeptides mimotopic pharmaco-ligands based on the “distorted key energy binding fitness scoring” theory to in-silico anti-sense peptides by in-silico translate them and transform them into a scaffold energy hopping structure in order to design potent selective super-agonsist anti-peptide poly-mimic new superstructure which is explicitly elucidated. We also combined all existing methods for computational huper-structured drug design methodologies to induce catalysis of Ebola Virus EBOV NP and EBO16 peptides by inducing energetically targeted favorable hydrogen bonds, van der Waals, and electrostatic interactions to a high-energy reaction conserved motif-based transition state(s) and/or intermediate(s) of Ebola virus. In this present Research Scientific Project , for first time we developed a computational method for designing motif-like conserved residues and ligand binding virus proteins with two properties characteristic of naturally occurring binding sites in addition to specific energetically favorable interactions with our newly designed hyper-multi-target ligand. Here, in Biogenea we have in silico discovered a virion-attached pharmacophore cross-reacting synthetic EQHHRRTDN peptide mimetic ligand comprising potential therapeutic properties against Ebola virus using an in silico drug design structure peptide-sequence-based combinatorial analysis by a multi-objective cluster of algorithms.

Abstract

We have developed a novel class of multivalent tubulin mimotopic VDAC-1 peptide like chemical inhibitor assembly by nano-chemical HA14-1 modifying scaffold, which is a Bcl-2 inhibitor discovered in previous scientific projects. Cell-penetrating VDAC1-based peptides were designed and screened to identify the most stable, short and apoptosis-inducing peptides toward CLL-derived lymphocytes revealing the potential of VDAC1-based peptides as an innovative and effective anti-CLL therapy. Multivalency is a design principle that can convert inhibitors with low affinity to ones with high avidity and/or biological “activity” gauged by some relevant parameter: (for example, values of IC50 the concentration of free ligand, often approximated as the total ligand, that reduces the experimental signal to 50% of its initial value). In addition, multivalent approaches can be effective in generating high-avidity ligands for proteins with multiple binding sites from low-affinity ligands. Multivalent ligands (primarily polyvalent ones) are especially well suited for inhibiting or augmenting interactions at biological surfaces (e. g., surfaces of bacteria, viruses, cells they can prevent adhesion of these surfaces to other surfaces by grafting polymers to the surfaces of viruses to prevent adhesion to cells). Computational docking, colchicine-tubulin competitive binding, and tubulin polymerization studies demonstrated that these compounds bind at the colchicine-binding site on tubulin and inhibit the formation of microtubules. The mode of action of the VDAC-1 peptides involves dysfunction of mitochondria energy production and apoptosis induction. In this study, we confine attention to the so called ligand-based target prediction machine learning peptide mimetic drug discovery approaches, commonly referred to as drug target fishing. These results demonstrate that the VDAC1 treating CLL peptides may assist target-fishing approaches that are currently ubiquitous in cheminformatics and can be essentially viewed as single-label peptidomimetic drug discovery schemes. Here, we have for the first time in silico discovered a Novel Class of VDAC1-peptide mimetic Tubulin targeted HA14-1-based multivalent chemical Inhibitor with Promising Anticancer Activities as novel pro-apoptotic annotated agent for B-cell chronic lymphocytic leukemia.

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

The effectivenes of cancer vaccines in inducing CD8+Tcell responses remains a challenge, resulting in a need for testing more potent adjuvants. In previous clinical trials it has been determined the safetyand immunogenicity of vaccination against melanoma-related antigens employing MART-1,gp100, and tysosinase paptides combined with the TLR-9 agonist PF-3512676 and local GM-CSFin-oil emulsion.Using continuous monitoring of safety and a two-stage design for immunological efficacy, More than 20 immune-response evaluable patients were targetted. Vaccinations were given subcutaneously ondays 1 and 15 per cycle (1 cycle=28 days) for up to 13 cycles. Structure-based virtual screening of molecular compound libraries is a potentially powerful and inexpensive method for the discovery of novel lead compounds for drug development. That said, virtual screening is heavily dependent on detailed understanding of the tertiary or quaternary structure of the protein target of interest, including knowledge of the relevant binding pocket. Here, in Biogenea we have for the first time discovered a Safe and immunogenic pharmacophore activator mimic physicochemical properties of the MART-1 (26-35,27L), gp100 (209-217, 210M), and tyrosinase (368-376, 370D) inadjuvantwith PF-3512676 and GM-CSF as a future anti-cancer agent in metastatic melanoma conditions introducing a novel multi-parametric algorithm drug discovery approach using a Ligand-Based Virtual Screening approach through a Support Vector Machine and Information Fusion attempt.

