Markku Hämäläinen

Label-free primary screening and affinity ranking of fragment libraries using parallel analysis of protein panels.

The authors present fragment screening data obtained using a label-free parallel analysis approach where the binding of fragment library compounds to 4 different target proteins can be screened simultaneously using surface plasmon resonance detection. They suggest this method as a first step in fragment screening to identify and select binders, reducing the demanding requirements on subsequent X-ray or nuclear magnetic resonance studies, and as a valuable “clean-up” tool to eliminate unwanted promiscuous binders from libraries. A small directed fragment library of known thrombin binders and a general 500-compound fragment library were used in this study. Thrombin, blocked thrombin, carbonic anhydrase, and glutathione-S-transferase were immobilized on the sensor chip surface, and the direct binding of the fragments was studied in real time. Only 12 µg of each protein is needed for screening of a 3000-compound fragment library. For screening, a binding site-blocked target as reference facilitates the identification of binding site-selective hits and the signals from other reference proteins for the elimination of false positives. The scope and limitations of this screening approach are discussed for both target-directed and general fragment libraries. (Journal of Biomolecular Screening 2008:202-209)

Identification of MMP-12 Inhibitors by Using Biosensor-Based Screening of a Fragment Library

Small inhibitors of matrix metalloproteinase 12 (MMP-12) have been identified with a biosensor-based screening strategy and a specifically designed fragment library. The interaction between fragments and three variants of the target and a reference protein with an active-site zinc ion was measured continuously by surface plasmon resonance. The developed experimental design overcame the inherent instability of MMP-12 and allowed the identification of fragments that interacted specifically with the active-site of MMP-12 but not with the reference protein. The interaction with MMP-12 for selected compounds were analyzed for concentration dependence and saturability. Compounds interacting distinctly with the target were further evaluated by an activity-based assay, verifying MMP-12 inhibition. Two effective inhibitors were identified, and the compound with highest affinity was confirmed to be a competitive inhibitor with an IC50 of 290 nM and a ligand efficiency of 0.7 kcal/mol heavy atom. This procedure integrates selectivity and binding site identification into the screening procedure and does not require structure determination.

Predicting the kinetics of peptide–antibody interactions using a multivariate experimental design of sequence and chemical space

A multivariate approach involving modifications in peptide sequence and chemical buffer medium was used as an attempt to predict the kinetics of peptide‐antibody interactions. Using a BIACORE® system the kinetic parameters of the interaction of Fab 57P with 18 peptide analogues of an epitope of tobacco mosaic virus protein were characterized in 20 buffers of various pH values and containing different chemical additives (NaCl, urea, EDTA, KSCN and DMSO). For multivariate peptide design, three amino acid positions were selected because their modification was known to moderately affect binding, without abolishing it entirely. Predictive mathematical models were developed which related kinetic parameters (ka or kd) measured in standard buffer to the amino acid sequence of the antigen. ZZ‐scales and a helix‐forming‐tendency (HFT) scale were used as descriptors of the physico‐chemical properties of amino acids in the peptide antigen. These mathematical models had good predictive power (Q2 = 0.49 for ka, Q2 = 0.73 for kd). For the non‐essential residues under study, HFT and charge were found to be the most important factors that influenced the activity. Experiments in 19 buffers were performed to assess the sensitivity of the interactions to buffer composition. The presence of urea, DMSO and NaCl in the buffer influenced binding properties, while change in pH and the presence of EDTA and KSCN had no effect. The chemical sensitivity fingerprints were different for the various peptides. The results indicate that multivariate experimental design and mathematical modeling can be applied to the prediction of interaction kinetics. Copyright

Characterization of a set of HIV-1 protease inhibitors using binding kinetics data from a biosensor-based screen

The interaction between 290 structurally diverse human immunodeficiency virus type 1 (HIV-1) protease inhibitors and the immobilized enzyme was analyzed with an optical biosensor. Although only a single concentration of inhibitor was used, information about the kinetics of the interaction could be obtained by extracting binding signals at discrete time points. The statistical correlation between the biosensor binding data, inhibition of enzyme activity (K;), and viral replication (EC50) revealed that the association and dissociation rates for the interaction could be resolved and that they were characteristic for the compounds. The most potent inhibitors, with respect to K; and EC50 values, including the clinically used drugs, all exhibited fast association and slow dissociation rates. Selective or partially selective binders for HIV-1 protease could be distinguished from compounds that showed a general protein-binding tendency by using three reference target proteins. This biosensor-based direct binding assay revealed a capacity to efficiently provide high-resolution information on the interaction kinetics and specificity of the interaction of a set of compounds with several targets simultaneously.

