Fragonomics: fragment-based drug discovery

The use of smaller molecules (fragments) in the drug discovery process has led to success in delivering novel leads for many different targets. This process is a highly integrated process, starting from library design to screening and medicinal chemistry. An overview of this process is presented with particular emphasis placed on the NMR aspect of screening.     

Drug discovery in academia

Drug discovery and development is generally done in the commercial rather than the academic realm. Drug discovery involves target discovery and validation, lead identification by high-throughput screening, and lead optimization by medicinal chemistry. Follow-up preclinical evaluation includes analysis in animal models of compound efficacy and pharmacology (ADME: administration, distribution, metabolism, elimination) and studies of toxicology, specificity, and drug interactions. Notwithstanding the high-cost, labor-intensive, and non-hypothesis-driven aspects of drug discovery, the academic setting has a unique and expanding niche in this important area of investigation. For example, academic drug discovery can focus on targets of limited commercial value, such as third-world and rare diseases, and on the development of research reagents such as high-affinity inhibitors for pharmacological "gene knockout" in animal models ("chemical genetics"). This review describes the practical aspects of the preclinical drug discovery process for academic investigators. The discovery of small molecule inhibitors and activators of the cystic fibrosis transmembrane conductance regulator is presented as an example of an academic drug discovery program that has yielded new compounds for physiology research and clinical development. high-throughput screening; drug development; pharmacology; fluorescence; cystic fibrosis transmembrane conductance regulator     

Chemical proteomics and its impact on the drug discovery process

Despite the rapid growth of postgenomic data and fast-paced technology advancement, drug discovery is still a lengthy and difficult process. More effective drug design requires a better understanding of the interaction between drug candidates and their targets/off-targets in various situations. The ability of chemical proteomics to integrate a multiplicity of disciplines enables the direct analysis of protein activities on a proteome-wide scale, which has enormous potential to facilitate drug target elucidation and lead drug verification. Over recent years, chemical proteomics has experienced rapid growth and provided a valuable method for drug target identification and inhibitor discovery. This review introduces basic concepts and technologies of different popular chemical proteomic approaches. It also covers the essential features and recent advances of each approach while underscoring their potentials in drug discovery and development.     

Recent encounters with atropisomerism in drug discovery

Atropisomerism is stereochemistry arising from restricted bond rotation that creates a chiral axis. Atropisomers are subject to time-dependent inversion of chirality via bond rotation, a property which in drug molecules introduces complexity and challenges for drug discovery and development processes. Greater recognition of the occurrence of atropisomerism and improved characterization techniques have helped medicinal chemists successfully advance atropisomeric drug molecules. This review provides recent examples of atropisomerism encountered in medicinal chemistry efforts and the strategies used to address the accompanying challenges.     

Improving success rates for lead generation using affinity binding technologies

Affinity technologies have been applied at several stages of the drug discovery process, ranging from target identification and purification to the identification of preclinical candidates. The detection of ligand-macromolecule interactions in lead discovery is the best studied and most powerful of these techniques. Although affinity methods have been in widespread use for about a decade, only recently have many reports emerged on their utility. Primary affinity screens of large libraries of small molecules or fragments have begun to produce results for challenging targets. Furthermore, in secondary assays affinity methods are opening new avenues to tackle important medicinal chemistry tasks.     

Inhibition of the bacterial surface protein anchoring transpeptidase sortase by medicinal plants

Inhibition by medicinal plant extracts of a recombinant sortase was evaluated for antibacterial drug discovery. The coding region of sortase, a transpeptidase that cleaves surface proteins of gram-positive bacteria, was amplified by PCR from the chromosome of Staphylococcus aureus ATCC 6538p with the exception of an N-terminal membrane anchor sequence, expressed in Escherichia coli, and purified by metal chelate affinity chromatography. The purified sortase had maximum activity at pH 7.5 and was stable at 20-45 degrees C for the cleavage of a synthetic fluorophore substrate. The enzyme inhibitory activity in medicinal plants was also evaluated for antibacterial drug discovery. Among 80 medicinal plants tested, Cocculus trilobus, Fritillaria verticillata, Liriope platyphylla, and Rhus verniciflua had strong inhibitory activity. The extract with the greatest activity was the ethyl acetate fraction derived from the rhizome of Cocculus trilobus (IC50 = 1.52 microg/ml).     

Rational approaches,design strategies,structure activity relationship and mechanistic insights for therapeutic coumarin hybrids

Hybrid molecules, furnished by combining two or more pharmacophores is an emerging concept in the field of medicinal chemistry and drug discovery that has attracted substantial traction in the past few years. Naturally occurring scaffolds such as coumarins display a wide spectrum of pharmacological activities including anticancer, antibiotic, antidiabetic and others, by acting on multiple targets. In this view, various coumarin-based hybrids possessing diverse medicinal attributes were synthesized in the last five years by conjugating coumarin moiety with other therapeutic pharmacophores. The current review summarizes the recent development (2014 and onwards) of these pharmacologically active coumarin hybrids and demonstrates rationale behind their design, structure-activity relationships (SAR) and mechanistic studies performed on these hybrid molecules. This review will be beneficial for medicinal chemist and chemical biologist, and in general to the drug discovery community and will facilitate the synthesis and development of novel, potent coumarin hybrid molecules serving as lead molecules for the treatment of complex disorders.     

