Unravelling Hot Spots: a comprehensive computational mutagenesis study

New insights into protein-protein interaction modulators in drug discovery and therapeutic advance

Protein-protein interactions (PPIs) are fundamental to cellular signaling and transduction which marks them as attractive therapeutic drug development targets. What were once considered to be undruggable targets have become increasingly feasible due to the progress that has been made over the last two decades and the rapid technological advances. This work explores the influence of technological innovations on PPI research and development. Additionally, the diverse strategies for discovering, modulating, and characterizing PPIs and their corresponding modulators are examined with the aim of presenting a streamlined pipeline for advancing PPI-targeted therapeutics. By showcasing carefully selected case studies in PPI modulator discovery and development, we aim to illustrate the efficacy of various strategies for identifying, optimizing, and overcoming challenges associated with PPI modulator design. The valuable lessons and insights gained from the identification, optimization, and approval of PPI modulators are discussed with the aim of demonstrating that PPI modulators have transitioned beyond early-stage drug discovery and now represent a prime opportunity with significant potential. The selected examples of PPI modulators encompass those developed for cancer, inflammation and immunomodulation, as well as antiviral applications. This perspective aims to establish a foundation for the effective targeting and modulation of PPIs using PPI modulators and pave the way for future drug development.

Evaluation of binding of potential ADMET/tox screened saquinavir analogues for inhibition of HIV-protease via molecular dynamics and binding free energy calculations

Developing novel drug molecules against HIV is a scientific quest necessitated by development of drug resistance against used drugs. We report comparative results of molecular dynamics simulation studies on 11 structural analogues of Saquinavir (SQV) - against HIV-protease that were earlier examined for pharmacodynamic and pharmacokinetic properties. We reported analogues S1, S5 and S8 to qualify the ADMET criterion and may be considered as potential lead molecules. In this study the designed molecules were successively docked with native HIV-protease at AutoDock. Docking scores established relative goodness of the 11 analogues against the benchmark for Saquinavir. The docked complexes were subjected to molecular dynamics simulation studies using GROMACS 4.6.2. Four parameters viz. H-bonding, RMSD, Binding energy and Protein-Ligand Distance were used for comparative analyses of the analogues relative to Saquinavir. The comparison and analysis of the results are indicative that analogues S8, S9 and S1 are promising candidates among all the analogues studied. From our earlier work and present study it is evident that among the three S8 and S1 qualify the ADMET criterion and between S1 and S8, the analogue S8 shows more target efficacy and specificity over S1 and have better molecular dynamics simulation results. Thus, of the 11 de novo Saquinavir analogues, the S8 appears to be the most promising candidate as lead molecule for HIV-protease inhibitor and is best suited for testing under biological system. Further validation of the proposed lead molecules through wet lab studies involving antiviral assays however is required.Communicated by Ramaswamy H. Sarma.

A molecular dynamic simulation approach: development of dengue virus vaccine by affinity improvement techniques

This study is about proposing a vaccine for all four strains of dengue virus (DENV) that could be an important approach for reaching the WHO goal of reducing dengue morbidity and mortality. The significance of the DENV envelope proteins III lies in the fact that it elicits an immune response and hence can be a potential vaccine design candidate. This domain appears to play a key role in the host cell receptor binding for viral entry and in inducing long lasting protective immunity against the infection. We used long molecular dynamic simulation and mutagenesis scanning methods to provide the dynamic environment and propose the potential mutation that may result in enhancing the binding specificity and affinity of the antigen-antibody (Ag-Ab) complex. The binding free energetics were also estimated using free energy perturbation method. One charged mutation that is theorinine 93L to arginine interacting with epitopic glutamic acid 368 strongly contributing in increasing the binding affinity as well as specificity, predicted as -9.6 kcal/mol gain in 2H12-Fab with dengue envelope domain III binding free energy relative to the wild-type. In conclusion, the one charged residue that showed theoretically enhances the binding affinity of Ag-Ab complex by making couple of interactions i.e. by substituting theorinine to arginine in the antibody chains and can be considered as potential dengue vaccine candidate.Communicated by Ramaswamy H. Sarma.

