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ABSTRACT: In this study, we use the recently released 2012 Community Structure-Activity Resource (CSAR) Dataset to evaluate two knowledge-based scoring functions, ITScore and STScore, and a simple force-field-based potential (VDWScore). The CSAR Dataset contains 757 compounds, most with known affinities, and 57 crystal structures. With the help of the script files for docking preparation, we use the full CSAR Dataset to evaluate the performances of the scoring functions on binding affinity prediction and active/inactive compound discrimination. The CSAR subset that includes crystal structures is used as well, to evaluate the performances of the scoring functions on binding mode and affinity predictions. Within this structure subset, we investigate the importance of accurate ligand and protein conformational sampling and find that the binding affinity predictions are less sensitive to the non-native ligand and protein conformations than the binding mode predictions. We also find the full CSAR Dataset to be more challenging in making binding mode predictions than the subset with structures. The script files used for preparing the CSAR Dataset for docking, including scripts for canonicalization of the ligand atoms, are offered freely to the academic community.
Journal of Chemical Information and Modeling 05/2013; · 4.68 Impact Factor
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ABSTRACT: Protein-RNA interactions play an important role in many biological processes. The ability to predict the molecular structures of protein-RNA complexes from docking would be valuable for understanding the underlying chemical mechanisms. We have developed a novel nonredundant benchmark dataset for protein-RNA docking and scoring. The diverse dataset of 72 targets consists of 52 unbound-unbound test complexes, and 20 unbound-bound test complexes. Here, unbound-unbound complexes refer to cases in which both binding partners of the cocrystallized complex are either in apo form or in a conformation taken from a different protein-RNA complex, whereas unbound-bound complexes are cases in which only one of the two binding partners has another experimentally determined conformation. The dataset is classified into three categories according to the interface root mean square deviation and the percentage of native contacts in the unbound structures: 49 easy, 16 medium, and 7 difficult targets. The bound and unbound cases of the benchmark dataset are expected to benefit the development and improvement of docking and scoring algorithms for the docking community. All the easy-to-view structures are freely available to the public at http://zoulab.dalton.missouri.edu/RNAbenchmark/. © 2012 Wiley Periodicals, Inc.
Journal of Computational Chemistry 10/2012; · 4.58 Impact Factor
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ABSTRACT: Mutations in ClC channel proteins may cause serious functional changes and even diseases. The function of ClC proteins mainly manifests as Cl(-) transport, which is related to the binding free energies of chloride ions. Therefore, the influence of a mutation on ClC function can be studied by investigating the mutational effect on the binding free energies of chloride ions. The present study provides quantitative and systematic investigations on the influences of residue mutations on the electrostatic binding free energies in Escherichia coli ClC (EcClC) proteins, using all-atom molecular dynamics simulations. It was found that the change of the electrostatic binding free energy decreases linearly with the increase of the residue-chloride ion distance for a mutation. This work reveals how changes in the charge of a mutated residue and in the distance between the mutated residue and the binding site govern the variations in the electrostatic binding free energies and therefore influence the transport of chloride ions and conduction in EcClC. This work would facilitate our understanding of the mutational effects on transport of chloride ions and functions of ClC proteins and provide a guideline to estimate which residue mutations will have great influences on ClC functions.
The Journal of Physical Chemistry B 05/2012; 116(22):6431-8. · 3.70 Impact Factor
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Sarel J Fleishman,
Timothy A Whitehead,
Eva-Maria Strauch,
Jacob E Corn,
Sanbo Qin,
Huan-Xiang Zhou,
Julie C Mitchell,
Omar N A Demerdash,
Mayuko Takeda-Shitaka,
Genki Terashi, [......],
Juan Esquivel-Rodríguez,
Daisuke Kihara,
P Benjamin Stranges,
Ron Jacak,
Brian Kuhlman,
Sheng-You Huang, Xiaoqin Zou,
Shoshana J Wodak,
Joel Janin,
David Baker
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ABSTRACT: The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.
