An Integrated Markov State Model and Path Metadynamics Approach To Characterize Drug Binding Processes

Bernetti, Mattia; Masetti, Matteo; Recanatini, Maurizio; Amaro, Rommie E.; Cavalli, Andrea

doi:10.1021/acs.jctc.9b00450

Cited by 57 publications

(67 citation statements)

References 97 publications

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“…Methods that depend on the definition of one or more progress coordinates to describe the infrequent event and enhance the sampling, such as metadynamics [277] and weighted ensemble MD (WEMD) [278,279], have been used to reveal mechanistic details of drug-protein association and dissociation. Metadynamics was used to distinguish cyclin-dependent kinase 8 inhibitors with short or long residence times [280] and to study association or dissociation events for relevant pharmacological targets such as HIV reverse transcriptase [281], Src kinase [282,283], p38 MAP kinase [284], the M3 muscarinic receptor [285], the adenosine A2A receptor [285,286] and the β2-adrenergic receptor [287]. WEMD was used to study ligand dissociation from epoxide hydrolase [288] and from proteins used as model systems to study binding kinetics [289,290].…”

Section: Drug-protein Binding Kinetics Estimationmentioning

confidence: 99%

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

et al. 2020

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Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

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Section: Drug-protein Binding Kinetics Estimationmentioning

confidence: 99%

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

et al. 2020

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“…2B). This rotation process was also associated with the ligand transition over the highest energy barrier on the dissociation pathway in a metadynamics study 26 . While this difference may arise due to differences in the force fields used, another possible explanation is that this barrier has a mainly entropic character as the ligand needs to undergo conformational changes and adopt a specific orientation to pass through a narrow tunnel leading to the egress route ECV1.…”

Section: And 8) That Are Intermediates On the Main Dissociation Pathways Ecv1 And Ecv2; Metastable States Are Depicted As Iso-surfaces Ofmentioning

confidence: 77%

“…Correspondingly, in the binding free energy profile computed later in metadynamics simulations in Ref. 26 , two energy minima were found: a deep one, corresponding to the bound state, and a shallow local energy minimum located between two barriers to ligand exit (the first for the ligand passing between Y308 and F193, and the second for ligand solvation upon leaving the ECV). 26 This observation agrees qualitatively with the metastable states found in the present RAMD simulations.…”

Section: And 8) That Are Intermediates On the Main Dissociation Pathways Ecv1 And Ecv2; Metastable States Are Depicted As Iso-surfaces Ofmentioning

confidence: 90%

G Protein-Coupled Receptor-Ligand Dissociation Rates and Mechanisms from τRAMD Simulations

Kokh

Wade

2021

Preprint

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There is a growing appreciation of the importance of drug-target binding kinetics for lead optimization. For G protein-coupled receptors (GPCRs), which mediate signaling over a wide range of timescales, the drug dissociation rate is often a better predictor of in vivo efficacy than binding affinity, although it is more challenging to compute. Here, we assess the ability of the τ-Random Acceleration Molecular Dynamics (τRAMD) approach to reproduce relative residence times and reveal dissociation mechanisms and the effects of allosteric modulation for two important membrane-embedded drug targets: the β2-adrenergic receptor and the muscarinic acetylcholine receptor M2. The dissociation mechanisms observed in the relatively short RAMD simulations (in which molecular dynamics (MD) simulations are performed using an additional force with an adaptively assigned random orientation applied to the ligand) are in general agreement with much more computationally intensive conventional MD and metadynamics simulations. Remarkably, although decreasing the magnitude of the random force generally reduces the number of egress routes observed, the ranking of ligands by dissociation rate is hardly affected and agrees well with experiment. The simulations also reproduce changes in residence time due to allosteric modulation and reveal associated changes in ligand dissociation pathways.

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“…MFEP can be determined by iteratively refine a pathway connecting stable states that converges to the minimum free energy trajectories between them. MFEP could also be obtained through the Path Collective Variables description coupled with metadynamics 43 . Alternatively to biased-MD simulation methods, certain spontaneous binding events can also be achieved through extensive standard MD simulations, for example, running for µs to ms simulation time 44,45 .…”

Section: Phos Hvr Backbone Farmentioning

confidence: 99%

Long-lasting salt bridges provide the anchoring mechanism of oncogenic KRas-4B proteins at cell membranes

Martı́

2020

Preprint

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Ras is a family of related proteins participating in all animal cell lineages and organs which work as GDP-GTP binary switches and regulate cytoplasmic signalling networks able to control several cellular processes, playing an essential role in signal transduction pathways involved in cell growth, differentiation and survival. In this work, a G12D mutated farnesylated GTP bound KRas-4B protein has been simulated at the interface of a DOPC/DOPS/cholesterol model anionic cell membrane at the all-atom level. A specific long-lasting salt bridge connection between farnesyl and the hypervariable region of the protein has been identified as the main mechanism responsible of the binding of oncogenic farnesylated KRas-4B to the cell membrane, since this particular bond is absent in both wild-type and oncogenic methylated species of KRas-4B. This finding may lead to a deeper understanding of the mechanisms of protein binding and eventual growing and spreading inside cell membranes. From free energy landscapes obtained by well-tempered metadynamics simulations, we have characterised local and global minima of KRas-4B binding and revealed the main pathways between anchored and released states.

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An Integrated Markov State Model and Path Metadynamics Approach To Characterize Drug Binding Processes

Cited by 57 publications

References 97 publications

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

G Protein-Coupled Receptor-Ligand Dissociation Rates and Mechanisms from τRAMD Simulations

Long-lasting salt bridges provide the anchoring mechanism of oncogenic KRas-4B proteins at cell membranes

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