Visvaldas Kairys

HIV-1 Protease Inhibitors from Inverse Design in the Substrate Envelope Exhibit Subnanomolar Binding to Drug-Resistant Variants

The acquisition of drug-resistant mutations by infectious pathogens remains a pressing health concern, and the development of strategies to combat this threat is a priority. Here we have applied a general strategy, inverse design using the substrate envelope, to develop inhibitors of HIV-1 protease. Structure-based computation was used to design inhibitors predicted to stay within a consensus substrate volume in the binding site. Two rounds of design, synthesis, experimental testing, and structural analysis were carried out, resulting in a total of 51 compounds. Improvements in design methodology led to a roughly 1000-fold affinity enhancement to a wild-type protease for the best binders, from a Ki of 30-50 nM in round one to below 100 pM in round two. Crystal structures of a subset of complexes revealed a binding mode similar to each design that respected the substrate envelope in nearly all cases. All four best binders from round one exhibited broad specificity against a clinically relevant panel of drug-resistant HIV-1 protease variants, losing no more than 6-13-fold affinity relative to wild type. Testing a subset of second-round compounds against the panel of resistant variants revealed three classes of inhibitors: robust binders (maximum affinity loss of 14-16-fold), moderate binders (35-80-fold), and susceptible binders (greater than 100-fold). Although for especially high-affinity inhibitors additional factors may also be important, overall, these results suggest that designing inhibitors using the substrate envelope may be a useful strategy in the development of therapeutics with low susceptibility to resistance.

Screening drug-like compounds by docking to homology models: a systematic study.

In the absence of an experimentally solved structure, a homology model of a protein target can be used instead for virtual screening of drug candidates by docking and scoring. This approach poses a number of questions regarding the choice of the template to use in constructing the model, the accuracy of the screening results, and the importance of allowing for protein flexibility. The present study addresses such questions with compound screening calculations for multiple homology models of five drug targets. A central result is that docking to homology models frequently yields enrichments of known ligands as good as that obtained by docking to a crystal structure of the actual target protein. Interestingly, however, standard measures of the similarity of the template used to build the homology model to the targeted protein show little correlation with the effectiveness of the screening calculations, and docking to the template itself often is as successful as docking to the corresponding homology model. Treating key side chains as mobile produces a modest improvement in the results. The reasons for these sometimes unexpected results, and their implications for future methodologic development, are discussed.

Evaluating the substrate-envelope hypothesis: structural analysis of novel HIV-1 protease inhibitors designed to be robust against drug resistance.

ABSTRACT Drug resistance mutations in HIV-1 protease selectively alter inhibitor binding without significantly affecting substrate recognition and cleavage. This alteration in molecular recognition led us to develop the substrate-envelope hypothesis which predicts that HIV-1 protease inhibitors that fit within the overlapping consensus volume of the substrates are less likely to be susceptible to drug-resistant mutations, as a mutation impacting such inhibitors would simultaneously impact the processing of substrates. To evaluate this hypothesis, over 130 HIV-1 protease inhibitors were designed and synthesized using three different approaches with and without substrate-envelope constraints. A subset of 16 representative inhibitors with binding affinities to wild-type protease ranging from 58 nM to 0.8 pM was chosen for crystallographic analysis. The inhibitor-protease complexes revealed that tightly binding inhibitors (at the picomolar level of affinity) appear to “lock” into the protease active site by forming hydrogen bonds to particular active-site residues. Both this hydrogen bonding pattern and subtle variations in protein-ligand van der Waals interactions distinguish nanomolar from picomolar inhibitors. In general, inhibitors that fit within the substrate envelope, regardless of whether they are picomolar or nanomolar, have flatter profiles with respect to drug-resistant protease variants than inhibitors that protrude beyond the substrate envelope; this provides a strong rationale for incorporating substrate-envelope constraints into structure-based design strategies to develop new HIV-1 protease inhibitors.

Evaluation of the substrate envelope hypothesis for inhibitors of HIV‐1 protease

Crystallographic data show that various substrates of HIV protease occupy a remarkably uniform region within the binding site; this region has been termed the substrate envelope. It has been suggested that an inhibitor that fits within the substrate envelope should tend to evade viral resistance because a protease mutation that reduces the affinity of the inhibitor will also tend to reduce the affinity of substrate, and will hence decrease the activity of the enzyme. Accordingly, inhibitors that fit the substrate envelope better should be less susceptible to clinically observed resistant mutations, since these must also allow substrates to bind. The present study describes a quantitative measure of the volume of a bound inhibitor falling outside the substrate envelope, and observes that this quantity correlates with the inhibitors losses in affinity to clinically relevant mutants. This measure may thus be useful as a penalty function in the design of robust HIV protease inhibitors. Proteins 2007.

Design of Mutation‐resistant HIV Protease Inhibitors with the Substrate Envelope Hypothesis

There is a clinical need for HIV protease inhibitors that can evade resistance mutations. One possible approach to designing such inhibitors relies upon the crystallographic observation that the substrates of HIV protease occupy a rather constant region within the binding site. In particular, it has been hypothesized that inhibitors which lie within this region will tend to resist clinically relevant mutations. The present study offers the first prospective evaluation of this hypothesis, via computational design of inhibitors predicted to conform to the substrate envelope, followed by synthesis and evaluation against wild‐type and mutant proteases, as well as structural studies of complexes of the designed inhibitors with HIV protease. The results support the utility of the substrate envelope hypothesis as a guide to the design of robust protease inhibitors.

