Design of Novel Series of Antimalarial PMX Inhibitors with Increased Half-Life via Molecular Property Optimization.

Plasmepsin X (PMX) has been identified as a multistage antimalarial target. PMX is a malarial aspartyl protease essential for merozoite egress from infected red blood cells and invasion of the host erythrocytes. Previously, we reported the identification of PMX inhibitors by structure-based optimization of a cyclic guanidine core. Preclinical assessment of UCB7362, which displayed both in vitro and in vivo antimalarial activity, revealed a suboptimal dose paradigm (once daily dosing of 50 mg for 7 days for treatment of uncomplicated malaria) relative to current standard of care (three-dose regime). We report here the efforts toward extending the half-life (t1/2) by reducing metabolic clearance and increasing volume of distribution (Vss). Our efforts culminated in the identification of a biaryl series, with an expected longer t1/2 in human than UCB7362 while maintaining a similar in vitro off-target hit rate.

Water Networks in Complexes between Proteins and FDA-Approved Drugs.

Water molecules at protein-ligand interfaces are often of significant pharmaceutical interest, owing in part to the entropy which can be released upon the displacement of an ordered water by a therapeutic compound. Protein structures may not, however, completely resolve all critical bound water molecules, or there may be no experimental data available. As such, predicting the location of water molecules in the absence of a crystal structure is important in the context of rational drug design. Grand canonical Monte Carlo (GCMC) is a computational technique that is gaining popularity for the simulation of buried water sites. In this work, we assess the ability of GCMC to accurately predict water binding locations, using a dataset that we have curated, containing 108 unique structures of complexes between proteins and Food and Drug Administration (FDA)-approved small-molecule drugs. We show that GCMC correctly predicts 81.4% of nonbulk crystallographic water sites to within 1.4 Å. However, our analysis demonstrates that the reported performance of water prediction methods is highly sensitive to the way in which the performance is measured. We also find that crystallographic water sites with more protein/ligand hydrogen bonds and stronger electron density are more reliably predicted by GCMC. An analysis of water networks revealed that more than half of the structures contain at least one ligand-contacting water network. In these cases, displacement of a water site by a ligand modification might yield unexpected results if the larger network is destabilized. Cooperative effects between waters should therefore be explicitly considered in structure-based drug design.

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein-Ligand Binding Poses.

Predicting the correct pose of a ligand binding to a protein and its associated binding affinity is of great importance in computer-aided drug discovery. A number of approaches have been developed to these ends, ranging from the widely used fast molecular docking to the computationally expensive enhanced sampling molecular simulations. In this context, methods such as coarse-grained metadynamics and binding pose metadynamics (BPMD) use simulations with metadynamics biasing to probe the binding affinity without trying to fully converge the binding free energy landscape in order to decrease the computational cost. In BPMD, the metadynamics bias perturbs the ligand away from the initial pose. The resistance of the ligand to this bias is used to calculate a stability score. The method has been shown to be useful in reranking predicted binding poses from docking. Here, we present OpenBPMD, an open-source Python reimplementation and reinterpretation of BPMD. OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. We also investigated the role of accurate water positioning on the performance of the algorithm and showed how the combination with a grand-canonical Monte Carlo algorithm improves the accuracy of the predictions.

Discovery and Characterization of Potent, Efficacious, Orally Available Antimalarial Plasmepsin X Inhibitors and Preclinical Safety Assessment of UCB7362.

Plasmepsin X (PMX) is an essential aspartyl protease controlling malaria parasite egress and invasion of erythrocytes, development of functional liver merozoites (prophylactic activity), and blocking transmission to mosquitoes, making it a potential multistage drug target. We report the optimization of an aspartyl protease binding scaffold and the discovery of potent, orally active PMX inhibitors with in vivo antimalarial efficacy. Incorporation of safety evaluation early in the characterization of PMX inhibitors precluded compounds with a long human half-life (t1/2) to be developed. Optimization focused on improving the off-target safety profile led to the identification of UCB7362 that had an improved in vitro and in vivo safety profile but a shorter predicted human t1/2. UCB7362 is estimated to achieve 9 log 10 unit reduction in asexual blood-stage parasites with once-daily dosing of 50 mg for 7 days. This work demonstrates the potential to deliver PMX inhibitors with in vivo efficacy to treat malaria.

