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. Their potency was estimated by using four popular docking scoring functions. Common docking hits for NSP13 were finally tested using advanced nonequilibrium alchemical techniques for binding free energy calculations on a high-performing parallel cluster. Four potential NSP13 inhibitors with potency from submicrimolar to nanomolar were finally identified.

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. Performing a preliminary Hamiltonian replica exchange enhances the sampling of slow degrees of freedom of the ligand and the target, allowing the system to populate the correct binding pose when starting from an approximate docking pose. We apply the method on 6 ligands of the first bromodomain of the BRD4 bromodomain-containing protein. For each ligand, we start nonequilibrium alchemical transformations from both the crystallographic pose and the top-scoring docked pose that are often significantly different. We show that the method produces statistically equivalent binding free energies, making it a useful tool for computational drug discovery pipelines.

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. Canonical sampling of the associated end-state is efficiently obtained by performing a Hamiltonian replica exchange simulation of the gas-phase solute molecule alone, combined with equilibrium configurations of the solvent. Before submitting the prediction, a pre-assessment of the method and of the force field was made by comparing with the known experimental counterpart the calculated octanol-water partition coefficients using different set of atomic charges. The analysis allowed to optimize our blind prediction for the toluene-water partition coefficients, providing at the same time valid clues for improving the performance and reliability of the non-polarizable force field in free energy calculations of drug-receptor systems.

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. The article is supplemented by a detailed online tutorial, available at https://procacci.github.io/vdssb_gromacs/NE-RDFE and by a public Zenodo repository available at https://zenodo.org/record/6982932.

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. Correct sampling can be restored in λ-hopping simulation by the addition of a "hot-zone" scaling factor to the λ-stratification (FEP+ approach), provided that the additive hot-zone scaling factors are tuned and optimized using preliminary ordinary replica-exchange simulation of the end-states.

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. The dissipation of the NE process, negatively affecting accuracy, has been minimized by introducing a smooth regularization based on shifted electrostatic and Lennard-Jones non bonded potentials. As a challenging testbed, we have applied our method to the calculation of the RBFEs in the recent host-guest SAMPL international contest, featuring a macrocyclic host with guests varying in the net charge, volume, and chemical fingerprints. Closure validation has been successfully verified in cycles involving compounds with disparate Tanimoto coefficients, volume, and net charge. NE-RBFE is specifically tailored for massively parallel facilities and can be used with little or no code modification on most of the popular software packages supporting nonequilibrium alchemical simulations, such as Gromacs, Amber, NAMD, or OpenMM. The proposed methodology bypasses most of the entanglements and limitations of the standard single topology RBFE approach for strictly congeneric series based on free-energy perturbation, such as slowly relaxing cavity water, sampling issues along the alchemical stratification, and the need for highly overlapping molecular fingerprints.

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., J. Chem. Theory Comput. 16, 7160 (2020)]. As far as Pearson and Kendall coefficients are concerned, performances were acceptable and, in general, better than those we submitted for calixarenes, cucurbituril-like open cavitand, and beta-cyclodextrines in previous SAMPL host-guest challenges, confirming the reliability of nonequilibrium approaches for absolute binding free energy calculations. In comparison with previous submissions, we found a rather large mean signed error that we attribute to the way the finite charge correction was addressed through the assumption of a neutralizing background plasma.

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. Nonbonded interaction between the inhibitor and the residues of the binding pocket, as well as with water molecules on the protein surface, have been characterized using two different force fields and the two possible protonation states of the main protease catalytic dyad HIS41-CYS145. When the catalytic dyad is in the neutral state, the non-covalent binding is likely to be stronger. Molecular dynamics simulations seems to lend support for an inhibitory mechanism in two steps: a first non-covalent addition with the dyad in neutral form and then the formation of the thiolate-imidazolium ion pair and the ligand relocation for finalising the electrophilic attack.

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. The procedure has been applied to the calculation of the absolute dissociation free energy of PF-07321332, an oral antiviral proposed by Pfizer, with the main protease (3CLpro) of SARS-CoV-2.

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. Performances were acceptable and similar in accuracy to those we submitted for Gibb's Deep Cavity Cavitands in the previous SAMPL6 host-guest challenge, confirming the reliability of the computational approach and exposing, in some cases, some important deficiencies of the GAFF2 non-polarizable force field.

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.

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. A biotinylated oligonucleotide sequence (20mer-BIO) complementary to the aptamer was chosen to carry out a competitive format. Graphite screen-printed electrodes (GSPEs) were electrochemically modified with polyaniline and gold nanoparticles (AuNPs@PANI) by means of cyclic voltammetry (CV) and worked as a scaffold for the immobilization of the DNA aptamer. Solutions containing increasing concentrations of DON and a fixed amount of 20mer-BIO were dropped onto the aptasensor surface: the resulting hybrids were labeled with an alkaline phosphatase (ALP) conjugate to hydrolyze 1-naphthyl phosphate (1-NPP) substrate into 1-naphthol product, detected by differential pulse voltammetry (DPV). According to its competitive format, the aptasensor response was signal-off in the range 5.0-30.0 ng·mL-1 DON. A detection limit of 3.2 ng·mL-1 was achieved within a 1-hour detection time. Preliminary experiments on maize flour samples spiked with DON yielded good recovery values.

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 (3CLpro) of SARS-CoV-2. The core structures of 3CLpro ligands were previously identified using a multimodal structure-based ligand design in combination with docking techniques. The calculated binding free energies for four additional ligands with known activity (either for SARS-CoV or SARS-CoV-2 main protease) are also reported. The nature of binding in the 3CLpro active site and the involved residues besides the CYS-HYS catalytic dyad have been thoroughly characterized by enhanced sampling simulations of the bound state. We have identified several noncongeneric compounds with predicted low micromolar activity for 3CLpro inhibition, which may constitute possible lead compounds for the development of antiviral agents in Covid-19 treatment.

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.

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. The new zinc-binding ASP and GLU residues, along with the CYS and HIS zinc-binding residues, parameterized in a recent work [Macchiagodena M.;J. Chem. Inf. Model.2019, 59, 3803-3816], allow users to reliably simulate 96% of the Zn-proteins available in the Protein Data Bank. The upgraded force field for zinc(II)-bound residues has been tested performing molecular dynamics simulations with an explicit solvent and comparing the structural information with experimental data for five different proteins binding zinc(II) with GLU, ASP, HIS, and CYS. We further validated our approach by evaluating the binding free energy of (R)-2-benzyl-3-nitropropanoic acid to carboxypeptidase A using a recently developed nonequilibrium alchemical method. We demonstrated that in this setting it is crucial to take into account polarization effects also on the metal-bound inhibitor.

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. The involvement of FKBP12 dysregulation in the aberrant aggregation of disordered proteins pinpoints this protein as a possible therapeutic target and, at the same time, as a predictive biomarker for early diagnosis in neurodegeneration, calling for the development of reliable, fast and cost-effective detection methods in body fluids for community-based screening campaigns.