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.

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.

Radiological markers of neurological manifestations of post-acute sequelae of SARS-CoV-2 infection: a mini-review.

The neurological impact of COVID-19 is a rising concern among medical professionals, as patients continue to experience symptoms long after their recovery. This condition, known as neurological post-acute sequelae of COVID-19 (Neuro-PASC), can last for more than 12 weeks and includes symptoms such as attention disorders, brain fog, fatigue, and memory loss. However, researchers and health professionals face significant challenges in understanding how COVID-19 affects the brain, limiting the development of effective prevention and treatment strategies. In this mini-review, we provide readers with up-to-date information on the imaging techniques currently available for measuring the neurological impact of post-SARS-CoV-2 infection. Our search of PubMed and Google Scholar databases yielded 38 articles on various brain imaging techniques, including structural MRI (magnetic resonance imaging), functional MRI, diffusion MRI, susceptibility-weighted imaging, SPECT (single-photon emission computed tomography) imaging, and PET (positron emission tomography) imaging. We also discuss the optimal usage, limitations, and potential benefits of these techniques. Our findings show that various cerebral imaging techniques have been evaluated to identify a reliable marker for Neuro-PASC. For instance, 18F-FDG-PET/CT and functional MRI have demonstrated hypometabolism in cerebral regions that are directly linked to patient symptoms. Structural MRI studies have revealed different findings, such as infarcts, white matter atrophy, and changes in gray matter volumes. One SPECT imaging study noted frontal lobe hypometabolism, while diffusion MRI showed increased diffusivity in the limbic and olfactory cortical systems. The sequence SWI showed abnormalities primarily in white matter near the gray-white matter junction. A study on 18F-amyloid PET/CT found amyloid lesions in frontal and anterior cingulate cortex areas, and a study on arterial spin labeling (ASL) found hypoperfusion primarily in the frontal lobe. While accessibility and cost limit the widespread use of 18F-FDG-PET/CT scans and functional MRI, they seem to be the most promising techniques. SPECT, SWI sequence, and 18F-amyloid PET/CT require further investigation. Nevertheless, imaging remains a reliable tool for diagnosing Neuro-PASC and monitoring recovery.

Development of an Engineered Mycobacterium tuberculosis Strain for a Safe and Effective Tuberculosis Human Challenge Model.

Human challenge experiments could greatly accelerate the development of a tuberculosis (TB) vaccine. Human challenge for tuberculosis requires a strain that can both replicate in the host and be reliably cleared. To accomplish this, we designed Mycobacterium tuberculosis (Mtb) strains featuring up to three orthogonal kill switches, tightly regulated by exogenous tetracyclines and trimethoprim. The resultant strains displayed immunogenicity and antibiotic susceptibility similar to wild-type Mtb under permissive conditions. In the absence of supplementary exogenous compounds, the strains were rapidly killed in axenic culture, mice and nonhuman primates. Notably, the strain that contained three kill switches had an escape rate of less than 10 -10 per genome per generation and displayed no relapse in a SCID mouse model. Collectively, these findings suggest that this engineered Mtb strain could be a safe and effective candidate for a human challenge model.

Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field.

We introduce the Open Force Field (OpenFF) 2.0.0 small molecule force field for drug-like molecules, code-named Sage, which builds upon our previous iteration, Parsley. OpenFF force fields are based on direct chemical perception, which generalizes easily to highly diverse sets of chemistries based on substructure queries. Like the previous OpenFF iterations, the Sage generation of OpenFF force fields was validated in protein-ligand simulations to be compatible with AMBER biopolymer force fields. In this work, we detail the methodology used to develop this force field, as well as the innovations and improvements introduced since the release of Parsley 1.0.0. One particularly significant feature of Sage is a set of improved Lennard-Jones (LJ) parameters retrained against condensed phase mixture data, the first refit of LJ parameters in the OpenFF small molecule force field line. Sage also includes valence parameters refit to a larger database of quantum chemical calculations than previous versions, as well as improvements in how this fitting is performed. Force field benchmarks show improvements in general metrics of performance against quantum chemistry reference data such as root-mean-square deviations (RMSD) of optimized conformer geometries, torsion fingerprint deviations (TFD), and improved relative conformer energetics (ΔΔE). We present a variety of benchmarks for these metrics against our previous force fields as well as in some cases other small molecule force fields. Sage also demonstrates improved performance in estimating physical properties, including comparison against experimental data from various thermodynamic databases for small molecule properties such as ΔHmix, ρ(x), ΔGsolv, and ΔGtrans. Additionally, we benchmarked against protein-ligand binding free energies (ΔGbind), where Sage yields results statistically similar to previous force fields. All the data is made publicly available along with complete details on how to reproduce the training results at https://github.com/openforcefield/openff-sage.

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.

A Program to Reduce Post-Operative Opioid Prescribing at a Veteran's Affairs Hospital.

