Differential Water Thermodynamics Determine PI3K-Beta/Delta Selectivity for Solvent-Exposed Ligand Modifications

Discovery and optimization of narrow spectrum inhibitors of Tousled like kinase 2 (TLK2) using quantitative structure activity relationships

The oxindole scaffold has been the center of several kinase drug discovery programs, some of which have led to approved medicines. A series of two oxindole matched pairs from the literature were identified where TLK2 was potently inhibited as an off-target kinase. The oxindole has long been considered a promiscuous kinase inhibitor template, but across these four specific literature oxindoles TLK2 activity was consistent, while the kinome profile was radically different ranging from narrow to broad spectrum kinome coverage. We synthesized a large series of analogues, utilizing quantitative structure-activity relationship (QSAR) analysis, water mapping of the kinase ATP binding sites, kinome profiling, and small-molecule x-ray structural analysis to optimize TLK2 inhibition and kinome selectivity. This resulted in the identification of several narrow spectrum, sub-family selective, chemical tool compounds including 128 (UNC-CA2-103) that could enable elucidation of TLK2 biology.

The application of WaterMap-guided structure-based virtual screening in novel drug discovery

INTRODUCTION

Nowadays, it is widely accepted that water molecules play a key role in binding a ligand to a molecular target. Neglecting water molecules in the process of molecular recognition was the result of several failures of the structure-based drug discovery campaigns. The application of WaterMap, in particular WaterMap-guided molecular docking, enables the reasonably accurate and quick description of the location and energetics of water molecules at the ligand-protein interface.

AREAS COVERED

In this review, the authors shortly discuss the importance of water in drug design and discovery and provide a brief overview of the computational approaches used to predict the solvent-related effects for the purposes of presenting WaterMap in the context of other available techniques and tools. A concise description of WaterMap concept is followed by the presentation of WaterMap-assisted virtual screening literature published between 2013 and 2023.

EXPERT OPINION

In recent years, WaterMap software has been extensively used to support structure-based drug design, in particular structure-based virtual screening. Indeed, it is a useful tool to rescore docking results considering water molecules in the binding pocket. Although WaterMap allows for the consideration of the dynamic behavior of water molecules in the binding site, for best accuracy, its application in conjunction with other techniques such as molecular mechanics-generalized Born surface area of FEP (Free Energy Perturbation) is recommended.

Turning down PI3K/AKT/mTOR signalling pathway by natural products: an in silico multi-target approach

The PI3K/AKT/mTOR pathway is a significant target for cancer drug discovery. Many efforts have focused on discovering new inhibitors against key kinase proteins involved in this pathway for cancer treatment. PI3K/mTOR dual inhibitors, such as PKI-179, have been reported to be more effective than agents that act only on a single protein target. The present computational study aimed to discover triple target inhibitors against PI3K, AKT, and mTOR proteins. Accordingly, the PI3K protein bound with the ligand was used as input for e-pharmacophore modelling to generate the pharmacophore hypothesis and then screened for a library of 270,540 natural products from the Zinc database resulting in 57,220 compounds that matched the hypothesis. These compounds were then docked into the active site of PI3K, resulting in 292 compounds with better docking scores than the co-crystallized ligand. These compounds were re-docked into AKT and mTOR proteins. Besides, MM-GBSA binding free energy calculations, MD simulations, and ADMET prediction were carried out, leading to 5 potential triple-target inhibitors namely, ZINC000014644152, ZINC000014760695, ZINC000014644839, ZINC000095099451, and ZINC000005998557. In conclusion, these inhibitors may be possible leads for inhibiting PI3K/AKT/mTOR pathway, and they may be further evaluated in vitro and clinically as anticancer agents.

Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization

Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying “magic bullets” amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand–target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural–energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.

