IP6 and PF74 affect HIV-1 Capsid Stability through Modulation of Hexamer-Hexamer Tilt Angle Preference.

The HIV-1 capsid is an irregularly shaped complex of about 1200 protein chains containing the viral genome and several viral proteins. Together, these components are the key to unlocking passage into the nucleus, allowing for permanent integration of the viral genome into the host cell genome. Recent interest into the role of the capsid in viral replication has been driven by the approval of the first-in-class drug lenacapavir, which marks the first drug approved to target a non-enzymatic HIV-1 viral protein. In addition to lenacapavir, other small molecules such as the drug-like compound PF74, and the anionic sugar inositolhexakisphosphate (IP6), are known to impact capsid stability, and although this is widely accepted as a therapeutic effect, the mechanisms through which they do so remain unknown. In this study, we employed a systematic atomistic simulation approach to study the impact of molecules bound to hexamers at the central pore (IP6) and the FG-binding site (PF74) on capsid oligomer dynamics, compared to apo hexamers and pentamers. We found that neither small molecule had a sizeable impact on the free energy of binding of the interface between neighboring hexamers but that both had impacts on the free energy profiles of performing angular deformations to the pair of oligomers akin to the variations in curvature along the irregular surface of the capsid. The IP6 cofactor, on one hand, stabilizes a pair of neighboring hexamers in their flattest configurations, whereas without IP6, the hexamers prefer a high tilt angle between them. On the other hand, having PF74 bound introduces a strong preference for intermediate tilt angles. These results suggest that structural instability is a natural feature of the HIV-1 capsid which is modulated by molecules bound in either the central pore or the FG-binding site. Such modulators, despite sharing many of the same effects on non-bonded interactions at the various protein-protein interfaces, have decidedly different effects on the flexibility of the complex. This study provides a detailed model of the HIV-1 capsid and its interactions with small molecules, informing structure-based drug design, as well as experimental design and interpretation.

Synergy of machine learning and density functional theory calculations for predicting experimental Lewis base affinity and Lewis polybase binding atoms.

Investigation of Lewis acid-base interactions has been conducted by ab initio calculations and machine learning (ML) models. This study aims to resolve two critical tasks that have not been quantitatively investigated. First, ML models developed from density functional theory (DFT) calculations predict experimental BF3 affinity with Pearson correlation coefficients around 0.9 and mean absolute errors around 10 kJ mol-1. The ML models are trained by DFT-calculated BF3 affinity of more than 3000 adducts, with input features readily obtained by rdkit. Second, the ML models have the capability of predicting the relative strength of Lewis base binding atoms in Lewis polybases, which is either an extremely challenging task to conduct experimentally or a computationally expensive task for ab initio methods. The study demonstrates and solidifies the potential of combining DFT calculations and ML models to predict experimental properties, especially those that are scarce and impractical to empirically acquire.

Reactive Docking: A Computational Method for High-Throughput Virtual Screenings of Reactive Species.

We describe the formalization of the reactive docking protocol, a method developed to model and predict reactions between small molecules and biological macromolecules. The method has been successfully used in a number of applications already, including recapitulating large proteomics data sets, performing structure-reactivity target optimizations, and prospective virtual screenings. By modeling a near-attack conformation-like state, no QM calculations are required to model the ligand and receptor geometries. Here, we present its generalization using a large data set containing more than 400 ligand-target complexes, 8 nucleophilic modifiable residue types, and more than 30 warheads. The method correctly predicts the modified residue in ∼85% of complexes and shows enrichments comparable to standard focused virtual screenings in ranking ligands. This performance supports this approach for the docking and screening of reactive ligands in virtual chemoproteomics and drug design campaigns.

Stretching Peptides to Generate Small Molecule ß-Strand Mimics.

Advances in the modulation of protein-protein interactions (PPIs) enable both characterization of PPI networks that govern diseases and design of therapeutics and probes. The shallow protein surfaces that dominate PPIs are challenging to target using standard methods, and approaches for accessing extended backbone structures are limited. Here, we incorporate a rigid, linear, diyne brace between side chains at the i to i+2 positions to generate a family of low-molecular-weight, extended-backbone peptide macrocycles. NMR and density functional theory studies show that these stretched peptides adopt stable, rigid conformations in solution and can be tuned to explore extended peptide conformational space. The diyne brace is formed in excellent conversions (>95%) and amenable to high-throughput synthesis. The minimalist structure-inducing tripeptide core (<300 Da) is amenable to further synthetic elaboration. Diyne-braced inhibitors of bacterial type 1 signal peptidase demonstrate the utility of the technique.

