Dragos Horvath

Bio: Dragos Horvath is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Pharmacophore & Quantitative structure–activity relationship. The author has an hindex of 24, co-authored 59 publications receiving 1372 citations. Previous affiliations of Dragos Horvath include University of Strasbourg & Pasteur Institute.

Predicting ADME properties and side effects: the BioPrint approach.

Abstract: Computational methods are increasingly used to streamline and enhance the lead discovery and optimization process. However, accurate prediction of absorption, distribution, metabolism and excretion (ADME) and adverse drug reactions (ADR) is often difficult, due to the complexity of underlying physiological mechanisms. Modeling approaches have been hampered by the lack of large, robust and standardized training datasets. In an extensive effort to build such a dataset, the BioPrint database was constructed by systematic profiling of nearly all drugs available on the market, as well as numerous reference compounds. The database is composed of several large datasets: compound structures and molecular descriptors, in vitro ADME and pharmacology profiles, and complementary clinical data including therapeutic use information, pharmacokinetics profiles and ADR profiles. These data have allowed the development of computational tools designed to integrate a program of computational chemistry into library design and lead development. Models based on chemical structure are strengthened by in vitro results that can be used as additional compound descriptors to predict complex in vivo endpoints. The BioPrint pharmacoinformatics platform represents a systematic effort to accelerate the process of drug discovery, improve quantitative structure-activity relationships and develop in vitro/in vivo associations. In this review, we will discuss the importance of training set size and diversity in model development, the implementation of linear and neighborhood modeling approaches, and the use of in silico methods to predict potential clinical liabilities.

A Virtual Screening Approach Applied to the Search for Trypanothione Reductase Inhibitors

Abstract: A prediction algorithm of the binding affinity of ligands to trypanothione reductase (TR), the enzyme replacing glutathione reductase in the metabolism of trypanosomatidae, has been used for the “virtual screening” of a data base of 2500 molecular sketches and has detected several structures of putative TR ligands. Most of these compounds turned out to be micromolar inhibitors of TR, as predicted by the algorithm. While their inhibitory potencies are lower than those of previously reported compounds, one of the molecules reported here could represent the lead toward a structurally different class of TR inhibitors. The fully automated prediction algorithm converts the 2D molecular sketches into 3D ligand structures, explores the conformational space of the latter, and performs a grid-based, rigid-body docking of the resulting family of ligand conformations into the TR site, calculating enthalpic and entropic binding indexes and predicting the binding affinity. The docking model has also been used to obtain...

Neighborhood Behavior of in Silico Structural Spaces with Respect to in Vitro Activity Spaces−A Novel Understanding of the Molecular Similarity Principle in the Context of Multiple Receptor Binding Profiles

Abstract: As a consequence of recent advances in the field of High Throughput Screening, the systematic testing (“in vitro profiling”) of compounds against a panel of targets covering different therapeutic areas is nowadays used to generate relevant information with respect to the in vivo behavior of drug candidates. However, the development of chemoinformatics tools required for the exploitation of such data is yet in an incipient phase. In this paper, a formalism for the analysis of activity profile vectors (describing the experimental responses of compounds in each of the considered activity tests) is introduced and applied at the study of Neighborhood Behavior (NB; the hypothesis that structurally similar compounds display similar biological properties) of molecular similarity metrics. The experimental activity profiles define an Activity Space in which more than 500 drugs and reference compounds are positioned, their coordinates being inhibitory propensities in the included tests and unambiguously characterizi...

Pin1: a therapeutic target in Alzheimer neurodegeneration.

Abstract: In Alzheimer's disease, the peptidyl prolyl cis/trans isomerase Pin1 binds to phospho-Thr231 on Tau proteins and, hence, is found within degenerating neurons, where it is associated to the large amounts of abnormally phosphorylated Tau proteins. Conversely, Pin1 may restore the tubulin polymerization function of these hyperphosphorylated Tau. In the present work, we investigated, both at the cellular and molecular levels, the role of Pin1 in Alzheimer's disease through the study of its interactions with phosphorylated Tau proteins. We also showed that in neuronal cells, Pin1 upregulates the expression of cyclin D1. This, in turn, could facilitate the transition from quiescence to the G1 phase (re-entry in cell cycle) in a neuron and, subsequently, neuronal dedifferentiation and apoptosis. The involvement of Pin1 in the G0/G1 transition in neurons points to its function as a good target for the development of new therapeutic strategies in neurodegenerative disorders.

From hit to lead. Combining two complementary methods for focused library design. Application to mu opiate ligands.

Abstract: Compound 1 obtained by random screening and displaying a micromolar activity on the mu opiate receptor was chosen as a starting point for optimization. Two complementary concepts of similarity were used for the design of analogues and compared. These are based, respectively, on a computer-aided comparison of pharmacophoric patterns and on topological similarity. The structure-activity relationships are discussed in light of both similarity concepts. Compound 40, an N-methyl-3-(4-oxo-1-phenyl-1,3,8-triazaspiro[4.5]decyl)acetamide derivative, designed by combining the structure-activity relationships enlightened by each method, has a subnanomolar affinity for mu (h) receptor (IC(50) = 0.9 nM). It is a promising lead, allowing the design of a new series of analogues substituted at the N-3 of the spirocycle moiety.

Docking and scoring in virtual screening for drug discovery: methods and applications.

Abstract: Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches

Metaheuristics: From Design to Implementation

Abstract: A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

The combinatorial synthesis of bicyclic privileged structures or privileged substructures

Abstract: Privileged substructures are of potentially great importance in medicinal chemistry. These scaffolds are characterized by their ability to promiscuously bind to a multitude of receptors through a variety of favorable characteristics. This may include presentation of their substituents in a spatially defined manner and perhaps also the ability to directly bind to the receptor itself, as well as exhibiting promising characteristics to aid bioavailability of the overall molecule. It is believed that some privileged substructures achieve this through the mimicry of common protein surface elements that are responsible for binding, such as β- and gamma;-turns. As a result, these structures represent a promising means by which new lead compounds may be identified.

The influence of drug-like concepts on decision-making in medicinal chemistry

Abstract: The application of guidelines linked to the concept of drug-likeness, such as the 'rule of five', has gained wide acceptance as an approach to reduce attrition in drug discovery and development. However, despite this acceptance, analysis of recent trends reveals that the physical properties of molecules that are currently being synthesized in leading drug discovery companies differ significantly from those of recently discovered oral drugs and compounds in clinical development. The consequences of the marked increase in lipophilicity--the most important drug-like physical property--include a greater likelihood of lack of selectivity and attrition in drug development. Tackling the threat of compound-related toxicological attrition needs to move to the mainstream of medicinal chemistry decision-making.

Relating protein pharmacology by ligand chemistry

Abstract: The identification of protein function based on biological information is an area of intense research. Here we consider a complementary technique that quantitatively groups and relates proteins based on the chemical similarity of their ligands. We began with 65,000 ligands annotated into sets for hundreds of drug targets. The similarity score between each set was calculated using ligand topology. A statistical model was developed to rank the significance of the resulting similarity scores, which are expressed as a minimum spanning tree to map the sets together. Although these maps are connected solely by chemical similarity, biologically sensible clusters nevertheless emerged. Links among unexpected targets also emerged, among them that methadone, emetine and loperamide (Imodium) may antagonize muscarinic M3, α2 adrenergic and neurokinin NK2 receptors, respectively. These predictions were subsequently confirmed experimentally. Relating receptors by ligand chemistry organizes biology to reveal unexpected relationships that may be assayed using the ligands themselves.