X-ray crystallography over the past decade for novel drug discovery - where are we heading next?

Molecular Dynamic Simulations for Biopolymers with Biomedical Applications

Computational modeling (CM) is a versatile scientific methodology used to examine the properties and behavior of complex systems, such as polymeric materials for biomedical bioengineering. CM has emerged as a primary tool for predicting, setting up, and interpreting experimental results. Integrating in silico and in vitro experiments accelerates scientific advancements, yielding quicker results at a reduced cost. While CM is a mature discipline, its use in biomedical engineering for biopolymer materials has only recently gained prominence. In biopolymer biomedical engineering, CM focuses on three key research areas: (A) Computer-aided design (CAD/CAM) utilizes specialized software to design and model biopolymers for various biomedical applications. This technology allows researchers to create precise three-dimensional models of biopolymers, taking into account their chemical, structural, and functional properties. These models can be used to enhance the structure of biopolymers and improve their effectiveness in specific medical applications. (B) Finite element analysis, a computational technique used to analyze and solve problems in engineering and physics. This approach divides the physical domain into small finite elements with simple geometric shapes. This computational technique enables the study and understanding of the mechanical and structural behavior of biopolymers in biomedical environments. (C) Molecular dynamics (MD) simulations involve using advanced computational techniques to study the behavior of biopolymers at the molecular and atomic levels. These simulations are fundamental for better understanding biological processes at the molecular level. Studying the wide-ranging uses of MD simulations in biopolymers involves examining the structural, functional, and evolutionary aspects of biomolecular systems over time. MD simulations solve Newton's equations of motion for all-atom systems, producing spatial trajectories for each atom. This provides valuable insights into properties such as water absorption on biopolymer surfaces and interactions with solid surfaces, which are crucial for assessing biomaterials. This review provides a comprehensive overview of the various applications of MD simulations in biopolymers. Additionally, it highlights the flexibility, robustness, and synergistic relationship between in silico and experimental techniques.

A Novel NMR-Based Protocol to Screen Ultralow Molecular Weight Fragments

Fragment-based lead discovery has emerged as one of the most efficient screening strategies for finding hit molecules in drug discovery. Recently, a novel strategy based on a class of fragments characterized by an ultralow molecular weight (ULMW) has been proposed. These fragments bind to the target with a very low affinity, requiring reliable biophysical methods for detection. The most notable application of ULMW used a set of 81 fragments, named MiniFrags, and screened them by X-ray crystallography. We extended the utilization of this novel class of fragments to another gold standard technique for fragment-based screening: nuclear magnetic resonance (NMR). Here, we present a novel NMR protocol to detect and analyze such weak interactions in a challenging real-world scenario: a flexible target with a flat, water-exposed binding site. We identified a subset of 69 highly water-soluble MiniFrags that were screened against the antiapoptotic protein human Bfl-1.

Molecular Gas-Phase Conformational Ensembles

Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility-mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.

Chemical Reactions in Living Systems

The term "in vivo ("in the living") chemistry" refers to chemical reactions that take place in a complex living system such as cells, tissue, body liquids, or even in an entire organism. In contrast, reactions that occur generally outside living organisms in an artificial environment (e.g., in a test tube) are referred to as in vitro. Over the past decades, significant contributions have been made in this rapidly growing field of in vivo chemistry, but it is still not fully understood, which transformations proceed efficiently without the formation of by-products or how product formation in such complex environments can be characterized. Potential applications can be imagined that synthesize drug molecules directly within the cell or confer new cellular functions through controlled chemical transformations that will improve the understanding of living systems and develop new therapeutic strategies. The guiding principles of this contribution are twofold: 1) Which chemical reactions can be translated from the laboratory to the living system? 2) Which characterization methods are suitable for studying reactions and structure formation in complex living environments?

