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.

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.

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.

Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking.

Docking calculations can accelerate drug discovery by predicting the bound poses of ligands for a targeted protein. However, it is not clear which docking methods work best. Furthermore, predicting poses requires steps outside the docking algorithm itself, such as preparation of the protein and ligand, and it is not known which components are most in need of improvement. The Continuous Evaluation of Ligand Protein Predictions (CELPP) is a blinded prediction challenge designed to address these issues. Participants create a workflow to predict protein-ligand binding poses, which is then tasked with predicting 10-100 new protein-ligand crystal structures each week. CELPP evaluates the accuracy of each workflow's predictions and posts the scores online. The results can be used to identify the strengths and weaknesses of current approaches, help map docking problems to the algorithms most likely to overcome them, and illuminate areas of unmet need in structure-guided drug design.

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.

POVME 3.0: Software for Mapping Binding Pocket Flexibility.

We present a substantial update to the open-source POVME binding pocket analysis software. New capabilities of POVME 3.0 include a flexible chemical coloring scheme for feature identification, postanalysis tools for comparing large ensembles of pockets (e.g., from molecular dynamics simulations), and the introduction of scripts and methods that facilitate binding pocket comparison and analysis. We envision the use of this software for visualization of binding pocket dynamics, selection of representative structures for ensemble docking, and incorporation of molecular dynamics results into ligand design efforts.

Role of a p53 polymorphism in the development of nonfunctional pituitary adenomas.

Non-functional pituitary adenomas (NFPAs) are among the commonest intracranial neoplasms. While histologically benign, NFPAs sometimes become large enough to limit therapeutic options and reduce quality of life. Investigations of the molecular etiology of NFPAs have failed to identify prevalent genetic changes and, while a role for p53 has been suggested, TP53 gene alterations have yet to be described in NFPAs. We found that the polymorphism rs1042522:C > G in codon 72 of exon 4 of the TP53 gene, whose C variant produces a proline and is more common in most ethnicities, has a G variant producing an arginine in 79.8% of NFPAs (n = 42; p < 1.411 × 10-18 vs. 1000 Genomes database), causing patients to present a decade earlier with symptomatic NFPAs. In cultured NFPA cells, transfection with the rs1042522 G variant versus the C variant reduced expression of cell arrest gene p21 and increased proliferation. These findings suggest that this TP53 polymorphism influences NFPA growth.

GLUT3 upregulation promotes metabolic reprogramming associated with antiangiogenic therapy resistance.

Clinical trials revealed limited response duration of glioblastomas to VEGF-neutralizing antibody bevacizumab. Thriving in the devascularized microenvironment occurring after antiangiogenic therapy requires tumor cell adaptation to decreased glucose, with 50% less glucose identified in bevacizumab-treated xenografts. Compared with bevacizumab-responsive xenograft cells, resistant cells exhibited increased glucose uptake, glycolysis, 13C NMR pyruvate to lactate conversion, and survival in low glucose. Glucose transporter 3 (GLUT3) was upregulated in bevacizumab-resistant versus sensitive xenografts and patient specimens in a HIF-1α-dependent manner. Resistant versus sensitive cell mitochondria in oxidative phosphorylation-selective conditions produced less ATP. Despite unchanged mitochondrial numbers, normoxic resistant cells had lower mitochondrial membrane potential than sensitive cells, confirming poorer mitochondrial health, but avoided the mitochondrial dysfunction of hypoxic sensitive cells. Thin-layer chromatography revealed increased triglycerides in bevacizumab-resistant versus sensitive xenografts, a change driven by mitochondrial stress. A glycogen synthase kinase-3ß inhibitor suppressing GLUT3 transcription caused greater cell death in bevacizumab-resistant than -responsive cells. Overexpressing GLUT3 in tumor cells recapitulated bevacizumab-resistant cell features: survival and proliferation in low glucose, increased glycolysis, impaired oxidative phosphorylation, and rapid in vivo proliferation only slowed by bevacizumab to that of untreated bevacizumab-responsive tumors. Targeting GLUT3 or the increased glycolysis reliance in resistant tumors could unlock the potential of antiangiogenic treatments.

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.

Improved versus worsened endocrine function after transsphenoidal surgery for nonfunctional pituitary adenomas: rate, time course, and radiological analysis.

