Assessing PDB macromolecular crystal structure confidence at the individual amino acid residue level.

Approximately 87% of the more than 190,000 atomic-level three-dimensional (3D) biostructures in the PDB were determined using macromolecular crystallography (MX). Agreement between 3D atomic coordinates and experimental data for >100 million individual amino acid residues occurring within ∼150,000 PDB MX structures was analyzed in detail. The real-space correlation coefficient (RSCC) calculated using the 3D atomic coordinates for each residue and experimental-data-derived electron density enables outlier detection of unreliable atomic coordinates (particularly important for poorly resolved side-chain atoms) and ready evaluation of local structure quality by PDB users.

Establishing a blockchain-enabled Indigenous data sovereignty framework for genomic data.

Technological advances have enabled the rapid generation of health and genomic data, though rarely do these technologies account for the values and priorities of marginalized communities. In this commentary, we conceptualize a blockchain genomics data framework built out of the concept of Indigenous Data Sovereignty.

Structure-selected RBM immunogens prime polyclonal memory responses that neutralize SARS-CoV-2 variants of concern.

Successful control of the COVID-19 pandemic depends on vaccines that prevent transmission. The full-length Spike protein is highly immunogenic but the majority of antibodies do not target the virus: ACE2 interface. In an effort to affect the quality of the antibody response focusing it to the receptor-binding motif (RBM) we generated a series of conformationally-constrained immunogens by inserting solvent-exposed RBM amino acid residues into hypervariable loops of an immunoglobulin molecule.

Playing catch-up in building an open research commons.

As efforts advance around the globe, the US falls behind.

The role of BAG3 in dilated cardiomyopathy and its association with Charcot-Marie-Tooth disease type 2.

Bcl2-associated athanogene 3 (BAG3) is a multifunctional cochaperone responsible for protein quality control within cells. BAG3 interacts with chaperones HSPB8 and Hsp70 to transport misfolded proteins to the Microtubule Organizing Center (MTOC) and degrade them in autophagosomes in a process known as Chaperone Assisted Selective Autophagy (CASA). Mutations in the second conserved IPV motif of BAG3 are known to cause Dilated Cardiomyopathy (DCM) by inhibiting adequate removal of non-native proteins.

Exploring protein symmetry at the RCSB Protein Data Bank.

The symmetry of biological molecules has fascinated structural biologists ever since the structure of hemoglobin was determined. The Protein Data Bank (PDB) archive is the central global archive of three-dimensional (3D), atomic-level structures of biomolecules, providing open access to the results of structural biology research with no limitations on usage. Roughly 40% of the structures in the archive exhibit some type of symmetry, including formal global symmetry, local symmetry, or pseudosymmetry.

How Good Is the Density-Corrected SCAN Functional for Neutral and Ionic Aqueous Systems, and What Is So Right about the Hartree-Fock Density?

Density functional theory (DFT) is the most widely used electronic structure method, due to its simplicity and cost effectiveness. The accuracy of a DFT calculation depends not only on the choice of the density functional approximation (DFA) adopted but also on the electron density produced by the DFA. SCAN is a modern functional that satisfies all known constraints for meta-GGA functionals.

Computer-aided drug design, quantum-mechanical methods for biological problems.

Quantum chemistry enables to study systems with chemical accuracy (<1 kcal/mol from experiment) but is restricted to a handful of atoms due to its computational expense. This has led to ongoing interest to optimize and simplify these methods while retaining accuracy. Implementing quantum mechanical (QM) methods on modern hardware such as multiple-GPUs is one example of how the field is optimizing performance.

BIPSPI+: Mining Type-Specific Datasets of Protein Complexes to Improve Protein Binding Site Prediction.

Computational approaches for predicting protein-protein interfaces are extremely useful for understanding and modelling the quaternary structure of protein assemblies. In particular, partner-specific binding site prediction methods allow delineating the specific residues that compose the interface of protein complexes. In recent years, new machine learning and other algorithmic approaches have been proposed to solve this problem.

Machine-learning-based virtual screening to repurpose drugs for treatment of Candida albicans infection.

Background: Approximately 30% of Candida genus isolates are resistant to all currently available antifungal drugs and it is highly important to develop new treatments. Additionally, many current drugs are toxic and cause unwanted side effects. 1,3-beta-glucan synthase is an essential enzyme that builds the cell walls of Candida.

Amino acids control blood glucose levels through mTOR signaling.

Amino Acids are not only major nutrient sources, but also serve as chemical signals to control cellular growth. Rab1A recently emerged as a key component in amino acid sensing and signaling to activate the mTOR complex1 (mTORC1). In a recently published study [1], we generated tamoxifen-inducible, conditional whole-body Rab1A knockout in adult mice.

RCSB Protein Data Bank 1D3D module: displaying positional features on macromolecular assemblies.

Motivation: Mapping positional features from one-dimensional (1D) sequences onto three-dimensional (3D) structures of biological macromolecules is a powerful tool to show geometric patterns of biochemical annotations and provide a better understanding of the mechanisms underpinning protein and nucleic acid function at the atomic level.

