Parameterization of General Organic Polymers within the Open Force Field Framework.

Polymer and chemically modified biopolymer systems present unique challenges to traditional molecular simulation preparation workflows. First, typical polymer and biomolecular input formats, such as Protein Data Bank (PDB) files, lack adequate chemical information needed for the parameterization of new chemistries. Second, polymers are typically too large for accurate partial charge generation methods. In this work, we employ direct chemical perception through the Open Force Field toolkit to create a flexible polymer simulation workflow for organic polymers, encompassing everything from biopolymers to soft materials. We propose and test a new input specification for monomer information that can, along with a 3D conformational geometry, parametrize and simulate most soft-material systems within the same workflow used for smaller ligands. The monomer format encompasses a subset of the SMIRKS substructure query language to uniquely identify chemical information and repeating charges in underspecified systems through matching atomic connectivity. This workflow is combined with several different approaches for automatic partial-charge generation for larger systems. As an initial proof of concept, a variety of diverse polymeric systems were parametrized with the Open Force Field toolkit, including functionalized proteins, DNA, homopolymers, cross-linked systems, and sugars. Additionally, shape properties and radial distribution functions were computed from molecular dynamics simulations of poly(ethylene glycol), polyacrylamide, and poly(N-isopropylacrylamide) homopolymers in aqueous solution and compared to previous simulation results in order to demonstrate a start-to-finish workflow for simulation and property prediction. We expect that these tools will greatly expedite the day-to-day computational research of soft-matter simulations and create a robust atomic-scale polymer specification in conjunction with existing polymer structural notations.

Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale.

The development of accurate transferable force fields is key to realizing the full potential of atomistic modeling in the study of biological processes such as protein-ligand binding for drug discovery. State-of-the-art transferable force fields, such as those produced by the Open Force Field Initiative, use modern software engineering and automation techniques to yield accuracy improvements. However, force field torsion parameters, which must account for many stereoelectronic and steric effects, are considered to be less transferable than other force field parameters and are therefore often targets for bespoke parametrization. Here, we present the Open Force Field QCSubmit and BespokeFit software packages that, when combined, facilitate the fitting of torsion parameters to quantum mechanical reference data at scale. We demonstrate the use of QCSubmit for simplifying the process of creating and archiving large numbers of quantum chemical calculations, by generating a dataset of 671 torsion scans for druglike fragments. We use BespokeFit to derive individual torsion parameters for each of these molecules, thereby reducing the root-mean-square error in the potential energy surface from 1.1 kcal/mol, using the original transferable force field, to 0.4 kcal/mol using the bespoke version. Furthermore, we employ the bespoke force fields to compute the relative binding free energies of a congeneric series of inhibitors of the TYK2 protein, and demonstrate further improvements in accuracy, compared to the base force field (MUE reduced from 0.560.390.77 to 0.420.280.59 kcal/mol and R2 correlation improved from 0.720.350.87 to 0.930.840.97).

Collaborative Assessment of Molecular Geometries and Energies from the Open Force Field.

Force fields form the basis for classical molecular simulations, and their accuracy is crucial for the quality of, for instance, protein-ligand binding simulations in drug discovery. The huge diversity of small-molecule chemistry makes it a challenge to build and parameterize a suitable force field. The Open Force Field Initiative is a combined industry and academic consortium developing a state-of-the-art small-molecule force field. In this report, industry members of the consortium worked together to objectively evaluate the performance of the force fields (referred to here as OpenFF) produced by the initiative on a combined public and proprietary dataset of 19,653 relevant molecules selected from their internal research and compound collections. This evaluation was important because it was completely blind; at most partners, none of the molecules or data were used in force field development or testing prior to this work. We compare the Open Force Field "Sage" version 2.0.0 and "Parsley" version 1.3.0 with GAFF-2.11-AM1BCC, OPLS4, and SMIRNOFF99Frosst. We analyzed force-field-optimized geometries and conformer energies compared to reference quantum mechanical data. We show that OPLS4 performs best, and the latest Open Force Field release shows a clear improvement compared to its predecessors. The performance of established force fields such as GAFF-2.11 was generally worse. While OpenFF researchers were involved in building the benchmarking infrastructure used in this work, benchmarking was done entirely in-house within industrial organizations and the resulting assessment is reported here. This work assesses the force field performance using separate benchmarking steps, external datasets, and involving external research groups. This effort may also be unique in terms of the number of different industrial partners involved, with 10 different companies participating in the benchmark efforts.