Molecular mechanism and binding free energy of doxorubicin intercalation in DNA

The intercalation process of binding doxorubicin (DOX) in DNA is studied by extensive MD simulations. Many molecular factors that control the binding affinity of DOX to DNA to form a stable complex are inspected and quantified by employing continuum solvation models for estimating the binding free energy. The modified MM-PB(GB)SA methodology provides a complete energetic profile of ΔGele, ΔGvDW, ΔGpolar, ΔGnon-polar, TΔStotal, ΔGdeform, ΔGcon, and ΔGion. To identify the sequence specificity of DOX, two different DNA sequences, d(CGATCG) or DNA1 and d(CGTACG) or DNA2, with one molecule (1 : 1 complex) or two molecule (2 : 1 complex) configurations of DOX were selected in this study. Our results show that the DNA deformation energy (ΔGdeform), the energy cost from translational and rotational entropic contributions (TΔStran+rot), the total electrostatic interactions (ΔGpolar-PB/GB + ΔGele) of incorporation, the intramolecular electrostatic interactions (ΔGele) and electrostatic polar solvation interactions (ΔGpolar-PB/GB) are all unfavorable to the binding of DOX to DNA. However, they are overcome by at least five favorable interactions: the van der Waals interactions (ΔGvDW), the non-polar solvation interaction (ΔGnon-polar), the vibrational entropic contribution (TΔSvib), and the standard concentration dependent free energies of DOX (ΔGcon) and the ionic solution (ΔGion). Specifically, the van der Waals interaction appears to be the major driving force to form a stable DOX-DNA complex. We also predict that DOX has stronger binding to DNA1 than DNA2. The DNA deformation penalty and entropy cost in the 2 : 1 complex are less than those in the 1 : 1 complex, thus they indicate that the 2 : 1 complex is more stable than the 1 : 1 complex. We have calculated the total binding free energy (BFE) (ΔGt-sim) using both MM-PBSA and MM-GBSA methods, which suggests a more stable DOX-DNA complex at lower ionic concentration. The calculated BFE from the modified MM-GBSA method for DOX-DNA1 and DOX-DNA2 in the 1 : 1 complex is -9.1 and -5.1 kcal mol-1 respectively. The same quantities from the modified MM-PBSA method are -12.74 and -8.35 kcal mol-1 respectively. The value of the total BFE ΔGt-sim in the 1 : 1 complex is in reasonable agreement with the experimental value of -7.7 ± 0.3 kcal mol-1.

Discovering key residues of dengue virus NS2b-NS3-protease: New binding sites for antiviral inhibitors design

The NS2B-NS3 protease is essential for the Dengue Virus (DENV) replication process. This complex constitutes a target for efficient antiviral discovery because a drug could inhibit the viral polyprotein processing. Furthermore, since the protease is highly conserved between the four Dengue virus serotypes, it is probable that a drug would be equally effective against all of them. In this article, a strategy is reported that allowed us to identify influential residues on the function of the Dengue NS2b-NS3 Protease. Moreover, this is a strategy that could be applied to virtually any protein for the search of alternative influential residues, and for non-competitive inhibitor development. First, we incorporated several features derived from computational alanine scanning mutagenesis, sequence, structure conservation, and other structure-based characteristics. Second, these features were used as variables to obtain a multilayer perceptron model to identify defined groups (clusters) of key residues as possible candidate pockets for binding sites of new leads on the DENV protease. The identified residues included: i) amino acids close to the beta sheet-loop-beta sheet known to be important in its closed conformation for NS2b ii) residues close to the active site, iii) several residues evenly spread on the NS2b-NS3 contact surface, and iv) some inner residues most likely related to the overall stability of the protease. In addition, we found concordance on our list of residues with previously identified amino acids part of a highly conserved peptide studied for vaccine development.

Computer aided design and NMR characterization of an oligopeptide targeting the Ebola virus VP24 protein

The nona-peptide RS, designed on the basis of computational studies, is able to interact with Ebola VP24 and potentially inhibit its interaction with KPNA.

In silico study of VP35 inhibitors: from computational alanine scanning to essential dynamics

In recent years the Ebola virus has spread through several countries in Africa, highlighting the need to develop new treatments for this disease and boosting a new research effort on this subject. The Ebola virus Viral Protein 35 (VP35) carries out multiple functions necessary for virus replication and infection, in particular interfering with (IFN)-α/β signaling. Recently, VP35 has been crystallized in complex with small organic molecules able to inhibit its interaction with viral nucleoproteins, thus reducing Ebola infections of cultured cells. In this work, starting from these structures, we carry out a computational study aimed at investigating the energetic and dynamical aspects of the interaction between VP35 and its ligands at the atomic level. Molecular dynamics simulations, computational alanine scanning, root mean square fluctuations bootstrap analysis and essential dynamics analysis were performed. Our results expand the experimental ones obtained in previous works, adding information about the interactions landscape with the identification of a set of new hot-spots residues exerting a critical function in the protein-ligand interaction. Moreover we characterized the dynamics of the complexes, showing that the presence of ligands modifies the overall protein dynamics as well as the behavior of particular protein segments.

