LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands.

The accurate calculation of protein/nucleic acid-ligand interactions or condensed phase properties by force field-based methods require a precise description of the energetics of intermolecular interactions. Despite the progress made in force fields, small molecule parameterization remains an open problem due to the magnitude of the chemical space; the most critical issue is the estimation of a balanced set of atomic charges with the ability to reproduce experimental properties. The LigParGen web server provides an intuitive interface for generating OPLS-AA/1.14*CM1A(-LBCC) force field parameters for organic ligands, in the formats of commonly used molecular dynamics and Monte Carlo simulation packages. This server has high value for researchers interested in studying any phenomena based on intermolecular interactions with ligands via molecular mechanics simulations. It is free and open to all at jorgensenresearch.com/ligpargen, and has no login requirements.

Porphyrin Binding to Gun4 Protein, Facilitated by a Flexible Loop, Controls Metabolite Flow through the Chlorophyll Biosynthetic Pathway.

In oxygenic phototrophs, chlorophylls, hemes, and bilins are synthesized by a common branched pathway. Given the phototoxic nature of tetrapyrroles, this pathway must be tightly regulated, and an important regulatory role is attributed to magnesium chelatase enzyme at the branching between the heme and chlorophyll pathway. Gun4 is a porphyrin-binding protein known to stimulate in vitro the magnesium chelatase activity, but how the Gun4-porphyrin complex acts in the cell was unknown. To address this issue, we first performed simulations to determine the porphyrin-docking mechanism to the cyanobacterial Gun4 structure. After correcting crystallographic loop contacts, we determined the binding site for magnesium protoporphyrin IX. Molecular modeling revealed that the orientation of α6/α7 loop is critical for the binding, and the magnesium ion held within the porphyrin is coordinated by Asn-211 residue. We also identified the basis for stronger binding in the Gun4-1 variant and for weaker binding in the W192A mutant. The W192A-Gun4 was further characterized in magnesium chelatase assay showing that tight porphyrin binding in Gun4 facilitates its interaction with the magnesium chelatase ChlH subunit. Finally, we introduced the W192A mutation into cells and show that the Gun4-porphyrin complex is important for the accumulation of ChlH and for channeling metabolites into the chlorophyll biosynthetic pathway.

A theoretical multiscale treatment of protein-protein electron transfer: The ferredoxin/ferredoxin-NADP(+) reductase and flavodoxin/ferredoxin-NADP(+) reductase systems.

In the photosynthetic electron transfer (ET) chain, two electrons transfer from photosystem I to the flavin-dependent ferredoxin-NADP(+) reductase (FNR) via two sequential independent ferredoxin (Fd) electron carriers. In some algae and cyanobacteria (as Anabaena), under low iron conditions, flavodoxin (Fld) replaces Fd as single electron carrier. Extensive mutational studies have characterized the protein-protein interaction in FNR/Fd and FNR/Fld complexes. Interestingly, even though Fd and Fld share the interaction site on FNR, individual residues on FNR do not participate to the same extent in the interaction with each of the protein partners, pointing to different electron transfer mechanisms. Despite of extensive mutational studies, only FNR/Fd X-ray structures from Anabaena and maize have been solved; structural data for FNR/Fld remains elusive. Here, we present a multiscale modelling approach including coarse-grained and all-atom protein-protein docking, the QM/MM e-Pathway analysis and electronic coupling calculations, allowing for a molecular and electronic comprehensive analysis of the ET process in both complexes. Our results, consistent with experimental mutational data, reveal the ET in FNR/Fd proceeding through a bridge-mediated mechanism in a dominant protein-protein complex, where transfer of the electron is facilitated by Fd loop-residues 40-49. In FNR/Fld, however, we observe a direct transfer between redox cofactors and less complex specificity than in Fd; more than one orientation in the encounter complex can be efficient in ET.

Ecoupling server: A tool to compute and analyze electronic couplings.

