Determination of binding affinity upon mutation for type I dockerin–cohesin complexes from Clostridium thermocellum and Clostridium cellulolyticum using deep sequencing

The comprehensive sequence determinants of binding affinity for type I cohesin toward dockerin from Clostridium thermocellum and Clostridium cellulolyticum was evaluated using deep mutational scanning coupled to yeast surface display. We measured the relative binding affinity to dockerin for 2970 and 2778 single point mutants of C. thermocellum and C. cellulolyticum, respectively, representing over 96% of all possible single point mutants. The interface ΔΔG for each variant was reconstructed from sequencing counts and compared with the three independent experimental methods. This reconstruction results in a narrow dynamic range of ?0.8–0.5 kcal/mol. The computational software packages FoldX and Rosetta were used to predict mutations that disrupt binding by more than 0.4 kcal/mol. The area under the curve of receiver operator curves was 0.82 for FoldX and 0.77 for Rosetta, showing reasonable agreements between predictions and experimental results. Destabilizing mutations to core and rim positions were predicted with higher accuracy than support positions. This benchmark dataset may be useful for developing new computational prediction tools for the prediction of the mutational effect on binding affinities for protein–protein interactions. Experimental considerations to improve precision and range of the reconstruction method are discussed. Proteins 2016; 84:1914–1928. © 2016 Wiley Periodicals, Inc.     

Zinc finger protein binding to DNA: an energy perspective using molecular dynamics simulation and free energy calculations on mutants of both zinc finger domains and their specific DNA bases

Energy calculations based on MM-GBSA were employed to study various zinc finger protein (ZF) motifs binding to DNA. Mutants of both the DNA bound to their specific amino acids were studied. Calculated energies gave evidence for a relationship between binding energy and affinity of ZF motifs to their sites on DNA. ΔG values were ?15.82(12), ?3.66(12), and ?12.14(11.6) kcal/mol for finger one, finger two, and finger three, respectively. The mutations in the DNA bases reduced the value of the negative energies of binding (maximum value for ΔΔG = 42Kcal/mol for F1 when GCG mutated to GGG, and ΔΔG = 22 kcal/mol for F2, the loss in total energy of binding originated in the loss in electrostatic energies upon mutation (r = .98). The mutations in key amino acids in the ZF motif in positions-1, 2, 3, and 6 showed reduced binding energies to DNA with correlation coefficients between total free energy and electrostatic was .99 and with Van der Waal was .93. Results agree with experimentally found selectivity which showed that Arginine in position-1 is specific to G, while Aspartic acid (D) in position 2 plays a complicated role in binding. There is a correlation between the MD calculated free energies of binding and those obtained experimentally for prepared ZF motifs bound to triplet bases in other reports (), our results may help in the design of ZF motifs based on the established recognition codes based on energies and contributing energies to the total energy.     

A multiscale approach to predicting affinity changes in protein–protein interfaces

Substitution mutations in protein–protein interfaces can have a substantial effect on binding, which has consequences in basic and applied biomedical research. Experimental expression, purification, and affinity determination of protein complexes is an expensive and time‐consuming means of evaluating the effect of mutations, making a fast and accurate in silico method highly desirable. When the structure of the wild‐type complex is known, it is possible to economically evaluate the effect of point mutations with knowledge based potentials, which do not model backbone flexibility, but these have been validated only for single mutants. Substitution mutations tend to induce local conformational rearrangements only. Accordingly, ZEMu (Zone Equilibration of Mutants) flexibilizes only a small region around the site of mutation, then computes its dynamics under a physics‐based force field. We validate with 1254 experimental mutants (with 1–15 simultaneous substitutions) in a wide variety of different protein environments (65 protein complexes), and obtain a significant improvement in the accuracy of predicted ΔΔG. Proteins 2014; 82:2681–2690. © 2014 Wiley Periodicals, Inc.     

