Small Molecule Drug Discovery Research Articles

Individual and collective human intelligence in drug design: evaluating the search strategy

In recent years, individual and collective human intelligence, defined as the knowledge, skills, reasoning and intuition of individuals and groups, have been used in combination with computer algorithms to solve complex scientific problems. Such approach was successfully used in different research fields such as: structural biology, comparative genomics, macromolecular crystallography and RNA design. Herein we describe an attempt to use a similar approach in small-molecule drug discovery, specifically to drive search strategies of de novo drug design. This is assessed with a case study that consists of a series of public experiments in which participants had to explore the huge chemical space in silico to find predefined compounds by designing molecules and analyzing the score associate with them. Such a process may be seen as an instantaneous surrogate of the classical design-make-test cycles carried out by medicinal chemists during the drug discovery hit to lead phase but not hindered by long synthesis and testing times. We present first findings on (1) assessing human intelligence in chemical space exploration, (2) comparing individual and collective human intelligence performance in this task and (3) contrasting some human and artificial intelligence achievements in de novo drug design.

Identification of Novel Potential VEGFR-2 Inhibitors Using a Combination of Computational Methods for Drug Discovery.

The vascular endothelial growth factor receptor 2 (VEGFR-2) is largely recognized as a potent therapeutic molecular target for the development of angiogenesis-related tumor treatment. Tumor growth, metastasis and multidrug resistance highly depends on the angiogenesis and drug discovery of the potential small molecules targeting VEGFR-2, with the potential anti-angiogenic activity being of high interest to anti-cancer research. Multiple small molecule inhibitors of the VEGFR-2 are approved for the treatment of different type of cancers, with one of the most recent, tivozanib, being approved by the FDA for the treatment of relapsed or refractory advanced renal cell carcinoma (RCC). However, the endogenous and acquired resistance of the protein, toxicity of compounds and wide range of side effects still remain critical issues, which lead to the short-term clinical effects and failure of antiangiogenic drugs. We applied a combination of computational methods and approaches for drug design and discovery with the goal of finding novel, potential and small molecule inhibitors of VEGFR2, as alternatives to the known inhibitors’ chemical scaffolds and components. From studying several of these compounds, the derivatives of pyrido[1,2-a]pyrimidin-4-one and isoindoline-1,3-dione in particular were identified.

Glossary and tutorial of xenobiotic metabolism terms used during small molecule drug discovery and development (IUPAC Technical Report)

Article Glossary and tutorial of xenobiotic metabolism terms used during small molecule drug discovery and development (IUPAC Technical Report) was published on October 1, 2021 in the journal Chemistry International (volume 43, issue 4).

Glioma-Targeted Therapeutics: Computer-Aided Drug Design Prospective.

Amongst the several types of brain cancers known to humankind, glioma is one of the most severe and life-threatening types of cancer, comprising 40% of all primary brain tumors. Recent reports have shown the incident rate of gliomas to be 6 per 100,000 individuals per year globally. Despite the various therapeutics used in the treatment of glioma, patient survival rate remains at a median of 15months after undergoing first-line treatment including surgery, radiation, and chemotherapy with Temozolomide. As such, the discovery of newer and more effective therapeutic agents is imperative for patient survival rate. The advent of computer-aided drug design in the development of drug discovery has emerged as a powerful means to ascertain potential hit compounds with distinctively high therapeutic effectiveness against glioma. This review encompasses the recent advances of bio-computational in-silico modeling that have elicited the discovery of small molecule inhibitors and/or drugs against various therapeutic targets in glioma. The relevant information provided in this report will assist researchers, especially in the drug design domains, to develop more effective therapeutics against this global disease.

Synthesis, biological evaluation, and in silico study of novel library sulfonates containing quinazolin-4(3H)-one derivatives as potential aldose reductase inhibitors.

