Hybrid Steered Molecular Dynamics-Docking: An Efficient Solution to the Problem of Ranking Inhibitor Affinities Against a Flexible Drug Target

Decrypting a Cryptic Allosteric Pocket in H. pylori Glutamate Racemase

One of our greatest challenges in drug design is targeting cryptic allosteric pockets in enzyme targets. Drug leads that do bind to these cryptic pockets are often discovered during HTS campaigns, and the mechanisms of action are rarely understood. Nevertheless, it is often the case that the allosteric pocket provides the best option for drug development against a given target. In the current studies we present a successful way forward in rationally exploiting the cryptic allosteric pocket of H. pylori glutamate racemase, an essential enzyme in this pathogen's life cycle. A wide range of computational and experimental methods are employed in a workflow leading to the discovery of a series of natural product allosteric inhibitors which occupy the allosteric pocket of this essential racemase. The confluence of these studies reveals a fascinating source of the allosteric inhibition, which centers on the abolition of essential monomer-monomer coupled motion networks.

The prediction of protein-ligand unbinding for modern drug discovery

INTRODUCTION

Drug-target thermodynamic and kinetic information have perennially important roles in drug design. The prediction of protein-ligand unbinding, which can provide important kinetic information, in experiments continues to face great challenges. Uncovering protein-ligand unbinding through molecular dynamics simulations has become efficient and inexpensive with the progress and enhancement of computing power and sampling methods.

AREAS COVERED

In this review, various sampling methods for protein-ligand unbinding and their basic principles are firstly briefly introduced. Then, their applications in predicting aspects of protein-ligand unbinding, including unbinding pathways, dissociation rate constants, residence time and binding affinity, are discussed.

EXPERT OPINION

Although various sampling methods have been successfully applied in numerous systems, they still have shortcomings and deficiencies. Most enhanced sampling methods require researchers to possess a wealth of prior knowledge of collective variables or reaction coordinates. In addition, most systems studied at present are relatively simple, and the study of complex systems in real drug research remains greatly challenging. Through the combination of machine learning and enhanced sampling methods, prediction accuracy can be further improved, and some problems encountered in complex systems also may be solved.

Ranking of Ligand Binding Kinetics Using a Weighted Ensemble Approach and Comparison with a Multiscale Milestoning Approach

To improve lead optimization efforts in finding the right ligand, pharmaceutical industries need to know the ligand's binding kinetics, such as binding and unbinding rate constants, which often correlate with the ligand's efficacy in vivo. To predict binding kinetics efficiently, enhanced sampling methods, such as milestoning and the weighted ensemble (WE) method, have been used in molecular dynamics (MD) simulations of these systems. However, a comparison of these enhanced sampling methods in ranking ligands has not been done. Hence, a WE approach called the concurrent adaptive sampling (CAS) algorithm that uses MD simulations was used to rank seven ligands for β-cyclodextrin, a system in which a multiscale milestoning approach called simulation enabled estimation of kinetic rates (SEEKR) was also used, which uses both MD and Brownian dynamics simulations. Overall, the CAS algorithm can successfully rank ligands using the unbinding rate constant k_off values and binding free energy ΔG values, as SEEKR did, with reduced computational cost that is about the same as SEEKR. We compare the CAS algorithm simulations with different parameters and discuss the impact of parameters in ranking ligands and obtaining rate constant and binding free energy estimates. We also discuss similarities and differences and advantages and disadvantages of SEEKR and the CAS algorithm for future use.

Molecular Docking: Challenges, Advances and its Use in Drug Discovery Perspective

Molecular docking is a process through which small molecules are docked into the macromolecular structures for scoring its complementary values at the binding sites. It is a vibrant research area with dynamic utility in structure-based drug-designing, lead optimization, biochemical pathway and for drug designing being the most attractive tools. Two pillars for a successful docking experiment are correct pose and affinity prediction. Each program has its own advantages and drawbacks with respect to their docking accuracy, ranking accuracy and time consumption so a general conclusion cannot be drawn. Moreover, users don't always consider sufficient diversity in their test sets which results in certain programs to outperform others. In this review, the prime focus has been laid on the challenges of docking and troubleshooters in existing programs, underlying algorithmic background of docking, preferences regarding the use of docking programs for best results illustrated with examples, comparison of performance for existing tools and algorithms, state of art in docking, recent trends of diseases and current drug industries, evidence from clinical trials and post-marketing surveillance are discussed. These aspects of the molecular drug designing paradigm are quite controversial and challenging and this review would be an asset to the bioinformatics and drug designing communities.

