-
Nature Reviews. Molecular Cell Biology May 2018RNA-binding proteins (RBPs) are typically thought of as proteins that bind RNA through one or multiple globular RNA-binding domains (RBDs) and change the fate or... (Review)
Review
RNA-binding proteins (RBPs) are typically thought of as proteins that bind RNA through one or multiple globular RNA-binding domains (RBDs) and change the fate or function of the bound RNAs. Several hundred such RBPs have been discovered and investigated over the years. Recent proteome-wide studies have more than doubled the number of proteins implicated in RNA binding and uncovered hundreds of additional RBPs lacking conventional RBDs. In this Review, we discuss these new RBPs and the emerging understanding of their unexpected modes of RNA binding, which can be mediated by intrinsically disordered regions, protein-protein interaction interfaces and enzymatic cores, among others. We also discuss the RNA targets and molecular and cellular functions of the new RBPs, as well as the possibility that some RBPs may be regulated by RNA rather than regulate RNA.
Topics: Animals; Humans; Protein Binding; Proteome; RNA; RNA-Binding Proteins
PubMed: 29339797
DOI: 10.1038/nrm.2017.130 -
Nature Reviews. Drug Discovery Feb 2017Small-molecule drug discovery has traditionally focused on occupancy of a binding site that directly affects protein function, and this approach typically precludes... (Review)
Review
Small-molecule drug discovery has traditionally focused on occupancy of a binding site that directly affects protein function, and this approach typically precludes targeting proteins that lack such amenable sites. Furthermore, high systemic drug exposures may be needed to maintain sufficient target inhibition in vivo, increasing the risk of undesirable off-target effects. Induced protein degradation is an alternative approach that is event-driven: upon drug binding, the target protein is tagged for elimination. Emerging technologies based on proteolysis-targeting chimaeras (PROTACs) that exploit cellular quality control machinery to selectively degrade target proteins are attracting considerable attention in the pharmaceutical industry owing to the advantages they could offer over traditional small-molecule strategies. These advantages include the potential to reduce systemic drug exposure, the ability to counteract increased target protein expression that often accompanies inhibition of protein function and the potential ability to target proteins that are not currently therapeutically tractable, such as transcription factors, scaffolding and regulatory proteins.
Topics: Animals; Drug Discovery; High-Throughput Screening Assays; Humans; Mutant Chimeric Proteins; Protein Binding; Proteins; Proteomics; Small Molecule Libraries
PubMed: 27885283
DOI: 10.1038/nrd.2016.211 -
PLoS Computational Biology Jan 2019The lack of a deep understanding of how proteins interact remains an important roadblock in advancing efforts to identify binding partners and uncover the corresponding...
The lack of a deep understanding of how proteins interact remains an important roadblock in advancing efforts to identify binding partners and uncover the corresponding regulatory mechanisms of the functions they mediate. Understanding protein-protein interactions is also essential for designing specific chemical modifications to develop new reagents and therapeutics. We explored the hypothesis of whether protein interaction sites serve as generic biding sites for non-cognate protein ligands, just as it has been observed for small-molecule-binding sites in the past. Using extensive computational docking experiments on a test set of 241 protein complexes, we found that indeed there is a strong preference for non-cognate ligands to bind to the cognate binding site of a receptor. This observation appears to be robust to variations in docking programs, types of non-cognate protein probes, sizes of binding patches, relative sizes of binding patches and full-length proteins, and the exploration of obligate and non-obligate complexes. The accuracy of the docking scoring function appears to play a role in defining the correct site. The frequency of interaction of unrelated probes recognizing the binding interface was utilized in a simple prediction algorithm that showed accuracy competitive with other state of the art methods.