Effects of ligand binding on the stability of aldo–keto reductases: Implications for stabilizer or destabilizer chaperones

Ligands such as enzyme inhibitors stabilize the native conformation of a protein upon binding to the native state, but some compounds destabilize the native conformation upon binding to the non‐native state. The former ligands are termed “stabilizer chaperones” and the latter ones “destabilizer chaperones.” Because the stabilization effects are essential for the medical chaperone (MC) hypothesis, here we have formulated a thermodynamic system consisting of a ligand and a protein in its native‐ and non‐native state. Using the differential scanning fluorimetry and the circular dichroism varying the urea concentration and temperature, we found that when the coenzyme NADP⁺ was absent, inhibitors such as isolithocholic acid stabilized the aldo–keto reductase AKR1A1 upon binding, which showed actually the three‐state folding, but destabilized AKR1B10. In contrast, in the presence of NADP⁺, they destabilized AKR1A1 and stabilized AKR1B10. To explain these phenomena, we decomposed the free energy of stabilization (ΔΔG) into its enthalpy (ΔΔH) and entropy (ΔΔS) components. Then we found that in a relatively unstable protein showing the three‐state folding, native conformation was stabilized by the negative ΔΔH in association with the negative ΔΔS, suggesting that the stabilizer chaperon decreases the conformational fluctuation of the target protein or increase its hydration. However, in other cases, ΔΔG was essentially determined by the delicate balance between ΔΔH and ΔΔS. The proposed thermodynamic formalism is applicable to the system including multiple ligands with allosteric interactions. These findings would promote the development of screening strategies for MCs to regulate the target conformations.     

Urea interactions with protein groups: A volumetric study

We determined the partial molar volumes and adiabatic compressibilities of N‐acetyl amino acid amides, N‐acetyl amino acid methylamides, N‐acetyl amino acids, and short oligoglycines as a function of urea concentration. We analyze these data within the framework of a statistical thermodynamic formalism to determine the association constants for the reaction in which urea binds to the glycyl unit and each of the naturally occurring amino acid side chains replacing two waters of hydration. Our determined association constants, k, range from 0.04 to 0.39M. We derive a general equation that links k with changes in free energy, ΔG_tr, accompanying the transfer of functional groups from water to urea. In this equation, ΔG_tr is the sum of a change in the free energy of cavity formation, ΔΔG_C, and the differential free energy of solute–solvent interactions, ΔΔG_I, in urea and water. The observed range of affinity coefficients, k, corresponds to the values of ΔΔG_I ranging from highly favorable to slightly unfavorable. Taken together, our data support a direct interaction model in which urea denatures a protein by concerted action via favorable interactions with a wide range of protein groups. Our derived equation linking k to ΔG_tr suggests that ΔΔG_I and, hence, the net transfer free energy, ΔG_tr, are both strongly influenced by the concentration of a solute used in the experiment. We emphasize the need to exercise caution when two solutes differing in solubility are compared to determine the ΔG_tr contribution of a particular functional group. © 2010 Wiley Periodicals, Inc. Biopolymers 93: 866–879, 2010.     

Recognition of specific and nonspecific DNA by human lactoferrin

The general principles of recognition of nucleic acids by proteins are among the most exciting problems of molecular biology. Human lactoferrin (LF) is a remarkable protein possessing many independent biological functions, including interaction with DNA. In human milk, LF is a major DNase featuring two DNA‐binding sites with different affinities for DNA. The mechanism of DNA recognition by LF was studied here for the first time. Electrophoretic mobility shift assay and fluorescence measurements were used to probe for interactions of the high‐affinity DNA‐binding site of LF with a series of model‐specific and nonspecific DNA ligands, and the structural determinants of DNA recognition by LF were characterized quantitatively. The minimal ligands for this binding site were orthophosphate (K_i = 5 mM), deoxyribose 5'‐phosphate (K_i = 3 mM), and different dNMPs (K_i = 0.56–1.6 mM). LF interacted additionally with 9–12 nucleotides or nucleotide pairs of single‐ and double‐stranded ribo‐ and deoxyribooligonucleotides of different lengths and sequences, mainly through weak additive contacts with internucleoside phosphate groups. Such nonspecific interactions of LF with noncognate single‐ and double‐stranded d(pN)₁₀ provided ~6 to ~7.5 orders of magnitude of the enzyme affinity for any DNA. This corresponds to the Gibbs free energy of binding (ΔG⁰) of ?8.5 to ?10.0 kcal/mol. Formation of specific contacts between the LF and its cognate DNA results in an increase of the DNA affinity for the enzyme by approximately 1 order of magnitude (K_d = 10 nM; ΔG⁰ ≈ ?11.1 kcal/mol). A general function for the LF affinity for nonspecific d(pN)_n of different sequences and lengths was obtained, giving the K_d values comparable with the experimentally measured ones. A thermodynamic model was constructed to describe the interactions of LF with DNA. Copyright © 2013 John Wiley & Sons, Ltd.     

