Analysis and prediction of calcium-binding pockets from apo-protein structures exhibiting calcium-induced localized conformational changes

Calcium binding in proteins exhibits a wide range of polygonal geometries that relate directly to an equally diverse set of biological functions. The binding process stabilizes protein structures and typically results in local conformational change and/or global restructuring of the backbone. Previously, we established the MUG program, which utilized multiple geometries in the Ca²⁺‐binding pockets of holoproteins to identify such pockets, ignoring possible Ca²⁺‐induced conformational change. In this article, we first report our progress in the analysis of Ca²⁺‐induced conformational changes followed by improved prediction of Ca²⁺‐binding sites in the large group of Ca²⁺‐binding proteins that exhibit only localized conformational changes. The MUG^SR algorithm was devised to incorporate side chain torsional rotation as a predictor. The output from MUG^SR presents groups of residues where each group, typically containing two to five residues, is a potential binding pocket. MUG^SR was applied to both X‐ray apo structures and NMR holo structures, which did not use calcium distance constraints in structure calculations. Predicted pockets were validated by comparison with homologous holo structures. Defining a “correct hit” as a group of residues containing at least two true ligand residues, the sensitivity was at least 90%; whereas for a “correct hit” defined as a group of residues containing at least three true ligand residues, the sensitivity was at least 78%. These data suggest that Ca²⁺‐binding pockets are at least partially prepositioned to chelate the ion in the apo form of the protein.     

Side-chain flexibility in proteins upon ligand binding

Ligand binding may involve a wide range of structural changes in the receptor protein, from hinge movement of entire domains to small side-chain rearrangements in the binding pocket residues. The analysis of side chain flexibility gives insights valuable to improve docking algorithms and can provide an index of amino-acid side-chain flexibility potentially useful in molecular biology and protein engineering studies. In this study we analyzed side-chain rearrangements upon ligand binding. We constructed two non-redundant databases (980 and 353 entries) of "paired" protein structures in complexed (holo-protein) and uncomplexed (apo-protein) forms from the PDB macromolecular structural database. The number and identity of binding pocket residues that undergo side-chain conformational changes were determined. We show that, in general, only a small number of residues in the pocket undergo such changes (e.g., approximately 85% of cases show changes in three residues or less). The flexibility scale has the following order: Lys > Arg, Gln, Met > Glu, Ile, Leu > Asn, Thr, Val, Tyr, Ser, His, Asp > Cys, Trp, Phe; thus, Lys side chains in binding pockets flex 25 times more often then do the Phe side chains. Normalizing for the number of flexible dihedral bonds in each amino acid attenuates the scale somewhat, however, the clear trend of large, polar amino acids being more flexible in the pocket than aromatic ones remains. We found no correlation between backbone movement of a residue upon ligand binding and the flexibility of its side chain. These results are relevant to 1. Reduction of search space in docking algorithms by inclusion of side-chain flexibility for a limited number of binding pocket residues; and 2. Utilization of the amino acid flexibility scale in protein engineering studies to alter the flexibility of binding pockets.     

A novel and efficient tool for locating and characterizing protein cavities and binding sites

Systematic investigation of a protein and its binding site characteristics are crucial for designing small molecules that modulate protein functions. However, fundamental uncertainties in binding site interactions and insufficient knowledge of the properties of even well‐defined binding pockets can make it difficult to design optimal drugs. Herein, we report the development and implementation of a cavity detection algorithm built with HINT toolkit functions that we are naming Vectorial Identification of Cavity Extents (VICE). This very efficient algorithm is based on geometric criteria applied to simple integer grid maps. In testing, we carried out a systematic investigation on a very diverse data set of proteins and protein–protein/protein–polynucleotide complexes for locating and characterizing the indentations, cavities, pockets, grooves, channels, and surface regions. Additionally, we evaluated a curated data set of unbound proteins for which a ligand‐bound protein structures are also known; here the VICE algorithm located the actual ligand in the largest cavity in 83% of the cases and in one of the three largest in 90% of the cases. An interactive front‐end provides a quick and simple procedure for locating, displaying and manipulating cavities in these structures. Information describing the cavity, including its volume and surface area metrics, and lists of atoms, residues, and/or chains lining the binding pocket, can be easily obtained and analyzed. For example, the relative cross‐sectional surface area (to total surface area) of cavity openings in well‐enclosed cavities is 0.06 ± 0.04 and in surface clefts or crevices is 0.25 ± 0.09. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

