Computational alanine scanning mutagenesis--an improved methodological approach

Alanine scanning mutagenesis of protein-protein interfacial residues can be applied to a wide variety of protein complexes to understand the structural and energetic characteristics of the hot-spots. Binding free energies have been estimated with reasonable accuracy with empirical methods, such as Molecular Mechanics/Poisson-Boltzmann surface area (MM-PBSA), and with more rigorous computational approaches like Free Energy Perturbation (FEP) and Thermodynamic Integration (TI). The main objective of this work is the development of an improved methodological approach, with less computational cost, that predicts accurately differences in binding free energies between the wild-type and alanine mutated complexes (DeltaDeltaG(binding)). The method was applied to three complexes, and a mean unsigned error of 0.80 kcal/mol was obtained in a set of 46 mutations. The computational method presented here achieved an overall success rate of 80% and an 82% success rate in residues for which alanine mutation causes an increase in the binding free energy > 2.0 kcal/mol (warm- and hot-spots). This fully atomistic computational methodological approach consists in a computational Molecular Dynamics simulation protocol performed in a continuum medium using the Generalized Born model. A set of three different internal dielectric constants, to mimic the different degree of relaxation of the interface when different types of amino acids are mutated for alanine, have to be used for the proteins, depending on the type of amino acid that is mutated. This method permits a systematic scanning mutagenesis of protein-protein interfaces and it is capable of anticipating the experimental results of mutagenesis, thus guiding new experimental investigations.     

Hot spot computational identification: Application to the complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL‐10

The definition and comprehension of the hot spots in an interface is a subject of primary interest for a variety of fields, including structure‐based drug design. Therefore, to achieve an alanine mutagenesis computational approach that is at the same time accurate and predictive, capable of reproducing the experimental mutagenesis values is a major challenge in the computational biochemistry field. Antibody/protein antigen complexes provide one of the greatest models to study protein–protein recognition process because they have three fundamentally features: specificity, high complementary association and a small epitope restricted to the diminutive complementary determining regions (CDR) region, while the remainder of the antibody is largely invariant. Thus, we apply a computational mutational methodological approach to the study of the antigen–antibody complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL‐10. A critical evaluation that focuses essentially on the limitations and advantages between different computational methods for hot spot determination, as well as between experimental and computational methodological approaches, is presented. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007     

A pH‐dependent computational approach to the effect of mutations on protein stability

This article describes a novel software implementation for high‐throughput scanning mutagenesis with a focus on protein stability. The approach combines molecular mechanics calculations with calculations of protein ionization and a Gaussian‐chain model of electrostatic interactions in unfolded state. Comprehensive testing demonstrates a state‐of‐the‐art accuracy for predicted free energy differences on single, double, and triple mutations with a correlation coefficient R above 0.7, which takes about 1.5 min per mutation on a single CPU. Unlike most of existing in silico methods for fast mutagenesis, the stability changes are reported as a continuous function of solution pH for wide pH intervals. We also propose a novel in silico strategy for searching stabilized protein variants that is based on combinatorial scanning mutagenesis using representative amino acid types. Our in silico predictions are in excellent agreement with the hyper‐stabilized variants of mesophilic cold shock protein found using the Proside method of direct evolution. © 2016 Wiley Periodicals, Inc.     

Assessment of free energy predictors for ligand binding to a methyllysine histone code reader

Methyllysine histone code readers constitute a new promising group of potential drug targets. For instance, L3MBTL1, a malignant brain tumor (MBT) protein, selectively binds mono- and di-methyllysine epigenetic marks (KMe, KMe(2) ) that eventually results in the negative regulation of multiple genes through the E2F/Rb oncogenic pathway. There is a pressing need in potent and selective small-molecule probes that would enable further target validation and might become therapeutic leads. Such an endeavor would require efficient tools to assess the free energy of protein-ligand binding. However, due to an unparalleled function of the MBT binding pocket (i.e., selective binding to KMe/KMe(2) ) and because of its distinctive structure representing a small aromatic "cage," an accurate assessment of its binding affinity to a ligand appears to be a challenging task. Here, we report a comparative analysis of computationally affordable affinity predictors applied to a set of seven small-molecule ligands interacting with L3MBTL1. The analysis deals with novel ligands and targets, but applies widespread computational approaches and intuitive comparison metrics that makes this study compatible with and incremental to earlier large scale accounts on the efficiency of affinity predictors. Ultimately, this study has revealed three top performers, far ahead of the other techniques, including two scoring functions, PMF04 and PLP, along with a simulation-based method MM-PB/SA. We discuss why some methods may perform better than others on this target class, the limits of their application, as well as how the efficiency of the most CPU-demanding techniques could be optimized.     