OBJECTIVE: The impact of transsphenoidal surgery for nonfunctional pituitary adenomas (NFAs) on preoperative hypopituitarism relative to the incidence of new postoperative endocrine deficits remains unclear. The authors investigated rates of hypopituitarism resolution and development after transsphenoidal surgery. METHODS: Over a 5-year period, 305 transsphenoidal surgeries for NFAs performed at The California Center for Pituitary Disorders were retrospectively reviewed. RESULTS: Patients with preoperative endocrine deficits (n = 153, 50%) were significantly older (mean age 60 vs 54 years; p = 0.004), more frequently male (65% vs 44%; p = 0.0005), and had larger adenomas (2.4 cm vs 2.1 cm; p = 0.02) than patients without preoperative deficits (n = 152, 50%). Of patients with preoperative endocrine deficits, 53% exhibited symptoms. Preoperative deficit rates were 26% for the thyroid axis; 20% and 16% for the male and female reproductive axes, respectively; 13% for the adrenocorticotropic hormone (ACTH)/cortisol axis, and 19% for the growth hormone (GH)/insulin-like growth factor-1 (IGF-1) axis. Laboratory normalization rates 6 weeks and 6 months after surgery without hormone replacement were 26% and 36% for male and 13% and 13% for female reproductive axes, respectively; 30% and 49% for the thyroid axis; 3% and 3% for the cortisol axis; and 9% and 22% for the IGF-1 axis (p < 0.05). New postoperative endocrine deficits occurred in 42 patients (13.7%). Rates of new deficits by axes were: male reproductive 3% (n = 9), female reproductive 1% (n = 4), thyroid axis 3% (n = 10), cortisol axis 6% (n = 19), and GH/IGF-1 axis 4% (n = 12). Patients who failed to exhibit any endocrine normalization had lower preoperative gland volumes than those who did not (0.24 cm(3) vs 0.43 cm(3), respectively; p < 0.05). Multivariate analyses revealed that no variables predicted new postoperative deficits or normalization of the female reproductive, cortisol, and IGF-1 axes. However, increased preoperative gland volume and younger age predicted the chances of a patient with any preoperative deficit experiencing normalization of at least 1 axis. Younger age and less severe preoperative hormonal deficit predicted normalization of the thyroid and male reproductive axes (p < 0.05). CONCLUSIONS: After NFA resection, endocrine normalization rates in this study varied with the hormonal axis and were greater than the incidence of new endocrine deficits. Low preoperative gland volume precluded recovery. Patient age and the severity of the deficiency influenced the recovery of the thyroid and male reproductive axes, the most commonly impaired axes and most likely to normalize postoperatively. This information can be of use in counseling patients with hypopituitarism who undergo NFA surgery.

Incidence of headache as a presenting complaint in over 1000 patients with sellar lesions and factors predicting postoperative improvement.

INTRODUCTION: Due to the high incidence of headaches and pituitary tumors, neurosurgeons often evaluate patients with benign-appearing sellar lesions and headaches without insight into whether the headache is attributable to the lesion. We sought to evaluate the incidence of headache as a presenting complaint in patients undergoing transsphenoidal surgery for various pathologies and to identify factors predicting postoperative improvement. METHODS: We conducted a 5-year retrospective review of our first 1015 transsphenoidal surgeries since establishing a dedicated pituitary center. RESULTS: Of 1015 patients, 329 (32%) presented with headache. Of these 329 patients, 241 (73)% had headache as their chief complaint. Headache was most common in patients with apoplexy (84%), followed by Rathke's cleft cysts (RCCs) (60%). Multivariate analyses revealed diagnosis (P = 0.001), younger age (P = 0.001), and female gender (P = 0.006) to be associated with headache. Of patients presenting with headaches, 11% reported improvement at 6-week follow-up and 53% improved at 6-month follow-up. Multivariate analyses revealed gross total resection (GTR; P = 0.04) and decreased duration of headache (P = 0.04) to be associated with improvement, while diagnosis, age, gender, lesion size, whether headache was a chief complaint, and location of headache were not associated with improvement (P > 0.05). CONCLUSION: In analyzing over 1000 consecutive patients undergoing transsphenoidal surgery, younger patients, females, and patients with RCCs and apoplexy were more likely to present with headache. Patients who underwent GTR and had shorter duration of headache were more likely to experience headache improvement. This information can be used to counsel patients preoperatively.