Topics: Algorithms; Binding Sites; Computational Biology; Databases, Protein; Molecular Docking Simulation; Protein Binding; Protein Conformation; Proteins; ROC Curve
PubMed: 30615604
DOI: 10.1371/journal.pcbi.1006704 -
Accounts of Chemical Research May 2016The dynamics of protein binding pockets are crucial for their interaction specificity. Structural flexibility allows proteins to adapt to their individual molecular... (Review)
Review
The dynamics of protein binding pockets are crucial for their interaction specificity. Structural flexibility allows proteins to adapt to their individual molecular binding partners and facilitates the binding process. This implies the necessity to consider protein internal motion in determining and predicting binding properties and in designing new binders. Although accounting for protein dynamics presents a challenge for computational approaches, it expands the structural and physicochemical space for compound design and thus offers the prospect of improved binding specificity and selectivity. A cavity on the surface or in the interior of a protein that possesses suitable properties for binding a ligand is usually referred to as a binding pocket. The set of amino acid residues around a binding pocket determines its physicochemical characteristics and, together with its shape and location in a protein, defines its functionality. Residues outside the binding site can also have a long-range effect on the properties of the binding pocket. Cavities with similar functionalities are often conserved across protein families. For example, enzyme active sites are usually concave surfaces that present amino acid residues in a suitable configuration for binding low molecular weight compounds. Macromolecular binding pockets, on the other hand, are located on the protein surface and are often shallower. The mobility of proteins allows the opening, closing, and adaptation of binding pockets to regulate binding processes and specific protein functionalities. For example, channels and tunnels can exist permanently or transiently to transport compounds to and from a binding site. The influence of protein flexibility on binding pockets can vary from small changes to an already existent pocket to the formation of a completely new pocket. Here, we review recent developments in computational methods to detect and define binding pockets and to study pocket dynamics. We introduce five different classes of protein pocket dynamics: (1) appearance/disappearance of a subpocket in an existing pocket; (2) appearance/disappearance of an adjacent pocket on the protein surface in the direct vicinity of an already existing pocket; (3) pocket breathing, which may be caused by side-chain fluctuations or backbone or interdomain vibrational motion; (4) opening/closing of a channel or tunnel, connecting a pocket inside the protein with solvent, including lid motion; and (5) the appearance/disappearance of an allosteric pocket at a site on a protein distinct from an already existing pocket with binding of a ligand to the allosteric binding site affecting the original pocket. We suggest that the class of pocket dynamics, as well as the type and extent of protein motion affecting the binding pocket, should be factors considered in choosing the most appropriate computational approach to study a given binding pocket. Furthermore, we examine the relationship between pocket dynamics classes and induced fit, conformational selection, and gating models of ligand binding on binding kinetics and thermodynamics. We discuss the implications of protein binding pocket dynamics for drug design and conclude with potential future directions for computational analysis of protein binding pocket dynamics.
Topics: Algorithms; Binding Sites; Protein Binding; Proteins
PubMed: 27110726
DOI: 10.1021/acs.accounts.5b00516 -
Journal of Alzheimer's Disease : JAD 2019Mounting evidence has identified that impaired amyloid-β (Aβ) clearance might contribute to Alzheimer's disease (AD) pathology. The lysosome-autophagy network plays an... (Review)
Review
Mounting evidence has identified that impaired amyloid-β (Aβ) clearance might contribute to Alzheimer's disease (AD) pathology. The lysosome-autophagy network plays an important role in protein homeostasis and cell health by removing abnormal protein aggregates via intracellular degradation. Therefore, stimulation of cellular degradative machinery for efficient removal of Aβ has emerged as a growing field in AD research. However, mechanisms controlling such pathways and drugs to promote such mechanisms are poorly understood. Aspirin is a widely used drug throughout the world and recent studies have identified a new function of this drug. At low doses, aspirin stimulates lysosomal biogenesis and autophagy to clear amyloid plaques in an animal model of AD. This review delineates such functions of aspirin and analyzes underlying mechanisms that involve peroxisome proliferator-activated receptor alpha (PPARα)-mediated transcription of transcription factor EB (TFEB), the master regulator of lysosomal biogenesis.
Topics: Animals; Anti-Inflammatory Agents, Non-Steroidal; Aspirin; Humans; PPAR alpha; Plaque, Amyloid; Protein Binding; Protein Structure, Secondary
PubMed: 31424405
DOI: 10.3233/JAD-190586 -
Antimicrobial Agents and Chemotherapy Feb 2018This review summarizes evidence that the impact of protein binding of the activity of antibiotics is multifaceted and more complex than indicated by the numerical value... (Review)
Review
This review summarizes evidence that the impact of protein binding of the activity of antibiotics is multifaceted and more complex than indicated by the numerical value of protein binding alone. A plethora of studies has proven that protein binding of antibiotics matters, as the free fraction only is antibacterially active and governs pharmacokinetics. Several studies have indicated that independent from protein binding of immunoglobulin G, albumin, α-acid-glycoprotein, and pulmonary surfactant acted synergistically with antibacterial agents, thus suggesting that some intrinsic properties of serum proteins may have mediated serum-antibiotic synergisms. It has been demonstrated that IgG and albumin permeabilized Gram-negative and Gram-positive bacteria and facilitated the uptake of poorly penetrating antibiotics. Alpha-1-acid-glycoprotein and pulmonary surfactant also exerted a permeabilizing activity, but proof that this property results in a sensitizing effect is missing. The permeabilizing effect of serum proteins may explain why serum-antibiotic synergisms do not represent a general phenomenon but are limited to specific drug-bug associations only. Although evidence has been generated to support the hypothesis that native serum proteins interact synergistically with antibiotics, systematic and well-controlled studies have to be performed to substantiate this phenomenon. The interactions between serum proteins and bacterial surfaces are driven by physicochemical forces. However, preparative techniques, storage conditions, and incubation methods have a significant impact on the intrinsic activities of these serum proteins affecting serum-antibiotic synergisms, so these techniques have to be standardized; otherwise, contradictory data or even artifacts will be generated.