Electron transfer processes are often studied through the evaluation and analysis of the electronic coupling (EC). Since most standard QM codes do not provide readily such a measure, additional, and user-friendly tools to compute and analyze electronic coupling from external wave functions will be of high value. The first server to provide a friendly interface for evaluation and analysis of electronic couplings under two different approximations (FDC and GMH) is presented in this communication. Ecoupling server accepts inputs from common QM and QM/MM software and provides useful plots to understand and analyze the results easily. The web server has been implemented in CGI-python using Apache and it is accessible at http://ecouplingserver.bsc.es. Ecoupling server is free and open to all users without login. © 2016 Wiley Periodicals, Inc.

Conformational response to ligand binding in phosphomannomutase2: insights into inborn glycosylation disorder.

The most common glycosylation disorder is caused by mutations in the gene encoding phosphomannomutase2, producing a disease still without a cure. Phosphomannomutase2, a homodimer in which each chain is composed of two domains, requires a bisphosphate sugar (either mannose or glucose) as activator, opening a possible drug design path for therapeutic purposes. The crystal structure of human phosphomannomutase2, however, lacks bound substrate and a key active site loop. To speed up drug discovery, we present here the first structural model of a bisphosphate substrate bound to human phosphomannomutase2. Taking advantage of recent developments in all-atom simulation techniques in combination with limited and site-directed proteolysis, we demonstrated that α-glucose 1,6-bisphosphate can adopt two low energy orientations as required for catalysis. Upon ligand binding, the two domains come close, making the protein more compact, in analogy to the enzyme in the crystals from Leishmania mexicana. Moreover, proteolysis was also carried out on two common mutants, R141H and F119L. It was an unexpected finding that the mutant most frequently found in patients, R141H, although inactive, does bind α-glucose 1,6-bisphosphate and changes conformation.

Atomic level rendering of DNA-drug encounter.

Computer simulations have been demonstrated to be important for unraveling atomic mechanisms in biological systems. In this study, we show how combining unbiased molecular dynamic simulations with appropriate analysis tools can successfully describe metal-based drug interactions with DNA. To elucidate the noncovalent affinity of cisplatin's family to DNA, we performed extensive all-atom molecular dynamics simulations (3.7 µs total simulation length). The results show that the parent drug, cisplatin, has less affinity to form noncovalent adducts in the major groove than its aquo complexes. Furthermore, the relative position in which the drugs enter the major groove is dependent on the compound's net charge. Based on the simulations, we estimated noncovalent binding free energies through the use of Markov state models. In addition, and to overcome the lack of experimental information, we employed two additional methods: Molecular Mechanics Poisson-Boltzmann Surface Area (MMPB-SA) and steered molecular dynamics with the Jarzynski estimator, with an overall good agreement between the three methods. All complexes show interaction energies below 3 kcal/mol with DNA but the charged hydrolysis products have slightly more favorable binding free energies than the parent drug. Moreover, this study sets the precedent for future unbiased DNA-ligand simulations of more complex binders.

AlphaFold accelerated discovery of psychotropic agonists targeting the trace amine-associated receptor 1.

Artificial intelligence is revolutionizing protein structure prediction, providing unprecedented opportunities for drug design. To assess the potential impact on ligand discovery, we compared virtual screens using protein structures generated by the AlphaFold machine learning method and traditional homology modeling. More than 16 million compounds were docked to models of the trace amine-associated receptor 1 (TAAR1), a G protein-coupled receptor of unknown structure and target for treating neuropsychiatric disorders. Sets of 30 and 32 highly ranked compounds from the AlphaFold and homology model screens, respectively, were experimentally evaluated. Of these, 25 were TAAR1 agonists with potencies ranging from 12 to 0.03 µM. The AlphaFold screen yielded a more than twofold higher hit rate (60%) than the homology model and discovered the most potent agonists. A TAAR1 agonist with a promising selectivity profile and drug-like properties showed physiological and antipsychotic-like effects in wild-type but not in TAAR1 knockout mice. These results demonstrate that AlphaFold structures can accelerate drug discovery.

Identification of 14 Known Drugs as Inhibitors of the Main Protease of SARS-CoV-2.