A method for localizing ligand binding pockets in protein structures

The accurate identification of ligand binding sites in protein structures can be valuable in determining protein function. Once the binding site is known, it becomes easier to perform in silico and experimental procedures that may allow the ligand type and the protein function to be determined. For example, binding pocket shape analysis relies heavily on the correct localization of the ligand binding site. We have developed SURFNET-ConSurf, a modular, two-stage method for identifying the location and shape of potential ligand binding pockets in protein structures. In the first stage, the SURFNET program identifies clefts in the protein surface that are potential binding sites. In the second stage, these clefts are trimmed in size by cutting away regions distant from highly conserved residues, as defined by the ConSurf-HSSP database. The largest clefts that remain tend to be those where ligands bind. To test the approach, we analyzed a nonredundant set of 244 protein structures from the PDB and found that SURFNET-ConSurf identifies a ligand binding pocket in 75% of them. The trimming procedure reduces the original cleft volumes by 30% on average, while still encompassing an average 87% of the ligand volume. From the analysis of the results we conclude that for those cases in which the ligands are found in large, highly conserved clefts, the combined SURFNET-ConSurf method gives pockets that are a better match to the ligand shape and location. We also show that this approach works better for enzymes than for nonenzyme proteins.     

On the molecular discrimination between adenine and guanine by proteins

The molecular recognition and discrimination of adenine and guanine ligand moieties in complexes with proteins have been studied using empirical observations on carefully selected crystal structures. The distribution of protein folds that bind these purines has been found to differ significantly from that across the whole PDB, but the most populated architectures and folds are also the most common in three genomes from the three different domains of life. The protein environments around the two nucleic acid bases were significantly different, in terms of the propensities of amino acid residues to be in the binding site, as well as their propensities to form hydrogen bonds to the bases. Plots of the distribution of protein atoms around the two purines clearly show different clustering of hydrogen bond donors and acceptors opposite complimentary acceptors and donors in the rings, with hydrophobic areas below and above the rings. However, the clustering pattern is fuzzy, reflecting the variety of ways that proteins have evolved to recognise the same molecular moiety. Furthermore, an analysis of the conservation of residues in the protein chains binding guanine shows that residues in contact with the base are in general better conserved than the rest of the chain.     

Cofactor‐binding sites in proteins of deviating sequence: Comparative analysis and clustering in torsion angle,cavity, and fold space

Small molecules are recognized in protein‐binding pockets through surface‐exposed physicochemical properties. To optimize binding, they have to adopt a conformation corresponding to a local energy minimum within the formed protein–ligand complex. However, their conformational flexibility makes them competent to bind not only to homologous proteins of the same family but also to proteins of remote similarity with respect to the shape of the binding pockets and folding pattern. Considering drug action, such observations can give rise tounexpected and undesired cross reactivity. In this study, datasets of six different cofactors (ADP, ATP, NAD(P)(H), FAD, and acetyl CoA, sharing an adenosine diphosphate moiety as common substructure), observed in multiple crystal structures of protein–cofactor complexes exhibiting sequence identity below 25%, have been analyzed for the conformational properties of the bound ligands, the distribution of physicochemical properties in the accommodating protein‐binding pockets, and the local folding patterns next to the cofactor‐binding site. State‐of‐the‐art clustering techniques have been applied to group the different protein–cofactor complexes in the different spaces. Interestingly, clustering in cavity (Cavbase) and fold space (DALI) reveals virtually the same data structuring. Remarkable relationships can be found among the different spaces. They provide information on how conformations are conserved across the host proteins and which distinct local cavity and fold motifs recognize the different portions of the cofactors. In those cases, where different cofactors are found to be accommodated in a similar fashion to the same fold motifs, only a commonly shared substructure of the cofactors is used for the recognition process. Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Protein Functional Surfaces: Global Shape Matching and Local Spatial Alignments of Ligand Binding Sites

Background

Protein surfaces comprise only a fraction of the total residues but are the most conserved functional features of proteins. Surfaces performing identical functions are found in proteins absent of any sequence or fold similarity. While biochemical activity can be attributed to a few key residues, the broader surrounding environment plays an equally important role.

