Knob-socket Model Research Articles

Characterizing the consensus residue specificity and surface of BCL-2 binding to BH3 ligands using the Knob-Socket model.

Cancer cells bypass cell death by changing the expression of the BCL-2 family of proteins, which are apoptotic pathway regulators. Upregulation of pro-survival BCL-2 proteins or downregulation of cell death effectors BAX and BAK interferes with the initiation of the intrinsic apoptotic pathway. In normal cells, apoptosis can occur through pro-apoptotic BH3-only proteins interacting and inhibiting pro-survival BCL-2 proteins. When cancer cells over-express pro-survival BCL-2 proteins, a potential remedy is the sequestration of these pro-survival proteins through a class of anti-cancer drugs called BH3 mimetics that bind in the hydrophobic groove of pro-survival BCL-2 proteins. To improve the design of these BH3 mimetics, the packing interface between BH3 domain ligands and pro-survival BCL-2 proteins was analyzed using the Knob-Socket model to identify the amino acid residues responsible for interaction affinity and specificity. A Knob-Socket analysis organizes all the residues in a binding interface into simple 4 residue units: 3-residue sockets defining surfaces on a protein that pack a 4th residue knob from the other protein. In this way, the position and composition of the knobs packing into sockets across the BH3/BCL-2 interface can be classified. A Knob-Socket analysis of 19 BCL-2 protein and BH3 helix co-crystals reveal multiple conserved binding patterns across protein paralogs. Conserved knob residues such as a Gly, Leu, Ala and Glu most likely define binding specificity in the BH3/BCL-2 interface, whereas other residues such as Asp, Asn, and Val are important for forming surface sockets that bind these knobs. These findings can be used to inform the design of BH3 mimetics that are specific to pro-survival BCL-2 proteins for cancer therapeutics.

Designing a PDZ chelator for Alzheimer’s peptides based on the knob-socket model

PDZ domains bind to the C-terminal peptide of other proteins with affinities ranging from mM to high nM. Understanding the basis for peptide specificity to PDZ domains could open possibilities to change the PDZ domain into a chelator of peptides as a potential treatment for Alzheimer’s disease. The knob-socket model was used to identify the amino acid residues critical for the affinity and specificity to PDZ domains. The PDZ domain structure comprises 5 β-strands and 2 α-helices connected by 6 coil/turn segments.

Rational Design of Peptide Ligands Based on Knob–Socket Protein Packing Model Using CD13 as a Prototype Receptor

Structure-based computational peptide design methods have gained significant interest in recent years owing to the availability of structural insights into protein–protein interactions obtained from the crystal structures. The majority of these approaches design new peptide ligands by connecting the crucial amino acid residues from the protein interface and are generally not based on any predicted receptor–ligand interaction. In this work, a peptide design method based on the Knob–Socket model was used to identify the specific ligand residues packed into the receptor interface. This method enables peptide ligands to be designed rationally by predicting amino acid residues that will fit best at the binding site of the receptor protein. In this, specific peptide ligands were designed for the model receptor CD13, overexpression of which has been observed in several cancer types. From the initial library of designed peptides, three potential candidates were selected based on simulated energies in the CD13 bin...

A Rational Approach for Creating Peptides Mimicking Antibody Binding

This study reports a novel method to design peptides that mimic antibody binding. Using the Knob-Socket model for protein-protein interaction, the interaction surface between Cetuximab and EGFR was mapped. EGFR binding peptides were designed based on geometry and the probability of the mapped knob-sockets pairs. Designed peptides were synthesized and then characterized for binding specificity, affinity, cytotoxicity of drug-peptide conjugate and inhibition of phosphorylation. In cell culture studies, designed peptides specifically bind and internalize to EGFR overexpressing cells with three to four-fold higher uptake compared to control cells that do not overexpress EGFR. The designed peptide, Pep11, bound to EGFR with KD of 252 nM. Cytotoxicity of Monomethyl Auristatin E (MMAE)-EGFR-Pep11 peptide-drug conjugate was more than 2,000 fold higher against EGFR overexpressing cell lines A431, MDA MB 468 than control HEK 293 cells which lack EGFR overexpression. MMAE-EGFR-Pep11 conjugate also showed more than 90-fold lower cytotoxicity towards non-EGFR overexpressing HEK 293 cells when compared with cytotoxicity of MMAE itself. In conclusion, a method that can rationally design peptides using knob-socket model is presented. This method was successfully applied to create peptides based on the antigen-antibody interaction to mimic the specificity, affinity and functionality of antibody.

