Ensemble-docking approach on BACE-1: pharmacophore perception and guidelines for drug design

A combined approach of structure-based virtual screening and NMR to interrupt the PD-1/PD-L1 axis: Biphenyl-benzimidazole containing compounds as novel PD-L1 inhibitors

Immunotherapy has emerged as a game-changing approach for cancer treatment. Although monoclonal antibodies (mAbs) targeting the programmed cell death protein 1/programmed cell death protein 1 ligand 1 (PD-1/PD-L1) axis have entered the market revolutionizing the treatment landscape of many cancer types, small molecules, although presenting several advantages including the possibility of oral administration and/or reduced costs, struggled to enter in clinical trials, suffering of water insolubility and/or inadequate potency compared with mAbs. Thus, the search for novel scaffolds for both the design of effective small molecules and possible synergistic strategies is an ongoing field of interest. In an attempt to find novel chemotypes, a virtual screening approach was employed, resulting in the identification of new chemical entities with a certain binding capability, the most versatile of which was the benzimidazole-containing compound 10. Through rational design, a small library of its derivatives was synthesized and evaluated. The homogeneous time-resolved fluorescence (HTRF) assay revealed that compound 17 shows the most potent inhibitory activity (IC50 ) in the submicromolar range and notably, differently from the major part of PD-L1 inhibitors, exhibits satisfactory water solubility properties. These findings highlight the potential of benzimidazole-based compounds as novel promising candidates for PD-L1 inhibition.

Identification of Catechins' Binding Sites in Monomeric Aβ42 through Ensemble Docking and MD Simulations

The assembly of the amyloid-β peptide (Aβ) into toxic oligomers and fibrils is associated with Alzheimer's disease and dementia. Therefore, disrupting amyloid assembly by direct targeting of the Aβ monomeric form with small molecules or antibodies is a promising therapeutic strategy. However, given the dynamic nature of Aβ, standard computational tools cannot be easily applied for high-throughput structure-based virtual screening in drug discovery projects. In the current study, we propose a computational pipeline-in the framework of the ensemble docking strategy-to identify catechins' binding sites in monomeric Aβ₄₂. It is shown that both hydrophobic aromatic interactions and hydrogen bonding are crucial for the binding of catechins to Aβ₄₂. Additionally, it has been found that all the studied ligands, especially EGCG, can act as potent inhibitors against amyloid aggregation by blocking the central hydrophobic region of Aβ. Our findings are evaluated and confirmed with multi-microsecond MD simulations. Finally, it is suggested that our proposed pipeline, with low computational cost in comparison with MD simulations, is a suitable approach for the virtual screening of ligand libraries against Aβ.

Approaches to the Structure-Based Design of Antivirulence Drugs: Therapeutics for the Post-Antibiotic Era

The alarming rise of multidrug-resistant bacterial strains, coupled with decades of stagnation in the field of antibiotic development, necessitates exploration of new therapeutic approaches to treat bacterial infections. Targeting bacterial virulence is an attractive alternative to traditional antibiotics in that this approach disarms pathogens that cause human diseases, without placing immediate selective pressure on the target bacterium or harming commensal species. The growing number of validated virulence protein targets for which structural information has been obtained, along with advances in computational power and screening algorithms, make the rational design of antivirulence drugs a promising avenue to explore. Here, we review the principles of structure-based drug design and the exciting opportunities this technique presents for antivirulence drug discovery.

Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations

Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.

Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: discovery of novel phytochemicals for BACE1 inhibition

Mimicking receptor flexibility during receptor-ligand binding is a challenging task in computational drug design since it is associated with a large increase in the conformational search space. In the present study, we have devised an in silico design strategy incorporating receptor flexibility in virtual screening to identify potential lead compounds as inhibitors for flexible proteins. We have considered BACE1 (β-secretase), a key target protease from a therapeutic perspective for Alzheimer's disease, as the highly flexible receptor. The protein undergoes significant conformational transitions from open to closed form upon ligand binding, which makes it a difficult target for inhibitor design. We have designed a hybrid structure-activity model containing both ligand based descriptors and energetic descriptors obtained from molecular docking based on a dataset of structurally diverse BACE1 inhibitors. An ensemble of receptor conformations have been used in the docking study, further improving the prediction ability of the model. The designed model that shows significant prediction ability judged by several statistical parameters has been used to screen an in house developed 3-D structural library of 731 phytochemicals. 24 highly potent, novel BACE1 inhibitors with predicted activity (Ki) ≤ 50 nM have been identified. Detailed analysis reveals pharmacophoric features of these novel inhibitors required to inhibit BACE1.

