Going Viral: An Investigation into the Chameleonic Behaviour of Antiviral Compounds.

The ability to adjust conformations in response to the polarity of the environment, i.e. molecular chameleonicity, is considered to be important for conferring both high aqueous solubility and high cell permeability to drugs in chemical space beyond Lipinski's rule of 5. We determined the conformational ensembles populated by the antiviral drugs asunaprevir, simeprevir, atazanavir and daclatasvir in polar (DMSO-d6 ) and non-polar (chloroform) environments with NMR spectroscopy. Daclatasvir was fairly rigid, whereas the first three showed large flexibility in both environments, that translated into major differences in solvent accessible 3D polar surface area within each conformational ensemble. No significant differences in size and polar surface area were observed between the DMSO-d6 and chloroform ensembles of these three drugs. We propose that such flexible compounds are characterized as "partial molecular chameleons" and hypothesize that their ability to adopt conformations with low polar surface area contributes to their membrane permeability and oral absorption.

Simulation Reveals the Chameleonic Behavior of Macrocycles.

Conformational analysis is central to the design of bioactive molecules. It is particularly challenging for macrocycles due to noncovalent transannular interactions, steric interactions, and ring strain that are often coupled. Herein, we simulated the conformations of five macrocycles designed to express a progression of increasing complexity in environment-dependent intramolecular interactions and verified the results against NMR measurements in chloroform and dimethyl sulfoxide. Molecular dynamics using an explicit solvent model, but not the Monte Carlo method with implicit solvation, handled both solvents correctly. Refinement of conformations at the ab initio level was fundamental to reproducing the experimental observations─standard state-of-the-art molecular mechanics force fields were insufficient. Our simulations correctly predicted the intramolecular interactions between side chains and the macrocycle and revealed an unprecedented solvent-induced conformational switch of the macrocyclic ring. Our results provide a platform for the rational, prospective design of molecular chameleons that adapt to the properties of the environment.

Search, Identification, and Design of Effective Antiviral Drugs Against Pandemic Human Coronaviruses.

Recent coronavirus outbreaks of SARS-CoV-1 (2002-2003), MERS-CoV (since 2012), and SARS-CoV-2 (since the end of 2019) are examples of how viruses can damage health care and generate havoc all over the world. Coronavirus can spread quickly from person to person causing high morbidity and mortality. Unfortunately, the antiviral armamentarium is insufficient to fight these infections. In this chapter, we provide a detailed summary of the current situation in the development of drugs directed against pandemic human coronaviruses. Apart from the recently licensed remdesivir, other antiviral agents discussed in this review include molecules targeting viral components (e.g., RNA polymerase inhibitors, entry inhibitors, or protease inhibitors), compounds interfering with virus-host interactions, and drugs identified in large screening assays, effective against coronavirus replication, but with an uncertain mechanism of action.

Drug Syntheses Beyond the Rule of 5.

Drugs in the chemical space beyond the rule of 5 (bRo5) can modulate targets with difficult binding sites while retaining cell permeability and oral absorption. Reviewing the syntheses of bRo5 drugs approved since 1990 highlights synthetic chemistry's contribution to drug discovery in this space. Initially, bRo5 drugs were mainly natural products and semi-synthetic derivatives. Later, peptidomimetics and de novo designed compounds, that include up to seven chiral centres and macrocyclic rings became dominant. These drugs are prepared by total synthesis, sometimes by routes of more than 25 steps with stereocentres originating from the chiral pool, or being installed by chiral induction or enzymatic resolution. Interestingly, ring-closing metathesis proved to be the method of choice for macrocyclisation in hepatitis C virus protease inhibitors. We conclude that structural simplification, planning of synthetic routes regarding incorporation of stereocentres and macrocyclisation, as well as incorporation of structural knowledge and consideration of chameleonic properties in design, should facilitate drug discovery in bRo5 space.

Solution Conformations Explain the Chameleonic Behaviour of Macrocyclic Drugs.

It has been hypothesised that drugs in the chemical space "beyond the rule of 5" (bRo5) must behave as molecular chameleons to combine otherwise conflicting properties, including aqueous solubility, cell permeability and target binding. Evidence for this has, however, been limited to the cyclic peptide cyclosporine A. Herein, we show that the non-peptidic and macrocyclic drugs roxithromycin, telithromycin and spiramycin behave as molecular chameleons, with rifampicin showing a less pronounced behaviour. In particular roxithromycin, telithromycin and spiramycin display a marked, yet limited flexibility and populate significantly less polar and more compact conformational ensembles in an apolar than in a polar environment. In addition to balancing of membrane permeability and aqueous solubility, this flexibility also allows binding to targets that vary in structure between species. The drugs' passive cell permeability correlates to their 3D polar surface area and corroborate two theoretical models for permeability, developed for cyclic peptides. We conclude that molecular chameleonicity should be incorporated in the design of orally administered drugs in the bRo5 space.