Knob-Socket Predictions of Alpha-Helical Stability

The novel knob-socket (KS) model provides a construct to interpret and analyze the direct contributions of amino acid residues to the stability in α-helical protein structures. Based on residue preferences derived from a set of protein structures, the KS construct characterizes intra- and inter-helical packing into regular patterns of simple motifs. Intra-helical interactions consist of a regular pattern of three residue triangular motifs called sockets, which contribute to helical stability. For inter-helical interactions, a single amino acid knob from one α-helix packs into a three amino acid socket within another α-helix. Therefore, sockets are defined in three categories: (1) free, unpacked and favoring intra-helical interactions, (2) filled, packed and favoring inter-helical interactions, and (3) non, unpacked and disfavoring α-helical structure. The three amino acid socket composition serves as a code that can be used to predict protein packing and by extension, can also be used to understand individual amino acid contributions to helical stability. The KS model was used in the de novo design of an α-helical homodimer, KSα1.1. Using site-directed mutagenesis, KSα1.1 point mutants have been generated to correlate KS propensities with changes in α-helical structure and stability. In the KS α-helical model, each point mutation affects six surrounding sockets by altering the free/filled propensity values. By analyzing the changes in the propensities of these six sockets, KS based stability predictions were made for each mutant. These predicted values are compared to the experimentally determined stability of each peptide from chemical and thermal denaturation studies as measured by circular dichroism spectroscopy. This study serves as a starting point to reveal how residue packing contributes to protein stability.

Novel Method for the Design of a New Alpha-Helical Fold

Our group developed a novel description of packing in protein structure that provides an amino acid code to protein design. To test the knob-socket model's application in protein design, a protein fold with five α-helices arranged in a five-pointed star topology has been designed: the helical star fold. For α-helical protein design, the knob-socket model is described as a four residue tetrahedral motif, where a single amino acid knob from one α-helix packs into a three amino acid socket within another α-helix. The three residue sockets can be classified into three categories: (1) free, unpacked favoring helical structures, (2) filled, packed favoring inter-helical interactions, and (3) disfavoring α-helical structure. Each type of socket has previously been characterized and show preferences for certain amino acid compositions. A practical application of the amino acid preferences for each socket type is a rational method for design of α-helical structure. To start the helical star fold, a 37 residue α-helix was constructed with only free sockets that served as the basis sequence to each leg of the star. Using known crossing angles between helices, specific packing patterns were designed between helices by changing the composition of free sockets into filled sockets and corresponding knobs. In the helical star fold, each α-helical leg crosses once with two other α-helices, meaning each helical leg has two patches of filled sockets. Short connecting loops between helices were designed to promote the packing between non-consecutive helical legs and therefore favor the star packing. The theoretical amino acid sequence was used for gene synthesis and cloning for over-expression in E. coli. The novel star protein was purified and analyzed for α-helical content using circular dichroism. The results provide further support of the knob-socket model and code for protein packing.

KScons: a Bayesian approach for protein residue contact prediction using the knob-socket model of protein tertiary structure.

By simplifying the many-bodied complexity of residue packing into patterns of simple pairwise secondary structure interactions between a single knob residue with a three-residue socket, the knob-socket construct allows a more direct incorporation of structural information into the prediction of residue contacts. By modeling the preferences between the amino acid composition of a socket and knob, we undertake an investigation of the knob-socket construct's ability to improve the prediction of residue contacts. The statistical model considers three priors and two posterior estimations to better understand how the input data affects predictions. This produces six implementations of KScons that are tested on three sets: PSICOV, CASP10 and CASP11. We compare against the current leading contact prediction methods. The results demonstrate the usefulness as well as the limits of knob-socket based structural modeling of protein contacts. The construct is able to extract good predictions from known structural homologs, while its performance degrades when no homologs exist. Among our six implementations, KScons MST-MP (which uses the multiple structure alignment prior and marginal posterior incorporating structural homolog information) performs the best in all three prediction sets. An analysis of recall and precision finds that KScons MST-MP improves accuracy not only by improving identification of true positives, but also by decreasing the number of false positives. Over the CASP10 and CASP11 sets, KScons MST-MP performs better than the leading methods using only evolutionary coupling data, but not quite as well as the supervised learning methods of MetaPSICOV and CoinDCA-NN that incorporate a large set of structural features. qiwei.li@rice.eduSupplementary information: Supplementary data are available at Bioinformatics online.

