Epilogue to the Gerald Maggiora Festschrift: a tribute to an exemplary mentor, colleague, collaborator, and innovator.

In May 2022, JCAMD published a Special Issue in honor of Gerald (Gerry) Maggiora, whose scientific leadership over many decades advanced the fields of computational chemistry and chemoinformatics for drug discovery. Along the way, he has impacted many researchers in both academia and the pharmaceutical industry. In this Epilogue, we explain the origins of the Festschrift and present a series of first-hand vignettes, in approximate chronological sequence, that together paint a picture of this remarkable man. Whether they highlight Gerry's endless curiosity about molecular life sciences or his willingness to challenge conventional wisdom or his generous support of junior colleagues and peers, these colleagues and collaborators are united in their appreciation of his positive influence. These tributes also reflect key trends and themes during the evolution of modern drug discovery, seen through the lens of people who worked with a visionary leader. Junior scientists will find an inspiring roadmap for creative collegiality and collaboration.

Prediction of the Favorable Hydration Sites in a Protein Binding Pocket and Its Application to Scoring Function Formulation.

The important role of water molecules in protein-ligand binding energetics has attracted wide attention in recent years. A range of computational methods has been developed to predict the favorable locations of water molecules in a protein binding pocket. Most of the current methods are based on extensive molecular dynamics or Monte Carlo simulations. They are time-consuming and thus cannot be applied to high-throughput tasks. To overcome this difficulty, we have developed an empirical method, called HydraMap, to predict the favorable hydration sites in the binding pocket of a protein molecule. This method uses statistical potentials to quantify the interactions between protein atoms and water molecules. Such statistical potentials were derived from 10,987 crystal structures selected from the Protein Data Bank. The probability of placing a water probe at each spot in the binding pocket was evaluated to derive a density map. The density map was then deduced into explicit hydration sites through a clustering process. HydraMap was validated on two external test sets, where it produced comparable results as 3D-RISM and WATsite but was 30-1000 times faster. In addition, we have attempted to estimate the desolvation energy associated with water molecule replacement upon ligand binding based on the outcomes of HydraMap. This desolvation term, called DEWED, was incorporated into the framework of four scoring functions, i.e., ASP, ChemPLP, GoldScore, and X-Score. The derivative scoring functions were tested in terms of scoring power, docking power, and screening power on a range of data sets. It was observed that X-Score exhibited the most obvious improvement in accuracy after adding the DEWED terms. Moreover, all scoring functions augmented with the DEWED terms exhibited improved or comparable performance on most data sets as the corresponding ones augmented with the GB/SA terms. Our study has demonstrated the potential application of HydraMap and DEWED to the formulation of new scoring functions. A beta-version of the HydraMap software is freely available from our Web site (http://www.sioc-ccbg.ac.cn/software/hydramap/) for testing.

Computational Chemistry: A Rising Tide of Women.

The authors were inspired to explore the topic of gender diversity in computational chemistry on the basis of similar recent publications in the related fields of medicinal chemistry ( Huryn , D. M. ; et al. ACS Med. Chem. Lett. 2017 , 8 , 900 ) and computational biology ( Bonham , K. S. ; Stefan , M. I. PLoS Comput. Biol. 2017 , 13 , e1005134 ). To do so, we examined historical demographics in two different professional settings, i.e., attendance/participation at the Gordon Research Conferences on Computer-Aided Drug Design and Computational Chemistry and membership in the Computers in Chemistry Division of the American Chemical Society. We conclude that female representation in computational chemistry has risen steadily over the last 40 years and likely stands at around 25%, which appears to slightly exceed that of the neighboring fields of computer science and medicinal chemistry. In accordance with the old slogan that "a rising tide lifts all boats", here a rising tide of women scientists is having an impact on the field of computational chemistry. Tactics to ensure that this number continues to improve are highlighted.

The evolution of drug design at Merck Research Laboratories.

On October 5, 1981, Fortune magazine published a cover article entitled the "Next Industrial Revolution: Designing Drugs by Computer at Merck". With a 40+ year investment, we have been in the drug design business longer than most. During its history, the Merck drug design group has had several names, but it has always been in the "design" business, with the ultimate goal to provide an actionable hypothesis that could be tested experimentally. Often the result was a small molecule but it could just as easily be a peptide, biologic, predictive model, reaction, process, etc. To this end, the concept of design is now front and center in all aspects of discovery, safety assessment and early clinical development. At present, the Merck design group includes computational chemistry, protein structure determination, and cheminformatics. By bringing these groups together under one umbrella, we were able to align activities and capabilities across multiple research sites and departments. This alignment from 2010 to 2016 resulted in an 80% expansion in the size of the department, reflecting the increase in impact due to a significant emphasis across the organization to "design first" along the entire drug discovery path from lead identification (LID) to first in human (FIH) dosing. One of the major advantages of this alignment has been the ability to access all of the data and create an adaptive approach to the overall LID to FIH pathway for any modality, significantly increasing the quality of candidates and their probability of success. In this perspective, we will discuss how we crafted a new strategy, defined the appropriate phenotype for group members, developed the right skillsets, and identified metrics for success in order to drive continuous improvement. We will not focus on the tactical implementation, only giving specific examples as appropriate.

