Integrating biophysics with HTS-driven drug discovery projects

Creating a more strategic small molecule biophysical hit characterization workflow

To confirm target engagement of hits from our high-throughput screening efforts, we ran biophysical assays on several hundreds of hits from 15 different high-throughput screening campaigns. Analyzing the biophysical assay results from these screening campaigns led us to conclude that we could be more strategic in our biophysical analysis of hits by first confirming activity in a thermal shift assay (TSA) and then confirming activity in either a surface plasmon resonance (SPR) assay or a temperature-related intensity change (TRIC) assay. To understand how this new workflow shapes the quality of the final hits, we compared TSA/SPR or TSA/TRIC confirmed and unconfirmed hits to one another using four measures of compound quality: quantitative estimate of drug-likeness (QED), Pan-Assay Interference Compounds (PAINS), promiscuity, and aqueous solubility. In general, we found that the biophysically confirmed hits performed better in the compound quality metrics than the unconfirmed hits, demonstrating that our workflow not only confirmed target engagement of the hits but also enriched for higher quality hits.

Evolution of chemistry and selection technology for DNA-encoded library

DNA-encoded chemical library (DEL) links the power of amplifiable genetics and the non-self-replicating chemical phenotypes, generating a diverse chemical world. In analogy with the biological world, the DEL world can evolve by using a chemical central dogma, wherein DNA replicates using the PCR reactions to amplify the genetic codes, DNA sequencing transcripts the genetic information, and DNA-compatible synthesis translates into chemical phenotypes. Importantly, DNA-compatible synthesis is the key to expanding the DEL chemical space. Besides, the evolution-driven selection system pushes the chemicals to evolve under the selective pressure, i.e., desired selection strategies. In this perspective, we summarized recent advances in expanding DEL synthetic toolbox and panning strategies, which will shed light on the drug discovery harnessing in vitro evolution of chemicals via DEL.

Recent Advances in Chemotherapeutics for Leishmaniasis: Importance of the Cellular Biochemistry of the Parasite and Its Molecular Interaction with the Host

Leishmaniasis, a category 1 neglected protozoan disease caused by a kinetoplastid pathogen called Leishmania, is transmitted through dipteran insect vectors (phlebotomine, sand flies) in three main clinical forms: fatal visceral leishmaniasis, self-healing cutaneous leishmaniasis, and mucocutaneous leishmaniasis. Generic pentavalent antimonials have long been the drug of choice against leishmaniasis; however, their success is plagued with limitations such as drug resistance and severe side effects, which makes them redundant as frontline therapy for endemic visceral leishmaniasis. Alternative therapeutic regimens based on amphotericin B, miltefosine, and paromomycin have also been approved. Due to the unavailability of human vaccines, first-line chemotherapies such as pentavalent antimonials, pentamidine, and amphotericin B are the only options to treat infected individuals. The higher toxicity, adverse effects, and perceived cost of these pharmaceutics, coupled with the emergence of parasite resistance and disease relapse, makes it urgent to identify new, rationalized drug targets for the improvement in disease management and palliative care for patients. This has become an emergent need and more relevant due to the lack of information on validated molecular resistance markers for the monitoring and surveillance of changes in drug sensitivity and resistance. The present study reviewed the recent advances in chemotherapeutic regimens by targeting novel drugs using several strategies including bioinformatics to gain new insight into leishmaniasis. Leishmania has unique enzymes and biochemical pathways that are distinct from those of its mammalian hosts. In light of the limited number of available antileishmanial drugs, the identification of novel drug targets and studying the molecular and cellular aspects of these drugs in the parasite and its host is critical to design specific inhibitors targeting and controlling the parasite. The biochemical characterization of unique Leishmania-specific enzymes can be used as tools to read through possible drug targets. In this review, we discuss relevant metabolic pathways and novel drugs that are unique, essential, and linked to the survival of the parasite based on bioinformatics and cellular and biochemical analyses.