A series of novel sulfonates containing quinazolin-4(3H)-one ring derivatives was designed to inhibit aldose reductase (ALR2, EC 1.1.1.21). Novel quinazolinone derivatives (1-21) were synthesized from the reaction of sulfonated aldehydes with 3-amino-2-alkylquinazolin-4(3H)-ones in glacial acetic acid with good yields (85%-94%). The structures of the novel molecules were characterized using IR, 1 H-NMR, 13 C-NMR, and HRMS. All the novel quinazolinones (1-21) demonstrated nanomolar levels of inhibitory activity against ALR2 (KI s are in the range of 101.50-2066.00 nM). Besides, 4-[(2-isopropyl-4-oxoquinazolin-3[4H]-ylimino)methyl]phenyl benzenesulfonate (15) showed higher inhibitor activity inhibited ALR2 up to 7.7-fold compared to epalrestat, a standard inhibitor. Binding interactions between ALR2 and quinazolinones have been investigated using Schrödinger Small-Molecule Drug Discovery Suite 2021-1, reported possible inhibitor-ALR2 interactions. Both in vitro and in silico study results suggest that these quinazolin-4(3H)-one ring derivatives (1-21) require further molecular modification to improve their drug nominee potency as an ALR2 inhibitor.

Protein-Protein Interactions in Translesion Synthesis.

Translesion synthesis (TLS) is an error-prone DNA damage tolerance mechanism used by actively replicating cells to copy past DNA lesions and extend the primer strand. TLS ensures that cells continue replication in the presence of damaged DNA bases, albeit at the expense of an increased mutation rate. Recent studies have demonstrated a clear role for TLS in rescuing cancer cells treated with first-line genotoxic agents by allowing them to replicate and survive in the presence of chemotherapy-induced DNA lesions. The importance of TLS in both the initial response to chemotherapy and the long-term development of acquired resistance has allowed it to emerge as an interesting target for small molecule drug discovery. Proper TLS function is a complicated process involving a heteroprotein complex that mediates multiple attachment and switching steps through several protein–protein interactions (PPIs). In this review, we briefly describe the importance of TLS in cancer and provide an in-depth analysis of key TLS PPIs, focusing on key structural features at the PPI interface while also exploring the potential druggability of each key PPI.

Protein–Small Molecule Interactions in Native Mass Spectrometry

Small molecule drug discovery has been propelled by the continual development of novel scientific methodologies to occasion therapeutic advances. Although established biophysical methods can be used to obtain information regarding the molecular mechanisms underlying drug action, these approaches are often inefficient, low throughput, and ineffective in the analysis of heterogeneous systems including dynamic oligomeric assemblies and proteins that have undergone extensive post-translational modification. Native mass spectrometry can be used to probe protein-small molecule interactions with unprecedented speed and sensitivity, providing unique insights into polydisperse biomolecular systems that are commonly encountered during the drug discovery process. In this review, we describe potential and proven applications of native MS in the study of interactions between small, drug-like molecules and proteins, including large multiprotein complexes and membrane proteins. Approaches to quantify the thermodynamic and kinetic properties of ligand binding are discussed, alongside a summary of gas-phase ion activation techniques that have been used to interrogate the structure of protein-small molecule complexes. We additionally highlight some of the key areas in modern drug design for which native mass spectrometry has elicited significant advances. Future developments and applications of native mass spectrometry in drug discovery workflows are identified, including potential pathways toward studying protein-small molecule interactions on a whole-proteome scale.

Targeting Autophagy with Natural Compounds in Cancer: A Renewed Perspective from Molecular Mechanisms to Targeted Therapy.

