The urokinase receptor (uPAR) is a cell-surface protein that is part of an intricate web of transient and tight protein interactions that promote cancer cell invasion and metastasis. Here we evaluate the binding and biological activity of a new class of pyrrolidinone (3) and piperidinone (4) compounds, along with derivatives of previously-identified pyrazole (1) and propylamine (2) compounds. Competition assays revealed that the compounds displaced a fluorescently-labeled peptide (AE147-FAM) with inhibition constant Ki ranging from 6 to 63 μM. Structure-based computational pharmacophore analysis followed by extensive explicit-solvent molecular dynamics simulations and free energy calculations suggested pyrazole-based 1a and piperidinone-based 4 adopt different binding modes, despite their similar two-dimensional structures. In cells, compounds 1b and 1f showed significant inhibition of breast MDA-MB-231 and pancreatic ductal adenocarcinoma (PDAC) cell proliferation, but 4b exhibited no cytotoxicity even at concentrations of 100 μM. 1f impaired MDA-MB-231 invasion, adhesion, and migration in a concentration-dependent manner, while 4b inhibited only invasion. 1f inhibited gelatinase (MMP-9) activity in a concentration-dependent manner, while 4b showed no effect suggesting different mechanisms for inhibition of cell invasion. Signaling studies further highlighted these differences, showing that pyrazole compounds completely inhibited ERK phosphorylation and impaired HIF1α and NF-κB signaling, while pyrrolidinone and piperidinone (3 and 4b) had no effect. Annexin V staining suggested that the effect of pyrazole-based 1f on proliferation was due to cell killing through an apoptotic mechanism.
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 ρ 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 (ρ = 0.91 for ε = 10). But larger ε significantly reduced the contributions of electrostatics, suggesting that the improvement is due to the non-polar and entropy components, rather than a better representation of the electrostatics. SVRKB scoring function applied to MD snapshots resulted in excellent rank-ordering (ρ = 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-PBSAADAPT), there is less agreement with the ITC data for the individual free energies, but remarkably good rank-ordering is observed (ρ = 0.89). Interestingly, filtering MD snapshots by pre-scoring protein-ligand complexes with a machine learning-based approach (SVMSP) resulted in a significant improvement in the MM-PBSA results (ε = 1) from ρ = 0.40 to ρ = 0.81. Finally, the non-polar 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.
The uPAR·uPA protein-protein interaction (PPI) is involved in signaling and proteolytic events that promote tumor invasion and metastasis. A previous study had identified 4 (IPR-803) from computational screening of a commercial chemical library and shown that the compound inhibited uPAR·uPA PPI in competition biochemical assays and invasion cellular studies. Here, we synthesize 4 to evaluate in vivo pharmacokinetic (PK) and efficacy studies in a murine breast cancer metastasis model. First, we show, using fluorescence polarization and saturation transfer difference (STD) NMR, that 4 binds directly to uPAR with sub-micromolar affinity of 0.2 μM. We show that 4 blocks invasion of breast MDA-MB-231, and inhibits matrix metalloproteinase (MMP) breakdown of the extracellular matrix (ECM). Derivatives of 4 also inhibited MMP activity and blocked invasion in a concentration-dependent manner. 4 also impaired MDA-MB-231 cell adhesion and migration. Extensive in vivo PK studies in NOD-SCID mice revealed a half-life of nearly 5 hours and peak concentration of 5 μM. Similar levels of the inhibitor were detected in tumor tissue up to 10 hours. Female NSG mice inoculated with highly malignant TMD-MDA-MB-231 in their mammary fat pads showed that 4 impaired metastasis to the lungs with only four of the treated mice showing severe or marked metastasis compared to ten for the untreated mice. Compound 4 is a promising template for the development of compounds with enhanced PK parameters and greater efficacy.
The urokinase receptor (uPAR) serves as a docking site to the serine protease urokinase-type plasminogen activator (uPA) to promote extracellular matrix (ECM) degradation and tumor invasion and metastasis. Previously, we had reported a small molecule inhibitor of the uPAR•uPA interaction that emerged from structure-based virtual screening. Here, we measure the affinity of a large number of derivatives from commercial sources. Synthesis of additional compounds was carried out to probe the role of various groups on the parent compound. Extensive structure-based computational studies suggested a binding mode for these compounds that led to a structure-activity relationship study. Cellular studies in non-small cell lung cancer (NSCLC) cell lines that include A549, H460 and H1299 showed that compounds blocked invasion, migration and adhesion. The effects on invasion of active compounds were consistent with their inhibition of uPA and MMP proteolytic activity. These compounds showed weak cytotoxicity consistent with the confined role of uPAR to metastasis.
