Author
Tudor I. Oprea
Other affiliations: University of Copenhagen, Technical University of Denmark, Rosalind Franklin University of Medicine and Science ...read more
Bio: Tudor I. Oprea is an academic researcher from University of New Mexico. The author has contributed to research in topics: Virtual screening & Medicine. The author has an hindex of 70, co-authored 280 publications receiving 18067 citations. Previous affiliations of Tudor I. Oprea include University of Copenhagen & Technical University of Denmark.
Topics: Virtual screening, Medicine, GPER, Receptor, G protein-coupled receptor
Papers published on a yearly basis
Papers
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TL;DR: An updated comprehensive map of molecular targets of approved drugs is presented and the relationships between bioactivity class and clinical success, as well as the presence of orthologues between human and animal models and between pathogen and human genomes are explored.
Abstract: The success of mechanism-based drug discovery depends on the definition of the drug target. This definition becomes even more important as we try to link drug response to genetic variation, understand stratified clinical efficacy and safety, rationalize the differences between drugs in the same therapeutic class and predict drug utility in patient subgroups. However, drug targets are often poorly defined in the literature, both for launched drugs and for potential therapeutic agents in discovery and development. Here, we present an updated comprehensive map of molecular targets of approved drugs. We curate a total of 893 human and pathogen-derived biomolecules through which 1,578 US FDA-approved drugs act. These biomolecules include 667 human-genome-derived proteins targeted by drugs for human disease. Analysis of these drug targets indicates the continued dominance of privileged target families across disease areas, but also the growth of novel first-in-class mechanisms, particularly in oncology. We explore the relationships between bioactivity class and clinical success, as well as the presence of orthologues between human and animal models and between pathogen and human genomes. Through the collaboration of three independent teams, we highlight some of the ongoing challenges in accurately defining the targets of molecular therapeutics and present conventions for deconvoluting the complexities of molecular pharmacology and drug efficacy.
1,465 citations
TL;DR: The optimization of low-potency leads into drugs is often accompanied by an increase in molecular weight and lipophilicity, as a consequence of affinity enhancement, shown schematically by the distributions of M(r) for a leadlike library, oral drugs, and a typical combinatorial chemistry library.
Abstract: The optimization of low-potency leads into drugs is often accompanied by an increase in molecular weight (M(r)) and lipophilicity, as a consequence of affinity enhancement. Hits with affinity at µM levels discovered by screening leadlike libraries allow scope for this optimization process, as shown schematically by the distributions of M(r) for a leadlike library (1), oral drugs (2), and a typical combinatorial chemistry library (3). y=percentage with a particular molecular weight.
742 citations
TL;DR: The identification of the first G PR30-specific agonist, G-1 (1), capable of activating GPR30 in a complex environment of classical and new estrogen receptors is described.
Abstract: Estrogen is a hormone critical in the development, normal physiology and pathophysiology of numerous human tissues. The effects of estrogen have traditionally been solely ascribed to estrogen receptor alpha (ERalpha) and more recently ERbeta, members of the soluble, nuclear ligand-activated family of transcription factors. We have recently shown that the seven-transmembrane G protein-coupled receptor GPR30 binds estrogen with high affinity and resides in the endoplasmic reticulum, where it activates multiple intracellular signaling pathways. To differentiate between the functions of ERalpha or ERbeta and GPR30, we used a combination of virtual and biomolecular screening to isolate compounds that selectively bind to GPR30. Here we describe the identification of the first GPR30-specific agonist, G-1 (1), capable of activating GPR30 in a complex environment of classical and new estrogen receptors. The development of compounds specific to estrogen receptor family members provides the opportunity to increase our understanding of these receptors and their contribution to estrogen biology.
741 citations
TL;DR: Lead structures exhibit, on the average, less molecular complexity, are less hydrophobic, and less druglike (lower druglike scores), and this information should be used in the design of novel combinatorial libraries that are aimed at lead discovery.
