Aortic disease and cardiomyopathy in patients with a novel DNMT3A gene variant causing Tatton-Brown-Rahman syndrome.

Tatton-Brown-Rahman syndrome (TBRS) is a rare congenital genetic disorder caused by autosomal dominant pathogenic variants in the DNA methyltransferase DNMT3A gene. Typical TBRS clinical features are overgrowth, intellectual disability, and minor facial anomalies. However, since the syndrome was first described in 2014, a widening spectrum of abnormalities is being described.

PPI3D: a web server for searching, analyzing and modeling protein-protein, protein-peptide and protein-nucleic acid interactions.

Structure-resolved protein interactions with other proteins, peptides and nucleic acids are key for understanding molecular mechanisms. The PPI3D web server enables researchers to query preprocessed and clustered structural data, analyze the results and make homology-based inferences for protein interactions. PPI3D offers three interaction exploration modes: (i) all interactions for proteins homologous to the query, (ii) interactions between two proteins or their homologs and (iii) interactions within a specific PDB entry.

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.

Prediction of protein assemblies by structure sampling followed by interface-focused scoring.

Proteins often function as part of permanent or transient multimeric complexes, and understanding function of these assemblies requires knowledge of their three-dimensional structures. While the ability of AlphaFold to predict structures of individual proteins with unprecedented accuracy has revolutionized structural biology, modeling structures of protein assemblies remains challenging. To address this challenge, we developed a protocol for predicting structures of protein complexes involving model sampling followed by scoring focused on the subunit-subunit interaction interface.

The COMER web server for protein analysis by homology.

Summary: Sequence homology is a basic concept in protein evolution, structure and function studies. However, there are not many different tools and services for homology searches being sensitive, accurate and fast at the same time. We present a new web server for protein analysis based on COMER2, a sequence alignment and homology search method that exhibits these characteristics.

PIGN-Related Disease in Two Lithuanian Families: A Report of Two Novel Pathogenic Variants, Molecular and Clinical Characterisation.

Background and Objectives: Pathogenic variants of PIGN are a known cause of multiple congenital anomalies-hypotonia-seizures syndrome 1 (MCAHS1). Many affected individuals have clinical features overlapping with Fryns syndrome and are mainly characterised by developmental delay, congenital anomalies, hypotonia, seizures, and specific minor facial anomalies. This study investigates the clinical and molecular data of three individuals from two unrelated families, the clinical features of which were consistent with a diagnosis of MCAHS1.

Donor Splice Site Variant in Causes Christianson Syndrome in a Lithuanian Family: A Case Report.

Background and Objectives: The pathogenic variants of SLC9A6 are a known cause of a rare, X-linked neurological disorder called Christianson syndrome (CS). The main characteristics of CS are developmental delay, intellectual disability, and neurological findings. This study investigated the genetic basis and explored the molecular changes that led to CS in two male siblings presenting with intellectual disability, epilepsy, behavioural problems, gastrointestinal dysfunction, poor height, and weight gain.

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment.

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers).

Modeling of protein complexes in CASP14 with emphasis on the interaction interface prediction.

The goal of CASP experiments is to monitor the progress in the protein structure prediction field. During the 14th CASP edition we aimed to test our capabilities of predicting structures of protein complexes. Our protocol for modeling protein assemblies included both template-based modeling and free docking.

Mapping of Recognition Sites of Monoclonal Antibodies Responsible for the Inhibition of Pneumolysin Functional Activity.

The pathogenicity of many bacteria, including depends on pore-forming toxins (PFTs) that cause host cell lysis by forming large pores in cholesterol-containing cell membranes. Therefore, PFTs-neutralising antibodies may provide useful tools for reducing pathogenic effects. This study aimed at the development and characterisation of monoclonal antibodies (MAbs) with neutralising activity to PFT pneumolysin (PLY).

Template-Based Modeling of Protein Complexes Using the PPI3D Web Server.

There is a large gap between the numbers of known protein-protein interactions and the corresponding experimentally solved structures of protein complexes. Fortunately, this gap can be in part bridged by computational structure modeling methods. Currently, template-based modeling is the most accurate means to predict both individual protein structures and protein complexes.

Template-based modeling of diverse protein interactions in CAPRI rounds 38-45.