Results: We present a new library designed to display fully customizable interactive views between 1D positional features of protein and/or nucleic acid sequences and their 3D structures as isolated chains or components of macromolecular assemblies.

Availability And Implementation: https://github.

Genetic and Structural Analysis of SARS-CoV-2 Spike Protein for Universal Epitope Selection.

Evaluation of immunogenic epitopes for universal vaccine development in the face of ongoing SARS-CoV-2 evolution remains a challenge. Herein, we investigate the genetic and structural conservation of an immunogenically relevant epitope (C662-C671) of spike (S) protein across SARS-CoV-2 variants to determine its potential utility as a broad-spectrum vaccine candidate against coronavirus diseases. Comparative sequence analysis, structural assessment, and molecular dynamics simulations of C662-C671 epitope were performed.

Assessing the Interplay between Functional-Driven and Density-Driven Errors in DFT Models of Water.

We investigate the interplay between functional-driven and density-driven errors in different density functional approximations within density functional theory (DFT) and the implications of these errors for simulations of water with DFT-based data-driven potentials. Specifically, we quantify density-driven errors in two widely used dispersion-corrected functionals derived within the generalized gradient approximation (GGA), namely BLYP-D3 and revPBE-D3, and two modern -GGA functionals, namely strongly constrained and appropriately normed (SCAN) and B97M-rV. The effects of functional-driven and density-driven errors on the interaction energies are first assessed for the water clusters of the BEGDB dataset.

Potential SARS-CoV-2 nonstructural proteins inhibitors: drugs repurposing with drug-target networks and deep learning.

Background: In the current COVID-19 pandemic, with an absence of approved drugs and widely accessible vaccines, repurposing existing drugs is vital to quickly developing a treatment for the disease.

Methods: In this study, we used a dataset consisting of sequences of viral proteins and chemical structures of pharmaceutical drugs for known drug-target interactions (DTIs) and artificially generated non-interacting DTIs to train a binary classifier with the ability to predict new DTIs. Random Forest (RF), deep neural network (DNN), and convolutional neural networks (CNN) were tested.

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology.

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org).

Modular and mechanistic changes across stages of colorectal cancer.

Background: While mechanisms contributing to the progression and metastasis of colorectal cancer (CRC) are well studied, cancer stage-specific mechanisms have been less comprehensively explored. This is the focus of this manuscript.

Methods: Using previously published data for CRC (Gene Expression Omnibus ID GSE21510), we identified differentially expressed genes (DEGs) across four stages of the disease.

Effects of data and entity ablation on multitask learning models for biomedical entity recognition.

Motivation: Training domain-specific named entity recognition (NER) models requires high quality hand curated gold standard datasets which are time-consuming and expensive to create. Furthermore, the storage and memory required to deploy NLP models can be prohibitive when the number of tasks is large. In this work, we explore utilizing multi-task learning to reduce the amount of training data needed to train new domain-specific models.

The Pfizer Crystal Structure Database: An essential tool for structure-based design at Pfizer.

Pfizer's Crystal Structure Database (CSDB) is a key enabling technology that allows scientists on structure-based projects rapid access to Pfizer's vast library of in-house crystal structures, as well as a significant number of structures imported from the Protein Data Bank. In addition to capturing basic information such as the asymmetric unit coordinates, reflection data, and the like, CSDB employs a variety of automated methods to first ensure a standard level of annotations and error checking, and then to add significant value for design teams by processing the structures through a sequence of algorithms that prepares the structures for use in modeling. The structures are made available, both as the original asymmetric unit as submitted, as well as the final prepared structures, through REST-based web services that are consumed by several client desktop applications.

Combined Theoretical, Bioinformatic, and Biochemical Analyses of RNA Editing by Adenine Base Editors.

Adenine base editors (ABEs) have been subjected to multiple rounds of mutagenesis with the goal of optimizing their function as efficient and precise genome editing agents. Despite an ever-expanding data set of ABE mutants and their corresponding DNA or RNA-editing activity, the molecular mechanisms defining these changes remain to be elucidated. In this study, we provide a systematic interpretation of the nature of these mutations using an entropy-based classification model that relies on evolutionary data from extant protein sequences.

Modeling of mutant superoxide dismutase 1 octamers with cross-linked disulfide bonds.

Mutant superoxide dismutase 1 (SOD1) may form cyclic structures due to its greater instability from aberrant demetallization and oxidation of cysteine bonds. This cyclic structure may allow SOD1 to form ion channels on membranes such as the mitochondrial membrane, causing imbalances in the concentration of intracellular ions as a potential mechanism for the progressive neuron death involved in amyotrophic lateral sclerosis (ALS). Using docking programs within modeling software, models of mutant SOD1 dimers and eventually ring oligomers were constructed based on known descriptions of such structures in addition to information on the orientation of the models associated with a membrane.