Natural products are well-characterized to have pharmacological or biological activities that can be of therapeutic benefits for cancer therapy, which also provide an important source of inspiration for discovery of potential novel small-molecule drugs. In the past three decades, accumulating evidence has revealed that natural products can modulate a series of key autophagic signaling pathways and display therapeutic effects in different types of human cancers. In this review, we focus on summarizing some representative natural active compounds, mainly including curcumin, resveratrol, paclitaxel, Bufalin, and Ursolic acid that may ultimately trigger cancer cell death through the regulation of some key autophagic signaling pathways, such as RAS-RAF-MEK-ERK, PI3K-AKT-mTOR, AMPK, ULK1, Beclin-1, Atg5 and p53. Taken together, these inspiring findings would shed light on exploiting more natural compounds as candidate small-molecule drugs, by targeting the crucial pathways of autophagy for the future cancer therapy.

Abstract 298: Dissection of drug-protein interactions by HR-LiP-MS in target validation and lead optimization

Abstract Background A central focus of preclinical drug discovery is the thorough characterization of lead compounds. This is a key step that helps ensure that drug candidates are worthy of clinical testing. In addition to phenotypic characterization, quantitative profiling of drug-protein interactions is a major hurdle during preclinical lead optimization. Traditionally, the gold standard technique informing structure-based drug design has been x-ray crystallography, despite the fact that under crystallization conditions protein conformation is frozen and aspects of protein structural transitions are neglected by this approach. More recently, hydrogen-deuterium exchange (HDX) has emerged as an alternative tool to profile ligand-protein interactions. While correlation of HDX-profiles with functional readouts provides valuable insights into structure-activity relations (SAR), the method itself can be laborious with extensive optimization required to generate high quality data. To address some of these shortcomings, we developed a high-throughput approach based on limited proteolysis (LiP) and next-generation quantitative mass spectrometry that enables the dissection of drug-protein interactions at peptide-level resolution. Methods To simulate the complex protein mixture obtained from cell lysis, purified recombinant proteins were spiked into a cell lysate background. Next, the mixtures were incubated with the compounds of interest. The samples were subjected to limited digestion with proteinase K and subsequently processed to peptides with trypsin for DIA-MS analysis. MS data were analyzed using a DirectDIA-workflow. Results High-Resolution Limited Proteolysis (HR-LiP) was established using calmodulin and its robust interactions with Ca2+ ions and CAMKII peptide as a model system. From here, we expanded the technique to small molecule-protein interactions of established, druggable protein targets spanning several protein classes. Herein we demonstrate that using HR-LiP we are able to identify binding sites of various compound classes on their target proteins including well characterized small molecules such as the BRD4 inhibitor JQ1. HR-LiP data are in good accordance with orthogonal HDX-MS, NMR and X-ray studies. Conclusions We demonstrate that HR-LiP can be used to dissect small molecule-protein binding characteristics with a resolution of 5-10 amino acids. Quantitative properties of the binding events are accurately recapitulated in dosage series and can therefore be deployed to rank and compare different compounds and compound classes. The ability to deal with complex backgrounds and unpurified proteins enables its application on difficult-to-purify or unstable proteins, and potentially multi-protein complexes. We envision the application of HR-LiP as a routine approach for target validation and lead optimization in small molecule drug discovery pipelines. Citation Format: Nigel Beaton, Jagat Adhikari, Yuehan Feng, Roland Bruderer, Ron Tomlinson, Ivan Cornella-Taracido, Lukas Reiter. Dissection of drug-protein interactions by HR-LiP-MS in target validation and lead optimization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 298.

Computational study on the molecular interactions of tramadol with selected antioxidant and detoxification enzymes in Drosophila melanogaster