Molecular design opportunities presented by solvent-exposed regions of target proteins.

Solvent-exposed regions, or solvent-filled pockets, within or adjacent to the ligand-binding sites of drug-target proteins provide opportunities for substantial modifications of existing small-molecular drug molecules without serious loss of activity. In this review, we present recent selected examples of exploitation of solvent-exposed regions of proteins in drug design and development from the recent medicinal-chemistry literature.

Development of an Efficient G-Quadruplex-Stabilised Thrombin-Binding Aptamer Containing a Three-Carbon Spacer Molecule.

The thrombin-binding aptamer (TBA), which shows anticoagulant properties, is one of the most studied G-quadruplex-forming aptamers. In this study, we investigated the impact of different chemical modifications such as a three-carbon spacer (spacer-C3 ), unlocked nucleic acid (UNA) and 3'-amino-modified UNA (amino-UNA) on the structural dynamics and stability of TBA. All three modifications were incorporated at three different loop positions (T3, T7, T12) of the TBA G-quadruplex structure to result in a series of TBA variants and their stability was studied by thermal denaturation; folding was studied by circular dichroism spectroscopy and thrombin clotting time. The results showed that spacer-C3 introduction at the T7 loop position (TBA-SP7) significantly improved stability and thrombin clotting time while maintaining a similar binding affinity as TBA to thrombin. Detailed molecular modelling experiments provided novel insights into the experimental observations, further supporting the efficacy of TBA-SP7. The results of this study could provide valuable information for future designs of TBA analogues with superior thrombin inhibition properties.

Computational Analysis of Sterol Ligand Specificity of the Niemann Pick C2 Protein.

Transport of cholesterol derived from hydrolysis of lipoprotein associated cholesteryl esters out of late endosomes depends critically on the function of the Niemann Pick C1 (NPC1) and C2 (NPC2) proteins. Both proteins bind cholesterol but also various other sterols and both with strongly varying affinity. The molecular mechanisms underlying this multiligand specificity are not known. On the basis of the crystal structure of NPC2, we have here investigated structural details of NPC2-sterol interactions using molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. We found that an aliphatic side chain in the sterol ligand results in strong binding to NPC2, while side-chain oxidized sterols gave weaker binding. Estradiol and the hydrophobic amine U18666A had the lowest affinity of all tested ligands and at the same time showed the highest flexibility within the NPC2 binding pocket. The binding affinity of all ligands correlated highly with their calculated partitioning coefficient (logP) between octanol/water phases and with the potential of sterols to stabilize the protein backbone. From molecular dynamics simulations, we suggest a general mechanism for NPC2 mediated sterol transfer, in which Phe66, Val96, and Tyr100 act as reversible gate keepers. These residues stabilize the sterol in the binding pose via π-π stacking but move transiently apart during sterol release. A computational mutation analysis revealed that the binding of various ligands depends critically on the same specific amino acid residues within the binding pocket providing shape complementary to sterols, but also on residues in distal regions of the protein.

Synthesis, biological evaluation and molecular modelling studies of 4-anilinoquinazoline derivatives as protein kinase inhibitors.

A series of novel 4-anilinoquinazoline derivatives (3a-3j) has been synthesized and evaluated as potential inhibitors for protein kinases implicated in Alzheimer's disease. Among all the synthesized compounds, compound 3e (N-(3,4-dimethoxyphenyl)-6,7-dimethoxyquinazolin-4-amine) exhibited the most potent inhibitory activity against CLK1 and GSK-3α/ß kinase with IC50 values of 1.5 µM and 3 µM, respectively. Docking studies were performed to elucidate the binding mode of the compounds to the active site of CLK1 and GSK-3ß. The results of our study suggest that compound 3e may serve as a valuable template for the design and development of dual inhibitors of CLK1 and GSK-3α/ß enzymes with potential therapeutic application in Alzheimer's disease.

Molecular chameleons in drug discovery.

Molecular chameleons possess a flexibility that allows them to dynamically shield or expose polar functionalities in response to the properties of the environment. Although the concept of molecular chameleons was introduced already in 1970, interest in them has grown considerably since the 2010s, when drug discovery has focused to an increased extent on new chemical modalities. Such modalities include cyclic peptides, macrocycles and proteolysis-targeting chimeras, all of which reside in a chemical space far from that of traditional small-molecule drugs. Both cell permeability and aqueous solubility are required for the oral absorption of drugs. Engineering these properties, and potent target binding, into the larger new modalities is a more daunting task than for traditional small-molecule drugs. The ability of chameleons to adapt to different environments may be essential for success. In this Review, we provide both general and theoretical insights into the realm of molecular chameleons. We discuss why chameleons have come into fashion and provide a do-it-yourself toolbox for their design; we then provide a glimpse of how advanced in silico methods can support molecular chameleon design.

