Molecular Recognition in a Diverse Set of Protein–Ligand Interactions Studied with Molecular Dynamics Simulations and End-Point Free Energy Calculations

End-point free energy calculations using MM-GBSA and MM-PBSA provide a detailed understanding of molecular recognition in protein–ligand interactions. The binding free energy can be used to rank-order protein–ligand structures in virtual screening for compound or target identification. Here, we carry out free energy calculations for a diverse set of 11 proteins bound to 14 small molecules using extensive explicit-solvent MD simulations. The structure of these complexes was previously solved by crystallography and their binding studied with isothermal titration calorimetry (ITC) data enabling direct comparison to the MM-GBSA and MM-PBSA calculations. Four MM-GBSA and three MM-PBSA calculations reproduced the ITC free energy within 1 kcal·mol^–1 highlighting the challenges in reproducing the absolute free energy from end-point free energy calculations. MM-GBSA exhibited better rank-ordering with a Spearman <i>ρ</i> of 0.68 compared to 0.40 for MM-PBSA with dielectric constant (ε = 1). An increase in ε resulted in significantly better rank-ordering for MM-PBSA (<i>ρ</i> = 0.91 for ε = 10), but larger ε significantly reduced the contributions of electrostatics, suggesting that the improvement is due to the nonpolar and entropy components, rather than a better representation of the electrostatics. The SVRKB scoring function applied to MD snapshots resulted in excellent rank-ordering (<i>ρ</i> = 0.81). Calculations of the configurational entropy using normal-mode analysis led to free energies that correlated significantly better to the ITC free energy than the MD-based quasi-harmonic approach, but the computed entropies showed no correlation with the ITC entropy. When the adaptation energy is taken into consideration by running separate simulations for complex, apo, and ligand (MM-PBSA_ADAPT), there is less agreement with the ITC data for the individual free energies, but remarkably good rank-ordering is observed (<i>ρ</i> = 0.89). Interestingly, filtering MD snapshots by prescoring protein–ligand complexes with a machine learning-based approach (SVMSP) resulted in a significant improvement in the MM-PBSA results (ε = 1) from <i>ρ</i> = 0.40 to <i>ρ</i> = 0.81. Finally, the nonpolar components of MM-GBSA and MM-PBSA, but not the electrostatic components, showed strong correlation to the ITC free energy; the computed entropies did not correlate with the ITC entropy

Development of Selective Inhibitors for Aldehyde Dehydrogenases Based on Substituted Indole-2,3-diones

Aldehyde dehydrogenases (ALDH) participate in multiple metabolic pathways and have been indicated to play a role in several cancerous disease states. Our laboratory is interested in developing novel and selective ALDH inhibitors. We looked to further work recently published by developing a class of isoenzyme-selective inhibitors using similar indole-2,3-diones that exhibit differential inhibition of ALDH1A1, ALDH2, and ALDH3A1. Kinetic and X-ray crystallography data suggest that these inhibitors are competitive against aldehyde binding, forming direct interactions with active-site cysteine residues. The selectivity is precise in that these compounds appear to interact directly with the catalytic nucleophile, Cys243, in ALDH3A1 but not in ALDH2. In ALDH2, the 3-keto group is surrounded by the adjacent Cys301/303. Surprisingly, the orientation of the interaction changes depending on the nature of the substitutions on the basic indole ring structure and correlates well with the observed structure–activity relationships for each ALDH isoenzyme

Phylogeny of primate <i>ADH1</i> paralogs.

<p>Phylogeny of primate <i>ADH1</i> paralogs inferred from (A) exonic sequence data (“exonic tree”) and (B) intronic data (“intronic tree”). Parallel black lines indicate bifurcations associated with gene duplications without speciation. <i>ADH1</i> genes from New World monkeys (represented by marmoset) form a separate clade from the hominid/OWM genes in the exonic tree (A), while they interleave with hominid/OWM genes in the intronic tree (B). The lower panels, (C) and (D), redraw the gene tree from (A) and (B) in a species tree format, highlighting where each gene duplication occurs relative to the divergence of each primate lineage. The exonic tree is rooted using multiple non-primate <i>ADH1</i> genes (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041175#pone.0041175.s002" target="_blank">Figure S2</a>). The intronic tree is unrooted (due to ambiguity, see text). The names of <i>ADH1</i> paralogs have been shortened (e.g. the marmoset (<i>Callthrix jacchus</i>) ADH1 paralog “Cal_<i>ADH1.1”</i> is simply referred to as “marmoset ADH1.1”). Numbers at nodes refer to the Bayesian posterior probability values.</p

Average of pairwise distances for ADH1 intronic regions (shown in Table 1) among paralogs and between orthologs.

