Recent applications of artificial intelligence in RNA-targeted small molecule drug discovery

INTRODUCTION

Targeting RNAs with small molecules offers an alternative to the conventional protein-targeted drug discovery and can potentially address unmet and emerging medical needs. The recent rise of interest in the strategy has already resulted in large amounts of data on disease associated RNAs, as well as on small molecules that bind to such RNAs. Artificial intelligence (AI) approaches, including machine learning and deep learning, present an opportunity to speed up the discovery of RNA-targeted small molecules by improving decision-making efficiency and quality.

AREAS COVERED

The topics described in this review include the recent applications of AI in the identification of RNA targets, RNA structure determination, screening of chemical compound libraries, and hit-to-lead optimization. The impact and limitations of the recent AI applications are discussed, along with an outlook on the possible applications of next-generation AI tools for the discovery of novel RNA-targeted small molecule drugs.

EXPERT OPINION

Key areas for improvement include developing AI tools for understanding RNA dynamics and RNA - small molecule interactions. High-quality and comprehensive data still need to be generated especially on the biological activity of small molecules that target RNAs.

MolOptimizer: A Molecular Optimization Toolkit for Fragment-Based Drug Design

MolOptimizer is a user-friendly computational toolkit designed to streamline the hit-to-lead optimization process in drug discovery. MolOptimizer extracts features and trains machine learning models using a user-provided, labeled, and small-molecule dataset to accurately predict the binding values of new small molecules that share similar scaffolds with the target in focus. Hosted on the Azure web-based server, MolOptimizer emerges as a vital resource, accelerating the discovery and development of novel drug candidates with improved binding properties.

Discovery of RNA-targeted small molecules through the merging of experimental and computational technologies

INTRODUCTION

The field of RNA-targeted small molecules is rapidly evolving, owing to the advances in experimental and computational technologies. With the identification of several bioactive small molecules that target RNA, including the FDA-approved risdiplam, the biopharmaceutical industry is gaining confidence in the field. This review, based on the literature obtained from PubMed, aims to disseminate information about the various technologies developed for targeting RNA with small molecules and propose areas for improvement to develop drugs more efficiently, particularly those linked to diseases with unmet medical needs.

AREAS COVERED

The technologies for the identification of RNA targets, screening of chemical libraries against RNA, assessing the bioactivity and target engagement of the hit compounds, structure determination, and hit-to-lead optimization are reviewed. Along with the description of the technologies, their strengths, limitations, and examples of how they can impact drug discovery are provided.

EXPERT OPINION

Many existing technologies employed for protein targets have been repurposed for use in the discovery of RNA-targeted small molecules. In addition, technologies tailored for RNA targets have been developed. Nevertheless, more improvements are necessary, such as artificial intelligence to dissect important RNA structures and RNA-small-molecule interactions and more powerful chemical probing and structure prediction techniques.

Metabolism-Guided Optimization of Tryptophanol-Derived Isoindolinone p53 Activators

For the first time, the pharmacokinetic (PK) profile of tryptophanol-derived isoindolinones, previously reported as p53 activators, was investigated. From the metabolites' identification, performed by liquid chromatography coupled to high resolution tandem mass spectrometry (LC-HRMS/MS), followed by their preparation and structural elucidation, it was possible to identify that the indole C2 and C3 are the main target of the cytochrome P450 (CYP)-promoted oxidative metabolism in the tryptophanol-derived isoindolinone scaffold. Based on these findings, to search for novel p53 activators a series of 16 enantiopure tryptophanol-derived isoindolinones substituted with a bromine in indole C2 was prepared, in yields of 62-89%, and their antiproliferative activity evaluated in human colon adenocarcinoma HCT116 cell lines with and without p53. Structural optimization led to the identification of two (S)-tryptophanol-derived isoindolinones 3.9-fold and 1.9-fold more active than hit SLMP53-1, respectively. Compounds' metabolic stability evaluation revealed that this substitution led to a metabolic switch, with the impact of Phase I oxidative metabolism being minimized. Through differential scanning fluorimetry (DSF) experiments, the most active compound of the series in cell assays led to an increase in the protein melting temperature (Tm) of 10.39 °C, suggesting an effective binding to wild-type p53 core domain.