Interaction of the urokinase receptor (uPAR) with its binding partners including the urokinase-type plasminogen activator (uPA) at the cell surface triggers a series of proteolytic and signaling events that promote invasion and metastasis. Here, we report the discovery of a small molecule (IPR-456) and its derivatives that inhibit the tight uPAR·uPA protein-protein interaction. IPR-456 was discovered by virtual screening against multiple conformations of uPAR sampled from explicit-solvent molecular dynamics simulations. Biochemical characterization reveal that the compound binds to uPAR with sub-micromolar affinity (Kd = 310 nM) and inhibits the tight protein-protein interaction with an IC50 of 10 μM. Free energy calculations based on explicit-solvent molecular dynamics simulations suggested the importance of a carboxylate moiety on IPR-456, which was confirmed by the activity of several derivatives including IPR-803. Immunofluorescence imaging showed that IPR-456 inhibited uPA binding to uPAR of breast MDA-MB-231 tumor cells with an IC50 of 8 μM. The compounds blocked MDA-MB-231 cell invasion, but IPR-456 showed little effect on MDA-MB-231 migration, and no effect on adhesion, suggesting that uPAR mediates these processes through its other binding partners.
Virtual screening; small molecule; protein-protein interaction; inhibitor; urokinase receptor; invasion; migration; metastasis; MDA-MB-231; cancer; breast cancer; urokinase-type plasminogen activator; uPAR; uPA; docking; scoring; flexible docking
Virtual screening targeting the urokinase receptor (uPAR) led to (3R)-4-cyclohexyl-3-(hexahydrobenzo[d][1,3]dioxol-5-yl)-N-((hexahydrobenzo[d][1,3]dioxol-5-yl)methyl)butan-1-aminium 1 (IPR-1) and 4-(4-((3,5-dimethylcyclohexyl)carbamoyl)-2-(4-isopropylcyclohexyl)pyrazolidin-3-yl)piperidin-1-ium 3 (IPR-69). Synthesis of an analog of 1, namely 2 (IPR-9), and 3 led to breast MDA-MB-231 invasion, migration and adhesion assays with IC50 near 30 μM. Both compounds blocked angiogenesis with IC50 of 3 μM. Compounds 2 and 3 inhibited cell growth with IC50 of 6 and 18 μM and induced apoptosis. Biochemical assays revealed lead-like properties for 3, but not 2. Compound 3 administered orally reached peak concentration of nearly 40 μM with a half-life of about 2 hours. In NOD-SCID mice inoculated with breast TMD-231 cells in their mammary fat pads, compound 3 showed a 20% reduction in tumor volumes and less extensive metastasis was observed for the treated mice. The suitable pharmacokinetic properties of 3 and the encouraging preliminary results in metastasis make it an ideal starting point for next generation compounds.
The Community Structure-Activity Resource (CSAR) datasets are used develop and test a Support Vector Machine-based scoring function in regression mode (SVR). Two scoring functions (SVR-KB and SVR-EP) are derived with the objective of reproducing the trend of the experimental binding affinities provided within the two CSAR datasets. The features used to train SVR-KB are knowledge-based pairwise potentials, while SVR-EP is based on physico-chemical properties. SVR-KB and SVR-EP were compared to seven other widely-used scoring functions, including Glide, X-score, GoldScore, ChemScore, Vina, Dock and PMF. Results showed that SVR-KB trained with features obtained from three-dimensional complexes of the PDBbind dataset outperformed all other scoring functions including best performing X-score, by nearly 0.1 using three correlation coefficients, namely Pearson, Spearman and Kendall. It was interesting that higher performance in rank-ordering did not translate into greater enrichment in virtual screening assessed using the 40 targets of the Directory of Useful Decoys (DUD). To remedy this situation, a variant of SVR-KB (SVR-KBD) was developed by following a target-specific tailoring strategy that we had previously employed to derive SVM-SP. SVR-KBD showed much higher enrichment outperforming all other scoring functions tested, and was comparable in performance to our previously-derived scoring function SVM-SP.