Compounds Binding to the S2−S3 Pockets of Thrombin

A set of compounds designed to bind to the S2-S3 pockets of thrombin was prepared. These compounds included examples with no interactions in the S1 pocket. Proline, a common P2 in many thrombin inhibitors, was combined with known P3 residues and P1 substituents of varying size and lipophilicity. Binding constants were determined using surface plasmon resonance (SPR) biosensor technology and were found to be in good agreement with results from an enzyme assay. A dramatic increase in affinity (100-1000 times) was seen for compounds incorporating an amino group capable of forming a hydrogen bond with gly216 in the protein backbone. The ligand efficiency was increased by including substituents that form stronger hydrophobic interactions with the P1 pocket. The binding mode was confirmed by X-ray analysis, which revealed the anticipated binding motif that included hydrogen bonds as well as a tightly bound water molecule. A QSAR model indicated that hydrogen bonding and lipophilicity were important for the prediction of binding constants. The results described here may have implications for how directed compound libraries for shallow protein pockets, like S2 and S3 in serine proteases, can be designed.

Label-free kinetic binding data as a decisive element in drug discovery.

The emerging possibilities to obtain label-free, kinetic-based binding data for drug–target and drug absorption, distribution, metabolism and excretion (ADME)–marker interactions have proven useful in many drug discovery related issues. Multiple reports have demonstrated that the common use of affinity as an early measure of drug potency may be directly misleading. This review summarises findings in the literature related to compound selection in the drug discovery process. It is important to understand the different properties of association and dissociation rates, the former being related to both structure and dosage and the latter depending solely on molecular structure. By performing parallel optimisations of association and dissociation rates, compounds with desirable kinetic profiles for target binding may be generated. In addition, compound selection may also consider the kinetic properties of the drug–ADME–marker binding profiles, further refining the quality of compounds early in the drug discovery process. The promising results found in the literature indicate that kinetic data on drug–protein interactions may soon become a crucial decisive element in modern drug discovery.

Capture and analysis of low molecular weight ligands by surface plasmon resonance combined with mass spectrometry

The combination of biomolecular interaction analysis (BIA)by surface plasmon resonance (SPR)and nano-electrospray ionization ion trap mass spectrometry (nanoESI-Ion Trap MS)as well as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS)is demonstrated for the binding of low molecular weight inhibitors (∼ 600 Da) to HIV-1 protease. Inhibitors were captured on sensor chips of a manual or an automated SPR biosensor, to which HIV-1 protease was immobilized. Compounds and buffer components that bound unspecifically to the sensor surface were removed and the inhibitors were eluted in a minimal volume (3 μL), between air bubbles, in order to prevent dispersion of analyte into buffer eluent. Molecular weights were subsequently determined by mass spectrometry, structural information was obtained by MALDI-ToF post-source decay as well as by electrospray ionization tandem mass spectrometry (MS/MS)analysis. Furthermore, competition experiments, using a mixture of different ligands, demonstrated that the peak intensities in the MALDI-ToF spectrum could be used for relative quantification of the amount of the different ligands bound to the immobilized target. Methodology for automated capture and elution of analytes was developed and evaluated.

