RosettaDDGPrediction for high‐throughput mutational scans: From stability to binding

Reliable prediction of free energy changes upon amino acid substitutions (ΔΔGs) is crucial to investigate their impact on protein stability and protein–protein interaction. Advances in experimental mutational scans allow high‐throughput studies thanks to multiplex techniques. On the other hand, genomics initiatives provide a large amount of data on disease‐related variants that can benefit from analyses with structure‐based methods. Therefore, the computational field should keep the same pace and provide new tools for fast and accurate high‐throughput ΔΔG calculations. In this context, the Rosetta modeling suite implements effective approaches to predict folding/unfolding ΔΔGs in a protein monomer upon amino acid substitutions and calculate the changes in binding free energy in protein complexes. However, their application can be challenging to users without extensive experience with Rosetta. Furthermore, Rosetta protocols for ΔΔG prediction are designed considering one variant at a time, making the setup of high‐throughput screenings cumbersome. For these reasons, we devised RosettaDDGPrediction, a customizable Python wrapper designed to run free energy calculations on a set of amino acid substitutions using Rosetta protocols with little intervention from the user. Moreover, RosettaDDGPrediction assists with checking completed runs and aggregates raw data for multiple variants, as well as generates publication‐ready graphics. We showed the potential of the tool in four case studies, including variants of uncertain significance in childhood cancer, proteins with known experimental unfolding ΔΔGs values, interactions between target proteins and disordered motifs, and phosphomimetics. RosettaDDGPrediction is available, free of charge and under GNU General Public License v3.0, at https://github.com/ELELAB/RosettaDDGPrediction.     

Investigating the linkage between disease‐causing amino acid variants and their effect on protein stability and binding

Single amino acid variations (SAV) occurring in human population result in natural differences between individuals or cause diseases. It is well understood that the molecular effect of SAV can be manifested as changes of the wild type characteristics of the corresponding protein, among which are the protein stability and protein interactions. Typically the effect of SAV on protein stability and interactions was assessed via the changes of the wild type folding and binding free energies. However, in terms of SAV affecting protein functionally and disease susceptibility, one wants to know to what extend the wild type function is perturbed by the SAV. Here it is demonstrated that relative, rather than the absolute, change of the folding and binding free energy serves as a good indicator for SAV association with disease. Using HumVar as a source for disease‐causing SAV and experimentally determined free energy changes from ProTherm and SKEMPI databases, correlation coefficients (CC) between the disease index and relative folding and binding probability indexes, respectively, was achieved. The obtained CCs demonstrated the applicability of the proposed approach and it served as good indicator for SAV association with disease. Proteins 2016; 84:232–239. © 2015 Wiley Periodicals, Inc.     

Insights into the binding mode of sulphamates and sulphamides to hCA II: crystallographic studies and binding free energy calculations

Sulphamate and sulphamide derivatives have been largely investigated as carbonic anhydrase inhibitors (CAIs) by means of different experimental techniques. However, the structural determinants responsible for their different binding mode to the enzyme active site were not clearly defined so far. In this paper, we report the X-ray crystal structure of hCA II in complex with a sulphamate inhibitor incorporating a nitroimidazole moiety. The comparison with the structure of hCA II in complex with its sulphamide analogue revealed that the two inhibitors adopt a completely different binding mode within the hCA II active site. Starting from these results, we performed a theoretical study on sulphamate and sulphamide derivatives, demonstrating that electrostatic interactions with residues within the enzyme active site play a key role in determining their binding conformation. These findings open new perspectives in the design of effective CAIs using the sulphamate and sulphamide zinc binding groups as lead compounds.     

Computational analysis of binding of P1 variants to trypsin

The binding of P1 variants of bovine pancreatic trypsin inhibitor (BPTI) to trypsin has been investigated by means of molecular dynamics simulations. The specific interaction formed between the amino acid at the primary binding (P1) position of the binding loop of BPTI and the specificity pocket of trypsin was estimated by use of the linear interaction energy (LIE) method. Calculations for 13 of the naturally occurring amino acids at the P1 position were carried out, and the results obtained were found to correlate well with the experimental binding free energies. The LIE calculations rank the majority of the 13 variants correctly according to the experimental association energies and the mean error between calculated and experimental binding free energies is only 0.38 kcal/mole, excluding the Glu and Asp variants, which are associated with some uncertainties regarding protonation and the possible presence of counter-ions. The three-dimensional structures of the complex with three of the P1 variants (Asn, Tyr, and Ser) included in this study have not at present been solved by any experimental techniques and, therefore, were modeled on the basis of experimental data from P1 variants of similar size. Average structures were calculated from the MD simulations, from which specific interactions explaining the broad variation in association energies were identified. The present study also shows that explicit treatment of the complex water-mediated hydrogen bonding network at the protein-protein interface is of crucial importance for obtaining reliable binding free energies. The successful reproduction of relative binding energies shows that this type of methodology can be very useful as an aid in rational design and redesign of biologically active macromolecules.     

