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Kaludov N.,Gradient Biomodeling, Llc | Martinov M.N.,Gradient Biomodeling, Llc
Malaria Journal | Year: 2011

Background: Developing resistance towards existing anti-malarial therapies emphasize the urgent need for new therapeutic options. Additionally, many malaria drugs in use today have high toxicity and low therapeutic indices. Gradient Biomodeling, LLC has developed a quantum-model search technology that uses quantum similarity and does not depend explicitly on chemical structure, as molecules are rigorously described in fundamental quantum attributes related to individual pharmacological properties. Therapeutic activity, as well as toxicity and other essential properties can be analysed and optimized simultaneously, independently of one another. Such methodology is suitable for a search of novel, non-toxic, active anti-malarial compounds. Methods. A set of innovative algorithms is used for the fast calculation and interpretation of electron-density attributes of molecular structures at the quantum level for rapid discovery of prospective pharmaceuticals. Potency and efficacy, as well as additional physicochemical, metabolic, pharmacokinetic, safety, permeability and other properties were characterized by the procedure. Once quantum models are developed and experimentally validated, the methodology provides a straightforward implementation for lead discovery, compound optimizzation and de novo molecular design. Results: Starting with a diverse training set of 26 well-known anti-malarial agents combined with 1730 moderately active and inactive molecules, novel compounds that have strong anti-malarial activity, low cytotoxicity and structural dissimilarity from the training set were discovered and experimentally validated. Twelve compounds were identified in silico and tested in vitro; eight of them showed anti-malarial activity (IC50 10 M), with six being very effective (IC50 1 M), and four exhibiting low nanomolar potency. The most active compounds were also tested for mammalian cytotoxicity and found to be non-toxic, with a therapeutic index of more than 6,900 for the most active compound. Conclusions: Gradient's metric modelling approach and electron-density molecular representations can be powerful tools in the discovery and design of novel anti-malarial compounds. Since the quantum models are agnostic of the particular biological target, the technology can account for different mechanisms of action and be used for de novo design of small molecules with activity against not only the asexual phase of the malaria parasite, but also against the liver stage of the parasite development, which may lead to true causal prophylaxis. © 2011 Sullivan et al; licensee BioMed Central Ltd.


Mott B.T.,U.S. National Institutes of Health | Kaludov N.,Gradient Biomodeling, Llc | Martinov M.N.,Gradient Biomodeling, Llc
PLoS ONE | Year: 2015

Without quantum theory any understanding of molecular interactions is incomplete. In principal, chemistry, and even biology, can be fully derived from non-relativistic quantum mechanics. In practice, conventional quantum chemical calculations are computationally too intensive and time consuming to be useful for drug discovery on more than a limited basis. A previously described, original, quantum-based computational process for drug discovery and design bridges this gap between theory and practice, and allows the application of quantum methods to large-scale in silico identification of active compounds. Here, we show the results of this quantum-similarity approach applied to the discovery of novel liver-stage antimalarials. Testing of only five of the model-predicted compounds in vitro and in vivo hepatic stage drug inhibition assays with P. berghei identified four novel chemical structures representing three separate quantum classes of liver-stage antimalarials. All four compounds inhibited liver-stage Plasmodium as a single oral dose in the quantitative PCR mouse liver-stage sporozoites-challenge model. One of the newly identified compounds, cethromycin [ABT-773], a macrolide-quinoline hybrid, is a drug with an extensive (over 5,000 people) safety profile warranting its exploitation as a new weapon for the current effort of malaria eradication. The results of our molecular modeling exceed current state-of-theart computational methods. Drug discovery through quantum similarity is data-driven, agnostic to any particular target or disease process that can evaluate multiple phenotypic, target-specific, or co-crystal structural data. This allows the incorporation of additional pharmacological requirements, as well as rapid exploration of novel chemical spaces for therapeutic applications.


Williamson T.P.,University of Wisconsin - Madison | Amirahmadi S.,University of Wisconsin - Madison | Joshi G.,University of Wisconsin - Madison | Kaludov N.K.,Gradient Biomodeling, Llc | And 3 more authors.
Chemical Biology and Drug Design | Year: 2012