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs.

Community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single program. The Quantum Chemistry Common Driver and Databases (QCDB) project provides such capability through an application programming interface (API) that facilitates interoperability across multiple quantum chemistry software packages. In tandem with the Molecular Sciences Software Institute and their Quantum Chemistry Archive ecosystem, the unique functionalities of several CMS programs are integrated, including CFOUR, GAMESS, NWChem, OpenMM, Psi4, Qcore, TeraChem, and Turbomole, to provide common computational functions, i.e., energy, gradient, and Hessian computations as well as molecular properties such as atomic charges and vibrational frequency analysis. Both standard users and power users benefit from adopting these APIs as they lower the language barrier of input styles and enable a standard layout of variables and data. These designs allow end-to-end interoperable programming of complex computations and provide best practices options by default.

Blood Pressure after Endovascular Therapy for Ischemic Stroke (BEST): A Multicenter Prospective Cohort Study.

Background and Purpose- To identify the specific post-endovascular stroke therapy (EVT) peak systolic blood pressure (SBP) threshold that best discriminates good from bad functional outcomes (a priori hypothesized to be 160 mm Hg), we conducted a prospective, multicenter, cohort study with a prespecified analysis plan. Methods- Consecutive adult patients treated with EVT for an anterior ischemic stroke were enrolled from November 2017 to July 2018 at 12 comprehensive stroke centers accross the United States. All SBP values within 24 hours post-EVT were recorded. Using Youden index, the threshold of peak SBP that best discriminated primary outcome of dichotomized 90-day modified Rankin Scale score (0-2 versus 3-6) was identified. Association of this SBP threshold with the outcomes was quantified using multiple logistic regression. Results- Among 485 enrolled patients (median age, 69 [interquartile range, 57-79] years; 51% females), a peak SBP of 158 mm Hg was associated with the largest difference in the dichotomous modified Rankin Scale score (absolute risk reduction of 19%). Having a peak SBP >158 mm Hg resulted in an increased likelihood of modified Rankin Scale score 3 to 6 (odds ratio, 2.24 [1.52-3.29], P<0.01; adjusted odds ratio, 1.29 [0.81-2.06], P=0.28, after adjustment for prespecified variables). Conclusions- A peak post-EVT SBP of 158 mm Hg was prospectively identified to best discriminate good from bad functional outcome. Those with a peak SBP >158 had an increased likelihood of having a bad outcome in unadjusted, but not in adjusted analysis. The observed effect size was similar to prior studies. This finding should undergo further testing in a future randomized trial of goal-targeted post-EVT antihypertensive treatment.

Determinants of Oligonucleotide Selectivity of APOBEC3B.

APOBEC3B (A3B) is a prominent source of mutation in many cancers. To date, it has been difficult to capture the native protein-DNA interactions that confer A3B's substrate specificity by crystallography due to the highly dynamic nature of wild-type A3B active site. We use computational tools to restore a recent crystal structure of a DNA-bound A3B C-terminal domain mutant construct to its wild type sequence, and run molecular dynamics simulations to study its substrate recognition mechanisms. Analysis of these simulations reveal dynamics of the native A3Bctd-oligonucleotide interactions, including the experimentally inaccessible loop 1-oligonucleotide interactions. A second series of simulations in which the target cytosine nucleotide was computationally mutated from a deoxyribose to a ribose show a change in sugar ring pucker, leading to a rearrangement of the binding site and revealing a potential intermediate in the binding pathway. Finally, apo simulations of A3B, starting from the DNA-bound open state, experience a rapid and consistent closure of the binding site, reaching conformations incompatible with substrate binding. This study reveals a more realistic and dynamic view of the wild type A3B binding site and provides novel insights for structure-guided design efforts for A3B.