Logical memory, visual reproduction, and verbal paired associates are effective embedded validity indicators in patients with traumatic brain injury.

OBJECTIVE: This study was design to evaluate the potential of the recognition trials for the Logical Memory (LM), Visual Reproduction (VR), and Verbal Paired Associates (VPA) subtests of the Wechsler Memory Scales-Fourth Edition (WMS-IV) to serve as embedded performance validity tests (PVTs). METHOD: The classification accuracy of the three WMS-IV subtests was computed against three different criterion PVTs in a sample of 103 adults with traumatic brain injury (TBI). RESULTS: The optimal cutoffs (LM ≤ 20, VR ≤ 3, VPA ≤ 36) produced good combinations of sensitivity (.33-.87) and specificity (.92-.98). An age-corrected scaled score of ≤5 on either of the free recall trials on the VPA was specific (.91-.92) and relatively sensitive (.48-.57) to psychometrically defined invalid performance. A VR I ≤ 5 or VR II ≤ 4 had comparable specificity, but lower sensitivity (.25-.42). There was no difference in failure rate as a function of TBI severity. CONCLUSIONS: In addition to LM, VR, and VPA can also function as embedded PVTs. Failing validity cutoffs on these subtests signals an increased risk of non-credible presentation and is robust to genuine neurocognitive impairment. However, they should not be used in isolation to determine the validity of an overall neurocognitive profile.

Orphan receptor GPR158 serves as a metabotropic glycine receptor: mGlyR.

Glycine is a major neurotransmitter involved in several fundamental neuronal processes. The identity of the metabotropic receptor mediating slow neuromodulatory effects of glycine is unknown. We identified an orphan G protein-coupled receptor, GPR158, as a metabotropic glycine receptor (mGlyR). Glycine and a related modulator, taurine, directly bind to a Cache domain of GPR158, and this event inhibits the activity of the intracellular signaling complex regulator of G protein signaling 7-G protein ß5 (RGS7-Gß5), which is associated with the receptor. Glycine signals through mGlyR to inhibit production of the second messenger adenosine 3',5'-monophosphate. We further show that glycine, but not taurine, acts through mGlyR to regulate neuronal excitability in cortical neurons. These results identify a major neuromodulatory system involved in mediating metabotropic effects of glycine, with implications for understanding cognition and affective states.

Ringtail: A Python Tool for Efficient Management and Storage of Virtual Screening Results.

Virtual screening using molecular docking is now routinely used for the rapid evaluation of very large ligand libraries in early stage drug discovery. As the size of compound libraries which can feasibly be screened grows, so do the challenges in result management and storage. Here we introduce Ringtail, a new Python tool in the AutoDock Suite for efficient storage and analysis of virtual screening data based on portable SQLite databases. Ringtail is designed to work with AutoDock-GPU and AutoDock Vina out-of-the-box. Its modular design also allows for easy extension to support input file types from other docking software, different storage solutions, and incorporation into other applications. Ringtail's SQLite database output can dramatically reduce the required disk storage (36-46 fold) by selecting individual poses to store and by taking advantage of the relational database format. Filtering times are also dramatically reduced, requiring minutes to filter millions of ligands. Thus, Ringtail is a tool that can immediately integrate into existing virtual screening pipelines using AutoDock-GPU and Vina, and is scriptable and modifiable to fit specific user needs.

Evaluation of AlphaFold2 structures as docking targets.

AlphaFold2 is a promising new tool for researchers to predict protein structures and generate high-quality models, with low backbone and global root-mean-square deviation (RMSD) when compared with experimental structures. However, it is unclear if the structures predicted by AlphaFold2 will be valuable targets of docking. To address this question, we redocked ligands in the PDBbind datasets against the experimental co-crystallized receptor structures and against the AlphaFold2 structures using AutoDock-GPU. We find that the quality measure provided during structure prediction is not a good predictor of docking performance, despite accurately reflecting the quality of the alpha carbon alignment with experimental structures. Removing low-confidence regions of the predicted structure and making side chains flexible improves the docking outcomes. Overall, despite high-quality prediction of backbone conformation, fine structural details limit the naive application of AlphaFold2 models as docking targets.

Take Their Word for It: The Inventory of Problems Provides Valuable Information on Both Symptom and Performance Validity.