Free energy calculations of ALS‐causing SOD1 mutants reveal common perturbations to stability and dynamics along the maturation pathway

With over 150 heritable mutations identified as disease‐causative, superoxide dismutase 1 (SOD1) has been a main target of amyotrophic lateral sclerosis (ALS) research and therapeutic efforts. However, recent evidence has suggested that neither loss of function nor protein aggregation is responsible for promoting neurotoxicity. Furthermore, there is no clear pattern to the nature or the location of these mutations that could suggest a molecular mechanism behind SOD1‐linked ALS. Here, we utilize reliable and accurate computational techniques to predict the perturbations of 10 such mutations to the free energy changes of SOD1 as it matures from apo monomer to metallated dimer. We find that the free energy perturbations caused by these mutations strongly depend on maturational progress, indicating the need for state‐specific therapeutic targeting. We also find that many mutations exhibit similar patterns of perturbation to native and non‐native maturation, indicating strong thermodynamic coupling between the dynamics at various sites of maturation within SOD1. These results suggest the presence of an allosteric network in SOD1 which is vulnerable to disruption by these mutations. Analysis of these perturbations may contribute to uncovering a unifying molecular mechanism which explains SOD1‐linked ALS and help to guide future therapeutic efforts.     

ATLAS: A database linking binding affinities with structures for wild‐type and mutant TCR‐pMHC complexes

The ATLAS (Altered TCR Ligand Affinities and Structures) database ( https://zlab.umassmed.edu/atlas/web /) is a manually curated repository containing the binding affinities for wild‐type and mutant T cell receptors (TCRs) and their antigens, peptides presented by the major histocompatibility complex (pMHC). The database links experimentally measured binding affinities with the corresponding three dimensional (3D) structures for TCR‐pMHC complexes. The user can browse and search affinities, structures, and experimental details for TCRs, peptides, and MHCs of interest. We expect this database to facilitate the development of next‐generation protein design algorithms targeting TCR‐pMHC interactions. ATLAS can be easily parsed using modeling software that builds protein structures for training and testing. As an example, we provide structural models for all mutant TCRs in ATLAS, built using the Rosetta program. Utilizing these structures, we report a correlation of 0.63 between experimentally measured changes in binding energies and our predicted changes. Proteins 2017; 85:908–916. © 2016 Wiley Periodicals, Inc.     

Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes

Absolute binding free energy calculations and free energy decompositions are presented for the protein-protein complexes H-Ras/C-Raf1 and H-Ras/RalGDS. Ras is a central switch in the regulation of cell proliferation and differentiation. In our study, we investigate the capability of the molecular mechanics (MM)-generalized Born surface area (GBSA) approach to estimate absolute binding free energies for the protein-protein complexes. Averaging gas-phase energies, solvation free energies, and entropic contributions over snapshots extracted from trajectories of the unbound proteins and the complexes, calculated binding free energies (Ras-Raf: -15.0(+/-6.3)kcal mol(-1); Ras-RalGDS: -19.5(+/-5.9)kcal mol(-1)) are in fair agreement with experimentally determined values (-9.6 kcal mol(-1); -8.4 kcal mol(-1)), if appropriate ionic strength is taken into account. Structural determinants of the binding affinity of Ras-Raf and Ras-RalGDS are identified by means of free energy decomposition. For the first time, computationally inexpensive generalized Born (GB) calculations are applied in this context to partition solvation free energies along with gas-phase energies between residues of both binding partners. For selected residues, in addition, entropic contributions are estimated by classical statistical mechanics. Comparison of the decomposition results with experimentally determined binding free energy differences for alanine mutants of interface residues yielded correlations with r(2)=0.55 and 0.46 for Ras-Raf and Ras-RalGDS, respectively. Extension of the decomposition reveals residues as far apart as 25A from the binding epitope that can contribute significantly to binding free energy. These "hotspots" are found to show large atomic fluctuations in the unbound proteins, indicating that they reside in structurally less stable regions. Furthermore, hotspot residues experience a significantly larger-than-average decrease in local fluctuations upon complex formation. Finally, by calculating a pair-wise decomposition of interactions, interaction pathways originating in the binding epitope of Raf are found that protrude through the protein structure towards the loop L1. This explains the finding of a conformational change in this region upon complex formation with Ras, and it may trigger a larger structural change in Raf, which is considered to be necessary for activation of the effector by Ras.     

