High-Throughput and Format-Agnostic Mispairing Assay for Multispecific Antibodies Using Intact Mass Spectrometry.

Multispecific antibodies have gained significant importance in a broad indication space due to their ability to engage multiple epitopes simultaneously and to thereby overcome therapeutic barriers. With growing therapeutic potential, however, the molecular complexity increases, thus intensifying the demand for innovative protein engineering and analytical strategies. A major challenge for multispecific antibodies is the correct assembly of light and heavy chains. Engineering strategies exist to stabilize the correct pairing, but typically individual engineering campaigns are required to arrive at the anticipated format. Mass spectrometry has proven to be a versatile tool to identify mispaired species. However, due to manual data analysis procedures, mass spectrometry is limited to lower throughputs. To keep pace with increasing sample numbers, we developed a high-throughput-capable mispairing workflow based on intact mass spectrometry with automated data analysis, peak detection, and relative quantification using Genedata Expressionist. This workflow is capable of detecting mispaired species of ∼1000 multispecific antibodies in three weeks and thus is applicable to complex screening campaigns. As a proof of concept, the assay was applied to engineering a trispecific antibody. Strikingly, the new setup has not only proved successful in mispairing analysis but has also revealed its potential to automatically annotate other product-related impurities. Furthermore, we could confirm the assay to be format-agnostic, as shown by analyzing several different multispecific formats in one run. With these comprehensive capabilities, the new automated intact mass workflow can be applied as a universal tool to detect and annotate peaks in a format-agnostic approach and in high-throughput, thus enabling complex discovery campaigns.

An end-to-end automated platform process for high-throughput engineering of next-generation multi-specific antibody therapeutics.

Next-generation multi-specific antibody therapeutics (MSATs) are engineered to combine several functional activities into one molecule to provide higher efficacy compared to conventional, mono-specific antibody therapeutics. However, highly engineered MSATs frequently display poor yields and less favorable drug-like properties (DLPs), which can adversely affect their development. Systematic screening of a large panel of MSAT variants in very high throughput (HT) is thus critical to identify potent molecule candidates with good yield and DLPs early in the discovery process. Here we report on the establishment of a novel, format-agnostic platform process for the fast generation and multiparametric screening of tens of thousands of MSAT variants. To this end, we have introduced full automation across the entire value chain for MSAT engineering. Specifically, we have automated the in-silico design of very large MSAT panels such that it reflects precisely the wet-lab processes for MSAT DNA library generation. This includes mass saturation mutagenesis or bulk modular cloning technologies while, concomitantly, enabling library deconvolution approaches using HT Sanger DNA sequencing. These DNA workflows are tightly linked to fully automated downstream processes for compartmentalized mammalian cell transfection expression, and screening of multiple parameters. All sub-processes are seamlessly integrated with tailored workflow supporting bioinformatics. As described here, we used this platform to perform multifactor optimization of a next-generation bispecific, cross-over dual variable domain-Ig (CODV-Ig). Screening of more than 25,000 individual protein variants in mono- and bispecific format led to the identification of CODV-Ig variants with over 1,000-fold increased potency and significantly optimized production titers, demonstrating the power and versatility of the platform.

Trace elements in commonly used medicinal plants from Varna region, Bulgaria.

In this study, we assessed the concentrations of some trace and toxic elements (Cd, Pb, Zn, Cu, Ni, Cr, Fe, and Mn) in traditionally used wild medicinal plants: chamomile (Matricaria chamomilla), white yarrow (Achillea millefolium), linden (Tilia sp.), and elder (Sambucus nigra L.) collected from urban and rural region near Varna, Bulgaria. Concentrations of examined elements were determined by inductively coupled plasma-optical emission spectrometry (ICP-OES) after sample mineralization. The samples were digested with concentrated nitric acid in a microwave system. Mean element levels in medicinal herbs were established in decreasing order as follows: Fe > Mn > Zn ≈ Cu > Pb > Ni > Cr > Cd. The content of toxic elements in medicinal herbs was found significantly higher in areas with intensive traffic compared with a suburban area. Instead discrimination between metal content in rural and urban samples was confirmed by PCA. Concentrations of toxic elements Cd and Pb in all plant species from the rural region were found in the range from not detected to 0.08 and 0.796 ng/kg, respectively and were below the permissible limit of the WHO.

Mapping Biological Activities to Different Types of Molecular Scaffolds: Exemplary Application to Protein Kinase Inhibitors.

Scaffolds were originally introduced to delineate core structures of active compounds. They are also used to assess the ability of computational methods to identify structurally diverse active compounds. Biological activities of compound series are often mapped to scaffolds. This is done to better understand activity distributions over different structural classes or search for core structures of compounds that are preferentially active against target families of interest. Herein, we describe in detail how such scaffold activity profiles are generated and compare profiles for differently defined scaffolds. As an exemplary application, scaffolds of currently available kinase inhibitors covering the human kinome are analyzed.