Tramadol is a potent analgesic medication prescribed worldwide for treatment of acute and chronic pains. Its relative tendency to be abused has become a public health concern. This study was designed to evaluate the molecular interactions of tramadol with selected antioxidant and detoxification enzymes of Drosophila melanogaster. The structures of CYP2D6, catalase and defense repressor 1 were retrieved from protein database (PubMed, Swiss model) while tramadol 2D structure was obtained from PubChem repository and prepared using LigPrep scripts as implemented in Small-Molecule Drug Discovery Suite of Schrödinger. 2D structure of tramadol was docked into the protein model binding site using Glide software from Schrodinger. The result revealed that, on the binding pocket of CYP2D6, tramadol and CYP2D6 inhibitor bind the protein pocket via hydrogen bond. The hydroxyl group of tramadol and the inhibitor interacts with the C=O groups of the residues Glu 128 and Lys 264 on the protein pocket respectively. Tramadol binds with higher affinity with a docking score of -4.581 kcal/mol when compared with the inhibitor which gave a docking score of -1.865 kcal/mol. With catalase, tramadol and the crystalized ligands were observed to exhibit hydrogen bonding with Ala 64 residue on the protein binding pocket with docking score of -2.348 kcal/mol and -3.431 kcal/mol respectively. The ability of tramadol to interact with these enzymes, strongly suggests that tramadol treatment may induce oxidative stress and at high dose might result in cellular toxicity. Therefore, the toxic effects of tramadol should be of concern despite the important role it plays in pain management.

Systematically Studying the Effect of Small Molecules Interacting with RNA in Cellular and Preclinical Models.

The interrogation and manipulation of biological systems by small molecules is a powerful approach in chemical biology. Ideal compounds selectively engage a target and mediate a downstream phenotypic response. Although historically small molecule drug discovery has focused on proteins and enzymes, targeting RNA is an attractive therapeutic alternative, as many disease-causing or -associated RNAs have been identified through genome-wide association studies. As the field of RNA chemical biology emerges, the systematic evaluation of target validation and modulation of target-associated pathways is of paramount importance. In this Review, through an examination of case studies, we outline the experimental characterization, including methods and tools, to evaluate comprehensively the impact of small molecules that target RNA on cellular phenotype.

Mechanistic Model for the Prediction of Small-Molecule Vitreal Clearance Combining Diffusion-Limited and Permeability-Limited Clearance.

The discovery of new small-molecule drugs for intravitreal administration would benefit from simple models to predict vitreal clearance (CL). The current models available have limitations in their applicability to small-molecule drugs and translatability to humans. We developed a mechanistic model combining the diffusion rate of the molecule in the vitreous and permeability across posterior segment tissues and applied it to 30 small molecules with observed CL available mostly from literature. We used Caco-2 permeability as a surrogate for ocular tissue permeability. The model predicted rabbit vitreal CL well, with 80% of the predictions being within a 2-fold range of the observed CL. For an accurate prediction, it was crucial to consider the anterior diffusion CL from the vitreous to the aqueous and a limiting diffusion CL for the whole eye. We observed no major differences in model accuracy when using literature permeability values from retinal pigment epithelial cell models. Importantly, by adopting the specific dimensions of the human eye, the model was able to accurately predict vitreal CL of four compounds for which human vitreal CL data are available. In summary, this mechanistic model enables a simple, accurate, and translatable estimation of small-molecule vitreal CL.

Design concepts for DNA-encoded library synthesis

An approach of building block (BB) inclusivity and atom efficient library schemes deliver the quality and diversity of DNA-encoded libraries best suited for small molecule drug discovery. In this Perspective, we offer key learnings in DEL design from a decade’s worth of DEL-driven screening.

High-throughput Screening Technology for Selective Inhibitors of Transporters and Its Application in Drug Discovery

The first step in small-molecule drug discovery is the identification of hit compounds via high-throughput screening (HTS). In transporter drug discovery, most HTS assays are based on the uptake of labeled substrates, but such functional assays cannot be developed for many transporters, such as intracellular organelle transporters. These transporters remain unexplored in drug discovery despite their promise as drug targets. Affinity selection-mass spectrometry (AS-MS) is a label-free binding assay technology that has been developed as an HTS technology for analyzing interactions between targets and compounds. The use of AS-MS technology enables HTS against every type of drug target, in contrast to functional assays. AS-MS technology is usually used for soluble proteins, but we have developed this technology for application to membrane proteins as well. So far, we have used AS-MS for HTS of approximately 400000 compounds. In this review, the principles and application of AS-MS technology are introduced and an HTS campaign for solute carrier type 17A8 (SLC17A8) (vesicular glutamate transporter 3) is presented as an example.

