抗体成药性筛选流程及评价策略

自1986年OKT3作为第一个治疗性单克隆抗体获批上市后,抗体技术及抗体药物迅猛发展。单克隆抗体、抗体片段、双(多)特异性抗体、融合蛋白、纳米抗体以及抗体偶联药物(antibody-drug conjugates, ADCs)等推陈出新,在肿瘤、血液、免疫、呼吸和代谢等相关疾病的治疗领域发挥着举足轻重的作用。抗体药物的发现过程,是通过多轮生物学功能评估和可成药性评估,筛选出具有安全、有效、稳定和可工艺放大的最佳候选序列,从而提高药物开发和临床研究的效率及成功率。抗体药物发现阶段的“成药性筛选与评估”已日益受到关注和重视,从药物发现和设计、先导分子筛选到候选分子确认,可及时发现分子潜在的物理化学风险因素,并评估可控性,保证后续药物开发过程中的质量稳定性。本文对抗体发现阶段的成药性筛选评估流程进行了分类和定义,涉及单克隆抗体、双特异性抗体、纳米抗体和ADCs等相关技术和药物形式,同时总结了成药性筛选评估中应重点关注的质量属性和高通量检测技术;系统性地阐述成药性开发流程和策略,为不断涌现的创新型药物的成药性筛选评估提供参考,大幅提高抗体药物开发的效率和成功率。     

Ligand specificity in the CRAL-TRIO protein family

Intracellular trafficking of hydrophobic ligands is often mediated by specific binding proteins. The CRAL-TRIO motif is common to several lipid binding proteins including the cellular retinaldehyde binding protein (CRALBP), the alpha-tocopherol transfer protein (alpha-TTP), yeast phosphatidylinositol transfer protein (Sec14p), and supernatant protein factor (SPF). To examine the ligand specificity of these proteins, we measured their affinity toward a variety of hydrophobic ligands using a competitive [(3)H]-RRR-alpha-tocopherol binding assay. Alpha-TTP preferentially bound RRR-alpha-tocopherol over all other tocols assayed, exhibiting a K(d) of 25 nM. Binding affinities of other tocols for alphaTTP closely paralleled their ability to inhibit in vitro intermembrane transfer and their potency in biological assays. All other homologous proteins studied bound alpha-tocopherol but with pronouncedly weaker (> 10-fold) affinities than alpha-TTP. Sec14p demonstrated a K(d) of 373 nM for alpha-tocopherol, similar to that for its native ligand, phosphatidylinositol (381 nM). Human SPF had the highest affinity for phosphatidylinositol (216 nM) and gamma-tocopherol (268 nM) and significantly weaker affinity for alpha-tocopherol (K(d) 615 nM). SPF bound [(3)H]-squalene more weakly (879 nM) than the other ligands. Our data suggest that of all known CRAL-TRIO proteins, only alphaTTP is likely to serve as the physiological mediator of alpha-tocopherol's biological activity. Further, ligand promiscuity observed within this family suggests that caution should be exercised when suggesting protein function(s) from measurements utilizing a single ligand.     

Ligand binding specificity of the Escherichia coli periplasmic histidine binding protein,HisJ

The HisJ protein from Escherichia coli and related Gram negative bacteria is the periplasmic component of a bacterial ATP‐cassette (ABC) transporter system. Together these proteins form a transmembrane complex that can take up L‐histidine from the environment and translocate it into the cytosol. We have studied the specificity of HisJ for binding L‐His and many related naturally occurring compounds. Our data confirm that L‐His is the preferred ligand, but that 1‐methyl‐L‐His and 3‐methyl‐L‐His can also bind, while the dipeptide carnosine binds weakly and D‐histidine and the histidine degradation products, histamine, urocanic acid and imidazole do not bind. L‐Arg, homo‐L‐Arg, and post‐translationally modified methylated Arg‐analogs also bind with reasonable avidity, with the exception of symmetric dimethylated‐L‐Arg. In contrast, L‐Lys and L‐Orn have considerably weaker interactions with HisJ and methylated and acetylated Lys variants show relatively poor binding. It was also observed that the carboxylate group of these amino acids and their variants was very important for proper recognition of the ligand. Taken together our results are a key step towards designing HisJ as a specific protein‐based reagentless biosensor.     

Docking, virtual high throughput screening and in silico fragment-based drug design

The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high-throughput screening and fragment-based ligand design.     

Ligand specificity of group I biotin protein ligase of Mycobacterium tuberculosis

Background

Fatty acids are indispensable constituents of mycolic acids that impart toughness & permeability barrier to the cell envelope of M. tuberculosis. Biotin is an essential co-factor for acetyl-CoA carboxylase (ACC) the enzyme involved in the synthesis of malonyl-CoA, a committed precursor, needed for fatty acid synthesis. Biotin carboxyl carrier protein (BCCP) provides the co-factor for catalytic activity of ACC.