Journal of Molecular Biology 11/2011; 414(2):289-302. · 4.00 Impact Factor
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William M Rockey,
Frank J Hernandez,
Sheng-You Huang,
Song Cao,
Craig A Howell,
Gregory S Thomas,
Xiu Ying Liu,
Natalia Lapteva,
David M Spencer,
James O McNamara, Xiaoqin Zou,
Shi-Jie Chen,
Paloma H Giangrande
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ABSTRACT: RNA aptamers represent an emerging class of pharmaceuticals with great potential for targeted cancer diagnostics and therapy. Several RNA aptamers that bind cancer cell-surface antigens with high affinity and specificity have been described. However, their clinical potential has yet to be realized. A significant obstacle to the clinical adoption of RNA aptamers is the high cost of manufacturing long RNA sequences through chemical synthesis. Therapeutic aptamers are often truncated postselection by using a trial-and-error process, which is time consuming and inefficient. Here, we used a "rational truncation" approach guided by RNA structural prediction and protein/RNA docking algorithms that enabled us to substantially truncateA9, an RNA aptamer to prostate-specific membrane antigen (PSMA),with great potential for targeted therapeutics. This truncated PSMA aptamer (A9L; 41mer) retains binding activity, functionality, and is amenable to large-scale chemical synthesis for future clinical applications. In addition, the modeled RNA tertiary structure and protein/RNA docking predictions revealed key nucleotides within the aptamer critical for binding to PSMA and inhibiting its enzymatic activity. Finally, this work highlights the utility of existing RNA structural prediction and protein docking techniques that may be generally applicable to developing RNA aptamers optimized for therapeutic use.
Nucleic acid therapeutics. 10/2011; 21(5):299-314.
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ABSTRACT: In this study, we have developed a statistical mechanics-based iterative method to extract statistical atomic interaction potentials from known, nonredundant protein structures. Our method circumvents the long-standing reference state problem in deriving traditional knowledge-based scoring functions, by using rapid iterations through a physical, global convergence function. The rapid convergence of this physics-based method, unlike other parameter optimization methods, warrants the feasibility of deriving distance-dependent, all-atom statistical potentials to keep the scoring accuracy. The derived potentials, referred to as ITScore/Pro, have been validated using three diverse benchmarks: the high-resolution decoy set, the AMBER benchmark decoy set, and the CASP8 decoy set. Significant improvement in performance has been achieved. Finally, comparisons between the potentials of our model and potentials of a knowledge-based scoring function with a randomized reference state have revealed the reason for the better performance of our scoring function, which could provide useful insight into the development of other physical scoring functions. The potentials developed in this study are generally applicable for structural selection in protein structure prediction.
Proteins Structure Function and Bioinformatics 09/2011; 79(9):2648-61. · 3.39 Impact Factor
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ABSTRACT: Based on a statistical mechanics-based iterative method, we have extracted a set of distance-dependent, all-atom pairwise potentials for protein-ligand interactions from the crystal structures of 1300 protein-ligand complexes. The iterative method circumvents the long-standing reference state problem in knowledge-based scoring functions. The resulted scoring function, referred to as ITScore 2.0, has been tested with the CSAR (Community Structure-Activity Resource, 2009 release) benchmark of 345 diverse protein-ligand complexes. ITScore 2.0 achieved a Pearson correlation of R(2) = 0.54 in binding affinity prediction. A comparative analysis has been done on the scoring performances of ITScore 2.0, the van der Waals (VDW) scoring function, the VDW with heavy atoms only, and the force field (FF) scoring function of DOCK which consists of a VDW term and an electrostatic term. The results reveal several important factors that affect the scoring performances, which could be helpful for the improvement of scoring functions.
