Solvated interaction energy: from small-molecule to antibody drug design.

Scoring functions are ubiquitous in structure-based drug design as an aid to predicting binding modes and estimating binding affinities. Ideally, a scoring function should be broadly applicable, obviating the need to recalibrate and refit its parameters for every new target and class of ligands. Traditionally, drugs have been small molecules, but in recent years biologics, particularly antibodies, have become an increasingly important if not dominant class of therapeutics. This makes the goal of having a transferable scoring function, i.e., one that spans the range of small-molecule to protein ligands, even more challenging. One such broadly applicable scoring function is the Solvated Interaction Energy (SIE), which has been developed and applied in our lab for the last 15 years, leading to several important applications. This physics-based method arose from efforts to understand the physics governing binding events, with particular care given to the role played by solvation. SIE has been used by us and many independent labs worldwide for virtual screening and discovery of novel small-molecule binders or optimization of known drugs. Moreover, without any retraining, it is found to be transferrable to predictions of antibody-antigen relative binding affinities and as accurate as functions trained on protein-protein binding affinities. SIE has been incorporated in conjunction with other scoring functions into ADAPT (Assisted Design of Antibody and Protein Therapeutics), our platform for affinity modulation of antibodies. Application of ADAPT resulted in the optimization of several antibodies with 10-to-100-fold improvements in binding affinity. Further applications included broadening the specificity of a single-domain antibody to be cross-reactive with virus variants of both SARS-CoV-1 and SARS-CoV-2, and the design of safer antibodies by engineering of a pH switch to make them more selective towards acidic tumors while sparing normal tissues at physiological pH.

Antibody mutations favoring pH-dependent binding in solid tumor microenvironments: Insights from large-scale structure-based calculations.

Antibody-based therapeutics for treatment of various tumors have grown rapidly in recent years. Unfortunately, safety issues, attributed to off-tumor effects and cytotoxicity, are still a significant concern with the standard of care. Improvements to ensure targeted delivery of antitumor pharmaceuticals are desperately needed. We previously demonstrated that incorporating histidyl pH-switches in an anti-HER2 antibody induced selective antigen binding under acidic pH conditions (MAbs 2020;12:1682866). This led to an improved safety profile due to preferential targeting of the oncoprotein in the acidic solid tumor microenvironment. Following this success, we expanded this approach to a set of over 400 antibody structures complexed with over 100 different human oncoproteins, associated with solid tumors. Calculations suggested that mutations to His of certain residue types, namely Trp, Arg, and Tyr, could be significantly more successful for inducing pH-dependent binding under acidic conditions. Furthermore, 10 positions within the complementarity-determining region were also predicted to exhibit greater successes. Combined, these two accessible metrics could serve as the basis for a sequence-based engineering of pH-selective binding. This approach could be applied to most anticancer antibodies, which lack detailed structural characterization.

Redesigning an antibody H3 loop by virtual screening of a small library of human germline-derived sequences.

The design of superior biologic therapeutics, including antibodies and engineered proteins, involves optimizing their specific ability to bind to disease-related molecular targets. Previously, we developed and applied the Assisted Design of Antibody and Protein Therapeutics (ADAPT) platform for virtual affinity maturation of antibodies (Vivcharuk et al. in PLoS One 12(7):e0181490, https://doi.org/10.1371/journal.pone.0181490 , 2017). However, ADAPT is limited to point mutations of hot-spot residues in existing CDR loops. In this study, we explore the possibility of wholesale replacement of the entire H3 loop with no restriction to maintain the parental loop length. This complements other currently published studies that sample replacements for the CDR loops L1, L2, L3, H1 and H2. Given the immense sequence space theoretically available to H3, we focused on the virtual grafting of over 5000 human germline-derived H3 sequences from the IGMT/LIGM database increasing the diversity of the sequence space when compared to using crystalized H3 loop sequences. H3 loop conformations are generated and scored to identify optimized H3 sequences. Experimental testing of high-ranking H3 sequences grafted into the framework of the bH1 antibody against human VEGF-A led to the discovery of multiple hits, some of which had similar or better affinities relative to the parental antibody. In over 75% of the tested designs, the re-designed H3 loop contributed favorably to overall binding affinity. The hits also demonstrated good developability attributes such as high thermal stability and no aggregation. Crystal structures of select re-designed H3 variants were solved and indicated that although some deviations from predicted structures were seen in the more solvent accessible regions of the H3 loop, they did not significantly affect predicted affinity scores.

