David J. Huggins

Rational approaches to improving selectivity in drug design.

David J. Huggins,*,†,‡,∞ Woody Sherman,* and Bruce Tidor* †Department of Oncology, Hutchison/MRC Research Centre, University of Cambridge, Hills Road, Cambridge, CB2 0XZ, United Kingdom ‡Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom Schrödinger Inc., 120 West 45th Street, New York, New York 10036, United States Computer Science and Artificial Intelligence Laboratory, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States

Rational Approaches to Improving Selectivity in Drug Design

David J. Huggins,*,†,‡,∞ Woody Sherman,* and Bruce Tidor* †Department of Oncology, Hutchison/MRC Research Centre, University of Cambridge, Hills Road, Cambridge, CB2 0XZ, United Kingdom ‡Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom Schrödinger Inc., 120 West 45th Street, New York, New York 10036, United States Computer Science and Artificial Intelligence Laboratory, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States

Rational Methods for the Selection of Diverse Screening Compounds

Traditionally a pursuit of large pharmaceutical companies, high-throughput screening assays are becoming increasingly common within academic and government laboratories. This shift has been instrumental in enabling projects that have not been commercially viable, such as chemical probe discovery and screening against high-risk targets. Once an assay has been prepared and validated, it must be fed with screening compounds. Crafting a successful collection of small molecules for screening poses a significant challenge. An optimized collection will minimize false positives while maximizing hit rates of compounds that are amenable to lead generation and optimization. Without due consideration of the relevant protein targets and the downstream screening assays, compound filtering and selection can fail to explore the great extent of chemical diversity and eschew valuable novelty. Herein, we discuss the different factors to be considered and methods that may be employed when assembling a structurally diverse compound collection for screening. Rational methods for selecting diverse chemical libraries are essential for their effective use in high-throughput screens.

Characterization and tissue‐specific expression of two lepidopteran farnesyl diphosphate synthase homologs: Implications for the biosynthesis of ethyl‐substituted juvenile hormones

The sesquiterpenoid juvenile hormone (JH) regulates insect development and reproduction. Most insects produce only one chemical form of JH, but the Lepidoptera produce four derivatives featuring ethyl branches. The biogenesis of these JHs requires the synthesis of ethyl‐substituted farnesyl diphosphate (FPP) by FPP synthase (FPPS). To determine if there exist more than one lepidopteran FPPS, and whether one FPPS homolog is better adapted for binding the bulkier ethyl‐branched substrates/products, we cloned three lepidopteran FPPS cDNAs, two from Choristoneura fumiferana and one from Pseudaletia unipuncta. Amino acid sequence comparisons among these and other eukaryotic FPPSs led to the recognition of two lepidopteran FPPS types. Type‐I FPPSs display unique active site substitutions, including several in and near the first aspartate‐rich motif, whereas type‐II proteins have a more “conventional” catalytic cavity. In a yeast assay, a Drosophila FPPS clone provided full complementation of an FPPS mutation, but lepidopteran FPPS clones of either type yielded only partial complementation, suggesting unusual catalytic features and/or requirements of these enzymes. Although a structural analysis of lepidopteran FPPS active sites suggested that type‐I enzymes are better suited than type‐II for generating ethyl‐substituted products, a quantitative real‐time PCR assessment of their relative abundance in insect tissues indicated that type‐I expression is ubiquitous whereas that of type‐II is essentially confined to the JH‐producing glands, where its transcripts are ∼20 times more abundant than those of type‐I. These results suggest that type‐II FPPS plays a leading role in lepidopteran JH biosynthesis in spite of its apparently more conventional catalytic cavity. Proteins 2006.

