Hydrophobic patches on the surfaces of protein structures

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity, and Antibody Developability

The electrostatic properties of proteins arise from the number and distribution of polar and charged residues. Electrostatic interactions in proteins play a critical role in numerous processes such as molecular recognition, protein solubility, viscosity, and antibody developability. Thus, characterizing and quantifying electrostatic properties of a protein are prerequisites for understanding these processes. Here, we present PEP-Patch, a tool to visualize and quantify the electrostatic potential on the protein surface in terms of surface patches, denoting separated areas of the surface with a common physical property. We highlight its applicability to elucidate protease substrate specificity and antibody-antigen recognition and predict heparin column retention times of antibodies as an indicator of pharmacokinetics.

DeepBSRPred: deep learning-based binding site residue prediction for proteins

MOTIVATION

Proteins-protein interactions (PPIs) are important to govern several cellular activities. Amino acid residues, which are located at the interface are known as the binding sites and the information about binding sites helps to understand the binding affinities and functions of protein-protein complexes.

RESULTS

We have developed a deep neural network-based method, DeepBSRPred, for predicting the binding sites using protein sequence information and predicted structures from AlphaFold2. Specific sequence and structure-based features include position-specific scoring matrix (PSSM), solvent accessible surface area, conservation score and amino acid properties, and residue depth, respectively. Our method predicted the binding sites with an average F1 score of 0.73 in a dataset of 1236 proteins. Further, we compared the performance with other existing methods in the literature using four benchmark datasets and our method outperformed those methods.

AVAILABILITY AND IMPLEMENTATION

The DeepBSRPred web server can be found at https://web.iitm.ac.in/bioinfo2/deepbsrpred/index.html , along with all datasets used in this study. The trained models, the DeepBSRPred standalone source code, and the feature computation pipeline are freely available at https://web.iitm.ac.in/bioinfo2/deepbsrpred/download.html .

An in-silico study to understand the effect of lineage diversity on cold shock response: unveiling protein-RNA interactions among paralogous CSPs of E. coli

Cold shock proteins (CSPs) are small, cytoplasmic, ubiquitous and acidic proteins. They have a single nucleic acid-binding domain and pose as "RNA chaperones" by binding to ssRNA in a low sequence specificity and cooperative manner. They are found in a family of nine homologous CSPs in E. coli. CspA, CspB, CspG and CspI are immensely cold inducible, CspE and CspC are consistently released at usual physiological temperatures and CspD is also induced under nutrient stress. The paralogous protein pairs CSPA/CSPB, CSPC/CSPE, CSPG/CSPI and CSPF/CSPH were first identified. The eight proteins were subjected to molecular modelling and simulation to obtain the most stable conformation in correspondence to their equilibrated RMSD and RMSF graph. The results were compared and it was observed that CSPB, CSPE, CSPF and CSPI were more stable than their paralogous partner conforming to their near equilibrated RMSD curve and low fluctuating RMSF graph. The paralogous proteins were docked with ssRNA and simultaneously binding affinity, interaction types, electrostatic surface potential, hydrophobicity, conformational analysis and SASA were calculated to minutely study and understand the molecular mechanism initiated by these proteins. It was found that CSPB, CSPC, CSPH and CSPI displayed higher affinity towards ssRNA than their paralogous partner. The results further corroborated with ΔGmmgbsa and ΔGfold energy. Between the paralogous pairs CSPC, CSPH and CSPI exhibited higher binding free energy than their partner. Further, CSPB, CSPC and CSPI exhibited higher folding free energy than their paralogous pair. CSPH exhibited highest ΔGmmgbsa of - 522.2 kcal/mol and lowest was displayed by CSPG of around - 309.3 kcal/mol. Highest number of mutations were recognised in CSPF/CSPH and CSPG/CSPI pair. Difference in interaction pattern was maximum in CSPF/CSPH owing to their high number of non-synonymous substitutions. Maximum difference in surface electrostatic potential was observed in case of CSPA, CSPG and CSPF. This research work emphasizes on discerning the molecular mechanism initiated by these proteins with a structural, mutational and functional approach.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03656-2.