Structure-based engineering of pH-dependent antibody binding for selective targeting of solid-tumor microenvironment.

Recent development of monoclonal antibodies as mainstream anticancer agents demands further optimization of their safety for use in humans. Potent targeting and/or effector activities on normal tissues is an obvious toxicity concern. Optimization of specific tumor targeting could be achieved by taking advantage of the extracellular acidity of solid tumors relative to normal tissues. Here, we applied a structure-based computational approach to engineer anti-human epidermal growth factor receptor 2 (Her2) antibodies with selective binding in the acidic tumor microenvironment. We used an affinity maturation platform in which dual-pH histidine-scanning mutagenesis was implemented for pH selectivity optimization. Testing of a small set of designs for binding to the recombinant Her2 ectodomain led to the identification of antigen-binding fragment (Fab) variants with the desired pH-dependent binding behavior. Binding selectivity toward acidic pH was improved by as much as 25-fold relative to the parental bH1-Fab. In vitro experiments on cells expressing intact Her2 confirmed that designed variants formatted as IgG1/k full-size antibodies have high affinity and inhibit the growth of tumor spheroids at a level comparable to that of the benchmark anti-Her2 antibody trastuzumab (Herceptin®) at acidic pH, whereas these effects were significantly reduced at physiological pH. In contrast, both Herceptin and the parental bH1 antibody exhibited strong cell binding and growth inhibition irrespective of pH. This work demonstrates the feasibility of computational optimization of antibodies for selective targeting of the acidic environment such as that found in many solid tumors.

A Targeted Bivalent Androgen Receptor Binding Compound for Prostate Cancer Therapy.

The androgen-directed treatment of prostate cancer (PCa) is fraught with the recurrent profile of failed treatment due to drug resistance and must be addressed if we are to provide an effective therapeutic option. The most singular difficulty in the treatment of PCa is the failure to respond to classical androgen withdrawal or androgen blockade therapy, which often develops as the malignancy incurs genetic alterations and gain-of-function somatic mutations in the androgen receptor (AR). Physical cellular damaging therapeutic agents, such as radiation or activatable heat-generating transducers would circumvent classical "anti-functional" biological resistance, but to become ultimately effective would require directed application modalities. To this end, we have developed a novel AR-directed therapeutic agent by creating bivalent androgen hormone-AF-2 compounds that bind with high affinity to AR within cells. Here, we used molecular modeling and synthetic chemistry to create a number of compounds by conjugating 5α-dihydrotestosterone (DHT) to various AF-2 motif sequence peptides, through the use of a glycine and other spacer linkers. Our data indicates these compounds will bind to the AR in vitro and that altering the AF-2 peptide composition of the compound does indeed improve affinity for the AR. We also show that many of these bivalent compounds can readily pass through the plasma membrane and effectively compete against androgens alone.

Assisted Design of Antibody and Protein Therapeutics (ADAPT).

Effective biologic therapeutics require binding affinities that are fine-tuned to their disease-related molecular target. The ADAPT (Assisted Design of Antibody and Protein Therapeutics) platform aids in the selection of mutants that improve/modulate the affinity of antibodies and other biologics. It uses a consensus z-score from three scoring functions and interleaves computational predictions with experimental validation, significantly enhancing the robustness of the design and selection of mutants. The platform was tested on three antibody Fab-antigen systems that spanned a wide range of initial binding affinities: bH1-VEGF-A (44 nM), bH1-HER2 (3.6 nM) and Herceptin-HER2 (0.058 nM). Novel triple mutants were obtained that exhibited 104-, 46- and 32-fold improvements in binding affinity for each system, respectively. Moreover, for all three antibody-antigen systems over 90% of all the intermediate single and double mutants that were designed and tested showed higher affinities than the parent sequence. The contributions of the individual mutants to the change in binding affinity appear to be roughly additive when combined to form double and triple mutants. The new interactions introduced by the affinity-enhancing mutants included long-range electrostatics as well as short-range nonpolar interactions. This diversity in the types of new interactions formed by the mutants was reflected in SPR kinetics that showed that the enhancements in affinities arose from increasing on-rates, decreasing off-rates or a combination of the two effects, depending on the mutation. ADAPT is a very focused search of sequence space and required only 20-30 mutants for each system to be made and tested to achieve the affinity enhancements mentioned above.

Exhaustive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge.