Discovery of Clinical Candidate NT-0796, a Brain-Penetrant and Highly Potent NLRP3 Inflammasome Inhibitor for Neuroinflammatory Disorders.

The NLRP3 inflammasome is a component of the innate immune system involved in the production of proinflammatory cytokines. Neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and amyotrophic lateral sclerosis, have been shown to have a component driven by NLRP3 inflammasome activation. Diseases such as these with large unmet medical needs have resulted in an interest in inhibiting the NLRP3 inflammasome as a potential pharmacological treatment, but to date, no marketed drugs specifically targeting NLRP3 have been approved. Furthermore, the requirement for CNS-penetrant molecules adds additional complexity to the search for NLRP3 inflammasome inhibitors suitable for clinical investigation of neuroinflammatory disorders. We designed a series of ester-substituted carbamate compounds as selective NLRP3 inflammasome inhibitors, leading to NT-0796, an isopropyl ester that undergoes intracellular conversion to NDT-19795, the carboxylic acid active species. NT-0796 was shown to be a potent and selective NLRP3 inflammasome inhibitor with demonstrated in vivo brain penetration.

Development of macrocyclic inhibitors of HCV NS3/4A protease with cyclic constrained P2-P4 linkers.

A series of macrocyclic compounds containing a cyclic constraint in the P2-P4 linker region have been discovered and shown to exhibit excellent HCV NS3/4a genotype 3a and genotype 1b R155K, A156T, A156V, and D168V mutant activity while maintaining high rat liver exposure. The effect of the constraint is most dramatic against gt 1b A156 mutants where ~20-fold improvements in potency are achieved by introduction of a variety of ring systems into the P2-P4 linker.

Development of potent macrocyclic inhibitors of genotype 3a HCV NS3/4A protease.

A series of macrocyclic compounds containing 2-substituted-quinoline moieties have been discovered and shown to exhibit excellent HCV NS3/4a genotype 3a and genotype 1b R155K mutant activity while maintaining the high rat liver exposure. Cyclization of the 2-substituted quinoline substituent led to a series of tricyclic P2 compounds which also display superb gt3a potency.

Discovery and Optimization of Triazolopyrimidinone Derivatives as Selective NLRP3 Inflammasome Inhibitors.

The NLRP3 inflammasome is a multiprotein complex that facilitates activation and release of the proinflammatory cytokines interleukin-1ß (IL-1ß) and IL-18 in response to infection or endogenous stimuli. It can be inappropriately activated by a range of danger signals resulting in chronic, low-grade inflammation underlying a multitude of diseases, such as Alzheimer's disease, Parkinson's disease, osteoarthritis, and gout. The discovery of potent and specific NLRP3 inhibitors could reduce the burden of several common morbidities. In this study, we identified a weakly potent triazolopyrimidone hit (1) following an in silico modeling exercise. This was optimized to furnish potent and selective small molecule NLRP3 inflammasome inhibitors. Compounds such as NDT-30805 could be useful tool molecules for a scaffold-hopping or pharmacophore generation project or used as leads toward the development of clinical candidates.

Discovery of Ethyl Ketone-Based Highly Selective HDACs 1, 2, 3 Inhibitors for HIV Latency Reactivation with Minimum Cellular Potency Serum Shift and Reduced hERG Activity.

We describe the discovery of histone deacetylase (HDACs) 1, 2, and 3 inhibitors with ethyl ketone as the zinc-binding group. These HDACs 1, 2, and 3 inhibitors have good enzymatic and cellular activity. Their serum shift in cellular potency has been minimized, and selectivity against hERG has been improved. They are also highly selective over HDACs 6 and 8. These inhibitors contain a variety of substituted heterocycles on the imidazole or oxazole scaffold. Compounds 31 and 48 stand out due to their good potency, high selectivity over HDACs 6 and 8, reduced hERG activity, optimized serum shift in cellular potency, and good rat and dog PK profiles.

Redefining the Histone Deacetylase Inhibitor Pharmacophore: High Potency with No Zinc Cofactor Interaction.