Results

We describe a methodology that attempts to optimize two components, global shape and local physicochemical texture, for evaluating the similarity between a pair of surfaces. Surface shape similarity is assessed using a three-dimensional object recognition algorithm and physicochemical texture similarity is assessed through a spatial alignment of conserved residues between the surfaces. The comparisons are used in tandem to efficiently search the Global Protein Surface Survey (GPSS), a library of annotated surfaces derived from structures in the PDB, for studying evolutionary relationships and uncovering novel similarities between proteins.

Conclusion

We provide an assessment of our method using library retrieval experiments for identifying functionally homologous surfaces binding different ligands, functionally diverse surfaces binding the same ligand, and binding surfaces of ubiquitous and conformationally flexible ligands. Results using surface similarity to predict function for proteins of unknown function are reported. Additionally, an automated analysis of the ATP binding surface landscape is presented to provide insight into the correlation between surface similarity and function for structures in the PDB and for the subset of protein kinases.     

C‐H…O hydrogen bonds in FK506‐binding protein–ligand interactions

Hydrogen bonds are important interaction forces observed in protein structures. They can be classified as stronger or weaker depending on their energy, thereby reflecting on the type of donor. The contribution of weak hydrogen bonds is deemed as an important factor toward structure stability along with the stronger bonds. One such bond, the C‐H…O type hydrogen bond, is shown to make a contribution in maintaining three dimensional structures of proteins. Apart from their presence within protein structures, the role of these bonds in protein–ligand interactions is also noteworthy. In this study, we present a statistical analysis on the presence of C‐H…O hydrogen bonds observed between FKBPs and their cognate ligands. The FK506‐binding proteins (FKBPs) carry peptidyl cis–trans isomerase activity apart from the immunosuppressive property by binding to the immunosuppressive drugs FK506 or rapamycin. Because the active site of FKBPs is lined up by many hydrophobic residues, we speculated that the prevalence of C‐H…O hydrogen bonds will be considerable. In a total of 25 structures analyzed, a higher frequency of C‐H…O hydrogen bonds is observed in comparison with the stronger hydrogen bonds. These C‐H…O hydrogen bonds are dominated by a highly conserved donor, the C^α/β of Val55 and an acceptor, the backbone oxygen of Glu54. Both these residues are positioned in the β4‐α1 loop, whereas the other residues Tyr26, Phe36 and Phe99 with higher frequencies are lined up at the opposite face of the active site. These preferences could be implicated in FKBP pharmacophore models toward enhancing the ligand affinity. This study could be a prelude to studying other proteins with hydrophobic pockets to gain better insights into ligand recognition. Copyright © 2013 John Wiley & Sons, Ltd.     

Structural basis of the drug-binding specificity of human serum albumin

Human serum albumin (HSA) is an abundant plasma protein that binds a remarkably wide range of drugs, thereby restricting their free, active concentrations. The problem of overcoming the binding affinity of lead compounds for HSA represents a major challenge in drug development. Crystallographic analysis of 17 different complexes of HSA with a wide variety of drugs and small-molecule toxins reveals the precise architecture of the two primary drug-binding sites on the protein, identifying residues that are key determinants of binding specificity and illuminating the capacity of both pockets for flexible accommodation. Numerous secondary binding sites for drugs distributed across the protein have also been identified. The binding of fatty acids, the primary physiological ligand for the protein, is shown to alter the polarity and increase the volume of drug site 1. These results clarify the interpretation of accumulated drug binding data and provide a valuable template for design efforts to modulate the interaction with HSA.     