PARP1-dependent recruitment of KDM4D histone demethylase to DNA damage sites promotes double-strand break repair

Significance Sophisticated DNA damage repair mechanisms are required to fix DNA lesions and preserve the integrity of the genome. This manuscript provides characterization of KDM4D role in promoting the repair of double-strand breaks (DSBs). Our findings show that KDM4D lysine demethylase is swiftly recruited to DNA breakage sites via its C-terminal region in a PARP1-dependent manner. Further, we have uncovered an exciting function of KDM4D in regulating the association of the DNA damage response master kinase, ATM, with chromatin, thus explaining the defective phosphorylation of ATM substrates found in KDM4D-depleted cells. Altogether, this study advances our understanding of the molecular mechanisms that regulate the repair of DSBs, a critical pathway that is essential for maintaining genome integrity. Members of the lysine (K)-specific demethylase 4 (KDM4) A–D family of histone demethylases are dysregulated in several types of cancer. Here, we reveal a previously unrecognized role of KDM4D in the DNA damage response (DDR). We show that the C-terminal region of KDM4D mediates its rapid recruitment to DNA damage sites. Interestingly, this recruitment is independent of the DDR sensor ataxia telangiectasia mutated (ATM), but dependent on poly (ADP-ribose) polymerase 1 (PARP1), which ADP ribosylates KDM4D after damage. We demonstrate that KDM4D is required for efficient phosphorylation of a subset of ATM substrates. We note that KDM4D depletion impairs the DNA damage-induced association of ATM with chromatin, explaining its effect on ATM substrate phosphorylation. Consistent with an upstream role in DDR, KDM4D knockdown disrupts the damage-induced recombinase Rad51 and tumor protein P53 binding protein foci formation. Consequently, the integrity of homology-directed repair and nonhomologous end joining of DNA breaks is impaired in KDM4D-deficient cells. Altogether, our findings implicate KDM4D in DDR, furthering the links between the cancer-relevant networks of epigenetic regulation and genome stability.

Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions

Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs.

Correlations in liquid water for the TIP3P-Ewald, TIP4P-2005, TIP5P-Ewald, and SWM4-NDP models

Water is one of the simplest molecules in existence, but also one of the most important in biological and engineered systems. However, understanding the structure and dynamics of liquid water remains a major scientific challenge. Molecular dynamics simulations of liquid water were performed using the water models TIP3P-Ewald, TIP4P-2005, TIP5P-Ewald, and SWM4-NDP to calculate the radial distribution functions (RDFs), the relative angular distributions, and the excess enthalpies, entropies, and free energies. In addition, lower-order approximations to the entropy were considered, identifying the fourth-order approximation as an excellent estimate of the full entropy. The second-order and third-order approximations are ~20% larger and smaller than the true entropy, respectively. All four models perform very well in predicting the radial distribution functions, with the TIP5P-Ewald model providing the best match to the experimental data. The models also perform well in predicting the excess entropy, enthalpy, and free energy of liquid water. The TIP4P-2005 and SWM4-NDP models are more accurate than the TIP3P-Ewald and TIP5P-Ewald models in this respect. However, the relative angular distribution functions of the four water models reveal notable differences. The TIP5P-Ewald model demonstrates an increased preference for water molecules to act both as tetrahedral hydrogen bond donors and acceptors, whereas the SWM4-NDP model demonstrates an increased preference for water molecules to act as planar hydrogen bond acceptors. These differences are not uncovered by analysis of the RDFs or the commonly employed tetrahedral order parameter. However, they are expected to be very important when considering water molecules around solutes and are thus a key consideration in modelling solvent entropy.

Thermodynamic Properties of Water Molecules at a Protein–Protein Interaction Surface