Comparing Outcomes of Patients With Idiopathic Subarachnoid Hemorrhage by Stratifying Perimesencephalic Bleeding Patterns.

BACKGROUND: To determine the clinical outcomes of perimesencephalic subarachnoid hemorrhages based on the computed tomography (CT) bleeding patterns. METHODS: This retrospective cohort study included: (1) patients (≥18 years) admitted to a comprehensive stroke center (January 2015-May 2018), (2) with angiography-negative, nontraumatic subarachnoid hemorrhage in a perimesencephalic or diffuse bleeding pattern, and (3) had CT imaging performed in ≤ 72 hours of symptom onset. Patients were stratified by location of bleeding on CT: Peri-1: focal prepontine hemorrhage; Peri-2: prepontine with suprasellar cistern +/- intraventricular extension; and diffuse. RESULTS: Of the 39 patients included, 13 were Peri-1, 11 were Peri-2, and 15 were diffuse. The majority were male (n = 26), with a mean (standard deviation) age of 55.3 (11.3) years, who often presented with headache (n = 37) and nausea (n = 28). Overall, patients in Peri-1 were significantly less likely to have hydrocephalus compared to Peri-2 and dSAH (P= .003), and 4 patients required an external ventricular drain. Five patients developed symptomatic vasospasm. Patients in Peri-1, compared to Peri-2 and diffuse, had a significantly shorter median neuro critical care unit length of stay (LOS) and hospital LOS. Most patients (n = 35) had a discharge modified Rankin Score between 0 and 2 with no significant differences found between groups. CONCLUSION: These data suggest that patients with the best clinical course were those in Peri-1, followed by Peri-2, and then diffuse. Because these patients often present with similar clinical signs, stratifying by hemorrhage pattern may help clinicians predict which patients with perimesencephalic subarachnoid hemorrhage develop complications.

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

Efficient CRISPR-Cas9-mediated genome editing in Plasmodium falciparum.

Malaria is a major cause of global morbidity and mortality, and new strategies for treating and preventing this disease are needed. Here we show that the Streptococcus pyogenes Cas9 DNA endonuclease and single guide RNAs (sgRNAs) produced using T7 RNA polymerase (T7 RNAP) efficiently edit the Plasmodium falciparum genome. Targeting the genes encoding native knob-associated histidine-rich protein (kahrp) and erythrocyte binding antigen 175 (eba-175), we achieved high (≥ 50-100%) gene disruption frequencies within the usual time frame for generating transgenic parasites.

Long-Term Survival after Complete Surgical Resection and Adjuvant Immunotherapy for Distant Melanoma Metastases.

BACKGROUND: This phase III study was undertaken to evaluate the efficacy of an allogeneic whole-cell vaccine (Canvaxin™) plus bacillus Calmette-Guerin (BCG) after complete resection of stage IV melanoma. METHODS: After complete resection of ≤5 distant metastases, patients were randomly assigned to BCG+Canvaxin (BCG/Cv) or BCG+placebo (BCG/Pl). The primary endpoint was overall survival (OS); secondary endpoints were disease-free survival (DFS), and immune response measured by skin test (ClinicalTrials.gov identifier: NCT00052156). RESULTS: Beginning in May 1998, 496 patients were randomized. In April 2005, the Data Safety Monitoring Board recommended stopping enrollment due to a low probability of efficacy. At that time, median OS and 5-year OS rate were 38.6 months and 44.9%, respectively, for BCG/Pl versus 31.4 months and 39.6% in the BCG/Cv group (hazard ratio (HR), 1.18; p = 0.250). Follow-up was extended at several trial sites through March 2010. Median OS and 5-year and 10-year survival was 39.1 months, 43.3 and 33.3%, respectively, for BCG/Pl versus 34.9 months, 42.5 and 36.4%, in the BCG/Cv group (HR 1.053; p = 0.696). Median DFS, 5- and 10-year DFS were 7.6 months, 23.8 and 21.7%, respectively, for BCG/Pl versus 8.5 months, 30.0%, and 30.0%, respectively, for the BCG/Cv group (HR 0.882; p = 0.260). Positive DTH skin testing correlated with increased survival. DISCUSSION: In this, the largest study of postsurgical adjuvant therapy for stage IV melanoma reported to date, BCG/Cv did not improve outcomes over BCG/placebo. Favorable long-term survival among study patients suggests that metastasectomy should be considered for selected patients with stage IV melanoma.