High-Throughput Screening of Natural Product and Synthetic Molecule Libraries for Antibacterial Drug Discovery

Due to the continued emergence of resistance and a lack of new and promising antibiotics, bacterial infection has become a major public threat. High-throughput screening (HTS) allows rapid screening of a large collection of molecules for bioactivity testing and holds promise in antibacterial drug discovery. More than 50% of the antibiotics that are currently available on the market are derived from natural products. However, with the easily discoverable antibiotics being found, finding new antibiotics from natural sources has seen limited success. Finding new natural sources for antibacterial activity testing has also proven to be challenging. In addition to exploring new sources of natural products and synthetic biology, omics technology helped to study the biosynthetic machinery of existing natural sources enabling the construction of unnatural synthesizers of bioactive molecules and the identification of molecular targets of antibacterial agents. On the other hand, newer and smarter strategies have been continuously pursued to screen synthetic molecule libraries for new antibiotics and new druggable targets. Biomimetic conditions are explored to mimic the real infection model to better study the ligand-target interaction to enable the designing of more effective antibacterial drugs. This narrative review describes various traditional and contemporaneous approaches of high-throughput screening of natural products and synthetic molecule libraries for antibacterial drug discovery. It further discusses critical factors for HTS assay design, makes a general recommendation, and discusses possible alternatives to traditional HTS of natural products and synthetic molecule libraries for antibacterial drug discovery.

High-throughput mechanistic screening of non-equilibrium inhibitors by a fully automated data analysis pipeline in early drug-discovery

Recent efforts for increasing the success in drug discovery focus on an early, massive, and routine mechanistic and/or kinetic characterization of drug-target engagement as part of a design-make-test-analyze strategy. From an experimental perspective, many mechanistic assays can be translated into a scalable format on automation platforms and thereby enable routine characterization of hundreds or thousands of compounds. However, now the limiting factor to achieve such in-depth characterization at high-throughput becomes the quality-driven data analysis, the sheer scale of which outweighs the time available to the scientific staff of most labs. Therefore, automated analytical workflows are needed to enable such experimental scale-up. We have implemented such a fully automated workflow in Genedata Screener for time-dependent ligand-target binding analysis to characterize non-equilibrium inhibitors. The workflow automates Quality Control (QC) / data modelling and decision-making process in a staged analysis: (1) quality control of raw input data-fluorescence signal-based progress curves - featuring automated rejection of unsuitable measurements; (2) automated model selection - one-step versus two-step binding model - using statistical methods and biological validity rules; (3) result visualization in specific plots and annotated result tables, enabling the scientist to review large result sets efficiently and, at the same time, to rapidly identify and focus on interesting or unusual results; (4) an interactive user interface for immediate adjustment of automated decisions, where necessary. Applying this workflow to first-pass, high-throughput kinetic studies on kinase projects has allowed us to surmount previously rate-limiting manual analysis steps and boost productivity; and is now routinely embedded in a biopharma discovery research process.

Screening for Small-Molecule Inhibitors of Histone Methyltransferases

Potent and highly selective small-molecule inhibitors are needed to unravel the biological complexities of histone methyltransferases and to reveal their therapeutic potential. A prerequisite to developing these inhibitors is the identification of validated chemical matter for initiating a medicinal chemistry campaign. For the most part, finding these initial starting points occurs through screening of large, unbiased compound libraries. The size and nature of these libraries, coupled with the complexities of the bisubstrate utilizing histone methyltransferases, necessitates that the primary screen and subsequent hit triage be carefully considered.In this chapter, using EZH2 as a representative example, we describe a screening and hit triage campaign that identified validated chemical matter allowing initiation of medicinal chemistry studies. Moreover, we discuss a cell-based assay to support lead identification and optimization. The approach described here entailing a mixture of biochemical, biophysical and cell-based assays should be applicable to identifying validated starting points for other histone methyltransferases.

DNA-Encoded Chemical Libraries: A Comprehensive Review with Succesful Stories and Future Challenges

DNA-encoded chemical libraries (DELs) represent a versatile and powerful technology platform for the discovery of small-molecule ligands to protein targets of biological and pharmaceutical interest. DELs are collections of molecules, individually coupled to distinctive DNA tags serving as amplifiable identification barcodes. Thanks to advances in DNA-compatible reactions, selection methodologies, next-generation sequencing, and data analysis, DEL technology allows the construction and screening of libraries of unprecedented size, which has led to the discovery of highly potent ligands, some of which have progressed to clinical trials. In this Review, we present an overview of diverse approaches for the generation and screening of DEL molecular repertoires. Recent success stories are described, detailing how novel ligands were isolated from DEL screening campaigns and were further optimized by medicinal chemistry. The goal of the Review is to capture some of the most recent developments in the field, while also elaborating on future challenges to further improve DEL technology as a therapeutic discovery platform.