The myth of the biotech revolution

The existence of a medicinal 'biotech revolution' has been widely accepted and promoted by academics, consultants, industry and government. This has generated expectations about significant improvements in the drug discovery process, healthcare and economic development that influence a considerable amount of policy-making. Here we present empirical evidence, from a variety of indicators, that shows that a range of outputs have failed to keep pace with increased research and development spending. Rather than producing revolutionary changes, medicinal biotechnology is following a well-established pattern of slow and incremental technology diffusion. Consequently, many expectations are wildly optimistic and over-estimate the speed and extent of the impact of biotechnology, suggesting that the assumptions underpinning much contemporary policymaking need to be rethought.     

The use of spirocyclic scaffolds in drug discovery

Owing to their inherent three-dimensionality and structural novelty, spiro scaffolds have been increasingly utilized in drug discovery. In this brief review, we highlight selected examples from the primary medicinal chemistry literature during the last three years to demonstrate the versatility of spiro scaffolds. With recent progress in synthetic methods providing access to spiro building blocks, spiro scaffolds are likely to be used more frequently in drug discovery.     

Structural chemoproteomics and drug discovery

Our laboratories have developed several technologies to accelerate drug discovery process on the basis of structural chemoproteomics. They include SPS technology for the efficient determination of protein structures, SCP technology for the rapid lead generation and SDF technology for the productive lead optimization. Using these technologies, we could determine many 3D structures of target proteins bound with biologically active chemicals including the structure of phosphodiesterase 5/Viagra complex and obtain highly potent compounds in animal models of obesity, diabetes, cancer and inflammation. In this paper, we will discuss concepts and applications of structural chemoproteomics for drug discovery.     

Drug discovery from medicinal plants

Current research in drug discovery from medicinal plants involves a multifaceted approach combining botanical, phytochemical, biological, and molecular techniques. Medicinal plant drug discovery continues to provide new and important leads against various pharmacological targets including cancer, HIV/AIDS, Alzheimer's, malaria, and pain. Several natural product drugs of plant origin have either recently been introduced to the United States market, including arteether, galantamine, nitisinone, and tiotropium, or are currently involved in late-phase clinical trials. As part of our National Cooperative Drug Discovery Group (NCDDG) research project, numerous compounds from tropical rainforest plant species with potential anticancer activity have been identified. Our group has also isolated several compounds, mainly from edible plant species or plants used as dietary supplements, that may act as chemopreventive agents. Although drug discovery from medicinal plants continues to provide an important source of new drug leads, numerous challenges are encountered including the procurement of plant materials, the selection and implementation of appropriate high-throughput screening bioassays, and the scale-up of active compounds.     

Pursuing the leadlikeness concept in pharmaceutical research

Lipinski and others, through concepts such as drug-likeness, re-focussed drug discovery back to the principles of medicinal chemistry in the high-throughput era as key to reducing attrition. More recently, the need to go further in defining what makes a good lead has been recognised with the concept of leadlikeness. Leadlikeness implies cut-off values in the physico-chemical profile of chemical libraries such that they have reduced complexity (e.g. MW below <400) and other more restricted properties. We examine these concepts in the context of Virtual (theoretically possible), Tangible (chemically feasible) and Real (physically available) worlds of molecules. In a thought experiment, we take the HTS concept to the extreme: screening an estimated 60 million 'Global Collection' on 5000 targets and realising that perhaps millions of drug candidates might be found that could not possibly be handled in reality. Sampling of the Virtual and Tangible worlds is therefore a necessity. We show that the world of Reals is significantly under-sampled as the MW of compounds increases. This supports the design and screening of 'reduced complexity' (leadlike) compound libraries, preferably with synthetic handles available for rapid chemical iteration and detected as interesting by careful screening or biophysical assays.     

Drug Guru: a computer software program for drug design using medicinal chemistry rules

Drug Guru (drug generation using rules) is a new web-based computer software program for medicinal chemists that applies a set of transformations, that is, rules, to an input structure. The transformations correspond to medicinal chemistry design rules-of-thumb taken from the historical lore of drug discovery programs. The output of the program is a list of target analogs that can be evaluated for possible future synthesis. A discussion of the features of the program is followed by an example of the software applied to sildenafil (Viagra) in generating ideas for target analogs for phosphodiesterase inhibition. Comparison with other computer-assisted drug design software is given.     

The successful quest for oral factor Xa inhibitors; learnings for all of medicinal chemistry?

The medicinal chemistry of oral small molecule factor Xa inhibitors is discussed, highlighting key advances that led to clinical candidates and the first licensed medicines. Identification of neutral ligands for the primary specificity pocket was a key discovery; capitalised upon by structure based design and combinatorial methods to deliver many variations on the theme; but it was good medicinal chemistry practice, in the optimisation of physical properties, which ultimately delivered efficacious compounds with adequate oral exposure. As a retrospective appraisal, representative compounds were profiled using the more contemporary concepts of Ligand Efficiency and Property Forecast Indices; which gave clear indications of the value of these principles.     