A Four-Year Experience of Symptomatic Intracranial Hemorrhage Following Intravenous Tissue Plasminogen Activator at a Comprehensive Stroke Center.

BACKGROUND: To describe the 4-year experience of symptomatic intracranial hemorrhage (sICH) rate at a high-volume comprehensive stroke center. METHODS: All admitted adult (≥18 years) patients presenting with an ischemic stroke from 2010 to 2013 were included in this study. The primary outcome was sICH, defined as any hemorrhage with neurological deterioration (change in National Institutes of Health Stroke Scale score ≥4) within 36 hours of intravenous tissue plasminogen activator (IV-tPA) treatment, or any hemorrhage resulting in death. Secondary outcomes were in-hospital mortality and having a favorable modified Rankin Scale (mRS) score (≤2). RESULTS: A total of 1925 did not receive intravascular (IV) or intra-arterial (IA) therapy; only 451 received IV therapy; and 175 received both IV and IA therapies. In IV-only patients, the overall rate of sICH was 2.2%; in IV and IA patients, the rate was 5.7%; and in patients who received no therapy, the rate was .4%. The IV-only group had an sICH rate of .9% in 2013. There were no differences in the adjusted odds of dying in the hospital between the study groups. IV-only treatment offered significantly better odds of achieving a favorable functional outcome, compared to no therapy, among patients with moderate stroke severity, whereas IV and IA treatments offered significantly better odds among patients with severe strokes. The odds of achieving a favorable functional outcome by discharge were decreased by 97% if patients suffered an sICH (OR = .03, 95%CI = .004, .19). CONCLUSIONS: Despite an increased risk of sICH with IV-tPA, treatment with IV-tPA continues to be associated with increased odds of a favorable discharge mRS.

Age ≥80 Years Is Not a Contraindication for Intra-Arterial Therapy after Ischemic Stroke.

BACKGROUND: Clinical trials confirmed the safety and efficacy of intra-arterial therapy (IAT) in the management of ischemic stroke. At a community hospital, we compared outcomes in patients aged ≥80 and patients in the age range 55-79 years receiving IAT following ischemic stroke. METHODS: Data were retrospectively abstracted for ischemic stroke patients ≥55 years treated with IAT at an urban comprehensive stroke center between 2010 and 2013. Baseline demographics, incidence of symptomatic intracranial hemorrhage (sICH), in-hospital mortality, discharge modified Rankin scale (mRS) score (favorable ≤2) and improvement in National Institutes of Health Stroke Scale Score (NIHSS; decreased score at discharge) were compared between patients in the age range 55-79 and patients ≥80 years. Data were analyzed using univariate analyses and multivariate logistic regression. RESULTS: IAT was performed in 239 patients with ischemic stroke; 63 (26.4%) were ≥80 years. When compared to patients aged 55-79, the elderly patients were more often female and non-smokers, with a history of atrial fibrillation. No differences were observed in those ≥80 years compared to patients in the age range 55-79 years for sICH (10 vs. 5%, p = 0.23), mortality (24 vs. 18%, p = 0.28), favorable discharge mRS score (13 vs. 19%, p = 0.27), or improvement in NIHSS (83 vs. 92%, p = 0.10). The nonsignificant association of age with the outcomes persisted after adjusting for covariates and when analyzing the subset of patients who received IAT only. CONCLUSIONS: These findings suggest that in a cohort not subject to the criteria of a clinical trial, age ≥80 years should not be a contraindication to IAT.