Protein–protein interactions (PPIs) have been identified as a vital regulator of cellular pathways and networks. However, the determinants that control binding affinity and specificity at protein surfaces are incompletely characterized and thus unable to be exploited for the purpose of developing PPI inhibitors to control cellular pathways in disease states. One of the key factors in intermolecular interactions that remains poorly understood is the role of water molecules and in particular the importance of solvent entropy. This factor is expected to be particularly important at protein surfaces, and the release of water molecules from hydrophobic regions is one of the most important drivers of PPIs. In this work, we have studied the protein surface of a mutant of the protein RadA to quantify the thermodynamics of surface water molecules. RadA and its human homologue RAD51 function as recombinases in the process of homologous recombination. RadA binds to itself to form oligomeric structures and thus contains a well-characterized protein–protein binding surface. Similarly, RAD51 binds either to itself to form oligomers or to the protein BRCA2 to form filaments. X-ray crystallography has determined that the same interface functions in both interactions. Work in our group has generated a partially humanized mutant of RadA, termed MAYM, which has been crystallized in the apo form. We studied this apo form of MAYM using a combination of molecular dynamics (MD) simulations and inhomogeneous fluid solvation theory (IFST). The method locates a number of the hydration sites observed in the crystal structure and locates hydrophobic sites where hydrophobic species are known to bind experimentally. The simulations also highlight the importance of the restraints placed on the protein in determining the results. Finally, the results identify a correlation between the predicted entropy of water molecules at a given site and the solvent-accessible surface area and suggest that correlations between water molecules only need to be considered for water molecules separated by less than 3.2 Å. The combination of MD and IFST has been used previously to study PPIs and represents one of the few existing methods to quantify solvent thermodynamics. This is a vital aspect of molecular recognition and one which we believe must be developed.

Quantifying the Entropy of Binding for Water Molecules in Protein Cavities by Computing Correlations

Protein structural analysis demonstrates that water molecules are commonly found in the internal cavities of proteins. Analysis of experimental data on the entropies of inorganic crystals suggests that the entropic cost of transferring such a water molecule to a protein cavity will not typically be greater than 7.0 cal/mol/K per water molecule, corresponding to a contribution of approximately +2.0 kcal/mol to the free energy. In this study, we employ the statistical mechanical method of inhomogeneous fluid solvation theory to quantify the enthalpic and entropic contributions of individual water molecules in 19 protein cavities across five different proteins. We utilize information theory to develop a rigorous estimate of the total two-particle entropy, yielding a complete framework to calculate hydration free energies. We show that predictions from inhomogeneous fluid solvation theory are in excellent agreement with predictions from free energy perturbation (FEP) and that these predictions are consistent with experimental estimates. However, the results suggest that water molecules in protein cavities containing charged residues may be subject to entropy changes that contribute more than +2.0 kcal/mol to the free energy. In all cases, these unfavorable entropy changes are predicted to be dominated by highly favorable enthalpy changes. These findings are relevant to the study of bridging water molecules at protein-protein interfaces as well as in complexes with cognate ligands and small-molecule inhibitors.

Assessing the Accuracy of Inhomogeneous Fluid Solvation Theory in Predicting Hydration Free Energies of Simple Solutes

Accurate prediction of hydration free energies is a key objective of any free energy method that is applied to modeling and understanding interactions in the aqueous phase. Inhomogeneous fluid solvation theory (IFST) is a statistical mechanical method for calculating solvation free energies by quantifying the effect of a solute acting as a perturbation to bulk water. IFST has found wide application in understanding hydration phenomena in biological systems, but quantitative applications have not been comprehensively assessed. In this study, we report the hydration free energies of six simple solutes calculated using IFST and independently using free energy perturbation (FEP). This facilitates a validation of IFST that is independent of the accuracy of the force field. The results demonstrate that IFST shows good agreement with FEP, with an R2 coefficient of determination of 0.99 and a mean unsigned difference of 0.7 kcal/mol. However, sampling is a major issue that plagues IFST calculations and the results suggest that a histogram method may require prohibitively long simulations to achieve convergence of the entropies, for bin sizes which effectively capture the underlying probability distributions. Results also highlight the sensitivity of IFST to the reference interaction energy of a water molecule in bulk, with a difference of 0.01 kcal/mol changing the predicted hydration free energies by approximately 2.4 kcal/mol for the systems studied here. One of the major advantages of IFST over perturbation methods such as FEP is that the systems are spatially decomposed to consider the contribution of specific regions to the total solvation free energies. Visualizing these contributions can yield detailed insights into solvation thermodynamics. An insight from this work is the identification and explanation of regions with unfavorable free energy density relative to bulk water. These regions contribute unfavorably to the hydration free energy. Further work is necessary before IFST can be extended to yield accurate predictions of binding free energies, but the work presented here demonstrates its potential.