Knowledge-based annotation of small molecule binding sites in proteins

Background  

The study of protein-small molecule interactions is vital for understanding protein function and for practical applications in drug discovery. To benefit from the rapidly increasing structural data, it is essential to improve the tools that enable large scale binding site prediction with greater emphasis on their biological validity.     

A global optimization algorithm for protein surface alignment

Background  

A relevant problem in drug design is the comparison and recognition of protein binding sites. Binding sites recognition is generally based on geometry often combined with physico-chemical properties of the site since the conformation, size and chemical composition of the protein surface are all relevant for the interaction with a specific ligand. Several matching strategies have been designed for the recognition of protein-ligand binding sites and of protein-protein interfaces but the problem cannot be considered solved.     

A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction

Background  

Predicting which molecules can bind to a given binding site of a protein with known 3D structure is important to decipher the protein function, and useful in drug design. A classical assumption in structural biology is that proteins with similar 3D structures have related molecular functions, and therefore may bind similar ligands. However, proteins that do not display any overall sequence or structure similarity may also bind similar ligands if they contain similar binding sites. Quantitatively assessing the similarity between binding sites may therefore be useful to propose new ligands for a given pocket, based on those known for similar pockets.     

Auto-FACE: An NMR Based Binding Site Mapping Program for Fast Chemical Exchange Protein-Ligand Systems

Background

Nuclear Magnetic Resonance (NMR) spectroscopy offers a variety of experiments to study protein-ligand interactions at atomic resolution. Among these experiments, N Heteronuclear Single Quantum Correlation (HSQC) experiment is simple, less time consuming and highly informative in mapping the binding site of the ligand. The interpretation of N HSQC becomes ambiguous when the chemical shift perturbations are caused by non-specific interactions like allosteric changes and local structural rearrangement. Under such cases, detailed chemical exchange analysis based on chemical shift perturbation will assist in locating the binding site accurately.

Methodology/Principal Findings

We have automated the mapping of binding sites for fast chemical exchange systems using information obtained from N HSQC spectra of protein serially titrated with ligand of increasing concentrations. The automated program Auto-FACE (Auto-FAst Chemical Exchange analyzer) determines the parameters, e.g. rate of change of perturbation, binding equilibrium constant and magnitude of chemical shift perturbation to map the binding site residues. Interestingly, the rate of change of perturbation at lower ligand concentration is highly sensitive in differentiating the binding site residues from the non-binding site residues. To validate this program, the interaction between the protein and the ligand BH3I-1 was studied. Residues in the hydrophobic BH3 binding groove of were easily identified to be crucial for interaction with BH3I-1 from other residues that also exhibited perturbation. The geometrically averaged equilibrium constant () calculated for the residues present at the identified binding site is consistent with the values obtained by other techniques like isothermal calorimetry and fluorescence polarization assays (). Adjacent to the primary site, an additional binding site was identified which had an affinity of 3.8 times weaker than the former one. Further NMR based model fitting for individual residues suggest single site model for residues present at these binding sites and two site model for residues present between these sites. This implies that chemical shift perturbation can represent the local binding event much more accurately than the global binding event.

Conclusion/Significance

Detail NMR chemical shift perturbation analysis enabled binding site residues to be distinguished from non-binding site residues for accurate mapping of interaction site in complex fast exchange system between small molecule and protein. The methodology is automated and implemented in a program called “Auto-FACE”, which also allowed quantitative information of each interaction site and elucidation of binding mechanism.     

Prediction of protein-protein binding site by using core interface residue and support vector machine

Background  

The prediction of protein-protein binding site can provide structural annotation to the protein interaction data from proteomics studies. This is very important for the biological application of the protein interaction data that is increasing rapidly. Moreover, methods for predicting protein interaction sites can also provide crucial information for improving the speed and accuracy of protein docking methods.     

Structural adaptation of extreme halophilic proteins through decrease of conserved hydrophobic contact surface

Background

Disrupting protein-protein interactions by small organic molecules is nowadays a promising strategy employed to block protein targets involved in different pathologies. However, structural changes occurring at the binding interfaces make difficult drug discovery processes using structure-based drug design/virtual screening approaches. Here we focused on two homologous calcium binding proteins, calmodulin and human centrin 2, involved in different cellular functions via protein-protein interactions, and known to undergo important conformational changes upon ligand binding.