Topics: Animals; Anti-Bacterial Agents; Blood Proteins; Humans; Protein Binding
PubMed: 29158276
DOI: 10.1128/AAC.01663-17 -
Proceedings of the National Academy of... Nov 2020Most proteins have evolved to spontaneously fold into native structure and specifically bind with their partners for the purpose of fulfilling biological functions....
Most proteins have evolved to spontaneously fold into native structure and specifically bind with their partners for the purpose of fulfilling biological functions. According to Darwin, protein sequences evolve through random mutations, and only the fittest survives. The understanding of how the evolutionary selection sculpts the interaction patterns for both biomolecular folding and binding is still challenging. In this study, we incorporated the constraint of functional binding into the selection fitness based on the principle of minimal frustration for the underlying biomolecular interactions. Thermodynamic stability and kinetic accessibility were derived and quantified from a global funneled energy landscape that satisfies the requirements of both the folding into the stable structure and binding with the specific partner. The evolution proceeds via a bowl-like evolution energy landscape in the sequence space with a closed-ring attractor at the bottom. The sequence space is increasingly reduced until this ring attractor is reached. The molecular-interaction patterns responsible for folding and binding are identified from the evolved sequences, respectively. The residual positions participating in the interactions responsible for folding are highly conserved and maintain the hydrophobic core under additional evolutionary constraints of functional binding. The positions responsible for binding constitute a distributed network via coupling conservations that determine the specificity of binding with the partner. This work unifies the principles of protein binding and evolution under minimal frustration and sheds light on the evolutionary design of proteins for functions.
Topics: Amino Acid Sequence; Biophysical Phenomena; Kinetics; Models, Molecular; Physical Phenomena; Protein Binding; Protein Conformation; Protein Folding; Proteins; Thermodynamics
PubMed: 33067388
DOI: 10.1073/pnas.2013822117 -
Bioinformatics (Oxford, England) Dec 2023Identifying the functional sites of a protein, such as the binding sites of proteins, peptides, or other biological components, is crucial for understanding related...
MOTIVATION
Identifying the functional sites of a protein, such as the binding sites of proteins, peptides, or other biological components, is crucial for understanding related biological processes and drug design. However, existing sequence-based methods have limited predictive accuracy, as they only consider sequence-adjacent contextual features and lack structural information.
RESULTS
In this study, DeepProSite is presented as a new framework for identifying protein binding site that utilizes protein structure and sequence information. DeepProSite first generates protein structures from ESMFold and sequence representations from pretrained language models. It then uses Graph Transformer and formulates binding site predictions as graph node classifications. In predicting protein-protein/peptide binding sites, DeepProSite outperforms state-of-the-art sequence- and structure-based methods on most metrics. Moreover, DeepProSite maintains its performance when predicting unbound structures, in contrast to competing structure-based prediction methods. DeepProSite is also extended to the prediction of binding sites for nucleic acids and other ligands, verifying its generalization capability. Finally, an online server for predicting multiple types of residue is established as the implementation of the proposed DeepProSite.
AVAILABILITY AND IMPLEMENTATION
The datasets and source codes can be accessed at https://github.com/WeiLab-Biology/DeepProSite. The proposed DeepProSite can be accessed at https://inner.wei-group.net/DeepProSite/.
Topics: Protein Binding; Proteins; Peptides; Binding Sites; Software
PubMed: 38015872
DOI: 10.1093/bioinformatics/btad718 -
Genomics, Proteomics & Bioinformatics Dec 2021The cellular functions of proteins are maintained by forming diverse complexes. The stability of these complexes is quantified by the measurement of binding affinity,...
