Methodological and force field effects in the molecular dynamics-based prediction of binding free energies of host-guest systems.

As a contribution to the understanding and rationalization of methodological and modeling effects in recent host-guest SAMPL challenges, using an alchemical molecular dynamics technique we have examined the impact of force field parameterization and ionic strength in connection with guest charge neutralization on computed dissociation free energies in two typical SAMPL heavily charged macrocyclic hosts encapsulating small protonated amines with disparate binding affinities. We have shown that the methodological treatment for host neutralization, with explicit ions or with the background neutralizing plasma in the context of alchemical calculations under periodic boundary conditions, has a moderate effect on the calculated affinities. On the other hand, we have shown that seemingly small differences in the force field parameterization in highly symmetric hosts can produce systematic effects on the structural features that can have a significant impact on the predicted binding affinities.

Identification of Potential Inhibitors of the SARS-CoV-2 NSP13 Helicase via Structure-Based Ligand Design, Molecular Docking and Nonequilibrium Alchemical Simulations.

We have assembled a computational pipeline based on virtual screening, docking techniques, and nonequilibrium molecular dynamics simulations, with the goal of identifying possible inhibitors of the SARS-CoV-2 NSP13 helicase, catalyzing by ATP hydrolysis the unwinding of double or single-stranded RNA in the viral replication process inside the host cell. The druggable sites for broad-spectrum inhibitors are represented by the RNA binding sites at the 5' entrance and 3' exit of the central channel, a structural motif that is highly conserved across coronaviruses. Potential binders were first generated using structure-based ligand techniques.

Addressing Suboptimal Poses in Nonequilibrium Alchemical Calculations.

Alchemical transformations can be used to quantitatively estimate absolute binding free energies at a reasonable computational cost. However, most of the approaches currently in use require knowledge of the correct (crystallographic) pose. In this paper, we present a combined Hamiltonian replica exchange nonequilibrium alchemical method that allows us to reliably calculate absolute binding free energies, even when starting from suboptimal initial binding poses.

Dealing with Induced Fit, Conformational Selection, and Secondary Poses in Molecular Dynamics Simulations for Reliable Free Energy Predictions.

In this study, we have tested the performance of standard molecular dynamics (MD) simulations, replicates of shorter standard MD simulations, and Hamiltonian Replica Exchange (HREM) simulations for the sampling of two macrocyclic hosts for guest delivery, characterized by induced fit (phenyl-based host) and conformation selection (naphthyl-based host) and of the ODR-BRD4(I) drug-receptor system where the ligand can assume two main poses. For the optimization of the HREM simulation, we have proposed and tested an on-the-fly iterative scheme for equalizing the acceptance ratio along the replica progression at a constant replica number resulting in a moderate impact of the sampling efficiency. Concerning standard MD, we have found that, while splitting the total allocated simulation time in short MD replicates can reproduce the sampling efficiency of HREM in the phenyl-based host and in the ODR-BRD4(I) complex, in the naphthyl-based macrocycle, characterized by long-lived metastable states, enhanced sampling techniques are the only viable alternative for a reliable canonical sampling of the rugged conformational landscape.

SAMPL9 blind predictions for toluene/water partition coefficients using nonequilibrium alchemical approaches.

We present our blind prediction of the toluene-water partition coefficients in the context of the SAMPL9 challenge. For the calculation of the solvation free energies in water, toluene, and 1-octanol, we used an efficient MD-based nonequilibrium alchemical technique relying on the GAFF2 non-polarizable force field. The method is based on the fast-growth of an initially decoupled solute.

NE-RDFE: A protocol and toolkit for computing relative dissociation free energies with GROMACS between dissimilar molecules using bidirectional nonequilibrium dual topology schemes.

We describe a step-by-step protocol and toolkit for the computation of the relative dissociation free energy (RDFE) with the GROMACS molecular dynamics package, based on a novel bidirectional nonequilibrium alchemical approach. The proposed methodology does not require any intervention on the code and allows computing with good accuracy the RDFE between small molecules with arbitrary differences in volume, charge, and chemical topology. The procedure is illustrated for the challenging SAMPL9 batch of host-guest pairs.