Collection of analog series-based scaffolds from public compound sources.

AIM: Providing a large and freely available in silico collection of analog series-based (ASB) scaffolds for computational design and medicinal chemistry applications. METHODOLOGY: Using a recently introduced computational method, ASB scaffolds with single and multiple substitution sites were systematically isolated from publicly available active compounds. DATA: A total of 23,791 unique ASB scaffolds are made available in an organized and machine-readable form as an open access deposition. For each ASB scaffold, the number of analogs it represents is also provided. NEXT STEPS: The freely available collection of ASB scaffolds will be further analyzed to explore different types of scaffold relationships. The ASB scaffold collection will periodically be updated.

Redundancy in two major compound databases.

Public repositories of compounds and activity data are of prime importance for pharmaceutical research in academic and industrial settings. Major databases have evolved over the years. Their growth is accompanied by an increasing tendency toward data sharing. This is a positive development but not without potential problems. Using ChEMBL and PubChem as examples, we show that crosstalk between databases also leads to substantial data redundancy that might not be obvious. Redundancy is an important issue because it biases data analysis and knowledge extraction and leads to inflated views of available compounds, assays and activity data. Going forward it will be important to further refine data exchange and deposition criteria and make redundancy as transparent as possible.

Computational design of new molecular scaffolds for medicinal chemistry, part II: generalization of analog series-based scaffolds.

AIM: Extending and generalizing the computational concept of analog series-based (ASB) scaffolds. MATERIALS & METHODS: Methodological modifications were introduced to further increase the coverage of analog series (ASs) and compounds by ASB scaffolds. From bioactive compounds, ASs were systematically extracted and second-generation ASB scaffolds isolated. RESULTS: More than 20,000 second-generation ASB scaffolds with single or multiple substitution sites were extracted from active compounds, achieving more than 90% coverage of ASs. CONCLUSION: Generalization of the ASB scaffold approach has yielded a large knowledge base of scaffold-capturing compound series and target information.

Rationalizing Promiscuity Cliffs.

Compound promiscuity can be viewed in different ways. We distinguish "bad" promiscuity resulting from chemical liabilities, nonspecific binding, or assay artifacts, from "good" promiscuity representing true multitarget activities. Investigating multitarget activities of small molecules is scientifically stimulating and therapeutically relevant. To better understand the molecular basis of multitarget activities, structure-promiscuity relationships (SPRs) are explored. For this purpose, "promiscuity cliffs" (PCs) have been introduced, which can be rationalized as an extension of the activity cliff (AC) concept. A PC is defined as a pair of structural analogues that are active against different numbers of targets (given a difference threshold). As discussed herein PCs frequently capture surprising SPRs and encode many experimentally testable hypotheses.

Is scaffold hopping a reliable indicator for the ability of computational methods to identify structurally diverse active compounds?

Computational scaffold hopping aims to identify core structure replacements in active compounds. To evaluate scaffold hopping potential from a principal point of view, regardless of the computational methods that are applied, a global analysis of conventional scaffolds in analog series from compound activity classes was carried out. The majority of analog series was found to contain multiple scaffolds, thus enabling the detection of intra-series scaffold hops among closely related compounds. More than 1000 activity classes were found to contain increasing proportions of multi-scaffold analog series. Thus, using such activity classes for scaffold hopping analysis is likely to overestimate the scaffold hopping (core structure replacement) potential of computational methods, due to an abundance of artificial scaffold hops that are possible within analog series.

Assessing Scaffold Diversity of Kinase Inhibitors Using Alternative Scaffold Concepts and Estimating the Scaffold Hopping Potential for Different Kinases.

Publicly available kinase inhibitors provide a large source of information for structure-activity relationship analysis and kinase drug design. In this study, publicly available inhibitors of the human kinome were collected and analog series formed by kinase inhibitors systematically identified. Then, alternative scaffold concepts were applied to assess diversity and promiscuity of kinase inhibitors. Over the past two years, the number of publicly available kinase inhibitors with high-confidence activity data more than doubled, but coverage of the human kinome only slightly increased. Approximately 70% of current kinase inhibitors belonged to analog series. However, the detectable degree of promiscuity among these kinase inhibitors remained low. Approximately 76% of all inhibitors were only annotated with a single kinase, compared to ~70% two years ago. For many kinases, the assessment of scaffold diversity among their inhibitors and the distribution of differently defined scaffolds over analog series made it possible to assess scaffold hopping potential. Our analysis revealed that the consideration of conventional compound-based scaffolds most likely leads to an overestimation of scaffold hopping frequency, at least for compounds forming analog series.

