Drug Discovery Applications Research Articles

MultiplexMS: A Mass Spectrometry-Based Multiplexing Strategy for Ultra-High-Throughput Analysis of Complex Mixtures.

High-throughput chemical analysis of natural product mixtures lags behind developments in genome sequencing technologies and laboratory automation, leading to a disconnect between library-scale chemical and biological profiling that limits new molecule discovery. Here, we report a new orthogonal sample multiplexing strategy that can increase mass spectrometry-based profiling up to 30-fold over traditional methods. Profiled pooled samples undergo subsequent computational deconvolution to reconstruct peak lists for each sample in the set. We validated this approach using in silico experiments and demonstrated a high assignment precision (>97%) for large, pooled samples (r = 30), particularly for infrequently occurring metabolites of relevance in drug discovery applications. Requiring only 5% of the previously required MS acquisition time, this approach was repeated in a recent biological activity profiling study on 925 natural product extracts, leading to the rediscovery of all previously reported bioactive metabolites. This new method is compatible with MS data from any instrument vendor and is supported by an open-source software package: https://github.com/liningtonlab/MultiplexMS.

A novel Hyperledger blockchain-enabled decentralized application for drug discovery chain management

The aim of the drug discovery process is to create a brand-new drug that is both safe and useful for treating disease in patients. The trustworthy collaboration of the organisations involved in the drug discovery process and the integrity of their contributions are essential for this process. Current drug discovery chains use centralised systems, which are susceptible to lockdown by cyberattacks. Blockchain, with its many characteristics such as accountability, immutability, integrity, privacy, and security, has the potential to be extremely useful in drug discovery chain management. The purpose of this work is to create a drug discovery framework utilizing the strengths of blockchain technology in combination with machine learning (ML). Such a system would provide a secure, efficient, and faster drug development life cycle. This study presents a novel Hyperledger fabric-based drug discovery application that empowers the permissioned organisations to upload, update, view, and verify contributions. ML is used to preprocess data and visualise features. In the proposed work, a unique identifier is assigned to each contribution asset using the secure hash algorithm (SHA-256). The proposed design also enables the regulatory authority to issue certificates proving the ownership of contributions to the contributing organisations. The blockchain ledger has been used to store the meta-data and InChIKey of drug contributions, and actual contributions are in off-chain storage. In this work, we have successfully built an end-to-end decentralised drug discovery application with a front-end interface and demonstrated chaincode algorithms. The end-to-end application is not available in any previous work. The Caliper tool has been used to investigate throughput, latency, and resource statistics. The performance and comparative analysis show that the proposed design is scalable and promising for drug discovery chain management.

NGS Analysis to Detect Mutation in Brain Tumor Diagnostic

Abstract: This study presents an integrated computational approach for analyzing protein sequences and their 3D structures. By leveraging the MMDB Macromolecular database, homologs of a protein sequence of interest are identified, and interactive visualization of their structural properties is provided. The computational alignment method, using BLASTP, allows for efficient determination of sequence similarities and identification of conserved regions among multiple protein sequences. COBALT is employed to refine sequence alignments and facilitate graphical analysis of sequence relationships. RASMOL, a computational analysis program, generates 2-D representations of protein-ligand complexes, enabling visual exploration of their interactions. ORF finder is used to identify coding regions in mRNA sequences, aiding in the prediction of protein-coding regions. The approach is applied to brain tumor diagnostics using human biological samples, exploring the structural properties of brain tumor-related proteins with the help of the 2RHU protein structure and PYMOL visualization software. Overall, this integrated computational framework offers a comprehensive toolkit for protein sequence analysis, structure visualization, and homology modeling, with potential applications in drug discovery, molecular biology, and medical diagnostics

D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening

Resource- and time-consuming biological experiments are unavoidable in traditional drug discovery, which have directly driven the evolution of various computational algorithms and tools for drug-target interaction (DTI) prediction. For improving the prediction reliability, a comprehensive platform is highly expected as some previously reported webservers are small in scale, single-method, or even out of service. In this study, we integrated the multiple-conformation based docking, 2D/3D ligand similarity search and deep learning approaches to construct a comprehensive webserver, namely D3CARP, for target prediction and virtual screening. Specifically, 9352 conformations with positive control of 1970 targets were used for molecular docking, and approximately 2 million target-ligand pairs were used for 2D/3D ligand similarity search and deep learning. Besides, the positive compounds were added as references, and related diseases of therapeutic targets were annotated for further disease-based DTI study. The accuracies of the molecular docking and deep learning approaches were 0.44 and 0.89, respectively. And the average accuracy of five ligand similarity searches was 0.94. The strengths of D3CARP encompass the support for multiple computational methods, ensemble docking, utilization of positive controls as references, cross-validation of predicted outcomes, diverse disease types, and broad applicability in drug discovery. The D3CARP is freely accessible at https://www.d3pharma.com/D3CARP/index.php.