Elucidating the Catalytic Power of Glutamate Racemase by Investigating a Series of Covalent Inhibitors

The application of covalent inhibitors has experienced a renaissance within drug discovery programs in the last decade. To leverage the superior potency and drug target residence time of covalent inhibitors, there have been extensive efforts to develop highly specific covalent modifications to decrease off-target liabilities. Herein, we present a series of covalent inhibitors of an antimicrobial drug target, glutamate racemase, discovered through structure-based virtual screening. A combination of enzyme kinetics, mass spectrometry, and surface-plasmon resonance experiments details a highly specific 1,4-conjugate addition of a small-molecule inhibitor with a catalytic cysteine of glutamate racemase. Molecular dynamics simulations and quantum mechanics-molecular mechanics geometry optimizations reveal the chemistry of the conjugate addition. Two compounds from this series of inhibitors display antimicrobial potency similar to β-lactam antibiotics, with significant activity against methicillin-resistant S. aureus strains. This study elucidates a detailed chemical rationale for covalent inhibition and provides a platform for the development of antimicrobials with a novel mechanism of action against a target in the cell wall biosynthesis pathway.

In silico Prediction, Characterization, Molecular Docking, and Dynamic Studies on Fungal SDRs as Novel Targets for Searching Potential Fungicides Against Fusarium Wilt in Tomato

Vascular wilt of tomato caused by Fusarium oxysporum f.sp. lycopersici (FOL) is one of the most devastating diseases, that delimits the tomato production worldwide. Fungal short-chain dehydrogenases/reductases (SDRs) are NADP(H) dependent oxidoreductases, having shared motifs and common functional mechanism, have been demonstrated as biochemical targets for commercial fungicides. The 1,3,6,8 tetra hydroxynaphthalene reductase (T4HNR) protein, a member of SDRs family, catalyzes the naphthol reduction reaction in fungal melanin biosynthesis. We retrieved an orthologous member of T4HNR, (complexed with NADP(H) and pyroquilon from Magnaporthe grisea) in the FOL (namely; FOXG_04696) based on homology search, percent identity and sequence similarity (93% query cover; 49% identity). The hypothetical protein FOXG_04696 (T4HNR like) had conserved T-G-X-X-X-G-X-G motif (cofactor binding site) at N-terminus, similar to M. grisea (1JA9) and Y-X-X-X-K motif, as a part of the active site, bearing homologies with two fungal keto reductases T4HNR (M. grisea) and 17-β-hydroxysteroid dehydrogenase from Curvularia lunata (teleomorph: Cochliobolus lunatus PDB ID: 3IS3). The catalytic tetrad of T4HNR was replaced with ASN¹¹⁵, SER¹⁴¹, TYR¹⁵⁴, and LYS¹⁵⁸ in the FOXG_04696. The structural alignment and superposition of FOXG_04696 over the template proteins (3IS3 and 1JA9) revealed minimum RMSD deviations of the C alpha atomic coordinates, and therefore, had structural conservation. The best protein model (FOXG_04696) was docked with 37 fungicides, to evaluate their binding affinities. The Glide XP and YASARA docked complexes showed discrepancies in results, for scoring and ranking the binding affinities of fungicides. The docked complexes were further refined and rescored from their docked poses through 50 ns long MD simulations, and binding free energies (ΔG_bind) calculations, using MM/GBSA analysis, revealed Oxathiapiprolin and Famoxadone as better fungicides among the selected one. However, Famoxadone had better interaction of the docked residues, with best protein ligand contacts, minimum RMSD (high accuracy of the docking pose) and RMSF (structural integrity and conformational flexibility of docking) at the specified docking site. The Famoxadone was found to be acceptable based on in silico toxicity and in vitro growth inhibition assessment. We conclude that the FOXG_04696, could be employed as a novel candidate protein, for structure-based design, and screening of target fungicides against the FOL pathogen.