Survey on the Recent Advances in 4-Hydroxyphenylpyruvate Dioxygenase (HPPD) Inhibition by Diketone and Triketone Derivatives and Congeneric Compounds: Structural Analysis of HPPD/Inhibitor Complexes and Structure-Activity Relationship Considerations

The serendipitous discovery of the HPPD inhibitors from allelopathic plants opened the way for searching new and effective herbicidal agents by application of classical hit-to-lead optimization approaches. A plethora of active and selective compounds were discovered that belong to three major classes of cyclohexane-based triketones, pyrazole-based diketones, and diketonitriles. In addition, to enhance inhibitory constant and herbicidal activity, many efforts were also made to gain broader weed control, crop safety, and eventual agricultural applicability. Moreover, HPPD inhibitors emerged as therapeutic agents for inherited and metabolic human diseases as well as vector-selective insecticides in the control of hematophagous arthropods. Given the large set of experimental data available, structure-activity relationship analysis could be used to derive suggestions for next generation optimized compounds.

Cheminformatic Profiling and Hit Prioritization of Natural Products with Activities against Methicillin-Resistant Staphylococcus aureus (MRSA)

Several natural products (NPs) have displayed varying in vitro activities against methicillin-resistant Staphylococcus aureus (MRSA). However, few of these compounds have not been developed into potential antimicrobial drug candidates. This may be due to the high cost and tedious and time-consuming process of conducting the necessary preclinical tests on these compounds. In this study, cheminformatic profiling was performed on 111 anti-MRSA NPs (AMNPs), using a few orally administered conventional drugs for MRSA (CDs) as reference, to identify compounds with prospects to become drug candidates. This was followed by prioritizing these hits and identifying the liabilities among the AMNPs for possible optimization. Cheminformatic profiling revealed that most of the AMNPs were within the required drug-like region of the investigated properties. For example, more than 76% of the AMNPs showed compliance with the Lipinski, Veber, and Egan predictive rules for oral absorption and permeability. About 34% of the AMNPs showed the prospect to penetrate the blood–brain barrier (BBB), an advantage over the CDs, which are generally non-permeant of BBB. The analysis of toxicity revealed that 59% of the AMNPs might have negligible or no toxicity risks. Structure–activity relationship (SAR) analysis revealed chemical groups that may be determinants of the reported bioactivity of the compounds. A hit prioritization strategy using a novel “desirability scoring function” was able to identify AMNPs with the desired drug-likeness. Hit optimization strategies implemented on AMNPs with poor desirability scores led to the design of two compounds with improved desirability scores.

Discovery and optimizing polycyclic pyridone compounds as anti-HBV agents

INTRODUCTION

Hepatitis B disease is caused by the hepatitis B virus (HBV), which is a DNA virus that belongs to the Hepadnaviridae family. It is a considerable health burden, with 257 million active cases globally. Long-standing infection may create a fundamental cause of liver disease and chronic infections, including cirrhosis, hepatocellular, and carcinoma liver failure. There is an urgent need to develop novel, safe, and effective drug candidates with a novel mechanism of action, improved activity, efficacy, and cure rate.

AREAS COVERED

Herein, the authors provide a concise report focusing on a general and cutting-edge overview of the current state of polycyclic pyridone-related anti-HBV agent patents from 2016 to 2018 and some future perspectives.

EXPERT OPINION

In medicinal chemistry, high-throughput screening (HTS), hit-to-lead optimization (H2L), bioisosteric replacement, and scaffold hopping approaches are playing a major role in the discovery and development of HBV inhibitors. Developing polycyclic pyridone-related anti-HBV agents that could target host factors has attracted significant interest and attention in recent years.

Current insights into anti-HIV drug discovery and development: a review of recent patent literature (2014-2017)

INTRODUCTION

To deal with the rapid emergence of drug resistance challenges, together with the difficulty to eradicate the virus, off-target effects and significant cumulative drug toxicities, it is still imperative to develop next-generation anti-HIV agents with novel chemical classes or new mechanisms of action.

