Unbinding free energy of acetylcholinesterase bound oxime drugs along the gorge pathway from metadynamics-umbrella sampling investigation

Attempting Well-Tempered Funnel Metadynamics Simulations for the Evaluation of the Binding Kinetics of Methionine Aminopeptidase-II Inhibitors

Understanding the unbinding kinetics of protein-ligand complexes is considered a significant approach for the design of ligands with desired specificity and safety. In recent years, enhanced sampling methods have emerged as effective tools for studying the unbinding kinetics of protein-ligand complexes at the atomistic level. MetAP-II is a target for the treatment of cancer for which not a single effective drug is available yet. The identification of the dissociation rate of ligands from the complexes often serves as a better predictor for in vivo efficacy than the ligands' binding affinity. Here, funnel-based restraint well-tempered metadynamics simulations were applied to predict the residence time of two ligands bound to MetAP-II, along with the ligand association and dissociation mechanism involving the identification of the binding hotspot during ligand egress. The ligand-egressing route revealed by metadynamics simulations also correlated with the identified pathways from the CAVER analysis and by the enhanced sampling simulation using PLUMED. Ligand 1 formed a strong H-bond interaction with GLU364 estimating a higher residence time of 28.22 ± 5.29 ns in contrast to ligand 2 with a residence time of 19.05 ± 3.58 ns, which easily dissociated from the binding pocket of MetAP-II. The results obtained from the simulations were consistent to reveal ligand 1 being superior to ligand 2; however, the experimental data related to residence time were close for both ligands, and no kinetic data were available for ligand 2. The current study could be considered the first attempt to apply an enhanced sampling method for the evaluation of the binding kinetics and thermodynamics of two different classes of ligands to a binuclear metalloprotein.

Accuracy and precision of binding free energy prediction for a tacrine related lead inhibitor of acetylcholinesterase with an arsenal of supercomputerized molecular modelling methods: a comparative study

Nowadays, advanced computational chemistry methods offer various strategies for revealing prospective hit structures in drug development essentially through accurate binding free energy predictions. After the era of molecular docking and quantitative structure-activity relationships, much interest has been lately oriented to perturbed molecular dynamic approaches like replica exchange with solute tempering and free energy perturbation (REST/FEP) and the potential of the mean force with adaptive biasing and accelerated weight histograms (PMF/AWH). Both of these receptor-based techniques can exploit exascale CPU&GPU supercomputers to achieve high throughput performance. In this fundamental study, we have compared the predictive power of a panel of supercomputerized molecular modelling methods to distinguish the major binding modes and the corresponding binding free energies of a promising tacrine related potential antialzheimerics in human acetylcholinesterase. The binding free energies were estimated using flexible molecular docking, molecular mechanics/generalized Born surface area/Poisson-Boltzmann surface area (MM/GBSA/PBSA), transmutation REST/FEP with 12 x 5 ns/λ windows, annihilation FEP with 20 x 5 ns/λ steps, PMF with weight histogram analysis method (WHAM) and 40 x 5 ns samples, and PMF/AWH with 10 x 100 ns replicas. Confrontation of the classical approaches such as canonical molecular dynamics and molecular docking with alchemical calculations and steered molecular dynamics enabled us to show how large errors in ΔG predictions can be expected if these in silico methods are employed in the elucidation of a common case of enzyme inhibition.Communicated by Ramaswamy H. Sarma.

The Molecular Mechanism of Human Voltage-Dependent Anion Channel 1 Blockade by the Metallofullerenol Gd@C82(OH)22: An In Silico Study

The endohedral metallofullerenol Gd@C₈₂(OH)₂₂ has been identified as a possible antineoplastic agent that can inhibit both the growth and metastasis of cancer cells. Despite these potentially important effects, our understanding of the interactions between Gd@C₈₂(OH)₂₂ and biomacromolecules remains incomplete. Here, we study the interaction between Gd@C₈₂(OH)₂₂ and the human voltage-dependent anion channel 1 (hVDAC1), the most abundant porin embedded in the mitochondrial outer membrane (MOM), and a potential druggable target for novel anticancer therapeutics. Using in silico approaches, we observe that Gd@C₈₂(OH)₂₂ molecules can permeate and form stable interactions with the pore of hVDAC1. Further, this penetration can occur from either side of the MOM to elicit blockage of the pore. The binding between Gd@C₈₂(OH)₂₂ and hVDAC1 is largely driven by long-range electrostatic interactions. Analysis of the binding free energies indicates that it is thermodynamically more favorable for Gd@C₈₂(OH)₂₂ to bind to the hVDAC1 pore when it enters the channel from inside the membrane rather than from the cytoplasmic side of the protein. Multiple factors contribute to the preferential penetration, including the surface electrostatic landscape of hVDAC1 and the unique physicochemical properties of Gd@C₈₂(OH)₂₂. Our findings provide insights into the potential molecular interactions of macromolecular biological systems with the Gd@C₈₂(OH)₂₂ nanodrug.

Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies

Calculating absolute binding free energies is challenging and important. In this paper, we test some recently developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on 18 chemically diverse ligands with a wide range of different binding affinities to a complex target; namely, human soluble epoxide hydrolase. The results suggest that metadynamics with a funnel-shaped restraint can be used to calculate, in a computationally affordable and relatively accurate way, the absolute binding free energy for small fragments. When used in combination with an optimal pathlike variable obtained using machine learning or with the Hamiltonian replica-exchange algorithm SWISH, this method can achieve reasonably accurate results for increasingly complex ligands, with a good balance of computational cost and speed. An additional benefit of using the combination of metadynamics and SWISH is that it also provides useful information about the role of water in the binding mechanism.

Potential Mean Force from Umbrella Sampling Simulations: What Can We Learn and What Is Missed?