Ferric uptake regulator protein: binding free energy calculations and per-residue free energy decomposition

Iron homeostasis is, in many bacterial species, mediated by the ferric uptake regulator (Fur). A regulatory site able to bind iron to activate Fur for DNA binding has been described, and a structural zinc site essential for the dimerization has also been proposed. They have been localized and named site 1 and site 2, respectively, from the crystal structure of a zinc-substituted Pseudomonas aeruginosa Fur (PA-Fur). Notwithstanding the studies on Fur proteins from various species, both the precise site of iron binding and the effect on DNA binding affinity are still controversial. These issues were investigated here by molecular dynamics simulations and free energy calculations. Simulations were performed for eight molecular systems represented by the three forms of Fur, that is, apo Fur, metal-substituted Fur, and Fur complexed with DNA. Because of the lack of a Fur-DNA complex crystal structure, the recently published model based on mass spectrometry experiments on Escherichia coli Fur (EC-Fur), and the crystal structure of PA-Fur, was used, after adjustment to adopt a symmetric conformation. The simulation results suggest that the formerly proposed site 2 is, in fact, the regulatory iron-sensing site. The calculations also predict that Fe(2+) at site 2 is hexacoordinated having an octahedral environment with only nitrogen and oxygen atoms, which is in accordance with previous spectroscopic characterizations. Energy decomposition pinpoints H87 as an additional amino acid that defines the regulatory metal site. Finally, free energy decomposition analysis reveals a number of amino acids potentially important in dimerization and in DNA binding.     

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     

Computation of entropy contribution to protein-ligand binding free energy

The entropy contribution ΔS to protein-ligand binding free energy is studied for nine protein-lipid complexes. The entropy effect from the loss of the translational/rotational degrees of freedom (ΔS _tr) is calculated using the ideal gas approach. The change in the vibrational entropy (ΔS _vib) is calculated using the effective quantum oscillator approach with frequencies derived from the coordinate covariance matrix, so the inharmonic effects are taken into account. The change in the entropy of solvation (ΔS _solv) is considered using the binomial cell model (developed by the authors) for the hydrophobic effect. The entropy contribution from loss of conformations that are available for the free ligand (ΔS _conf) is also estimated. It is revealed that the negative in view of binding term ΔS _tr is only partly compensated by increasing of ΔS _vib, so T(ΔS _tr + ΔS _vib + ΔS _conf) < 0 for all complexes under investigation, but taking into account ΔS _solv leads to significantly increased ΔS. For all complexes except biotin-streptavidin, the results are found to be in reasonable agreement with experimental data. Published in Russian in Biokhimiya, 2007, Vol. 72, No. 7, pp. 963–973.     

The ubiquitin domain superfold: structure-based sequence alignments and characterization of binding epitopes

Ubiquitin-like domains are present, apart from ubiquitin-like proteins themselves, in many multidomain proteins involved in different signal transduction processes. The sequence conservation for all ubiquitin superfold family members is rather poor, even between subfamily members, leading to mistakes in sequence alignments using conventional sequence alignment methods. However, a correct alignment is essential, especially for in silico methods that predict binding partners on the basis of sequence and structure. In this study, using 3D-structural information we have generated and manually corrected sequence alignments for proteins of the five ubiquitin superfold subfamilies. On the basis of this alignment, we suggest domains for which structural information will be useful to allow homology modelling. In addition, we have analysed the energetic and electrostatic properties of ubiquitin-like domains in complex with various functional binding proteins using the protein design algorithm FoldX. On the basis of an in silico alanine-scanning mutagenesis, we provide a detailed binding epitope mapping of the hotspots of the ubiquitin domain fold, involved in the interaction with different domains and proteins. Finally, we provide a consensus fingerprint sequence that identifies all sequences described to belong to the ubiquitin superfold family. It is possible that the method that we describe may be applied to other domain families sharing a similar fold but having low levels of sequence homology.     