Biochemical Characterization of Glutamate Racemase-A New Candidate Drug Target against Burkholderia cenocepacia Infections

The greatest obstacle for the treatment of cystic fibrosis patients infected with the Burkholderia species is their intrinsic antibiotic resistance. For this reason, there is a need to develop new effective compounds. Glutamate racemase, an essential enzyme for the biosynthesis of the bacterial cell wall, is an excellent candidate target for the design of new antibacterial drugs. To this aim, we recombinantly produced and characterized glutamate racemase from Burkholderia cenocepacia J2315. From the screening of an in-house library of compounds, two Zn (II) and Mn (III) 1,3,5-triazapentadienate complexes were found to efficiently inhibit the glutamate racemase activity with IC50 values of 35.3 and 10.0 μM, respectively. Using multiple biochemical approaches, the metal complexes have been shown to affect the enzyme activity by binding to the enzyme-substrate complex and promoting the formation of an inhibited dimeric form of the enzyme. Our results corroborate the value of glutamate racemase as a good target for the development of novel inhibitors against Burkholderia.

Ensemble-based docking: From hit discovery to metabolism and toxicity predictions

This paper describes and illustrates the use of ensemble-based docking, i.e., using a collection of protein structures in docking calculations for hit discovery, the exploration of biochemical pathways and toxicity prediction of drug candidates. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.

Small-molecule inhibitors identify the RAD52-ssDNA interaction as critical for recovery from replication stress and for survival of BRCA2 deficient cells

The DNA repair protein RAD52 is an emerging therapeutic target of high importance for BRCA-deficient tumors. Depletion of RAD52 is synthetically lethal with defects in tumor suppressors BRCA1, BRCA2 and PALB2. RAD52 also participates in the recovery of the stalled replication forks. Anticipating that ssDNA binding activity underlies the RAD52 cellular functions, we carried out a high throughput screening campaign to identify compounds that disrupt the RAD52-ssDNA interaction. Lead compounds were confirmed as RAD52 inhibitors in biochemical assays. Computational analysis predicted that these inhibitors bind within the ssDNA-binding groove of the RAD52 oligomeric ring. The nature of the inhibitor-RAD52 complex was validated through an in silico screening campaign, culminating in the discovery of an additional RAD52 inhibitor. Cellular studies with our inhibitors showed that the RAD52-ssDNA interaction enables its function at stalled replication forks, and that the inhibition of RAD52-ssDNA binding acts additively with BRCA2 or MUS81 depletion in cell killing.

DOI:http://dx.doi.org/10.7554/eLife.14740.001

Cells are constantly in danger of losing or scrambling critical genetic information because of DNA damage. To cope with this stress, cells have numerous DNA repair systems. One of these systems – homology-directed DNA repair – involves the proteins BRCA1 and BRCA2, which are often missing or defective in breast and ovarian cancers. The BRCA-deficient cancer cells can still survive, but become “addicted” to other DNA repair proteins – among them a protein called RAD52. It might be possible to kill these cancer cells using drugs that stop RAD52 from working. Such treatments would have the benefit of not harming normal healthy cells, as these cells contain working BRCA proteins and can survive without RAD52.

It is not currently known exactly how RAD52 allows the BRCA-deficient cells to survive, but this probably depends on RAD52’s ability to bind to single strands of DNA. Small molecules that block the interaction between the RAD52 protein and DNA might therefore help to kill cancer cells.

Hengel et al. developed a high throughput biophysical method to search through a large collection of small molecules to find those that prevent RAD52 from binding to DNA. The best potential drug leads were then tested in laboratory-grown human cells and using biophysical and biochemical techniques. Computational approaches were also used to model how these molecules block the interaction between RAD52 and DNA at the atomistic level.

Hengel et al. then used the information about how the small molecules bind to RAD52 to perform further computational screening. This identified a natural compound that competes with single-stranded DNA to bind to RAD52. The activity of this molecule was then validated using biophysical methods.

The methods used by Hengel et al. provide the foundation for further searches for new anticancer drugs. Future studies that employ the small molecule drugs identified so far will also help to determine exactly how RAD52 works in human cells and how it helps cancer cells to survive.

