Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR.

We introduce AlphaFold-NMR, a novel approach to NMR structure determination that reveals previously undetected protein conformational states. Unlike conventional NMR methods that rely on NOE-derived spatial restraints, AlphaFold-NMR combines AI-driven conformational sampling with Bayesian scoring of realistic protein models against NOESY and chemical shift data. This method uncovers alternative conformational states of the enzyme luciferase, involving large-scale changes in the lid, binding pockets, and other surface cavities.

An isothermal calorimetry assay for determining steady state kinetic and Ensitrelvir inhibition parameters for SARS-CoV-2 3CL-protease.

This manuscript details the application of Isothermal Titration Calorimetry (ITC) to characterize the kinetics of 3CL, the main protease from the Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2), and its inhibition by Ensitrelvir, a known non-covalent inhibitor. 3CL is essential for producing the proteins necessary for viral infection, which led to the COVID-19 pandemic. The ITC-based assay provided rapid and reliable measurements of 3CL activity, allowing for the direct derivation of the kinetic enzymatic constants K and k by monitoring the thermal power required to maintain a constant temperature as the substrate is consumed.

Synthesis and Structure-Activity Relationship of Covalent Inhibitors of SARS-CoV-2 Papain-Like Protease with Antiviral Potency.

The papain-like protease (PLpro) is a highly conserved domain encoded by the coronavirus (CoV) genome and it plays an essential role in the replication and maturation of the virus in addition to weakening host immune response. Due to the virus's reliance on PLpro for survival and propagation, small-molecule inhibitors of PLpro serve as an attractive model for direct-acting antiviral therapeutic agents against SARS-CoV-2. Building upon existing work aimed at designing covalent inhibitors against PLpro, we report the synthesis and structure-activity relationship of analogs based on the known covalent inhibitor 1 (Sanders, et al.

Integrative Modeling of Protein-Polypeptide Complexes by Bayesian Model Selection using AlphaFold and NMR Chemical Shift Perturbation Data.

Protein-polypeptide interactions, including those involving intrinsically-disordered peptides and intrinsically-disordered regions of protein binding partners, are crucial for many biological functions. However, experimental structure determination of protein-peptide complexes can be challenging. Computational methods, while promising, generally require experimental data for validation and refinement.

Enumerative Discovery of Noncanonical Polypeptide Secondary Structures.

Energetically favorable local interactions can overcome the entropic cost of chain ordering and cause otherwise flexible polymers to adopt regularly repeating backbone conformations. A prominent example is the α helix present in many protein structures, which is stabilized by , + 4 hydrogen bonds between backbone peptide units. With the increased chemical diversity offered by unnatural amino acids and backbones, it has been possible to identify regularly repeating structures not present in proteins, but to date, there has been no systematic approach for identifying new polymers likely to have such structures despite their considerable potential for molecular engineering.

Modeling Alternative Conformational States of Pseudo-Symmetric Solute Carrier Transporters using Methods from Deep Learning.

The Solute Carrier (SLC) superfamily of integral membrane proteins function to transport a wide array of small molecules across plasma and organelle membranes. SLC proteins also function as important drug transporters and as viral receptors. Despite being classified as a single superfamily, SLC proteins do not share a single common fold classification; however, most belong to multi-pass transmembrane helical protein fold families.

Design of intrinsically disordered region binding proteins.

Intrinsically disordered proteins and peptides play key roles in biology, but the lack of defined structures and the high variability in sequence and conformational preferences has made targeting such systems challenging. We describe a general approach for designing proteins that bind intrinsically disordered protein regions in diverse extended conformations with side chains fitting into complementary binding pockets. We used the approach to design binders for 39 highly diverse unstructured targets and obtain designs with pM to 100 nM affinities in 34 cases, testing ∼22 designs per target (including polar targets).

Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR.

We introduce AlphaFold-NMR, a novel approach to NMR structure determination that reveals previously undetected protein conformational states. Unlike conventional NMR methods that rely on NOE-derived spatial restraints, AlphaFold-NMR combines AI-driven conformational sampling with Bayesian scoring of realistic protein models against NOESY and chemical shift data. This method uncovers alternative conformational states of the enzyme luciferase, involving large-scale changes in the lid, binding pockets, and other surface cavities.

A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.

Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank.

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NEF and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints.

An isothermal calorimetry assay for determining steady state kinetic and enzyme inhibition parameters for SARS-CoV-2 3CL-protease.

This manuscript describes the application of Isothermal Titration Calorimetry (ITC) to characterize the kinetics of 3CL from the Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2) and its inhibition by Ensitrelvir, a known non-covalent inhibitor. 3CL is the main protease that plays a crucial role of producing the whole array of proteins necessary for the viral infection that caused the spread of COVID-19, responsible for millions of deaths worldwide as well as global economic and healthcare crises in recent years. The proposed calorimetric method proved to have several advantages over the two types of enzymatic assays so far applied to this system, namely Förster Resonance Energy Transfer (FRET) and Liquid Chromatography-Mass Spectrometry (LC-MS).

The NS1 protein of influenza B virus binds 5'-triphosphorylated dsRNA to suppress RIG-I activation and the host antiviral response.

Influenza A and B viruses overcome the host antiviral response to cause a contagious and often severe human respiratory disease. Here, integrative structural biology and biochemistry studies on non-structural protein 1 of influenza B virus (NS1B) reveal a previously unrecognized viral mechanism for innate immune evasion. Conserved basic groups of its C-terminal domain (NS1B-CTD) bind 5'triphosphorylated double-stranded RNA (5'-ppp-dsRNA), the primary pathogen-associated feature that activates the host retinoic acid-inducible gene I protein (RIG-I) to initiate interferon synthesis and the cellular antiviral response.

Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data Bank.

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NMR exchange (NEF) and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints.

Sifting Through the Noise: A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners, but often include false positives. Furthermore, they provide no information about what the binding region is (e.

Protocol for production and purification of SARS-CoV-2 3CL.

3CL protease from SARS-CoV-2 is a primary target for COVID-19 antiviral drug development. Here, we present a protocol for 3CL production in Escherichia coli. We describe steps to purify 3CL, expressed as a fusion with the Saccharomyces cerevisiae SUMO protein, with yields up to 120 mg L following cleavage.

Cell-permeable chameleonic peptides: Exploiting conformational dynamics in de novo cyclic peptide design.

Membrane-traversing peptides offer opportunities for targeting intracellular proteins and oral delivery. Despite progress in understanding the mechanisms underlying membrane traversal in natural cell-permeable peptides, there are still several challenges to designing membrane-traversing peptides with diverse shapes and sizes. Conformational flexibility appears to be a key determinant of membrane permeability of large macrocycles.

Structure Determination of Challenging Protein-Peptide Complexes Combining NMR Chemical Shift Data and Molecular Dynamics Simulations.

Intrinsically disordered regions of proteins often mediate important protein-protein interactions. However, the folding-upon-binding nature of many polypeptide-protein interactions limits the ability of modeling tools to predict the three-dimensional structures of such complexes. To address this problem, we have taken a tandem approach combining NMR chemical shift data and molecular simulations to determine the structures of peptide-protein complexes.