On the calculation of binding free energies using continuum methods: Application to MHC class I protein-peptide interactions

This paper describes a methodology to calculate the binding free energy (ΔG) of a protein-ligand complex using a continuum model of the solvent. A formal thermodynamic cycle is used to decompose the binding free energy into electrostatic and non-electrostatic contributions. In this cycle, the reactants are discharged in water, associated as purely nonpolar entities, and the final complex is then recharged. The total electrostatic free energies of the protein, the ligand, and the complex in water are calculated with the finite difference Poisson-Boltzmann (FDPB) method. The nonpolar (hydrophobic) binding free energy is calculated using a free energy-surface area relationship, with a single alkane/water surface tension coefficient (γ_aw). The loss in backbone and side-chain configurational entropy upon binding is estimated and added to the electrostatic and the nonpolar components of ΔG. The methodology is applied to the binding of the murine MHC class I protein H-2K^b with three distinct peptides, and to the human MHC class I protein HLA-A2 in complex with five different peptides. Despite significant differences in the amino acid sequences of the different peptides, the experimental binding free energy differences (ΔΔG_exp) are quite small (<0.3 and <2.7 kcal/mol for the H-2K^b and HLA-A2 complexes, respectively). For each protein, the calculations are successful in reproducing a fairly small range of values for ΔΔG_calc (<4.4 and <5.2 kcal/mol, respectively) although the relative peptide binding affinities of H-2K^b and HLA-A2 are not reproduced. For all protein-peptide complexes that were treated, it was found that electrostatic interactions oppose binding whereas nonpolar interactions drive complex formation. The two types of interactions appear to be correlated in that larger nonpolar contributions to binding are generally opposed by increased electrostatic contributions favoring dissociation. The factors that drive the binding of peptides to MHC proteins are discussed in light of our results.     

From coarse-grain to all-atom: toward multiscale analysis of protein landscapes

Multiscale methods are becoming increasingly promising as a way to characterize the dynamics of large protein systems on biologically relevant time-scales. The underlying assumption in multiscale simulations is that it is possible to move reliably between different resolutions. We present a method that efficiently generates realistic all-atom protein structures starting from the C(alpha) atom positions, as obtained for instance from extensive coarse-grain simulations. The method, a reconstruction algorithm for coarse-grain structures (RACOGS), is validated by reconstructing ensembles of coarse-grain structures obtained during folding simulations of the proteins src-SH3 and S6. The results show that RACOGS consistently produces low energy, all-atom structures. A comparison of the free energy landscapes calculated using the coarse-grain structures versus the all-atom structures shows good correspondence and little distortion in the protein folding landscape.     

Trifluoperazine regulation of calmodulin binding to Fas: a computational study

Death-inducing signaling complex (DISC) formation is a critical step in Fas-mediated signaling for apoptosis. Previous experiments have demonstrated that the calmodulin (CaM) antagonist, trifluoperazine (TFP) regulates CaM-Fas binding and affects Fas-mediated DISC formation. In this study, we investigated the anti-cooperative characteristics of TFP binding to CaM and the effect of TFP on the CaM-Fas interaction from both structural and thermodynamic perspectives using combined molecular dynamics simulations and binding free energy analyses. We studied the interactions of different numbers of TFP molecules with CaM and explored the effects of the resulting conformational changes in CaM on CaM-Fas binding. Results from these analyses showed that the number of TFP molecules bound to CaM directly influenced α-helix formation and hydrogen bond occupancy within the α-helices of CaM, contributing to the conformational and motion changes in CaM. These changes affected CaM binding to Fas, resulting in secondary structural changes in Fas and conformational and motion changes of Fas in CaM-Fas complexes, potentially perturbing the recruitment of Fas-associated death domain for DISC formation. The computational results from this study reveal the structural and molecular mechanisms that underlie the role of the CaM antagonist, TFP, in regulation of CaM-Fas binding and Fas-mediated DISC formation in a concentration-dependent manner.     