Stereoselective synthesis, biological evaluation, and modeling of novel bile acid-derived G-protein coupled bile acid receptor 1 (GP-BAR1, TGR5) agonists.

GP-BAR1 (also known as TGR5), a novel G-protein coupled receptor regulating various non-genomic functions via bile acid signaling, has emerged as a promising target for metabolic disorders, including obesity and type II diabetes. However, given that many bile acids (BAs) are poorly tolerated for systemic therapeutic use, there is significant need to develop GP-BAR1 agonists with improved potency and specificity and there also is significant impetus to develop a stereoselective synthetic methodology for GP-BAR1 agonists. Here, we report the development of highly stereo-controlled strategies to investigate a series of naturally occurring bile acid derivatives with markedly enhanced GP-BAR1 activity. These novel GP-BAR1 agonists are evaluated in vitro using luciferase-based reporter and cAMP assays to elucidate their biological properties. In vivo studies revealed that the GP-BAR1 agonist 23(S)-m-LCA increased intestinal GLP-1 transcripts by 26-fold. Additionally, computational modeling studies of selected ligands that exhibit enhanced potency and specificity for GP-BAR1 provide information on potential binding sites for these ligands in GP-BAR1.

GneimoSim: a modular internal coordinates molecular dynamics simulation package.

The generalized Newton-Euler inverse mass operator (GNEIMO) method is an advanced method for internal coordinates molecular dynamics (ICMD). GNEIMO includes several theoretical and algorithmic advancements that address longstanding challenges with ICMD simulations. In this article, we describe the GneimoSim ICMD software package that implements the GNEIMO method. We believe that GneimoSim is the first software package to include advanced features such as the equipartition principle derived for internal coordinates, and a method for including the Fixman potential to eliminate systematic statistical biases introduced by the use of hard constraints. Moreover, by design, GneimoSim is extensible and can be easily interfaced with third party force field packages for ICMD simulations. Currently, GneimoSim includes interfaces to LAMMPS, OpenMM, and Rosetta force field calculation packages. The availability of a comprehensive Python interface to the underlying C++ classes and their methods provides a powerful and versatile mechanism for users to develop simulation scripts to configure the simulation and control the simulation flow. GneimoSim has been used extensively for studying the dynamics of protein structures, refinement of protein homology models, and for simulating large scale protein conformational changes with enhanced sampling methods. GneimoSim is not limited to proteins and can also be used for the simulation of polymeric materials.

Protein structure refinement of CASP target proteins using GNEIMO torsional dynamics method.

A longstanding challenge in using computational methods for protein structure prediction is the refinement of low-resolution structural models derived from comparative modeling methods into highly accurate atomistic models useful for detailed structural studies. Previously, we have developed and demonstrated the utility of the internal coordinate molecular dynamics (MD) technique, generalized Newton-Euler inverse mass operator (GNEIMO), for refinement of small proteins. Using GNEIMO, the high-frequency degrees of freedom are frozen and the protein is modeled as a collection of rigid clusters connected by torsional hinges. This physical model allows larger integration time steps and focuses the conformational search in the low frequency torsional degrees of freedom. Here, we have applied GNEIMO with temperature replica exchange to refine low-resolution protein models of 30 proteins taken from the continuous assessment of structure prediction (CASP) competition. We have shown that GNEIMO torsional MD method leads to refinement of up to 1.3 Å in the root-mean-square deviation in coordinates for 30 CASP target proteins without using any experimental data as restraints in performing the GNEIMO simulations. This is in contrast with the unconstrained all-atom Cartesian MD method performed under the same conditions, where refinement requires the use of restraints during the simulations.