Exploring Structural Relationships between Bioactive and Commercial Chemical Space and Developing Target Hypotheses for Compound Acquisition.

Analog series were systematically extracted from more than 650 000 bioactive compounds originating from medicinal chemistry and screening sources and more than 3.6 million commercial compounds that were not biologically annotated. Then, analog series-based (ASB) scaffolds were generated. For each scaffold from a bioactive series, a target profile was derived and ASB scaffolds shared by bioactive and commercial compounds were determined. On the basis of our analysis, large segments of commercial chemical space were not yet explored biologically. Shared ASB scaffolds established structural relationships between bioactive and commercial chemical space, and the target profiles of these scaffolds were transferred to commercially available analogs of active compounds. This made it possible to derive target hypotheses for more than 37 000 compounds without biological annotations covering more than 1000 different targets. For many molecules, alternative target assignments were available. Target hypotheses for these compounds should be of interest, for example, for hit expansion, acquisition of compounds to design or further extend focused libraries for drug discovery, or testing of expanded analog series on different targets. They can also be used to search for analogs and complement compound series during target-directed optimization. Therefore, all of the commercial molecules with new target hypotheses as well as key scaffolds identified in our analysis and their target profiles are made freely available.

Application of a New Scaffold Concept for Computational Target Deconvolution of Chemical Cancer Cell Line Screens.

Target deconvolution of phenotypic assays is a hot topic in chemical biology and drug discovery. The ultimate goal is the identification of targets for compounds that produce interesting phenotypic readouts. A variety of experimental and computational strategies have been devised to aid this process. A widely applied computational approach infers putative targets of new active molecules on the basis of their chemical similarity to compounds with activity against known targets. Herein, we introduce a molecular scaffold-based variant for similarity-based target deconvolution from chemical cancer cell line screens that were used as a model system for phenotypic assays. A new scaffold type was used for substructure-based similarity assessment, termed analog series-based (ASB) scaffold. Compared with conventional scaffolds and compound-based similarity calculations, target assignment centered on ASB scaffolds resulting from screening hits and bioactive reference compounds restricted the number of target hypotheses in a meaningful way and lead to a significant enrichment of known cancer targets among candidates.

Highly Promiscuous Small Molecules from Biological Screening Assays Include Many Pan-Assay Interference Compounds but Also Candidates for Polypharmacology.

In PubChem screening assays, 466 highly promiscuous compounds were identified that were examined for known pan-assay interference compounds (PAINS) and aggregators using publicly available filters. These filters detected 210 PAINS and 67 aggregators. Compounds passing the filters included additional PAINS that were not detected, mostly due to tautomerism, and a variety of other potentially reactive compounds currently not encoded as PAINS. For a subset of compounds passing the filters, there was no evidence of potential artifacts. These compounds are considered candidates for further exploring multitarget activities and the molecular basis of polypharmacology.

Computational Method for the Systematic Identification of Analog Series and Key Compounds Representing Series and Their Biological Activity Profiles.

A computational methodology is introduced for detecting all unique series of analogs in large compound data sets, regardless of chemical relationships between analogs. No prior knowledge of core structures or R-groups is required, which are automatically determined. The approach is based upon the generation of retrosynthetic matched molecular pairs and analog networks from which distinct series are isolated. The methodology was applied to systematically extract more than 17 000 distinct series from the ChEMBL database. For comparison, analog series were also isolated from screening compounds and drugs. Known biological activities were mapped to series from ChEMBL, and in more than 13 000 of these series, key compounds were identified that represented substitution sites of all analogs within a series and its complete activity profile. The analog series, key compounds, and activity profiles are made freely available as a resource for medicinal chemistry applications.

Advances in Activity Cliff Research.

Activity cliffs, i.e. similar compounds with large potency differences, are of interest from a chemical and informatics viewpoint; as a source of structure-activity relationship information, for compound optimization, and activity prediction. Herein, recent highlights of activity cliff research are discussed including studies that have further extended our understanding of activity cliffs, yielded unprecedented insights, or paved the way for practical applications.

Analog series-based scaffolds: computational design and exploration of a new type of molecular scaffolds for medicinal chemistry.

AIM: Computational design of and systematic search for a new type of molecular scaffolds termed analog series-based scaffolds. MATERIALS & METHODS: From currently available bioactive compounds, analog series were systematically extracted, key compounds identified and new scaffolds isolated from them. RESULTS: Using our computational approach, more than 12,000 scaffolds were extracted from bioactive compounds. CONCLUSION: A new scaffold definition is introduced and a computational methodology developed to systematically identify such scaffolds, yielding a large freely available scaffold knowledge base.