<p>Average of pairwise distances for ADH1 intronic regions (shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041175#pone-0041175-t001" target="_blank">Table 1</a>) among paralogs and between orthologs.</p

Pairwise distance estimates for orthologous intronic regions in a dataset composed of non-<i>ADH1</i> genes.

<p>Pairwise distance estimates for orthologous intronic regions in a dataset composed of non-<i>ADH1</i> genes.</p

Overview of primate phylogeny.

<p>An overview of primate phylogeny is shown, with the number of <i>ADH1</i> paralogs identified within select taxon indicated by the circled numbers at the leaves of the tree. Black numbers are derived from analysis of public databases, while red numbers were determined from cDNA sequencing reported here. The “4+1” designation for the macaque taxon indicates the presence of four <i>ADH1</i> paralogous genes plus one <i>ADH1</i> pseudogene. The genome sequencing projects are not completed for any lemur, so additional <i>ADH1</i> paralogs may be present (see text).</p

Estimate of the ADH1 paralog duplications relative to the time of the major primate speciation events.

<p>The average pairwise distances separating the introns of the <i>ADH1</i> paralogs were compared with the average pairwise distances separating a set of introns in paired taxa. (A) This schematic illustrates the various ortholog comparisons used to estimate the relative age among the ADH1 paralogs. (B) This plot summaries the data in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041175#pone-0041175-t002" target="_blank">Table 2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041175#pone-0041175-t003" target="_blank">3</a>. The distances among the <i>ADH1</i> paralogs in marmoset, macaque and human (black diamonds) are somewhat larger than those separating catarrhine and platyrrhine orthologs (green circles), implying that these <i>ADH1</i> paralogs diverged (duplicated) before the catarrhine-platyrrhine split. Conversely, distances separating the <i>ADH1</i> paralogs in marmoset, macaque and human are somewhat smaller than those separating orthologous introns among strepsirhine and haplorhine (red squares), implying that these <i>ADH1</i> paralogs diverged after the split between strepsirhine and haplorhine.</p

Gene duplication can generate “whole gene” and “chimeric gene” paralogs.

<p>(a) When unequal crossing-over (denoted with an “X”) occurs within the intergenic region between two paralogs, one chromosome gains an extra copy of a paralog, while the other chromosome loses one of the paralogs. This is followed by divergence of each paralog (only shown for the chromosome that gained a paralog and denoted as shift in color). A similar process can lead to the creation of the original paralog duplication, if, for example, transposons generate regions of sequence similarity on either side of a gene, thus enabling unequal crossing-over (not shown). (b) The same process can also lead to a chimeric gene duplicate if the crossing over occurs within the intragenic region (most likely within an intronic region).</p

Pairwise distance estimates of <i>ADH1</i> intronic regions.

<p>Pairwise distance among the <i>ADH1</i> paralogs for the concatenated intronic dataset were calculated using the Maximum Composite Likelihood method implemented by MEGAv4.0. Pairwise distances are shown in the lower left of the table, with variance estimates in the upper right of table.</p

Model of <i>ADH1</i> paralog duplication and subsequent evolution in haplorhines.

<p>Thin vertical black arrows indicate the direction of the chromosome while thick vertical arrows identify ADH genes in the direction of transcription, with <i>ADH1</i> paralogs in primates colored according to the intronic phylogeny in Fig. 2B. Dashed lines connect orthologs. Diagonal lines indicate the proposed phylogeny of haplorrhine <i>ADH1</i> paralogs. The root of the haplorhine <i>ADH1</i> tree is not specified because the duplication order of haplorhine <i>ADH1</i> paralogs is ambiguous (see text). Putative gene conversions are indicated with open circles connected by vertical lines (from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041175#pone-0041175-t004" target="_blank">Table 4</a>).</p