The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

INTRODUCTION

The molecular mechanics energies combined with the Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor-ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success.

AREAS COVERED

The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications.

EXPERT OPINION

MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used successfully to reproduce and rationalize experimental findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approximations, for example, the lack of conformational entropy and information about the number and free energy of water molecules in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mechanical calculations, polarizable force fields or improved solvation have deteriorated the results.

Solvent accessible surface area-based hot-spot detection methods for protein-protein and protein-nucleic acid interfaces

Due to the importance of hot-spots (HS) detection and the efficiency of computational methodologies, several HS detecting approaches have been developed. The current paper presents new models to predict HS for protein-protein and protein-nucleic acid interactions with better statistics compared with the ones currently reported in literature. These models are based on solvent accessible surface area (SASA) and genetic conservation features subjected to simple Bayes networks (protein-protein systems) and a more complex multi-objective genetic algorithm-support vector machine algorithms (protein-nucleic acid systems). The best models for these interactions have been implemented in two free Web tools.

A new scoring function for protein-protein docking that identifies native structures with unprecedented accuracy

Protein-protein (P-P) 3D structures are fundamental to structural biology and drug discovery. However, most of them have never been determined. Many docking algorithms were developed for that purpose, but they have a very limited accuracy in generating native-like structures and identifying the most correct one, in particular when a single answer is asked for. With such a low success rate it is difficult to point out one docked structure as being native-like. Here we present a new, high accuracy, scoring method to identify the 3D structure of P-P complexes among a set of trial poses. It incorporates alanine scanning mutagenesis experimental data that need to be obtained a priori. The scoring scheme works by matching the computational and the experimental alanine scanning mutagenesis results. The size of the trial P-P interface area is also taken into account. We show that the method ranks the trial structures and identifies the native-like structures with unprecedented accuracy (∼94%), providing the correct P-P 3D structures that biochemists and molecular biologists need to pursue their studies. With such a success rate, the bottleneck of protein-protein docking moves from the scoring to searching algorithms.

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.

Discovery of new sites for drug binding to the hypertension-related renin-angiotensinogen complex

Renin (REN) is a key drug target to stop the hypertension cascade, but thus far only one direct inhibitor has been made commercially available. In this study, we assess an innovative REN inhibition strategy, by targeting the interface of the renin:angiotensinogen (REN:ANG) complex. We characterized the energetic role of interfacial residues of REN:ANG and identified the ones responsible for protein:protein binding, which can serve as drug targets for disruption of the REN:ANG association. For this purpose, we applied a computational alanine scanning mutagenesis protocol, which measures the contribution of each side chain for the protein:protein binding free energy with an accuracy of ≈ 1 kcal/mol. As a result, in REN and ANG, six and eight residues were found to be critical for binding, respectively. The leading force behind REN:ANG complexation was found to be the hydrophobic effect. The binding free energy per residue was found to be proportional to the buried area. Residues responsible for binding were occluded from water at the complex, which promotes an efficient pairing between the two proteins. Two druggable pockets involving critical residues for binding were found on the surface of REN, where small druglike molecules can bind and disrupt the ANG:REN association that may provide an efficient way to achieve REN inhibition and control hypertension.

Solvent-accessible surface area: How well can be applied to hot-spot detection?

A detailed comprehension of protein-based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA-based features for their ability to correlate and differentiate hot- and null-spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot- and null-spots, while presenting low correlations. Residue standardization such as rel SASAi or rel/res SASAi , improved the features as a tool to predict ΔΔGbinding values. A new method using support machine learning algorithms was developed: SBHD (Sasa-Based Hot-spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set.

Structural features of the G-protein/GPCR interactions

BACKGROUND

The details of the functional interaction between G proteins and the G protein coupled receptors (GPCRs) have long been subjected to extensive investigations with structural and functional assays and a large number of computational studies.

SCOPE OF REVIEW

The nature and sites of interaction in the G-protein/GPCR complexes, and the specificities of these interactions selecting coupling partners among the large number of families of GPCRs and G protein forms, are still poorly defined.