A computer-aided approach to identify novel Leishmania major protein disulfide isomerase inhibitors for treatment of leishmaniasis

Leishmaniasis is an infectious disease caused by parasites of the genus Leishmania and transmitted by the bite of a sand fly. To date, most available drugs for treatment are toxic and beyond the economic means of those affected by the disease. Protein disulfide isomerase (PDI) is a chaperone protein that plays a major role in the folding of newly synthesized proteins, specifically assisting in disulfide bond formation, breakage, or rearrangement in all non-native proteins. In previous work, we demonstrated that Leishmania major PDI (LmPDI) has an essential role in pathogen virulence. Furthermore, inhibition of LmPDI further blocked parasite infection in macrophages. In this study, we utilized a computer-aided approach to design a series of LmPDI inhibitors. Fragment-based virtual screening allowed for the understanding of the inhibitors' modes of action on LmPDI active sites. The generated compounds obtained after multiple rounds of virtual screening were synthesized and significantly inhibited target LmPDI reductase activity and were shown to decrease in vitro parasite growth in human monocyte-derived macrophages. This novel cheminformatics and synthetic approach led to the identification of a new series of compounds that might be optimized into novel drugs, likely more specific and less toxic for the treatment of leishmaniasis.

A Single-Stranded DNA-Encoded Chemical Library Based on a Stereoisomeric Scaffold Enables Ligand Discovery by Modular Assembly of Building Blocks

A versatile and Lipinski-compliant DNA-encoded library (DEL), comprising 366 600 glutamic acid derivatives coupled to oligonucleotides serving as amplifiable identification barcodes is designed, constructed, and characterized. The GB-DEL library, constructed in single-stranded DNA format, allows de novo identification of specific binders against several pharmaceutically relevant proteins. Moreover, hybridization of the single-stranded DEL with a set of known protein ligands of low to medium affinity coupled to a complementary DNA strand results in self-assembled selectable chemical structures, leading to the identification of affinity-matured compounds.

Statistical models for identifying frequent hitters in high throughput screening

High throughput screening (HTS) interrogates compound libraries to find those that are “active” in an assay. To better understand compound behavior in HTS, we assessed an existing binomial survivor function (BSF) model of “frequent hitters” using 872 publicly available HTS data sets. We found large numbers of “infrequent hitters” using this model leading us to reject the BSF for identifying “frequent hitters.” As alternatives, we investigated generalized logistic, gamma, and negative binomial distributions as models for compound behavior. The gamma model reduced the proportion of both frequent and infrequent hitters relative to the BSF. Within this data set, conclusions about individual compound behavior were limited by the number of times individual compounds were tested (1–1613 times) and disproportionate testing of some compounds. Specifically, most tests (78%) were on a 309,847-compound subset (17.6% of compounds) each tested ≥ 300 times. We concluded that the disproportionate retesting of some compounds represents compound repurposing at scale rather than drug discovery. The approach to drug discovery represented by these 872 data sets characterizes the assays well by challenging them with many compounds while each compound is characterized poorly with a single assay. Aggregating the testing information from each compound across the multiple screens yielded a continuum with no clear boundary between normal and frequent hitting compounds.

Of Drugs and Trypanosomatids: New Tools and Knowledge to Reduce Bottlenecks in Drug Discovery

Leishmaniasis (Leishmania species), sleeping sickness (Trypanosoma brucei), and Chagas disease (Trypanosoma cruzi) are devastating and globally spread diseases caused by trypanosomatid parasites. At present, drugs for treating trypanosomatid diseases are far from ideal due to host toxicity, elevated cost, limited access, and increasing rates of drug resistance. Technological advances in parasitology, chemistry, and genomics have unlocked new possibilities for novel drug concepts and compound screening technologies that were previously inaccessible. In this perspective, we discuss current models used in drug-discovery cascades targeting trypanosomatids (from in vitro to in vivo approaches), their use and limitations in a biological context, as well as different examples of recently discovered lead compounds.