The ubiquity of protein-protein interactions in biological signaling offers ample opportunities for therapeutic intervention. We previously identified a peptide, designated CBD3, that suppressed inflammatory and neuropathic behavioral hypersensitivity in rodents by inhibiting the ability of collapsin response mediator protein 2 (CRMP-2) to bind to N-type voltage-activated calcium channels (CaV2.2) [Brittain et al. Nature Medicine 17:822–829 (2011)].
Results and discussion
Here, we utilized SPOTScan analysis to identify an optimized variation of the CBD3 peptide (CBD3A6K) that bound with greater affinity to Ca2+ channels. Molecular dynamics simulations demonstrated that the CBD3A6K peptide was more stable and less prone to the unfolding observed with the parent CBD3 peptide. This mutant peptide, conjugated to the cell penetrating motif of the HIV transduction domain protein TAT, exhibited greater anti-nociception in a rodent model of AIDS therapy-induced peripheral neuropathy when compared to the parent TAT-CBD3 peptide. Remarkably, intraperitoneal administration of TAT-CBD3A6K produced none of the minor side effects (i.e. tail kinking, body contortion) observed with the parent peptide. Interestingly, excitability of dissociated small diameter sensory neurons isolated from rats was also reduced by TAT-CBD3A6K peptide suggesting that suppression of excitability may be due to inhibition of T- and R-type Ca2+ channels. TAT-CBD3A6K had no effect on depolarization-evoked calcitonin gene related peptide (CGRP) release compared to vehicle control.
Collectively, these results establish TAT-CBD3A6K as a peptide therapeutic with greater efficacy in an AIDS therapy-induced model of peripheral neuropathy than its parent peptide, TAT-CBD3. Structural modifications of the CBD3 scaffold peptide may result in peptides with selectivity against a particular subset of voltage-gated calcium channels resulting in a multipharmacology of action on the target.
Peptide; Excitability; Nociception; AIDS therapy-induced chronic pain; Calcium channels; Molecular dynamics
β -Lactamases and penicillin-binding proteins are bacterial enzymes involved in antibiotic resistance to β-lactam antibiotics and biosynthetic assembly of cell wall, respectively. Members of these large families of enzymes all experience acylation by their respective substrates at an active site serine as the first step in their catalytic activities. A Ser-X-X-Lys sequence motif is seen in all these proteins, and crystal structures demonstrate that the side-chain functions of the serine and lysine are in contact with one another. Three independent methods were used in this report to address the question of the protonation state of this important lysine (Lys-73) in the TEM-1 β-lactamase from Escherichia coli. These techniques included perturbation of the pKa of Lys-73 by the study of the γ-thialysine-73 variant and the attendant kinetic analyses, investigation of the protonation state by titration of specifically labeled proteins by nuclear magnetic resonance, and by computational treatment using the thermodynamic integration method. All three methods indicated that the pKa of Lys-73 of this enzyme is attenuated to 8.0–8.5. It is argued herein that the unique ground-state ion pair of Glu-166 and Lys-73 of class A β-lactamases has actually raised the pKa of the active site lysine to 8.0–8.5 from that of the parental penicillin-binding protein. Whereas we cannot rule out that Glu-166 might activate the active site water, which in turn promotes Ser-70 for the acylation event, such as proposed earlier, we would like to propose as a plausible alternative for the acylation step the possibility that the ion pair would reconfigure to the protonated Glu-166 and unprotonated Lys-73. As such, unprotonated Lys-73 could promote serine for acylation, a process that should be shared among all active-site serine β-lactamases and penicillin-binding proteins.