An Amino Acid Code for the Rational Design and Investigation of Protein Packing Structure using the knob-socket Model

The applications of protein design are limited by the ability to determine a protein's fold and function based solely on a given amino acid sequence. The novel knob-socket model accurately classifies protein tertiary packing structure and provides a code that aims to accurately describe the packing interactions of side-chain residues. It is able to classify protein structure based on distinct amino acid side-chain preferences, which then predict the knob-socket arrangement of the packed protein. From the frequency of appearance in known structures, the knob-socket model provides the basis for prediction of stabilizing and destabilizing mutations. This model was used to design a 27 amino acid sequence, KSalpha1.1, which has been shown to fold into a stable alpha-helix configuration and that oligomerizes. The effects of helix stability are characterized with CD spectroscopy and oligomerization with NMR. Using known correlations of amino acid composition to alpha-helix propensity from the knob-socket model specific amino acids in the KSalpha1.1 sequence are changed to predictively strengthened or weakened packing stability. Current work involves purification and characterization of these mutations in the KSalpha1.1 protein to demonstrate the accuracy of the knob-socket model for protein design. The results provide further proof of knob-socket's ability to correctly model the packing in protein structure and serve as a fundamental descriptor of higher order protein structure.

Protein Packing Code for DNA Recognition Based on the Knob-Socket Model

Understanding protein-nucleic acid packing interactions is a fundamental step in deciphering how proteins specifically recognize and bind DNA. A knob-socket analysis of protein-DNA interfaces simply and clearly identifies the packing contributions to binding specificity. All of the approximately 3,500 protein-DNA complexes in the NDB database were evaluated using the knob-socket approach, where this study focuses on α-helix binding to DNA. Amino acid and DNA base composition in sockets and knobs is presented as well as a protein-DNA packing surface topology map. Generally, DNA packing naturally divides into specific interactions with the nucleic acid bases and non-specific interactions with the phosphate backbone groups. The ∼280,000 four-body packing cliques were found to be the dominant packing interaction similar to protein-protein packing interfaces. Among these four-body cliques, about 9% are DNA sockets formed by 2 adjacent bases packing with a knob from a protein and about 27% are protein sockets packing against a DNA base acting as a knob. A general pattern can be characterized for α-helix binding to DNA. The α-helical knobs are aligned along the i±4 ridge and pack into very regular diamond pockets (multiple sockets) on the DNA double helix. This i±4 ridge of knobs divides the binding of the α-helix into 2 regions of sockets that recognize blocks of DNA bases: one on the coding strand and the other on the non-coding strand. Therefore, an α-helix splits DNA sequence recognition to a part on the coding and the other part on the non-coding strands. The pocket pattern and amino acid composition on α-helices provide specificity for DNA base recognition. The results demonstrate that the knob-socket model can rationally investigate and produce clear insight into protein-DNA binding interfaces.

The knob-Socket Model: An Amino Acid Code Describing Protein Tertiary Packing Structure

A construct that simplifies the complexity of residue packing would significantly impact our understanding and analysis higher order protein structure in the same way that the covalent peptide bond allows linear comparisons of protein sequences and main-chain hydrogen bonding patterns identify secondary structure. For every secondary structure type including the irregular coil elements, the knob-socket model decomposes the many-bodied and non-specific side-chain interactions into regular patterns of a 3-residue socket. The 3-residue socket describes packing interactions within secondary structure elements and exists in 2 states: free and filled with a knob. The 4-residue filled socket or knob-socket indicates tertiary structure packing between secondary structure elements. Amino acid composition analysis of the 2 sockets across secondary structure classes shows strong preferences for either a free state or packed with a knob. Therefore, the relative arrangement of these socket types in the secondary structure different elements defines the packing architecture of a protein and provides a correlation of a protein's primary sequence directly with its tertiary structure. This analysis characterizes packing structure even in irregular coil structure and that coil residues contribute as much to tertiary structure packing as alpha-helices. Moreover, the knob-socket construct decomposes the complicated 3D interactions of protein tertiary structure into an easily understood 2D representation called a packing surface topology map. This approach unambiguously illustrates the canonical packing patterns between alpha-helices and reveals the canonical packing patterns between beta-sheets as well as between alpha-helices and beta-sheets. Furthermore, knobs are found to consistently pack into individual sockets and only a few shapes of contiguous sockets (or pockets). These analyses and results demonstrate that the knob-socket model functions as a fundamental unit to describe packing in higher order protein structure.

