Biology subjects

DeGrado, W.

Publications and source records attributed to DeGrado, W..

10 recordsLinked to original sources

bioRxiv2025

The Emergence of Novel Versus Known Three-Dimensional Structures from Random Sequences.

It has been hypothesized that while random sequences are unlikely to fold into proteins of the length of globular proteins, repeated random sequences are more likely to adopt stably folded structures, with implications for molecular evolution. We used structure prediction methods to determine the foldability of approximately 120-residue sequences composed of 5-to 60-residue random repeats. With repeats of less than 30-residues, sequences were frequently discovered (1-12%) that fold with high confidence. For less than 60-residue repeats, we frequently observe {beta}-solenoids, similar to those seen in natural proteins. We observe solenoids stabilized by apolar packing as well as ones stabilized by polar interactions with Ca2+ in the core of the structure as in natural RTX domains. Helical bundles were observed with high frequency when insertions or deletions (INDELs) were included between blocks of repeating sequences. We also observed a new super-secondary structure consisting of a tightly wound -helical screw, and experimentally confirmed its stability and structure by CD spectroscopy and X-ray crystallography. Thus, structure predictors can discover structures that are well out of the distribution of the data upon which they were trained. Beyond 40-residue repeat lengths very few sequences were predicted to fold. The small number of structures we observed were representative of well-established major classes of tertiary structures; greater sampling would be needed to discover novel structures from a random distribution. These studies illuminate dark matter regions of protein structure space and support previous predictions that proteins evolved through the assortment of shorter peptide sequences. Significance statementThe availability of powerful and accurate programs for predicting protein three-dimensional structures enables one to ask fundamental questions concerning the origin of folded functional proteins during evolution. We show that 120-residue proteins composed of random sequences repeated in tandem are predicted to be much more likely to fold than fully random proteins. These studies validate previous predictions that proteins evolved through the repetition and assortment of short peptide sequences. Also, some of the predicted structures represent novel conformations, which were confirmed experimentally. These findings advance our understanding of molecular evolution and have implications for design of novel proteins.

biophysics↗

bioRxiv2024

Sequence-dependent scale for translocon-mediated insertion of interfacial helices in membranes

Biological membranes consist of a lipid bilayer studded with integral and peripheral membrane proteins. Most -helical membrane proteins require protein-conducting insertases known as translocons to assist in their membrane insertion and folding. While the sequence-dependent propensities for a helix to either translocate through the translocon or insert into the membrane have been codified into numerical hydrophobicity scales, the corresponding propensity to partition into the membrane interface remains unraveled. By engineering diagnostic glycosylation sites around test peptide sequences inserted into a host protein, we devised a system that can differentiate between water-soluble, surface-bound, and transmembrane (TM) states of the sequence based on its glycosylation pattern. Using this system, we determined the sequence-dependent propensities for transfer from the translocon to a TM, interfacial or extramembrane space. UMAP analysis of a large collection of TM and water-soluble helices provide useful embeddings for analysis of these propensities and aid in understanding the physical properties and functions of antimicrobial, lytic, and fusogenic peptides.

molecular biology↗

bioRxiv2024

ProBASS: a language model with sequence and structural features for predicting the effect of mutations on binding affinity

Protein-protein interactions (PPIs) govern virtually all cellular processes. Even a single mutation within PPI can significantly influence overall protein functionality and potentially lead to various types of diseases. To date, numerous approaches have emerged for predicting the change in free energy of binding ({Delta}{Delta}Gbind) resulting from mutations, yet the majority of these methods lack precision. In recent years, protein language models (PLMs) have been developed and shown powerful predictive capabilities by leveraging both sequence and structural data from protein-protein complexes. Yet, PLMs have not been optimized specifically for predicting {Delta}{Delta}Gbind. We developed an approach to predict effects of mutations on PPI binding affinity based on two most advanced protein language models ESM2 and ESM-IF1 that incorporate PPI sequence and structural features, respectively. We used the two models to generate embeddings for each PPI mutant and subsequently fine-tuned our model by training on a large dataset of experimental {Delta}{Delta}Gbind values. Our model, ProBASS (Protein Binding Affinity from Structure and Sequence) achieved a correlation with experimental {Delta}{Delta}Gbind values of 0.83 {+/-} 0.05 for single mutations and 0.69 {+/-} 0.04 for double mutations when model training and testing was done on the same PDB. Moreover, ProBASS exhibited very high correlation (0.81 {+/-} 0.02) between prediction and experiment when training and testing was performed on a dataset containing 2325 single mutations in 132 PPIs. ProBASS surpasses the state-of-the-art methods in correlation with experimental data and could be further trained as more experimental data becomes available. Our results demonstrate that the integration of extensive datasets containing {Delta}{Delta}Gbind values across multiple PPIs to refine the pre-trained PLMs represents a successful approach for achieving a precise and broadly applicable model for {Delta}{Delta}Gbind prediction, greatly facilitating future protein engineering and design studies.

