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Academic and pharmaceutical industry research are both key for progresses in the field of molecular machine learning. Despite common open research questions and long-term goals, the nature and scope of investigations typically differ between academia and industry. Herein, we highlight the opportunities that machine learning models offer to accelerate and improve compound selection. All parts of the model life cycle are discussed, including data preparation, model building, validation, and deployment. Main challenges in molecular machine learning as well as differences between academia and industry are highlighted. Furthermore, application aspects in the design-make-test-analyze cycle are discussed. We close with strategies that could improve collaboration between academic and industrial institutions and will advance the field even further.

A hallmark of N-linked glycosylation in the secretory compartments of eukaryotic cells is the sequential remodeling of an initially uniform oligosaccharide to a site-specific, heterogeneous ensemble of glycostructures on mature proteins. To understand site-specific processing, we used protein disulfide isomerase (PDI), a model protein with five glycosylation sites, for molecular dynamics (MD) simulations and compared the result to a biochemical in vitro analysis with four different glycan processing enzymes. As predicted by an analysis of the accessibility of the N-glycans for their processing enzymes derived from the MD simulations, N-glycans at different glycosylation sites showed different kinetic properties for the processing enzymes. In addition, altering the tertiary structure of the glycoprotein PDI affected its N-glycan remodeling in a site-specific way. We propose that the observed differential N-glycan reactivities depend on the surrounding protein tertiary structure and lead to different glycan structures in the same protein through kinetically controlled processing pathways.

Experimental determination of the absolute stereochemistry of chiral molecules has been a fundamental challenge in natural sciences for decades. Vibrational circular dichroism (VCD) spectroscopy represents an attractive alternative to traditional methods like X-ray crystallography due to the use of molecules in solution. The interpretation of measured VCD spectra and thus the assignment of the absolute configuration relies on quantum-mechanical calculations. While such calculations are straightforward for rigid molecules with a single conformation, the need to estimate the correct conformational ensemble and energy landscape to obtain the appropriate theoretical spectra poses significant challenges for flexible molecules. In this work, we present the development of a VCD spectra alignment (VSA) algorithm to compare theoretical and experimental VCD spectra. The algorithm determines which enantiomer is more likely to reproduce the experimental spectrum and thus allows the correct assignment of the absolute stereochemistry. The VSA algorithm is successfully applied to determine the absolute chirality of highly flexible molecules, including commercial drug substances. Furthermore, we show that the computational cost can be reduced by performing the full frequency calculation only for a reduced set of conformers. The presented approach has the potential to allow the determination of the absolute configuration of chiral molecules in a robust and efficient manner.

Experimental determination of the absolute stereochemistry of chiral molecules has been a fundamental challenge in natural sciences for decades. Vibrational circular dichroism (VCD) spectroscopy represents an attractive alternative to traditional methods like X-ray crystallography due to the use of molecules in solution. The interpretation of measured VCD spectra and thus the assignment of the absolute configuration relies on quantum-mechanical calculations. While such calculations are straightforward for rigid molecules with a single conformation, the need to estimate the correct conformational ensemble and energy landscape to obtain the appropriate theoretical spectra poses significant challenges for flexible molecules. In this work, we present the development of a VCD spectra alignment (VSA) algorithm to compare theoretical and experimental VCD spectra. The algorithm determines which enantiomer is more likely to reproduce the experimental spectrum and thus allows the correct assignment of the absolute stereochemistry. The VSA algorithm is successfully applied to determine the absolute chirality of highly flexible molecules, including commercial drug substances. Furthermore, we show that the computational cost can be reduced by performing the full frequency calculation only for a reduced set of conformers. The presented approach has the potential to allow the determination of the absolute configuration of chiral molecules in a robust and efficient manner.

Postprint (published version)

Simulation of the dynamics of a protein in aqueous solution using an atomic model for both the protein and the many water molecules is still computationally extremely demanding considering the time scale of protein motions. The use of supra-atomic or supra-molecular coarse-grained (CG) models may enhance the computational efficiency, but inevitably at the cost of reduced accuracy. Coarse-graining solvent degrees of freedom is likely to yield a favourable balance between reduced accuracy and enhanced computational speed. Here, the use of a supra-molecular coarse-grained water model that largely preserves the thermodynamic and dielectric properties of atomic level fine-grained (FG) water in molecular dynamics simulations of an atomic model for four proteins is investigated. The results of using an FG, a CG, an implicit, or a vacuum solvent environment of the four proteins are compared, and for hen egg-white lysozyme a comparison to NMR data is made. The mixed-grained simulations do not show large differences compared to the FG atomic level simulations, apart from an increased tendency to form hydrogen bonds between long side chains, which is due to the reduced ability of the supra-molecular CG beads that represent five FG water molecules to make solvent-protein hydrogen bonds. But, the mixed-grained simulations are at least an order of magnitude faster than the atomic level ones

