Misfolding PRSS1 variant p.Ala61Val in a case of suspected intrauterine pancreatitis.

Background/objectives: Genetic variants in PRSS1 encoding human cationic trypsinogen are associated with hereditary pancreatitis. The clinically frequent variants exert their pathogenic effect by increasing intrapancreatic trypsin activity, while a distinct subset of variants causes disease via mutation-induced trypsinogen misfolding and endoplasmic reticulum (ER) stress. Here, we report a novel misfolding PRSS1 variant.

Identification and Ranking of Binding Sites from Structural Ensembles: Application to SARS-CoV-2.

Target identification and evaluation is a critical step in the drug discovery process. Although time-intensive and complex, the challenge becomes even more acute in the realm of infectious disease, where the rapid emergence of new viruses, the swift mutation of existing targets, and partial effectiveness of approved antivirals can lead to outbreaks of significant public health concern. The COVID-19 pandemic, caused by the SARS-CoV-2 virus, serves as a prime example of this, where despite the allocation of substantial resources, Paxlovid is currently the only effective treatment.

Predicting multiple conformations of ligand binding sites in proteins suggests that AlphaFold2 may remember too much.

The goal of this paper is predicting the conformational distributions of ligand binding sites using the AlphaFold2 (AF2) protein structure prediction program with stochastic subsampling of the multiple sequence alignment (MSA). We explored the opening of cryptic ligand binding sites in 16 proteins, where the closed and open conformations define the expected extreme points of the conformational variation. Due to the many structures of these proteins in the Protein Data Bank (PDB), we were able to study whether the distribution of X-ray structures affects the distribution of AF2 models.

Nanoplasmonic sensing to study CO and oxygen adsorption and CO oxidation on size-selected Pt clusters.

The adsorption of CO and oxygen and CO oxidation on size-selected Pt clusters were studied by indirect nanoplasmonic sensing (INPS) in the pressure range of 1-100 Pa at = 418 K. CO adsorption was reversible, inducing a blue-shift in the localised surface plasmon resonance (LSPR) response, regardless of the initial CO pressure. We observe a plateau at approximately Δ = -0.

Which cryptic sites are feasible drug targets?

Cryptic sites can expand the space of druggable proteins, but the potential usefulness of such sites needs to be investigated before any major effort. Given that the binding pockets are not formed, the druggability of such sites is not well understood. The analysis of proteins and their ligands shows that cryptic sites that are formed primarily by the motion of side chains moving out of the pocket to enable ligand binding generally do not bind drug-sized molecules with sufficient potency.

MHC-Fine: Fine-tuned AlphaFold for precise MHC-peptide complex prediction.

The precise prediction of major histocompatibility complex (MHC)-peptide complex structures is pivotal for understanding cellular immune responses and advancing vaccine design. In this study, we enhanced AlphaFold's capabilities by fine-tuning it with a specialized dataset consisting of exclusively high-resolution class I MHC-peptide crystal structures. This tailored approach aimed to address the generalist nature of AlphaFold's original training, which, while broad-ranging, lacked the granularity necessary for the high-precision demands of class I MHC-peptide interaction prediction.

[Thrombolysis treatment and multi- disciplinary management of central retinal artery occlusion in comparison with traditional ophthalmological treatment options].

Background And Purpose:

Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites.

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands.

Low-Temperature Selective Oxidative Dehydrogenation of Cyclohexene by Titania-Supported Nanostructured Pd, Pt, and Pt-Pd Catalytic Films.

Films of titania-supported monometallic Pd, Pt, and bimetallic Pt-Pd catalysts made of metallic nanoparticles were prepared by magnetron sputtering and studied in the oxidative dehydrogenation (ODH) of cyclohexene. Pd/TiO and Pt-Pd/TiO were found active at as low temperature as 150 °C and showed high catalytic activity with high conversion (up to 81%) and benzene selectivity exceeding 97% above 200 °C. In turn, the Pt/TiO catalyst performed poorly with the onset of benzene production at 200 °C only and conversions not exceeding 5%.

Conservation of Hot Spots and Ligand Binding Sites in Protein Models by AlphaFold2.

The neural network-based program AlphaFold2 (AF2) provides high accuracy structure prediction for a large fraction of globular proteins. An important question is whether these models are accurate enough for reliably docking small ligands. Several recent papers and the results of CASP15 reveal that local conformational errors reduce the success rates of direct ligand docking.

MHC-Fine: Fine-tuned AlphaFold for Precise MHC-Peptide Complex Prediction.

The precise prediction of Major Histocompatibility Complex (MHC)-peptide complex structures is pivotal for understanding cellular immune responses and advancing vaccine design. In this study, we enhanced AlphaFold's capabilities by fine-tuning it with a specialized dataset comprised by exclusively high-resolution MHC-peptide crystal structures. This tailored approach aimed to address the generalist nature of AlphaFold's original training, which, while broad-ranging, lacked the granularity necessary for the high-precision demands of MHC-peptide interaction prediction.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target.

Cyclohexane Oxidative Dehydrogenation on Graphene-Oxide-Supported Cobalt Ferrite Nanohybrids: Effect of Dynamic Nature of Active Sites on Reaction Selectivity.