Protein-DNA interactions: amino acid conservation and the effects of mutations on binding specificity

We investigate the conservation of amino acid residue sequences in 21 DNA-binding protein families and study the effects that mutations have on DNA-sequence recognition. The observations are best understood by assigning each protein family to one of three classes: (i) non-specific, where binding is independent of DNA sequence; (ii) highly specific, where binding is specific and all members of the family target the same DNA sequence; and (iii) multi-specific, where binding is also specific, but individual family members target different DNA sequences. Overall, protein residues in contact with the DNA are better conserved than the rest of the protein surface, but there is a complex underlying trend of conservation for individual residue positions. Amino acid residues that interact with the DNA backbone are well conserved across all protein families and provide a core of stabilising contacts for homologous protein-DNA complexes. In contrast, amino acid residues that interact with DNA bases have variable levels of conservation depending on the family classification. In non-specific families, base-contacting residues are well conserved and interactions are always found in the minor groove where there is little discrimination between base types. In highly specific families, base-contacting residues are highly conserved and allow member proteins to recognise the same target sequence. In multi-specific families, base-contacting residues undergo frequent mutations and enable different proteins to recognise distinct target sequences. Finally, we report that interactions with bases in the target sequence often follow (though not always) a universal code of amino acid-base recognition and the effects of amino acid mutations can be most easily understood for these interactions.     

Zinc coordination sphere in biochemical zinc sites

Zinc is known to be indispensable to growth and development and transmission of the genetic message. It does this through a remarkable mosaic of zinc binding motifs that orchestrate all aspects of metabolism. There are now nearly 200 three dimensional structures for zinc proteins, representing all six classes of enzymes and covering a wide range of phyla and species. These structures provide standards of reference for the identity and nature of zinc ligands in other proteins for which only the primary structure is known. Three primary types of zinc sites are apparent from examination of these structures: structural, catalytic and cocatalytic. The most common amino acids that supply ligands to these sites are His, Glu, Asp and Cys. In catalytic sites zinc generally forms complexes with water and any three nitrogen, oxygen and sulfur donors with His being the predominant amino acid chosen. Water is always a ligand to such sites. Structural zinc sites have four protein ligands and no bound water molecule. Cys is the preferred ligand in such sites. Cocatalytic sites contain two or three metals in close proximity with two of the metals bridged by a side chain moiety of a single amino acid residue, such as Asp, Glu or His and sometimes a water molecule. Asp and His are the preferred amino acids for these sites. No Cys ligands are found in such sites. The scaffolding of the zinc sites is also important to the function and reactivity of the bound metal. The influence of zinc on quaternary protein structure has led to the identification of a fourth type of zinc binding site, protein inteface. In this case zinc sites are formed from ligands supplied from amino acid residues residing in the binding surface of two proteins. The resulting zinc site usually has the coordination properties of a catalytic or structural zinc binding site.     

Vicinity analysis: a methodology for the identification of similar protein active sites

Vicinity analysis (VA) is a new methodology developed to identify similarities between protein binding sites based on their three-dimensional structure and the chemical similarity of matching residues. The major objective is to enable searching of the Protein Data Bank (PDB) for similar sub-pockets, especially in proteins from different structural and biochemical series. Inspection of the ligands bound in these pockets should allow ligand functionality to be identified, thus suggesting novel monomers for use in library synthesis. VA has been developed initially using the ATP binding site in kinases, an important class of protein targets involved in cell signalling and growth regulation. This paper defines the VA procedure and describes matches to the phosphate binding sub-pocket of cyclin-dependent protein kinase 2 that were found by searching a small test database that has also been used to parameterise the methodology.     