This study was designed to compare the validity of the Inventory of Problems (IOP-29) and its newly developed memory module (IOP-M) in 150 patients clinically referred for neuropsychological assessment. Criterion groups were psychometrically derived based on established performance and symptom validity tests (PVTs and SVTs). The criterion-related validity of the IOP-29 was compared to that of the Negative Impression Management scale of the Personality Assessment Inventory (NIMPAI) and the criterion-related validity of the IOP-M was compared to that of Trial-1 on the Test of Memory Malingering (TOMM-1). The IOP-29 correlated significantly more strongly (z = 2.50, p = .01) with criterion PVTs than the NIMPAI (rIOP-29 = .34; rNIM-PAI = .06), generating similar overall correct classification values (OCCIOP-29: 79-81%; OCCNIM-PAI: 71-79%). Similarly, the IOP-M correlated significantly more strongly (z = 2.26, p = .02) with criterion PVTs than the TOMM-1 (rIOP-M = .79; rTOMM-1 = .59), generating similar overall correct classification values (OCCIOP-M: 89-91%; OCCTOMM-1: 84-86%). Findings converge with the cumulative evidence that the IOP-29 and IOP-M are valuable additions to comprehensive neuropsychological batteries. Results also confirm that symptom and performance validity are distinct clinical constructs, and domain specificity should be considered while calibrating instruments.

Direct observation of peptide hydrogel self-assembly.

The characterization of self-assembling molecules presents significant experimental challenges, especially when associated with phase separation or precipitation. Transparent window infrared (IR) spectroscopy leverages site-specific probes that absorb in the "transparent window" region of the biomolecular IR spectrum. Carbon-deuterium (C-D) bonds are especially compelling transparent window probes since they are non-perturbative, can be readily introduced site selectively into peptides and proteins, and their stretch frequencies are sensitive to changes in the local molecular environment. Importantly, IR spectroscopy can be applied to a wide range of molecular samples regardless of solubility or physical state, making it an ideal technique for addressing the solubility challenges presented by self-assembling molecules. Here, we present the first continuous observation of transparent window probes following stopped-flow initiation. To demonstrate utility in a self-assembling system, we selected the MAX1 peptide hydrogel, a biocompatible material that has significant promise for use in drug delivery and medical applications. C-D labeled valine was synthetically introduced into five distinct positions of the twenty-residue MAX1 ß-hairpin peptide. Consistent with current structural models, steady-state IR absorption frequencies and linewidths of C-D bonds at all labeled positions indicate that these side chains occupy a hydrophobic region of the hydrogel and that the motion of side chains located in the middle of the hairpin is more restricted than those located on the hairpin ends. Following a rapid change in ionic strength to initiate self-assembly, the peptide absorption spectra were monitored as function of time, allowing determination of site-specific time constants. We find that within the experimental resolution, MAX1 self-assembly occurs as a cooperative process. These studies suggest that stopped-flow transparent window FTIR can be extended to other time-resolved applications, such as protein folding and enzyme kinetics.

Critical item (CR) analysis expands the classification accuracy of performance validity tests based on the forced choice paradigm-Replicating previously introduced CR cutoffs within the Word Choice Test.

OBJECTIVE: This study was designed to replicate previous research on critical item analysis within the Word Choice Test (WCT). METHOD: Archival data were collected from a mixed clinical sample of 119 consecutively referred adults (Mage = 51.7, Meducation = 14.7). The classification accuracy of the WCT was calculated against psychometrically defined criterion groups. RESULTS: Critical item analysis identified an additional 2%-5% of the sample that passed traditional cutoffs as noncredible. Passing critical items after failing traditional cutoffs was associated with weaker independent evidence of invalid performance, alerting the assessor to the elevated risk for false positives. Failing critical items in addition to failing select traditional cutoffs increased overall specificity. Non-White patients were 2.5 to 3.5 times more likely to Fail traditional WCT cutoffs, but select critical item cutoffs limited the risk to 1.5-2. CONCLUSIONS: Results confirmed the clinical utility of critical item analysis. Although the improvement in sensitivity was modest, critical items were effective at containing false positive errors in general, and especially in racially diverse patients. Critical item analysis appears to be a cost-effective and equitable method to improve an instrument's classification accuracy. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

BNT-15: Revised Performance Validity Cutoffs and Proposed Clinical Classification Ranges.