Interaction identification of Zif268 and TATAZF proteins with GC‐/AT‐rich DNA sequence: A theoretical study

Molecular dynamics (MD) simulations for Zif268 (a zinc‐finger‐protein binding specifically to the GC‐rich DNA)‐d(A₁G₂C₃G₄T₅G₆G₇G₈C₉A₁₀C₁₁)₂ and TATA_ZF (a zinc‐finger‐protein recognizing the AT‐rich DNA)‐d(A₁C₂G₃C₄T₅A₆T₇A₈A₉A₁₀A₁₁G₁₂G₁₃)₂ complexes have been performed for investigating the DNA binding affinities and specific recognitions of zinc fingers to GC‐rich and AT‐rich DNA sequences. The binding free energies for the two systems have been further analyzed by using the molecular mechanics Poisson‐Boltzmann surface area (MM‐PBSA) method. The calculations of the binding free energies reveal that the affinity energy of Zif268‐DNA complex is larger than that of TATA_ZF‐DNA one. The affinity between the zinc‐finger‐protein and DNA is mainly driven by more favorable van‐der‐Waals and nonpolar/solvation interactions in both complexes. However, the affinity energy difference of the two binding systems is mainly caused by the difference of van‐der‐Waals interactions and entropy components. The decomposition analysis of MM‐PBSA free energies on each residue of the proteins predicts that the interactions between the residues with the positive charges and DNA favor the binding process; while the interactions between the residues with the negative charges and DNA behave in the opposite way. The interhydrogen‐bonds at the protein‐DNA interface and the induced intrafinger hydrogen bonds between the residues of protein for the Zif268‐DNA complex have been identified at some key contact sites. However, only the interhydrogen‐bonds between the residues of protein and DNA for TATA_ZF‐DNA complex have been found. The interactions of hydrogen‐bonds, electrostatistics and van‐der‐Waals type at some new contact sites have been identified. Moreover, the recognition characteristics of the two studied zinc‐finger‐proteins have also been discussed. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011     

Energy exchange network of inter‐residue interactions within a thermally fluctuating protein molecule: A computational study

Protein function is regulated not only by the structure but also by physical dynamics and thermal fluctuations. We have developed the computer program, CURrent calculation for proteins (CURP), for the flow analysis of physical quantities within thermally fluctuating protein media. The CURP program was used to calculate the energy flow within the third PDZ domain of the neuronal protein PSD‐95, and the results were used to illustrate the energy exchange network of inter‐residue interactions based on atomistic molecular dynamics simulations. The removal of the α3 helix is known to decrease ligand affinity by 21‐fold without changing the overall protein structure; nevertheless, we demonstrated that the helix constitutes an essential part of the network graph. © 2015 Wiley Periodicals, Inc.     

Finding the transition state without initial guess: the growing string method for Newton trajectory to isomerization and enantiomerization reaction of alanine dipeptide and poly(15)alanine

We report a new, high-dimensional application of a method for finding a transition state (TS) between a reactant and a product on the potential energy surface: the search of a growing string along a reaction path defined by any Newton trajectory in combination with the Berny method (Quapp, J Chem Phys (2005), 122, 174106; we have provided this algorithm on a web page). Two given minima are connected by a one-dimensional, but usually curvilinear reaction coordinate. It leads to the TS region. The application of the method to alanine dipeptide finds the TS of the isomerisation C(7 ax) --> C(5), some TSs of the enantiomerisation of C(7 ax) from L-form to quasi-D-form, and it finds the TS region of a transition of a partly unfolded, bent structure which turns back into a mainly alpha-helix in the Ac(Ala)(15)NHMe polyalanine (all at the quantum mechanical level B3LYP/6-31G: the growing string calculation is interfaced with the Gaussian03 package). The formation or dissolvation of some alpha- or 3(10)-hydrogen bonds of the helix are discussed along the TS pathway, as well as the case of an enantiomer at the central residue of the helix.     