Exploring the chemical space of orally bioavailable PROTACs.

A principal challenge in the discovery of proteolysis targeting chimeras (PROTACs) as oral medications is their bioavailability. To facilitate drug design, it is therefore essential to identify the chemical space where orally bioavailable PROTACs are more likely to be situated. To this aim, we extracted structure-bioavailability insights from published data using traditional 2D descriptors, thereby shedding light on their potential and limitations as drug design tools. Subsequently, we describe cutting-edge experimental, computational and hybrid design strategies based on 3D descriptors, which show promise for enhancing the probability of discovering PROTACs with high oral bioavailability.

Hydrophobic tagging of small molecules: an overview of the literature and future outlook.

INTRODUCTION: Hydrophobic tagging (HyT) technology presents a distinct therapeutic strategy diverging from conventional small molecule drugs, providing an innovative approach to drug design. This review aims to provide an overview of the HyT literature and future outlook to offer guidance for drug design. AREAS COVERED: In this review, the authors introduce the composition, mechanisms and advantages of HyT technology, as well as summarize the detailed applications of HyT technology in anti-cancer, neurodegenerative diseases (NDs), autoimmune disorders, cardiovascular diseases (CVDs), and other fields. Furthermore, this review discusses key aspects of the future development of HyT molecules. EXPERT OPINION: HyT emerges as a highly promising targeted protein degradation (TPD) strategy, following the successful development of proteolysis targeting chimeras (PROTAC) and molecular glue. Based on exploring new avenues, modification of the HyT molecule itself potentially enhances the technology. Improved synthetic pathways and emphasis on pharmacokinetic (PK) properties will facilitate the development of HyT. Furthermore, elucidating the biochemical basis by which the compound's hydrophobic moiety recruits the protein homeostasis network will enable the development of more precise assays that can guide the optimization of the linker and hydrophobic moiety.

Macrocycles in Drug Discovery─Learning from the Past for the Future.

We have analyzed FDA-approved macrocyclic drugs, clinical candidates, and the recent literature to understand how macrocycles are used in drug discovery. Current drugs are mainly used in infectious disease and oncology, while oncology is the major indication for the clinical candidates and in the literature Most macrocyclic drugs bind to targets that have difficult to drug binding sites. Natural products have provided 80-90% of the drugs and clinical candidates, whereas macrocycles in ChEMBL have less complex structures. Macrocycles usually reside in the beyond the Rule of 5 chemical space, but 30-40% of the drugs and clinical candidates are orally bioavailable. Simple bi-descriptor models, i.e., HBD ≤ 7 in combination with either MW < 1000 Da or cLogP > 2.5, distinguished orals from parenterals and can be used as filters in design. We propose that recent breakthroughs in conformational analysis and inspiration from natural products will further improve the de novo design of macrocycles.

Predictive Modeling of PROTAC Cell Permeability with Machine Learning.

Approaches for predicting proteolysis targeting chimera (PROTAC) cell permeability are of major interest to reduce resource-demanding synthesis and testing of low-permeable PROTACs. We report a comprehensive investigation of the scope and limitations of machine learning-based binary classification models developed using 17 simple descriptors for large and structurally diverse sets of cereblon (CRBN) and von Hippel-Lindau (VHL) PROTACs. For the VHL PROTAC set, kappa nearest neighbor and random forest models performed best and predicted the permeability of a blinded test set with >80% accuracy (k ≥ 0.57). Models retrained by combining the original training and the blinded test set performed equally well for a second blinded VHL set. However, models for CRBN PROTACs were less successful, mainly due to the imbalanced nature of the CRBN datasets. All descriptors contributed to the models, but size and lipophilicity were the most important. We conclude that properly trained machine learning models can be integrated as effective filters in the PROTAC design process.

Targeting hepatitis B virus cccDNA levels: Recent progress in seeking small molecule drug candidates.

Hepatitis B virus (HBV) infection is a major global health problem that puts people at high risk of death from cirrhosis and liver cancer. The presence of covalently closed circular DNA (cccDNA) in infected cells is considered to be the main obstacle to curing chronic hepatitis B. At present, the cccDNA cannot be completely eliminated by standard treatments. There is an urgent need to develop drugs or therapies that can reduce HBV cccDNA levels in infected cells. We summarize the discovery and optimization of small molecules that target cccDNA synthesis and degradation. These compounds are cccDNA synthesis inhibitors, cccDNA reducers, core protein allosteric modulators, ribonuclease H inhibitors, cccDNA transcriptional modulators, HBx inhibitors and other small molecules that reduce cccDNA levels.