bioinformatics↗

bioRxiv2024

IL-13 and IL-17A Activate β1 Integrin through an NF-κB/Rho kinase/PIP5K1γ pathway to Enhance Force Transmission in Airway Smooth Muscle

Integrin activation resulting in enhanced adhesion to the extracellular matrix plays a key role in fundamental cellular processes. Although G-protein coupled receptor-mediated integrin activation has been extensively studied in non-adherent migratory cells such as leukocytes and platelets, much less is known about the regulation and functional impact of integrin activation in adherent stationary cells such as airway smooth muscle. Here we show that two different asthmagenic cytokines, IL-13 and IL-17A, activate type I and IL-17 cytokine receptor families respectively, to enhance adhesion of muscle to the matrix. These cytokines also induce activation of {beta}1 integrins as detected by the conformation-specific antibody HUTS-4. Moreover, HUTS-4 binding is significantly increased in the smooth muscle of patients with asthma compared to healthy controls, suggesting a disease-relevant role for aberrant integrin activation. Indeed, we find integrin activation induced by a {beta}1 activating antibody, the divalent cation manganese, or the synthetic peptide {beta}1-CHAMP, dramatically enhances force transmission in collagen gels, mouse tracheal rings, and human bronchial rings even in the absence of cytokines. We further demonstrate that cytokine-induced activation of {beta}1 integrins is regulated by a common pathway of NF-O_SCPLOWKC_SCPLOWB-mediated induction of RhoA and its effector Rho kinase, which in turn stimulates PIP5K1{gamma}-mediated synthesis of PIP2 resulting in {beta}1 integrin activation. Taken together, these data identify a previously unknown pathway by which type I and IL-17 cytokine receptor family stimulation induces functionally relevant {beta}1 integrin activation in adherent smooth muscle and help explain the exaggerated force transmission that characterizes chronic airways diseases such as asthma. SIGNIFICANCE STATEMENTIntegrin activation plays a central role in regulating cellular adhesion and migration. While chemokine-mediated integrin activation has been extensively studied in circulating cells, the role and impact of other cytokine families on non-migratory cells remains incompletely characterized. Here, we demonstrate in airway smooth muscle that asthmagenic cytokines IL-13 and IL-17A stimulate type I and IL-17 cytokine receptor families to induce {beta}1 integrin activation and enhance adhesion. We also identify a common pathway linking NF-O_SCPLOWKC_SCPLOWB/RhoA/Rho kinase with PIP5K1{gamma}/PIP2/{beta}1 integrin activation. We show that airway biopsies from asthmatic patients have increased active {beta}1 integrin staining in the muscle, and furthermore that {beta}1 integrin activation alone dramatically enhances force transmission, underscoring the disease-relevant impact of cytokine-mediated integrin activation in adherent muscle.

molecular biology↗

bioRxiv2023

De novo design of drug-binding proteins with predictable binding energy and specificity

The de novo design of small-molecule-binding proteins has seen exciting recent progress; however, the ability to achieve exquisite affinity for binding small molecules while tuning specificity has not yet been demonstrated directly from computation. Here, we develop a computational procedure that results in the highest affinity binders to date with predetermined relative affinities, targeting a series of PARP1 inhibitors. Two of four designed proteins bound with affinities ranging from < 5 nM to low M, in a predictable manner. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free-energy calculations performed directly on the designed models are in excellent agreement with the experimentally measured affinities, suggesting that the de novo design of small-molecule-binding proteins with tuned interaction energies is now feasible entirely from computation. We expect these methods to open many opportunities in biomedicine, including rapid sensor development, antidote design, and drug delivery vehicles. One Sentence SummaryWe use informatic sampling to design low nM drug-binding proteins, and physics-based calculations to accurately predict affinities.