Variability in surgeon prescribing patterns is common in the post-operative period and can be the nidus for dependence and addiction. This project aims to reduce opioid overprescribing at the Veteran's Affairs Pittsburgh Healthcare System (VAPHS). The VAPHS Opioid Stewardship Committee collaborated to create prescribing guidelines for inpatient and outpatient general, thoracic, and vascular surgery procedures. We incorporated bundled order sets into the provider workflow in the electronic medical system and performed a retrospective cohort study comparing opioid prescription patterns for Veterans who underwent any surgical procedure for a three-month period pre- and post- guideline implementation. After implementation of opioid prescribing guidelines, morphine milligram equivalents (MME), quantity of pills prescribed, and days prescribed were statistically significantly reduced for procedures with associated guidelines, including cholecystectomy (MME 140.8 vs. 57.5, p = 0.002; quantity 18.8 vs. 8, p = 0.002; days 5.1 vs. 2.8, p = 0.021), inguinal hernia repair (MME 129.9 vs. 45.3, p = 0.002; quantity 17.3 vs. 6.1, p = 0.002; days 5.0 vs. 2.4, p = 0.002), and umbilical hernia repair (MME 128.8 vs. 53.8, p = 0.002; quantity 17.1 vs. 7.8, p = 0.002; days 5.1 vs. 2.5, p = 0.022). Procedures without associated recommendations also preceded a decrease in overall opioid prescribing. Post-operative opioid prescribing guidelines can steer clinicians toward more conscientious opioid disbursement. There may also be reductions in prescribing opioids for procedures without guidelines as an indirect effect of practice change.

Hydrocephalus After Gamma Knife Radiosurgery for Vestibular Schwannoma: Favorable Outcomes After Shunt Placement.

Recent literature has described the development of a normal pressure hydrocephalus after Gamma Knife radiosurgery in patients with vestibular schwannoma. However, there is minimal detail regarding the clinical course and extent of recovery in these patients following shunt placement. This information would help clinicians weigh the risks and benefits of shunt surgery. We describe the clinical course of two such patients who received shunt placement and made a significant recovery not only in gait but also in their cognitive function. Unlike idiopathic normal pressure hydrocephalus, where patients can have a limited recovery after shunt placement, patients with this form of secondary hydrocephalus appear to make a significant recovery following shunting. Due to the complexity of these patients, it is possible for clinicians to attribute normal pressure hydrocephalus symptoms to neurodegenerative disease or vestibular dysfunction. Thus, it is vital that clinicians have a high index of suspicion for hydrocephalus in vestibular schwannoma patients receiving Gamma Knife radiosurgery so that these patients can be treated early with shunt placement.

Global assessment improves risk stratification for major adverse cardiac events across a wide range of triglyceride levels: Insights from the KP REACH study.

OBJECTIVE: Patients with risk factors for or established atherosclerotic cardiovascular disease (ASCVD) remain at high risk for subsequent ischemic events despite statin therapy. Triglyceride (TG) levels may contribute to residual ASCVD risk, and the performance of global risk assessment calculators across a broad range of TG levels is unknown. METHODS: We performed a retrospective cohort study of Kaiser Permanente Northern California members aged ≥45 years with ≥1 ASCVD risk factor (primary prevention cohort) or established ASCVD (secondary prevention cohort) between 2010 and 2017 who were receiving statin therapy and had a low-density lipoprotein cholesterol between 41-100 mg/dL. Global ASCVD risk assessment was performed using both the Kaiser Permanente ASCVD Risk Estimator (KPARE) and the ACC/AHA ASCVD Pooled Cohort Equation (PCE). Outcomes included major adverse cardiovascular events (MACE) defined as myocardial infarction, stroke, or peripheral artery disease, and expanded MACE (MACE + coronary revascularization + hospitalization for unstable angina). RESULTS: Among 373,389 patients in the primary prevention cohort, median TG was 122 mg/dL (IQR 88-172 mg/dL) and there were 0.2 MACE events and 0.3 expanded MACE events per 100-person years. Among 97,832 patients in the secondary prevention cohort, median TG level was 116 mg/dL (IQR 84-164 mg/dL) and there were 9.6 MACE events and 22.0 expanded MACE events per 100-person years. KPARE and the ACC/AHA PCE stratified patients for MACE and expanded MACE over the entire range of TGs. CONCLUSION: In a cohort receiving statin therapy for primary or secondary prevention, we found global assessment further improves risk stratification for initial and/or recurrent ASCVD events irrespective of baseline TG level.

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.

Triglyceride Levels and Residual Risk of Atherosclerotic Cardiovascular Disease Events and Death in Adults Receiving Statin Therapy for Primary or Secondary Prevention: Insights From the KP REACH Study.