Strengthening E-cadherin adhesion via antibody-mediated binding stabilization

E-cadherins (Ecads) are a crucial cell-cell adhesion protein with tumor suppression properties. Ecad adhesion can be enhanced by the monoclonal antibody 66E8, which has potential applications in inhibiting cancer metastasis. However, the biophysical mechanisms underlying 66E8-mediated adhesion strengthening are unknown. Here, we use molecular dynamics simulations, site-directed mutagenesis, and single-molecule atomic force microscopy experiments to demonstrate that 66E8 strengthens Ecad binding by stabilizing the primary Ecad adhesive conformation: the strand-swap dimer. By forming electrostatic interactions with Ecad, 66E8 stabilizes the swapped β-strand and its hydrophobic pocket and impedes Ecad conformational changes, which are necessary for rupture of the strand-swap dimer. Our findings identify fundamental mechanistic principles for strengthening of Ecad binding using monoclonal antibodies.

Mechanistic Insights into S-Depalmitolyse Activity of Cln5 Protein Linked to Neurodegeneration and Batten Disease: A QM/MM Study

Ceroid lipofuscinosis neuronal protein 5 (Cln5) is encoded by the CLN5 gene. The genetic variants of this gene are associated with the CLN5 form of Batten disease. Recently, the first crystal structure of Cln5 was reported. Cln5 shows cysteine palmitoyl thioesterase S-depalmitoylation activity, which was explored via fluorescent emission spectroscopy utilizing the fluorescent probe DDP-5. In this work, the mechanism of the reaction between Cln5 and DDP-5 was studied computationally by applying a QM/MM methodology at the ωB97X-D/6-31G(d,p):AMBER level. The results of our study clearly demonstrate the critical role of the catalytic triad Cys280-His166-Glu183 in S-depalmitoylation activity. This is evidenced through a comparison of the pathways catalyzed by the Cys280-His166-Glu183 triad and those with only Cys280 involved. The computed reaction barriers are in agreement with the catalytic efficiency. The calculated Gibb's free-energy profile suggests that S-depalmitoylation is a rate-limiting step compared to the preceding S-palmitoylation, with barriers of 26.1 and 25.3 kcal/mol, respectively. The energetics were complemented by monitoring the fluctuations in the electron density distribution through NBO charges and bond strength alterations via local mode stretching force constants during the catalytic pathways. This comprehensive protocol led to a more holistic picture of the reaction mechanism at the atomic level. It forms the foundation for future studies on the effects of gene mutations on both the S-palmitoylation and S-depalmitoylation steps, providing valuable data for the further development of enzyme replacement therapy, which is currently the only FDA-approved therapy for childhood neurodegenerative diseases, including Batten disease.

Exploring the World of Membrane Proteins: Techniques and Methods for Understanding Structure, Function, and Dynamics

In eukaryotic cells, membrane proteins play a crucial role. They fall into three categories: intrinsic proteins, extrinsic proteins, and proteins that are essential to the human genome (30% of which is devoted to encoding them). Hydrophobic interactions inside the membrane serve to stabilize integral proteins, which span the lipid bilayer. This review investigates a number of computational and experimental methods used to study membrane proteins. It encompasses a variety of technologies, including electrophoresis, X-ray crystallography, cryogenic electron microscopy (cryo-EM), nuclear magnetic resonance spectroscopy (NMR), biophysical methods, computational methods, and artificial intelligence. The link between structure and function of membrane proteins has been better understood thanks to these approaches, which also hold great promise for future study in the field. The significance of fusing artificial intelligence with experimental data to improve our comprehension of membrane protein biology is also covered in this paper. This effort aims to shed light on the complexity of membrane protein biology by investigating a variety of experimental and computational methods. Overall, the goal of this review is to emphasize how crucial it is to understand the functions of membrane proteins in eukaryotic cells. It gives a general review of the numerous methods used to look into these crucial elements and highlights the demand for multidisciplinary approaches to advance our understanding.