Origins of life: first came evolutionary dynamics

When life arose from prebiotic molecules 3.5 billion years ago, what came first? Informational molecules (RNA, DNA), functional ones (proteins), or something else? We argue here for a different logic: rather than seeking a molecule type, we seek a dynamical process. Biology required an ability to evolve before it could choose and optimise materials. We hypothesise that the evolution process was rooted in the peptide folding process. Modelling shows how short random peptides can collapse in water and catalyse the elongation of others, powering both increased folding stability and emergent autocatalysis through a disorder-to-order process.

Comparison of hydrophobicity scales for predicting biophysical properties of antibodies

While antibody-based therapeutics have grown to be one of the major classes of novel medicines, some antibody development candidates face significant challenges regarding expression levels, solubility, as well as stability and aggregation, under physiological and storage conditions. A major determinant of those properties is surface hydrophobicity, which promotes unspecific interactions and has repeatedly proven problematic in the development of novel antibody-based drugs. Multiple computational methods have been devised for in-silico prediction of antibody hydrophobicity, often using hydrophobicity scales to assign values to each amino acid. Those approaches are usually validated by their ability to rank potential therapeutic antibodies in terms of their experimental hydrophobicity. However, there is significant diversity both in the hydrophobicity scales and in the experimental methods, and consequently in the performance of in-silico methods to predict experimental results. In this work, we investigate hydrophobicity of monoclonal antibodies using hydrophobicity scales. We implement several scoring schemes based on the solvent-accessibility and the assigned hydrophobicity values, and compare the different scores and scales based on their ability to predict retention times from hydrophobic interaction chromatography. We provide an overview of the strengths and weaknesses of several commonly employed hydrophobicity scales, thereby improving the understanding of hydrophobicity in antibody development. Furthermore, we test several datasets, both publicly available and proprietary, and find that the diversity of the dataset affects the performance of hydrophobicity scores. We expect that this work will provide valuable guidelines for the optimization of biophysical properties in future drug discovery campaigns.

Boosting the analysis of protein interfaces with multiple interface string alignments: Illustration on the spikes of coronaviruses

We introduce multiple interface string alignment (MISA), a visualization tool to display coherently various sequence and structure based statistics at protein-protein interfaces (SSE elements, buried surface area, Δ ASA , B factor values, etc). The amino acids supporting these annotations are obtained from Voronoi interface models. The benefit of MISA is to collate annotated sequences of (homologous) chains found in different biological contexts, that is, bound with different partners or unbound. The aggregated views MISA/SSE, MISA/BSA, MISA/ΔASA, and so forth, make it trivial to identify commonalities and differences between chains, to infer key interface residues, and to understand where conformational changes occur upon binding. As such, they should prove of key relevance for knowledge-based annotations of protein databases such as the Protein Data Bank. Illustrations are provided on the receptor binding domain of coronaviruses, in complex with their cognate partner or (neutralizing) antibodies. MISA computed with a minimal number of structures complement and enrich findings previously reported. The corresponding package is available from the Structural Bioinformatics Library (http://sbl.inria.frand https://sbl.inria.fr/doc/Multiple_interface_string_alignment-user-manual.html).

PEGylation near a Patch of Nonpolar Surface Residues Increases the Conformational Stability of the WW Domain

Many proteins have one or more surface-exposed patches of nonpolar residues; our observations here suggest that PEGylation near such locations might be a useful strategy for increasing protein conformational stability. Specifically, we show that conjugating a PEG-azide to a propargyloxyphenylalanine via the copper(I)-catalyzed azide-alkyne cycloaddition can increase the conformational stability of the WW domain due to a favorable synergistic effect that depends on the hydrophobicity of a nearby patch of nonpolar surface residues.

