Hybrid MPI/OpenMP Implementation of the ORAC Molecular Dynamics Program for Generalized Ensemble and Fast Switching Alchemical Simulations

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. 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.

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.

Open-Source Machine Learning in Computational Chemistry

The field of computational chemistry has seen a significant increase in the integration of machine learning concepts and algorithms. In this Perspective, we surveyed 179 open-source software projects, with corresponding peer-reviewed papers published within the last 5 years, to better understand the topics within the field being investigated by machine learning approaches. For each project, we provide a short description, the link to the code, the accompanying license type, and whether the training data and resulting models are made publicly available. Based on those deposited in GitHub repositories, the most popular employed Python libraries are identified. We hope that this survey will serve as a resource to learn about machine learning or specific architectures thereof by identifying accessible codes with accompanying papers on a topic basis. To this end, we also include computational chemistry open-source software for generating training data and fundamental Python libraries for machine learning. Based on our observations and considering the three pillars of collaborative machine learning work, open data, open source (code), and open models, we provide some suggestions to the community.

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.

Molecular Modelling of Ionic Liquids: Situations When Charge Scaling Seems Insufficient

Charge scaling as an effective solution to the experiment-computation disagreement in molecular modelling of ionic liquids (ILs) could bring the computational results close to the experimental reference for various thermodynamic properties. According to the large-scale benchmark calculations of mass density, solvation, and water-ILs transfer-free energies in our series of papers, the charge-scaling factor of 0.8 serves as a near-optimal option generally applicable to most ILs, although a system-dependent parameter adjustment could be attempted for further improved performance. However, there are situations in which such a charge-scaling treatment would fail. Namely, charge scaling cannot really affect the simulation outcome, or minimally perturbs the results that are still far from the experimental value. In such situations, the vdW radius as an additional adjustable parameter is commonly tuned to minimize the experiment-calculation deviation. In the current work, considering two ILs from the quinuclidinium family, we investigate the impacts of this vdW-scaling treatment on the mass density and the solvation/partition thermodynamics in a fashion similar to our previous charge-scaling works, i.e., scanning the vdW-scaling factor and computing physical properties under these parameter sets. It is observed that the mass density exhibits a linear response to the vdW-scaling factor with slopes close to -1.8 g/mL. By further investigating a set of physiochemically relevant temperatures between 288 K and 348 K, we confirm the robustness of the vdW-scaling treatment in the estimation of bulk properties. The best vdW-scaling parameter for mass density would worsen the computation of solvation/partition thermodynamics, and a marginal decrease in the vdW-scaling factor is considered as an intermediate option balancing the reproductions of bulk properties and solvation thermodynamics. These observations could be understood in a way similar to the charge-scaling situation. i.e., overfitting some properties (e.g., mass density) would degrade the accuracy of the other properties (e.g., solvation free energies). Following this principle, the general guideline for applying this vdW-tuning protocol is by using values between the density-derived choice and the solvation/partition-derived solution. The charge and current vdW scaling treatments cover commonly encountered ILs, completing the protocol for accurate modelling of ILs with fixed-charge force fields.

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.

Fast and Accurate Solution of Integral Formulations of Large MQS Problems Based on Hybrid OpenMP–MPI Parallelization

This paper proposes an optimal strategy to parallelize the solution of large 3D magneto-quasi-static (MQS) problems, by combining the MPI and OpenMP approaches. The studied numerical problem comes from a weak-form integral formulation of a MQS problem and is finally cast in terms of a large linear system to be solved by means of a direct method. For this purpose, two main tasks are identified: the assembly and the inversion of the matrices. The paper focuses on the optimization of the resources required for assembling the matrices, by exploiting the feature of a hybrid OpenMP–MPI approach. Specifically, the job is shared between clusters of nodes in parallel by adopting an OpenMP paradigm at the node level and a MPI one at the process level between nodes. Compared with other solutions, such as pure MPI, this hybrid parallelization optimizes the available resources, with respect to the speed, allocated memory, and the communication between nodes. These advantages are clearly observed in the case studies analyzed in this paper, coming from the study of large plasma fusion machines, such as the fusion reactor ITER. Indeed, the MQS problems associated with such applications are characterized by a huge computational cost that requires parallel computing approaches.

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 (3CL^pro) of SARS-CoV-2.