2-Butanol Aqueous Solutions: A Combined Molecular Dynamics and Small/Wide-Angle X-ray Scattering Study.

Structural properties of 2-butanol aqueous solutions at different concentrations have been studied using small- and wide-angle X-ray scattering and molecular dynamics simulations. The experimental structure factors have been accurately reproduced by the simulations, allowing one to explain their variation with concentration and to achieve a detailed description of the structural and dynamic properties of the studied systems. The analysis of experimental and computational data has shown that 2-butanol, the simplest aliphatic chiral alcohol, tends to form aggregates at a concentration above 1 M, affecting also both the structural and dynamic properties of the solvent.

Does Hamiltonian Replica Exchange via Lambda-Hopping Enhance the Sampling in Alchemical Free Energy Calculations?

In the context of computational drug design, we examine the effectiveness of the enhanced sampling techniques in state-of-the-art free energy calculations based on alchemical molecular dynamics simulations. In a paradigmatic molecule with competition between conformationally restrained E and Z isomers whose probability ratio is strongly affected by the coupling with the environment, we compare the so-called λ-hopping technique to the Hamiltonian replica exchange methods assessing their convergence behavior as a function of the enhanced sampling protocols (number of replicas, scaling factors, simulation times). We found that the pure λ-hopping, commonly used in solvation and binding free energy calculations via alchemical free energy perturbation techniques, is ineffective in enhancing the sampling of the isomeric states, exhibiting a pathological dependence on the initial conditions.

Relative Binding Free Energy between Chemically Distant Compounds Using a Bidirectional Nonequilibrium Approach.

In the context of advanced hit-to-lead drug design based on atomistic molecular dynamics simulations, we propose a dual topology alchemical approach for calculating the relative binding free energy (RBFE) between two chemically distant compounds. The method (termed NE-RBFE) relies on the enhanced sampling of the end-states in bulk and in the bound state via Hamiltonian Replica Exchange, alchemically connected by a series of independent and fast nonequilibrium (NE) simulations. The technique has been implemented in a bidirectional fashion, applying the Crooks theorem to the NE work distributions for RBFE predictions.

SAMPL9 blind predictions using nonequilibrium alchemical approaches.

We present our blind predictions for the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL), ninth challenge, focusing on the binding of WP6 (carboxy-pillar[6]arene) with ammonium/diammonium cationic guests. Host-guest binding free energies have been calculated using the recently developed virtual double system single box approach, based on the enhanced sampling of the bound and unbound end-states followed by fast switching nonequilibrium alchemical simulations [M. Macchiagodena et al.

Virtual Double-System Single-Box for Absolute Dissociation Free Energy Calculations in GROMACS.

We describe a step-by-step protocol for the computation of absolute dissociation free energy with GROMACS code and PLUMED library, which exploits a combination of advanced sampling techniques and nonequilibrium alchemical methodologies. The computational protocol has been automated through an open source Python middleware (HPC_Drug) which allows one to set up the GROMACS/PLUMED input files for execution on high performing computing facilities. The proposed protocol, by exploiting its inherent parallelism and the power of the GROMACS code on graphical processing units, has the potential to afford accurate and precise estimates of the dissociation constants in drug-receptor systems described at the atomistic level.

Characterization of the non-covalent interaction between the PF-07321332 inhibitor and the SARS-CoV-2 main protease.

We have studied the non-covalent interaction between PF-07321332 and SARS-CoV-2 main protease at the atomic level using a computational approach based on extensive molecular dynamics simulations with explicit solvent. PF-07321332, whose chemical structure has been recently disclosed, is a promising oral antiviral clinical candidate with well-established anti-SARS-CoV-2 activity in vitro. The drug, currently in phase III clinical trials in combination with ritonavir, relies on the electrophilic attack of a nitrile warhead to the catalytic cysteine of the protease.

On the NS-DSSB unidirectional estimates in the SAMPL6 SAMPLing challenge.