Lead Identification of 8-(Methylamino)-2-oxo-1,2-dihydroquinoline Derivatives as DNA Gyrase Inhibitors: Hit-to-Lead Generation Involving Thermodynamic Evaluation

DNA gyrase and topoisomerase IV are well-validated pharmacological targets, and quinolone antibacterial drugs are marketed as their representative inhibitors. However, in recent years, resistance to these existing drugs has become a problem, and new chemical classes of antibiotics that can combat resistant strains of bacteria are strongly needed. In this study, we applied our hit-to-lead (H2L) chemistry for the identification of a new chemical class of GyrB/ParE inhibitors by efficient use of thermodynamic parameters. Investigation of the core fragments obtained by fragmentation of high-throughput screening hit compounds and subsequent expansion of the hit fragment was performed using isothermal titration calorimetry (ITC). The 8-(methylamino)-2-oxo-1,2-dihydroquinoline derivative 13e showed potent activity against Escherichia coli DNA gyrase with an IC₅₀ value of 0.0017 μM. In this study, we demonstrated the use of ITC for primary fragment screening, followed by structural optimization to obtain lead compounds, which advanced into further optimization for creating novel antibacterial agents.

Action plan for hit identification (APHID): KAT6A as a case study

Here, we describe our action plan for hit identification (APHID) that guides the process of hit triage, with elimination of less tractable hits and retention of more tractable hits. We exemplify the process with reference to our high-throughput screening (HTS) campaign against the enzyme, KAT6A, that resulted in successful identification of a tractable hit. We hope that APHID could serve as a useful, concise and digestible guide for those involved in HTS and hit triage, especially those that are relatively new to this exciting and continually evolving technology.

Multifunctional Building Blocks Compatible with Photoredox-Mediated Alkylation for DNA-Encoded Library Synthesis

DNA-encoded library (DEL) technology has emerged as a novel interrogation modality for ligand discovery in the pharmaceutical industry. Given the increasing demand for a higher proportion of C(sp³)-hybridized centers in DEL platforms, a photoredox-mediated cross-coupling and defluorinative alkylation process is introduced using commercially available alkyl bromides and structurally diverse α-silylamines. Notably, no protecting group strategies for amines are necessary for the incorporation of a variety of amino-acid-based organosilanes, providing crucial branching points for further derivatization.

A Decoupled Automation Platform for Hydrogen/Deuterium Exchange Mass Spectrometry Experiments

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) is a biophysical technique well suited to the characterization of protein dynamics and protein-ligand interactions. In order to accurately define the rate of exchange, HDX experiments require the repeated measure of deuterium incorporation into the target protein across a range of time points. Accordingly, the HDX-MS experiment is well suited to automation, and a number of automated systems for HDX-MS have been developed. The most widely utilized platforms all operate an integrated design, where robotic liquid handling is interfaced directly with a mass spectrometer. With integrated designs, the exchange samples are prepared and injected into the LC-MS following a "real-time" serial workflow. Here we describe a new HDX-MS platform that is comprised of two complementary pieces of automation that disconnect the sample preparation from the LC-MS analysis. For preparation, a plate-based automation system is used to prepare samples in parallel, followed by immediate freezing and storage. A second piece of automation has been constructed to perform the thawing and LC-MS analysis of frozen samples in a serial mode and has been optimized to maximize the duty cycle of the mass spectrometer. The decoupled configuration described here reduces experiment time, significantly improves capacity, and improves the flexibility of the platform when compared with a fully integrated system.

AntiBac-Pred: A Web Application for Predicting Antibacterial Activity of Chemical Compounds

Discovery of new antibacterial agents is a never-ending task of medicinal chemistry. Every new drug brings significant improvement to patients with bacterial infections, but prolonged usage of antibacterials leads to the emergence of resistant strains. Therefore, novel active structures with new modes of action are required. We describe a web application called AntiBac-Pred aimed to help users in the rational selection of the chemical compounds for experimental studies of antibacterial activity. This application is developed using antibacterial activity data available in ChEMBL and PASS software. It allows users to classify chemical structures of interest into growth inhibitors or noninhibitors of 353 different bacteria strains, including both resistant and nonresistant ones.