Corrigendum: Higher Affinity Antibodies Bind With Lower Hydration and Flexibility in Large Scale Simulations.

[This corrects the article DOI: 10.3389/fimmu.2022.884110.].

Rings in Clinical Trials and Drugs: Present and Future.

We present a comprehensive analysis of all ring systems (both heterocyclic and nonheterocyclic) in clinical trial compounds and FDA-approved drugs. We show 67% of small molecules in clinical trials comprise only ring systems found in marketed drugs, which mirrors previously published findings for newly approved drugs. We also show there are approximately 450 000 unique ring systems derived from 2.24 billion molecules currently available in synthesized chemical space, and molecules in clinical trials utilize only 0.1% of this available pool. Moreover, there are fewer ring systems in drugs compared with those in clinical trials, but this is balanced by the drug ring systems being reused more often. Furthermore, systematic changes of up to two atoms on existing drug and clinical trial ring systems give a set of 3902 future clinical trial ring systems, which are predicted to cover approximately 50% of the novel ring systems entering clinical trials.

Higher Affinity Antibodies Bind With Lower Hydration and Flexibility in Large Scale Simulations.

We have carried out a long-timescale simulation study on crystal structures of nine antibody-antigen pairs, in antigen-bound and antibody-only forms, using molecular dynamics with enhanced sampling and an explicit water model to explore interface conformation and hydration. By combining atomic level simulation and replica exchange to enable full protein flexibility, we find significant numbers of bridging water molecules at the antibody-antigen interface. Additionally, a higher proportion of interactions excluding bulk waters and a lower degree of antigen bound CDR conformational sampling are correlated with higher antibody affinity. The CDR sampling supports enthalpically driven antibody binding, as opposed to entropically driven, in that the difference between antigen bound and unbound conformations do not correlate with affinity. We thus propose that interactions with waters and CDR sampling are aspects of the interface that may moderate antibody-antigen binding, and that explicit hydration and CDR flexibility should be considered to improve antibody affinity prediction and computational design workflows.

The Chemical Synthesis of Knob Domain Antibody Fragments.

Cysteine-rich knob domains found in the ultralong complementarity determining regions of a subset of bovine antibodies are capable of functioning autonomously as 3-6 kDa peptides. While they can be expressed recombinantly in cellular systems, in this paper we show that knob domains are also readily amenable to a chemical synthesis, with a co-crystal structure of a chemically synthesized knob domain in complex with an antigen showing structural equivalence to the biological product. For drug discovery, following the immunization of cattle, knob domain peptides can be synthesized directly from antibody sequence data, combining the power and diversity of the bovine immune repertoire with the ability to rapidly incorporate nonbiological modifications. We demonstrate that, through rational design with non-natural amino acids, a paratope diversity can be massively expanded, in this case improving the efficacy of an allosteric peptide. As a potential route to further improve stability, we also performed head-to-tail cyclizations, exploiting the proximity of the N and C termini to synthesize functional, fully cyclic antibody fragments. Lastly, we highlight the stability of knob domains in plasma and, through pharmacokinetic studies, use palmitoylation as a route to extend the plasma half-life of knob domains in vivo. This study presents an antibody-derived medicinal chemistry platform, with protocols for solid-phase synthesis of knob domains, together with the characterization of their molecular structures, in vitro pharmacology, and pharmacokinetics.

Water molecules at protein-drug interfaces: computational prediction and analysis methods.