Journal of Chemical Information and Modeling 08/2011; 51(9):2097-106. · 4.68 Impact Factor
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ABSTRACT: Two sets of ligand binding decoys have been constructed for the community structure-activity resource (CSAR) benchmark by using the MDock and DOCK programs for rigid- and flexible-ligand docking, respectively. The decoys generated for each complex in the benchmark thoroughly cover the binding site and also contain a certain number of near-native binding modes. A few scoring functions have been evaluated using the ligand binding decoy sets for their abilities of predicting near-native binding modes. Among them, ITScore achieved a success rate of 86.7% for the rigid-ligand decoys and 79.7% for the flexible-ligand decoys, under the common definition of a successful prediction as root-mean-square deviation <2.0 Å from the native structure if the top-scored binding mode was considered. The decoy sets may serve as benchmarks for binding mode prediction of a scoring function, which are available at the CSAR Web site ( http://www.csardock.org/).
Journal of Chemical Information and Modeling 08/2011; 51(9):2107-14. · 4.68 Impact Factor
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ABSTRACT: The common gating of CLC-1 has been shown to be inhibited by intracellular adenosine triphosphate (ATP) in acidic pH conditions. Such modulation is thought to be mediated by direct binding of ATP to the cystathionine β-synthase (CBS) domains at the C-terminal cytoplasmic region of CLC-1. Guided by the crystal structure of the C-terminal domain of CLC-5, we constructed a homology model of CLC-1's C terminus and mutated critical amino acid residues lining the potential ATP-binding site. The CLC-1 mutations V634A and E865A completely abolished the ATP inhibition of CLC-1, consistent with the loss of ATP binding seen with the corresponding mutations in CLC-5. Mutating two other residues, V613 and V860, also disrupted the ATP modulation of CLC-1. However, placing aromatic amino acids at position 634 increases the apparent ATP affinity. Mutant cycle analyses showed that the modulation effects of ATP and cytidine triphosphate on wild-type CLC-1 and the V634F mutant were nonadditive, suggesting that the side chain of amino acid at position 634 interacts with the base moiety of the nucleotide. The mutation effects of V634F and V613A on the ATP modulation were also nonadditive, which is consistent with the assertion suggested from the homology model that these two residues may both interact with the bound nucleotide. These results provide evidence for a direct ATP binding for modulating the function of CLC-1 and suggest an overall conserved architecture of the ATP-binding sites in CLC-1 and CLC-5. This study also demonstrates that CLC-1 is a convenient experimental model for studying the interaction of nucleotides/nucleosides with the CBS domain.
The Journal of General Physiology 04/2011; 137(4):357-68. · 3.84 Impact Factor
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ABSTRACT: Inverse docking is a relatively new technique that has been used to identify potential receptor targets of small molecules. Our docking software package MDock is well suited for such an application as it is both computationally efficient, yet simultaneously shows adequate results in binding affinity predictions and enrichment tests. As a validation study, we present the first stage results of an inverse-docking study which seeks to identify potential direct targets of PRIMA-1. PRIMA-1 is well known for its ability to restore mutant p53's tumor suppressor function, leading to apoptosis in several types of cancer cells. For this reason, we believe that potential direct targets of PRIMA-1 identified in silico should be experimentally screened for their ability to inhibit cancer cell growth. The highest-ranked human protein of our PRIMA-1 docking results is oxidosqualene cyclase (OSC), which is part of the cholesterol synthetic pathway. The results of two followup experiments which treat OSC as a possible anti-cancer target are promising. We show that both PRIMA-1 and Ro 48-8071, a known potent OSC inhibitor, significantly reduce the viability of BT-474 and T47-D breast cancer cells relative to normal mammary cells. In addition, like PRIMA-1, we find that Ro 48-8071 results in increased binding of p53 to DNA in BT-474 cells (which express mutant p53). For the first time, Ro 48-8071 is shown as a potent agent in killing human breast cancer cells. The potential of OSC as a new target for developing anticancer therapies is worth further investigation.