Changes in free energy provide valuable information for molecular recognition, including both ligand-receptor binding thermodynamics and kinetics. Umbrella sampling (US), a widely used free energy calculation method, has long been used to explore the dissociation process of ligand-receptor systems and compute binding free energy. In existing publications, the binding free energy computed from the potential of mean force (PMF) with US simulation mostly yielded "ball park" values with experimental data. However, the computed PMF values are highly influenced by factors such as initial conformations and/or trajectories provided, the reaction coordinate, and sampling of conformational space in each US window. These critical factors have rarely been carefully studied. Here we used US to study the guest aspirin and 1-butanol dissociation processes of β-cyclodextrin (β-CD) and an inhibitor SB2 dissociation from a p38α mitogen-activated protein kinase (MAPK) complex. For β-CD, we used three different β-CD conformations to generate the dissociation path with US windows. For p38α, we generated the dissociation pathway by using accelerated molecular dynamics followed by conformational relaxing with short conventional MD, steered MD, and manual pulling. We found that, even for small β-CD complexes, different β-CD conformations altered the height of the PMF, but the pattern of PMF was not affected if the MD sampling in each US window was well-converged. Because changing the macrocyclic ring conformation needs to rotate dihedral angles in the ring, a bound ligand largely restrains the motion of cyclodextrin. Therefore, once a guest is in the binding site, cyclodextrin cannot freely change its initial conformation, resulting in different absolute heights of the PMF, which cannot be overcome by running excessively long MD simulations for each US window. Moreover, if the US simulations were not converged, the important barrier and minimum were missed. For ligand-protein systems, our studies also suggest that the dissociation trajectories modeled by an enhanced sampling method must maintain a natural molecular movement to avoid biased PMF plots when using US simulations.

Metadynamics supports molecular dynamics simulation-based binding affinities of eucalyptol and beta-cyclodextrin inclusion complexes

The development of various molecular dynamics methods enables the detailed investigation of association processes, like host–guest complexes, including their dynamics and, additionally, the release of the guest compound.

Probing the ATP-induced conformational flexibility of the PcrA helicase protein using molecular dynamics simulation

Helicases are enzymes that unwind double-stranded DNA (dsDNA) into its single-stranded components. It is important to understand the binding and unbinding of ATP from the active sites of helicases, as this knowledge can be used to elucidate the functionality of helicases during the unwinding of dsDNA. In this work, we investigated the unbinding of ATP and its effect on the active-site residues of the helicase PcrA using molecular dynamic simulations. To mimic the unbinding process of ATP from the active site of the helicase, we simulated the application of an external force that pulls ATP from the active site and computed the free-energy change during this process. We estimated an energy cost of ~85 kJ/mol for the transformation of the helicase from the ATP-bound state (1QHH) to the ATP-free state (1PJR). Unbinding led to conformational changes in the residues of the protein at the active site. Some of the residues at the ATP-binding site were significantly reoriented when the ATP was pulled. We observed a clear competition between reorientation of the residues and energy stabilization by hydrogen bonds between the ATP and active-site residues. We also checked the flexibility of the PcrA protein using a principal component analysis of domain motion. We found that the ATP-free state of the helicase is more flexible than the ATP-bound state.

Ortho-7 bound to the active-site gorge of free and OP-conjugated acetylcholinesterase: cation-π interactions

Despite the immense importance of cation-π interactions prevailing in bispyridinium drug acetylcholinesterase (AChE) complexes, a precise description of cation-π interactions at molecular level has remained elusive. Here, we consider a bispyridinium drug, namely, ortho-7 in three different structures of AChE, with and without complexation with organophosphorus (OP) compounds for detailed investigation using all atom molecular dynamics simulation. By quantum mechanical calculations, Y72, W86, Y124, W286, Y337, and Y341 aromatic residues of the enzyme are investigated for possible cation-π interactions with ortho-7. The cation-π interactions in each of the protein-drug complexes are studied using distance, angle, a suitable functional form of them, and electrostatic criteria. The variation of cation-π functional is remarkably consistent with that of the Columbic variation. It is clearly observed that cation-π interactions for some of the residues in the catalytic active site (CAS) and peripheral anionic site (PAS) of the enzyme are either enhanced or reduced based on the nature of OP conjugation (i.e., nerve gas, tabun or pesticide, fenamiphos) when compared with the OP-free enzyme. The strength of cation-π interaction is strongly dependent on the type OP conjugation. The effect of conjugation at CAS is also seen to influence the cation-π interaction at the PAS region. The variation of cation-π interactions on the type of conjugating OP compounds might be suggestive of a reason as to why wide spectrum drug against any OP poisoning is yet to arrive in the market.

Including ligand-induced protein flexibility into protein tunnel prediction

In proteins with buried active sites, understanding how ligands migrate through the tunnels that connect the exterior of the protein to the active site can shed light on substrate specificity and enzyme function. A growing body of evidence highlights the importance of protein flexibility in the binding site on ligand binding; however, the influence of protein flexibility throughout the body of the protein during ligand entry and egress is much less characterized. We have developed a novel tunnel prediction and evaluation method named IterTunnel, which includes the influence of ligand-induced protein flexibility, guarantees ligand egress, and provides detailed free energy information as the ligand proceeds along the egress route. IterTunnel combines geometric tunnel prediction with steered molecular dynamics in an iterative process to identify tunnels that open as a result of ligand migration and calculates the potential of mean force of ligand egress through a given tunnel. Applying this new method to cytochrome P450 2B6, we demonstrate the influence of protein flexibility on the shape and accessibility of tunnels. More importantly, we demonstrate that the ligand itself, while traversing through a tunnel, can reshape tunnels due to its interaction with the protein. This process results in the exposure of new tunnels and the closure of preexisting tunnels as the ligand migrates from the active site.