Strengthening E-cadherin adhesion via antibody mediated binding stabilization

E-cadherins (Ecads) are a crucial cell-cell adhesion protein with tumor suppression properties. Ecad adhesion can be enhanced by the monoclonal antibody 66E8, which has potential applications in inhibiting cancer metastasis. However, the biophysical mechanisms underlying 66E8 mediated adhesion strengthening are unknown. Here, we use molecular dynamics simulations, site directed mutagenesis and single molecule atomic force microscopy experiments to demonstrate that 66E8 strengthens Ecad binding by stabilizing the primary Ecad adhesive conformation: the strand-swap dimer. By forming electrostatic interactions with Ecad, 66E8 stabilizes the swapped β-strand and its hydrophobic pocket and impedes Ecad conformational changes, which are necessary for rupture of the strand-swap dimer. Our findings identify fundamental mechanistic principles for strengthening of Ecad binding using monoclonal antibodies.

The current role and evolution of X-ray crystallography in drug discovery and development

INTRODUCTION

Macromolecular X-ray crystallography and cryo-EM are currently the primary techniques used to determine the three-dimensional structures of proteins, nucleic acids, and viruses. Structural information has been critical to drug discovery and structural bioinformatics. The integration of artificial intelligence (AI) into X-ray crystallography has shown great promise in automating and accelerating the analysis of complex structural data, further improving the efficiency and accuracy of structure determination.

AREAS COVERED

This review explores the relationship between X-ray crystallography and other modern structural determination methods. It examines the integration of data acquired from diverse biochemical and biophysical techniques with those derived from structural biology. Additionally, the paper offers insights into the influence of AI on X-ray crystallography, emphasizing how integrating AI with experimental approaches can revolutionize our comprehension of biological processes and interactions.

EXPERT OPINION

Investing in science is crucially emphasized due to its significant role in drug discovery and advancements in healthcare. X-ray crystallography remains an essential source of structural biology data for drug discovery. Recent advances in biochemical, spectroscopic, and bioinformatic methods, along with the integration of AI techniques, hold the potential to revolutionize drug discovery when effectively combined with robust data management practices.

Epitopes and Mimotopes Identification Using Phage Display for Vaccine Development against Infectious Pathogens

Traditional vaccines use inactivated or weakened forms of pathogens which could have side effects and inadequate immune responses. To overcome these challenges, phage display has emerged as a valuable tool for identifying specific epitopes that could be used in vaccines. This review emphasizes the direct connection between epitope identification and vaccine development, filling a crucial gap in the field. This technique allows vaccines to be engineered to effectively stimulate the immune system by presenting carefully selected epitopes. Phage display involves screening libraries of random peptides or gene/genome fragments using serum samples from infected, convalescent, or vaccinated individuals. This method has been used to identify epitopes from various pathogens including SARS-CoV-2, Mycobacterium tuberculosis, hepatitis viruses, H5N1, HIV-1, Human T-lymphotropic virus 1, Plasmodium falciparum, Trypanosoma cruzi, and Dirofilaria repens. Bacteriophages offer advantages such as being immunogenic carriers, low production costs, and customization options, making them a promising alternative to traditional vaccines. The purpose of this study has been to highlight an approach that encompasses the entire process from epitope identification to vaccine production using a single technique, without requiring additional manipulation. Unlike conventional methods, phage display demonstrates exceptional efficiency and speed, which could provide significant advantages in critical scenarios such as pandemics.

A Flexible, Modular Platform for Multidimensional Ion Mobility of Native-like Ions

Native ion mobility (IM) mass spectrometry (MS) is used to probe the size, shape, and assembly of biomolecular complexes. IM-IM-MS can increase the amount of information available in structural studies by isolating subpopulations of structures for further analysis. Previously, IM-IM-MS has been implemented using the Structures for Lossless Ion Manipulations (SLIM) architecture to probe the structural stability of gas-phase protein ions. Here, a new multidimensional IM instrument constructed from SLIM devices is characterized using multiple operational modes. In this new design, modular devices are used to perform all ion manipulations, including initial accumulation, injection, separation, selection, and trapping. Using single-dimension IM, collision cross section (Ω) values are determined for a set of native-like ions. These Ω values are within 3% of those reported previously based on measurements using RF-confining drift cells. Tandem IM experiments are performed on a sample of ubiquitin ions that contains both compact and partially unfolded structures, demonstrating that this platform can isolate subpopulations of structures. Finally, additional modes of analysis, including multiplexed IM and inverse IM, are demonstrated using this platform. The ability of this platform to quickly switch between different modes of IM analysis makes it a highly flexible tool for studying protein structures and dynamics.