Journal of molecular graphics & modelling 01/2011; 29(6):795-9. · 2.17 Impact Factor
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ABSTRACT: A hierarchical approach has been developed for protein-protein docking. In the first step, a Fast Fourier Transform (FFT)-based docking algorithm is used to globally sample all putative binding modes, in which the protein is represented by a reduced model, that is, each side chain on the protein surface is represented by its center of mass. Compared to conventional FFT docking with all-atom models, the FFT docking method with a reduced model is expected to generate more hits because it allows larger side-chain flexibility. Next, the filtered binding modes (normally several thousands) are refined by an iteratively derived knowledge-based scoring function ITScorePP and by considering backbone/loop flexibility using an ensemble docking algorithm. The distance-dependent potentials of ITScorePP were extracted by a physics-based iterative method, which circumvents the long-standing reference state problem in the knowledge-based approaches. With this hierarchical protocol, we have participated in the CAPRI experiments for Rounds 15-19 of 11 targets (T32-T42). In the predictor experiments, we achieved correct binding modes for six targets: three are with high accuracy (T40 for both distinct binding modes, T41, and T42), two are with medium accuracy (T34 and T37), and one is acceptable (T32). In the scorer experiments, of the seven target complexes that contain at least one acceptable mode submitted by the CAPRI predictor groups, we obtained correct binding modes for four targets: three are with high accuracy (T37, T40, and T41) and one is with medium accuracy (T34), suggesting good accuracy and robustness of ITScorePP.
Proteins Structure Function and Bioinformatics 11/2010; 78(15):3096-103. · 3.39 Impact Factor
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ABSTRACT: The scoring function is one of the most important components in structure-based drug design. Despite considerable success, accurate and rapid prediction of protein-ligand interactions is still a challenge in molecular docking. In this perspective, we have reviewed three basic types of scoring functions (force-field, empirical, and knowledge-based) and the consensus scoring technique that are used for protein-ligand docking. The commonly-used assessment criteria and publicly available protein-ligand databases for performance evaluation of the scoring functions have also been presented and discussed. We end with a discussion of the challenges faced by existing scoring functions and possible future directions for developing improved scoring functions.
Physical Chemistry Chemical Physics 10/2010; 12(40):12899-908. · 3.57 Impact Factor
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ABSTRACT: BK-type K(+) channels are activated by voltage and intracellular Ca(2+), which is important in modulating muscle contraction, neural transmission, and circadian pacemaker output. Previous studies suggest that the cytosolic domain of BK channels contains two different Ca(2+) binding sites, but the molecular composition of one of the sites is not completely known. Here we report, by systematic mutagenesis studies, the identification of E535 as part of this Ca(2+) binding site. This site is specific for binding to Ca(2+) but not Cd(2+). Experimental results and molecular modeling based on the X-ray crystallographic structures of the BK channel cytosolic domain suggest that the binding of Ca(2+) by the side chains of E535 and the previously identified D367 changes the conformation around the binding site and turns the side chain of M513 into a hydrophobic core, providing a basis to understand how Ca(2+) binding at this site opens the activation gate of the channel that is remotely located in the membrane.
Proceedings of the National Academy of Sciences 10/2010; 107(43):18700-5. · 9.68 Impact Factor
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ABSTRACT: A three-state, multiion kinetic model was proposed to enable the conduction properties of the mammalian channel ClC-0 to be well characterized. Using this rate-theory based model, the current-voltage and conductance-concentration relations were obtained. The five parameters needed were determined by fitting the data of conduction experiments of the wild-type ClC-0 and its K519C mutant. The model was then tested against available calculation and simulation data, and the energy differences between distinct chloride-occupancy states computed agreed with an independent calculation on the binding free energies solved by using the Poisson-Boltzmann equation. The average ion number of conduction and the ion passing duration calculated closely resembled the values obtained from Brownian dynamics simulations. According to the model, the decrease of conductance caused by mutating residue K519 to C519 can be attributed to the effect of K519C mutation on translocation rate constants. Our study sets up a theoretical model for ion permeation and conductance in ClC-0. It provides a starting point for experimentalists to test the three-state model, and would help in understanding the conduction mechanism of ClC-0.