Fingerprint-based in silico models for the prediction of P-glycoprotein substrates and inhibitors.

P-Glycoprotein (P-gp, ABCB1) plays a significant role in determining the ADMET properties of drugs and drug candidates. Substrates of P-gp are not only subject to multidrug resistance (MDR) in tumor therapy, they are also associated with poor pharmacokinetic profiles. In contrast, inhibitors of P-gp have been advocated as modulators of MDR. However, due to the polyspecificity of P-gp, knowledge on the molecular basis of ligand-transporter interaction is still poor, which renders the prediction of whether a compound is a P-gp substrate/non-substrate or an inhibitor/non-inhibitor quite challenging. In the present investigation, we used a set of fingerprints representing the presence/absence of various functional groups for machine learning based classification of a set of 484 substrates/non-substrates and a set of 1935 inhibitors/non-inhibitors. Best models were obtained using a combination of a wrapper subset evaluator (WSE) with random forest (RF), kappa nearest neighbor (kNN) and support vector machine (SVM), showing accuracies >70%. Best P-gp substrate models were further validated with three sets of external P-gp substrate sources, which include Drug Bank (n = 134), TP Search (n = 90) and a set compiled from literature (n = 76). Association rule analysis explores the various structural feature requirements for P-gp substrates and inhibitors.

Enhancing preclinical drug discovery with artificial intelligence.

Artificial intelligence (AI) is becoming an integral part of drug discovery. It has the potential to deliver across the drug discovery and development value chain, starting from target identification and reaching through clinical development. In this review, we provide an overview of current AI technologies and a glimpse of how AI is reimagining preclinical drug discovery by highlighting examples where AI has made a real impact. Considering the excitement and hyperbole surrounding AI in drug discovery, we aim to present a realistic view by discussing both opportunities and challenges in adopting AI in drug discovery.

Linker-Dependent Folding Rationalizes PROTAC Cell Permeability.

Proteolysis-targeting chimeras (PROTACs) must be cell permeable to reach their target proteins. This is challenging as the bivalent structure of PROTACs puts them in chemical space at, or beyond, the outer limits of oral druggable space. We used NMR spectroscopy and molecular dynamics (MD) simulations independently to gain insights into the origin of the differences in cell permeability displayed by three flexible cereblon PROTACs having closely related structures. Both methods revealed that the propensity of the PROTACs to adopt folded conformations with a low solvent-accessible 3D polar surface area in an apolar environment is correlated to high cell permeability. The chemical nature and the flexibility of the linker were essential for the PROTACs to populate folded conformations stabilized by intramolecular hydrogen bonds, π-π interactions, and van der Waals interactions. We conclude that MD simulations may be used for the prospective ranking of cell permeability in the design of cereblon PROTACs.

Cell Permeability of Isomeric Macrocycles: Predictions and NMR Studies.

Conformation-dependent 3D descriptors have been shown to provide better predictions of the physicochemical properties of macrocycles than 2D descriptors. However, the computational identification of relevant conformations for macrocycles is nontrivial. Herein, we report that the Caco-2 cell permeability difference between a pair of diastereomeric macrocycles correlated with their solvent accessible 3D polar surface area and radius of gyration. The descriptors were calculated from the macrocycles' solution-phase conformational ensembles and independently from ensembles obtained by conformational sampling. Calculation of the two descriptors for three other stereo- and regioisomeric macrocycles also allowed the correct ranking of their cell permeability. Methods for conformational sampling may thus allow ranking of passive permeability for moderately flexible macrocycles, thereby contributing to the prioritization of macrocycles for synthesis in lead optimization.

Steering New Drug Discovery Campaigns: Permeability, Solubility, and Physicochemical Properties in the bRo5 Chemical Space.

An increasing number of drug discovery programs concern compounds in the beyond rule of 5 (bRo5) chemical space, such as cyclic peptides, macrocycles, and degraders. Recent results show that common paradigms of property-based drug design need revision to be applied to larger and more flexible compounds. A virtual event entitled "Solubility, permeability and physico-chemical properties in the bRo5 chemical space" was organized to provide preliminary guidance on how to make the discovery of oral drugs in the bRo5 space more effective. The four speakers emphasized the importance of the bRo5 space as a source of new oral drugs and provided examples of experimental and computational methods specifically tailored for design and optimization in this chemical space.