A detailed representation of electrostatic energy in prediction of sequence and pH dependence of protein stability

A molecular mechanics model, previously validated in applications to structure prediction, is shown to reproduce experiment in predictions of protein ionization state, and in predictions of sequence and pH dependence of protein stability. Over a large dataset, 1876 values of ΔΔG of folding, the RMSD is 1.34 kcal/mol. Using an alternative measure of accuracy, either the sign of the calculated ΔΔG agrees with experiment or the absolute value of the deviation is less than 1.0 kcal/mol, 1660 of 1876 data points (88.5%) pass the condition. Relative to models used previously in computer‐aided protein design, the concept, we propose, most responsible for the performance of our model, and for the extensibility to non‐neutral values of pH, is the treatment of electrostatic energy. The electronic structure of the protein is modeled using distributed atomic multipoles. The structured liquid state of the solvent is modeled using a dielectric continuum. A modification to the energetics of the reaction field, induced by the protein in the dielectric continuum, attempts to account for preformed multipoles of solvent water molecules and ions. An adjustable weight (with optimal value.141) applied to the total vacuum energy accounts implicitly for electronic polarization. A threshold distance, beyond which pairwise atomic interactions are neglected, is not used. In searches through subspaces of sequences and conformations, efficiency remains acceptable for useful applications. Proteins 2014; 82:2497–2511. © 2014 Wiley Periodicals, Inc.     

Protein�Cprotein binding affinities by pulse proteolysis: Application to TEM-1/BLIP protein complexes

Efficient methods for quantifying dissociation constants have become increasingly important for high‐throughput mutagenesis studies in the postgenomic era. However, experimentally determining binding affinity is often laborious, requires large amounts of purified protein, and utilizes specialized equipment. Recently, pulse proteolysis has been shown to be a robust and simple method to determine the dissociation constants for a protein–ligand pair based on the increase in thermodynamic stability upon ligand binding. Here, we extend this technique to determine binding affinities for a protein–protein complex involving the β‐lactamase TEM‐1 and various β‐lactamase inhibitor protein (BLIP) mutants. Interaction with BLIP results in an increase in the denaturation curve midpoint, C_m, of TEM‐1, which correlates with the rank order of binding affinities for several BLIP mutants. Hence, pulse proteolysis is a simple, effective method to assay for mutations that modulate binding affinity in protein–protein complexes. From a small set (n = 4) of TEM‐1/BLIP mutant complexes, a linear relationship between energy of stabilization (dissociation constant) and ΔC_m was observed. From this “calibration curve,” accurate dissociation constants for two additional BLIP mutants were calculated directly from proteolysis‐derived ΔC_m values. Therefore, in addition to qualitative information, armed with knowledge of the dissociation constants from the WT protein and a limited number of mutants, accurate quantitation of binding affinities can be determined for additional mutants from pulse proteolysis. Minimal sample requirements and the suitability of impure protein preparations are important advantages that make pulse proteolysis a powerful tool for high‐throughput mutagenesis binding studies.     