biophysics↗

bioRxiv2023

De novo Design of Peptides that Bind Specific Conformers of α-Synuclein

Insoluble amyloids rich in cross-{beta} fibrils are observed in a number of neurodegenerative diseases. Depending on the clinicopathology, the amyloids can adopt distinct supramolecular assemblies, termed conformational strains. However, rapid methods to study amyloid in a conformationally specific manner are lacking. We introduce a novel computational method for de novo design of peptides that tile the surface of -synuclein fibrils in a conformationally specific manner. Our method begins by identifying surfaces that are unique to the conformational strain of interest, which becomes a "target backbone" for the design of a peptide binder. Next, we interrogate structures in the PDB database with high geometric complementarity to the target. Then, we identify secondary structural motifs that interact with this target backbone in a favorable, highly occurring geometry. This method produces monomeric helical motifs with a favorable geometry for interaction with the strands of the underlying amyloid. Each motif is then symmetrically replicated to form a monolayer that tiles the amyloid surface. Finally, amino acid sequences of the peptide binders are computed to provide a sequence with high geometric and physicochemical complementarity to the target amyloid. This method was applied to a conformational strain of -synuclein fibrils, resulting in a peptide with high specificity for the target relative to other amyloids formed by -synuclein, tau, or A{beta}40. This designed peptide also markedly slowed the formation of -synuclein amyloids. Overall, this method offers a new tool for examining conformational strains of amyloid proteins.

biophysics↗

bioRxiv2023

EMBER multi-dimensional spectral microscopy enables quantitative determination of disease- and cell-specific amyloid strains

In neurodegenerative diseases proteins fold into amyloid structures with distinct conformations (strains) that are characteristic of different diseases. However, there is a need to rapidly identify amyloid conformations in situ. Here we use machine learning on the full information available in fluorescent excitation/emission spectra of amyloid binding dyes to identify six distinct different conformational strains in vitro, as well as A{beta} deposits in different transgenic mouse models. Our EMBER (excitation multiplexed bright emission recording) imaging method rapidly identifies conformational differences in A{beta} and tau deposits from Down syndrome, sporadic and familial Alzheimers disease human brain slices. EMBER has in situ identified distinct conformational strains of tau inclusions in astrocytes, oligodendrocytes, and neurons from Picks disease. In future studies, EMBER should enable high-throughput measurements of the fidelity of strain transmission in cellular and animal neurodegenerative diseases models, time course of amyloid strain propagation, and identification of pathogenic versus benign strains. SignificanceIn neurodegenerative diseases proteins fold into amyloid structures with distinct conformations (strains) that are characteristic of different diseases. There is a need to rapidly identify these amyloid conformations in situ. Here we use machine learning on the full information available in fluorescent excitation/emission spectra of amyloid binding dyes to identify six distinct different conformational strains in vitro, as well as A{beta} deposits in different transgenic mouse models. Our imaging method rapidly identifies conformational differences in A{beta} and tau deposits from Down syndrome, sporadic and familial Alzheimers disease human brain slices. We also identified distinct conformational strains of tau inclusions in astrocytes, oligodendrocytes, and neurons from Picks disease. These findings will facilitate the identification of pathogenic protein aggregates to guide research and treatment of protein misfolding diseases.

neuroscience↗

bioRxiv2022

Transient Water Wires Mediate Selective Proton Conduction in Designed Channel Proteins

Summary paragraphSelective proton transport through proteins is essential for forming and utilizing proton gradients in cells. Protons are conducted along hydrogen-bonded "wires" of water molecules and polar sidechains, which, somewhat surprisingly, are often interrupted by dry apolar stretches in the conduction pathways inferred from static protein structures. We hypothesize that protons are conducted through such dry spots by forming transient water wires, often highly correlated with the presence of the excess proton itself in the water wire. To test this hypothesis, we used molecular dynamics simulations to design transmembrane channels with stable water pockets interspersed by apolar segments capable of forming flickering water wires. The minimalist designed channels conduct protons at rates similar to viral proton channels, and they are at least 106-fold more selective for H+ over Na+. These studies inform mechanisms of biological proton conduction and principles for engineering proton-conductive materials.