Monitoring the Progression of Structure-Activity Relationship Information during Lead Optimization.

Lead optimization (LO) in medicinal chemistry is largely driven by hypotheses and depends on the ingenuity, experience, and intuition of medicinal chemists, focusing on the key question of which compound should be made next. It is essentially impossible to predict whether an LO project might ultimately be successful, and it is also very difficult to estimate when a sufficient number of compounds has been evaluated to judge the odds of a project. Given the subjective nature of LO decisions and the inherent optimism of project teams, very few attempts have been made to systematically evaluate project progression. Herein, we introduce a computational framework to follow the evolution of structure-activity relationship (SAR) information over a time course. The approach is based on the use of SAR matrix data structures as a diagnostic tool and enables graphical analysis of SAR redundancy and project progression. This framework should help the process of making decisions in close-in analogue work.

One hundred ABO-incompatible kidney transplantations between 2004 and 2014: a single-centre experience.

BACKGROUND: ABO-incompatible kidney transplantation (ABOi KTx) expands the living donor transplantation options. However, long-term outcome data, especially in comparison with ABO-compatible kidney transplantation (ABOc KTx), remain limited. Since the first ABOi KTx in Germany on 1 April 2004 at our centre, we have followed 100 ABOi KTx over up to 10 years. METHODS: One hundred ABOi KTx and 248 ABOc KTx from 1 April 2004 until 28 October 2014 were analysed in this observational, single-centre study. Three ABOi KTx and 141 ABOc KTx were excluded because of cyclosporine A-based immunosuppression, and 1 ABOc KTx was lost to follow-up. RESULTS: Median estimated 10-year patient and graft survival in ABOi KTx was 99 and 94%, respectively, and surpassed ABOc-KTx patient and graft survival of 80 and 88%, respectively. The incidence rate of antibody-mediated rejections was 10 and 8%, and that of T-cell-mediated rejections was 17 and 20% in ABOi KTx and ABOc KTx, respectively. Infectious and malignant complications in ABOi KTx were not more common than in ABOc KTx. However, postoperative lymphoceles occurred more frequently in ABOi KTx. Subgroup analysis of ABOi-KTx patients revealed that patients with high-titre isohaemagglutinins before transplantation had equal long-term results compared with low-titre isohaemagglutinin patients. CONCLUSION: Taken together, long-term outcome of ABOi KTx is not inferior to ABOc KTx. Incidences of rejection episodes, infectious complications and malignancies are not increased, despite the more vigorous immunosuppression in ABOi KTx. Our data provide further evidence that ABOi KTx with living donation is a safe, successful and reasonable option to reduce the organ shortage.

Visualization of multi-property landscapes for compound selection and optimization.

Compound optimization generally requires considering multiple properties in concert and reaching a balance between them. Computationally, this process can be supported by multi-objective optimization methods that produce numerical solutions to an optimization task. Since a variety of comparable multi-property solutions are usually obtained further prioritization is required. However, the underlying multi-dimensional property spaces are typically complex and difficult to rationalize. Herein, an approach is introduced to visualize multi-property landscapes by adapting the concepts of star and parallel coordinates from computer graphics. The visualization method is designed to complement multi-objective compound optimization. We show that visualization makes it possible to further distinguish between numerically equivalent optimization solutions and helps to select drug-like compounds from multi-dimensional property spaces. The methodology is intuitive, applicable to a wide range of chemical optimization problems, and made freely available to the scientific community.

Systematic assessment of scaffold hopping versus activity cliff formation across bioactive compound classes following a molecular hierarchy.

Scaffold hopping and activity cliff formation define opposite ends of the activity landscape feature spectrum. To rationalize these events at the level of scaffolds, active compounds involved in scaffold hopping were required to contain topologically distinct scaffolds but have only limited differences in potency, whereas compounds involved in activity cliffs were required to share the same scaffold but have large differences in potency. A systematic search was carried out for compounds involved in scaffold hopping and/or activity cliff formation. Results obtained for compound data sets covering more than 300 human targets revealed clear trends. If scaffolds represented multiple but fewer than 10 active compounds, nearly 90% of all scaffolds were exclusively involved in hopping events. With increasing compound coverage, the fraction of scaffolds involved in both scaffold hopping and activity cliff formation significantly increased to more than 50%. However, ∼40% of the scaffolds representing large numbers of active compounds continued to be exclusively involved in scaffold hopping. More than 200 scaffolds with broad target coverage were identified that consistently represented potent compounds and yielded an abundance of scaffold hops in the low-nanomolar range. These and other subsets of scaffolds we characterized are of prime interest for structure-activity relationship (SAR) exploration and compound design. Therefore, the complete scaffold classification generated in the course of our analysis is made freely available.