An Amino Acid Code to Protein Quaternary Structure

Cellular functions are mediated by protein-protein interactions. How proteins bind interaction partners is largely an open problem. The state of our understanding in protein-protein interactions could benefit greatly from a simple model to probe the complexities of the subject. The knob-socket model has been shown to be an important motif for protein tertiary structure packing. The knob-socket is a four residue tetrahedral motif calculated using Voronoi Polyhedra, where the knob from one secondary structure element packs into a socket formed by three residues from another secondary structure element. It has been shown that the knob-socket model naturally leads to an amino acid code for protein structure. The work presented extends the knob-socket analysis of protein tertiary structure to quaternary structure packing. Using the 3D Complex database of protein-protein interactions, the amino acid composition of knob-sockets at the interface between proteins is described. The extent to which protein tertiary and quaternary structure are similar is described in terms of the knob-socket construct. Furthermore, this work illustrates how knob-socket data can design helices that homodimerize in solution. In conclusion, knob-socket approaches to protein-protein interactions provide a clear and concise classification of protein-protein interactions into three separate classes. Class 1 is defined through peptide-protein interactions. Here, the peptide provides knobs that pack into the already established free sockets of the protein interaction surface. Class 2 is characterized by knobs-sockets shared between the two protein interaction partners. Class 3 is characterized by structure formation upon interaction. Class 3 exhibits induction of protein structure with knob-socket packing from both chains. This can occur for both protein-protein interactions as well as peptide-protein interactions. This knob-socket analysis provides unique insights into the complexity of protein-protein interactions.

An amino acid code to define a protein's tertiary packing surface.

One difficult aspect of the protein-folding problem is characterizing the nonspecific interactions that define packing in protein tertiary structure. To better understand tertiary structure, this work extends the knob-socket model by classifying the interactions of a single knob residue packed into a set of contiguous sockets, or a pocket made up of 4 or more residues. The knob-socket construct allows for a symbolic two-dimensional mapping of pockets. The two-dimensional mapping of pockets provides a simple method to investigate the variety of pocket shapes to understand the geometry of protein tertiary surfaces. The diversity of pocket geometries can be organized into groups of pockets that share a common core, which suggests that some interactions in pockets are ancillary to packing. Further analysis of pocket geometries displays a preferred configuration that is right-handed in α-helices and left-handed in β-sheets. The amino acid composition of pockets illustrates the importance of nonpolar amino acids in packing as well as position specificity. As expected, all pocket shapes prefer to pack with hydrophobic knobs; however, knobs are not selective for the pockets they pack. Investigating side-chain rotamer preferences for certain pocket shapes uncovers no strong correlations. These findings allow a simple vocabulary based on knobs and sockets to describe protein tertiary packing that supports improved analysis, design, and prediction of protein structure.

An amino acid code for irregular and mixed protein packing.

To advance our understanding of protein tertiary structure, the development of the knob-socket model is completed in an analysis of the packing in irregular coil and turn secondary structure packing as well as between mixed secondary structure. The knob-socket model simplifies packing based on repeated patterns of two motifs: a three-residue socket for packing within secondary (2°) structure and a four-residue knob-socket for tertiary (3°) packing. For coil and turn secondary structure, knob-sockets allow identification of a correlation between amino acid composition and tertiary arrangements in space. Coil contributes almost as much as α-helices to tertiary packing. In irregular sockets, Gly, Pro, Asp, and Ser are favored, while in irregular knobs, the preference order is Arg, Asp, Pro, Asn, Thr, Leu, and Gly. Cys, His,Met, and Trp are not favored in either. In mixed packing, the knob amino acid preferences are a function of the socket that they are packing into, whereas the amino acid composition of the sockets does not depend on the secondary structure of the knob. A unique motif of a coil knob with an XYZ β-sheet socket may potentially function to inhibit β-sheet extension. In addition, analysis of the preferred crossing angles for strands within a β-sheet and mixed α-helice/β-sheet identifies canonical packing patterns useful in protein design. Lastly, the knob-socket model abstracts the complexity of protein tertiary structure into an intuitive packing surface topology map.