Structures of proteins complexed with other proteins, peptides, or ligands are essential for investigation of molecular mechanisms. However, the experimental structures of protein complexes of interest are often not available. Therefore, computational methods are widely used to predict these structures, and, of those methods, template-based modeling is the most successful.

Structural modeling of protein complexes: Current capabilities and challenges.

Proteins frequently interact with each other, and the knowledge of structures of the corresponding protein complexes is necessary to understand how they function. Computational methods are increasingly used to provide structural models of protein complexes. Not surprisingly, community-wide Critical Assessment of protein Structure Prediction (CASP) experiments have recently started monitoring the progress in this research area.

Exogenous interleukin-1α signaling negatively impacts acquired chemoresistance and alters cell adhesion molecule expression pattern in colorectal carcinoma cells HCT116.

Proinflammatory cytokine and chemokine signaling from the tumor microenvironment is thought to be crucial for developing and sustaining colorectal cancer by regulating a multitude of pathways associated with a variety of cellular mechanisms. Among these pathways there is acquired chemoresistance, which is usually a major obstacle in the way towards successful chemotherapeutic treatment of advanced colorectal cancer cases. Despite of an emerging body of data published on the role of cytokine signaling network in cancer, little is known about the effects of the upstream cytokine interleukin-1α (IL-1α) signaling to the cancer cells.

SKEMPI 2.0: an updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation.

Motivation: Understanding the relationship between the sequence, structure, binding energy, binding kinetics and binding thermodynamics of protein-protein interactions is crucial to understanding cellular signaling, the assembly and regulation of molecular complexes, the mechanisms through which mutations lead to disease, and protein engineering.

Results: We present SKEMPI 2.0, a major update to our database of binding free energy changes upon mutation for structurally resolved protein-protein interactions.

Modeling of protein complexes in CAPRI Round 37 using template-based approach combined with model selection.

We participated in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), held jointly with the 12th edition of the Critical Assessment of protein Structure Prediction (CASP12), having two major objectives. First, we intended to test the utility of our PPI3D web server in finding and selecting templates for comparative modeling of structures of protein complexes. Our second aim was to evaluate the ability of our model accuracy estimation method VoroMQA to score and rank structural models for protein-protein interactions.

The PPI3D web server for searching, analyzing and modeling protein-protein interactions in the context of 3D structures.

Summary: The PPI3D web server is focused on searching and analyzing the structural data on protein-protein interactions. Reducing the data redundancy by clustering and analyzing the properties of interaction interfaces using Voronoi tessellation makes this software a highly effective tool for addressing different questions related to protein interactions.

Availability And Implementation: The server is freely accessible at http://bioinformatics.

Inferring the microscopic surface energy of protein-protein interfaces from mutation data.

Mutations at protein-protein recognition sites alter binding strength by altering the chemical nature of the interacting surfaces. We present a simple surface energy model, parameterized with empirical ΔΔG values, yielding mean energies of -48 cal mol(-1) Å(-2) for interactions between hydrophobic surfaces, -51 to -80 cal mol(-1) Å(-2) for surfaces of complementary charge, and 66-83 cal mol(-1) Å(-2) for electrostatically repelling surfaces, relative to the aqueous phase. This places the mean energy of hydrophobic surface burial at -24 cal mol(-1) Å(-2) .

QSAR analysis of blood-brain distribution: the influence of plasma and brain tissue binding.

The extent of brain delivery expressed as steady-state brain/blood distribution ratio (log BB) is the most frequently used parameter for characterizing central nervous system exposure of drugs and drug candidates. The aim of the current study was to propose a physicochemical QSAR model for log BB prediction. Model development involved the following steps: (i) A data set consisting of 470 experimental log BB values determined in rodents was compiled and verified to ensure that selected data represented drug disposition governed by passive diffusion across blood-brain barrier.

Trainable structure-activity relationship model for virtual screening of CYP3A4 inhibition.

A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for >800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain.

Probabilistic prediction of the human CYP3A4 and CYP2D6 metabolism sites.

This article briefly introduces the results of in silico prediction of the most probable metabolism sites for the human cytochrome P450 3A4 and 2D6 isoforms. Ligand-based QSAR models have been developed using a novel GALAS modeling approach, and provide probabilities of being a target of CYP3A4 or CYP2D6 for any atom in a molecule. The GALAS-model development methodology allows evaluation of the reliability of predictions in the form of estimated prediction Reliability Indices (RIs).