From Protein Features to Sensing Surfaces

Proteins play a major role in biosensors in which they provide catalytic activity and specificity in molecular recognition. However, the immobilization process is far from straightforward as it often affects the protein functionality. Extensive interaction of the protein with the surface or significant surface crowding can lead to changes in the mobility and conformation of the protein structure. This review will provide insights as to how an analysis of the physico-chemical features of the protein surface before the immobilization process can help to identify the optimal immobilization approach. Such an analysis can help to preserve the functionality of the protein when on a biosensor surface.

Foldamer hypothesis for the growth and sequence differentiation of prebiotic polymers

It is not known how life originated. It is thought that prebiotic processes were able to synthesize short random polymers. However, then, how do short-chain molecules spontaneously grow longer? Also, how would random chains grow more informational and become autocatalytic (i.e., increasing their own concentrations)? We study the folding and binding of random sequences of hydrophobic ([Formula: see text]) and polar ([Formula: see text]) monomers in a computational model. We find that even short hydrophobic polar (HP) chains can collapse into relatively compact structures, exposing hydrophobic surfaces. In this way, they act as primitive versions of today's protein catalysts, elongating other such HP polymers as ribosomes would now do. Such foldamer catalysts are shown to form an autocatalytic set, through which short chains grow into longer chains that have particular sequences. An attractive feature of this model is that it does not overconverge to a single solution; it gives ensembles that could further evolve under selection. This mechanism describes how specific sequences and conformations could contribute to the chemistry-to-biology (CTB) transition.

Inferring the microscopic surface energy of protein-protein interfaces from mutation data

Mutations at protein-protein recognition sites alter binding strength by altering the chemical nature of the interacting surfaces. We present a simple surface energy model, parameterized with empirical ΔΔG values, yielding mean energies of -48 cal mol(-1) Å(-2) for interactions between hydrophobic surfaces, -51 to -80 cal mol(-1) Å(-2) for surfaces of complementary charge, and 66-83 cal mol(-1) Å(-2) for electrostatically repelling surfaces, relative to the aqueous phase. This places the mean energy of hydrophobic surface burial at -24 cal mol(-1) Å(-2) . Despite neglecting configurational entropy and intramolecular changes, the model correlates with empirical binding free energies of a functionally diverse set of rigid-body interactions (r = 0.66). When used to rerank docking poses, it can place near-native solutions in the top 10 for 37% of the complexes evaluated, and 82% in the top 100. The method shows that hydrophobic burial is the driving force for protein association, accounting for 50-95% of the cohesive energy. The model is available open-source from http://life.bsc.es/pid/web/surface_energy/ and via the CCharpPPI web server http://life.bsc.es/pid/ccharppi/.

Predicting enzyme adsorption to lignin films by calculating enzyme surface hydrophobicity

The inhibitory action of lignin on cellulase cocktails is a major challenge to the biological saccharification of plant cell wall polysaccharides. Although the mechanism remains unclear, hydrophobic interactions between enzymes and lignin are hypothesized to drive adsorption. Here we evaluate the role of hydrophobic interactions in enzyme-lignin binding. The hydrophobicity of the enzyme surface was quantified using an estimation of the clustering of nonpolar atoms, identifying potential interaction sites. The adsorption of enzymes to lignin surfaces, measured using the quartz crystal microbalance, correlates to the hydrophobic cluster scores. Further, these results suggest a minimum hydrophobic cluster size for a protein to preferentially adsorb to lignin. The impact of electrostatic contribution was ruled out by comparing the isoelectric point (pI) values to the adsorption of proteins to lignin surfaces. These results demonstrate the ability to predict enzyme-lignin adsorption and could potentially be used to design improved cellulase cocktails, thus lowering the overall cost of biofuel production.

HomPPI: a class of sequence homology based protein-protein interface prediction methods

BACKGROUND

Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate.