Generation and application of avatars in pharmacometric modelling

Simulations from population models have critical applications in drug discovery and development. Avatars or digital twins, defined as individual simulations matching clinical criteria of interest compared to observations from a real subject within a predefined margin of accuracy, may be a better option for simulations performed to inform future drug development stages in cases where an adequate model is not achievable. The aim of this work was to (1) investigate methods for generating avatars with pharmacometric models, and (2) explore the properties of the generated avatars to assess the impact of the different selection settings on the number of avatars per subject, their closeness to the individual observations, and the properties of the selected samples subset from the theoretical model parameters probability density function. Avatars were generated using different combinations of nature and number of clinical criteria, accuracy of agreement, and/or number of simulations for two examples models previously published (hemato-toxicity and integrated glucose-insulin model). The avatar distribution could be used to assess the appropriateness of the models assumed parameter distribution. Similarly it could be used to assess the models ability to properly describe the trajectories of the observations. Avatars can give nuanced information regarding the ability of a model to simulate data similar to the observations both at the population and at the individual level. Further potential applications for avatars may be as a diagnostic tool, an alternative to simulations with insurance to replicate key clinical features, and as an individual measure of model fit.

Track‐Etched Membranes for Drug Pharmaceutical Research

AbstractOver the last decades, the incorporation of membranes into micro physiological systems used for pharmaceutical research and drug development has grown significantly. One example is the use of microporous track‐etched membranes in microfluidic systems like organs‐on‐a‐chip and cell culture inserts for tissue engineering. Tissue‐culture treated track‐etched membranes serve as excellent support for cell growth and efficient nutrient supply, with the added benefit of precise control of pore parameters, a critical pre‐requisite to achieve reproducible results. Here, we provide an overview of track‐etched membrane technology in the context of applications in drug discovery and development.

Photochemical Benzylation of White Phosphorus.

Organophosphorus compounds (OPCs) have wide application in organic synthesis, material sciences, and drug discovery. Generally, the vast majority of phosphorus atoms in OPCs are derived from white phosphorus (P4). However, the large-scale preparation of OPCs mainly proceeds through the multistep and environmentally toxic chlorine route from P4. Herein, we report the direct benzylation of P4 promoted by visible light. The cheap and readily available benzyl bromide was used as a benzylation reagent, and tetrabenzylphosphonium bromide was directly synthesized from P4. In addition, the metallaphotoredox catalysis strategy was applied to functionalize P4 for the first time, which significantly improved the application range of the substituted benzyl bromide.

Atroposelective Access to Dihydropyridinones with C-N Axial and Point Chirality via NHC-Catalyzed [3 + 3] Annulation.

An N-heterocyclic carbene-catalyzed atroposelective [3 + 3] annulation of enals with 2-aminomaleate derivatives is described. A series of substituted dihydropyridones bearing both C-N axis and point chirality were synthesized with good diastereo- and enantioselectivity under mild conditions. This efficient strategy successfully superpositions an extra point chiral element with an axial backbone, and the generated structurally interesting atropisomers may have potential application in drug discovery.

Bioreactor Technologies for Enhanced Organoid Culture.

An organoid is a 3D organization of cells that can recapitulate some of the structure and function of native tissue. Recent work has seen organoids gain prominence as a valuable model for studying tissue development, drug discovery, and potential clinical applications. The requirements for the successful culture of organoids in vitro differ significantly from those of traditional monolayer cell cultures. The generation and maturation of high-fidelity organoids entails developing and optimizing environmental conditions to provide the optimal cues for growth and 3D maturation, such as oxygenation, mechanical and fluidic activation, nutrition gradients, etc. To this end, we discuss the four main categories of bioreactors used for organoid culture: stirred bioreactors (SBR), microfluidic bioreactors (MFB), rotating wall vessels (RWV), and electrically stimulating (ES) bioreactors. We aim to lay out the state-of-the-art of both commercial and in-house developed bioreactor systems, their benefits to the culture of organoids derived from various cells and tissues, and the limitations of bioreactor technology, including sterilization, accessibility, and suitability and ease of use for long-term culture. Finally, we discuss future directions for improvements to existing bioreactor technology and how they may be used to enhance organoid culture for specific applications.