Molecular disease mechanisms of human antineuronal monoclonal autoantibodies

Autoantibodies targeting brain antigens can mediate a wide range of neurological symptoms ranging from epileptic seizures to psychosis to dementia. Although earlier experimental work indicated that autoantibodies can be directly pathogenic, detailed studies on disease mechanisms, biophysical autoantibody properties, and target interactions were hampered by the availability of human material and the paucity of monospecific disease-related autoantibodies. The emerging generation of patient-derived monoclonal autoantibodies (mAbs) provides a novel platform for the detailed characterization of immunobiology and autoantibody pathogenicity in vitro and in animal models. This Feature Review focuses on recent advances in mAb generation and discusses their potential as powerful scientific tools for high-resolution imaging, antigenic target identification, atomic-level structural analyses, and the development of antibody-selective immunotherapies.

Boosting Protein-Ligand Binding Pose Prediction and Virtual Screening Based on Residue-Atom Distance Likelihood Potential and Graph Transformer

The past few years have witnessed enormous progress toward applying machine learning approaches to the development of protein-ligand scoring functions. However, the robust performance and wide applicability of scoring functions remain a big challenge for increasing the success rate of docking-based virtual screening. Herein, a novel scoring function named RTMScore was developed by introducing a tailored residue-based graph representation strategy and several graph transformer layers for the learning of protein and ligand representations, followed by a mixture density network to obtain residue-atom distance likelihood potential. Our approach was resolutely validated on the CASF-2016 benchmark, and the results indicate that RTMScore can outperform almost all of the other state-of-the-art methods in terms of both the docking and screening powers. Further evaluation confirms the robustness of our approach that can not only retain its docking power on cross-docked poses but also achieve improved performance as a rescoring tool in larger-scale virtual screening.

A Selective Alkylating Agent for CTG Repeats in Myotonic Dystrophy Type 1

Disease intervention at the DNA level generally has been avoided because of off-target effects. Recent advances in genome editing technologies using CRISPR-Cas9 have opened a new era in DNA-targeted therapeutic approaches. However, delivery of such systems remains a major challenge. Here, we report a selective DNA-modifying small molecule that targets a disease-specific structure and mismatches involved in myotonic dystrophy type 1 (DM1). This ligand alkylates T-T mismatch-containing hairpins formed in the expanded CTG repeats (d(CTG)^exp) in DM1. Ligand alkylation of d(CTG)^exp inhibits the transcription of d(CAG·CTG)^exp, thereby reducing the level of the toxic r(CUG)^exp transcript. The bioactivity of the ligand also included a reduction in DM1 pathological features such as disease foci formation and misregulation of pre-mRNA splicing in DM1 model cells. Furthermore, the CTG-alkylating ligand may change the d(CAG·CTG)^exp repeat length dynamics in DM1 patient cells. Our strategy of linking an alkylating moiety to a DNA mismatch-selective small molecule may be generally applicable to other repeat expansion diseases such as Huntington's disease and amyotrophic lateral sclerosis.