A novel series of histone deacetylase (HDAC) inhibitors lacking a zinc-binding moiety has been developed and described herein. HDAC isozyme profiling and kinetic studies indicate that these inhibitors display a selectivity preference for HDACs 1, 2, 3, 10, and 11 via a rapid equilibrium mechanism, and crystal structures with HDAC2 confirm that these inhibitors do not interact with the catalytic zinc. The compounds are nonmutagenic and devoid of electrophilic and mutagenic structural elements and exhibit off-target profiles that are promising for further optimization. The efficacy of this new class in biochemical and cell-based assays is comparable to the marketed HDAC inhibitors belinostat and vorinostat. These results demonstrate that the long-standing pharmacophore model of HDAC inhibitors requiring a metal binding motif should be revised and offers a distinct class of HDAC inhibitors.

Discovery of an Anion-Dependent Farnesyltransferase Inhibitor from a Phenotypic Screen.

By employing a phenotypic screen, a set of compounds, exemplified by 1, were identified which potentiate the ability of histone deacetylase inhibitor vorinostat to reverse HIV latency. Proteome enrichment followed by quantitative mass spectrometric analysis employing a modified analogue of 1 as affinity bait identified farnesyl transferase (FTase) as the primary interacting protein in cell lysates. This ligand-FTase binding interaction was confirmed via X-ray crystallography and temperature dependent fluorescence studies, despite 1 lacking structural and binding similarity to known FTase inhibitors. Although multiple lines of evidence established the binding interaction, these ligands exhibited minimal inhibitory activity in a cell-free biochemical FTase inhibition assay. Subsequent modification of the biochemical assay by increasing anion concentration demonstrated FTase inhibitory activity in this novel class. We propose 1 binds together with the anion in the active site to inhibit farnesyl transferase. Implications for phenotypic screening deconvolution and HIV reactivation are discussed.

Epsilon substituted lysinol derivatives as HIV-1 protease inhibitors.

A series of HIV-1 protease inhibitors containing an epsilon substituted lysinol backbone was synthesized. Two novel synthetic routes using N-boc-L-glutamic acid alpha-benzyl ester and 2,6-diaminopimelic acid were developed. Incorporation of this epsilon substituent enabled access to the S2 pocket of the enzyme, affording high potency inhibitors. Modeling studies and synthetic efforts suggest the potency increase is due to both conformational bias and van der Waals interactions with the S2 pocket.

Drug-like density: a method of quantifying the "bindability" of a protein target based on a very large set of pockets and drug-like ligands from the Protein Data Bank.

One approach to estimating the "chemical tractability" of a candidate protein target where we know the atomic resolution structure is to examine the physical properties of potential binding sites. A number of other workers have addressed this issue. We characterize ~290,000 "pockets" from ~42,000 protein crystal structures in terms of a three parameter "pocket space": volume, buriedness, and hydrophobicity. A metric DLID (drug-like density) measures how likely a pocket is to bind a drug-like molecule. This is calculated from the count of other pockets in its local neighborhood in pocket space that contain drug-like cocrystallized ligands and the count of total pockets in the neighborhood. Surprisingly, despite being defined locally, a global trend in DLID can be predicted by a simple linear regression on log(volume), buriedness, and hydrophobicity. Two levels of simplification are necessary to relate the DLID of individual pockets to "targets": taking the best DLID per Protein Data Bank (PDB) entry (because any given crystal structure can have many pockets), and taking the median DLID over all PDB entries for the same target (because different crystal structures of the same protein can vary because of artifacts and real conformational changes). We can show that median DLIDs for targets that are detectably homologous in sequence are reasonably similar and that median DLIDs correlate with the "druggability" estimate of Cheng et al. (Nature Biotechnology 2007, 25, 71-75).

Discovery of Highly Selective and Potent HDAC3 Inhibitors Based on a 2-Substituted Benzamide Zinc Binding Group.

The selectivity of histone deacetylase inhibitors (HDACis) is greatly impacted by the zinc binding groups. In an effort to search for novel zinc binding groups, we applied a parallel medicinal chemistry (PMC) strategy to quickly synthesize substituted benzamide libraries. We discovered a series containing 2-substituted benzamides as the zinc binding group which afforded highly selective and potent HDAC3 inhibitors, exemplified by compound 16 with a 2-methylthiobenzamide. Compound 16 inhibited HDAC3 with an IC50 of 30 nM and with unprecedented selectivity of >300-fold over all other HDAC isoforms. Interestingly, a subtle change of the 2-methylthio to a 2-hydroxy benzamide in 20 retains HDAC3 potency but loses all selectivity over HDAC 1 and 2. This significant difference in selectivity was rationalized by X-ray crystal structures of HDACis 16 and 20 bound to HDAC2, revealing different binding modes to the catalytic zinc ion. This series of HDAC3 selective inhibitors served as tool compounds for investigating the minimal set of HDAC isoforms that must be inhibited for the HIV latency activation in a Jurkat 2C4 cell model and potentially as leads for selective HDAC3 inhibitors for other indications.