Conformational Fluctuations in GTP-Bound K-Ras: A Metadynamics Perspective with Harmonic Linear Discriminant Analysis

Biomacromolecules often undergo significant conformational rearrangements during function. In proteins, these motions typically consist in nontrivial, concerted rearrangement of multiple flexible regions. Mechanistic, thermodynamics, and kinetic predictions can be obtained via molecular dynamics simulations, provided that the simulation time is at least comparable to the relevant time scale of the process of interest. Because of the substantial computational cost, however, plain MD simulations often have difficulty in obtaining sufficient statistics for converged estimates, requiring the use of more-advanced techniques. Central in many enhanced sampling methods is the definition of a small set of relevant degrees of freedom (collective variables) that are able to describe the transitions between different metastable states of the system. The harmonic linear discriminant analysis (HLDA) has been shown to be useful for constructing low-dimensional collective variables in various complex systems. Here, we apply HLDA to study the free-energy landscape of a monomeric protein around its native state. More precisely, we study the K-Ras protein bound to GTP, focusing on two flexible loops and on the region associated with oncogenic mutations. We perform microsecond-long biased simulations on the wild type and on G12C, G12D, G12 V mutants, describe the resulting free-energy landscapes, and compare our predictions with previous experimental and computational studies. The fast interconversion between open and closed macroscopic states and their similar thermodynamic stabilities are observed. The mutation-induced effects include the alternations of the relative stabilities of different conformational states and the introduction of many microscopic metastable states. Together, our results demonstrate the applicability of the HLDA-based protocol for the conformational sampling of multiple flexible regions in folded proteins.

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.

Non-equilibrium approach for binding free energies in cyclodextrins in SAMPL7: force fields and software

In the current work we report on our participation in the SAMPL7 challenge calculating absolute free energies of the host–guest systems, where 2 guest molecules were probed against 9 hosts-cyclodextrin and its derivatives. Our submission was based on the non-equilibrium free energy calculation protocol utilizing an averaged consensus result from two force fields (GAFF and CGenFF). The submitted prediction achieved accuracy of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${1.38}\,\hbox {kcal}/\hbox {mol}$$\end{document}1.38kcal/mol in terms of the unsigned error averaged over the whole dataset. Subsequently, we further report on the underlying reasons for discrepancies between our calculations and another submission to the SAMPL7 challenge which employed a similar methodology, but disparate ligand and water force fields. As a result we have uncovered a number of issues in the dihedral parameter definition of the GAFF 2 force field. In addition, we identified particular cases in the molecular topologies where different software packages had a different interpretation of the same force field. This latter observation might be of particular relevance for systematic comparisons of molecular simulation software packages. The aforementioned factors have an influence on the final free energy estimates and need to be considered when performing alchemical calculations.

Molecular Basis of SARS-CoV-2 Infection and Rational Design of Potential Antiviral Agents: Modeling and Simulation Approaches

The emergence in late 2019 of the coronavirus SARS-CoV-2 has resulted in the breakthrough of the COVID-19 pandemic that is presently affecting a growing number of countries. The development of the pandemic has also prompted an unprecedented effort of the scientific community to understand the molecular bases of the virus infection and to propose rational drug design strategies able to alleviate the serious COVID-19 morbidity. In this context, a strong synergy between the structural biophysics and molecular modeling and simulation communities has emerged, resolving at the atomistic level the crucial protein apparatus of the virus and revealing the dynamic aspects of key viral processes. In this Review, we focus on how in silico studies have contributed to the understanding of the SARS-CoV-2 infection mechanism and the proposal of novel and original agents to inhibit the viral key functioning. This Review deals with the SARS-CoV-2 spike protein, including the mode of action that this structural protein uses to entry human cells, as well as with nonstructural viral proteins, focusing the attention on the most studied proteases and also proposing alternative mechanisms involving some of its domains, such as the SARS unique domain. We demonstrate that molecular modeling and simulation represent an effective approach to gather information on key biological processes and thus guide rational molecular design strategies.

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^pro) of SARS-CoV-2. The core structures of 3CL^pro 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 3CL^pro 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 3CL^pro 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.