The fundamental importance of water molecules at drug-protein interfaces is now widely recognised and a significant feature in structure-based drug design. Experimental methods for analysing the role of water in drug binding have many challenges, including the accurate location of bound water molecules in crystal structures, and problems in resolving specific water contributions to binding thermodynamics. Computational analyses of binding site water molecules provide an alternative, and in principle complete, structural and thermodynamic picture, and their use is now commonplace in the pharmaceutical industry. In this review, we describe the computational methodologies that are available and discuss their strengths and weaknesses. Additionally, we provide a critical analysis of the experimental data used to validate the methods, regarding the type and quality of experimental structural data. We also discuss some of the fundamental difficulties of each method and suggest directions for future study.

Insight into small molecule binding to the neonatal Fc receptor by X-ray crystallography and 100 kHz magic-angle-spinning NMR.

Aiming at the design of an allosteric modulator of the neonatal Fc receptor (FcRn)-Immunoglobulin G (IgG) interaction, we developed a new methodology including NMR fragment screening, X-ray crystallography, and magic-angle-spinning (MAS) NMR at 100 kHz after sedimentation, exploiting very fast spinning of the nondeuterated soluble 42 kDa receptor construct to obtain resolved proton-detected 2D and 3D NMR spectra. FcRn plays a crucial role in regulation of IgG and serum albumin catabolism. It is a clinically validated drug target for the treatment of autoimmune diseases caused by pathogenic antibodies via the inhibition of its interaction with IgG. We herein present the discovery of a small molecule that binds into a conserved cavity of the heterodimeric, extracellular domain composed of an α-chain and ß2-microglobulin (ß2m) (FcRnECD, 373 residues). X-ray crystallography was used alongside NMR at 100 kHz MAS with sedimented soluble protein to explore possibilities for refining the compound as an allosteric modulator. Proton-detected MAS NMR experiments on fully protonated [13C,15N]-labeled FcRnECD yielded ligand-induced chemical-shift perturbations (CSPs) for residues in the binding pocket and allosteric changes close to the interface of the two receptor heterodimers present in the asymmetric unit as well as potentially in the albumin interaction site. X-ray structures with and without ligand suggest the need for an optimized ligand to displace the α-chain with respect to ß2m, both of which participate in the FcRnECD-IgG interaction site. Our investigation establishes a method to characterize structurally small molecule binding to nondeuterated large proteins by NMR, even in their glycosylated form, which may prove highly valuable for structure-based drug discovery campaigns.

Discovery of a junctional epitope antibody that stabilizes IL-6 and gp80 protein:protein interaction and modulates its downstream signaling.

Protein:protein interactions are fundamental in living organism homeostasis. Here we introduce VHH6, a junctional epitope antibody capable of specifically recognizing a neo-epitope when two proteins interact, albeit transiently, to form a complex. Orthogonal biophysical techniques have been used to prove the "junctional epitope" nature of VHH6, a camelid single domain antibody recognizing the IL-6-gp80 complex but not the individual components alone. X-ray crystallography, HDX-MS and SPR analysis confirmed that the CDR regions of VHH6 interact simultaneously with IL-6 and gp80, locking the two proteins together. At the cellular level, VHH6 was able to alter the response of endothelial cells to exogenous IL-6, promoting a sustained STAT3 phosphorylation signal, an accumulation of IL-6 in vesicles and an overall pro-inflammatory phenotype supported further by transcriptomic analysis. Junctional epitope antibodies, like VHH6, not only offer new opportunities in screening and structure-aided drug discovery, but could also be exploited as therapeutics to modulate complex protein:protein interactions.

Computational design of an epitope-specific Keap1 binding antibody using hotspot residues grafting and CDR loop swapping.