Biophysical Journal 07/2010; 99(2):464-71. · 3.65 Impact Factor
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ABSTRACT: The effects of solvation and entropy play a critical role in determining the binding free energy in protein-ligand interactions. Despite the good balance between speed and accuracy, no current knowledge-based scoring functions account for the effects of solvation and configurational entropy explicitly due to the difficulty in deriving the corresponding pair potentials and the resulting double counting problem. In the present work, we have included the solvation effect and configurational entropy in the knowledge-based scoring function by an iterative method. The newly developed scoring function has yielded a success rate of 91% in identifying near-native binding modes with Wang et al.'s benchmark of 100 diverse protein-ligand complexes. The results have been compared with the results of 15 other scoring functions for validation purpose. In binding affinity prediction, our scoring function has yielded a correlation of R(2) = 0.76 between the predicted binding scores and the experimentally measured binding affinities on the PMF validation sets of 77 diverse complexes. The results have been compared with R(2) of four other well-known knowledge-based scoring functions. Finally, our scoring function was also validated on the large PDBbind database of 1299 protein-ligand complexes and yielded a correlation coefficient of 0.474. The present computational model can be applied to other scoring functions to account for solvation and entropic effects.
Journal of Chemical Information and Modeling 02/2010; 50(2):262-73. · 4.68 Impact Factor
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ABSTRACT: Molecular docking is a widely-used computational tool for the study of molecular recognition, which aims to predict the binding mode and binding affinity of a complex formed by two or more constituent molecules with known structures. An important type of molecular docking is protein-ligand docking because of its therapeutic applications in modern structure-based drug design. Here, we review the recent advances of protein flexibility, ligand sampling, and scoring functions-the three important aspects in protein-ligand docking. Challenges and possible future directions are discussed in the Conclusion.
International Journal of Molecular Sciences 01/2010; 11(8):3016-34. · 2.60 Impact Factor
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ABSTRACT: Generalized Born (GB) models are widely used to study the electrostatic energetics of solute molecules including proteins. Previous work demonstrates that GB models may produce satisfactory solvation energies if accurate effective Born radii are computed for all atoms. Our previous study showed that a GB model which reproduces the solvation energy may not necessarily be suitable for ligand binding calculations. In this work, we studied binding energetics using the exact GB model, in which Born radii are computed from the Poisson-Boltzmann (PB) equation. Our results showed that accurate Born radii lead to very good agreement between GB and PB in electrostatic calculations for ligand binding. However, recently developed GB models with high Born radii accuracy, when used in large database screening, may suffer from time constraints which make accurate, large-scale Born radii calculations impractical. We therefore present a multiscale GB approach in which atoms are divided into two groups. For atoms in the first group, those few atoms which are most likely to be critical to binding electrostatics, the Born radii are computed accurately at the sacrifice of speed. We propose two alternative approaches for atoms in the second group. The Born radii of these atoms may simply be computed by a fast GB method. Alternatively, the Born radii of these atoms may be computed accurately in the free state, and then, a variational form of a fast GB method may be used to compute the change in Born radii experienced by these atoms during binding. This strategy provides an accuracy advantage while still being fast enough for use in the virtual screening of large databases.
The Journal of Physical Chemistry B 09/2009; 113(35):11793-9. · 3.70 Impact Factor
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ABSTRACT: We have presented a new protein-protein docking approach to model heterodimeric structures based on the conformations of the monomeric units. The conventional modeling method relies on superimposing two monomeric structures onto the crystal structure of a homologous protein dimer. The resulting structure may exhibit severe backbone clashes at the dimeric interface depending on the backbone dissimilarity between the target and template proteins. Our method overcomes the backbone clashing problem and requires no a priori knowledge of the dimeric structure of a homologous protein. Here we used human Cystic Fibrosis Transmembrane conductance Regulator (CFTR), a chloride channel whose dysfunction causes cystic fibrosis, for illustration. The two intracellular nucleotide-binding domains (NBDs) of CFTR control the opening and closing of the channel. Yet, the structure of the CFTR's NBD1-NBD2 complex has not been experimentally determined. Thus, correct modeling of this heterodimeric structure is valuable for understanding CFTR functions and would have potential applications for drug design for cystic fibrosis treatment. Based on the crystal structure of human CFTR's NBD1, we constructed a model of the NBD1-NBD2 complex. The constructed model is consistent with the dimeric mode observed in the crystal structures of other ABC transporters. To verify our structural model, an ATP substrate was docked into the nucleotide-binding site. The predicted binding mode shows consistency with related crystallographic findings and CFTR functional studies. Finally, genistein, an agent that enhances CFTR activity, though the mechanism for such enhancement is unclear, was docked to the model. Our predictions agreed with genistein's bell-shaped dose-response relationship. Potential mutagenesis experiments were proposed for understanding the potentiation mechanism of genistein and for providing insightful information for drug design targeting at CFTR. The method used in this study can be applied to modeling studies of other dimeric protein structures.