Application of computational methods for the design of BACE-1 inhibitors: validation of in silico modelling

β-Secretase (BACE-1) constitutes an important target for search of anti-Alzheimer’s drugs. The first inhibitors of this enzyme were peptidic compounds with high molecular weight and low bioavailability. Therefore, the search for new efficient non-peptidic inhibitors has been undertaken by many scientific groups. We started our work from the development of in silico methodology for the design of novel BACE-1 ligands. It was validated on the basis of crystal structures of complexes with inhibitors, redocking, cross-docking and training/test sets of reference ligands. The presented procedure of assessment of the novel compounds as β-secretase inhibitors could be widely used in the design process.

Alzheimer's disease: identification and development of β-secretase (BACE-1) binding fragments and inhibitors by dynamic ligation screening (DLS)

The application of dynamic ligation screening (DLS), a methodology for fragment-based drug discovery (FBDD), to the aspartic protease β-secretase (BACE-1) is reported. For this purpose, three new fluorescence resonance energy transfer (FRET) substrates were designed and synthesized. Their kinetic parameters (Vmax , KM , and kcat ) were determined and compared with a commercial substrate. Secondly, a peptide aldehyde was designed as a chemically reactive inhibitor (CRI) based on the Swedish mutation substrate sequence. Incubation of this CRI with the protease, a FRET substrate, and one amine per well taken from an amine library, which was assembled by a maximum common substructure (MCS) approach, revealed the fragment 3-(3-aminophenyl)-2H-chromen-2-one (1) to be a competitive BACE-1 inhibitor that enhanced the activity of the CRI. Irreversibly formed fragment combination products of 1 with the initial peptide sequence were active and confirmed the targeting of the active site through the ethane-1,2-diamine isostere. Finally, structure-assisted combination of fragment 1 with secondary fragments that target the S1 site in hit optimization yielded novel, entirely fragment-based BACE-1 inhibitors with up to 30-fold improved binding affinity. Interactions with the protein were explained by molecular modeling studies, which indicate that the new fragment combinations interact with the catalytic aspartic acid dyad, as well as with the adjacent binding sites required for potency.

Novel peptidomimetics as BACE-1 inhibitors: synthesis, molecular modeling, and biological studies

Aiming at identifying new scaffolds for BACE-1 inhibition devoid of the pharmacokinetic drawbacks of peptide-like structures, we investigated a series of novel peptidomimetics based on a 1,4-benzodiazepine (BDZ) core 1a-h and their seco-analogues 2a-d. We herein discuss synthesis, molecular modeling and in vitro studies which, starting from 1a, led to the seco-analogues (R)-2c and (S)-2d endowed with BACE-1 inhibition properties in the micromolar range both on the isolated enzyme and in cellular studies. These data can encourage to pursue these analogues as hits for the development of a new series of BACE-1 inhibitors active on whole-cells.

Protein flexibility in virtual screening: the BACE-1 case study

Simulating protein flexibility is a major issue in the docking-based drug-design process for which a single methodological solution does not exist. In our search of new anti-Alzheimer ligands, we were faced with the challenge of including receptor plasticity in a virtual screening campaign aimed at finding new β-secretase inhibitors. To this aim, we incorporated protein flexibility in our simulations by using an ensemble of static X-ray enzyme structures to screen the National Cancer Institute database. A unified description of the protein motion was also generated by computing and combining a set of grid maps using an energy weighting scheme. Such a description was used in an energy-weighted virtual screening experiment on the same molecular database. Assessment of the enrichment factors from these two virtual screening approaches demonstrated comparable predictive powers, with the energy-weighted method being faster than the ensemble method. The in vitro evaluation demonstrated that out of the 32 tested ligands, 17 featured the predicted enzyme inhibiting property. Such an impressive success rate (53.1%) demonstrates the enhanced power of the two methodologies and suggests that energy-weighted virtual screening is a more than valid alternative to ensemble virtual screening given its reduced computational demands and comparable performance.