Tuning Potential Functions to Host-Guest Binding Data.

Software to more rapidly and accurately predict protein-ligand binding affinities is of high interest for early-stage drug discovery, and physics-based methods are among the most widely used technologies for this purpose. The accuracy of these methods depends critically on the accuracy of the potential functions that they use. Potential functions are typically trained against a combination of quantum chemical and experimental data. However, although binding affinities are among the most important quantities to predict, experimental binding affinities have not to date been integrated into the experimental data set used to train potential functions. In recent years, the use of host-guest complexes as simple and tractable models of binding thermodynamics has gained popularity due to their small size and simplicity, relative to protein-ligand systems. Host-guest complexes can also avoid ambiguities that arise in protein-ligand systems such as uncertain protonation states. Thus, experimental host-guest binding data are an appealing additional data type to integrate into the experimental data set used to optimize potential functions. Here, we report the extension of the Open Force Field Evaluator framework to enable the systematic calculation of host-guest binding free energies and their gradients with respect to force field parameters, coupled with the curation of 126 host-guest complexes with available experimental binding free energies. As an initial application of this novel infrastructure, we optimized generalized Born (GB) cavity radii for the OBC2 GB implicit solvent model against experimental data for 36 host-guest systems. This refitting led to a dramatic improvement in accuracy for both the training set and a separate test set with 90 additional host-guest systems. The optimized radii also showed encouraging transferability from host-guest systems to 59 protein-ligand systems. However, the new radii are significantly smaller than the baseline radii and lead to excessively favorable hydration free energies (HFEs). Thus, users of the OBC2 GB model currently may choose between GB cavity radii that yield more accurate binding affinities and GB cavity radii that yield more accurate HFEs. We suspect that achieving good accuracy on both will require more far-reaching adjustments to the GB model. We note that binding free-energy calculations using the OBC2 model in OpenMM gain about a 10× speedup relative to corresponding explicit solvent calculations, suggesting a future role for implicit solvent absolute binding free-energy (ABFE) calculations in virtual compound screening. This study proves the principle of using host-guest systems to train potential functions that are transferrable to protein-ligand systems and provides an infrastructure that enables a range of applications.

Mapping conformational dynamics of proteins using torsional dynamics simulations.

All-atom molecular dynamics simulations are widely used to study the flexibility of protein conformations. However, enhanced sampling techniques are required for simulating protein dynamics that occur on the millisecond timescale. In this work, we show that torsional molecular dynamics simulations enhance protein conformational sampling by performing conformational search in the low-frequency torsional degrees of freedom. In this article, we use our recently developed torsional-dynamics method called Generalized Newton-Euler Inverse Mass Operator (GNEIMO) to study the conformational dynamics of four proteins. We investigate the use of the GNEIMO method in simulations of the conformationally flexible proteins fasciculin and calmodulin, as well as the less flexible crambin and bovine pancreatic trypsin inhibitor. For the latter two proteins, the GNEIMO simulations with an implicit-solvent model reproduced the average protein structural fluctuations and sample conformations similar to those from Cartesian simulations with explicit solvent. The application of GNEIMO with replica exchange to the study of fasciculin conformational dynamics produced sampling of two of this protein's experimentally established conformational substates. Conformational transition of calmodulin from the Ca(2+)-bound to the Ca(2+)-free conformation occurred readily with GNEIMO simulations. Moreover, the GNEIMO method generated an ensemble of conformations that satisfy about half of both short- and long-range interresidue distances obtained from NMR structures of holo to apo transitions in calmodulin. Although unconstrained all-atom Cartesian simulations have failed to sample transitions between the substates of fasciculin and calmodulin, GNEIMO simulations show the transitions in both systems. The relatively short simulation times required to capture these long-timescale conformational dynamics indicate that GNEIMO is a promising molecular-dynamics technique for studying domain motion in proteins.