biophysics↗

bioRxiv2021

Brilacidin, a COVID-19 Drug Candidate, demonstrates broad-spectrum antiviral activity against human coronaviruses OC43, 229E and NL63 through targeting both the virus and the host cell

Brilacidin, a mimetic of host defense peptides (HDPs), is currently in phase 2 clinical trial as an antibiotic drug candidate. A recent study reported that brilacidin has antiviral activity against SARS-CoV-2 by inactivating the virus. In this work, we discovered an additional mechanism of action of brilacidin by targeting heparan sulfate proteoglycans (HSPGs) on host cell surface. Brilacidin, but not acetyl brilacidin, inhibits the entry of SARS-CoV-2 pseudovirus into multiple cell lines, and heparin, a HSPG mimetic, abolishes the inhibitory activity of brilacidin on SARS-CoV-2 pseudovirus cell entry. In addition, we found that brilacidin has broad-spectrum antiviral activity against multiple human coronaviruses (HCoVs) including HCoV-229E, HCoV-OC43, and HCoV-NL63. Mechanistic studies revealed that brilacidin has a dual antiviral mechanism of action including virucidal activity and binding to coronavirus attachment factor HSPGs on host cell surface. Brilacidin partially loses its antiviral activity when heparin was included in the cell cultures, supporting the host-targeting mechanism. Drug combination therapy showed that brilacidin has a strong synergistic effect with remdesivir against HCoV-OC43 in cell culture. Taken together, this study provides appealing findings for the translational potential of brilacidin as a broad-spectrum antiviral for coronaviruses including SARS-CoV-2.

pharmacology and toxicology↗

bioRxiv2020

Elucidation of the molecular interactions that enable stable assembly and structural diversity in multicomponent immune receptors

Multi-component immune receptors are essential complexes in which distinct ligand-recognition and signaling subunits are held together by interactions between acidic and basic residues of their transmembrane helices. A 2-to-1 acidic to basic motif in the transmembrane domains of the subunits is necessary and sufficient to assemble these receptor complexes. Here, we study a prototype for these receptors, a DAP12-NKG2C 2:1 heterotrimeric complex, in which the two DAP12 subunits each contribute a single transmembrane Asp residue, and the NKG2C subunit contributes a Lys to form the complex. DAP12 can also associate with 20 other subunits using a similar motif. Here we use molecular dynamics simulations to understand the basis for the high affinity and diversity of interactions in this group of receptors. Simulations of the transmembrane helices with differing protonation states of the Asp-Asp-Lys triad identified a structurally stable interaction in which a singly protonated Asp-Asp pair forms a hydrogen-bonded carboxyl-carboxylate clamp that clasps onto a charged Lys sidechain. This polar motif was also supported by density functional theory and a Protein Data Bank-wide search. In contrast, the helices are dynamic at sites distal to the stable carboxyl-carboxylate clamp motif. Such a locally stable but globally dynamic structure is well-suited to accommodate the sequence and structural variations in the transmembrane helices of multi-component receptors, which mix and match subunits to create combinatorial functional diversity from a limited number of subunits. It also supports a signaling mechanism based on multi-subunit clustering rather than propagation of rigid conformational changes through the membrane. SIGNIFICANCEReceptors that separate ligand recognition and intracellular signaling into separate protein subunits are ubiquitous in immunity. These subunits mix and match to create combinatorial functional diversity. The transmembrane domains of these receptors assemble through the interaction between two acidic and one basic residue on different helices. Using computational methods to study the DAP12-NKG2C receptor complex we identified a polar motif in which a singly protonated Asp-Asp pair forms a carboxyl-carboxylate clamp that clasps a charged Lys sidechain in the membrane. This local interaction allows dynamic variations in other regions of the helices that tolerate sequence diversity of the interacting subunits in this class of receptors, which signal through multi-subunit clustering rather than propagation of rigid conformational changes through the membrane.

biophysics↗