The Versatile Biocatalyst of Cytochrome P450 CYP102A1: Structure, Function, and Engineering.

Wild-type cytochrome P450 CYP102A1 from Bacillus megaterium is a highly efficient monooxygenase for the oxidation of long-chain fatty acids. The unique features of CYP102A1, such as high catalytic activity, expression yield, regio- and stereoselectivity, and self-sufficiency in electron transfer as a fusion protein, afford the requirements for an ideal biocatalyst. In the past three decades, remarkable progress has been made in engineering CYP102A1 for applications in drug discovery, biosynthesis, and biotechnology. The repertoire of engineered CYP102A1 variants has grown tremendously, whereas the substrate repertoire is avalanched to encompass alkanes, alkenes, aromatics, organic solvents, pharmaceuticals, drugs, and many more. In this article, we highlight the major advances in the past five years in our understanding of the structure and function of CYP102A1 and the methodologies used to engineer CYP102A1 for novel applications. The objective is to provide a succinct review of the latest developments with reference to the body of CYP102A1-related literature.

Indol-3-ylglyoxylamide as Privileged Scaffold in Medicinal Chemistry.

In recent years, indolylglyoxylamide-based derivatives have received much attention due to their application in drug design and discovery, leading to the development of a wide array of compounds that have shown a variety of pharmacological activities. Combining the indole nucleus, already validated as a "privileged structure," with the glyoxylamide function allowed for an excellent template to be obtained that is suitable to a great number of structural modifications aimed at permitting interaction with specific molecular targets and producing desirable therapeutic effects. The present review provides insight into how medicinal chemists have elegantly exploited the indolylglyoxylamide moiety to obtain potentially useful drugs, with a particular focus on compounds exhibiting activity in in vivo models or reaching clinical trials. All in all, this information provides exciting new perspectives on existing data that can be useful in further design of indolylglyoxylamide-based molecules with interesting pharmacological profiles. The aim of this report is to present an update of collection data dealing with the employment of this moiety in the rational design of compounds that are able to interact with a specific target, referring to the last 20 years.

Comparative assessment of Ca2+ oscillations in 2- and 3-dimensional hiPSC derived and isolated cortical neuronal networks

Human induced Pluripotent Stem Cell (hiPSC) derived neural cells offer great potential for modelling neurological diseases and toxicities and have found application in drug discovery and toxicology. As part of the European Innovative Medicines Initiative (IMI2) NeuroDeRisk (Neurotoxicity De-Risking in Preclinical Drug Discovery), we here explore the Ca2+ oscillation responses of 2D and 3D hiPSC derived neuronal networks of mixed Glutamatergic/GABAergic activity with a compound set encompassing both clinically as well as experimentally determined seizurogenic compounds. Both types of networks are scored against Ca2+ responses of a primary mouse cortical neuronal 2D network model serving as an established comparator assay. Parameters of frequency and amplitude of spontaneous global network Ca2+ oscillations and the drug-dependent directional changes to these were assessed, and predictivity of seizurogenicity scored using contingency table analysis. In addition, responses between models were compared between both 2D models as well as between 2D and 3D models. Concordance of parameter responses was best between the hiPSC neurospheroid and the mouse primary cortical neuron model (77% for frequency and 65% for amplitude). Decreases in spontaneous Ca2+ oscillation frequency and amplitude were found to be the most basic shared determinants of risk of seizurogenicity between the mouse and the neurospheroid model based on testing of clinical compounds with documented seizurogenic activity. Increases in spontaneous Ca2+ oscillation frequency were primarily observed with the 2D hIPSC model, though the specificity of this effect to seizurogenic clinical compounds was low (33%), while decreases to spike amplitude in this model were more predictive of seizurogenicity. Overall predictivities of the models were similar, with sensitivity of the assays typically exceeding specificity due to high false positive rates. Higher concordance of the hiPSC 3D model over the 2D model when compared to mouse cortical 2D responses may be the result of both a longer maturation time of the neurospheroid (84–87 days for 3D vs. 22–24 days for 2D maturation) as well as the 3-dimensional nature of network connections established. The simplicity and reproducibility of spontaneous Ca2+ oscillation readouts support further investigation of hiPSC derived neuronal sources and their 2- and 3-dimensional networks for neuropharmacological safety screening.