Journal of molecular graphics & modelling 01/2009; 27(7):822-8. · 2.17 Impact Factor
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ABSTRACT: An increasing attention has been dedicated to the characterization of complex networks within the protein world. Before now most investigations about protein structures were only considered where the interactive cutoff distance R(c)=5 or 7A. It is noteworthy that the length of peptide bond is about 1.5A, the length of hydrogen bond is about 3A, the range of London-van der Waals force is about 5A and the range of hydrophobic effect can reach to 12A in protein molecule. Present work reports a study on the topological properties of the amino acid network constructed by different interactions above. The results indicate that the small-world property of amino acid network constructed by the peptide and hydrogen bond, London-van der Waals force and the hydrophobic effect is strong, very strong and relatively weak, respectively. Besides, there exists a precise exponential relation C is proportional to k(-0.5) at R(c)=12A. It means that the amino acid network constructed by the hydrophobic effect tend to be hierarchical. Functional modules could be the cause for hierarchical modularity architecture in protein structures. This study on amino acid interactive network for different interactions facilitates the identification of binding sites which is strongly linked with protein function, and furthermore provides reasonable understanding of the underlying laws of evolution in genomics and proteomics.
Journal of Theoretical Biology 12/2008; 256(3):408-13. · 2.21 Impact Factor
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ABSTRACT: Using an efficient iterative method, we have developed a distance-dependent knowledge-based scoring function to predict protein-protein interactions. The function, referred to as ITScore-PP, was derived using the crystal structures of a training set of 851 protein-protein dimeric complexes containing true biological interfaces. The key idea of the iterative method for deriving ITScore-PP is to improve the interatomic pair potentials by iteration, until the pair potentials can distinguish true binding modes from decoy modes for the protein-protein complexes in the training set. The iterative method circumvents the challenging reference state problem in deriving knowledge-based potentials. The derived scoring function was used to evaluate the ligand orientations generated by ZDOCK 2.1 and the native ligand structures on a diverse set of 91 protein-protein complexes. For the bound test cases, ITScore-PP yielded a success rate of 98.9% if the top 10 ranked orientations were considered. For the more realistic unbound test cases, the corresponding success rate was 40.7%. Furthermore, for faster orientational sampling purpose, several residue-level knowledge-based scoring functions were also derived following the similar iterative procedure. Among them, the scoring function that uses the side-chain center of mass (SCM) to represent a residue, referred to as ITScore-PP(SCM), showed the best performance and yielded success rates of 71.4% and 30.8% for the bound and unbound cases, respectively, when the top 10 orientations were considered. ITScore-PP was further tested using two other published protein-protein docking decoy sets, the ZDOCK decoy set and the RosettaDock decoy set. In addition to binding mode prediction, the binding scores predicted by ITScore-PP also correlated well with the experimentally determined binding affinities, yielding a correlation coefficient of R = 0.71 on a test set of 74 protein-protein complexes with known affinities. ITScore-PP is computationally efficient. The average run time for ITScore-PP was about 0.03 second per orientation (including optimization) on a personal computer with 3.2 GHz Pentium IV CPU and 3.0 GB RAM. The computational speed of ITScore-PP(SCM) is about an order of magnitude faster than that of ITScore-PP. ITScore-PP and/or ITScore-PP(SCM) can be combined with efficient protein docking software to study protein-protein recognition.
Proteins Structure Function and Bioinformatics 09/2008; 72(2):557-79. · 3.39 Impact Factor