A highly efficient hybrid method for calculating the hydration free energy of a protein

We develop a new method for calculating the hydration free energy (HFE) of a protein with any net charge. The polar part of the energetic component in the HFE is expressed as a linear combination of four geometric measures (GMs) of the protein structure and the generalized Born (GB) energy plus a constant. The other constituents in the HFE are expressed as linear combinations of the four GMs. The coefficients (including the constant) in the linear combinations are determined using the three‐dimensional reference interaction site model (3D‐RISM) theory applied to sufficiently many protein structures. Once the coefficients are determined, the HFE and its constituents of any other protein structure are obtained simply by calculating the four GMs and GB energy. Our method and the 3D‐RISM theory give perfectly correlated results. Nevertheless, the computation time required in our method is over four orders of magnitude shorter.     

Computation of the binding affinities of catechol‐O‐methyltransferase inhibitors: Multisubstate relative free energy calculations

Alchemical free energy simulations are amongst the most accurate techniques for the computation of the free energy changes associated with noncovalent protein–ligand interactions. A procedure is presented to estimate the relative binding free energies of several ligands to the same protein target where multiple, low‐energy configurational substates might coexist, as opposed to one unique structure. The contributions of all individual substates were estimated, explicitly, with the free energy perturbation method, and combined in a rigorous fashion to compute the overall relative binding free energies and dissociation constants. It is shown that, unless the most stable bound forms are known a priori, inaccurate results may be obtained if the contributions of multiple substates are ignored. The method was applied to study the complex formed between human catechol‐O‐methyltransferase and BIA 9‐1067, a newly developed tight‐binding inhibitor that is currently under clinical evaluation for the therapy of Parkinson's disease. Our results reveal an exceptionally high‐binding affinity (K_d in subpicomolar range) and provide insightful clues on the interactions and mechanism of inhibition. The inhibitor is, itself, a slowly reacting substrate of the target enzyme and is released from the complex in the form of O‐methylated product. By comparing the experimental catalytic rate (k_cat) and the estimated dissociation rate (k_off) constants of the enzyme‐inhibitor complex, one can conclude that the observed inhibition potency (K_i) is primarily dependent on the catalytic rate constant of the inhibitor's O‐methylation, rather than the rate constant of dissociation of the complex. © 2012 Wiley Periodicals, Inc.     

Free energies of solvation in the context of protein folding: Implications for implicit and explicit solvent models

Implicit solvent models for biomolecular simulations have been developed to use in place of more expensive explicit models; however, these models make many assumptions and approximations that are likely to affect accuracy. Here, the changes in free energies of solvation upon folding of several fast folding proteins are calculated from previously run μs–ms simulations with a number of implicit solvent models and compared to the values needed to be consistent with the explicit solvent model used in the simulations. In the majority of cases, there is a significant and substantial difference between the values calculated from the two approaches that is robust to the details of the calculations. These differences could only be remedied by selecting values for the model parameters—the internal dielectric constant for the polar term and the surface tension coefficient for the nonpolar term—that were system‐specific or physically unrealistic. We discuss the potential implications of our findings for both implicit and explicit solvent simulations. © 2015 Wiley Periodicals, Inc.     

Computational methods for the study of enzymic reaction mechanisms III: a perturbation plus QM/MM approach for calculating relative free energies of protonation

We describe a coupling parameter, that is, perturbation, approach to effectively create and annihilate atoms in the quantum mechanical Hamiltonian within the closed shell restricted Hartree-Fock formalism. This perturbed quantum mechanical atom (PQA) method is combined with molecular mechanics (MM) methods (PQA/MM) within a molecular dynamics simulation, to model the protein environment (MM region) effects that also make a contribution to the overall free energy change. Using the semiempirical PM3 method to model the QM region, the application of this PQA/MM method is illustrated by calculation of the relative protonation free energy of the conserved OD2 (Asp27) and the N5 (dihydrofolate) proton acceptor sites in the active site of Escherichia coli dihydrofolate reductase (DHFR) with the bound nicotinamide adenine dinucleotide phosphate (NADPH) cofactor. For a number of choices for the QM region, the relative protonation free energy was calculated as the sum of contributions from the QM region and the interaction between the QM and MM regions via the thermodynamic integration (TI) method. The results demonstrate the importance of including the whole substrate molecule in the QM region, and the overall protein (MM) environment in determining the relative stabilities of protonation sites in the enzyme active site. The PQA/MM free energies obtained by TI were also compared with those estimated by a less computationally demanding nonperturbative method based on the linear response approximation (LRA). For some choices of QM region, the total free energies calculated using the LRA method were in very close agreement with the PQA/MM values. However, the QM and QM/MM component free energies were found to differ significantly between the two methods.     