On the Current Status of Ullmann-Type N-Arylation Reactions Promoted by Heterogeneous Catalysts

Ullmann-type C–N heterocoupling reactions have been applied for the syntheses of N-arylated amines. In the past decade, transition metal-catalyzed N-arylations have been recognized as particularly efficient procedures for the preparation of nitrogen-containing aromatic systems. These reactions typically carried out under optimized conditions, have also been found to be suitable for the synthesis of complex molecules with other functional groups, including natural products, drugs, or pharmaceuticals. Most importantly, copper-catalyzed N-arylations have been studied and employed in the total synthesis of biologically active compounds. The construction of fused N-heterocyclic compounds also remained the subject of extensive research because of their potential applications in drug discovery and the development of functional materials. The aim of this review is to summarize the recent progress in the synthetic applications of Ullmann-type N-arylation reactions performed in heterogeneous systems. In particular, the utilization of copper and palladium species immobilized on various support materials, modified by surface functionalization, has been discussed and evaluated.

Human Stem Cells for Cardiac Disease Modeling and Preclinical and Clinical Applications-Are We on the Road to Success?

Cardiovascular diseases (CVDs) are pointed out by the World Health Organization (WHO) as the leading cause of death, contributing to a significant and growing global health and economic burden. Despite advancements in clinical approaches, there is a critical need for innovative cardiovascular treatments to improve patient outcomes. Therapies based on adult stem cells (ASCs) and embryonic stem cells (ESCs) have emerged as promising strategies to regenerate damaged cardiac tissue and restore cardiac function. Moreover, the generation of human induced pluripotent stem cells (iPSCs) from somatic cells has opened new avenues for disease modeling, drug discovery, and regenerative medicine applications, with fewer ethical concerns than those associated with ESCs. Herein, we provide a state-of-the-art review on the application of human pluripotent stem cells in CVD research and clinics. We describe the types and sources of stem cells that have been tested in preclinical and clinical trials for the treatment of CVDs as well as the applications of pluripotent stem-cell-derived in vitro systems to mimic disease phenotypes. How human stem-cell-based in vitro systems can overcome the limitations of current toxicological studies is also discussed. Finally, the current state of clinical trials involving stem-cell-based approaches to treat CVDs are presented, and the strengths and weaknesses are critically discussed to assess whether researchers and clinicians are getting closer to success.

Foldamer Nanotubes Mediated Label-Free Detection of Protein-Small Molecule Interactions.

Development of miniaturized lab-on-chip devices for the detection of rapid and specific small molecule-protein binding interactions at very low concentrations holds significant importance in drug discovery and biomedical applications. Here, the label-free detection of small molecule-protein interactions is reported on the surface functionalizable nanotubes of α,γ-hybrid peptide helical foldamers using nanoscale capacitance and impedance spectroscopy. The 12-helix conformation of the α,γ-hybrid peptide observed in the single crystals, self-assembled into nanotubes in an aqueous environment with exposed cysteine thiols for small molecule conjugation. The binding of streptavidin to the covalently linked biotin on the surface of nanotubes was detected at the picomolar concentrations. No change in the capacitance and impedance were observed in the absence of either immobilized biotin or protein streptavidin. The functionalizable hybrid peptide nanotubes reported here pave the way for the label-free detection of various small molecule protein interactions at very low concentrations.

DAIKON: A Data Acquisition, Integration, and Knowledge Capture Web Application for Target-Based Drug Discovery.

Primitive data organization practices struggle to deliver at the scale and consistency required to meet multidisciplinary collaborations in drug discovery. For effective data sharing and coordination, a unified platform that can collect and analyze scientific information is essential. We present DAIKON, an open-source framework that integrates targets, screens, hits, and manages projects within a target-based drug discovery portfolio. Its knowledge capture components enable teams to record subsequent molecules as their properties improve, facilitate team collaboration through discussion threads, and include modules that visually illustrate the progress of each target as it advances through the pipeline. It serves as a repository for scientists sourcing data from Mycobrowser, UniProt, PDB. The goal is to globalize several variations of the drug-discovery program without compromising local aspects of specific workflows. DAIKON is modularized by abstracting the database and creating separate layers for entities, business logic, infrastructure, APIs, and frontend, with each tier allowing for extensions. Using Docker, the framework is packaged into two solutions: daikon-server-core and daikon-client. Organizations may deploy the project to on-premises servers or VPC. Active-Directory/SSO is supported for user administration. End users can access the application with a web browser. Currently, DAIKON is implemented in the TB Drug Accelerator program (TBDA).