Results

In order to find suitable protein conformations of calmodulin and centrin for further structure-based drug design/virtual screening, we performed in silico structural/energetic analysis and molecular docking of terphenyl (a mimicking alpha-helical molecule known to inhibit protein-protein interactions of calmodulin) into X-ray and NMR ensembles of calmodulin and centrin. We employed several scoring methods in order to find the best protein conformations. Our results show that docking on NMR structures of calmodulin and centrin can be very helpful to take into account conformational changes occurring at protein-protein interfaces.

Conclusions

NMR structures of protein-protein complexes nowadays available could efficiently be exploited for further structure-based drug design/virtual screening processes employed to design small molecule inhibitors of protein-protein interactions.     

PocketMatch: A new algorithm to compare binding sites in protein structures

Background  

Recognizing similarities and deriving relationships among protein molecules is a fundamental requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison.     

Exploring allosteric coupling in the α-subunit of Heterotrimeric G proteins using evolutionary and ensemble-based approaches

Background  

Allosteric coupling, which can be defined as propagation of a perturbation at one region of the protein molecule (such as ligand binding) to distant sites in the same molecule, constitutes the most general mechanism of regulation of protein function. However, unlike molecular details of ligand binding, structural elements involved in allosteric effects are difficult to diagnose. Here, we identified allosteric linkages in the α-subunits of heterotrimeric G proteins, which were evolved to transmit membrane receptor signals by allosteric mechanisms, by using two different approaches that utilize fundamentally different and independent information.     

Crystallographic Study of Novel Transthyretin Ligands Exhibiting Negative-Cooperativity between Two Thyroxine Binding Sites

Background

Transthyretin (TTR) is a homotetrameric serum and cerebrospinal fluid protein that transports thyroxine (T4) and retinol by binding to retinol binding protein. Rate-limiting tetramer dissociation and rapid monomer misfolding and disassembly of TTR lead to amyloid fibril formation in different tissues causing various amyloid diseases. Based on the current understanding of the pathogenesis of TTR amyloidosis, it is considered that the inhibition of amyloid fibril formation by stabilization of TTR in native tetrameric form is a viable approach for the treatment of TTR amyloidosis.

Methodology and Principal Findings

We have examined interactions of the wtTTR with a series of compounds containing various substitutions at biphenyl ether skeleton and a novel compound, previously evaluated for binding and inhibiting tetramer dissociation, by x-ray crystallographic approach. High resolution crystal structures of five ligands in complex with wtTTR provided snapshots of negatively cooperative binding of ligands in two T4 binding sites besides characterizing their binding orientations, conformations, and interactions with binding site residues. In all complexes, the ligand has better fit and more potent interactions in first T4 site i.e. (AC site) than the second T4 site (BD site). Together, these results suggest that AC site is a preferred ligand binding site and retention of ordered water molecules between the dimer interfaces further stabilizes the tetramer by bridging a hydrogen bond interaction between Ser117 and its symmetric copy.

Conclusion

Novel biphenyl ether based compounds exhibit negative-cooperativity while binding to two T4 sites which suggests that binding of only single ligand molecule is sufficient to inhibit the TTR tetramer dissociation.     

Localization of HIV-1 Vpr to the nuclear envelope: Impact on Vpr functions and virus replication in macrophages

Background

HIV-1 integrase (IN) is an emerging drug target, as IN strand transfer inhibitors (INSTIs) are proving potent antiretroviral agents in clinical trials. One credible theory sees INSTIs as docking at the cellular (acceptor) DNA-binding site after IN forms a transitional complex with viral (donor) DNA. However, mapping of the DNA and INSTI binding sites within the IN catalytic core domain (CCD) has been uncertain.

Methods

Structural superimpositions were conducted using the SWISS PDB and Cn3D free software. Docking simulations of INSTIs were run by a widely validated genetic algorithm (GOLD).