RESULTS

We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence.Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein.Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/.

CONCLUSIONS

Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners.

The theoretical three-dimensional structure of Bacillus thuringiensis Cry5Aa and its biological implications

Cry5Aa is a crystal protein produced by Bacillus thuringiensis serovar. damstadiensis during its stationary phase, this delta-endotoxin is active against nematodes and has great potential for nematodes control. The theoretical model of the three-dimensional structure of Cry5Aa was predicted by homology modeling on the structures of the Cry1Aa which is specific to Lepidopteran insects. The structure of the Cry5Aa resembles previously reported Cry toxin structures but shows the following distinctions. Cry5Aa has a long insertion in alpha2 of domain I. Some loops in the domain II and III of Cry5Aa are exposed to the solvent. In this work we give a brief description of our model and hypothesize the residues of the Cry5Aa that could be important in receptor recognition and pore formation. This model will be helpful for the design of mutagenesis experiments aimed to the improvement of toxicity, and lead to a deep understanding of the mechanism of action of nematicidal toxins.

A survey of available tools and web servers for analysis of protein-protein interactions and interfaces

The unanimous agreement that cellular processes are (largely) governed by interactions between proteins has led to enormous community efforts culminating in overwhelming information relating to these proteins; to the regulation of their interactions, to the way in which they interact and to the function which is determined by these interactions. These data have been organized in databases and servers. However, to make these really useful, it is essential not only to be aware of these, but in particular to have a working knowledge of which tools to use for a given problem; what are the tool advantages and drawbacks; and no less important how to combine these for a particular goal since usually it is not one tool, but some combination of tool-modules that is needed. This is the goal of this review.

Conformation and dynamics of a rhodamine probe attached at two sites on a protein: implications for molecular structure determination in situ

Replica exchange molecular dynamics (REMD) calculations were used to determine the conformation and dynamics of bifunctional rhodamine probes attached to pairs of cysteines in three model systems: (a) a polyalanine helix, (b) the isolated C helix (residues 53-66) of troponin C, and (c) the C helix of the N-terminal region (residues 1-90) of troponin C (sNTnC). In each case, and for both diastereoisomers of each probe-protein complex, the hydrophobic face of the probe is close to the protein surface, and its carboxylate group is highly solvated. The visible-range fluorescence dipole of the probe is approximately parallel to the line joining the two cysteine residues, as assumed in previous in situ fluorescence polarization studies. The independent rotational motion of the probe with respect to the protein on the nanosecond time scale is highly restricted, in agreement with data from fluorescence polarization and NMR relaxation studies. The detailed interaction of the probe with the protein surface depends on steric factors, electrostatic and hydrophobic interactions, hydrogen bonds, and hydration effects. The interaction is markedly different between diastereoisomers, and multiple preferred conformations exist for a single diasteroisomer. These results show that the combination of the hydrophobic xanthylium moiety of bifunctional rhodamine with the carboxylate substitution in its pendant phenyl ring causes the probe to be immobilized on the protein surface, while the two-site cysteine attachment defines the orientation of its fluorescence dipole. These features allow the orientation of protein components to be accurately determined in situ by polarized fluorescence measurements from bifunctional rhodamine probes.

The theoretical 3D structure of Bacillus thuringiensis Cry5Ba

Cry5Ba is a delta-endotoxin produced by Bacillus thuringiensis PS86A1 NRRL B-18900. It is active against nematodes and has great potential for nematode control. Here, we predict the first theoretical model of the three-dimensional (3D) structure of a Cry5Ba toxin by homology modeling on the structure of the Cry1Aa toxin, which is specific to Lepidopteran insects. Cry5Ba resembles the previously reported Cry1Aa toxin structure in that they share a common 3D structure with three domains, but there are some distinctions, with the main differences being located in the loops of domain I. Cry5Ba exhibits a changeable extending conformation structure, and this special structure may also be involved in pore-forming and specificity determination. A fuller understanding of the 3D structure will be helpful in the design of mutagenesis experiments aimed at improving toxicity, and lead to a deep understanding of the mechanism of action of nematicidal toxins.