We assess the performance of our previously reported structure-based support vector machine target-specific scoring function across 41 targets, 40 among them from the Directory of Useful Decoys (DUD). The area under the curve of receiver characteristic plots (ROC-AUC) revealed that scoring with SVMSP resulted in consistently better enrichment over all targets families and outperforming Glide and other scoring functions, most notably among kinases. In addition, SVM-SP performance showed little variation among protein classes, exhibited excellent performance in a test case using a homology model, and in some cases showed high enrichment even with few structures used to train a model. We put SVM-SP to the test by virtual screening 1,125 compounds against two kinases, EGFR and CaMKII. Among the top 25 EGFR compounds, three compounds (1–3) inhibited kinase activity in vitro with IC50 of 58, 2, and 10 μM. In cell culture, compounds 1–3 inhibited non-small cell lung carcinoma (H1299) cancer cell proliferation with similar IC50 values for compound 3. For CaMKII, one compound inhibited kinase activity in a dose-dependent manner among 20 tested with an IC50 of 48 μM. These results are encouraging given that our in-house library consists of compounds that emerged from virtual screening of other targets with pockets that are different from typical ATP binding sites found in kinases. In light of the importance of kinases in chemical biology, these findings could have implications in future efforts to identify chemical probes of kinases within the human kinome.
Penicillin-binding protein 1b (PBP 1b) of the Gram-positive bacterium Streptococcus pneumoniae catalyzes the cross-linking of adjacent peptidoglycan strands, as a critical event in the biosynthesis of its cell wall. This enzyme is representative of the biosynthetic PBP structures of the β-lactam-recognizing enzyme superfamily, and is the target of the β-lactam antibiotics. In the cross-linking reaction, the amide between the -D-Ala-D-Ala dipeptide at the terminus of a peptide stem acts as an acyl donor toward the ε-amino group of a lysine found on an adjacent stem. The mechanism of this transpeptidation was evaluated using explicit-solvent molecular dynamics simulations and ONIOM quantum mechanics/molecular mechanics calculations. Sequential acyl transfer occurs to, and then from, the active site serine. The resulting cross-link is predicted to have a cis-amide configuration. The ensuing and energetically favorable cis- to trans-amide isomerization, within the active site, may represent the key event driving product release to complete enzymatic turnover.
Although ∼50% of all types of human cancers harbour wild-type TP53, this p53 tumour suppressor is often deactivated through a concerted action by its abnormally elevated suppressors, MDM2, MDMX or SIRT1. Here, we report a novel small molecule Inauhzin (INZ) that effectively reactivates p53 by inhibiting SIRT1 activity, promotes p53-dependent apoptosis of human cancer cells without causing apparently genotoxic stress. Moreover, INZ stabilizes p53 by increasing p53 acetylation and preventing MDM2-mediated ubiquitylation of p53 in cells, though not directly in vitro. Remarkably, INZ inhibits cell proliferation, induces senescence and tumour-specific apoptosis, and represses the growth of xenograft tumours derived from p53-harbouring H460 and HCT116 cells without causing apparent toxicity to normal tissues and the tumour-bearing SCID mice. Hence, our study unearths INZ as a novel anti-cancer therapeutic candidate that inhibits SIRT1 activity and activates p53.
apoptosis; Inauhzin; p53; SIRT1; small molecule inhibitor
Glycopeptide antibiotics, including vancomycin, form complexes via a set of five hydrogen bonds with the acyl-l-Lys-d-Ala-d-Ala portion of the peptidyl stems of the bacterial cell wall peptidoglycan. This complexation deprives the organism from the ability to cross-link peptidyl stems of the peptidoglycan, leading to bacterial cell death. Four synthetic fragments as surrogates of the components of the bacterial cell wall have been prepared in our lab in multistep syntheses. These synthetic samples were used in investigations of the thermodynamics properties (ΔG°, ΔH°, and TΔS°) for the complexation with vancomycin by isothermal titration calorimetry (ITC). Complexation with the glycopeptide analogues are largely enthalpy-driven (formation of five hydrogen bonds) and in the analogues with a single peptidyl stem the complexation is 1:1. The complexation is more complicated with an approximately 2-kDa cell wall surrogate (compound 4), which possesses two peptidyl stems. The data were suggestive of interactions between the two vancomycin molecules, with an entropic penalty attributable to restriction of molecular movements within the complex due to restriction of motion of the highly mobile acyl-d-Ala-d-Ala moiety of the peptidyl stems. These data were reconciled with the recently determined NMR solution structure for the peptidoglycan fragment 4 and its implications for the larger cell wall.