DOI:http://dx.doi.org/10.7554/eLife.14740.002

In silico approach to explore the disruption in the molecular mechanism of human hyaluronidase 1 by mutant E268K that directs Natowicz syndrome

Natowicz syndrome (mucopolysaccharidoses type 9) is a lysosomal storage disorder caused by deficient or defective human hyaluronidase 1. The disorder is not well studied at the molecular level. Therefore, a new in silico approach was proposed to study the molecular basis on which one clinically observed mutation, Glu268Lys, results in a defective enzyme. The native and mutant structures were subjected to comparative analyses using a conformational sampling approach for geometrical variables viz, RMSF, RMSD, and Ramachandran plot. In addition, the strength of a Cys207-Cys221 disulfide bond and electrostatic interaction between Arg265 and Asp206 were studied, as they are known to be involved in the catalytic activity of the enzyme. Native and mutant E268K showed statistically significant variations with p < 0.05 in RMSD, Ramachandran plot, strengths of disulfide bond, and electrostatic interactions. Further, single model analysis showed variations between native and mutant structures in terms of intra-protein interactions, hydrogen bond dilution, secondary structure, and dihedral angles. Docking analysis predicted the mutant to have a less favorable substrate binding energy compared to the native protein. Additionally, steered MD analysis indicated that the substrate should have more affinity to the native than mutant enzymes. The observed changes theoretically explain the less favorable binding energy of substrate towards mutant E268K, thereby providing a structural basis for its reduced catalytic activity. Hence, our study provides a basis for understanding the disruption in the molecular mechanism of human hyaluronidase 1 by mutation E268K, which may prove useful for the development of synthetic chaperones as a treatment option for Natowicz syndrome.

Biosynthesis of a Novel Glutamate Racemase Containing a Site-Specific 7-Hydroxycoumarin Amino Acid: Enzyme-Ligand Promiscuity Revealed at the Atomistic Level

Glutamate racemase (GR) catalyzes the cofactor independent stereoinversion of l- to d-glutamate for biosynthesis of bacterial cell walls. Because of its essential nature, this enzyme is under intense scrutiny as a drug target for the design of novel antimicrobial agents. However, the flexibility of the enzyme has made inhibitor design challenging. Previous steered molecular dynamics (MD), docking, and experimental studies have suggested that the enzyme forms highly varied complexes with different competitive inhibitor scaffolds. The current study employs a mutant orthogonal tRNA/aminoacyl-tRNA synthetase pair to genetically encode a non-natural fluorescent amino acid, l-(7-hydroxycoumarin-4-yl) ethylglycine (7HC), into a region (Tyr53) remote from the active site (previously identified by MD studies as undergoing ligand-associated changes) to generate an active mutant enzyme (GR^Y53/7HC). The GR^Y53/7HC enzyme is an active racemase, which permitted us to examine the nature of these idiosyncratic ligand-associated phenomena. One type of competitive inhibitor resulted in a dose-dependent quenching of the fluorescence of GR^Y53/7HC, while another type of competitive inhibitor resulted in a dose-dependent increase in fluorescence of GR^Y53/7HC. In order to investigate the environmental changes of the 7HC ring system that are distinctly associated with each of the GR^Y53/7HC-ligand complexes, and thus the source of the disparate quenching phenomena, a parallel computational study is described, which includes essential dynamics, ensemble docking and MD simulations of the relevant GR^Y53/7HC-ligand complexes. The changes in the solvent exposure of the 7HC ring system due to ligand-associated GR changes are consistent with the experimentally observed quenching phenomena. This study describes an approach for rationally predicting global protein allostery resulting from enzyme ligation to distinctive inhibitor scaffolds. The implications for fragment-based drug discovery and high throughput screening are discussed.

Importance of protein flexibility in ranking inhibitor affinities: modeling the binding mechanisms of piperidine carboxamides as Type I1/2 ALK inhibitors

Anaplastic lymphoma kinase (ALK) has gained increased attention as an attractive therapeutic target for the treatment of various cancers, especially non-small-cell lung cancer (NSCLC).

Overcoming dissipation in the calculation of standard binding free energies by ligand extraction

This article addresses calculations of the standard free energy of binding from molecular simulations in which a bound ligand is extracted from its binding site by steered molecular dynamics (MD) simulations or equilibrium umbrella sampling (US). Host-guest systems are used as test beds to examine the requirements for obtaining the reversible work of ligand extraction. We find that, for both steered MD and US, marked irreversibilities can occur when the guest molecule crosses an energy barrier and suddenly jumps to a new position, causing dissipation of energy stored in the stretched molecule(s). For flexible molecules, this occurs even when a stiff pulling spring is used, and it is difficult to suppress in calculations where the spring is attached to the molecules by single, fixed attachment points. We, therefore, introduce and test a method, fluctuation-guided pulling, which adaptively adjusts the spring's attachment points based on the guest's atomic fluctuations relative to the host. This adaptive approach is found to substantially improve the reversibility of both steered MD and US calculations for the present systems. The results are then used to estimate standard binding free energies within a comprehensive framework, termed attach-pull-release, which recognizes that the standard free energy of binding must include not only the pulling work itself, but also the work of attaching and then releasing the spring, where the release work includes an accounting of the standard concentration to which the ligand is discharged.