The cellular functions of proteins are maintained by forming diverse complexes. The stability of these complexes is quantified by the measurement of binding affinity, and mutations that alter the binding affinity can cause various diseases such as cancer and diabetes. As a result, accurate estimation of the binding stability and the effects of mutations on changes of binding affinity is a crucial step to understanding the biological functions of proteins and their dysfunctional consequences. It has been hypothesized that the stability of a protein complex is dependent not only on the residues at its binding interface by pairwise interactions but also on all other remaining residues that do not appear at the binding interface. Here, we computationally reconstruct the binding affinity by decomposing it into the contributions of interfacial residues and other non-interfacial residues in a protein complex. We further assume that the contributions of both interfacial and non-interfacial residues to the binding affinity depend on their local structural environments such as solvent-accessible surfaces and secondary structural types. The weights of all corresponding parameters are optimized by Monte-Carlo simulations. After cross-validation against a large-scale dataset, we show that the model not only shows a strong correlation between the absolute values of the experimental and calculated binding affinities, but can also be an effective approach to predict the relative changes of binding affinity from mutations. Moreover, we have found that the optimized weights of many parameters can capture the first-principle chemical and physical features of molecular recognition, therefore reversely engineering the energetics of protein complexes. These results suggest that our method can serve as a useful addition to current computational approaches for predicting binding affinity and understanding the molecular mechanism of protein-protein interactions.
Topics: Protein Binding; Proteins
PubMed: 33838354
DOI: 10.1016/j.gpb.2021.03.004 -
Accounts of Chemical Research Jun 2017Protein-protein interactions (PPIs) are ubiquitous in biological systems and often misregulated in disease. As such, specific PPI modulators are desirable to unravel... (Review)
Review
Protein-protein interactions (PPIs) are ubiquitous in biological systems and often misregulated in disease. As such, specific PPI modulators are desirable to unravel complex PPI pathways and expand the number of druggable targets available for therapeutic intervention. However, the large size and relative flatness of PPI interfaces make them challenging molecular targets. This Account describes our systematic approach using secondary and tertiary protein domain mimics (PDMs) to specifically modulate PPIs. Our strategy focuses on mimicry of regular secondary and tertiary structure elements from one of the PPI partners to inspire rational PDM design. We have compiled three databases (HIPPDB, SIPPDB, and DIPPDB) of secondary and tertiary structures at PPI interfaces to guide our designs and better understand the energetics of PPI secondary and tertiary structures. Our efforts have focused on three of the most common secondary and tertiary structures: α-helices, β-strands, and helix dimers (e.g., coiled coils). To mimic α-helices, we designed the hydrogen bond surrogate (HBS) as an isosteric PDM and the oligooxopiperazine helix mimetic (OHM) as a topographical PDM. The nucleus of the HBS approach is a peptide macrocycle in which the N-terminal i, i + 4 main-chain hydrogen bond is replaced with a covalent carbon-carbon bond. In mimicking a main-chain hydrogen bond, the HBS approach stabilizes the α-helical conformation while leaving all helical faces available for functionalization to tune binding affinity and specificity. The OHM approach, in contrast, envisions a tetrapeptide to mimic one face of a two-turn helix. We anticipated that placement of ethylene bridges between adjacent amides constrains the tetrapeptide backbone to mimic the i, i + 4, and i + 7 side chains on one face of an α-helix. For β-strands, we developed triazolamers, a topographical PDM where the peptide bonds are replaced by triazoles. The triazoles simultaneously stabilize the extended, zigzag conformation of β-strands and transform an otherwise ideal protease substrate into a stable molecule by replacement of the peptide bonds. We turned to a salt bridge surrogate (SBS) approach as a means for stabilizing very short helix dimers. As with the HBS approach, the SBS strategy replaces a noncovalent interaction with a covalent bond. Specifically, we used a bis-triazole linkage that mimics a salt bridge interaction to drive helix association and folding. Using this approach, we were able to stabilize helix dimers that are less than half of the length required to form a coiled coil from two independent strands. In addition to demonstrating the stabilization of desired structures, we have also shown that our designed PDMs specifically modulate target PPIs in vitro and in vivo. Examples of PPIs successfully targeted include HIF1α/p300, p53/MDM2, Bcl-xL/Bak, Ras/Sos, and HIV gp41. The PPI databases and designed PDMs created in these studies will aid development of a versatile set of molecules to probe complex PPI functions and, potentially, PPI-based therapeutics.
Topics: Humans; Protein Binding; Protein Domains; Proteins
PubMed: 28561588
DOI: 10.1021/acs.accounts.7b00130