Covalent vs. Non‐Covalent Inhibition: Tackling Drug Resistance in EGFR – A Thorough Dynamic Perspective

A persistent challenge in the treatment of non‐small cell lung cancer (NSCLC) with EGFR is the emergence of drug‐resistant caused by somatic mutations. The EGFR L858R/T790 M double mutant (EGFR^DM) was found to be the most alarming variant. Despite the development of a wide range of inhibitors, none of them could inhibit EGFR^DM effectively. Recently, 11h and 45a , have been found to be potent inhibitors against EGFR^DM through two distinctive mechanisms, non‐covalent and covalent binding, respectively. However, the structural and dynamic implications of the two modes of inhibitions remain unexplored. Herein, two molecular dynamics simulation protocols, coupled with free‐energy calculations, were applied to gain insight into the atomistic nature of each binding mode. The comparative analysis confirmed that there is a significant difference in the binding free energy between 11h and 45a (ΔΔG_bind=?21.17 kcal/mol). The main binding force that governs the binding of both inhibitors is vdW, with a higher contribution for 45a . Two residues ARG841 and THR854 were found to have curtailed role in the binding of 45a to EGFR^DM by stabilizing its flexible alcohol chain. The 45a binding to EGFR^DM induces structural rearrangement in the active site to allow easier accessibility of 45a to target residue CYS797. The findings of this work can substantially shed light on new strategies for developing novel classes of covalent and non‐covalent inhibitors with increased specificity and potency.     

Critical biophysical properties in the Pseudomonas aeruginosa efflux gene regulator MexR are targeted by mutations conferring multidrug resistance

The self‐assembling MexA‐MexB‐OprM efflux pump system, encoded by the mexO operon, contributes to facile resistance of Pseudomonas aeruginosa by actively extruding multiple antimicrobials. MexR negatively regulates the mexO operon, comprising two adjacent MexR binding sites, and is as such highly targeted by mutations that confer multidrug resistance (MDR). To understand how MDR mutations impair MexR function, we studied MexR‐wt as well as a selected set of MDR single mutants distant from the proposed DNA‐binding helix. Although DNA affinity and MexA‐MexB‐OprM repression were both drastically impaired in the selected MexR‐MDR mutants, MexR‐wt bound its two binding sites in the mexO with high affinity as a dimer. In the MexR‐MDR mutants, secondary structure content and oligomerization properties were very similar to MexR‐wt despite their lack of DNA binding. Despite this, the MexR‐MDR mutants showed highly varying stabilities compared with MexR‐wt, suggesting disturbed critical interdomain contacts, because mutations in the DNA‐binding domains affected the stability of the dimer region and vice versa. Furthermore, significant ANS binding to MexR‐wt in both free and DNA‐bound states, together with increased ANS binding in all studied mutants, suggest that a hydrophobic cavity in the dimer region already shown to be involved in regulatory binding is enlarged by MDR mutations. Taken together, we propose that the biophysical MexR properties that are targeted by MDR mutations—stability, domain interactions, and internal hydrophobic surfaces—are also critical for the regulation of MexR DNA binding.     

PCA-MutPred: Prediction of Binding Free Energy Change Upon Missense Mutation in Protein-carbohydrate Complexes

Protein-carbohydrate interactions play an important role in several biological processes. The mutation of amino acid residues in carbohydrate-binding proteins may alter the binding affinity, affect the functions and lead to diseases. Elucidating the factors influencing the binding affinity change (ΔΔG) of protein-carbohydrate complexes upon mutation is a challenging task. In this work, we have collected the experimental data for the binding affinity change of 318 unique mutants and related with sequence and structural features of amino acid residues at the mutant sites. We found that accessible surface area, secondary structure, mutation preference, conservation score, hydrophobicity and contact energies are important to understand the binding affinity change upon mutation. We have developed multiple regression equations for predicting the binding affinity change upon mutation and our method showed an average correlation of 0.74 and a mean absolute error of 0.70 kcal/mol between experimental and predicted ΔΔG on a 10-fold cross-validation. Further, we have validated our method using an independent test data set of 124 (62 unique) mutations, which showed a correlation and MAE of 0.79 and 0.56 kcal/mol, respectively. We have developed a web server PCA-MutPred, Protein-CArbohydrate complex Mutation affinity Predictor, for predicting the change in binding affinity of protein–carbohydrate complexes and it is freely accessible at https://web.iitm.ac.in/bioinfo2/pcamutpred. We suggest that the method could be a useful resource for designing protein-carbohydrate complexes with desired affinities.     