An algorithm for predicting protein-protein interaction sites: Abnormally exposed amino acid residues and secondary structure elements

Multiprotein systems mediate most regulatory processes in living organisms. Although the structures of the individual proteins are often defined, less is known of the structures of multiprotein systems. Computational methods for predicting interfaces, using evolutionary conservation and/or physicochemical data, have been developed. Here we consider the use of solvent accessibility, residue propensity, and hydrophobicity, in conjunction with secondary structure data, as prediction parameters. We analyze the influence of residue type and secondary structure on solvent accessibility and define a measure of "relative exposedness." Clustering abnormally high scoring residues provides a basis for predicting interaction sites. The analysis is extended to investigate abnormally exposed secondary structure elements, particularly beta-sheet strands. We show that surface-exposed beta-strands lacking protective features are more likely to be found at protein-protein interfaces, allowing us to create an algorithm with approximately 68% and approximately 75% accuracy in differentiating between interacting and edge strands in isolated beta-strands and beta-sheet strands, respectively. These methods of identifying abnormally exposed surface regions are combined in an algorithm, which, on a data set of 77 unbound and disjoint (single chain extracted from complex) structures, predicts 79% of the protein-protein interfaces correctly. If enzyme-inhibitor complexes, where the inhibitor mimics a nonprotein substrate, are excluded, the accuracy increases to 85%.

Structure of the functional form of the mosquito larvicidal Cry4Aa toxin from Bacillus thuringiensis at a 2.8-angstrom resolution

The Cry4Aa delta-endotoxin from Bacillus thuringiensis is toxic to larvae of Culex, Anopheles, and Aedes mosquitoes, which are vectors of important human tropical diseases. With the objective of designing modified toxins with improved potency that could be used as biopesticides, we determined the structure of this toxin in its functional form at a resolution of 2.8 angstroms. Like other Cry delta-endotoxins, the activated Cry4Aa toxin consists of three globular domains, a seven-alpha-helix bundle responsible for pore formation (domain I) and the following two other domains having structural similarities with carbohydrate binding proteins: a beta-prism (domain II) and a plant lectin-like beta-sandwich (domain III). We also studied the effect on toxicity of amino acid substitutions and deletions in three loops located at the surface of the putative receptor binding domain II of Cry4Aa. Our results indicate that one loop is an important determinant of toxicity, presumably through attachment of Cry4Aa to the surface of mosquito cells. The availability of the Cry4Aa structure should guide further investigations aimed at the molecular basis of the target specificity and membrane insertion of Cry endotoxins.

Morphological aspects of oligomeric protein structures

Features of multimeric proteins are reviewed to shed light on the formation of protein assemblies from a structural perspective. The features comprise biochemical and geometric properties. They are compiled on new low-redundancy sets of crystal structures of homomeric proteins with different symmetry and subunit multiplicity, as well as on a set of heteromeric proteins. Crystal structures of likely monomers provide a control group.

Are protein-protein interfaces more conserved in sequence than the rest of the protein surface?

Protein interfaces are thought to be distinguishable from the rest of the protein surface by their greater degree of residue conservation. We test the validity of this approach on an expanded set of 64 protein-protein interfaces using conservation scores derived from two multiple sequence alignment types, one of close homologs/orthologs and one of diverse homologs/paralogs. Overall, we find that the interface is slightly more conserved than the rest of the protein surface when using either alignment type, with alignments of diverse homologs showing marginally better discrimination. However, using a novel surface-patch definition, we find that the interface is rarely significantly more conserved than other surface patches when using either alignment type. When an interface is among the most conserved surface patches, it tends to be part of an enzyme active site. The most conserved surface patch overlaps with 39% (+/- 28%) and 36% (+/- 28%) of the actual interface for diverse and close homologs, respectively. Contrary to results obtained from smaller data sets, this work indicates that residue conservation is rarely sufficient for complete and accurate prediction of protein interfaces. Finally, we find that obligate interfaces differ from transient interfaces in that the former have significantly fewer alignment gaps at the interface than the rest of the protein surface, as well as having buried interface residues that are more conserved than partially buried interface residues.