In the context of the recent SAMPL6 SAMPLing challenge (Rizzi et al. 2020 in J Comput Aided Mol Des 34:601-633) aimed at assessing convergence properties and reproducibility of molecular dynamics binding free energy methodologies, we propose a simple explanation of the severe errors observed in the nonequilibrium switch double-system-single-box (NS-DSSB) approach when using unidirectional estimates. At the same time, we suggest a straightforward and minimal modification of the NS-DSSB protocol for obtaining reliable unidirectional estimates for the process where the ligand is decoupled in the bound state and recoupled in the bulk.

Binding free energy predictions in host-guest systems using Autodock4. A retrospective analysis on SAMPL6, SAMPL7 and SAMPL8 challenges.

We systematically tested the Autodock4 docking program for absolute binding free energy predictions using the host-guest systems from the recent SAMPL6, SAMPL7 and SAMPL8 challenges. We found that Autodock4 behaves surprisingly well, outperforming in many instances expensive molecular dynamics or quantum chemistry techniques, with an extremely favorable benefit-cost ratio. Some interesting features of Autodock4 predictions are revealed, yielding valuable hints on the overall reliability of docking screening campaigns in drug discovery projects.

SAMPL7 blind predictions using nonequilibrium alchemical approaches.

In the context of the SAMPL7 challenge, we computed, employing a non-equilibrium (NE) alchemical technique, the standard binding free energy of two series of host-guest systems, involving as a host the Isaac's TrimerTrip, a Cucurbituril-like open cavitand, and the Gilson's Cyclodextrin derivatives. The adopted NE alchemy combines enhanced sampling molecular dynamics simulations with driven fast out-of-equilibrium alchemical trajectories to recover the free energy via the Jarzynski and Crooks NE theorems. The GAFF2 non-polarizable force field was used for the parametrization.

Mycotoxins aptasensing: From molecular docking to electrochemical detection of deoxynivalenol.

This work proposes a voltammetric aptasensor to detect deoxynivalenol (DON) mycotoxin. The development steps of the aptasensor were partnered for the first time to a computational study to gain insights onto the molecular mechanisms involved into the interaction between a thiol-tethered DNA aptamer (80mer-SH) and DON. The exploited docking study allowed to find the binding region of the oligonucleotide sequence and to determine DON preferred orientation.

Methodological uncertainties in drug-receptor binding free energy predictions based on classical molecular dynamics.

Computational approaches are becoming an essential tool in modern drug design and discovery, with fast compound triaging using a combination of machine learning and docking techniques followed by molecular dynamics binding free energies assessment using alchemical techniques. The traditional MD-based alchemical free energy perturbation (FEP) method faces severe sampling issues that may limits its reliability in automated workflows. Here we review the major sources of uncertainty in FEP protocols for drug discovery, showing how the sampling problem can be effectively tackled by switching to nonequilibrium alchemical techniques.

Virtual Double-System Single-Box: A Nonequilibrium Alchemical Technique for Absolute Binding Free Energy Calculations: Application to Ligands of the SARS-CoV-2 Main Protease.

In the context of drug-receptor binding affinity calculations using molecular dynamics techniques, we implemented a combination of Hamiltonian replica exchange (HREM) and a novel nonequilibrium alchemical methodology, called virtual double-system single-box, with increased accuracy, precision, and efficiency with respect to the standard nonequilibrium approaches. The method has been applied for the determination of absolute binding free energies of 16 newly designed noncovalent ligands of the main protease (3CL) of SARS-CoV-2. The core structures of 3CL ligands were previously identified using a multimodal structure-based ligand design in combination with docking techniques.

Upgraded AMBER Force Field for Zinc-Binding Residues and Ligands for Predicting Structural Properties and Binding Affinities in Zinc-Proteins.

We developed a novel force field in the context of AMBER parameterization for glutamate and aspartate zinc(II)-binding residues. The interaction between the zinc ion and the coordinating atoms is represented by a spherical nonbonded parameterization. The polarization effect due to the zinc ion has been taken into account by redefining the atomic charges on the residues through accurate quantum mechanical calculations.