Enhanced docking with the mining minima optimizer: acceleration and side-chain flexibility.

The ligand–protein docking algorithm based on the Mining Minima method has been substantially enhanced. First, the basic algorithm is accelerated by: (1) adaptively determining the extent of each energy well to help avoid previously discovered energy minima; (2) biasing the search away from ligand positions at the surface of the receptor to prevent the ligand from staying at the surface when large sampling regions are used; (3) quickly testing multiple different ligand positions and orientations for each ligand conformation; and (4) tuning the source code to increase computational efficiency. These changes markedly shorten the time needed to discover an accurate result, especially when large sampling regions are used. The algorithm now also allows user‐selected receptor sidechains to be treated as mobile during the docking procedure. The energies associated with the mobile side chains are computed as if they belonged to the ligand, except that atoms at the boundary between side chains and the rigid backbone are treated specially. This new capability is tested for several well‐known ligand/protein systems, and preliminary application to an enzyme whose substrate is unknown—the recently solved hypothetical protein YecO (HI0319) from Haemophilus influenzae—indicates that side‐chains relaxations allow candidate substrates of various sizes to be accommodated.

Enantioseparation and chiral recognition mechanism of new chiral derivatives of xanthones on macrocyclic antibiotic stationary phases.

A chiral HPLC method using four macrocyclic antibiotic chiral stationary phases (CSPs) has been investigated for determination of the enantiomeric purity of fourteen new chiral derivatives of xanthones (CDXs). The separations were performed with the CSPs Chirobiotic T, Chirobiotic TAG, Chirobiotic V and Chirobiotic R under multimodal elution conditions (normal-phase, reversed-phase and polar ionic mode). The analyses were performed at room temperature in isocratic mode and UV and CD detection at a wavelength of 254 nm. The best enantioselectivity and resolution were achieved on Chirobiotic R and Chirobiotic T CSPs, under normal elution conditions, with R(S) ranging from 1.25 to 2.50 and from 0.78 to 2.06, respectively. The optimized chromatographic conditions allowed the determination of the enantiomeric ratio of eight CDXs, always higher than 99%. In order to better understand the chromatographic behavior at a molecular level, and the structural features associated with the chiral recognition mechanism, computational studies by molecular docking were carried out using VDock. These studies shed light on the mechanisms involved in the enantioseparation for this important class of chiral compounds.

Comparing ligand interactions with multiple receptors via serial docking

Standard uses of ligand-receptor docking typically focus on the association of candidate ligands with a single targeted receptor, but actual applications increasingly require comparisons across multiple receptors. This study demonstrates that comparative docking to multiple receptors can help to select homology models for virtual compound screening and to discover ligands that bind to one set of receptors but not to another, potentially similar, set. A serial docking algorithm is furthermore described that reduces the computational costs of such calculations by testing compounds against a series of receptor structures and discarding a compound as soon as it fails to satisfy specified bind/no bind criteria for each receptor. The algorithm also realizes substantial efficiencies by taking advantage of the fact that a ligand typically binds in similar conformations to similar receptors. Thus, once detailed docking has been used to fit a ligand into the first of a series of similar receptors, much less extensive calculations can be used for the remaining structures.

Toward the design of mutation-resistant enzyme inhibitors: further evaluation of the substrate envelope hypothesis.

Previous studies have shown the usefulness of the substrate envelope concept in the analysis and prediction of drug resistance profiles for human immunodeficiency virus protease mutants. This study tests its applicability to several other therapeutic targets: Abl kinase, chitinase, thymidylate synthase, dihydrofolate reductase, and neuraminidase. For the targets where many (≥6) mutation data are available to compute the average mutation sensitivity of inhibitors, the total volume of an inhibitor molecule that projects outside the substrate envelope Vout, is found to correlate with average mutation sensitivity. Analysis of a locally computed volume suggests that the same correlation would hold for the other targets, if more extensive mutation data sets were available. It is concluded that the substrate envelope concept offers a promising and easily implemented computational tool for the design of drugs that will tend to resist mutations. Software implementing these calculations is provided with the ‘Supporting Information’.

Using Protein Homology Models for Structure-Based Studies: Approaches to Model Refinement

Homology modeling is a computational methodology to assign a 3-D structure to a target protein when experimental data are not available. The methodology uses another protein with a known structure that shares some sequence identity with the target as a template. The crudest approach is to thread the target protein backbone atoms over the backbone atoms of the template protein, but necessary refinement methods are needed to produce realistic models. In this mini-review anchored within the scope of drug design, we show the validity of using homology models of proteins in the discovery of binders for potential therapeutic targets. We also report several different approaches to homology model refinement, going from very simple to the most elaborate. Results show that refinement approaches are system dependent and that more elaborate methodologies do not always correlate with better performances from built homology models.