Methodology/Principal Findings

BPL/BirA (Biotin Protein Ligase), and its substrate, biotin carboxyl carrier protein (BCCP) of Mycobacterium tuberculosis (Mt) were cloned and expressed in E. coli BL21. In contrast to EcBirA and PhBPL, the ∼29.5 kDa MtBPL exists as a monomer in native, biotin and bio-5′AMP liganded forms. This was confirmed by molecular weight profiling by gel filtration on Superdex S-200 and Dynamic Light Scattering (DLS). Computational docking of biotin and bio-5′AMP to MtBPL show that adenylation alters the contact residues for biotin. MtBPL forms 11 H-bonds with biotin, relative to 35 with bio-5′AMP. Docking simulations also suggest that bio-5′AMP hydrogen bonds to the conserved ‘GRGRRG’ sequence but not biotin. The enzyme catalyzed transfer of biotin to BCCP was confirmed by incorporation of radioactive biotin and by Avidin blot. The K_m for BCCP was ∼5.2 µM and ∼420 nM for biotin. MtBPL has low affinity (K_b = 1.06×10⁻⁶ M) for biotin relative to EcBirA but their K_m are almost comparable suggesting that while the major function of MtBPL is biotinylation of BCCP, tight binding of biotin/bio-5′AMP by EcBirA is channeled for its repressor activity.

Conclusions/Significance

These studies thus open up avenues for understanding the unique features of MtBPL and the role it plays in biotin utilization in M. tuberculosis.     

Lead generation of heat shock protein 90 inhibitors by a combination of fragment-based approach, virtual screening, and structure-based drug design

Heat shock protein 90 (Hsp90) is a molecular chaperone which regulates maturation and stabilization of its substrate proteins, known as client proteins. Many client proteins of Hsp90 are involved in tumor progression and survival and therefore Hsp90 can be a good target for developing anticancer drugs. With the aim of efficiently identifying a new class of orally available inhibitors of the ATP binding site of this protein, we conducted fragment screening and virtual screening in parallel against Hsp90. This approach quickly identified 2-aminotriazine and 2-aminopyrimidine derivatives as specific ligands to Hsp90 with high ligand efficiency. In silico evaluation of the 3D X-ray Hsp90 complex structures of the identified hits allowed us to promptly design CH5015765, which showed high affinity for Hsp90 and antitumor activity in human cancer xenograft mouse models.     

Deconvoluting the biology and druggability of protein lipidation using chemical proteomics

Lipids are indispensable cellular building blocks, and their post-translational attachment to proteins makes them important regulators of many biological processes. Dysfunction of protein lipidation is also implicated in many pathological states, yet its systematic analysis presents significant challenges. Thanks to innovations in chemical proteomics, lipidation can now be readily studied by metabolic tagging using functionalized lipid analogs, enabling global profiling of lipidated substrates using mass spectrometry. This has spearheaded the first deconvolution of their full scope in a range of contexts, from cells to pathogens and multicellular organisms. Protein N-myristoylation, S-acylation, and S-prenylation are the most well-studied lipid post-translational modifications because of their extensive contribution to the regulation of diverse cellular processes. In this review, we focus on recent advances in the study of these post-translational modifications, with an emphasis on how novel mass spectrometry methods have elucidated their roles in fundamental biological processes.     

Ligand specificity and evolution of liver X receptors

Liver X receptors (LXRs) are key regulators of lipid and cholesterol metabolism in mammals. Little is known, however, about the function and evolution of LXRs in non-mammalian species. The present study reports the cloning of LXRs from African clawed frog (Xenopus laevis), Western clawed frog (Xenopus tropicalis), and zebrafish (Danio rerio), and their functional characterization and comparison with human and mouse LXRs. Additionally, an ortholog of LXR in the chordate invertebrate Ciona intestinalis was cloned and functionally characterized. Ligand specificities of the frog and zebrafish LXRs were very similar to LXRalpha and LXRbeta from human and mouse. All vertebrate LXRs studied were activated robustly by the synthetic ligands T-0901317 and GW3965 and by a variety of oxysterols. In contrast, Ciona LXR was not activated by T-0901317 or GW3965 but was activated by a limited number of oxysterols, as well as some androstane and pregnane steroids. Pharmacophore analysis, homology modeling, and docking studies of Ciona LXR predict a receptor with a more restricted ligand-binding pocket and less intrinsic disorder in the ligand-binding domain compared to vertebrate LXRs. The results suggest that LXRs have a long evolutionary history, with vertebrate LXRs diverging from invertebrate LXRs in ligand specificity.     