Water molecules in the binding pocket of a protein and their role in ligand binding have increasingly raised interest in recent years. Displacement of such water molecules by ligand atoms can be either favourable or unfavourable for ligand binding depending on the change in free enthalpy. In this study, we investigate the displacement of water molecules by an apolar probe in the binding pocket of two proteins, cyclin-dependent kinase 2 and tRNA-guanine transglycosylase, using the method of enveloping distribution sampling (EDS) to obtain free enthalpy differences. In both cases, a ligand core is placed inside the respective pocket and the remaining water molecules are converted to apolar probes, both individually and in pairs. The free enthalpy difference between a water molecule and a CH3 group at the same location in the pocket in comparison to their presence in bulk solution calculated from EDS molecular dynamics simulations corresponds to the binding free enthalpy of CH3 at this location. From the free enthalpy difference and the enthalpy difference, the entropic contribution of the displacement can be obtained too. The overlay of the resulting occupancy volumes of the water molecules with crystal structures of analogous ligands shows qualitative correlation between experimentally measured inhibition constants and the calculated free enthalpy differences. Thus, such an EDS analysis of the water molecules in the binding pocket may give valuable insight for potency optimization in drug design

Docking algorithms for computer-aided drug discovery and design often ignore or restrain the flexibility of the receptor, which may lead to a loss of accuracy of the relative free enthalpies of binding. In order to evaluate the contribution of receptor flexibility to relative binding free enthalpies, two host-guest systems have been examined: inclusion complexes of α-cyclodextrin (αCD) with 1-chlorobenzene (ClBn), 1-bromobenzene (BrBn) and toluene (MeBn), and complexes of DNA with the minor-groove binding ligands netropsin (Net) and distamycin (Dist). Molecular dynamics simulations and free energy calculations reveal that restraining of the flexibility of the receptor can have a significant influence on the estimated relative ligand-receptor binding affinities as well as on the predicted structures of the biomolecular complexes. The influence is particularly pronounced in the case of flexible receptors such as DNA, where a 50% contribution of DNA flexibility towards the relative ligand-DNA binding affinities is observed. The differences in the free enthalpy of binding do not arise only from the changes in ligand-DNA interactions but also from changes in ligand-solvent interactions as well as from the loss of DNA configurational entropy upon restraining

New parameter sets of the GROMOS biomolecular force field, 54A7 and 54B7, are introduced. These parameter sets summarise some previously published force field modifications: The 53A6 helical propensities are corrected through new φ/ψ torsional angle terms and a modification of the N-H, C=O repulsion, a new atom type for a charged −CH3 in the choline moiety is added, the Na+ and Cl− ions are modified to reproduce the free energy of hydration, and additional improper torsional angle types for free energy calculations involving a chirality change are introduced. The new helical propensity modification is tested using the benchmark proteins hen egg-white lysozyme, fox1 RNA binding domain, chorismate mutase and the GCN4-p1 peptide. The stability of the proteins is improved in comparison with the 53A6 force field, and good agreement with a range of primary experimental data is obtained

Simulation of the dynamics of a protein in aqueous solution using an atomic model for both the protein and the many water molecules is still computationally extremely demanding considering the time scale of protein motions. The use of supra-atomic or supra-molecular coarse-grained (CG) models may enhance the computational efficiency, but inevitably at the cost of reduced accuracy. Coarse-graining solvent degrees of freedom is likely to yield a favourable balance between reduced accuracy and enhanced computational speed. Here, the use of a supra-molecular coarse-grained water model that largely preserves the thermodynamic and dielectric properties of atomic level fine-grained (FG) water in molecular dynamics simulations of an atomic model for four proteins is investigated. The results of using an FG, a CG, an implicit, or a vacuum solvent environment of the four proteins are compared, and for hen egg-white lysozyme a comparison to NMR data is made. The mixed-grained simulations do not show large differences compared to the FG atomic level simulations, apart from an increased tendency to form hydrogen bonds between long side chains, which is due to the reduced ability of the supra-molecular CG beads that represent five FG water molecules to make solvent-protein hydrogen bonds. But, the mixed-grained simulations are at least an order of magnitude faster than the atomic level ones

Water molecules in the binding pocket of a protein and their role in ligand binding have increasingly raised interest in recent years. Displacement of such water molecules by ligand atoms can be either favourable or unfavourable for ligand binding depending on the change in free enthalpy. In this study, we investigate the displacement of water molecules by an apolar probe in the binding pocket of two proteins, cyclin-dependent kinase 2 and tRNA-guanine transglycosylase, using the method of enveloping distribution sampling (EDS) to obtain free enthalpy differences. In both cases, a ligand core is placed inside the respective pocket and the remaining water molecules are converted to apolar probes, both individually and in pairs. The free enthalpy difference between a water molecule and a CH3 group at the same location in the pocket in comparison to their presence in bulk solution calculated from EDS molecular dynamics simulations corresponds to the binding free enthalpy of CH3 at this location. From the free enthalpy difference and the enthalpy difference, the entropic contribution of the displacement can be obtained too. The overlay of the resulting occupancy volumes of the water molecules with crystal structures of analogous ligands shows qualitative correlation between experimentally measured inhibition constants and the calculated free enthalpy differences. Thus, such an EDS analysis of the water molecules in the binding pocket may give valuable insight for potency optimization in drug design