Phosphorus fluoride exchange: Multidimensional catalytic click chemistry from phosphorus connective hubs

Phosphorus Fluoride Exchange (PFEx) represents a cutting-edge advancement in catalytic click-reaction technology. Drawing inspiration from Nature's phosphate connectors, PFEx facilitates the reliable coupling of P(V)-F loaded hubs with aryl alcohols, alkyl alcohols, and amines to produce stable, multidimensional P(V)-O and P(V)-N linked products. The rate of P-F exchange is significantly enhanced by Lewis amine base catalysis, such as 1,5,7-triazabicyclo[4.4.0]dec-5-ene (TBD). PFEx substrates containing multiple P-F bonds are capable of selective, serial exchange reactions via judicious catalyst selection. In fewer than four synthetic steps, controlled projections can be deliberately incorporated along three of the four tetrahedral axes departing from the P(V) central hub, thus taking full advantage of the potential for generating three-dimensional diversity. Furthermore, late-stage functionalization of drugs and drug fragments can be achieved with the polyvalent PFEx hub, hexafluorocyclotriphosphazene (HFP), as has been demonstrated in prior research.

Bioprinted cancer-stromal in-vitro models in a decellularized ECM-based bioink exhibit progressive remodeling and maturation

Constant matrix remodeling and cellular heterogeneity in cancer are key contributors to its development and can profoundly alter treatment efficacy. Developing in-vitro models containing relevant features that can recapitulate these aspects of the tumor microenvironment and that are well characterized can circumvent the limitations of conventional 2D cultures and animal models. Automated fabrication methods combined with biomimetic biomaterials have provided the opportunity to create platforms that can potentially incorporate a heterogeneous population of cells in a 3D environment that allows cell–cell and cell-ECM interactions with reproducibility. This study used 3D extrusion bioprinting and a composite bioink containing a reinforced decellularized extracellular matrix (ECM) hydrogel to fabricate a head and neck cancer in-vitro model. The constituents of this model included fibroblasts and active ECM proteins to represent the stroma, along with HNSCC cells to represent the tumor component. The topographical characterization of the bioink showed a fibrous network with nanometer-sized pores. After cell encapsulation and model fabrication, we observed spheroid development and growth over time with cancer cells in the core and fibroblasts in the periphery. Our model is compatible with matrix metalloproteinase (MMP) quantification techniques and showed significant differences in the presence of MMP-9 and MMP-10 compared to the control groups. This characterized model is proposed as a tool for further translational and drug discovery applications since it provides a biomimetic scenario that allows the study of the tumor microenvironment in-vitro using nondestructive longitudinal monitoring over time.

Deciphering the Mechanistic Basis for Perfluoroalkyl-Protein Interactions.

Although rarely used in nature, fluorine has emerged as an important elemental ingredient in the design of proteins with altered folding, stability, oligomerization propensities, and bioactivity. Adding to the molecular modification toolbox, here we report the ability of privileged perfluorinated amphiphiles to noncovalently decorate proteins to alter their conformational plasticity and potentiate their dispersion into fluorous phases. Employing a complementary suite of biophysical, in-silico and in-vitro approaches, we establish structure-activity relationships defining these phenomena and investigate their impact on protein structural dynamics and intracellular trafficking. Notably, we show that the lead compound, perfluorononanoic acid, is 106 times more potent in inducing non-native protein secondary structure in select proteins than is the well-known helix inducer trifluoroethanol, and also significantly enhances the cellular uptake of complexed proteins. These findings could advance the rational design of fluorinated proteins, inform on potential modes of toxicity for perfluoroalkyl substances, and guide the development of fluorine-modified biologics with desirable functional properties for drug discovery and delivery applications.

PROTACs: A novel strategy for cancer drug discovery and development.

Proteolysis targeting chimera (PROTAC) technology has become a powerful strategy in drug discovery, especially for undruggable targets/proteins. A typical PROTAC degrader consists of three components: a small molecule that binds to a target protein, an E3 ligase ligand (consisting of an E3 ligase and its small molecule recruiter), and a chemical linker that hooks first two components together. In the past 20 years, we have witnessed advancement of multiple PROTAC degraders into the clinical trials for anticancer therapies. However, one of the major challenges of PROTAC technology is that only very limited number of E3 ligase recruiters are currently available as E3 ligand for targeted protein degradation (TPD), although human genome encodes more than 600 E3 ligases. Thus, there is an urgent need to identify additional effective E3 ligase recruiters for TPD applications. In this review, we summarized the existing RING-type E3 ubiquitin ligase and their small molecule recruiters that act as effective E3 ligands of PROTAC degraders and their application in anticancer drug discovery. We believe that this review could serve as a reference in future development of efficient E3 ligands of PROTAC technology for cancer drug discovery and development.