Factors predicting recurrence after resection of clival chordoma using variable surgical approaches and radiation modalities.

BACKGROUND: Clival chordomas frequently recur because of their location and invasiveness. OBJECTIVE: To investigate clinical, operative, and anatomic factors associated with clival chordoma recurrence. METHODS: Retrospective review of clival chordomas treated at our center from 1993 to 2013. RESULTS: Fifty patients (56% male) with median age of 59 years (range, 8-76) were newly diagnosed with clival chordoma of mean diameter 3.3 cm (range, 1.5-6.7). Symptoms included headaches (38%), diplopia (36%), and dysphagia (14%). Procedures included transsphenoidal (n=34), transoral (n=4), craniotomy (n=5), and staged approaches (n=7). Gross total resection (GTR) rate was 52%, with 83% mean volumetric reduction, values that improved over time. While the lower third of the clivus was the least likely superoinferior zone to contain tumor (upper third=72%/middle third=82%/lower third=42%), it most frequently contained residual tumor (upper third=33%/middle third=38%/lower third=63%; P<.05). Symptom improvement rates were 61% (diplopia) and 53% (headache). Postoperative radiation included proton beam (n=19), cyberknife (n=7), intensity-modulated radiation therapy (n=6), external beam (n=10), and none (n=4). At last follow-up of 47 patients, 23 (49%) remain disease-free or have stable residual tumor. Lower third of clivus progressed most after GTR (upper/mid/lower third=32%/41%/75%). In a multivariate Cox proportional hazards model, male gender (hazard ratio [HR]=1.2/P=.03), subtotal resection (HR=5.0/P=.02), and the preoperative presence of tumor in the middle third (HR=1.2/P=.02) and lower third (HR=1.8/P=.02) of the clivus increased further growth or regrowth, while radiation modality did not. CONCLUSION: Our findings underscore long-standing support for GTR as reducing chordoma recurrence. The lower third of the clivus frequently harbored residual or recurrent tumor, despite staged approaches providing mediolateral (transcranial+endonasal) or superoinferior (endonasal+transoral) breadth. There was no benefit of proton-based over photon-based radiation, contradicting conventional presumptions.

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.

A comprehensive long-term retrospective analysis of silent corticotrophic adenomas vs hormone-negative adenomas.

BACKGROUND: Silent corticotrophic adenomas (SCAs) stain adrenocorticotropic hormone (ACTH)+ without causing Cushing disease. SCAs are reportedly more aggressive, but information comes from small series. OBJECTIVE: To determine whether SCAs behave more aggressively than hormone-negative adenomas (HNAs), and characterize SCA ACTH production alterations. METHODS: SCAs (n = 75) and HNAs (n = 1726) diagnosed at our institution from 1990 to 2011 were retrospectively reviewed. RT-PCR was used to compare expression of ACTH-producing factors. RESULTS: SCA patients exhibited comparable sex and age as HNA patients (P = .7-.9). SCAs exhibited comparable size as HNAs (2.2 vs 2.0 cm, P = .2), with cavernous sinus invasion in 30% of SCAs vs 18% of HNAs (P = .03). SCA patients had higher mean preoperative serum ACTH (46 vs 19 ng/L; P = .005; normal = 5-27 ng/L), but comparable serum cortisol (13 vs 12 µg/dL; normal = 4-22 µg/dL; P < .05) as HNA patients. SCAs were gross totally resected 59% of the time, vs 53% for HNAs (P = .8). Kaplan-Meier 3-year progression/recurrence rates were 34% for strongly ACTH-positive Type I SCAs, 10% for weakly ACTH-positive Type II SCAs, and 6% for HNAs (P < .001 SCA vs HNA; P < .001 Type I vs HNA; and P = .08 Type II vs HNA). Expression of ACTH precursor pro-opiomelanocortin was 900-fold elevated in SCAs and 1300-fold elevated in Cushing disease-causing adenomas (CDCAs) vs HNAs (P < .001). Transcription of PC1/3, which cleaves pro-opiomelanocortin into ACTH, was 30-fold higher in CDCAs than SCAs (P = .02). CONCLUSION: In the largest series to date, SCAs exhibited comparable size, but increased cavernous sinus invasion and progression/recurrence vs HNAs. SCAs exhibit deficient pro-opiomelanocortin to ACTH conversion. Close follow-up is warranted for SCAs.

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.