Interaction of hydroxychloroquine with SARS-CoV2 functional proteins using all-atoms non-equilibrium alchemical simulations.

Using a combination of enhanced sampling molecular dynamics techniques and non-equilibrium alchemical transformations with full atomistic details, we have shown that hydroxychloroquine (HCQ) may act as a mild inhibitor of important functional proteins for SARS-CoV2 replication, with potency increasing in the series PLpro, 3CLpro, RdRp. By analyzing the bound state configurations, we were able to improve the potency for the 3CLpro target, designing a novel HCQ-inspired compound, named PMP329, with predicted nanomolar activity. If confirmed in vitro, our results provide a molecular rationale for the use of HCQ or of strictly related derivatives in the treatment of Covid-19.

Mounting evidence of FKBP12 implication in neurodegeneration.

Intrinsically disordered proteins, such as tau or α-synuclein, have long been associated with a dysfunctional role in neurodegenerative diseases. In Alzheimer's and Parkinson's' diseases, these proteins, sharing a common chemical-physical pattern with alternating hydrophobic and hydrophilic domains rich in prolines, abnormally aggregate in tangles in the brain leading to progressive loss of neurons. In this review, we present an overview linking the studies on the implication of the peptidyl-prolyl isomerase domain of immunophilins, and notably FKBP12, to a variety of neurodegenerative diseases, focusing on the molecular origin of such a role.

Identification of potential binders of the main protease 3CL of the COVID-19 via structure-based ligand design and molecular modeling.

We have applied a computational strategy, using a combination of virtual screening, docking and molecular dynamics techniques, aimed at identifying possible lead compounds for the non-covalent inhibition of the main protease 3CL of the SARS-CoV2 Coronavirus. Based on the X-ray structure (PDB code: 6LU7), ligands were generated using a multimodal structure-based design and then docked to the monomer in the active state. Docking calculations show that ligand-binding is strikingly similar in SARS-CoV and SARS-CoV2 main proteases.

A remark on the efficiency of the double-system/single-box nonequilibrium approach in the SAMPL6 SAMPLing challenge.

The alchemical nonequilibrium switching technique was one of several methods in the top tier of performance in the recent SAMPL6 SAMPLing challenge in both accuracy and efficiency. In this paper, in the context of nonequilibrium alchemical switching, we compare the efficiency of the double-system/single-box (DSSB) approach (used in the SAMPL6 challenges) to the standard single-system/double-box method (SSDB). Exploiting the Crooks theorem in a simple but effective test case, we analytically show that the DSSB approach is almost twice as efficient as SSDB for slow near-equilibrium switching but it gives basically no gain over the conventional SSDB approach when the variance of the work distribution exceeds few [Formula: see text], with the potential of producing artifacts and entanglements if not judiciously implemented.

SAMPL6 blind predictions of water-octanol partition coefficients using nonequilibrium alchemical approaches.

In this paper, we compute, by means of a non equilibrium alchemical technique, the water-octanol partition coefficients (LogP) for a series of drug-like compounds in the context of the SAMPL6 challenge initiative. Our blind predictions are based on three of the most popular non-polarizable force fields, CGenFF, GAFF2, and OPLS-AA and are critically compared to other MD-based predictions produced using free energy perturbation or thermodynamic integration approaches with stratification. The proposed non-equilibrium method emerges has a reliable tool for LogP prediction, systematically being among the top performing submissions in all force field classes for at least two among the various indicators such as the Pearson or the Kendall correlation coefficients or the mean unsigned error.

Accuracy, precision, and efficiency of nonequilibrium alchemical methods for computing free energies of solvation. I. Bidirectional approaches.

In the context of molecular dynamics simulations, alchemical approaches based on nonequilibrium techniques are recently emerging as a powerful method for the computation of solvation free energy of druglike compounds. Here, we present a rigorous and extensive analysis of the accuracy and precision of the method as a function of the parameters qualifying the nonequilibrium alchemical protocol (e.g.