Chronic pain hypersensitivity depends on N-type voltage-gated calcium channels (CaV2.2). However, the use of CaV2.2 blockers in pain therapeutics is limited by side effects that result from inhibited physiological functions of these channels. Here we report suppression of both inflammatory and neuropathic hypersensitivity by inhibiting the binding of the axonal collapsin response mediator protein 2 (CRMP-2) to CaV2.2, thus reducing channel function. A 15-amino acid peptide of CRMP-2 fused to the transduction domain of HIV TAT protein (TAT-CBD3) decreases neurotransmitter release from nociceptive dorsal root ganglion neurons, reduces meningeal blood flow, reduces nocifensive behavior induced by subcutaneous formalin injection or following corneal capsaicin application, and reverses neuropathic hypersensitivity produced by the antiretroviral drug 2’,3’-dideoxycytidine. TAT-CBD3 was mildly anxiolytic but innocuous on sensorimotor and cognitive functions and despair. By preventing CRMP-2-mediated enhancement of CaV2.2 function, TAT-CBD3 alleviates inflammatory and neuropathic hypersensitivity, an approach that may prove useful in managing clinical pain.
In an effort to develop a rational approach to identify anti-cancer agents with selective polypharmacology, we mine millions of docked protein-ligand complexes involving more than a thousand cancer targets from multiple signaling pathways to identify new structural templates for proven pharmacophores. Our method combines Support Vector Machine-based scoring to enrich the initial library of 1,592 molecules, with a fingerprint-based search for molecules that have the same binding profile as the EGFR kinase inhibitor erlotinib. Twelve new compounds were identified. In vitro activity assays revealed that three inhibited EGFR with IC50 values ranging from 250 nM to 200 µM. Additional in vitro studies with hERG, CYP450, DNA and cell culture-based assays further compared their properties to erlotinib. One compound combined suitable pharmacokinetic properties while closely mimicking the binding profile of erlotinib. The compound also inhibited H1299 and H460 tumor cell proliferation. The other two compounds shared some of the binding profile of erlotinib, and one gave the most potent inhibition of tumor cell growth. Interestingly, among the compounds that had not shown inhibition of EGFR, four blocked H1299 and H460 proliferation, one potently with IC50 values near 1 µM. This compound was from the menogaril family, which reached Phase II clinical trial for the treatment of lymphomas. This suggests that our computational approach comparing binding profile may have favored molecules with anti-cancer properties like erlotinib.
In an effort to develop a rational approach to identify anticancer agents with selective polypharmacology, we mined millions of docked protein−ligand complexes involving more than a thousand cancer targets from multiple signaling pathways to identify new structural templates for proven pharmacophores. Our method combines support vector machine-based scoring to enrich the initial library of 1592 molecules, with a fingerprint-based search for molecules that have the same binding profile as the EGFR kinase inhibitor erlotinib. Twelve new compounds were identified. In vitro activity assays revealed three inhibited EGFR with IC50 values ranging from 250 nM to 200 μM. Additional in vitro studies with hERG, CYP450, DNA, and cell culture-based assays further compared their properties to erlotinib. One compound combined suitable pharmacokinetic properties while closely mimicking the binding profile of erlotinib. The compound also inhibited H1299 and H460 tumor cell proliferation. The other two compounds shared some of the binding profile of erlotinib, and one gave the most potent inhibition of tumor cell growth. Interestingly, among the compounds that had not shown inhibition of EGFR, four blocked H1299 and H460 proliferation, one potently with IC50 values near 1 μM. This compound was from the menogaril family, which reached phase II clinical trials for the treatment of lymphomas. This suggests that our computational approach comparing binding profiles may have favored molecules with anticancer properties like erlotinib.
Docking; proteome; support vector machine; scoring; lung cancer; systems biology
Integral membrane proteins display two major types of transmembrane structures, helical bundles and beta barrels. The main functional roles of transmembrane proteins are the transport of small molecules and cell signaling, and sometimes these two roles are coupled. For cytosolic, water-soluble proteins, signaling and regulatory functions are often carried out by intrinsically disordered regions. Our long range goal is to determine whether integral membrane proteins likewise often use disordered regions for signaling and regulation. Here we carried out a systematic bioinformatics investigation of intrinsically disordered regions obtained from integral membrane proteins for which crystal structures have been determined, and for which the intrinsic disorder was identified as missing electron density. We found 120 disorder-containing integral membrane proteins having a total of 33,675 residues, with 3209 of the residues distributed among 240 different disordered regions. These disordered regions were compared with those obtained from water-soluble proteins with regard to their amino acid compositional biases, and with regard to accuracies of various disorder predictors. The results of these analyses show that the disordered regions from helical bundle integral membrane proteins, those from beta barrel integral membrane proteins, and those from water soluble proteins all exhibit statistically distinct amino acid compositional biases. Despite these differences in composition, current algorithms make reasonably accurate predictions of disorder for these membrane proteins. Although the small size of the current data sets are limiting, these results suggest that developing new predictors that make use of data from disordered regions in helical bundles and beta barrels, especially as these datasets increase in size, will likely lead to significantly more accurate disorder predictions for these two classes of integral membrane proteins.