Bayesian model of protein primary sequence for secondary structure prediction.

Determining the primary structure (i.e., amino acid sequence) of a protein has become cheaper, faster, and more accurate. Higher order protein structure provides insight into a protein’s function in the cell. Understanding a protein’s secondary structure is a first step towards this goal. Therefore, a number of computational prediction methods have been developed to predict secondary structure from just the primary amino acid sequence. The most successful methods use machine learning approaches that are quite accurate, but do not directly incorporate structural information. As a step towards improving secondary structure reduction given the primary structure, we propose a Bayesian model based on the knob-socket model of protein packing in secondary structure. The method considers the packing influence of residues on the secondary structure determination, including those packed close in space but distant in sequence. By performing an assessment of our method on 2 test sets we show how incorporation of multiple sequence alignment data, similarly to PSIPRED, provides balance and improves the accuracy of the predictions. Software implementing the methods is provided as a web application and a stand-alone implementation.

An amino acid code for β-sheet packing structure

To understand the relationship between protein sequence and structure, this work extends the knob-socket model in an investigation of β-sheet packing. Over a comprehensive set of β-sheet folds, the contacts between residues were used to identify packing cliques: sets of residues that all contact each other. These packing cliques were then classified based on size and contact order. From this analysis, the two types of four-residue packing cliques necessary to describe β-sheet packing were characterized. Both occur between two adjacent hydrogen bonded β-strands. First, defining the secondary structure packing within β-sheets, the combined socket or XY:HG pocket consists of four residues i, i+2 on one strand and j, j+2 on the other. Second, characterizing the tertiary packing between β-sheets, the knob-socket XY:H+B consists of a three-residue XY:H socket (i, i+2 on one strand and j on the other) packed against a knob B residue (residue k distant in sequence). Depending on the packing depth of the knob B residue, two types of knob-sockets are found: side-chain and main-chain sockets. The amino acid composition of the pockets and knob-sockets reveal the sequence specificity of β-sheet packing. For β-sheet formation, the XY:HG pocket clearly shows sequence specificity of amino acids. For tertiary packing, the XY:H+B side-chain and main-chain sockets exhibit distinct amino acid preferences at each position. These relationships define an amino acid code for β-sheet structure and provide an intuitive topological mapping of β-sheet packing.

An Amino Acid Packing Code for α-Helical Structure and Protein Design

This work demonstrates that all packing in α-helices can be simplified to repetitive patterns of a single motif: the knob–socket. Using the precision of Voronoi Polyhedra/Delauney Tessellations to identify contacts, the knob–socket is a four-residue tetrahedral motif: a knob residue on one α-helix packs into the three-residue socket on another α-helix. The principle of the knob–socket model relates the packing between levels of protein structure: the intra-helical packing arrangements within secondary structure that permit inter-helix tertiary packing interactions. Within an α-helix, the three-residue sockets arrange residues into a uniform packing lattice. Inter-helix packing results from a definable pattern of interdigitated knob–socket motifs between two α-helices. Furthermore, the knob–socket model classifies three types of sockets: (1) free, favoring only intra-helical packing; (2) filled, favoring inter-helical interactions; and (3) non, disfavoring α-helical structure. The amino acid propensities in these three socket classes essentially represent an amino acid code for structure in α-helical packing. Using this code, we used a novel yet straightforward approach for the design of α-helical structure to validate the knob–socket model. Unique sequences for three peptides were created to produce a predicted amount of α-helical structure: mostly helical, some helical, and no helix. These three peptides were synthesized, and helical content was assessed using CD spectroscopy. The measured α-helicity of each peptide was consistent with the expected predictions. These results and analysis demonstrate that the knob–socket motif functions as the basic unit of packing and presents an intuitive tool to decipher the rules governing packing in protein structure.