Ligand binding systems at equilibrium: specificity, heterogeneity, cross-reactivity, and site-site interactions

The simplest ligand binding model that can account for systems which consist of heterogeneous receptors that show site-site interactions and can react with several types of ligands was presented. This model was based on the grand canonical partition function whose properties and potentialities for obtaining binding functions are briefly illustrated. A computer simulation of this model was carried out in order to examine the contributions of site-site interactions on the shape of binding isotherms and on specificity curves. The shape of the binding isotherms was shown to be independent regardless of whether the path of binding was considered. However, the shape of the specificity curves was strongly dependent on site-site interactions and on the particular sequence of ligand-receptor configurations formed during the ligand binding process, leading to the conclusion that site-site interactions may influence the specificity of a system more than even very strong cross-reactions. A method based on the Ising model of statistical mechanics was also described and was used for obtaining binding functions applicable to infinite lattices which show site-site interactions and competitive binding. The results presented here point out possible errors that can arise if standard statistical methods are used to fit binding data in order to prove a given binding model.     

Structure-based computational analysis of protein binding sites for function and druggability prediction

Protein binding sites are the places where molecular interactions occur. Thus, the analysis of protein binding sites is of crucial importance to understand the biological processes proteins are involved in. Herein, we focus on the computational analysis of protein binding sites and present structure-based methods that enable function prediction for orphan proteins and prediction of target druggability. We present the general ideas behind these methods, with a special emphasis on the scopes and limitations of these methods and their validation. Additionally, we present some successful applications of computational binding site analysis to emphasize the practical importance of these methods for biotechnology/bioeconomy and drug discovery.     

Ligand specificity of H-NOX domains: from sGC to bacterial NO sensors

Soluble guanylate cyclase (sGC) is a nitric oxide (NO) sensing hemoprotein that has been found in eukaryotes from Drosophila to humans. Prokaryotic proteins with significant homology to the heme domain of sGC have recently been identified through genomic analysis. This family of heme proteins has been named the H-NOX domain, for Heme-Nitric oxide/OXygen binding domain. The key observation from initial studies in this family is that some members, those proteins from most eukaryotes and facultative aerobic prokaryotes, bind NO in a five-coordinate heme complex, but do not bind oxygen (O(2)), the same ligand binding characteristics as sGC. H-NOX family members from obligate aerobic prokaryotes bind O(2) and NO in six-coordinate complexes, similar to the globins and other O(2)-sensing heme proteins. The molecular factors that contribute to these differences in ligand specificity, within a family of sequence related proteins, are the subject of this review.     

Determining functional specificity from protein sequences

MOTIVATION: Given a large family of homologous protein sequences, many methods can divide the family into smaller groups that correspond to the different functions carried out by proteins within the family. One important problem, however, has been the absence of a general method for selecting an appropriate level of granularity, or size of the groups. RESULTS: We propose a consistent way of choosing the granularity that is independent of the sequence similarity and sequence clustering method used. We study three large, well-investigated protein families: basic leucine zippers, nuclear receptors and proteins with three consecutive C2H2 zinc fingers. Our method is tested against known functional information, the experimentally determined binding specificities, using a simple scoring method. The significance of the groups is also measured by randomizing the data. Finally, we compare our algorithm against a popular method of grouping proteins, the TRIBE-MCL method. In the end, we determine that dividing the families at the proposed level of granularity creates very significant and useful groups of proteins that correspond to the different DNA-binding motifs. We expect that such groupings will be useful in studying not only DNA binding but also other protein interactions.     

Allosteric perspective on the mutability and druggability of the SARS-CoV-2 Spike protein

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Ligand specificity and ligand-induced conformational change in gal repressor

Gal repressor (GalR) binds D-galactose, which is responsible for lifting of repression of the gal operon. Proton T1 measurements of alpha- and beta-anomers of galactose as a function of gal repressor show preferential binding of the beta-anomer. The beta-anomer was isolated by high-performance liquid chromatography and was shown to bind tightly to GalR. Calorimetry was used to determine enthalpy changes at several temperatures. Heat capacity change was found to be positive, indicating that a significant amount of hydrophobic surface area was exposed upon galactose binding. Bis-ANS binding to GalR is significantly enhanced in the presence of a saturating amount of galactose, indicating additional exposure of hydrophobic surfaces. We propose that the galactose-induced conformational change involves the opening of the two subdomains, which may disrupt protein-protein interactions responsible for repression.     

Using known substructures in protein model building and crystallography.

Retinol binding protein can be constructed from a small number of large substructures taken from three unrelated proteins. The known structures are treated as a knowledge base from which one extracts information to be used in molecular modelling when lacking true atomic resolution. This includes the interpretation of electron density maps and modelling homologous proteins. Models can be built into maps more accurately and more quickly. This requires the use of a skeleton representation for the electron density which improves the determination of the initial chain tracing. Fragment-matching can be used to bridge gaps for inserted residues when modelling homologous proteins.     

Evolution of protein specificity: insights from ancestral protein reconstruction

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