Therapeutic and diagnostic applications of monoclonal antibodies often require careful selection of binders that recognize specific epitopes on the target molecule to exert a desired modulation of biological function. Here we present a proof-of-concept application for the rational design of an epitope-specific antibody binding with the target protein Keap1, by grafting pre-defined structural interaction patterns from the native binding partner protein, Nrf2, onto geometrically matched positions of a set of antibody scaffolds. The designed antibodies bind to Keap1 and block the Keap1-Nrf2 interaction in an epitope-specific way. One resulting antibody is further optimised to achieve low-nanomolar binding affinity by in silico redesign of the CDRH3 sequences. An X-ray co-crystal structure of one resulting design reveals that the actual binding orientation and interface with Keap1 is very close to the design model, despite an unexpected CDRH3 tilt and VH/VL interface deviation, which indicates that the modelling precision may be improved by taking into account simultaneous CDR loops conformation and VH/VL orientation optimisation upon antibody sequence change. Our study confirms that, given a pre-existing crystal structure of the target protein-protein interaction, hotspots grafting with CDR loop swapping is an attractive route to the rational design of an antibody targeting a pre-selected epitope.

Combining Molecular Scaffolds from FDA Approved Drugs: Application to Drug Discovery.

We have enumerated all linear combinations of ring systems from FDA approved drugs, up to three rings in length and up to four bonds linkers to give an in silico database of approximately 14 million molecules. This virtual library was compared with molecular databases of published and commercially available compounds to assess the prevalence of drug ring combinations in modern medicinal chemistry and to identify areas of under-represented, but clinically validated, chemical space. From the 10 trillion molecular comparisons, we found that less than 1% of the possible combinations of drug ring systems appear in commercially available libraries. This key observation highlights significant opportunities to design new fragment-like and lead-like libraries aimed at improving success rates and reducing risk in small molecule drug discovery, as, based on our previous analysis ( Taylor J. Med. Chem. 2014 , 57 , 5845 - 5849 ), approximately 70% of all new drugs are made up of only ring systems that have been used in existing drugs.

Rings in drugs.

We have analyzed the rings, ring systems, and frameworks in drugs listed in the FDA Orange Book to understand the frequency, timelines, molecular property space, and the application of these rings in different therapeutic areas and target classes. This analysis shows that there are only 351 ring systems and 1197 frameworks in drugs that came onto the market before 2013. Furthermore, on average six new ring systems enter drug space each year and approximately 28% of new drugs contain a new ring system. Moreover, it is very unusual for a drug to contain more than one new ring system and the majority of the most frequently used ring systems (83%) were first used in drugs developed prior to 1983. These observations give insight into the chemical novelty of drugs and potentially efficient ways to assess compound libraries and develop compounds from hit identification to lead optimization and beyond.

Structure-based virtual screening for novel ligands.

Computational searches for novel ligands for a given protein binding site have become ubiquitous in the pharmaceutical industry, and are potentially equally useful in helping identify small-molecule tools for biology. Here we describe the steps needed to carry out a high-throughput docking (HTD) or three-dimensional (3D) pharmacophore virtual screen starting with a model of the target protein's structure. The advice given is, in most cases, software independent but some tips are provided which apply only to certain popular programs. Useful work can be carried out using free programs on a modest workstation. Of course, any resultant "hits" remain in the virtual world until they are experimentally tested.

Novel potent BRAF inhibitors: toward 1 nM compounds through optimization of the central phenyl ring.

BRAF, a serine/threonine specific protein kinase that is part of the MAPK pathway and acts as a downstream effector of RAS, is a potential therapeutic target in melanoma. We have developed a series of small-molecule BRAF inhibitors based on a 1H-imidazo[4,5-b]pyridine-2(3H)-one scaffold (ring A) as the hinge binding moiety and a number of substituted phenyl rings C that interact with the allosteric binding site. The introduction of various groups on the central phenyl ring B combined with appropriate A- and C-ring modifications afford very potent compounds that inhibit (V600E)BRAF kinase activity in vitro and oncogenic BRAF signaling in melanoma cells. Substitution on the central phenyl ring of a 3-fluoro, a naphthyl, or a 3-thiomethyl group improves activity to yield compounds with an IC(50) of 1 nM for purified (V600E)BRAF and nanomolar activity in cells.