Enhanced Suppression of a Protein–Protein Interaction in Cells Using Small-Molecule Covalent Inhibitors Based on an N-Acyl-N-alkyl Sulfonamide Warhead

Protein-protein interactions (PPIs) intimately govern various biological processes and disease states and therefore have been identified as attractive therapeutic targets for small-molecule drug discovery. However, the development of highly potent inhibitors for PPIs has proven to be extremely challenging with limited clinical success stories. Herein, we report irreversible inhibitors of the human double minute 2 (HDM2)/p53 PPI, which employ a reactive N-acyl-N-alkyl sulfonamide (NASA) group as a warhead. Mass-based analysis successfully revealed the kinetics of covalent inhibition and the modification sites on HDM2 to be the N-terminal α-amine and Tyr67, both rarely seen in traditional covalent inhibitors. Finally, we demonstrated prolonged p53-pathway activation and more effective induction of the p53-mediated cell death in comparison to a noncovalent inhibitor. This study highlights the potential of the NASA warhead as a versatile electrophile for the covalent inhibition of PPIs and opens new avenues for the rational design of potent covalent PPI inhibitors.

Comparison of Chemical Structure and Cell Morphology Information for Multitask Bioactivity Predictions.

The understanding of the mechanism-of-action (MoA) of compounds and the prediction of potential drug targets play an important role in small-molecule drug discovery. The aim of this work was to compare chemical and cell morphology information for bioactivity prediction. The comparison was performed using bioactivity data from the ExCAPE database, image data (in the form of CellProfiler features) from the Cell Painting data set (the largest publicly available data set of cell images with ∼30,000 compound perturbations), and extended connectivity fingerprints (ECFPs) using the multitask Bayesian matrix factorization (BMF) approach Macau. We found that the BMF Macau and random forest (RF) performance were overall similar when ECFPs were used as compound descriptors. However, BMF Macau outperformed RF in 159 out of 224 targets (71%) when image data were used as compound information. Using BMF Macau, 100 (corresponding to about 45%) and 90 (about 40%) of the 224 targets were predicted with high predictive performance (AUC > 0.8) with ECFP data and image data as side information, respectively. There were targets better predicted by image data as side information, such as β-catenin, and others better predicted by fingerprint-based side information, such as proteins belonging to the G-protein-Coupled Receptor 1 family, which could be rationalized from the underlying data distributions in each descriptor domain. In conclusion, both cell morphology changes and chemical structure information contain information about compound bioactivity, which is also partially complementary, and can hence contribute to in silico MoA analysis.

Small-Molecule Drug Discovery in Triple Negative Breast Cancer: Current Situation and Future Directions

Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, but an effective targeted therapy has not been well-established so far. Considering the lack of effective targets, where do we go next in the current TNBC drug development? A promising intervention for TNBC might lie in de novo small-molecule drugs that precisely target different molecular characteristics of TNBC. However, an ideal single-target drug discovery still faces a huge challenge. Alternatively, other new emerging strategies, such as dual-target drug, drug repurposing, and combination strategies, may provide new insight into the improvement of TNBC therapeutics. In this review, we focus on summarizing the current situation of a series of candidate small-molecule drugs in TNBC therapy, including single-target drugs, dual-target drugs, as well as drug repurposing and combination strategies that will together shed new light on the future directions targeting TNBC vulnerabilities with small-molecule drugs for future therapeutic purposes.