MAJOR CONCLUSIONS

Many of the contact sites between the two proteins in specific complexes have been identified, but the three dimensional molecular architecture of a receptor-Gα interface is only known for one pair. Consequently, many fundamental questions regarding this macromolecular assembly and its mechanism remain unanswered.

GENERAL SIGNIFICANCE

In the context of current structural data we review the structural details of the interfaces and recognition sites in complexes of sub-family A GPCRs with cognate G-proteins, with special emphasis on the consequences of activation on GPCR structure, the prevalence of preassembled GPCR/G-protein complexes, the key structural determinants for selective coupling and the possible involvement of GPCR oligomerization in this process.

Computational Alanine Scanning Mutagenesis-An Improved Methodological Approach for Protein-DNA Complexes

Proteins and protein-based complexes are the basis of many key systems in nature and have been the subject of intense research in the last decades, in an attempt to acquire comprehensive knowledge of reactions that take place in nature. Computational Alanine Scanning Mutagenesis approaches have been extensively used in the study of protein interfaces and in the determination of the most important residues for complex formation, the Hot-spots. However, as it is usually applied to the study of protein-protein interfaces, we tried to modify and apply it to the study of protein-DNA interfaces, which are also crucial in nature but have not been the subject of as much research. In this work, we carry out MD simulations of seven protein-DNA complexes and tested the influence of the variation of different parameters on the determination of the binding free energy terms (ΔΔGbinding) of 78 mutations: solvent representation, internal dielectric constant, Linear and Nonlinear Poisson-Boltzmann equation, Generalized Born model, simulation time, number of structures analyzed, number of MD trajectories, force field used, and energetic terms involved. Overall, this new approach gave an average error of 1.55 kcal/mol, and P, R, F1, accuracy, and specificity values of 0.78, 0.50, 0.61, 0.77, and 0.92, respectively. This improved computational alanine scanning mutagenesis approach may serve as a tool to explore the behavior of this important class of complexes.

Computational Alanine Scanning Mutagenesis: MM-PBSA vs TI

Understanding protein-protein association and being able to determine the crucial residues responsible for their association (hot-spots) is a key issue with huge practical applications such as rational drug design and protein engineering. A variety of computational methods exist to detect hot-spots residues, but the development of a fast and accurate quantitative alanine scanning mutagenesis (ASM) continues to be crucial. Using four protein-protein complexes, we have compared a variation of the standard computational ASM protocol developed at our group, based on the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM-PBSA) approach, against Thermodynamic Integration (TI), a well-known and accurate but computationally expensive method. To compare the efficiency and the accuracy of the two methods, we have calculated the protein-protein binding free energy differences upon alanine mutation of interfacial residues (ΔΔGbind). In relation to the experimental ΔΔGbind values, the average error obtained with TI was 1.53 kcal/mol, while the ASM protocol resulted in an average error of 1.18 kcal/mol. The results demonstrate that the much faster ASM protocol gives results at the same level of accuracy as the TI method but at a fraction of the computational time required to run TI. This ASM protocol is therefore a strong and efficient alternative to the systematic evaluation of protein-protein interfaces, involving hundreds of amino acid residues in search of hot-spots.

Of mice and men: Dissecting the interaction between Listeria monocytogenes Internalin A and E-cadherin

We report a study of the interaction between internalin A (inlA) and human or murine E-cadherin (Ecad). inlA is used by Listeria monocytogenes to internalize itself into host cell, but the bacterium is unable to invade murine cells, which has been attributed to the difference in sequence between hEcad and mEcad. Using molecular dynamics simulations, MM/GBSA free energy calculations, hydrogen bond analysis, water characterization and umbrella sampling, we provide a complete atomistic picture of the binding between inlA and Ecad. We dissect key residues in the protein–protein interface and analyze the energetics using MM/GBSA. From this analysis it is clear that the binding of inlA–mEcad is weaker than inlA–hEcad, on par with the experimentally observed inability of inlA to bind to mEcad. However, extended MD simulations of 200 ns in length show no destabilization of the inlA–mEcad complex and the estimation of the potential of mean force (PMF) using umbrella sampling corroborates this conclusion. The binding strength computed from the PMFs show no significant difference between the two protein complexes. Hence, our study suggests that the inability of L. monocytogenes to invade murine cells cannot be explained by processes at the nanosecond to sub-microsecond time scale probed by the simulations performed here.