A consensus virtual screening protocol has been applied to ca. 2000 approved drugs to seek inhibitors of the main protease (Mpro) of SARS-CoV-2, the virus responsible for COVID-19. 42 drugs emerged as top candidates, and after visual analyses of the predicted structures of their complexes with Mpro, 17 were chosen for evaluation in a kinetic assay for Mpro inhibition. Remarkably 14 of the compounds at 100-µM concentration were found to reduce the enzymatic activity and 5 provided IC50 values below 40 µM: manidipine (4.8 µM), boceprevir (5.4 µM), lercanidipine (16.2 µM), bedaquiline (18.7 µM), and efonidipine (38.5 µM). Structural analyses reveal a common cloverleaf pattern for the binding of the active compounds to the P1, P1', and P2 pockets of Mpro. Further study of the most active compounds in the context of COVID-19 therapy is warranted, while all of the active compounds may provide a foundation for lead optimization to deliver valuable chemotherapeutics to combat the pandemic.

Computation of protein-ligand binding free energies using quantum mechanical bespoke force fields.

A quantum mechanical bespoke molecular mechanics force field is derived for the L99A mutant of T4 lysozyme and used to compute absolute binding free energies of six benzene analogs to the protein. Promising agreement between theory and experiment highlights the potential for future use of system-specific force fields in computer-aided drug design.

Robust Free Energy Perturbation Protocols for Creating Molecules in Solution.

Accurate methods to estimate free energies play an important role for studying diverse condensed-phase problems in chemistry and biochemistry. The most common methods used in conjunction with molecular dynamics (MD) and Monte Carlo statistical mechanics (MC) simulations are free energy perturbation (FEP) and thermodynamic integration (TI). For common applications featuring the conversion of one molecule to another, simulations are run in stages or multiple "λ-windows" to promote convergence of the results. For computation of absolute free energies of solvation or binding, calculations are needed in which the solute is typically annihilated in the solvent and in the complex. The present work addresses identification of optimal protocols for such calculations, specifically, the creation/annihilation of organic molecules in aqueous solution. As is common practice, decoupling of the perturbations for electrostatic and Lennard-Jones interactions was performed. Consistent with earlier reports, FEP calculations for molecular creations are much more efficient, while annihilations require many more windows and may converge to incorrect values. Strikingly, we find that as few as four windows may be adequate for creation calculations for solutes ranging from argon to ethylbenzene. For a larger druglike molecule, MIF180, which contains 22 non-hydrogen atoms and three rotatable bonds, 10 creation windows are found to be adequate to yield the correct free energy of hydration. Convergence is impeded with procedures that use any sampling in the annihilation direction, and there is no need for postprocessing methods such as the Bennett acceptance ratio (BAR).

Absolute Free Energy of Binding Calculations for Macrophage Migration Inhibitory Factor in Complex with a Druglike Inhibitor.

Calculation of the absolute free energy of binding (ΔGbind) for a complex in solution is challenging owing to the need for adequate configurational sampling and an accurate energetic description, typically with a force field (FF). In this study, Monte Carlo (MC) simulations with improved side-chain and backbone sampling are used to assess ΔGbind for the complex of a druglike inhibitor (MIF180) with the protein macrophage migration inhibitory factor (MIF) using free energy perturbation (FEP) calculations. For comparison, molecular dynamics (MD) simulations were employed as an alternative sampling method for the same system. With the OPLS-AA/M FF and CM5 atomic charges for the inhibitor, the ΔGbind results from the MC/FEP and MD/FEP simulations, -8.80 ± 0.74 and -8.46 ± 0.85 kcal/mol, agree well with each other and with the experimental value of -8.98 ± 0.28 kcal/mol. The convergence of the results and analysis of the trajectories indicate that sufficient sampling was achieved for both approaches. Repeating the MD/FEP calculations using current versions of the CHARMM and AMBER FFs led to a 6 kcal/mol range of computed ΔGbind. These results show that calculation of accurate ΔGbind for large ligands is both feasible and numerically equivalent, within error limits, using either methodology.

Enhanced Monte Carlo Methods for Modeling Proteins Including Computation of Absolute Free Energies of Binding.