Nuclear factor erythroid 2-related factor 2 (Nrf2) is the master transcription factor of the antioxidant response element pathway, coordinating the induction of detoxifying and antioxidant enzymes. Nrf2 is normally sequestered in the cytoplasm by Kelch-like ECH-associating protein 1 (Keap1). To identify novel small molecules that will disturb Nrf2-Keap1 binding and promote activation of the Nrf2- antioxidant response element pathway, we generated a quantum model based on the structures of known Nrf2- antioxidant response element activators. We used the quantum model to perform in silico screening on over 18million commercially available chemicals to identify the structures predicted to activate the Nrf2- antioxidant response element pathway based on the quantum model. The top hits were tested in vitro, and half of the predicted hits activated the Nrf2-antioxidant response element pathway significantly in primary cell culture. In addition, we identified a new family of Nrf2-antioxidant response element-activating structures that all have comparable activity to tBHQ and protect against oxidative stress and dopaminergic toxins in vitro. The improved ability to identify potent activators of Nrf2 through the combination of in silico and in vitro screening described here improves the speed and cost associated with screening Nrf2-antioxidant response element -activating compounds for drug development. We generated a quantum model based on the structures of known Nrf2-ARE activators. The top hits were tested in vitro and half of the predicted hits activated the Nrf2-ARE pathway significantly in primary cell culture. The improved ability to identify potent activators of Nrf2 through the combination of in silico and in vitro screening described here improves the speed and cost associated with screening Nrf2-ARE activating compounds for drug development. © 2012 John Wiley & Sons A/S.


Grant
Agency: Department of Health and Human Services | Branch: National Institutes of Health | Program: SBIR | Phase: Phase I | Award Amount: 224.89K | Year: 2016

Project Summary Abstract Neurofibrillary lesions composed of tau protein aggregates are a defining pathology of Alzheimerandapos s disease AD Because lesion appearance correlates with neurodegeneration and cognitive decline diverse approaches for inhibiting their formation are under investigation as potential therapies against AD progression An attractive target is the tau aggregation reaction itself which is closely associated with lesion formation but not normal tau function Many tau aggregation inhibitors have been reported on the basis of in vitro screening demonstrating the feasibility of the approach but only recently have their potency driving features molecular targets in the tau aggregation pathway and activity in biological models been clarified The results are promising but point toward liabilities of existing inhibitors with respect to pharmacokinetics and or inhibitory mechanism Unlocking the utility of the aggregation inhibition strategy will require the identification of new chemotypes with greater drug like character than the existing generation of inhibitors The first objective of this Phase proposal is to meet this need using the computational platform developed by Gradient Biomodeling LLC Gradient The platform applies quantum methods to large scale in silico discovery facilitating the identification of novel chemotypes that retain the quantum signature of active compounds Its second objective is to evaluate the activity of selected compounds in established tau aggregation assays At the conclusion of this project a validated computation model capable of supporting for lead optimization and candidate compounds appropriate for in vivo testing will be in place for Phase SBIR study Project Narrative Alzheimer s disease is the most prevalent dementing illness of the elderly It is defined in part by the appearance of cellular lesions composed of aggregates of the microtubule associated protein tau This project seeks to identify novel tau aggregation inhibitors as potentially disease modifying therapeutics for AD


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 225.00K | Year: 2014

DESCRIPTION (provided by applicant): Human African trypanosomiasis (HAT) is an infectious disease with a large global health burden occurring primarily in Central and Eastern Africa. HAT is 100% fatal if untreated and the current drug therapies suffer frompoor safety profiles, difficult treatment regimens, limited effectiveness, and high costs. Furthermore, drugs that cross the blood brain barrier (BBB) are notoriously difficult to develop and have a lower probability of reaching the market place. Here, wepropose to apply a quantum-similarity approach to discover novel T. Brucei inhibitors. The approach allows for simultaneous interrogation of multiple targets and pathways, and for incorporation of various pharmacological requirements early in the discovery process, thus increasing the chances of finding novel therapeutics with great selectivity, potency and pharmacokinetic properties. Instead of screening millions of compounds for novel modulators of the target of interest, our focused testing of 10-2


Gradient Biomodeling, Llc | Entity website

Gradient Biomodeling, LLC has developed a versatile computational platform for modeling of biomolecular interactions and pathways.Applications of our technology include drug discovery and design, repositioning of therapeutic compounds, small-molecule diagnostics, chemical genetics, biomarker identification, etc


Gradient Biomodeling, Llc | Entity website

January 7, 2013Development of Small Molecules for Use in Diagnostic Devicesto Measure Plasma Renin ActivityThe project is funded by the EU Fund for Regional Development and being executed in Bulgaria


Gradient Biomodeling, Llc | Entity website

A Quantum Physics Search for Liver-Stage AntimalarialsThe project is a collaboration with Dr. David Sullivan of the Johns Hopkins Bloomberg School of Public Health andsponsoredby the Grand Challenges in Global Health initiative of the Gates Foundation


Gradient Biomodeling, Llc | Entity website

Formation ofNeuRho Farmaceutica, Inc.NeuRho Farmaceutica, Inc ...


Gradient Biomodeling, Llc | Entity website

May 2, 2014A Quantum Similarity Approach for the Discovery of Anti-Trypanosome Drug LeadsThe project is supported by a Phase I SBIR grant award from the National Institute of Allergies and Infectious Diseases (1R43AI114078-01). The experimental work will be subcontracted to the laboratory of Dr ...

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