Addressing a Trapped High-Energy Water: Design and Synthesis of Highly Potent Pyrimidoindole-Based Glycogen Synthase Kinase-3β Inhibitors

In small molecule binding, water is not a passive bystander but rather takes an active role in the binding site, which may be decisive for the potency of the inhibitor. Here, by addressing a high-energy water, we improved the IC₅₀ value of our co-crystallized glycogen synthase kinase-3β (GSK-3β) inhibitor by nearly two orders of magnitude. Surprisingly, our results demonstrate that this high-energy water was not displaced by our potent inhibitor (S)-3-(3-((7-ethynyl-9H-pyrimido[4,5-b]indol-4-yl)(methyl)amino)piperidin-1-yl)propanenitrile ((S)-15, IC₅₀ value of 6 nM). Instead, only a subtle shift in the location of this water molecule resulted in a dramatic decrease in the energy of this high-energy hydration site, as shown by the WaterMap analysis combined with microsecond timescale molecular dynamics simulations. (S)-15 demonstrated both a favorable kinome selectivity profile and target engagement in a cellular environment and reduced GSK-3 autophosphorylation in neuronal SH-SY5Y cells. Overall, our findings highlight that even a slight adjustment in the location of a high-energy water can be decisive for ligand binding.

Phosphatidylinositol 3-kinase (PI3K) inhibitors: a recent update on inhibitor design and clinical trials (2016-2020)

Introduction: The phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway plays a central role in regulating cell growth and proliferation and thus has been considered as effective anticancer drug targets. Many PI3K inhibitors have been developed and progressed to various stages of clinical trials, and some have been approved as anticancer treatment. In this review, we discuss the drug design and clinical development of PI3K inhibitors over the past 4 years. We review the selectivity and potency of 47 PI3K inhibitors. Structural determinants for increasing selectivity toward PI3K subtype-selectivity or mutant selectivity are discussed. Future research direction and current clinical development in combination therapy of inhibitors involved in PI3Ks are also discussed.Area covered: This review covers clinical trial reports and patent literature on PI3K inhibitors and their selectivity published between 2016 and 2020.Expert opinion: To PI3Kα mutants (E542K, E545K, and H1047R), it is highly desirable to design and develop mutant-specific PI3K inhibitors. It is also necessary to develop subtype-selective PI3Kα inhibitors to minimize toxicity. To reduce drug resistance and to improve efficacy, future studies should include combination therapy of PI3K inhibitors with existing anticancer drugs from different pathways.

Current and Future Challenges in Modern Drug Discovery

Drug discovery is an expensive, time-consuming, and risky business. To avoid late-stage failure, learnings from past projects and the development of new approaches are crucial. New modalities and emerging new target spaces allow the exploration of unprecedented indications or to address so far undrugable targets. Late-stage attrition is usually attributed to the lack of efficacy or to compound-related safety issues. Efficacy has been shown to be related to a strong genetic link to human disease, a better understanding of the target biology, and the availability of biomarkers to bridge from animals to humans. Compound safety can be improved by ligand optimization, which is becoming increasingly demanding for difficult targets. Therefore, new strategies include the design of allosteric ligands, covalent binders, and other modalities. Design methods currently heavily rely on artificial intelligence and advanced computational methods such as free energy calculations and quantum chemistry. Especially for quantum chemical methods, a more detailed overview is given in this chapter.

Design, synthesis, in silico and in vitro evaluation of novel diphenyl ether derivatives as potential antitubercular agents

Diphenyl ether derivatives inhibit mycobacterial cell wall synthesis by inhibiting an enzyme, enoyl-acyl carrier protein reductase (InhA), which catalyses the last step in the fatty acid synthesis cycle of genus Mycobacterium. To select and validate a protein crystal structure of enoyl-acyl carrier protein reductase of Mycobacterium tuberculosis for designing inhibitors using molecular modelling, a cross-docking and correlation study was performed. A series of novel 1-(3-(3-hydroxy-4-phenoxyphenyl)-5-phenyl-4,5-dihydro-1H-pyrazol-1-yl) ethan-1-ones were synthesized from this model and screened for their antitubercular activity against M. tuberculosis H37Rv. Compound PYN-8 showed good antitubercular activity on M. tuberculosis H37Rv (MIC = 4-7 µM) and Mycobacterium bovis (% inhibition at 10 µM = 95.91%). Cytotoxicity of all the synthesized derivatives was assessed using various cell lines, and they were found to be safe. Structure of PYN-8 was also confirmed by single-crystal X-ray diffraction. The molecular modelling studies also corroborated the biological activity of the compounds. Further, in silico findings revealed that all these tested compounds exhibited good ADME properties and drug likeness and thus may be considered as potential candidates for further drug development.

