Insight into Thermodynamic and Kinetic Profiles in Small-Molecule Optimization

Pathway Specific Unbinding Free Energy Profiles of Ritonavir Dissociation from HIV-1 Protease

Investigation of protein-drug recognition is key to understanding drug selectivity and binding affinity. In combination, the binding/unbinding free energy landscape and intermolecular interactions can be used to understand drug binding/unbinding mechanisms. This information is vital for the development of drugs with improved efficacy and explanation of mutation effects. This study investigated the dissociation processes of ritonavir unbinding from HIV protease (HIVp). Analyzing unbinding trajectories modeled by accelerated molecular dynamics (MD) simulations, three distinct pathways, pathways A-C, were characterized. Using a reduced dimensionality strategy with the principal component analysis, we carried out short classical MD runs with explicit water to sample local fluctuation during ritonavir dissociation and applied the milestoning theory to construct an unbinding free energy landscape. We found that each pathway showed similar values of binding free energy, albeit pathway A accounts for over 50% of dissociation trajectories. Interestingly, residue-residue correlation network analysis showed that in pathway A, a broad correlation network outside the flap region governs protein motions during ritonavir unbinding, which includes residues with reported mutation effects. However, the other two pathways showed limited correlation networks where no reported mutated residues were involved, explaining the favorability of pathway A. Guided by the free energy profile, we investigated each energy barrier and minimum, demonstrating that hydrogen bonding governed movement of the flap regions, directly impacting the calculated energy. Our study provided a new strategy to estimate ligand binding free energy and demonstrated the importance of the transient interactions during ligand-protein dissociation pathways in understanding drug unbinding.

Advances and Challenges in Milestoning Simulations for Drug-Target Kinetics

Molecular dynamics simulations have become indispensable for exploring complex biological processes, yet their limitations in capturing rare events hinder our understanding of drug-target kinetics. In this Perspective, we investigate the domain of milestoning simulations to understand this challenge. The milestoning approach divides the phase space of the drug-target complex into discrete cells, offering extended time scale insights. This Perspective traces the history, applications, and future potential of milestoning simulations in the context of drug-target kinetics. It explores the fundamental principles of milestoning, highlighting the importance of probabilistic transitions and transition time independence. Markovian milestoning with Voronoi tessellations is revisited to address the traditional milestoning challenges. While observing the advancements in this field, this Perspective also addresses impending challenges in estimating drug-target unbinding rate constants through milestoning simulations, paving the way for more effective drug design strategies.

Discovery of orally bioavailable SARS-CoV-2 papain-like protease inhibitor as a potential treatment for COVID-19

The RNA-dependent RNA polymerase (RdRp), 3C-like protease (3CLpro), and papain-like protease (PLpro) are pivotal components in the viral life cycle of SARS-CoV-2, presenting as promising therapeutic targets. Currently, all FDA-approved antiviral drugs against SARS-CoV-2 are RdRp or 3CLpro inhibitors. However, the mutations causing drug resistance have been observed in RdRp and 3CLpro from SARS-CoV-2, which makes it necessary to develop antivirals with novel mechanisms. Through the application of a structure-based drug design (SBDD) approach, we discover a series of novel potent non-covalent PLpro inhibitors with remarkable in vitro potency and in vivo PK properties. The co-crystal structures of PLpro with lead compounds reveal that the residues D164 and Q269 around the S2 site are critical for improving the inhibitor's potency. The lead compound GZNL-P36 not only inhibits SARS-CoV-2 and its variants at the cellular level with EC50 ranging from 58.2 nM to 306.2 nM, but also inhibits HCoV-NL63 and HCoV-229E with EC50 of 81.6 nM and 2.66 μM, respectively. Oral administration of the GZNL-P36 results in significantly improved survival and notable reductions in lung viral loads and lesions in SARS-CoV-2 infection mouse model, consistent with RNA-seq data analysis. Our results indicate that PLpro inhibitors represent a promising SARS-CoV-2 therapy.

The translational value of ligand-receptor binding kinetics in drug discovery

The translation of in vitro potency of a candidate drug, as determined by traditional pharmacology metrics (such as EC50/IC50 and KD/Ki values), to in vivo efficacy and safety is challenging. Residence time, which represents the duration of drug-target interaction, can be part of a more comprehensive understanding of the dynamic nature of drug-target interactions in vivo, thereby enabling better prediction of drug efficacy and safety. As a consequence, a prolonged residence time may help in achieving sustained pharmacological activity, while transient interactions with shorter residence times may be favourable for targets associated with side effects. Therefore, integration of residence time into the early stages of drug discovery and development has yielded a number of clinical candidates with promising in vivo efficacy and safety profiles. Insights from residence time research thus contribute to the translation of in vitro potency to in vivo efficacy and safety. Further research and advances in measuring and optimizing residence time will bring a much-needed addition to the drug discovery process and the development of safer and more effective drugs. In this review, we summarize recent research progress on residence time, highlighting its importance from a translational perspective.