Pyridoimidazolones as novel potent inhibitors of v-Raf murine sarcoma viral oncogene homologue B1 (BRAF).

BRAF is a serine/threonine kinase that is mutated in a range of cancers, including 50-70% of melanomas, and has been validated as a therapeutic target. We have designed and synthesized mutant BRAF inhibitors containing pyridoimidazolone as a new hinge-binding scaffold. Compounds have been obtained which have low nanomolar potency for mutant BRAF (12 nM for compound 5i) and low micromolar cellular potency against a mutant BRAF melanoma cell line, WM266.4. The series benefits from very low metabolism, and pharmacokinetics (PK) that can be modulated by methylation of the NH groups of the imidazolone, resulting in compounds with fewer H-donors and a better PK profile. These compounds have great potential in the treatment of mutant BRAF melanomas.

Efficient Generalized Born Models for Monte Carlo Simulations.

The Generalized Born Surface Area theory (GBSA) has become a popular method to model the solvation of biomolecules. While efficient in the context of molecular dynamics simulations, GBSA calculations do not integrate well with Monte Carlo simulations because of the nonlocal nature of the Generalized Born energy. We present a method by which Monte Carlo Generalized Born simulations can be made seven to eight times faster on a protein-ligand binding free energy calculation with little or no loss of accuracy. The method can be employed in any type of Monte Carlo or Hybrid Monte Carlo-molecular dynamics simulation and should prove useful in numerous applications.

Principal atrial fibrillation discharges by the new ACC/AHA/ESC classification.

BACKGROUND: The American College of Cardiology, American Heart Association, and European Society of Cardiology Board (ACC/AHA/ESC) 2001 guidelines for management of patients with atrial fibrillation (AF) include a new classification system consisting of 4 categories: first-detected episode; recurrent paroxysmal (self-terminating); recurrent persistent (requiring cardioversion); and permanent. The frequency of hospital discharges within these categories has not been reported. METHODS: The new classification system was applied to 135 consecutive hospital discharges with a principal diagnosis of AF. RESULTS: Classification of AF in these discharged patients included 74 (55%) with first-detected episode; 28 (21%) with recurrent paroxysmal AF; 17 (13%) with recurrent persistent AF; and 16 (12%) with permanent AF. Hypertension (n = 48; 35%) was the most common primary cause of AF, followed by alcohol related (n = 23; 17%), coronary artery disease (n = 20; 15%), and valvular heart disease (n = 17; 12%). For the 102 patients with first-detected and recurrent paroxysmal AF, 71 (69%) converted spontaneously to normal sinus rhythm within 48 hours of admission. Of the 48 patients with a discharge diagnosis of AF, 32 (67%) were receiving anticoagulation therapy. CONCLUSIONS: Most hospital discharges with a principal diagnosis of AF represent the first-detected episode. Diverse causes contribute to AF, and to examine them would help direct therapy. Importantly, in our analysis, 69% of those patients with first-detected or recurrent paroxysmal AF converted spontaneously to normal sinus rhythm within 48 hours of admission.

Modeling water molecules in protein-ligand docking using GOLD.

We implemented a novel approach to score water mediation and displacement in the protein-ligand docking program GOLD. The method allows water molecules to switch on and off and to rotate around their three principal axes. A constant penalty, sigma(p), representing the loss of rigid-body entropy, is added for water molecules that are switched on, hence rewarding water displacement. We tested the methodology in an extensive validation study. First, sigma(p) is optimized against a training set of 58 protein-ligand complexes. For this training set, our algorithm correctly predicts water mediation/displacement in approximately 92% of the cases. We observed small improvements in the quality of the predicted binding modes for water-mediated complexes. In the second part of this work, an entirely independent set of 225 complexes is used. For this test set, our algorithm correctly predicts water mediation/displacement in approximately 93% of the cases. Improvements in binding mode quality were observed for individual water-mediated complexes.