Abstract

Animals and higher plants express endogenous peptide antibiotics called defensins. These small cysteine-rich peptides are active against bacteria, fungi and viruses. Plectasin—the first defensin has been isolated from a fungus, the saprophytic ascomycetePseudoplectania nigrella. Polypeptides having antimicrobial activity may be capable of reducing the number of living cells of Bacillus subtilis (ATCC 6633). Plectasin has primary, secondary and tertiary structures that closely resemble those of defensins found in spiders, scorpions, dragonflies and mussels. Recombinant plectasin was produced at a very high, and commercially viable, yield and purity. In vitro, the recombinant peptide was especially active againstStreptococcus pneumoniae, including strains resistant to conventional antibiotics. Plectasin showed extremely low toxicity in mice, and cured them of experimental peritonitis and pneumonia caused by S. pneumoniae as efficaciously as vancomycin and penicillin. These findings identify fungi as a novel source of antimicrobial defensins, and show the therapeutic potential of plectasin. They also suggest that the defensins of insects, molluscs and fungi arose from a common ancestral gene. The Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational structural biology to estimate the electrostatic energetic component of the assembly of molecular biological systems. In the last decades, the amount of data concerning proteins and other biological macromolecules has remarkably increased. To fruitfully exploit these data, a huge computational power is needed as well as software tools capable of exploiting it. It is therefore necessary to move towards high performance computing and to develop parallel implementations of already existing and of novel algorithms. In this Research and Scientific Project, we propose the implementation of a full Poisson-Boltzmann solver based on a finite-difference scheme using different and combined parallel schemes and in particular a mixed MPI-CUDA implementation. Here, we have for the first time discovered a A Rational predicted pDRS-18-plectasin peptide-mimetic pharmacophore comprising antibiotic properties with therapeutic potential from a saprophytic fungus using BiogenetoligandorolTM drug discovery process combined MPI-CUDA parallel solution of linear and nonlinear Poisson-Boltzmann equation.

Abstract

Immune response, and clinicalresponse in melanoma patients after combined therapy with temozolomide and the telomerase peptide vaccine GV1001 in previous GV1001 trials showed immune responses in approximately 60% of lung orpancreatic cancer patients. Previous Experimental Studies Twenty-five subjects with advanced stage IV melanoma (M1B or M1C) received concomitant temozolomide and GV1001. Temozolomide was administered 200 mg/m2 orally for 5 daysevery fourth week, and GV1001 as eight injections over 11 weeks. Immune response was evaluated bydelayed type hypersensitivity, T-cell proliferation, and cytokine assays. The immunologic responders continued monthly vaccination. Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile alignments. Proc. Natl Acad. Sci. USA, 105, 5441–5446]. 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, in Biogenea we have for the first generated an in silico Telomerase Peptide mimotopic poly-chemo structure simulator eith promising clinical results in Stage IV Melanoma Patients when combined with Temozolamide using the BiogenetoligandorolTM and the SMAP-WS. A parallel web service for structural proteome-wide ligand-binding site comparison.

Abstract

Exploring hyper drug-target interactions using restricted Boltzmann machines. Computational development of rubromycin-based lead compounds for HIV-1 reverse transcriptase inhibition. Considerable success has been achieved in the treatment of HIV-1 infection, and more than two dozen antiretroviral drugs are available targeting several distinct steps in the viral replication cycle. However, resistance to these compounds emerges readily, even in the context of combination therapy. Drug toxicity, adverse drug-drug interactions, and accompanying poor patient adherence can also lead to treatment failure. These considerations make continued development of novel antiretroviral therapeutics necessary. Current approaches for designing chemical recored ligand binding proteins for medical and biotechnological uses rely upon raising antibodies against a target antigen in immunized animals and/or performing laboratory directed evolution of proteins with an existing low affinity for the desired ligand, both of which offer incomplete control over molecular details. Computational design has the potential to provide a general, complementary low mass algorithmic approach for small molecule recognition in which designed and predicted features and selectivity can be rationally in sioico programmed. Structural and biophysical characterization of previously designed ligand binding proteins has revealed numerous discrepancies with the design models, however, and it was concluded that protein-ligand interaction design is an unsolved problem. The development of robust computational methods for the design of small molecule-binding proteins with high affinity and selectivity would have wide-ranging applicationS. The goal of existing methods for computational enzyme design is to promote catalysis by creating energetically favorable hydrogen bonding, van der Waals, and electrostatic interactions to a high-energy reaction transition state(s) and/or intermediate(s). Although these interactions are also important for stabilizing the bound ground-state conformations of protein-motif conserved petide mimetic pharmacophore consisting of linked small molecule complexes as the sole determinant of small molecule binding. Here, in this research drug discovery approach we in silico discovered poly-target potential antagonists to HIV-II viral replication cycle associated enzymes using a Pocket-Based Drug Design Methodology.

Keywords

Cartigenea-Cardiogenea, Neurogenea-Cellgenea, Cordigenea-HyperoligandorolTM,

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.