Structure‐based design of novel Chlamydomonas reinhardtii D1‐D2 photosynthetic proteins for herbicide monitoring

The D1‐D2 heterodimer in the reaction center core of phototrophs binds the redox plastoquinone cofactors, Q_A and Q_B, the terminal acceptors of the photosynthetic electron transfer chain in the photosystem II (PSII). This complex is the target of the herbicide atrazine, an environmental pollutant competitive inhibitor of Q_B binding, and consequently it represents an excellent biomediator to develop biosensors for pollutant monitoring in ecosystems. In this context, we have undertaken a study of the Chlamydomonas reinhardtii D1‐D2 proteins aimed at designing site directed mutants with increased affinity for atrazine. The three‐dimensional structure of the D1 and D2 proteins from C. reinhardtii has been homology modeled using the crystal structure of the highly homologous Thermosynechococcus elongatus proteins as templates. Mutants of D1 and D2 were then generated in silico and the atrazine binding affinity of the mutant proteins has been calculated to predict mutations able to increase PSII affinity for atrazine. The computational approach has been validated through comparison with available experimental data and production and characterization of one of the predicted mutants. The latter analyses indicated an increase of one order of magnitude of the mutant sensitivity and affinity for atrazine as compared to the control strain. Finally, D1‐D2 heterodimer mutants were designed and selected which, according to our model, increase atrazine binding affinity by up to 20 kcal/mol, representing useful starting points for the development of high affinity biosensors for atrazine.     

Theoretical prediction of the binding free energy for mutants of replication protein A

The replication protein A (RPA) is a heterotrimeric (70, 32, and 14 kDa subunits), single stranded DNA (ssDNA) binding protein required for pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Studies based on deletions and mutations have identified the high affinity ssDNA binding domains in the 70 kDa subunit of RPA, regions A and B. Individually, the domain A and B have a low affinity for ssDNA, while tandems composed of AA, AB, BB, and BA sequences bind the ssDNA with moderate to high affinity. Single and double point mutations on polar residues in the binding domains leads to a reduction in affinity of RPA for ssDNA, in particular when two hydrophilic residues are involved. In view of these results, we performed a study based on molecular dynamics simulation aimed to reproduce the experimental change in binding free energy, ΔΔG, of RPA70 mutants to further elucidate the nature of the protein-ssDNA interaction. The MM-PB(GB)SA methods implemented in Amber10 and the code FoldX were used to estimate the binding free energy. The theoretical and experimental ΔΔG values correlate better when the results are obtained by MM-PBSA calculated on individual trajectories for each mutant. In these conditions, the correlation coefficient between experimental and theoretical ΔΔG reaches a value of 0.95 despite the overestimation of the energy change by one order of magnitude. The decomposition of the MM-GBSA energy per residue allows us to correlate the change of the affinity with the residue polarity and energy contribution to the binding. The method revealed reliable predictions of the change in the affinity in function of mutations, and can be used to identify new mutants with distinct binding properties.     

Intermolecular interactions between DNA and methamphetamine,amphetamine, ecstasy and their major metabolites

In this work, we carried out a theoretical investigation regarding amphetamine-type stimulants, which can cause central nervous system degeneration, interacting with human DNA. These include amphetamine, methamphetamine, 3,4-Methylenedioxymethamphetamine (also known as ecstasy), as well as their main metabolites. The studies were performed through molecular docking and molecular dynamics simulations, where molecular interactions of the receptor–ligand systems, along with their physical–chemical energies, were reported. Our results show that 3,4-Methylenedioxymethamphetamine and 3,4-Dihydroxymethamphetamine (ecstasy) present considerable reactivity with the receptor (DNA), suggesting that these molecules may cause damage due to human-DNA. These results were indicated by free Gibbs change of bind (ΔG_bind) values referring to intermolecular interactions between the drugs and the minor grooves of DNA, which were predominant for all simulations. In addition, it was observed that 3,4-Dihydroxymethamphetamine (ΔG_bind = ?13.15 kcal/mol) presented greater spontaneity in establishing interactions with DNA in comparison to 3,4-Methylenedioxymethamphetamine (ΔG_bind = ?8.61 kcal/mol). Thus, according with the calculations performed our results suggest that the 3,4-Methylenedioxymethamphetamine and 3,4-Dihydroxymethamphetamine have greater probability to provide damage to human DNA fragments.     