Hybrid Molecular Dynamics for Elucidating Cooperativity Between Halogen Bond and Water Molecules During the Interaction of p53-Y220C and the PhiKan5196 Complex

The cooperativity between hydrogen and halogen bonds plays an important role in rational drug design. However, mimicking the dynamic cooperation between these bonds is a challenging issue, which has impeded the development of the halogen bond force field. In this study, the Y220C–PhiKan5196 complex of p53 protein was adopted as a model, and the functions of three water molecules that formed hydrogen bonds with halogen atoms were analyzed by the simulation method governed by the hybrid quantum mechanical/molecular mechanical molecular dynamics. A comparison with the water-free model revealed that the strength of the halogen bond in the complex was consistently stronger. This confirmed that the water molecules formed weak hydrogen bonds with the halogen atom and cooperated with the halogen atom to enhance the halogen bond. Further, it was discovered that the roles of the three water molecules were not the same. Therefore, the results obtained herein can facilitate a rational drug design. Further, this work emphasizes on the fact that, in addition to protein pockets and ligands, the role of voids should also be considered with regard to the water molecules surrounding them.

Regioselective/electro-oxidative intermolecular [3 + 2] annulation for the preparation of indolines

Compared with the reported intramolecular electro-oxidative cyclization of alkenyl amines or vinyl anilines for the preparation of pyrrolidines or indolines, the intermolecular version is less studied. Herein, this electrochemical intermolecular oxidative annulation of anilines and alkenes for the preparation of indolines proceeded under external oxidant-free conditions. The most noteworthy achievement of our work is the facile generation of indolines with quaternary centers at the 2-position. In addition, alkenes and anilines bearing various functional groups can be well tolerated. Remarkably, electrolyte-free conditions were used in an electrochemical flow cell, which shows the application potential of this method.

Utilizing Grand Canonical Monte Carlo Methods in Drug Discovery

The concepts behind targeting waters for potency and selectivity gains have been well documented and explored, although maximizing such potential gains can prove to be challenging. This problem is exacerbated in cases where there are multiple interacting waters, wherein perturbation of one water can affect the free energy landscape of the remaining waters. Knowing the right modification a priori is challenging, and computational approaches are ideally suited to help answer the key question of which substitution is best to try. Here, we use Grand Canonical Monte Carlo and the recent Grand Canonical Alchemical Perturbation methods to both understand and predict the effect of ligand-mediated water displacement when more than one water molecule is involved, as well as to understand how exploiting water networks can help govern selectivity.

Computational Strategy Revealing the Structural Determinant of Ligand Selectivity towards Highly Similar Protein Targets

BACKGROUND

Poor selectivity of drug candidates may lead to toxicity and side effects accounting for as high as 60% failure rate, thus, the selectivity is consistently significant and challenging for drug discovery.

OBJECTIVE

To find highly specific small molecules towards very similar protein targets, multiple strategies are always employed, including (1) To make use of the diverse shape of binding pocket to avoid steric bump; (2) To increase binding affinities for favorite residues; (3) To achieve selectivity through allosteric regulation of target; (4) To stabalize the inactive conformation of protein target and (5) To occupy dual binding pockets of single target.

CONCLUSION

In this review, we summarize computational strategies along with examples of their successful applications in designing selective ligands, with the aim to provide insights into everdiversifying drug development practice and inspire medicinal chemists to utilize computational strategies to avoid potential side effects due to low selectivity of ligands.

How To Design Selective Ligands for Highly Conserved Binding Sites: A Case Study Using N-Myristoyltransferases as a Model System

A model system of two related enzymes with conserved binding sites, namely N-myristoyltransferase from two different organisms, was studied to decipher the driving forces that lead to selective inhibition in such cases. Using a combination of computational and experimental tools, two different selectivity-determining features were identified. For some ligands, a change in side-chain flexibility appears to be responsible for selective inhibition. Remarkably, this was observed for residues orienting their side chains away from the ligands. For other ligands, selectivity is caused by interfering with a water molecule that binds more strongly to the off-target than to the target. On the basis of this finding, a virtual screen for selective compounds was conducted, resulting in three hit compounds with the desired selectivity profile. This study delivers a guideline on how to assess selectivity-determining features in proteins with conserved binding sites and to translate this knowledge into the design of selective inhibitors.