Molecular mechanism study of several inhibitors binding to BRD9 bromodomain based on molecular simulations

Bromodomain-containing protein 9 (BRD9) has been employed as a potential target for anticancer drugs in recent years. In this work, molecular docking, molecular dynamics (MD) simulations, binding free energy calculations, and per residue energy decomposition approaches were performed to elucidate the different binding modes between four pyridinone-like scaffold inhibitors and BRD9 bromodomain. Analysis results indicate that non-polar contribution mainly deriving from van der Waals energy is a critical impact on binding affinity of inhibitors against BRD9. Some key residues Phe44, Phe47, Val49, and Ile53 (at ZA loop) enhance the binding energy of inhibitors in BRD9 by means of providing hydrophobic interactions. Moreover, it is observed that BRD9 is anchored by the formation of a stable hydrogen bond between the carbonyl of the inhibitors and the residue Asn100 (at BC loop), and a strong π–π stacking interaction formed between the residue Tyr106 (at BC loop) and the inhibitors. The existence of dimethoxyphenyl structure and the aromatic ring merged to pyridinone scaffold are useful to enhance the BRD9 binding affinity. These findings should guide the rational design of more prospective inhibitors targeting BRD9.

Communicated by Ramaswamy H. Sarma     

Molecular mechanisms of resistance: free energy calculations of mutation effects on inhibitor binding to HIV-1 protease

The changes in the inhibitor binding constants due to the mutation of isoleucine to valine at position 84 of HIV-1 protease are calculated using molecular dynamics simulations. The calculations are done for three potent inhibitors--KNI-272, L-735,524 (indinavir or MK-639), and Ro 31-8959 (saquinavir). The calculations agree with the experimental data both in terms of an overall trend and in the magnitude of the resulting free energy change. HIV-1 protease is a homodimer, so each mutation causes two changes in the enzyme. The decrease in the binding free energy from each mutated side chain differs among the three inhibitors and correlates well with the size of the cavities induced in the protein interior near the mutated residue. The cavities are created as a result of a mutation to a smaller side chain, but the cavities are less than would be predicted from the wild-type structures, indicating that there is significant relaxation to partially fill the cavities.     

A computational analysis of pyrazole-based inhibitors binding to Hsp90 using molecular dynamics simulation and the MM-GBSA method

Owing to the key role of heat-shock protein 90 (Hsp90) in the evolution, development and disease pathogenesis of cancer, it has been an important target for anti-cancer chemotherapy over the years. A five-nanosecond molecular dynamics simulation combined with the calculation of the binding free energy was carried out to investigate the binding mechanisms of three Hsp90 inhibitors 4BH, 2E1 and 2D9 to Hsp90. The binding free energy of each complex was computed using the molecular mechanics–generalised Born surface area method. Detailed binding free energies between each inhibitor and residues of Hsp90 were calculated using a per-residue basis decomposition method. The detailed inhibitor–residue interaction provides insights into binding mechanisms and in-depth understanding of the structure–affinity relationship. This study suggests that van der Waals energy is primarily responsible for driving the binding of the inhibitors to Hsp90, and the three inhibitors bind to Hsp90 in a similar binding mode. However, a substituent in 2D9 leads to higher binding free energy than the other two inhibitors. These data may assist in designing new potent drugs to combat cancer.     

Free energetics of rigid body association of ubiquitin binding domains: A biochemical model for binding mediated by hydrophobic interaction

Weak intermolecular interactions, such as hydrophobic associations, underlie numerous biomolecular recognition processes. Ubiquitin is a small protein that represents a biochemical model for exploring thermodynamic signatures of hydrophobic association as it is widely held that a major component of ubiquitin's binding to numerous partners is mediated by hydrophobic regions on both partners. Here, we use atomistic molecular dynamics simulations in conjunction with the Adaptive Biasing Force sampling method to compute potentials of mean force (the reversible work, or free energy, associated with the binding process) to investigate the thermodynamic signature of complexation in this well‐studied biochemical model of hydrophobic association. We observe that much like in the case of a purely hydrophobic solute (i.e., graphene, carbon nanotubes), association is favored by entropic contributions from release of water from the interprotein regions. Moreover, association is disfavored by loss of enthalpic interactions, but unlike in the case of purely hydrophobic solutes, in this case protein‐water interactions are lost and not compensated for by additional water‐water interactions generated upon release of interprotein and moreso, hydration, water. We further find that relative orientations of the proteins that mutually present hydrophobic regions of each protein to its partner are favored over those that do not. In fact, the free energy minimum as predicted by a force field based method recapitulates the experimental NMR solution structure of the complex. Proteins 2014; 82:1453–1468. © 2014 Wiley Periodicals, Inc.