We continued prospective assessments of the Wilma-solvated interaction energy (SIE) platform for pose prediction, binding affinity prediction, and virtual screening on the challenging SAMPL4 data sets including the HIV-integrase inhibitor and two host-guest systems. New features of the docking algorithm and scoring function are tested here prospectively for the first time. Wilma-SIE provides good correlations with actual binding affinities over a wide range of binding affinities that includes strong binders as in the case of SAMPL4 host-guest systems. Absolute binding affinities are also reproduced with appropriate training of the scoring function on available data sets or from comparative estimation of the change in target's vibrational entropy. Even when binding modes are known, SIE predictions lack correlation with experimental affinities within dynamic ranges below 2 kcal/mol as in the case of HIV-integrase ligands, but they correctly signaled the narrowness of the dynamic range. Using a common protein structure for all ligands can reduce the noise, while incorporating a more sophisticated solvation treatment improves absolute predictions. The HIV-integrase virtual screening data set consists of promiscuous weak binders with relatively high flexibility and thus it falls outside of the applicability domain of the Wilma-SIE docking platform. Despite these difficulties, unbiased docking around three known binding sites of the enzyme resulted in over a third of ligands being docked within 2 Å from their actual poses and over half of the ligands docked in the correct site, leading to better-than-random virtual screening results.

Molecular dynamics study of small molecule inhibitors of the Bcl-2 family.

We carried out docking and molecular dynamics simulations on ABT-737 and obatoclax, which are inhibitors of the Bcl-2 family of proteins. We modeled the binding mode of ABT-737 with Bcl-x(L) , Bcl-2, and Mcl-1 and examined their dynamical behavior. We found that the binding of the chlorobiphenyl end of ABT-737 was quite stable across all three proteins. However, the phenylpiperazine linker group was dramatically more mobile in Mcl-1 compared to either Bcl-x(L) or Bcl-2. The S-phenyl group at the p4 binding site was well-anchored in Bcl-x(L) and Bcl-2 but was somewhat more mobile in Mcl-1 although the phenyl ring itself on average stayed close to the p4 binding site in Mcl-1. This greater mobility is likely due to the greater openness of the p3 and p4 binding sites on Mcl-1. The calculated binding free energies were consistent with the much weaker binding affinity of ABT-737 for Mcl-1. Obatoclax was predicted to bind at the p1 and p2 binding sites of Mcl-1 and the binding mode was quite stable during the molecular dynamics simulation with Mcl-1 wrapping around the molecule. The modeled binding mode suggests that obatoclax is able to inhibit all three proteins because it makes use of the p1 and p2 binding sites alone, which is a fairly narrow groove in all three proteins unlike the p4 binding site, which is much broader in Mcl-1.

Identification of high-quality cancer prognostic markers and metastasis network modules.

Cancer patients are often overtreated because of a failure to identify low-risk cancer patients. Thus far, no algorithm has been able to successfully generate cancer prognostic gene signatures with high accuracy and robustness in order to identify these patients. In this paper, we developed an algorithm that identifies prognostic markers using tumour gene microarrays focusing on metastasis-driving gene expression signals. Application of the algorithm to breast cancer samples identified prognostic gene signature sets for both estrogen receptor (ER) negative (-) and positive (+) subtypes. A combinatorial use of the signatures allowed the stratification of patients into low-, intermediate- and high-risk groups in both the training set and in eight independent testing sets containing 1,375 samples. The predictive accuracy for the low-risk group reached 87-100%. Integrative network analysis identified modules in which each module contained the genes of a signature and their direct interacting partners that are cancer driver-mutating genes. These modules are recurrent in many breast tumours and contribute to metastasis.

A monovalent agonist of TrkA tyrosine kinase receptors can be converted into a bivalent antagonist.

BACKGROUND: Receptor tyrosine kinases (RTK) act through dimerization. Previously it was thought that only bivalent ligands could be agonistic, whereas monovalent ligands should be antagonistic. This notion changed after the demonstration that monovalent ligands can be agonistic, including our report of a small molecule monovalent ligand "D3" that is a partial agonist of the NGF receptor TrkA. A bivalent "D3-linker-D3" was expected to increase agonism. METHODS: Dimeric analogs were synthesized and tested in binding, biochemical, and biological assays. RESULTS: One analog, 1-ss, binds TrkA with higher affinity than D3 and induces or stabilizes receptor dimers. However, 1-ss exhibited antagonistic activity, through two mechanisms. One mechanism is that 1-ss blocks NGF binding, unlike D3 which is non-competitive. Inhibition of NGF binding may be due to the linker of 1-ss filling the inter-receptor space that NGF traverses before docking. In a second mechanism, 1-ss acts as a pure antagonist, inhibiting NGF-independent TrkA activity in cells over-expressing receptors. Inhibition is likely due to 1-ss "freezing" the TrkA dimer in the inactive state. CONCLUSIONS: Dimerization of an RTK can result in antagonism, through two independent mechanisms. GENERAL SIGNIFICANCE: we report a small molecule monovalent agonist being converted to a bivalent antagonist.