Selective Class I HDAC Inhibitors Based on Aryl Ketone Zinc Binding Induce HIV-1 Protein for Clearance.

HIV persistence in latently infected, resting CD4+ T cells is broadly considered a barrier to eradicate HIV. Activation of the provirus using latency-reversing agents (LRAs) followed by immune-mediated clearance to purge reservoirs has been touted as a promising therapeutic approach. Histone deacetylases (HDACs) and histone acetyltransferases (HATs) control the acetylation level of lysine residues in histones to regulate the gene transcription. Several clinical HDAC inhibitors had been examined as LRAs, which induced HIV activation in vitro and in vivo. Here we report the discovery of a series of selective and potent class I HDAC inhibitors based on aryl ketones as a zinc binding group, which reversed HIV latency using a Jurkat model of HIV latency in 2C4 cells. The SAR led to the discovery of a highly selective class I HDAC inhibitor 10 with excellent potency. HDACi 10 induces the HIV gag P24 protein in patient latent CD4+ T cells.

A conformational constraint improves a beta-secretase inhibitor but for an unexpected reason.

During our ongoing efforts to develop a small molecule inhibitor targeting the beta-amyloid cleaving enzyme (BACE-1), we discovered a class of compounds bearing an aminoimidazole motif. Initial optimization led to potent compounds that have high Pgp efflux ratios. Crystal structure-aided design furnished conformationally constrained compounds that are both potent and have relatively low Pgp efflux ratios. Computational studies performed after these optimizations suggest that the introduction of the constraint enhances potency via additional hydrophobic interactions rather than conformational restriction.

Molecular modeling based approach to potent P2-P4 macrocyclic inhibitors of hepatitis C NS3/4A protease.

Molecular modeling of inhibitor bound full length HCV NS3/4A protease structures proved to be a valuable tool in the design of a new series of potent NS3 protease inhibitors. Optimization of initial compounds provided 25a. The in vitro activity and selectivity as well as the rat pharmacokinetic profile of 25a compare favorably with the data for other NS3/4A protease inhibitors currently in clinical development for the treatment of HCV.

PL-100, a novel HIV-1 protease inhibitor displaying a high genetic barrier to resistance: an in vitro selection study.

The development of new HIV inhibitors with distinct resistance profiles is essential in order to combat the development of multi-resistant viral strains. A drug discovery program based on the identification of compounds that are active against drug-resistant viruses has produced PL-100, a novel potent protease inhibitor (PI) that incorporates a lysine-based scaffold. A selection for resistance against PL-100 in cord blood mononuclear cells was performed, using the laboratory-adapted IIIb strain of HIV-1, and it was shown that resistance appears to develop slower against this compound than against amprenavir, which was studied as a control. Four mutations in protease (PR) were selected after 25 weeks: two flap mutations (K45R and M46I) and two novel active site mutations (T80I and P81S). Site-directed mutagenesis revealed that all four mutations were required to develop low-level resistance to PL-100, which is indicative of the high genetic barrier of the compound. Importantly, these mutations did not cause cross-resistance to currently marketed PIs. In contrast, the P81S mutation alone caused hypersensitivity to two other PIs, saquinavir (SQV) and nelfinavir (NFV). Analysis of p55Gag processing showed that a marked defect in protease activity caused by mutation P81S could only be compensated when K45R and M46I were present. These data correlated well with the replication capacity (RC) of the mutant viruses as measured by a standard viral growth assay, since only viruses containing all four mutations approached the RC of wild type virus. X-ray crystallography provided insight on the structural basis of the resistance conferred by the identified mutations.

Molecular Simulations Identify Binding Poses and Approximate Affinities of Stapled α-Helical Peptides to MDM2 and MDMX.

Traditionally, computing the binding affinities of proteins to even relatively small and rigid ligands by free-energy methods has been challenging due to large computational costs and significant errors. Here, we apply a new molecular simulation acceleration method called MELD (Modeling by Employing Limited Data) to study the binding of stapled α-helical peptides to the MDM2 and MDMX proteins. We employ free-energy-based molecular dynamics simulations (MELD-MD) to identify binding poses and calculate binding affinities. Even though stapled peptides are larger and more complex than most protein ligands, the MELD-MD simulations can identify relevant binding poses and compute relative binding affinities. MELD-MD appears to be a promising method for computing the binding properties of peptide ligands with proteins.