Localization of a hydrophobic binding site for anticoagulant protein S on the beta -chain of complement regulator C4b-binding protein

C4b-binding protein (C4BP) is a plasma glycoprotein involved in regulation of the complement system. C4BP consists of seven alpha-chains and one unique beta-chain, all constructed of repeating complement control protein (CCP) modules. The beta-chain, made up of three CCPs, binds tightly to vitamin K-dependent protein S, a cofactor to anticoagulant activated protein C. When bound to C4BP, protein S loses its activated protein C cofactor function. In this study, we have mutated potentially important amino acids located at the surface of CCP1 of the beta-chain to probe the protein S-C4BP interaction. The substitutions were designed after analysis of a homology-based three-dimensional structure of the beta-chain and were L27T/F45Q, I16S/V18S, V31T/I33N, I16S/V18S/V31T/I33N, L38S/V39S, and K41E/K42E. The mutants were expressed in a prokaryotic system, purified using an N-terminal His-tag, refolded using an oxido-shuffling system, and tested in several assays for their ability to bind protein S. Our data define Ile(16), Val(18), Val(31), and Ile(33) as crucial for protein S binding, with secondary effects from Leu(38) and Val(39). In addition, Lys(41) and Lys(42) contribute slightly to the interaction. Our results further confirm that surface hydrophobicity analysis may be used to identify ligand recognition sites.

Hydrophobic hydration of amphipathic peptides

Biomolecular surfaces and interfaces are commonly found with apolar character. The hydrophobic effect thus plays a crucial role in processes involving association with biomolecular surfaces in the cellular environment. By computer simulation, we compared the hydrogen bonding structures and energetics of the proximal hydration shells of the monomer and dimer from a recent study of an extrinsic membrane peptide, melittin. The two peptides were studied in their amphipathic alpha-helical forms, which possess extended hydrophobic surfaces characterized by different topography. The topography of the peptide-water interface was found to be critical in determining the enthalpic nature of hydrophobic hydration. This topographical dependence has far-reaching implications in the regulation of bioactivities in the presence of amphipathicity. This result also engenders reconsideration of the validity of using free energy parameters that depend solely on the chemical nature of constituent moieties in characterizing hydrophobic hydration of proteins and biomolecules in general.

Stability and folding properties of a model beta-sheet protein, Escherichia coli CspA

Although beta-sheets represent a sizable fraction of the secondary structure found in proteins, the forces guiding the formation of beta-sheets are still not well understood. Here we examine the folding of a small, all beta-sheet protein, the E. coli major cold shock protein CspA, using both equilibrium and kinetic methods. The equilibrium denaturation of CspA is reversible and displays a single transition between folded and unfolded states. The kinetic traces of the unfolding and refolding of CspA studied by stopped-flow fluorescence spectroscopy are monoexponential and thus also consistent with a two-state model. In the absence of denaturant, CspA refolds very fast with a time constant of 5 ms. The unfolding of CspA is also rapid, and at urea concentrations above the denaturation midpoint, the rate of unfolding is largely independent of urea concentration. This suggests that the transition state ensemble more closely resembles the native state in terms of solvent accessibility than the denatured state. Based on the model of a compact transition state and on an unusual structural feature of CspA, a solvent-exposed cluster of aromatic side chains, we propose a novel folding mechanism for CspA. We have also investigated the possible complications that may arise from attaching polyhistidine affinity tags to the carboxy and amino termini of CspA.