Design of selective PI3Kδ inhibitors using an iterative scaffold-hopping workflow

PI3Kδ mediates key immune cell signaling pathways and is a target of interest for multiple indications in immunology and oncology. Here we report a structure-based scaffold-hopping strategy for the design of chemically diverse PI3Kδ inhibitors. Using this strategy, we identified several scaffolds that can be combined to generate new PI3Kδ inhibitors with high potency and isoform selectivity. In particular, an oxindole-based scaffold was found to impart exquisite selectivity when combined with several hinge binding motifs.

Structural Determinants of Isoform Selectivity in PI3K Inhibitors

Phosphatidylinositol 3-kinases (PI3Ks) are important therapeutic targets for the treatment of cancer, thrombosis, and inflammatory and immune diseases. The four highly homologous Class I isoforms, PI3K, PI3K, PI3K and PI3K have unique, non-redundant physiological roles and as such, isoform selectivity has been a key consideration driving inhibitor design and development. In this review, we discuss the structural biology of PI3Ks and how our growing knowledge of structure has influenced the medicinal chemistry of PI3K inhibitors. We present an analysis of the available structure-selectivity-activity relationship data to highlight key insights into how the various regions of the PI3K binding site influence isoform selectivity. The picture that emerges is one that is far from simple and emphasizes the complex nature of protein-inhibitor binding, involving protein flexibility, energetics, water networks and interactions with non-conserved residues.

Characterizing hydration sites in protein-ligand complexes towards the design of novel ligands

Water is an essential part of protein binding sites and mediates interactions to ligands. Its displacement by ligand parts affects the free binding energy of resulting protein-ligand complexes. Therefore the characterization of solvation properties is important for design. Of particular interest is the propensity of localized water to be favorably displaced by a ligand. This review discusses two popular computational approaches addressing these questions, namely WaterMap based on statistical mechanics analysis of MD simulations and 3D RISM based on integral equation theory of liquids. The theoretical background and recent applications in structure-based design will be presented.

Large-scale analysis of water stability in bromodomain binding pockets with grand canonical Monte Carlo

Conserved water molecules are of interest in drug design, as displacement of such waters can lead to higher affinity ligands and in some cases, contribute towards selectivity. Bromodomains, small protein domains involved in the epigenetic regulation of gene transcription, display a network of four conserved water molecules in their binding pockets and have recently been the focus of intense medicinal chemistry efforts. Understanding why certain bromodomains have displaceable water molecules and others do not is extremely challenging, and it remains unclear which water molecules in a given bromodomain can be targeted for displacement. Here we estimate the stability of the conserved water molecules in 35 bromodomains via binding free energy calculations using all-atom grand canonical Monte Carlo simulations. Encouraging quantitative agreement to the available experimental evidence is found. We thus discuss the expected ease of water displacement in different bromodomains and the implications for ligand selectivity.

Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations

Accurate in silico prediction of protein-ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently, a family of approaches commonly referred to as relative binding free energy (RBFE) calculations, which rely on physics-based molecular simulations and statistical mechanics, have shown promise in reliably generating accurate predictions in the context of drug discovery projects. This advance arises from accumulating developments in the underlying scientific methods (decades of research on force fields and sampling algorithms) coupled with vast increases in computational resources (graphics processing units and cloud infrastructures). Mounting evidence from retrospective validation studies, blind challenge predictions, and prospective applications suggests that RBFE simulations can now predict the affinity differences for congeneric ligands with sufficient accuracy and throughput to deliver considerable value in hit-to-lead and lead optimization efforts. Here, we present an overview of current RBFE implementations, highlighting recent advances and remaining challenges, along with examples that emphasize practical considerations for obtaining reliable RBFE results. We focus specifically on relative binding free energies because the calculations are less computationally intensive than absolute binding free energy (ABFE) calculations and map directly onto the hit-to-lead and lead optimization processes, where the prediction of relative binding energies between a reference molecule and new ideas (virtual molecules) can be used to prioritize molecules for synthesis. We describe the critical aspects of running RBFE calculations, from both theoretical and applied perspectives, using a combination of retrospective literature examples and prospective studies from drug discovery projects. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative binding free energy simulations, with a focus on real-world drug discovery applications. We offer guidelines for improving the accuracy of RBFE simulations, especially for challenging cases, and emphasize unresolved issues that could be improved by further research in the field.