Enhanced validation of small-molecule ligands and carbohydrates in the Protein Data Bank

The Worldwide Protein Data Bank (wwPDB) has provided validation reports based on recommendations from community Validation Task Forces for structures in the PDB since 2013. To further enhance validation of small molecules as recommended from the 2016 Ligand Validation Workshop, wwPDB, Global Phasing Ltd., and the Noguchi Institute, recently formed a public/private partnership to incorporate some of their software tools into the wwPDB validation package. Augmented wwPDB validation report features include: two-dimensional (2D) diagrams of small-molecule ligands and carbohydrates, highlighting geometric validation outcomes; 2D topological diagrams of oligosaccharides present in branched entities generated using 2D Symbol Nomenclature for Glycan representation; and views of 3D electron density maps for ligands and carbohydrates, illustrating the goodness-of-fit between the atomic structure and experimental data (X-ray crystallographic structures only). These improvements will impact confidence in ligand conformation and ligand-macromolecular interactions that will aid in understanding biochemical function and contribute to small-molecule drug discovery.

Glossary and tutorial of xenobiotic metabolism terms used during small molecule drug discovery and development (IUPAC Technical Report)

Abstract This project originated more than 15 years ago with the intent to produce a glossary of drug metabolism terms having definitions especially applicable for use by practicing medicinal chemists. A first-draft version underwent extensive beta-testing that, fortuitously, engaged international audiences in a wide range of disciplines involved in drug discovery and development. It became clear that the inclusion of information to enhance discussions among this mix of participants would be even more valuable. The present version retains a chemical structure theme while expanding tutorial comments that aim to bridge the various perspectives that may arise during interdisciplinary communications about a given term. This glossary is intended to be educational for early stage researchers, as well as useful for investigators at various levels who participate on today’s highly multidisciplinary, collaborative small molecule drug discovery teams.

Reinforced Universal Adhesive by Ribose Crosslinker: A Novel Strategy in Adhesive Dentistry.

Enzymatic biodegradation of demineralized collagen fibrils could lead to the reduction of resin–dentin bond strength. Therefore, methods that provide protection to collagen fibrils appear to be a pragmatic solution to improve bond strength. Thus, the study’s aim was to investigate the effect of ribose (RB) on demineralized resin–dentin specimens in a modified universal adhesive. Dentin specimens were obtained, standardized and then bonded in vitro with a commercial multi-mode adhesive modified with 0, 0.5%, 1%, and 2% RB, restored with resin composite, and tested for micro-tensile bond strength (µTBS) after storage for 24 h in artificial saliva. Scanning electron microscopy (SEM) was performed to analyze resin–dentin interface. Contact angles were analyzed using a contact angle analyzer. Depth of penetration of adhesives and nanoleakage were assessed using micro-Raman spectroscopy and silver tracing. Molecular docking studies were carried out using Schrodinger small-molecule drug discovery suite 2019-4. Matrix metalloproteinases-2 (MMP-2) and cathepsin-K activities in RB-treated specimens were quantified using enzyme-linked immunosorbent assay (ELISA). The significance level was set at α = 0.05 for all statistical analyses. Incorporation of RB at 1% or 2% is of significant potential (p < 0.05) as it can be associated with improved wettability on dentin surfaces (0.5% had the lowest contact angle) as well as appreciable hybrid layer quality, and higher resin penetration. Improvement of the adhesive bond strength was shown when adding RB at 1% concentration to universal adhesive (p < 0.05). Modified adhesive increased the resistance of collagen degradation by inhibiting MMP-2 and cathepsin-K. A higher RB concentration was associated with improved results (p < 0.01). D-ribose showed favorable negative binding to collagen. In conclusion, universal adhesive using 1% or 2% RB helped in maintaining dentin collagen scaffold and proved to be successful in improving wettability, protease inhibition, and stability of demineralized dentin substrates. A more favorable substrate is created which, in turn, leads to a more stable dentin-adhesive bond. This could lead to more advantageous outcomes in a clinical scenario where a stable bond may result in longevity of the dental restoration.