BACKGROUND: Abbreviated neurocognitive tests offer a practical alternative to full-length versions but often lack clear interpretive guidelines, thereby limiting their clinical utility. OBJECTIVE: To replicate validity cutoffs for the Boston Naming Test-Short Form (BNT-15) and to introduce a clinical classification system for the BNT-15 as a measure of object-naming skills. METHOD: We collected data from 43 university students and 46 clinical patients. Classification accuracy was computed against psychometrically defined criterion groups. Clinical classification ranges were developed using a z -score transformation. RESULTS: Previously suggested validity cutoffs (≤11 and ≤12) produced comparable classification accuracy among the university students. However, a more conservative cutoff (≤10) was needed with the clinical patients to contain the false-positive rate (0.20-0.38 sensitivity at 0.92-0.96 specificity). As a measure of cognitive ability, a perfect BNT-15 score suggests above average performance; ≤11 suggests clinically significant deficits. Demographically adjusted prorated BNT-15 T-scores correlated strongly (0.86) with the newly developed z -scores. CONCLUSION: Given its brevity (<5 minutes), ease of administration and scoring, the BNT-15 can function as a useful and cost-effective screening measure for both object-naming/English proficiency and performance validity. The proposed clinical classification ranges provide useful guidelines for practitioners.

Performance evaluation of flexible macrocycle docking in AutoDock.

Macrocycles represent an important class of ligands, both in natural products and designed drugs. In drug design, macrocyclizations can impart specific ligand conformations and contribute to passive permeation by encouraging intramolecular H-bonds. AutoDock-GPU and Vina can model macrocyclic ligands flexibly, without requiring the enumeration of macrocyclic conformers before docking. Here, we characterize the performance of the method for handling macrocyclic compounds, which is implemented and the default behaviour for ligand preparation with our ligand preparation pipeline, Meeko. A pseudoatom is used to encode bond geometry and produce an anisotropic closure force for macrocyclic rings. This method is evaluated on a diverse set of small molecule and peptide macrocycles, ranging from 7- to 33-membered rings, showing little accuracy loss compared to rigid redocking of the X-ray macrocycle conformers. This suggests that for conformationally flexible macrocycles with unknown binding modes, this method can be effectively used to predict the macrocycle conformation.

Examining the relationship between ethnic identity, depression, and alcohol use among students at historically black colleges/universities (HBCUs).

Alcohol abuse among college populations is a serious public health issue and is associated with many negative consequences; however, few studies have examined the drinking behavior of African American students at Historically Black Colleges/Universities (HBCUs). Alcohol abuse, including binge drinking, has historically been lower among African American than Caucasian college students; however, recent studies indicate that HBCU undergraduates are reporting increased rates of alcohol consumption, raising the question of which potential risk and protective factors are associated with alcohol consumption in this population. Ethnic identity has been identified as one protective factor for ethnic minorities, yet the processes that facilitate this relationship are little known. This study sought to further investigate the relationship between ethnic identity, depression, and alcohol use in a sample of 171 African American HBCU students. Participants were tightly clustered toward the desirable end on all measures, which restricted variability and thus attenuated correlational analyses to evaluate the relationships between study variables. There was a consistent pattern of high ethnic identification, minimal mental health distress, and low alcohol and substance use. Results suggest HBCU students are maintaining lower rates of alcohol consumption and binge drinking compared to nationally-stratified samples of undergraduates. Furthermore, these findings suggest African Americans attending HBCUs score highly on ethnic identity and resiliency. Cultural and social norms at HBCUs may help explain low rates of substance and alcohol misuse among HBCU students. Recommendations for culturally-informed alcohol use prevention and intervention strategies and for future research are provided.

The emotion word fluency test as an embedded performance validity indicator - Alone and in a multivariate validity composite.

OBJECTIVE: This project was designed to cross-validate existing performance validity cutoffs embedded within measures of verbal fluency (FAS and animals) and develop new ones for the Emotion Word Fluency Test (EWFT), a novel measure of category fluency. METHOD: The classification accuracy of the verbal fluency tests was examined in two samples (70 cognitively healthy university students and 52 clinical patients) against psychometrically defined criterion measures. RESULTS: A demographically adjusted T-score of ≤31 on the FAS was specific (.88-.97) to noncredible responding in both samples. Animals T ≤ 29 achieved high specificity (.90-.93) among students at .27-.38 sensitivity. A more conservative cutoff (T ≤ 27) was needed in the patient sample for a similar combination of sensitivity (.24-.45) and specificity (.87-.93). An EWFT raw score ≤5 was highly specific (.94-.97) but insensitive (.10-.18) to invalid performance. Failing multiple cutoffs improved specificity (.90-1.00) at variable sensitivity (.19-.45). CONCLUSIONS: Results help resolve the inconsistency in previous reports, and confirm the overall utility of existing verbal fluency tests as embedded validity indicators. Multivariate models of performance validity assessment are superior to single indicators. The clinical utility and limitations of the EWFT as a novel measure are discussed.