AREAS COVERED

We primarily focused on current strategies to discover novel anti-HIV agents. Moreover, examples of anti-HIV lead compounds were mainly selected from recently patented publications (reported between 2014 and 2017). In particular, 'privileged structure'-focused substituents decorating approach, scaffold hopping, natural-product diversification and prodrug are focused on. Furthermore, exploitation of new compounds with unexplored mechanisms of action and medicinal chemistry strategies to deplete the HIV reservoir were also described. Perspectives that could inspire future anti-HIV drug discovery are delineated.

EXPERT OPINION

Even if a large number of patents have been disclosed recently, additional HIV inhibitors are still required, especially novel chemical skeletons displaying a unexploited mechanism of action. Current medicinal chemistry strategies are inadequate, and appropriate and new methodologies and technologies should be exploited to identify novel anti-HIV drug candidates in a time- and cost- effective manner.

1-Benzyl-3-aryl-2-thiohydantoin Derivatives as New Anti-Trypanosoma brucei Agents: SAR and in Vivo Efficacy

A high throughput screening and subsequent hit validation identified compound 1 as an inhibitor of Trypanosoma brucei parasite growth. Extensive structure–activity relationship optimization based on antiparasitic activity led to the highly potent compounds, 1-(4-fluorobenzyl)-3-(4-dimethylamino-3-chlorophenyl)-2-thiohydantoin (68) and 1-(2-chloro-4-fluorobenzyl)-3-(4-dimethylamino-3-methoxyphenyl)-2-thiohydantoin (76), with a T. brucei EC₅₀ of 3 and 2 nM, respectively. This represents >100-fold improvement in potency compared to compound 1. In vivo efficacy experiments of 68 and 76 in an acute mouse model of Human African Trypanosomiasis showed a 100% cure rate after 4 days of oral treatment at 50 mg/kg twice per day.

Discovery of Novel Succinate Dehydrogenase Inhibitors by the Integration of in Silico Library Design and Pharmacophore Mapping

Succinate dehydrogenase (SDH) has been demonstrated as a promising target for fungicide discovery. Crystal structure data have indicated that the carboxyl "core" of current SDH inhibitors contributed largely to their binding affinity. Thus, identifying novel carboxyl "core" SDH inhibitors would remarkably improve the biological potency of current SDHI fungicides. Herein, we report the discovery and optimization of novel carboxyl scaffold SDH inhibitor via the integration of in silico library design and a highly specific amide feature-based pharmacophore model. To our delight, a promising SDH inhibitor, A16c (IC₅₀ = 1.07 μM), with a novel pyrazol-benzoic scaffold was identified, which displayed excellent activity against Rhizoctonia solani (EC₅₀ = 11.0 μM) and improved potency against Sclerotinia sclerotiorum (EC₅₀ = 5.5 μM) and Phyricularia grisea (EC₅₀ = 12.0 μM) in comparison with the positive control thifluzamide, with EC₅₀ values of 0.09, 33.2, and 33.4 μM, respectively. The results showed that our virtual screening strategy could serve as a powerful tool to accelerate the discovery of novel SDH inhibitors.

Discovery of ONO-7300243 from a Novel Class of Lysophosphatidic Acid Receptor 1 Antagonists: From Hit to Lead

Lysophosphatidic acid (LPA) evokes various physiological responses through a series of G protein-coupled receptors known as LPA_1-6. A high throughput screen against LPA₁ gave compound 7a as a hit. The subsequent optimization of 7a led to ONO-7300243 (17a) as a novel, potent LPA₁ antagonist, which showed good efficacy in vivo. The oral dosing of 17a at 30 mg/kg led to reduced intraurethral pressure in rats. Notably, this compound was equal in potency to the α₁ adrenoceptor antagonist tamsulosin, which is used in clinical practice to treat dysuria with benign prostatic hyperplasia (BPH). In contrast to tamsulosin, compound 17a had no impact on the mean blood pressure at this dose. These results suggest that LPA₁ antagonists could be used to treat BPH without affecting the blood pressure. Herein, we report the hit-to-lead optimization of a unique series of LPA₁ antagonists and their in vivo efficacy.