A network of dynamically conserved residues deciphers the motions of maltose transporter

The maltose transporter of Escherichia coli is a member of the ATP‐binding cassette (ABC) transporter superfamily. The crystal structures of maltose transporter MalK have been determined for distinct conformations in the presence and absence of the ligand ATP, and other interacting proteins. Using the distinct MalK structures, normal mode analysis was performed to understand the dynamics behavior of the system. A network of dynamically important residues was obtained from the normal mode analysis and the analysis of point mutation on the normal modes. Our results suggest that the intradomain rotation occurs earlier than the interdomain rotation during the maltose‐binding protein (MBP)‐driven conformational changes of MalK. We inquire if protein motion and functional‐driven evolutionary conservation are related. The sequence conservation of MalK was analyzed to derive a network of evolutionarily important residues. There are highly significant correlations between protein sequence and protein dynamics in many regions on the maltose transporter MalK, suggesting a link between the protein evolution and dynamics. The significant overlaps between the network of dynamically important residues and the network of evolutionarily important residues form a network of dynamically conserved residues. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Ligand binding site superposition and comparison based on Atomic Property Fields: identification of distant homologues, convergent evolution and PDB-wide clustering of binding sites

A new binding site comparison algorithm using optimal superposition of the continuous pharmacophoric property distributions is reported. The method demonstrates high sensitivity in discovering both, distantly homologous and convergent binding sites. Good quality of superposition is also observed on multiple examples. Using the new approach, a measure of site similarity is derived and applied to clustering of ligand binding pockets in PDB.     

Structure-Based Druggability Assessment of the Mammalian Structural Proteome with Inclusion of Light Protein Flexibility

Advances reported over the last few years and the increasing availability of protein crystal structure data have greatly improved structure-based druggability approaches. However, in practice, nearly all druggability estimation methods are applied to protein crystal structures as rigid proteins, with protein flexibility often not directly addressed. The inclusion of protein flexibility is important in correctly identifying the druggability of pockets that would be missed by methods based solely on the rigid crystal structure. These include cryptic pockets and flexible pockets often found at protein-protein interaction interfaces. Here, we apply an approach that uses protein modeling in concert with druggability estimation to account for light protein backbone movement and protein side-chain flexibility in protein binding sites. We assess the advantages and limitations of this approach on widely-used protein druggability sets. Applying the approach to all mammalian protein crystal structures in the PDB results in identification of 69 proteins with potential druggable cryptic pockets.     

Analysis of non-structural proteins,NSPs of SARS-CoV-2 as targets for computational drug designing

BackgroundThe ORF1ab of Severe Acute Respiratory Syndrome, SARS Corona Virus, SARS-CoV-2 genome is processed into 15 non-structural proteins, NSPs by proteases and each NSP has a specific role in the life cycle and pathogenicity of the virus. This research analyzes possible drugs for these proteins as targets in computational drug designing using already available experimental drugs from the drug bank database.MethodsOut of 471 proteins and 8820 drugs download from Protein Data Bank, PDB and Drug Bank database respectively, 16 proteins similar to NSP 1–15 and 31 drugs as per the “Rule of three” were selected for docking. Out of 88 docking results using PyRx, 18 proteins/chains with three promising drugs, DB01977, DB07132 and DB07535 were analyzed using PyMOL for final results.ResultsNSPs 3, 5, 11, 14 and 15 were identified as targets for the drugs, DB01977, BD07132 and DB07535. Drugs, DB01977 and DB07535 bind in the same binding pockets of NSP 5 and NSP 15. Drug, DB07132 binds with more number of residues when compared with the other two drugs and this indicates that the strength of protein-drug association is more by this drug with the NSPs than other drugs. Binding pockets of NSPs for these three drugs are very close with many sharing residues in common suggesting of similarity of pharmacophore of these drugs with the target binding pockets.ConclusionThe binding pockets of NSPs are well matched with the pharmacophore of drugs and with polar surface of drugs less than or equal to 100 A², drugs, DB01977, DB07132 and DB07535 bind individually and effectively with NSPs 3, 5, 11, 14 and 15 of ORF1ab of SARS-CoV-2 genome to bring changes in the activity of SARS-CoV-2 which may be useful for biological and clinical considerations.