In this work, we investigated cyclohexane oxidative dehydrogenation (ODH) catalyzed by cobalt ferrite nanoparticles supported on reduced graphene oxide (RGO). We aim to identify the active sites that are specifically responsible for full and partial dehydrogenation using advanced spectroscopic techniques such as X-ray photoelectron emission microscopy (XPEEM) and X-ray photoelectron spectroscopy (XPS) along with kinetic analysis. Spectroscopically, we propose that Fe/T sites could exclusively produce benzene through full cyclohexane dehydrogenation, while kinetic analysis shows that oxygen-derived species (O*) are responsible for partial dehydrogenation to form cyclohexene in a single catalytic sojourn.

Accurate ligand-protein docking in CASP15 using the ClusPro LigTBM server.

In the ligand prediction category of CASP15, the challenge was to predict the positions and conformations of small molecules binding to proteins that were provided as amino acid sequences or as models generated by the AlphaFold2 program. For most targets, we used our template-based ligand docking program ClusPro ligTBM, also implemented as a public server available at https://ligtbm.cluspro.

Improved prediction of MHC-peptide binding using protein language models.

Major histocompatibility complex Class I (MHC-I) molecules bind to peptides derived from intracellular antigens and present them on the surface of cells, allowing the immune system (T cells) to detect them. Elucidating the process of this presentation is essential for regulation and potential manipulation of the cellular immune system. Predicting whether a given peptide binds to an MHC molecule is an important step in the above process and has motivated the introduction of many computational approaches to address this problem.

The ClusPro AbEMap web server for the prediction of antibody epitopes.

Antibodies play an important role in the immune system by binding to molecules called antigens at their respective epitopes. These interfaces or epitopes are structural entities determined by the interactions between an antibody and an antigen, making them ideal systems to analyze by using docking programs. Since the advent of high-throughput antibody sequencing, the ability to perform epitope mapping using only the sequence of the antibody has become a high priority.

High Accuracy Prediction of PROTAC Complex Structures.

The design of PROteolysis-TArgeting Chimeras (PROTACs) requires bringing an E3 ligase into proximity with a target protein to modulate the concentration of the latter through its ubiquitination and degradation. Here, we present a method for generating high-accuracy structural models of E3 ligase-PROTAC-target protein ternary complexes. The method is dependent on two computational innovations: adding a "silent" convolution term to an efficient protein-protein docking program to eliminate protein poses that do not have acceptable linker conformations and clustering models of multiple PROTACs that use the same E3 ligase and target the same protein.

Absence of a pressure gap and atomistic mechanism of the oxidation of pure Co nanoparticles.

Understanding chemical reactivity and magnetism of 3d transition metal nanoparticles is of fundamental interest for applications in fields ranging from spintronics to catalysis. Here, we present an atomistic picture of the early stage of the oxidation mechanism and its impact on the magnetism of Co nanoparticles. Our experiments reveal a two-step process characterized by (i) the initial formation of small CoO crystallites across the nanoparticle surface, until their coalescence leads to structural completion of the oxide shell passivating the metallic core; (ii) progressive conversion of the CoO shell to CoO and void formation due to the nanoscale Kirkendall effect.

Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes.

Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field.

API Development Increases Access to Shared Computing Resources at Boston University.

Within the last few decades, increases in computational resources have contributed enormously to the progress of science and engineering (S & E). To continue making rapid advancements, the S & E community must be able to access computing resources. One way to provide such resources is through High-Performance Computing (HPC) centers.

Novel p.G250A Mutation Associated with Chronic Pancreatitis Highlights Misfolding-Prone Region in Carboxypeptidase A1 (CPA1).

Inborn mutations in the digestive protease carboxypeptidase A1 (CPA1) gene may be associated with hereditary and idiopathic chronic pancreatitis (CP). Pathogenic mutations, such as p.N256K, cause intracellular retention and reduced secretion of CPA1, accompanied by endoplasmic reticulum (ER) stress, suggesting that mutation-induced misfolding underlies the phenotype.

Mechanism of Catalytic CO Hydrogenation to Methane and Methanol Using a Bimetallic CuPd Cluster at a Zirconia Support.

For very small nanocluster-based catalysts, the exploration of the influence of the particle size, composition, and support offers precisely variable parameters in a wide material search space to control catalysts' performance. We present the mechanism of the CO methanation reaction on the oxidized bimetallic CuPd tetramer (CuPdO) supported on a zirconia model support represented by ZrO based on the energy profile obtained from density functional theory calculations on the reaction of CO and H. In order to determine the role of the Pd atom, the performance of CuPdO with monometallic CuO at the same support has been compared.

Oxidative dehydrogenation of cyclohexene on atomically precise subnanometer CuPd (0 ≤ ≤ 4) tetramer clusters: the effect of cluster composition and support on performance.

The pronounced effects of the composition of four-atom monometallic Cu and Pd and bimetallic CuPd clusters and the support on the catalytic activity and selectivity in the oxidative dehydrogenation of cyclohexene are reported. The ultra-nanocrystalline diamond supported clusters are highly active and dominantly produce benzene; some of the mixed clusters also produce cyclohexadiene, which are all clusters with a much suppressed combustion channel. The also highly active TiO-supported tetramers solely produce benzene, without any combustion to CO.