A Water-Bridged Cysteine-Cysteine Redox Regulation Mechanism in Bacterial Protein Tyrosine Phosphatases

The emergence of multidrug-resistant Mycobacterium tuberculosis (Mtb) strains highlights the need to develop more efficacious and potent drugs. However, this goal is dependent on a comprehensive understanding of Mtb virulence protein effectors at the molecular level. Here, we used a post-expression cysteine (Cys)-to-dehydrolanine (Dha) chemical editing strategy to identify a water-mediated motif that modulates accessibility of the protein tyrosine phosphatase A (PtpA) catalytic pocket. Importantly, this water-mediated Cys-Cys non-covalent motif is also present in the phosphatase SptpA from Staphylococcus aureus, which suggests a potentially preserved structural feature among bacterial tyrosine phosphatases. The identification of this structural water provides insight into the known resistance of Mtb PtpA to the oxidative conditions that prevail within an infected host macrophage. This strategy could be applied to extend the understanding of the dynamics and function(s) of proteins in their native state and ultimately aid in the design of small-molecule modulators.

Frontiers in Medicinal Chemistry 2017 in Bern, Switzerland

Sharing capital ideas: The 2017 Frontiers in Medicinal Chemistry (FiMC) conference, organized jointly by the German Chemical Society, the German Pharmaceutical Society, and the Swiss Chemical Society, was held at the Department of Chemistry and Biochemistry of the University of Bern in February 2017. Herein we summarize the many conference highlights, and look forward to the next FiMC meeting, to be held in Jena (Germany) in March 2018.

Explicit treatment of active-site waters enhances quantum mechanical/implicit solvent scoring: Inhibition of CDK2 by new pyrazolo[1,5-a]pyrimidines

We present comprehensive testing of solvent representation in quantum mechanics (QM)-based scoring of protein-ligand affinities. To this aim, we prepared 21 new inhibitors of cyclin-dependent kinase 2 (CDK2) with the pyrazolo[1,5-a]pyrimidine core, whose activities spanned three orders of magnitude. The crystal structure of a potent inhibitor bound to the active CDK2/cyclin A complex revealed that the biphenyl substituent at position 5 of the pyrazolo[1,5-a]pyrimidine scaffold was located in a previously unexplored pocket and that six water molecules resided in the active site. Using molecular dynamics, protein-ligand interactions and active-site water H-bond networks as well as thermodynamics were probed. Thereafter, all the inhibitors were scored by the QM approach utilizing the COSMO implicit solvent model. Such a standard treatment failed to produce a correlation with the experiment (R² = 0.49). However, the addition of the active-site waters resulted in significant improvement (R² = 0.68). The activities of the compounds could thus be interpreted by taking into account their specific noncovalent interactions with CDK2 and the active-site waters. In summary, using a combination of several experimental and theoretical approaches we demonstrate that the inclusion of explicit solvent effects enhance QM/COSMO scoring to produce a reliable structure-activity relationship with physical insights. More generally, this approach is envisioned to contribute to increased accuracy of the computational design of novel inhibitors.

AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking

Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters in the bulk region. The binding of a ligand to a protein causes a displacement of these waters from an active site to bulk, and this displacement process substantially contributes to the free energy change of protein-ligand binding. The free energy of active-site water molecules can be calculated by grid inhomogeneous solvation theory (GIST), using molecular dynamics (MD) and the trajectory of a target protein and water molecules. Here, we show a case study of the combination of GIST and a docking program and discuss the effectiveness of the displacing gain of unfavorable water in protein-ligand docking. We combined the GIST-based desolvation function with the scoring function of AutoDock4, which is called AutoDock-GIST. The proposed scoring function was assessed employing 51 ligands of coagulation factor Xa (FXa), and results showed that both scoring accuracy and docking success rate were improved. We also evaluated virtual screening performance of AutoDock-GIST using FXa ligands in the directory of useful decoys-enhanced (DUD-E), thus finding that the displacing gain of unfavorable water is effective for a successful docking campaign.