Results

Structural superimpositions suggested that a two-metal model for HIV-1 IN CCD in complex with small molecule, 1-(5-chloroindol-3-yl)-3-(tetrazoyl)-1,3-propandione-ene (5CITEP) could be used as a surrogate for an IN/viral DNA complex, because it allowed replication of contacts documented biochemically in viral DNA/IN complexes or displayed by a crystal structure of the IN-related enzyme Tn5 transposase in complex with transposable DNA. Docking simulations showed that the fitness of different compounds for the catalytic cavity of the IN/5CITEP complex significantly (P < 0.01) correlated with their 50% inhibitory concentrations (IC₅₀s) in strand transfer assays in vitro. The amino acids involved in inhibitor binding matched those involved in drug resistance. Both metal binding and occupation of the putative viral DNA binding site by 5CITEP appeared to be important for optimal drug/ligand interactions. The docking site of INSTIs appeared to overlap with a putative acceptor DNA binding region adjacent to but distinct from the putative donor DNA binding site, and homologous to the nucleic acid binding site of RNAse H. Of note, some INSTIs such as 4,5-dihydroxypyrimidine carboxamides/N -Alkyl-5-hydroxypyrimidinone carboxamides, a highly promising drug class including raltegravir/MK-0518 (now in clinical trials), displayed interactions with IN reminiscent of those displayed by fungal molecules from Fusarium sp., shown in the 1990s to inhibit HIV-1 integration.

Conclusion

The 3D model presented here supports the idea that INSTIs dock at the putative acceptor DNA-binding site in a IN/viral DNA complex. This mechanism of enzyme inhibition, likely to be exploited by some natural products, might disclose future strategies for inhibition of nucleic acid-manipulating enzymes.     

Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information

Background  

Protein-protein interactions play essential roles in protein function determination and drug design. Numerous methods have been proposed to recognize their interaction sites, however, only a small proportion of protein complexes have been successfully resolved due to the high cost. Therefore, it is important to improve the performance for predicting protein interaction sites based on primary sequence alone.     

High-throughput identification of interacting protein-protein binding sites

Background  

With the advent of increasing sequence and structural data, a number of methods have been proposed to locate putative protein binding sites from protein surfaces. Therefore, methods that are able to identify whether these binding sites interact are needed.     

PDTD: a web-accessible protein database for drug target identification

Background  

Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D) structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (TargetFishingDocking), which has been used widely by others. Recently, we have constructed a protein target database,PotentialDrugTargetDatabase (PDTD), and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation.     

Prediction of protein binding sites in protein structures using hidden Markov support vector machine

Background  

Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. Recent research on protein binding site prediction has been mainly based on widely known machine learning techniques, such as artificial neural networks, support vector machines, conditional random field, etc. However, the prediction performance is still too low to be used in practice. It is necessary to explore new algorithms, theories and features to further improve the performance.     

Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction

Background  

Structural variations caused by a wide range of physico-chemical and biological sources directly influence the function of a protein. For enzymatic proteins, the structure and chemistry of the catalytic binding site residues can be loosely defined as a substructure of the protein. Comparative analysis of drug-receptor substructures across and within species has been used for lead evaluation. Substructure-level similarity between the binding sites of functionally similar proteins has also been used to identify instances of convergent evolution among proteins. In functionally homologous protein families, shared chemistry and geometry at catalytic sites provide a common, local point of comparison among proteins that may differ significantly at the sequence, fold, or domain topology levels.     

Structural motifs recurring in different folds recognize the same ligand fragments

Background  

The structural analysis of protein ligand binding sites can provide information relevant for assigning functions to unknown proteins, to guide the drug discovery process and to infer relations among distant protein folds. Previous approaches to the comparative analysis of binding pockets have usually been focused either on the ligand or the protein component. Even though several useful observations have been made with these approaches they both have limitations. In the former case the analysis is restricted to binding pockets interacting with similar ligands, while in the latter it is difficult to systematically check whether the observed structural similarities have a functional significance.     

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

Background

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds.

Methodology

In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy.

Conclusions

The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.     

High-throughput kinase assays with protein substrates using fluorescent polymer superquenching

Background  

High-throughput screening is used by the pharmaceutical industry for identifying lead compounds that interact with targets of pharmacological interest. Because of the key role that aberrant regulation of protein phosphorylation plays in diseases such as cancer, diabetes and hypertension, kinases have become one of the main drug targets. With the exception of antibody-based assays, methods to screen for specific kinase activity are generally restricted to the use of small synthetic peptides as substrates. However, the use of natural protein substrates has the advantage that potential inhibitors can be detected that affect enzyme activity by binding to a site other than the catalytic site. We have previously reported a non-radioactive and non-antibody-based fluorescence quench assay for detection of phosphorylation or dephosphorylation using synthetic peptide substrates. The aim of this work is to develop an assay for detection of phosphorylation of chemically unmodified proteins based on this polymer superquenching platform.