Screening for NNRTIs with Slow Dissociation and High Affinity for a Panel of HIV-1 RT Variants

A lead optimization library consisting of 800 HIV-1 nonnucleoside reverse transcriptase inhibitors (NNRTIs) was screened in parallel against 4 clinically relevant variants of HIV-1 RT (Wt, L100I, Y181C, and K103N) using a surface plasmon resonance—based biosensor. The aim was to identify inhibitors suitable in specific topical microbicides efficient for preventing the transmission of a range of clinically significant strains of HIV-1. The authors hypothesized that such compounds should have high affinity and slow dissociation rates for multiple variants of the target. To efficiently analyze the large amount of real-time data (sensorgrams) that were generated in the screening, they initially used signals from 3 selected time points to identify compounds with high affinity and slow dissociation for the complete panel of enzyme variants. Hits were confirmed by visually inspecting the complete sensorgrams. Two structurally unrelated compounds fulfilled the hit criteria, but only 1 compound was found to (a) compete with a known NNRTI for binding to the NNRTI site, (b) inhibit HIV-1 RT activity, and (c) inhibit HIV-1 replication in cell culture, for all 4 enzyme variants. This novel screening methodology offers high-resolution real-time kinetic data for multiple targets in parallel. It is expected to have broad applicability for the discovery of compounds with defined kinetic profiles, crucial for optimal therapeutic effects. (Journal of Biomolecular Screening 2009:395-403)

Increased sensitivity of SPR assays in plasma through efficient parallel assay optimization

The sensitivity of biosensor assays in complex media such as plasma or serum is often limited by non-specific binding. The degree of binding often varies between individuals and therefore a large number of different plasma samples have to be used during assay development. Some surface plasmon resonance (SPR) biosensors allow for parallel screening of several running buffer compositions, with a number of different immobilization levels for each buffer. These technical possibilities combined with statistical design of experiments (DoE) enable efficient parallel optimization of multiple assay conditions. In this paper we outline how to increase the sensitivity in SPR-based assays by minimizing background binding and variability from negative control plasma while retaining high signals from positive samples. To mimic immunogenicity studies of biotherapeutics we have used a model assay with anti-rituximab as an anti-drug antibody to be detected in plasma by binding to immobilized rituximab. Immobilization level and sodium chloride concentration were found to be the most important factors to optimize. There were also a number of significant interaction effects and strong non-linearites between the buffer composition/immobilization level and the assay performance, which necessitated DoE based optimization strategies. The applicability of the optimized conditions was verified with several assays (anti-erythropoietin, omalizumab, anti-IgE and anti-myoglobin) in spiked plasma samples resulting in detection levels in the range of 80-170 ng ml(-1). The buffer conditions presented in this paper can be used for other immunogenicity assays on biosensor platforms or as a good starting point for further assay development for new immunogenicity assays.

Corrigendum: Real-time monitoring using a breathalyzer-based eHealth system can identify lapse/relapse patterns in alcohol use disorder patients

Aim We introduce a new remote real-time breathalyzer-based method for monitoring and early identification of lapse/relapse patterns for alcohol use disorder (AUD) patients using a composite measure of sobriety, the Addiction Monitoring Index (AMI). Methods We constructed AMI from (a) obtained test results and (b) the pattern of ignored tests using data from the first 30 patients starting in the treatment arms of two on-going clinical trials. The patients performed 2-4 scheduled breath alcohol content (BrAC)-tests per day presented as blood alcohol content (BAC) data. In total, 10,973 tests were scheduled, 7743 were performed and 3230 were ignored during 3982 patient days. Results AMI-time profiles could be used to monitor the daily trends of alcohol consumption and detect early signs of lapse and relapses. The pattern of ignored tests correlates with the onset of drinking. AMI correlated with phosphatidyl ethanol (n = 61, F-ratio = 34.6, P < 0.0001, R = -0.61). The recognition of secret drinking could further be improved using a low alcohol detection threshold (BrAC = 0.025 mg/l, BACSwe = 0.05‰ or US = 0.0053g/dl), in addition to the legal Swedish traffic limit (BrAC = 0.1 mg/l, BACSwe = 0.2‰ or US = 0.021 g/dl). Nine out of 10 patients who dropped out from the study showed early risk signs as reflected in the level and pattern in AMI before the actual dropout. Conclusions AMI-time profiles from an eHealth system are useful for monitoring the recovery process and for early identification of lapse/relapse patterns. High-resolution monitoring of sobriety enables new measurement-based treatment methods for proactive personalized long-term relapse prevention and treatment of AUD patients. Clinical Trial Registration The data used for construction of AMI was from two clinical trials approved by the Regional Ethics Committee of Uppsala, Sweden and performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participating subjects. The study was registered at ClinicalTrials.gov (NCT03195894).