Evidence of a Low-High Density Turning Point in Liquid Water at Ordinary Temperature under Pressure: A Molecular Dynamics Study

Water has a fundamental role in important processes spanning a wide range of pressure and temperature conditions. Knowledge of structural, dynamic and thermodynamic properties of water at nonstandard conditions is a primary concern since interest in astronomical, geological, and technological processes is continuously growing. Molecular dynamics simulations allow us to study thermodynamic conditions that require sophisticated techniques and instruments, while at the same time offering the interpretation of properties at the atomic level. It is established that the behavior of water is strongly affected by the temperature and pressure conditions, determining the existence of low and high density regimes. For the first time, a thermodynamic property, isothermal compressibility, has been adopted to detect the low-high density turning point at ambient temperature in liquid water due to pressure. Molecular dynamics simulations have been performed with five three-site models, allowing us to characterize the complexity of water nature at these conditions at the atomic level.

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. Contrarily to the widespread equilibrium approaches, that yielded apparently very disparate results in the SAMPL6 challenge, all our independent prediction sets, irrespective of the adopted force field and of the adopted estimate (unidirectional or bidirectional) are, mutually, from moderately to strongly correlated.

Blocking the FKBP12 induced dendrimeric burst in aberrant aggregation of α-synuclein by using the ElteN378 synthetic inhibitor

α-Synuclein (α-syn), a disordered cytoplasmatic protein, plays a fundamental role in the pathogenesis of Parkinson’s disease (PD). Here, we have shown, using photophysical measurements, that addition of FKBP12 to α-syn solutions, dramatically accelerates protein aggregation, leading to an explosion of dendritic structures revealed by fluorescence and phase-contrast microscopy. We have further demonstrated that this aberrant α-syn aggregation can be blocked using a recently discovered non-immunosuppressive synthetic inhibitor of FKBP12, ElteN378. The role of FKBP12 and of ElteN378 in the α-syn aggregation mechanism has been elucidated using molecular dynamics simulations based on an effective coarse-grained model. The reported data not only reveal a new potent synthetic drug as a candidate for early stage treatment of α-syn dependent neurodegenerations but also pave the way to a deeper understanding of the mechanism of action of FKBP12 on α-syn oligomeric aggregation, a topic which is still controversial.

Solvation free energies via alchemical simulations: let's get honest about sampling, once more

Free energy perturbation (FEP) approaches with stratification have seen widespread and increasing use in computational studies of biologically relevant molecules. However, when the molecular systems are characterized by a complex conformational free energy landscape, the assessment of convergence remains a concern for many practitioners. The sampling problem in FEP has been authoritatively addressed in a recent perspective paper [D. Mobley, J. Comput.-Aided Mol. Des., 2012, 26, 93], incisively entitled "Let's get honest about sampling". Here, I return to the issue of sampling in the determination of the octanol-water partition coefficient for a synthetic precursor of kinase inhibitors that has been included in the recent extension of the SAMPL6 blind challenge of log P coefficients. I will show that even for this simple compound, whose conformational space is essentially dictated by two sp₃ rotable bonds connecting rigid planar units, canonical sampling using standard techniques can be surprisingly hard to achieve. I will also show how the conformational sampling problem can be effectively bypassed using unidirectional and bidirectional nonequilibrium work methods, reliably recovering the solvation energy with minimal methodological uncertainty.

Dynamic Docking: A Paradigm Shift in Computational Drug Discovery

Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD) have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking). Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress.

PrimaDORAC: A Free Web Interface for the Assignment of Partial Charges, Chemical Topology, and Bonded Parameters in Organic or Drug Molecules

We present PrimaDORAC, a simple and freely accessible web interface for generating the topology and the parameter files of organic or drug molecules to be used in molecular mechanics or molecular dynamics calculations. The interface relies on our in-house FORTRAN90 parser, working on the recently released Generalized Amber Force Field parameter set (GAFF2). AM1/BCC charges are computed using the Public Domain MOPAC7 program and the bond charge corrections (BCC) reported in Jakalian, A.; Jack, D. B.; Bayly, C. I.; J. Comp. Chem., 2002, 23, 1623-1641. The interface has been tested on about 52,000 compounds (identified with a CAS registry number) taken from the National Cancer Institute (NCI) Open Database. PrimaDORAC has been found to be very reliable, producing GAFF2 minimized structures bearing a mean root square displacement of about 0.01-0.02 nm with respect to the original CORINA-generated 3D NCI structures. As a demonstrative example, we release the full topology and parameter files, along with the AM1/BCC-GAFF2 computed in vacuo IR spectrum, for some recently discovered PARP/MCL1 inhibitors. The web interface and parser, including the sources, are part of the ORAC code (Procacci, P.; J. Chem. Inf.

MODEL

, 2016, 56, 1117-1121), distributed under the General Public License at www.chim.unifi.it/orac.