Using Microscale Thermophoresis to Characterize Hits from High-Throughput Screening: A European Lead Factory Perspective

High-throughput screening (HTS) is a proven method for discovering new lead matter for drug discovery and chemical biology. To maximize the likelihood of identifying genuine binders to a molecular target, and avoid wasting resources following up compounds with unproductive/nonspecific mechanisms of action, it is important to employ a range of assays during an HTS campaign that build confidence of target engagement for hit compounds. Biophysical methods that measure direct target/compound engagement have established themselves as key techniques in generating this confidence, and they are now integral to the latter stages of HTS triage at the European Lead Factory (ELF). One relatively new technique that the ELF is using is microscale thermophoresis (MST), which measures the differences in rate of movement through a temperature gradient that are caused when single molecular species form complexes. Here we provide an overview of the MST assay development workflow that the ELF employs and a perspective of our experience to date of using MST to triage the output of HTS campaigns and how it compares and contrasts with the use of other biophysical techniques.

A Qualified Success: Discovery of a New Series of ATAD2 Bromodomain Inhibitors with a Novel Binding Mode Using High-Throughput Screening and Hit Qualification

The bromodomain of ATAD2 has proved to be one of the least-tractable proteins within this target class. Here, we describe the discovery of a new class of inhibitors by high-throughput screening and show how the difficulties encountered in establishing a screening triage capable of finding progressible hits were overcome by data-driven optimization. Despite the prevalence of nonspecific hits and an exceptionally low progressible hit rate (0.001%), our optimized hit qualification strategy employing orthogonal biophysical methods enabled us to identify a single active series. The compounds have a novel ATAD2 binding mode with noncanonical features including the displacement of all conserved water molecules within the active site and a halogen-bonding interaction. In addition to reporting this new series and preliminary structure-activity relationship, we demonstrate the value of diversity screening to complement the knowledge-based approach used in our previous ATAD2 work. We also exemplify tactics that can increase the chance of success when seeking new chemical starting points for novel and less-tractable targets.

Assessing molecular interactions with biophysical methods using the validation cross

There are numerous methods for studying molecular interactions. However, each method gives rise to false negative- or false positive binding results, stemming from artifacts of the scientific equipment or from shortcomings of the experimental format. To validate an initial positive binding result, additional methods need to be applied to cover the shortcomings of the primary experiment. The aim of such a validation procedure is to exclude as many artifacts as possible to confirm that there is a true molecular interaction that meets the standards for publishing or is worth investing considerable resources for follow-up activities in a drug discovery project. To simplify this validation process, a graphical scheme — the validation cross — can be used. This simple graphic is a powerful tool for identifying blind spots of a binding hypothesis, for selecting the most informative combination of methods to reveal artifacts and, in general, for understanding more thoroughly the nature of a validation process. The concept of the validation cross was originally introduced for the validation of protein–ligand interactions by NMR in drug discovery. Here, an attempt is made to expand the concept to further biophysical methods and to generalize it for binary molecular interactions.

Chemoinformatics Strategies for Leishmaniasis Drug Discovery

Leishmaniasis is a fatal neglected tropical disease (NTD) that is caused by more than 20 species of Leishmania parasites. The disease kills approximately 20,000 people each year and more than 1 billion are susceptible to infection. Although counting on a few compounds, the therapeutic arsenal faces some drawbacks such as drug resistance, toxicity issues, high treatment costs, and accessibility problems, which highlight the need for novel treatment options. Worldwide efforts have been made to that aim and, as well as in other therapeutic areas, chemoinformatics have contributed significantly to leishmaniasis drug discovery. Breakthrough advances in the comprehension of the parasites’ molecular biology have enabled the design of high-affinity ligands for a number of macromolecular targets. In addition, the use of chemoinformatics has allowed highly accurate predictions of biological activity and physicochemical and pharmacokinetics properties of novel antileishmanial compounds. This review puts into perspective the current context of leishmaniasis drug discovery and focuses on the use of chemoinformatics to develop better therapies for this life-threatening condition.