Combining dyad protonation and active site plasticity in BACE-1 structure-based drug design

The ability of the BACE-1 catalytic dyad to adopt multiple protonation states and the conformational flexibility of the active site have hampered the reliability of computational screening campaigns carried out on this drug target for Alzheimer's disease. Here, we propose a protocol that, for the first time, combining quantum mechanical calculations, molecular dynamics, and conformational ensemble virtual ligand screening addresses these issues simultaneously. The encouraging results prefigure this approach as a valuable tool for future drug discovery campaigns.

Potential and limitations of ensemble docking

A major problem in structure-based virtual screening applications is the appropriate selection of a single or even multiple protein structures to be used in the virtual screening process. A priori it is unknown which protein structure(s) will perform best in a virtual screening experiment. We investigated the performance of ensemble docking, as a function of ensemble size, for eight targets of pharmaceutical interest. Starting from single protein structure docking results, for each ensemble size up to 500,000 combinations of protein structures were generated, and, for each ensemble, pose prediction and virtual screening results were derived. Comparison of single to multiple protein structure results suggests improvements when looking at the performance of the worst and the average over all single protein structures to the performance of the worst and average over all protein ensembles of size two or greater, respectively. We identified several key factors affecting ensemble docking performance, including the sampling accuracy of the docking algorithm, the choice of the scoring function, and the similarity of database ligands to the cocrystallized ligands of ligand-bound protein structures in an ensemble. Due to these factors, the prospective selection of optimum ensembles is a challenging task, shown by a reassessment of published ensemble selection protocols.

Carbazole-containing arylcarboxamides as BACE1 inhibitors

β-Secretase (BACE1) is widely recognized as a prime drug target for the treatment of Alzheimer's disease (AD). In this Letter, we report the synthesis and the BACE1 inhibitory activity of novel, variously substituted N-[3-(9H-carbazol-9-yl)-2-hydroxypropyl]-arylcarboxamides. The best results have been obtained with the introduction of a 4-OMe substituent (IC(50)=3.8 μM) or a 3,4-dichloro substituent (IC(50)=2.5 μM) in the amidic aromatic ring. The blood-brain barrier penetration predictions resulted to be promising for this type of compounds. To better understand the structure-activity relationships (SAR) of the new derivatives, a docking study procedure has been applied exploiting different conformational and ionic states of BACE1.

Structure-based discovery of antibacterial drugs

The modern era of antibacterial chemotherapy began in the 1930s, and the next four decades saw the discovery of almost all the major classes of antibacterial agents that are currently in use. However, bacterial resistance to many of these drugs is becoming an increasing problem. As such, the discovery of drugs with novel modes of action will be vital to meet the threats created by the emergence of resistance. Success in discovering inhibitors using high-throughput screening of chemical libraries is rare. In this Review we explore the exciting opportunities for antibacterial-drug discovery arising from structure-based drug design.

Non-nucleoside inhibitors of human adenosine kinase: synthesis, molecular modeling, and biological studies

Adenosine kinase (AK) catalyzes the phosphorylation of adenosine (Ado) to AMP by means of a kinetic mechanism in which the two substrates Ado and ATP bind the enzyme in a binary and/or ternary complex, with distinct protein conformations. Most of the described inhibitors have Ado-like structural motifs and are nonselective, and some of them (e.g., the tubercidine-like ligands) are characterized by a toxic profile. We have cloned and expressed human AK (hAK) and searched for novel non-substrate-like inhibitors. Our efforts to widen the structural diversity of AK inhibitors led to the identification of novel non-nucleoside, noncompetitive allosteric modulators characterized by a unique molecular scaffold. Among the pyrrolobenzoxa(thia)zepinones (4a-qq) developed, 4a was identified as a non-nucleoside prototype hAK inhibitor. 4a has proapoptotic efficacy, slight inhibition of short-term RNA synthesis, and cytostatic activity on tumor cell lines while showing low cytotoxicity and no significant adverse effects on short-term DNA synthesis in cells.

Improving database enrichment through ensemble docking

While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.