The identification of near native protein-protein complexes among a set of decoys remains highly challenging. A strategy for improving the success rate of near native detection is to enrich near native docking decoys in a small number of top ranked decoys. Recently, we found that a combination of three scoring functions (energy, conservation and interface propensity) can predict the location of binding interface regions with reasonable accuracy. Here, these three scoring functions are modified and combined into a consensus scoring function called ENDES for enriching near native docking decoys. We found that all individual scores result in enrichment for the majority of 28 targets in ZDOCK2.3 decoy set and the 22 targets in Benchmark 2.0. Among the three scores, the interface propensity score yields the highest enrichment in both sets of protein complexes. When these scores are combined into the ENDES consensus score, a significant increase in enrichment of near-native structures is found. For example, when 2000 dock decoys are reduced to 200 decoys by ENDES, the fraction of near-native structures in docking decoys increases by a factor of about six in average. ENDES was implemented into a computer program that is available for download at http://sparks.informatics.iupui.edu.
Protein Docking; Near Native Decoy Selection; Energy Score; Interface Propensity; Conservation Score
The significant work that has been invested toward understanding protein–protein interaction has not translated into significant advances in structure-based predictions. In particular redesigning protein surfaces to bind to unrelated receptors remains a challenge, partly due to receptor flexibility, which is often neglected in these efforts. In this work, we computationally graft the binding epitope of various small proteins obtained from the RCSB database to bind to barnase, lysozyme, and trypsin using a previously derived and validated algorithm. In an effort to probe the protein complexes in a realistic environment, all native and designer complexes were subjected to a total of nearly 400 ns of explicit-solvent molecular dynamics (MD) simulation. The MD data led to an unexpected observation: some of the designer complexes were highly unstable and decomposed during the trajectories. In contrast, the native and a number of designer complexes remained consistently stable. The unstable conformers provided us with a unique opportunity to define the structural and energetic factors that lead to unproductive protein–protein complexes. To that end we used free energy calculations following the MM-PBSA approach to determine the role of nonpolar effects, electrostatics and entropy in binding. Remarkably, we found that a majority of unstable complexes exhibited more favorable electrostatics than native or stable designer complexes, suggesting that favorable electrostatic interactions are not prerequisite for complex formation between proteins. However, nonpolar effects remained consistently more favorable in native and stable designer complexes reinforcing the importance of hydrophobic effects in protein–protein binding. While entropy systematically opposed binding in all cases, there was no observed trend in the entropy difference between native and designer complexes. A series of alanine scanning mutations of hot-spot residues at the interface of native and designer complexes showed less than optimal contacts of hot-spot residues with their surroundings in the unstable conformers, resulting in more favorable entropy for these complexes. Finally, disorder predictions revealed that secondary structures at the interface of unstable complexes exhibited greater disorder than the stable complexes.
BioDrugScreen is a resource for ranking molecules docked against a large number of targets in the human proteome. Nearly 1600 molecules from the freely available NCI diversity set were docked onto 1926 cavities identified on 1589 human targets resulting in >3 million receptor–ligand complexes requiring >200 000 cpu-hours on the TeraGrid. The targets in BioDrugScreen originated from Human Cancer Protein Interaction Network, which we have updated, as well as the Human Druggable Proteome, which we have created for the purpose of this effort. This makes the BioDrugScreen resource highly valuable in drug discovery. The receptor–ligand complexes within the database can be ranked using standard and well-established scoring functions like AutoDock, DockScore, ChemScore, X-Score, GoldScore, DFIRE and PMF. In addition, we have scored the complexes with more intensive GBSA and PBSA approaches requiring an additional 120 000 cpu-hours on the TeraGrid. We constructed a simple interface to enable users to view top-ranking molecules and access purchasing and other information for further experimental exploration.