Small-molecule ligands of GD2 ganglioside, designed from NMR studies, exhibit induced-fit binding and bioactivity.

Ganglioside GD2 is a cell surface glycosphingolipid. Targeting of GD2, i.e., by anti-GD2 mAb 3F8, is used clinically for cancer diagnosis, prognosis, and therapy. Here, the conformations of free GD2, and of GD2 bound to mAb 3F8, were resolved by saturation transfer difference NMR and molecular modeling. Then, three small-molecule cyclic peptide ligands that bind to GD2 selectively were designed. Transferred nuclear Overhauser enhancement of the GD2-bound conformation of the peptide ligands showed an induced-fit binding mechanism. The mAb 3F8 and the peptidic GD2 ligands mediate similar biological functions in cell-based assays of calcium fluxes and src activation. Thus, small molecules can selectively and functionally interact with a sugar head group. This work furthers the concept of rationally designing ligands for carbohydrate targets, and may be expanded to other clinically relevant gangliosides.

Viral cystatin evolution and three-dimensional structure modelling: a case of directional selection acting on a viral protein involved in a host-parasitoid interaction.

BACKGROUND: In pathogens, certain genes encoding proteins that directly interact with host defences coevolve with their host and are subject to positive selection. In the lepidopteran host-wasp parasitoid system, one of the most original strategies developed by the wasps to defeat host defences is the injection of a symbiotic polydnavirus at the same time as the wasp eggs. The virus is essential for wasp parasitism success since viral gene expression alters the immune system and development of the host. As a wasp mutualist symbiont, the virus is expected to exhibit a reduction in genome complexity and evolve under wasp phyletic constraints. However, as a lepidopteran host pathogenic symbiont, the virus is likely undergoing strong selective pressures for the acquisition of new functions by gene acquisition or duplication. To understand the constraints imposed by this particular system on virus evolution, we studied a polydnavirus gene family encoding cyteine protease inhibitors of the cystatin superfamily. RESULTS: We show that cystatins are the first bracovirus genes proven to be subject to strong positive selection within a host-parasitoid system. A generated three-dimensional model of Cotesia congregata bracovirus cystatin 1 provides a powerful framework to position positively selected residues and reveal that they are concentrated in the vicinity of actives sites which interact with cysteine proteases directly. In addition, phylogenetic analyses reveal two different cystatin forms which evolved under different selective constraints and are characterized by independent adaptive duplication events. CONCLUSION: Positive selection acts to maintain cystatin gene duplications and induces directional divergence presumably to ensure the presence of efficient and adapted cystatin forms. Directional selection has acted on key cystatin active sites, suggesting that cystatins coevolve with their host target. We can strongly suggest that cystatins constitute major virulence factors, as was already proposed in previous functional studies.

An investigation into CAG repeat length variation and N/C terminal interactions in the T877A mutant androgen receptor found in prostate cancer.

Prostate cancer may progress by circumventing ablation therapy due to mutations in the androgen receptor (AR) gene. The most intensively studied is the T877A mutation in the ligand binding domain (LBD), which causes the AR to become promiscuous, i.e., respond to a number of different ligands. Our investigations have shown that the T877A mutation alters the inverse relationship between CAG repeat length and transactivation in a noticeable albeit minor manner, while increasing N/C terminal interactions. In the presence of beta-catenin, a coactivator over-expressed in prostate cancer, the inverse relationship between CAG repeat length and transactivation is reversed for the wild type (wt) AR as well. We have also used molecular modeling with the AR and FXXLF and LXXLL peptides to investigate N/C terminal and coactivator interactions. In T877A, this approach revealed an increase in the flexibility of amino acid residues in the activation function 2 (AF-2) domain in the LBD, and a larger solvent accessible surface in T877A compared to the wt AR AF-2 domain. Thus, the improved induced fit of the AR N-terminal domain FXXLF-containing peptide into the T877A LBD could be due to the increased flexibility and solvent accessibility of the AF-2 domain. These new observations suggest that the AR CAG effect can be overridden by prostate cancer mutations, and also further our understanding of hormone-refractory prostate cancer by helping to explain the promiscuity of the T877A mutation.