The generation of a complete ensemble of geometrical configurations is required to obtain reliable estimations of absolute binding free energies by alchemical free energy methods. Molecular dynamics (MD) is the most popular sampling method, but the representation of large biomolecular systems may be incomplete owing to energetic barriers that impede efficient sampling of the configurational space. Monte Carlo (MC) methods can possibly overcome this issue by adapting the attempted movement sizes to facilitate transitions between alternative local-energy minima. In this study, we present an MC statistical mechanics algorithm to explore the protein-ligand conformational space with emphasis on the motions of the protein backbone and side chains. The parameters for each MC move type were optimized to better reproduce conformational distributions of 18 dipeptides and the well-studied T4-lysozyme L99A protein. Next, the performance of the improved MC algorithms was evaluated by computing absolute free energies of binding for L99A lysozyme with benzene and seven analogs. Results for benzene with L99A lysozyme from MD and the optimized MC protocol were found to agree within 0.6 kcal/mol, while a mean unsigned error of 1.2 kcal/mol between MC results and experiment was obtained for the seven benzene analogs. Significant advantages in computation speed are also reported with MC over MD for similar extents of configurational sampling.

New Monte Carlo Based Technique To Study DNA-Ligand Interactions.

We present a new all-atom Monte Carlo technique capable of performing quick and accurate DNA-ligand conformational sampling. In particular, and using the PELE software as a frame, we have introduced an additional force field, an implicit solvent, and an anisotropic network model to effectively map the DNA energy landscape. With these additions, we successfully generated DNA conformations for a test set composed of six DNA fragments of A-DNA and B-DNA. Moreover, trajectories generated for cisplatin and its hydrolysis products identified the best interacting compound and binding site, producing analogous results to microsecond molecular dynamics simulations. Furthermore, a combination of the Monte Carlo trajectories with Markov State Models produced noncovalent binding free energies in good agreement with the published molecular dynamics results, at a significantly lower computational cost. Overall our approach will allow a quick but accurate sampling of DNA-ligand interactions.

Direct Measurement of the Nanomechanical Stability of a Redox Protein Active Site and Its Dependence upon Metal Binding.

The structural basis of the low reorganization energy of cupredoxins has long been debated. These proteins reconcile a conformationally heterogeneous and exposed metal-chelating site with the highly rigid copper center required for efficient electron transfer. Here we combine single-molecule mechanical unfolding experiments with statistical analysis and computer simulations to show that the metal-binding region of apo-azurin is mechanically flexible and that high mechanical stability is imparted by copper binding. The unfolding pathway of the metal site depends on the pulling residue and suggests that partial unfolding of the metal-binding site could be facilitated by the physical interaction with certain regions of the redox protein.

Tryptogalinin is a tick Kunitz serine protease inhibitor with a unique intrinsic disorder.

BACKGROUND: A salivary proteome-transcriptome project on the hard tick Ixodes scapularis revealed that Kunitz peptides are the most abundant salivary proteins. Ticks use Kunitz peptides (among other salivary proteins) to combat host defense mechanisms and to obtain a blood meal. Most of these Kunitz peptides, however, remain functionally uncharacterized, thus limiting our knowledge about their biochemical interactions. RESULTS: We discovered an unusual cysteine motif in a Kunitz peptide. This peptide inhibits several serine proteases with high affinity and was named tryptogalinin due to its high affinity for ß-tryptase. Compared with other functionally described peptides from the Acari subclass, we showed that tryptogalinin is phylogenetically related to a Kunitz peptide from Rhipicephalus appendiculatus, also reported to have a high affinity for ß-tryptase. Using homology-based modeling (and other protein prediction programs) we were able to model and explain the multifaceted function of tryptogalinin. The N-terminus of the modeled tryptogalinin is detached from the rest of the peptide and exhibits intrinsic disorder allowing an increased flexibility for its high affinity with its inhibiting partners (i.e., serine proteases). CONCLUSIONS: By incorporating experimental and computational methods our data not only describes the function of a Kunitz peptide from Ixodes scapularis, but also allows us to hypothesize about the molecular basis of this function at the atomic level.