Development and validation of a high‐performance liquid chromatography method for the quantification of talazoparib in rat plasma: Application to plasma protein binding studies

A sensitive and selective RP‐HPLC method has been developed and validated for the quantification of a highly potent poly ADP ribose polymerase inhibitor talazoparib (TZP) in rat plasma. Chromatographic separation was performed with isocratic elution method. Absorbance for TZP was measured with a UV detector (SPD‐20A UV–vis) at a λ_max of 227 nm. Protein precipitation was used to extract the drug from plasma samples using methanol–acetonitrile (65:35) as the precipitating solvent. The method proved to be sensitive and reproducible over a 100–2000 ng/mL linearity range with a lower limit of quantification (LLQC) of 100 ng/mL. TZP recovery was found to be >85%. Following analytical method development and validation, it was successfully employed to determine the plasma protein binding of TZP. TZP has a high level of protein binding in rat plasma (95.76 ± 0.38%) as determined by dialysis method.     

The role of protein “Stability patches” in molecular recognition: A case study of the human growth hormone‐receptor complex

Dynamic characteristics of protein surfaces are among the factors determining their functional properties, including their potential participation in protein‐protein interactions. The presence of clusters of static residues—“stability patches” (SPs)—is a characteristic of protein surfaces involved in intermolecular recognition. The mechanism, by with SPs facilitate molecular recognition, however, remains unclear. Analyzing the surface dynamic properties of the growth hormone and of its high‐affinity variant we demonstrated that reshaping of the SPs landscape may be among the factors accountable for the improved affinity of this variant to the receptor. We hypothesized that SPs facilitate molecular recognition by moderating the conformational entropy of the unbound state, diminishing enthalpy–entropy compensation upon binding, and by augmenting the favorable entropy of desolvation. SPs mapping emerges as a valuable tool for investigating the structural basis of the stability of protein complexes and for rationalizing experimental approaches, such as affinity maturation, aimed at improving it. © 2015 Wiley Periodicals, Inc.     

Simultaneous construction of a polyether backbone and a variety of keto side chains by three‐component polycondensation: An improved method for the use of a variety of silyl enol ethers

For the synthesis of polyethers with a variety of keto side chains in a one‐step reaction, the three‐component polycondensation of dialdehydes, diol disilyl ethers, and silyl enol ethers of ketones was investigated. The method of monomer addition strongly affected the molecular weight of polymers and was optimized to yield high molecular weight polymers by model reactions. A variety of dialdehydes, diol disilyl ethers, and silyl enol ethers were polymerized in the presence of a catalytic amount of triphenylmethyl (trityl) perchlorate in CH₂Cl₂ at −78 °C according to the method of monomer addition. This polymer synthesis was unusual in that it concurrently constructed both the polyether backbone and the keto side chains from three starting compounds. © 2000 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 38: 179–188, 2000     

A highly efficient and sensitive LC‐MS/MS method for the determination of afatinib in human plasma: application to a metabolic stability study

Afatinib (AFT) is a new tyrosine kinase inhibitor approved for the treatment of nonsmall cell lung cancer. In the present study, a simple, specific, rapid and sensitive liquid chromatography tandem mass‐spectrometric method for the quantification of AFT in human plasma, was developed and validated. Chromatographic separation of the analytes was accomplished on a reversed‐phase Luna^®‐PFP 100 Å column (50 × 2.0 mm; 3.0 μm) maintained at ambient temperature. Isocratic elution was carried out using acetonitrile–water (40:60, v/v) containing 10 mm ammonium formate buffer (pH 4.5) adjusted with formic acid at a flow rate of 0.4 mL min^?1. The analytes were monitored by electrospray ionization in positive ion multiple reaction monitoring mode. The method yields a linear calibration plot (r² = 0.9997) from a quantification range of 0.5–500 ng mL^?1 with the lower limit of quantification and lower limit of detection of 1.29 and 0.42 ng mL^?1, respectively. The intra‐ and inter‐day precision and accuracy were estimated and found to be in the ranges of 1.53–4.11% for precision and ?2.80–0.38% for accuracy. Finally, quantification of afatinib in a metabolic stability study in rat liver microsomes was achieved through the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.