Nexus between protein-ligand affinity rank-ordering, biophysical approaches, and drug discovery

The confluence of computational and biophysical methods to accurately rank-order the binding affinities of small molecules and determine structures of macromolecular complexes is a potentially transformative advance in the work flow of drug discovery. This viewpoint explores the impact that advanced computational methods may have on the efficacy of small molecule drug discovery and optimization, particularly with respect to emerging fragment-based methods.

In silico optimization of a fragment-based hit yields biologically active, high-efficiency inhibitors for glutamate racemase

A novel lead compound for inhibition of the antibacterial drug target, glutamate racemase (GR), was optimized for both ligand efficiency and lipophilic efficiency. A previously developed hybrid molecular dynamics-docking and scoring scheme, FERM-SMD, was used to predict relative potencies of potential derivatives prior to chemical synthesis. This scheme was successful in distinguishing between high- and low-affinity binders with minimal experimental structural information, saving time and resources in the process. In vitro potency was increased approximately fourfold against GR from the model organism, B. subtilis. Lead derivatives show two- to fourfold increased antimicrobial potency over the parent scaffold. In addition, specificity toward B. subtilis over E. coli and S. aureus depends on the substituent added to the parent scaffold. Finally, insight was gained into the capacity for these compounds to reach the target enzyme in vivo using a bacterial cell wall lysis assay. The outcome of this study is a novel small-molecule inhibitor of GR with the following characteristics: Ki=2.5 μM, LE=0.45 kcal mol(-1) atom(-1), LiPE=6.0, MIC50=260 μg mL(-1) against B. subtilis, EC50, lysis=520 μg mL(-1) against B. subtilis.

Flooding enzymes: quantifying the contributions of interstitial water and cavity shape to ligand binding using extended linear response free energy calculations

Glutamate racemase (GR) is a cofactor independent amino acid racemase that has recently garnered increasing attention as an antimicrobial drug target. There are numerous high resolution crystal structures of GR, yet these are invariably bound to either d-glutamate or very weakly bound oxygen-based salts. Recent in silico screens have identified a number of new competitive inhibitor scaffolds, which are not based on d-Glu, but exploit many of the same hydrogen bond donor positions. In silico studies on 1-H-benzimidazole-2-sulfonic acid (BISA) show that the sulfonic acid points to the back of the GR active site, in the most buried region, analogous to the C2-carboxylate binding position in the GR-d-glutamate complex. Furthermore, BISA has been shown to be the strongest nonamino acid competitive inhibitor. Previously published computational studies have suggested that a portion of this binding strength is derived from complexation with a more closed active site, relative to weaker ligands, and in which the internal water network is more isolated from the bulk solvent. In order to validate key contacts between the buried sulfonate moiety of BISA and moieties in the back of the enzyme active site, as well as to probe the energetic importance of the potentially large number of interstitial waters contacted by the BISA scaffold, we have designed several mutants of Asn75. GR-N75A removes a key hydrogen bond donor to the sulfonate of BISA, but also serves to introduce an additional interstitial water, due to the newly created space of the mutation. GR- N75L should also show the loss of a hydrogen bond donor to the sulfonate of BISA, but does not (a priori) seem to permit an additional interstitial water contact. In order to investigate the dynamics, structure, and energies of this water-mediated complexation, we have employed the extended linear response (ELR) approach for the calculation of binding free energies to GR, using the YASARA2 knowledge based force field on a set of ten GR complexes, and yielding an R-squared value of 0.85 and a RMSE of 2.0 kJ/mol. Surprisingly, the inhibitor set produces a uniformly large interstitial water contribution to the electrostatic interaction energy (⟨V^el⟩), ranging from 30 to >50%, except for the natural substrate (d-glutamate), which has only a 7% contribution of ⟨V^el⟩ from water. The broader implications for predicting and exploiting significant interstitial water contacts in ligand–enzyme complexation are discussed.

Molecular dynamics simulations in drug design

This minireview focuses on recent developments in the application of molecular dynamics to drug design. Recent applications of endpoint free-energy computational methods such as molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and generalized Born surface area (MM-GBSA) and linear response methods are described. Recent progress in steered molecular dynamics applied to drug design is reviewed.