This will only take a minute: Time cutoffs are superior to accuracy cutoffs on the forced choice recognition trial of the Hopkins Verbal Learning Test - Revised.

OBJECTIVE: This study was designed to evaluate the classification accuracy of the recently introduced forced-choice recognition trial to the Hopkins Verbal Learning Test - Revised (FCRHVLT-R) as a performance validity test (PVT) in a clinical sample. Time-to-completion (T2C) for FCRHVLT-R was also examined. METHOD: Forty-three students were assigned to either the control or the experimental malingering (expMAL) condition. Archival data were collected from 52 adults clinically referred for neuropsychological assessment. Invalid performance was defined using expMAL status, two free-standing PVTs and two validity composites. RESULTS: Among students, FCRHVLT-R ≤11 or T2C ≥45 seconds was specific (0.86-0.93) to invalid performance. Among patients, an FCRHVLT-R ≤11 was specific (0.94-1.00), but relatively insensitive (0.38-0.60) to non-credible responding0. T2C ≥35 s produced notably higher sensitivity (0.71-0.89), but variable specificity (0.83-0.96). The T2C achieved superior overall correct classification (81-86%) compared to the accuracy score (68-77%). The FCRHVLT-R provided incremental utility in performance validity assessment compared to previously introduced validity cutoffs on Recognition Discrimination. CONCLUSIONS: Combined with T2C, the FCRHVLT-R has the potential to function as a quick, inexpensive and effective embedded PVT. The time-cutoff effectively attenuated the low ceiling of the accuracy scores, increasing sensitivity by 19%. Replication in larger and more geographically and demographically diverse samples is needed before the FCRHVLT-R can be endorsed for routine clinical application.

Boston Naming Test: Lose the Noose.

OBJECTIVE: Administering the noose item of the Boston Naming Test (BNT) has been questioned given the cultural, historical, and emotional salience of the noose in American culture. In response, some have modified the BNT by skipping/removing this item and giving the point as if the examinee responded correctly. It is unknown, however, whether modifying standardized administration and scoring in this manner affects clinical interpretation. In the present study, we examined the prevalence of noose item failure, whether demographic and clinical characteristics differed between those who responded correctly versus failed the item, and whether giving a point to those who failed affected clinical interpretation. METHOD: Participants included a mixed clinical sample of 762 adults, ages 18-88 years, seen for neuropsychological evaluation at one of five sites within the USA. RESULTS: Those who failed the item (13.78%) were more likely to be female, non-White, and have primary diagnoses of major neurocognitive disorder, epilepsy, or neurodevelopmental disorder. Noose item failure was associated with lower BNT total score, fewer years of education and lower intellectual functioning, expressive vocabulary, and single word reading. Giving a point to those who failed the item resulted in descriptor category change for 17.1%, primarily for patients with poor overall BNT performance. CONCLUSIONS: Only a small percentage of patients fail the noose item, but adding a point for these has an impact on score interpretation. Factors associated with poorer overall performance on the BNT, rather than specific difficulty with the noose item, likely account for the findings.

Assessing the Perturbing Effects of Drugs on Lipid Bilayers Using Gramicidin Channel-Based In Silico and In Vitro Assays.

Partitioning of bioactive molecules, including drugs, into cell membranes may produce indiscriminate changes in membrane protein function. As a guide to safe drug development, it therefore becomes important to be able to predict the bilayer-perturbing potency of hydrophobic/amphiphilic drugs candidates. Toward this end, we exploited gramicidin channels as molecular force probes and developed in silico and in vitro assays to measure drugs' bilayer-modifying potency. We examined eight drug-like molecules that were found to enhance or suppress gramicidin channel function in a thick 1,2-dierucoyl-sn-glycero-3-phosphocholine (DC22:1PC) but not in thin 1,2-dioleoyl-sn-glycero-3-phosphocholine (DC18:1PC) lipid bilayer. The mechanism underlying this difference was attributable to the changes in gramicidin dimerization free energy by drug-induced perturbations of lipid bilayer physical properties and bilayer-gramicidin interactions. The combined in silico and in vitro approaches, which allow for predicting the perturbing effects of drug candidates on membrane protein function, have implications for preclinical drug safety assessment.