Exploring inhibitor binding at the S' subsites of cathepsin L.

We report a series of noncovalent, reversible inhibitors of cathepsin L that have been designed to explore additional binding interactions with the S' subsites. The design was based on our previously reported crystal structure that suggested the possibility of engineering increased interactions with the S' subsites ( Chowdhury et al. J. Med. Chem. 2002, 45, 5321-5329 ). A representative of these new inhibitors has been co-crystallized with mature cathepsin L, and the structure has been solved and refined at 2.2 A. The inhibitors described in this work extend farther into the S' subsites of cathepsins than any inhibitors reported in the literature thus far. These interactions appear to make use of a S3' subsite that can potentially be exploited for enhanced specificity and/or affinity.

A map of human cancer signaling.

We conducted a comprehensive analysis of a manually curated human signaling network containing 1634 nodes and 5089 signaling regulatory relations by integrating cancer-associated genetically and epigenetically altered genes. We find that cancer mutated genes are enriched in positive signaling regulatory loops, whereas the cancer-associated methylated genes are enriched in negative signaling regulatory loops. We further characterized an overall picture of the cancer-signaling architectural and functional organization. From the network, we extracted an oncogene-signaling map, which contains 326 nodes, 892 links and the interconnections of mutated and methylated genes. The map can be decomposed into 12 topological regions or oncogene-signaling blocks, including a few 'oncogene-signaling-dependent blocks' in which frequently used oncogene-signaling events are enriched. One such block, in which the genes are highly mutated and methylated, appears in most tumors and thus plays a central role in cancer signaling. Functional collaborations between two oncogene-signaling-dependent blocks occur in most tumors, although breast and lung tumors exhibit more complex collaborative patterns between multiple blocks than other cancer types. Benchmarking two data sets derived from systematic screening of mutations in tumors further reinforced our findings that, although the mutations are tremendously diverse and complex at the gene level, clear patterns of oncogene-signaling collaborations emerge recurrently at the network level. Finally, the mutated genes in the network could be used to discover novel cancer-associated genes and biomarkers.

Solvated interaction energy (SIE) for scoring protein-ligand binding affinities. 1. Exploring the parameter space.

We present a binding free energy function that consists of force field terms supplemented by solvation terms. We used this function to calibrate the solvation model along with the binding interaction terms in a self-consistent manner. The motivation for this approach was that the solute dielectric-constant dependence of calculated hydration gas-to-water transfer free energies is markedly different from that of binding free energies (J. Comput. Chem. 2003, 24, 954). Hence, we sought to calibrate directly the solvation terms in the context of a binding calculation. The five parameters of the model were systematically scanned to best reproduce the absolute binding free energies for a set of 99 protein-ligand complexes. We obtained a mean unsigned error of 1.29 kcal/mol for the predicted absolute binding affinity in a parameter space that was fairly shallow near the optimum. The lowest errors were obtained with solute dielectric values of Din = 20 or higher and scaling of the intermolecular van der Waals interaction energy by factors ranging from 0.03 to 0.15. The high apparent Din and strong van der Waals scaling may reflect the anticorrelation of the change in solvated potential energy and configurational entropy, that is, enthalpy-entropy compensation in ligand binding (Biophys. J. 2004, 87, 3035-3049). Five variations of preparing the protein-ligand data set were explored in order to examine the effect of energy refinement and the presence of bound water on the calculated results. We find that retaining water in the final protein structure used for calculating the binding free energy is not necessary to obtain good results; that is the continuum solvation model is sufficient. Virtual screening enrichment studies on estrogen receptor and thymidine kinase showed a good ability of the binding free energy function to recover true hits in a collection of decoys.

Binding site-based classification of coronaviral papain-like proteases.

The coronavirus replicase gene encodes one or two papain-like proteases (termed PL1pro and PL2pro) implicated in the N-terminal processing of the replicase polyprotein and thus contributing to the formation of the viral replicase complex that mediates genome replication. Using consensus fold recognition with the 3D-JURY meta-predictor followed by model building and refinement, we developed a structural model for the single PLpro present in the severe acute respiratory syndrome coronavirus (SCoV) genome, based on significant structural relationships to the catalytic core domain of HAUSP, a ubiquitin-specific protease (USP). By combining the SCoV PLpro model with comparative sequence analyses we show that all currently known coronaviral PLpros can be classified into two groups according to their binding site architectures. One group includes all PL2pros and some of the PL1pros, which are characterized by a restricted USP-like binding site. This group is designated the R-group. The remaining PL1pros from some of the coronaviruses form the other group, featuring a more open papain-like binding site, and is referred to as the O-group. This two-group, binding site-based classification is consistent with experimental data accumulated to date for the specificity of PLpro-mediated polyprotein processing and PLpro inhibition. It also provides an independent evaluation of the similarity-based annotation of PLpro-mediated cleavage sites, as well as a basis for comparison with previous groupings based on phylogenetic analyses.