Abstract: To be considered for further development, lead structures should display the following properties: (1) simple chemical features, amenable for chemistry optimization; (2) membership to an established SAR series; (3) favorable patent situation; and (4) good absorption, distribution, metabolism, and excretion (ADME) properties. There are two distinct categories of leads: those that lack any therapeutic use (i.e., “pure” leads), and those that are marketed drugs themselves but have been altered to yield novel drugs. We have previously analyzed the design of leadlike combinatorial libraries starting from 18 lead and drug pairs of structures (S. J. Teague et al. Angew. Chem., Int. Ed. Engl. 1999, 38, 3743−3748). Here, we report results based on an extended dataset of 96 lead-drug pairs, of which 62 are lead structures that are not marketed as drugs, and 75 are drugs that are not presumably used as leads. We examined the following properties: MW (molecular weight), CMR (the calculated molecular refractivity),...
704 citations
TL;DR: An overview of the evidence for the cellular and physiological actions of GPR30 in estrogen-dependent processes and the relationship of G PR30 with classical estrogen receptors is provided.
Abstract: Steroids play an important role in the regulation of normal physiology and the treatment of disease. Steroid receptors have classically been described as ligand-activated transcription factors mediating long-term genomic effects in hormonally regulated tissues. It is now clear that steroids also mediate rapid signaling events traditionally associated with growth factor receptors and G protein–coupled receptors. Although evidence suggests that the classical steroid receptors are capable of mediating many of these events, more recent discoveries reveal the existence of transmembrane receptors capable of responding to steroids with cellular activation. One such receptor, GPR30, is a member of the G protein–coupled receptor superfamily and mediates estrogen-dependent kinase activation as well as transcriptional responses. In this review, we provide an overview of the evidence for the cellular and physiological actions of GPR30 in estrogen-dependent processes and discuss the relationship of GPR30 with classica...
567 citations
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TL;DR: Glide approximates a complete systematic search of the conformational, orientational, and positional space of the docked ligand to find the best docked pose using a model energy function that combines empirical and force-field-based terms.
Abstract: Unlike other methods for docking ligands to the rigid 3D structure of a known protein receptor, Glide approximates a complete systematic search of the conformational, orientational, and positional space of the docked ligand In this search, an initial rough positioning and scoring phase that dramatically narrows the search space is followed by torsionally flexible energy optimization on an OPLS-AA nonbonded potential grid for a few hundred surviving candidate poses The very best candidates are further refined via a Monte Carlo sampling of pose conformation; in some cases, this is crucial to obtaining an accurate docked pose Selection of the best docked pose uses a model energy function that combines empirical and force-field-based terms Docking accuracy is assessed by redocking ligands from 282 cocrystallized PDB complexes starting from conformationally optimized ligand geometries that bear no memory of the correctly docked pose Errors in geometry for the top-ranked pose are less than 1 A in nearly ha
6,828 citations
TL;DR: The new SwissADME web tool is presented that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar are presented.
Abstract: To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.
6,135 citations
TL;DR: A description of their implementation has not previously been presented in the literature, and ECFPs can be very rapidly calculated and can represent an essentially infinite number of different molecular features.
Abstract: Extended-connectivity fingerprints (ECFPs) are a novel class of topological fingerprints for molecular characterization. Historically, topological fingerprints were developed for substructure and similarity searching. ECFPs were developed specifically for structure−activity modeling. ECFPs are circular fingerprints with a number of useful qualities: they can be very rapidly calculated; they are not predefined and can represent an essentially infinite number of different molecular features (including stereochemical information); their features represent the presence of particular substructures, allowing easier interpretation of analysis results; and the ECFP algorithm can be tailored to generate different types of circular fingerprints, optimized for different uses. While the use of ECFPs has been widely adopted and validated, a description of their implementation has not previously been presented in the literature.
4,173 citations
TL;DR: The UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal and a credit-based publication submission interface was developed.
Abstract: Abstract The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
4,001 citations
TL;DR: This topic is explored in terms ofDrug-like physicochemical features, drug-like structural features, a comparison of drug- like and non-drug-like in drug discovery and a discussion of how drug-Like features relate to clinical success.
3,499 citations