Visualizing RNA Structures by SAXS-Driven MD Simulations

The biological role of biomolecules is intimately linked to their structural dynamics. Experimental or computational techniques alone are often insufficient to determine accurate structural ensembles in atomic detail. We use all-atom molecular dynamics (MD) simulations and couple it to small-angle X-ray scattering (SAXS) experiments to resolve the structural dynamics of RNA molecules. To accomplish this task, we utilize a set of re-weighting and biasing techniques tailored for RNA molecules. To showcase our approach, we study two RNA molecules: a riboswitch that shows structural variations upon ligand binding, and a two-way junction RNA that displays structural heterogeneity and sensitivity to salt conditions. Integration of MD simulations and experiments allows the accurate construction of conformational ensembles of RNA molecules. We observe a dynamic change of the SAM-I riboswitch conformations depending on its binding partners. The binding of SAM and Mg²⁺ cations stabilizes the compact state. The absence of Mg²⁺ or SAM leads to the loss of tertiary contacts, resulting in a dramatic expansion of the riboswitch conformations. The sensitivity of RNA structures to the ionic strength demonstrates itself in the helix junction helix (HJH). The HJH shows non-monotonic compaction as the ionic strength increases. The physics-based picture derived from the experimentally guided MD simulations allows biophysical characterization of RNA molecules. All in all, SAXS-guided MD simulations offer great prospects for studying RNA structural dynamics.

Fragment-Based Drug Discovery by NMR. Where Are the Successes and Where can It Be Improved?

Over the last century, the definitions of pharmaceutical drug and drug discovery have changed considerably. Evolving from an almost exclusively serendipitous approach, drug discovery nowadays involves several distinct, yet sometimes interconnected stages aimed at obtaining molecules able to interact with a defined biomolecular target, and triggering a suitable biological response. At each of the stages, a wide range of techniques are typically employed to obtain the results required to move the project into the next stage. High Throughput Screening (HTS) and Fragment Based Drug Design (FBDD) are the two main approaches used to identify drug-like candidates in the early stages of drug discovery. Nuclear Magnetic Resonance (NMR) spectroscopy has many applications in FBDD and is used extensively in industry as well as in academia. In this manuscript, we discuss the paths of both successful and unsuccessful molecules where NMR had a crucial part in their development. We specifically focus on the techniques used and describe strengths and weaknesses of each stage by examining several case studies. More precisely, we examine the development history from the primary screening to the final lead optimisation of AZD3839 interacting with BACE-1, ABT-199 interacting with BCL2/XL and S64315 interacting with MCL-1. Based on these studies, we derive observations and conclusions regarding the FBDD process by NMR and discuss its potential improvements.

Deciphering the high viscosity of a therapeutic monoclonal antibody in high concentration formulations by microdialysis-hydrogen/deuterium exchange mass spectrometry

High concentration formulations of therapeutic monoclonal antibodies (mAbs) are highly desired for subcutaneous injection. However, high concentration formulations can exhibit unusual molecular behaviors, such as high viscosity or aggregation, that present challenges for manufacturing and administration. To understand the molecular mechanism of the high viscosity exhibited by high concentration protein formulations, we analyzed a human IgG4 (mAb1) at high protein concentrations using sedimentation velocity analytical ultracentrifugation (SV-AUC), X-ray crystallography, hydrogen/deuterium exchange mass spectrometry (HDX-MS), and protein surface patches analysis. Particularly, we developed a microdialysis HDX-MS method to determine intermolecular interactions at different protein concentrations. SV-AUC revealed that mAb1 displayed a propensity for self-association of Fab-Fab, Fab-Fc, and Fc-Fc. mAb1 crystal structure and HDX-MS results demonstrated self-association between complementarity-determining regions (CDRs) and Fc through electrostatic interactions. HDX-MS also indicated Fab-Fab interactions through hydrophobic surface patches constructed by mAb1 CDRs. Our multi-method approach, including fast screening of SV-AUC as well as interface analysis by X-ray crystallography and HDX-MS, helped to elucidate the high viscosity of mAb1 at high concentrations as induced by self-associations of Fab-Fc and Fab-Fab.