A Guide to Run Affinity Screens Using Differential Scanning Fluorimetry and Surface Plasmon Resonance Assays

Over the past 30 years, drug discovery has evolved from a pure phenotypic approach to an integrated target-based strategy. The implementation of high-throughput biochemical and cellular assays has enabled the screening of large compound libraries which has become an important and often times the main source of new chemical matter that serve as starting point for medicinal chemistry efforts. In addition, biophysical methods measuring the physical interaction (affinity) between a low molecular weight ligand and a target protein became an integral part of hit validation/optimization to rule out false positives due to assay artifacts. Recent advances in throughput, robustness, and sensitivity of biophysical affinity screening methods have broadened their application in hit identification and validation such that they can now complement classical functional readouts. As a result, new target classes can be accessed that have not been amenable to functional assays. In this chapter, two affinity screening methods, differential scanning fluorimetry and surface plasmon resonance, which are broadly utilized in both academia and pharmaceutical industry are discussed in respect to their use in hit identification and validation. These methods exemplify how assays which differ in complexity, throughput, and information content can support the hit identification/validation process. This chapter focuses on the practical aspects and caveats of these techniques in order to enable the reader to establish their own affinity-based screens in both formats.

DNA-Encoded Chemical Libraries: A Selection System Based on Endowing Organic Compounds with Amplifiable Information

The discovery of organic ligands that bind specifically to proteins is a central problem in chemistry, biology, and the biomedical sciences. The encoding of individual organic molecules with distinctive DNA tags, serving as amplifiable identification bar codes, allows the construction and screening of combinatorial libraries of unprecedented size, thus facilitating the discovery of ligands to many different protein targets. Fundamentally, one links powers of genetics and chemical synthesis. After the initial description of DNA-encoded chemical libraries in 1992, several experimental embodiments of the technology have been reduced to practice. This review provides a historical account of important milestones in the development of DNA-encoded chemical libraries, a survey of relevant ongoing research activities, and a glimpse into the future.

Computer-aided prediction of biological activity spectra for chemical compounds: opportunities and limitation

An essential characteristic of chemical compounds is their biological activity since its presence can become the basis for the use of the substance for therapeutic purposes, or, on the contrary, limit the possibilities of its practical application due to the manifestation of side action and toxic effects. Computer assessment of the biological activity spectra makes it possible to determine the most promising directions for the study of the pharmacological action of particular substances, and to filter out potentially dangerous molecules at the early stages of research. For more than 25 years, we have been developing and improving the computer program PASS (Prediction of Activity Spectra for Substances), designed to predict the biological activity spectrum of substance based on the structural formula of its molecules. The prediction is carried out by the analysis of structure-activity relationships for the training set, which currently contains information on structures and known biological activities for more than one million molecules. The structure of the organic compound is represented in PASS using Multilevel Neighborhoods of Atoms descriptors; the activity prediction for new compounds is performed by the naive Bayes classifier and the structure-activity relationships determined by the analysis of the training set. We have created and improved both local versions of the PASS program and freely available web resources based on PASS (http://www.way2drug.com). They predict several thousand biological activities (pharmacological effects, molecular mechanisms of action, specific toxicity and adverse effects, interaction with the unwanted targets, metabolism and action on molecular transport), cytotoxicity for tumor and non-tumor cell lines, carcinogenicity, induced changes of gene expression profiles, metabolic sites of the major enzymes of the first and second phases of xenobiotics biotransformation, and belonging to substrates and/or metabolites of metabolic enzymes. The web resource Way2Drug is used by over 18,000 researchers from more than 90 countries around the world, which allowed them to obtain over 600,000 predictions and publish about 500 papers describing the obtained results. The analysis of the published works shows that in some cases the interpretation of the prediction results presented by the authors of these publications requires an adjustment. In this work, we provide the theoretical basis and consider, on particular examples, the opportunities and limitations of computer-aided prediction of biological activity spectra.