The anti-intellectual effects of intellectual property

Intellectual property considerations decrease research productivity in subtle and unanticipated ways. Chemical probe exchange between Pharma and academia is hindered by academic IP interests. These are perceived as a subtle nuisance by the academic researcher. Novel ligands for oral targets are historically few and numbers of economically attractive oral drug targets are limited. Economically speculative targets lie in the academic domain but the medicinal chemistry to explore these in a drug discovery sense lies in Pharma and cooperation between the two is hindered by very different academic and Pharma views on chemical quality. Tools and probes for academic target validation can accommodate looser chemical quality criteria as opposed to the very strict chemical quality criteria required in Pharma drug discovery.     

Fragment-based discovery and optimization of BACE1 inhibitors

A novel series of 2-aminobenzimidazole inhibitors of BACE1 has been discovered using fragment-based drug discovery (FBDD) techniques. The rapid optimization of these inhibitors using structure-guided medicinal chemistry is discussed.     

Structure-based drug design with geometric deep learning

Structure-based drug design uses three-dimensional geometric information of macromolecules, such as proteins or nucleic acids, to identify suitable ligands. Geometric deep learning, an emerging concept of neural-network-based machine learning, has been applied to macromolecular structures. This review provides an overview of the recent applications of geometric deep learning in bioorganic and medicinal chemistry, highlighting its potential for structure-based drug discovery and design. Emphasis is placed on molecular property prediction, ligand binding site and pose prediction, and structure-based de novo molecular design. The current challenges and opportunities are highlighted, and a forecast of the future of geometric deep learning for drug discovery is presented.     

Biomolecular NMR: a chaperone to drug discovery

Biomolecular NMR now contributes routinely to every step in the development of new chemical entities ahead of clinical trials. The versatility of NMR--from detection of ligand binding over a wide range of affinities and a wide range of drug targets with its wealth of molecular information, to metabolomic profiling, both ex vivo and in vivo--has paved the way for broadly distributed applications in academia and the pharmaceutical industry. Proteomics and initial target selection both benefit from NMR: screenings by NMR identify lead compounds capable of inhibiting protein-protein interactions, still one of the most difficult development tasks in drug discovery. NMR hardware improvements have given access to the microgram domain of phytochemistry, which should lead to the discovery of novel bioactive natural compounds. Steering medicinal chemists through the lead optimisation process by providing detailed information about protein-ligand interactions has led to impressive success in the development of novel drugs. The study of biofluid composition--metabonomics--provides information about pharmacokinetics and helps toxicological safety assessment in animal model systems. In vivo, magnetic resonance spectroscopy interrogates metabolite distributions in living cells and tissues with increasing precision, which significantly impacts the development of anticancer or neurological disorder therapeutics. An overview of different steps in recent drug discovery is presented to illuminate the links with the most recent advances in NMR methodology.     

Diversity & tractability revisited in collaborative small molecule phenotypic screening library design

Identification of purposeful chemical matter on a broad range of drug targets is of high importance to the pharmaceutical industry. However, disease-relevant but more complex hit-finding plans require flexibility regarding the subset of the compounds that we screen. Herein we describe a strategy to design high-quality small molecule screening subsets of two different sizes to cope with a rapidly changing early discovery portfolio. The approach taken balances chemical tractability, chemical diversity and biological target coverage. Furthermore, using surveys, we actively involved chemists within our company in the selection process of the diversity decks to ensure current medicinal chemistry principles were incorporated. The chemist surveys revealed that not all published PAINS substructure alerts are considered productive by the medicinal chemistry community and in agreement with previously published results from other institutions, QED scores tracked quite well with chemists’ notions of chemical attractiveness.     

Database on pharmacophore analysis of active principles, from medicinal plants

Plants continue to be a major source of medicines, as they have been throughout human history. In the present days, drug discovery from plants involves a multidisciplinary approach combining ethnobotanical, phytochemical and biological techniques to provide us new chemical compounds (lead molecules) for the development of drugs against various pharmacological targets, including cancer, diabetes and its secondary complications. In view of this need in current drug discovery from medicinal plants, here we describe another web database containing the information of pharmacophore analysis of active principles possessing antidiabetic, antimicrobial, anticancerous and antioxidant properties from medicinal plants. The database provides the botanical, taxonomic classification, biochemical as well as pharmacological properties of medicinal plants. Data on antidiabetic, antimicrobial, anti oxidative, anti tumor and anti inflammatory compounds, and their physicochemical properties, SMILES Notation, Lipinski's properties are included in our database. One of the proposed features in the database is the predicted ADMET values and the interaction of bioactive compounds to the target protein. The database alphabetically lists the compound name and also provides tabs separating for anti microbial, antitumor, antidiabetic, and antioxidative compounds. AVAILABILITY: http://www.hccbif.info /