Background Patients with risk factors or established atherosclerotic cardiovascular disease remain at high-risk for ischemic events. Triglyceride levels may play a causal role. Methods and Results We performed a retrospective study of adults aged ≥45 years receiving statin therapy, with a low-density lipoprotein cholesterol of 41 to 100 mg/dL, and ≥1 risk factor or established atherosclerotic cardiovascular disease between 2010 and 2017. Outcomes included death, all-cause hospitalization, and major adverse cardiovascular events (myocardial infarction, stroke, or peripheral artery disease). The study sample included 373 389 primary prevention patients and 97 832 secondary prevention patients. The primary prevention cohort had a mean age of 65±10 years, with 51% women and 44% people of color, whereas the secondary prevention cohort had a mean age of 71±11 years, with 37% women and 32% people of color. Median triglyceride levels for the primary and secondary prevention cohorts were 122 mg/dL (interquartile range, 88-172 mg/dL) and 116 mg/dL (interquartile range, 84-164 mg/dL), respectively. In multivariable analyses, primary prevention patients with triglyceride levels ≥150 mg/dL were at lower adjusted risk of death (hazard ratio [HR], 0.91; 95% CI, 0.89-0.94) and higher risk of major adverse cardiovascular events (HR, 1.14; 95% CI, 1.05-1.24). In the secondary prevention cohort, patients with triglyceride levels ≥150 mg/dL were at lower adjusted risk of death (HR, 0.95; 95% CI, 0.92-0.97) and higher risk of all-cause hospitalization (HR, 1.03; 95% CI, 1.01-1.05) and major adverse cardiovascular events (HR, 1.04; 95% CI, 1.05-1.24). Conclusions In a contemporary cohort receiving statin therapy, elevated triglyceride levels were associated with a greater risk of atherosclerotic cardiovascular disease events and lower risk of death.

Development and Benchmarking of Open Force Field v1.0.0-the Parsley Small-Molecule Force Field.

We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 small-molecule force field, codenamed Parsley. Rather than using traditional atom typing, our approach is built on the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of the specification. Parameters are optimized with the ForceBalance tool, based on reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These quantum reference data are computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. In this initial application of the method, we present essentially a full optimization of all valence parameters and report tests of the resulting force field against compounds and data types outside the training set. These tests show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields, as is accuracy on binding free energies. We find that this initial Parsley force field affords accuracy similar to that of other general force fields when used to calculate relative binding free energies spanning 199 protein-ligand systems. Additionally, the resulting infrastructure allows us to rapidly optimize an entirely new force field with minimal human intervention.

An integrated platform for genome engineering and gene expression perturbation in Plasmodium falciparum.

Establishing robust genome engineering methods in the malarial parasite, Plasmodium falciparum, has the potential to substantially improve the efficiency with which we gain understanding of this pathogen's biology to propel treatment and elimination efforts. Methods for manipulating gene expression and engineering the P. falciparum genome have been validated. However, a significant barrier to fully leveraging these advances is the difficulty associated with assembling the extremely high AT content DNA constructs required for modifying the P. falciparum genome. These are frequently unstable in commonly-used circular plasmids. We address this bottleneck by devising a DNA assembly framework leveraging the improved reliability with which large AT-rich regions can be efficiently manipulated in linear plasmids. This framework integrates several key functional genetics outcomes via CRISPR/Cas9 and other methods from a common, validated framework. Overall, this molecular toolkit enables P. falciparum genetics broadly and facilitates deeper interrogation of parasite genes involved in diverse biological processes.

A Quality Improvement Initiative To Improve Postdischarge Antimicrobial Adherence.

OBJECTIVES: Bedside delivery of discharge medications improves caregiver understanding and experience. Less is known about its impact on medication adherence. We aimed to improve antimicrobial adherence by increasing on-time first home doses for patients discharged from the pediatric hospital medicine service from 33% to 80% over 1 year via creation of a discharge medication delivery and counseling "Meds to Beds" (M2B) program. METHODS: Using sequential plan-do-study-act cycles, an interprofessional workgroup implemented M2B on select pediatric hospital medicine units at our quaternary children's hospital from October 2017 through December 2018. Scripted telephone surveys were conducted with caregivers of patients prescribed antimicrobial agents at discharge. The primary outcome measure was on-time administration of the first home antimicrobial dose, defined as a dose given within the time of the inpatient dose equivalent plus 25%. Process measures primarily assessed caregiver report of barriers to adherence. Run charts, statistical process control charts, and inferential statistics were used for data analysis. RESULTS: Caregiver survey response rate was 35% (207 of 585). Median on-time first home antimicrobial doses increased from 33% to 67% (P < .001). Forty percent of M2B prescriptions were adjusted before discharge because of financial or insurance barriers. M2B participants reported significantly less difficulty in obtaining medications compared with nonparticipants (1% vs 17%, P < .001). CONCLUSIONS: The M2B program successfully increased parental report of timely administration of first home antimicrobial doses, a component of overall adherence. The program enabled providers to identify and resolve prescription problems before discharge. Importantly, caregivers reported reduced barriers to medication adherence.

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.