NMR Methods for Identification of False Positives in Biochemical Screens

Over the past few decades, NMR spectroscopy has become an established tool in drug discovery. This communication will highlight the potential of NMR spectroscopy as a method for identification of problematic compounds and as a valuable aid toward revealing some mechanisms of promiscuous behavior. NMR methods for detecting false positives will be analyzed on the basis of their performance, strengths, limitations, and potential pitfalls. Additionally, this communication aims to provide an insight into the limitations of NMR-based methodologies applied to ligand screening in the context of false-positive hits.

Mechanistic enzymology in drug discovery: a fresh perspective

Given the therapeutic and commercial success of small-molecule enzyme inhibitors, as exemplified by kinase inhibitors in oncology, a major focus of current drug-discovery and development efforts is on enzyme targets. Understanding the course of an enzyme-catalysed reaction can help to conceptualize different types of inhibitor and to inform the design of screens to identify desired mechanisms. Exploiting this information allows the thorough evaluation of diverse compounds, providing the knowledge required to efficiently optimize leads towards differentiated candidate drugs. This review highlights the rationale for conducting high-quality mechanistic enzymology studies and considers the added value in combining such studies with orthogonal biophysical methods.

Ligand-detected NMR Methods in Drug Discovery

This book chapter describes the basic principles of NMR-based techniques for detecting ligand binding and uses examples of the application of these techniques in drug discovery programs for screening, hit validation and optimization to illustrate their utility in characterizing ligand–protein interactions. The binding of small molecules to biological receptors can be observed directly by detecting changes in a particular NMR parameter when the protein is added to a sample containing the ligand, or indirectly, using a “spy” molecule in competitive NMR experiments. Combinations of different NMR experiments can be used to confirm binding and also to obtain structural information that can be used to guide medicinal chemistry decisions. Ligand-observed NMR methods are able to identify weak affinity ligands that cannot be detected by other biophysical techniques, which means that NMR-based methods are extremely valuable tools for fragment-based drug discovery approaches.

Harnessing the Versatility of Optical Biosensors for Target-Based Small-Molecule Drug Discovery

Optical biosensors entered target-based small-molecule drug discovery more than two decades ago and have since transformed into a value-adding component in the decision-making process. Here, we briefly highlight the major application areas of optical biosensors and focus on desirable profiles of such platforms in order to ensure their effective use in small molecule drug discovery. Furthermore, we will emphasize current technology-based constraints and discuss experimental strategies to address these limitations as well as provide a view of necessary technology improvements for next generation platforms.

Unified Software Solution for Efficient SPR Data Analysis in Drug Research

Surface plasmon resonance (SPR) is a powerful method for obtaining detailed molecular interaction parameters. Modern instrumentation with its increased throughput has enabled routine screening by SPR in hit-to-lead and lead optimization programs, and SPR has become a mainstream drug discovery technology. However, the processing and reporting of SPR data in drug discovery are typically performed manually, which is both time-consuming and tedious. Here, we present the workflow concept, design and experiences with a software module relying on a single, browser-based software platform for the processing, analysis, and reporting of SPR data. The efficiency of this concept lies in the immediate availability of end results: data are processed and analyzed upon loading the raw data file, allowing the user to immediately quality control the results. Once completed, the user can automatically report those results to data repositories for corporate access and quickly generate printed reports or documents. The software module has resulted in a very efficient and effective workflow through saved time and improved quality control. We discuss these benefits and show how this process defines a new benchmark in the drug discovery industry for the handling, interpretation, visualization, and sharing of SPR data.

Biophysics in drug discovery: impact, challenges and opportunities

Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound-target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems.

Twenty years on: the impact of fragments on drug discovery

After 20 years of sometimes quiet growth, fragment-based drug discovery (FBDD) has become mainstream. More than 30 drug candidates derived from fragments have entered the clinic, with two approved and several more in advanced trials. FBDD has been widely applied in both academia and industry, as evidenced by the large number of papers from universities, non-profit research institutions, biotechnology companies and pharmaceutical companies. Moreover, FBDD draws on a diverse range of disciplines, from biochemistry and biophysics to computational and medicinal chemistry. As the promise of FBDD strategies becomes increasingly realized, now is an opportune time to draw lessons and point the way to the future. This Review briefly discusses how to design fragment libraries, how to select screening techniques and how to make the most of information gleaned from them. It also shows how concepts from FBDD have permeated and enhanced drug discovery efforts.