Inhibition of a cathepsin L-like cysteine protease by a chimeric propeptide-derived inhibitor.

Like other papain-related cathepsins, congopain from Trypanosoma congolense is synthesized as a zymogen. We have previously identified a proregion-derived peptide (Pcp27), acting as a weak and reversible inhibitor of congopain. Pcp27 contains a 5-mer YHNGA motif, which is essential for selectivity in the inhibition of its mature form [Lalmanach, G., Lecaille, F., Chagas, J. R., Authié, E., Scharfstein, J., Juliano, M. A., and Gauthier, F. (1998) J. Biol. Chem. 273, 25112-25116]. In the work presented here, a homology model of procongopain was generated and subsequently used to model a chimeric 50-mer peptide (called H3-Pcp27) corresponding to the covalent linkage of an unrelated peptide (H3 helix from Antennapedia) to Pcp27. Molecular simulations suggested that H3-Pcp27 (pI = 9.99) maintains an N-terminal helical conformation, and establishes more complementary electrostatic interactions (E(coul) = -25.77 kcal/mol) than 16N-Pcp27, the 34-mer Pcp27 sequence plus the 16 native residues upstream from the proregion (E(coul) = 0.20 kcal/mol), with the acid catalytic domain (pI = 5.2) of the mature enzyme. In silico results correlated with the significant improvement of congopain inhibition by H3-Pcp27 (K(i) = 24 nM), compared to 16N-Pcp27 (K(i) = 1 microM). In addition, virtual alanine scanning of H3 and 16N identified the residues contributing most to binding affinity. Both peptides did not inhibit human cathepsins B and L. In conclusion, these data support the notion that the positively charged H3 helix favors binding, without modifying the selectivity of Pcp27 for congopain.

Carboxy-monopeptidase substrate specificity of human cathepsin X.

Cathepsin X is a papain-like cysteine protease with restricted positional specificity, acting primarily as a carboxy-monopeptidase. We mapped the specificities at the S2, S1, and S1' subsites of human cathepsin X by systematically and independently substituting the P2, P1, and P1' positions of the carboxy-monopeptidase substrate Abz-FRF(4NO(2)) with natural amino acids. Human cathepsin X has broad S2, S1, and S1' specificities within two orders of magnitude in k(cat)/K(M), excluding proline that is not tolerated at these subsites. Glycine is not favored in S2, but is among the preferred residues in S1 and S1', which highlights S2 as the affinity-determinant subsite. The presence of peculiar residues at several binding site positions (Asp76, His234, Asn75, and Glu72) does not translate into a markedly different sequence specificity profile relative to other human cathepsins. These findings suggest that a specific function of human cathepsin X is unlikely to result from sequence specificity, but rather from a combination of its unique positional specificity and the co-localization of enzyme and substrate in a specific cellular environment.

Design of noncovalent inhibitors of human cathepsin L. From the 96-residue proregion to optimized tripeptides.

A novel series of noncovalent inhibitors of cathepsin L have been designed to mimic the mode of autoinhibition of procathepsin L. Just like the propeptide, these peptide-based inhibitors have a reverse-binding mode relative to a substrate and span both the S' and S subsites of the enzyme active site. In contrast to previous studies in which even moderate truncation of the full-length propeptide led to rapid reduction in potency, these blocked tripeptide-sized inhibitors maintain nanomolar potency. Moreover, these short peptides show higher selectivity (up to 310-fold) for inhibiting cathepsin L over K versus only 2-fold selectivity of the 96-residue propeptide of cathepsin L. A 1.9 A X-ray crystallographic structure of the complex of cathepsin L with one of the inhibitors confirms the designed reverse-binding mode of the inhibitor as well as its noncovalent nature. Enzymatic analysis also shows the inhibitors to be resistant to hydrolysis at elevated concentrations of the enzyme. The mode of inhibition of these molecules provides a general strategy for inhibiting other cathepsins as well as other proteases.