Prediction of Threonine-Tyrosine Kinase Receptor-Ligand Unbinding Kinetics with Multiscale Milestoning and Metadynamics

Accurately describing protein-ligand binding and unbinding kinetics remains challenging. Computational calculations are difficult and costly, while experimental measurements often lack molecular detail and can be unobtainable. Here, we extend our multiscale milestoning method, Simulation-Enabled Estimation of Kinetics Rates (SEEKR), with metadynamics molecular dynamics simulations to yield accurate small molecule drug residence times. Using the pharmaceutically relevant threonine-tyrosine kinase (TTK) and eight long-residence-time (tens of seconds to hours) inhibitors, we demonstrate accurate prediction of absolute and rank-ordered ligand residence times and free energies of binding.

Kinetic profiling of novel spirobenzo-oxazinepiperidinone derivatives as equilibrative nucleoside transporter 1 inhibitors

Evaluation of kinetic parameters of drug-target binding, kon, koff, and residence time (RT), in addition to the traditional in vitro parameter of affinity is receiving increasing attention in the early stages of drug discovery. Target binding kinetics emerges as a meaningful concept for the evaluation of a ligand's duration of action and more generally drug efficacy and safety. We report the biological evaluation of a novel series of spirobenzo-oxazinepiperidinone derivatives as inhibitors of the human equilibrative nucleoside transporter 1 (hENT1, SLC29A1). The compounds were evaluated in radioligand binding experiments, i.e., displacement, competition association, and washout assays, to evaluate their affinity and binding kinetic parameters. We also linked these pharmacological parameters to the compounds' chemical characteristics, and learned that separate moieties of the molecules governed target affinity and binding kinetics. Among the 29 compounds tested, 28 stood out with high affinity and a long residence time of 87 min. These findings reveal the importance of supplementing affinity data with binding kinetics at transport proteins such as hENT1.

Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A3 Receptor

A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.

QMrebind: incorporating quantum mechanical force field reparameterization at the ligand binding site for improved drug-target kinetics through milestoning simulations

Understanding the interaction of ligands with biomolecules is an integral component of drug discovery and development. Challenges for computing thermodynamic and kinetic quantities for pharmaceutically relevant receptor-ligand complexes include the size and flexibility of the ligands, large-scale conformational rearrangements of the receptor, accurate force field parameters, simulation efficiency, and sufficient sampling associated with rare events. Our recently developed multiscale milestoning simulation approach, SEEKR2 (Simulation Enabled Estimation of Kinetic Rates v.2), has demonstrated success in predicting unbinding (koff) kinetics by employing molecular dynamics (MD) simulations in regions closer to the binding site. The MD region is further subdivided into smaller Voronoi tessellations to improve the simulation efficiency and parallelization. To date, all MD simulations are run using general molecular mechanics (MM) force fields. The accuracy of calculations can be further improved by incorporating quantum mechanical (QM) methods into generating system-specific force fields through reparameterizing ligand partial charges in the bound state. The force field reparameterization process modifies the potential energy landscape of the bimolecular complex, enabling a more accurate representation of the intermolecular interactions and polarization effects at the bound state. We present QMrebind (Quantum Mechanical force field reparameterization at the receptor-ligand binding site), an ORCA-based software that facilitates reparameterizing the potential energy function within the phase space representing the bound state in a receptor-ligand complex. With SEEKR2 koff estimates and experimentally determined kinetic rates, we compare and interpret the receptor-ligand unbinding kinetics obtained using the newly reparameterized force fields for model host-guest systems and HSP90-inhibitor complexes. This method provides an opportunity to achieve higher accuracy in predicting receptor-ligand koff rate constants.

Thermodynamic and kinetic approaches for drug discovery to target protein misfolding and aggregation

INTRODUCTION

Protein misfolding diseases, including Alzheimer's and Parkinson's diseases, are characterized by the aberrant aggregation of proteins. These conditions are still largely untreatable, despite having a major impact on our healthcare systems and societies.

AREAS COVERED

We describe drug discovery strategies to target protein misfolding and aggregation. We compare thermodynamic approaches, which are based on the stabilization of the native states of proteins, with kinetic approaches, which are based on the slowing down of the aggregation process. This comparison is carried out in terms of the current knowledge of the process of protein misfolding and aggregation, the mechanisms of disease and the therapeutic targets.

EXPERT OPINION

There is an unmet need for disease-modifying treatments that target protein misfolding and aggregation for the over 50 human disorders known to be associated with this phenomenon. With the approval of the first drugs that can prevent misfolding or inhibit aggregation, future efforts will be focused on the discovery of effective compounds with these mechanisms of action for a wide range of conditions.

Methyl and Fluorine Effects in Novel Orally Bioavailable Keap1-Nrf2 PPI Inhibitor

Oxidative stress is one of the causes of progression of chronic kidney disease (CKD). Activation of the antioxidant protein regulator Nrf2 by inhibition of the Keap1-Nrf2 protein-protein interaction (PPI) is of interest as a potential treatment for CKD. We report the identification of the novel and weak PPI inhibitor 7 with good physical properties by a high throughput screening (HTS) campaign, followed by structural and computational analysis. The installation of only methyl and fluorine groups successfully provided the lead compound 25, which showed more than 400-fold stronger activity. Furthermore, these dramatic substituent effects can be explained by the analysis of using isothermal titration calorimetry (ITC). Thus, the resulting 25, which exhibited high oral absorption and durability, would be a CKD therapeutic agent because of the dose-dependent manner for up-regulation of the antioxidant protein heme oxigenase-1 (HO-1) in rat kidneys.