Conformational analysis and design of cross-strand disulfides in antiparallel β-sheets

Cross‐strand disulfides bridge two cysteines in a registered pair of antiparallel β‐strands. A nonredundant data set comprising 5025 polypeptides containing 2311 disulfides was used to study cross‐strand disulfides. Seventy‐six cross‐strand disulfides were found of which 75 and 1 occurred at non‐hydrogen‐bonded (NHB) and hydrogen‐bonded (HB) registered pairs, respectively. Conformational analysis and modeling studies demonstrated that disulfide formation at HB pairs necessarily requires an extremely rare and positive χ¹ value for at least one of the cysteine residues. Disulfides at HB positions also have more unfavorable steric repulsion with the main chain. Thirteen pairs of disulfides were introduced in NHB and HB pairs in four model proteins: leucine binding protein (LBP), leucine, isoleucine, valine binding protein (LIVBP), maltose binding protein (MBP), and Top7. All mutants LIVBP T247C V331C showed disulfide formation either on purification, or on treatment with oxidants. Protein stability in both oxidized and reduced states of all mutants was measured. Relative to wild type, LBP and MBP mutants were destabilized with respect to chemical denaturation, although the sole exposed NHB LBP mutant showed an increase of 3.1°C in T _m . All Top7 mutants were characterized for stability through guanidinium thiocyanate chemical denaturation. Both exposed and two of the three buried NHB mutants were appreciably stabilized. All four HB Top7 mutants were destabilized (ΔΔG ⁰ = ?3.3 to ?6.7 kcal/mol). The data demonstrate that introduction of cross‐strand disulfides at exposed NHB pairs is a robust method of improving protein stability. All four exposed Top7 disulfide mutants showed mild redox activity. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Computational protein design suggests that human PCNA‐partner interactions are not optimized for affinity

Increasing the affinity of binding proteins is invaluable for basic and applied biological research. Currently, directed protein evolution experiments are the main approach for generating such proteins through the construction and screening of large mutant libraries. Proliferating cell nuclear antigen (PCNA) is an essential hub protein that interacts with many different partners to tightly regulate DNA replication and repair in all eukaryotes. Here, we used computational design to generate human PCNA mutants with enhanced affinity for several different partners. We identified double mutations in PCNA, outside the main partner binding site, that were predicted to increase PCNA‐partner binding affinities compared to the wild‐type protein by forming additional hydrophobic interactions with conserved residues in the PCNA partners. Affinity increases were experimentally validated with four different PCNA partners, demonstrating that computational design can reveal unexpected regions where affinity enhancements in natural systems are possible. The designed PCNA mutants can be used as a valuable tool for further examination of the regulation of PCNA‐partner interactions during DNA replication and repair both in vitro and in vivo. More broadly, the ability to engineer affinity increases toward several PCNA partners suggests that interaction affinity is not an evolutionarily optimized trait of this system. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Further Study on the Relation of Polyoxin Structure to Chitin Synthetase Inhibition

As a part of studies on the mechanism of action of antibiotics polyoxins, effects of various N-aminoacyl derivatives of polyoxin C and other polyoxins on chitin-UDP acetylglucosaminyl-transferase (EC 2.4.1.16, chitin synthetase) prepared from phytopathogenic fungus Piricularia oryzae were investigated. It was found that they inhibited the enzyme in competition with the substrate UDP-N-acetylglucosamine, Inhibitor constants, Ki, for these polyoxins were determined and the values of binding affinity, ?ΔG_bind of the inhibitors to the enzyme were calculated from the Ki values. In addition, by using these ?ΔG_bind values the values of partial binding affinity, ?Δg for the several atoms and atomic groups or the several moieties contained in the polyoxin J molecule were estimated. From the results obtained, it was concluded that the carbamoylpolyoxamic acid moiety of polyoxins helps to stabilize the polyoxin-enzyme complex through the contributions of its oxygen atom at C?1″, amino group at C?2″, hydroxyl groups at C?3″ and C?4″, aliphatic carbon chain and terminal carbamoyloxy group.