Vinblastine perturbation of tubulin protofilament structure: a computational insight

Tubulin is a heterodimeric protein whose self assembly leads to the formation of protofilaments and of more complex structures called microtubules, key components of the cytoskeleton which have a fundamental role in the cell division process. Due to its biological function, tubulin is the target of many antitumoral molecules that exert their action on proliferating tumoral cells. Among these drugs, vinblastine has been widely used in therapy for a long time, albeit its mechanism of interaction with tubulin has remained elusive until recently. Vinblastine acts as a microtubule destabilizing agent and induces the formation of curved or ring-shaped tubulin polymers instead of linear protofilaments in vitro. In this paper we compare, using molecular dynamics simulations and free energy calculations, the network of interactions that allow the assembly of model linear protofilaments with those present in curved tubulin polymers complexed with vinblastine. It is shown that vinblastine, wedging between tubulin heterodimers, actually mediates part of the interactions between them and acts by crosslinking the two proteins, leading to the observed curved polymers rather than to their disassembly.

Comparison of computational approaches for predicting the effects of missense mutations on p53 function

We applied our recently developed kinetic computational mutagenesis (KCM) approach [L.T. Chong, W.C. Swope, J.W. Pitera, V.S. Pande, Kinetic computational alanine scanning: application to p53 oligomerization, J. Mol. Biol. 357 (3) (2006) 1039-1049] along with the MM-GBSA approach [J. Srinivasan, T.E. Cheatham 3rd, P. Cieplak, P.A. Kollman, D.A. Case, Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate-DNA helices, J. Am. Chem. Soc. 120 (37) (1998) 9401-9409; P.A. Kollman, I. Massova, C.M. Reyes, B. Kuhn, S. Huo, L.T. Chong, M. Lee, T. Lee, Y. Duan, W. Wang, O. Donini, P. Cieplak, J. Srinivasan, D.A. Case, T.E. Cheatham 3rd., Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models, Acc. Chem. Res. 33 (12) (2000) 889-897] to evaluate the effects of all possible missense mutations on dimerization of the oligomerization domain (residues 326-355) of tumor suppressor p53. The true positive and true negative rates for KCM are comparable (within 5%) to those of MM-GBSA, although MM-GBSA is much less computationally intensive when it is applied to a single energy-minimized configuration per mutant dimer. The potential advantage of KCM is that it can be used to directly examine the kinetic effects of mutations.

Hot spots-A review of the protein-protein interface determinant amino-acid residues

Proteins tendency to bind to one another in a highly specific manner forming stable complexes is fundamental to all biological processes. A better understanding of complex formation has many practical applications, which include the rational design of new therapeutic agents, and the analysis of metabolic and signal transduction networks. Alanine-scanning mutagenesis made possible the detection of the functional epitopes, and demonstrated that most of the protein-protein binding energy is related only to a group of few amino acids at intermolecular protein interfaces: the hot spots. The scope of this review is to summarize all the available information regarding hot spots for a better atomic understanding of their structure and function. The ultimate objective is to improve the rational design of complexes of high affinity and specificity as well as that of small molecules, which can mimic the functional epitopes of the proteic complexes.

Hot Spot Occlusion from Bulk Water: a Comprehensive Study of the Complex between the Lysozyme HEL and the Antibody FVD1.3

Alanine scanning of protein-protein interfaces has shown that there are some residues in the protein-protein interfaces, responsible for most of the binding free energy, which are called hot spots. Hot spots tend to exist in densely packed central clusters, and a hypothesis has been proposed that considers that inaccessibility to the solvent must be a necessary condition to define a residue as a binding hot spot. This O-ring hypothesis is mainly based on the analysis of the accessible surface area (ASA) of 23 static, crystallographic structures of protein complexes. It is known, however, that protein flexibility allows for temporary exposures of buried interfacial groups, and even though the ASA provides a general trend of the propensity for hydration, protein/solvent-specific interactions or hydrogen bonding cannot be considered here. Therefore, a microscopic level, atomistic picture of hot spot solvation is needed to support the O-ring hypothesis. In this study, we began by applying a computational alanine-scanning mutagenesis technique, which reproduces the experimental results and allows for decomposing the binding free energy difference in its different energetic factors. Subsequently, we calculated the radial distribution function and residence times of the water molecules near the hot/warm spots to study the importance of the water environment around those energetically important amino acid residues. This study shows that within a flexible, dynamic protein framework, the warm/hot spot residues are, indeed, kept sheltered from the bulk solvent during the whole simulation, which allows a better interacting microenvironment.