The results obtained by the kinetic investigation using various nucleotides and nucleotide sugars suggested that there was a specific binding site on the enzyme corresponding to the uridine moiety of UDP-N-acetylglucosamine, and that the pyrimidine nucleoside moiety of polyoxins was also bound to this site.     

Thermodynamics calculation of protein–ligand interactions by QM/MM polarizable charge parameters

The calculation of protein–ligand binding free energy (ΔG) is of great importance for virtual screening and drug design. Molecular dynamics (MD) simulation has been an attractive tool to investigate this scientific problem. However, the reliability of such approach is affected by many factors including electrostatic interaction calculation. Here, we present a practical protocol using quantum mechanics/molecular mechanics (QM/MM) calculations to generate polarizable QM protein charge (QMPC). The calculated QMPC of some atoms in binding pockets was obviously different from that calculated by AMBER ff03, which might significantly affect the calculated ΔG. To evaluate the effect, the MD simulations and MM/GBSA calculation with QMPC for 10 protein–ligand complexes, and the simulation results were then compared to those with the AMBER ff03 force field and experimental results. The correlation coefficient between the calculated ΔΔG using MM/GBSA under QMPC and the experimental data is .92, while that with AMBER ff03 force field is .47 for the complexes formed by streptavidin or its mutants and biotin. Moreover, the calculated ΔΔG with QMPC for the complexes formed by ERβ and five ligands is positively related to experimental result with correlation coefficient of .61, while that with AMBER ff03 charge is negatively related to experimental data with correlation coefficient of .42. The detailed analysis shows that the electrostatic polarization introduced by QMPC affects the electrostatic contribution to the binding affinity and thus, leads to better correlation with experimental data. Therefore, this approach should be useful to virtual screening and drug design.     

Experimental and computational analyses of the energetic basis for dual recognition of immunity proteins by colicin endonucleases

Colicin endonucleases (DNases) are bound and inactivated by immunity (Im) proteins. Im proteins are broadly cross-reactive yet specific inhibitors binding cognate and non-cognate DNases with K_d values that vary between 10^− 4 and 10^− 14 M, characteristics that are explained by a ‘dual-recognition’ mechanism. In this work, we addressed for the first time the energetics of Im protein recognition by colicin DNases through a combination of E9 DNase alanine scanning and double-mutant cycles (DMCs) coupled with kinetic and calorimetric analyses of cognate Im9 and non-cognate Im2 binding, as well as computational analysis of alanine scanning and DMC data. We show that differential ΔΔGs observed for four E9 DNase residues cumulatively distinguish cognate Im9 association from non-cognate Im2 association. E9 DNase Phe86 is the primary specificity hotspot residue in the centre of the interface, which is coordinated by conserved and variable hotspot residues of the cognate Im protein. Experimental DMC analysis reveals that only modest coupling energies to Im9 residues are observed, in agreement with calculated DMCs using the program ROSETTA and consistent with the largely hydrophobic nature of E9 DNase-Im9 specificity contacts. Computed values for the 12 E9 DNase alanine mutants showed reasonable agreement with experimental ΔΔG data, particularly for interactions not mediated by interfacial water molecules. ΔΔG predictions for residues that contact buried water molecules calculated using solvated rotamer models met with mixed success; however, we were able to predict with a high degree of accuracy the location and energetic contribution of one such contact. Our study highlights how colicin DNases are able to utilise both conserved and variable amino acids to distinguish cognate from non-cognate Im proteins, with the energetic contributions of the conserved residues modulated by neighbouring specificity sites.     

The dataset for protein–RNA binding affinity

We have developed a non‐redundant protein–RNA binding benchmark dataset derived from the available protein–RNA structures in the Protein Database Bank. It consists of 73 complexes with measured binding affinity. The experimental conditions (pH and temperature) for binding affinity measurements are also listed in our dataset. This binding affinity dataset can be used to compare and develop protein–RNA scoring functions. The predicted binding free energy of the 73 complexes from three available scoring functions for protein–RNA docking has a low correlation with the binding Gibbs free energy calculated from K_d. © 2013 The Protein Society