Implementing Digital-Waveform Technology for Extended m/z Range Operation on a Native Dual-Quadrupole FT-IM-Orbitrap Mass Spectrometer

Here, we describe a digital-waveform dual-quadrupole mass spectrometer that enhances the performance of our drift tube FT-IMS high-resolution Orbitrap mass spectrometer (MS). The dual-quadrupole analyzer enhances the instrument capabilities for studies of large protein and protein complexes. The first quadrupole (q) provides a means for performing low-energy collisional activation of ions to reduce or eliminate noncovalent adducts, viz., salts, buffers, detergents, and/or endogenous ligands. The second quadrupole (Q) is used to mass-select ions of interest for further interrogation by ion mobility spectrometry and/or collision-induced dissociation (CID). Q is operated using digital-waveform technology (DWT) to improve the mass selection compared to that achieved using traditional sinusoidal waveforms at floated DC potentials (>500 V DC). DWT allows for increased precision of the waveform for a fraction of the cost of conventional RF drivers and with readily programmable operation and precision (Hoffman, N. M. . A comparison-based digital-waveform generator for high-resolution duty cycle. Review of Scientific Instruments 2018, 89, 084101).

Residue-based pharmacophore approaches to study protein-protein interactions

This review focuses on pharmacophore approaches in researching protein interfaces that bind protein ligands. Pharmacophore descriptions of binding interfaces that employ molecular dynamics simulation can account for effects of solvation and conformational flexibility. In addition, these calculations provide an approximation to entropic considerations and as such, a better approximation of the free energy of binding. Residue-based pharmacophore approaches can facilitate a variety of drug discovery tasks such as the identification of receptor-ligand partners, identifying their binding poses, designing protein interfaces for selectivity, or defining a reduced mutational combinatorial exploration for subsequent experimental engineering techniques by orders of magnitudes.

The Structure and Mechanism of Drug Transporters

Drug transporters are integral membrane proteins that play a critical role in drug disposition by affecting absorption, distribution, and excretion. They translocate drugs, as well as endogenous molecules and toxins, across membranes using ATP hydrolysis, or ion/concentration gradients. In general, drug transporters are expressed ubiquitously, but they function in drug disposition by being concentrated in tissues such as the intestine, the kidneys, the liver, and the brain. Based on their primary sequence and their mechanism, transporters can be divided into the ATP-binding cassette (ABC), solute-linked carrier (SLC), and the solute carrier organic anion (SLCO) superfamilies. Many X-ray crystallography and cryo-electron microscopy (cryo-EM) structures have been solved in the ABC and SLC transporter superfamilies or of their bacterial homologs. The structures have provided valuable insight into the structural basis of transport. This chapter will provide particular focus on the promiscuous drug transporters because of their effect on drug disposition and the challenges associated with them.

First-Principles Collision Cross Section Measurements of Large Proteins and Protein Complexes

Rotationally averaged collision cross section (CCS) values for a series of proteins and protein complexes ranging in size from 8.6 to 810 kDa are reported. The CCSs were obtained using a native electrospray ionization drift tube ion mobility-Orbitrap mass spectrometer specifically designed to enhance sensitivity while having high-resolution ion mobility and mass capabilities. Periodic focusing (PF)-drift tube (DT)-ion mobility (IM) provides first-principles determination of the CCS of large biomolecules that can then be used as CCS calibrants. The experimental, first-principles CCS values are compared to previously reported experimentally determined and computationally calculated CCS using projected superposition approximation (PSA), the Ion Mobility Projection Approximation Calculation Tool (IMPACT), and Collidoscope. Experimental CCS values are generally in agreement with previously reported CCSs, with values falling within ∼5.5%. In addition, an ion mobility resolution (CCS centroid divided by CCS fwhm) of ∼60 is obtained for pyruvate kinase (MW ∼ 233 kDa); however, ion mobility resolution for bovine serum albumin (MW ∼ 68 kDa) is less than ∼20, which arises from sample impurities and underscores the importance of sample quality. The high resolution afforded by the ion mobility-Orbitrap mass analyzer provides new opportunities to understand the intricate details of protein complexes such as the impact of post-translational modifications (PTMs), stoichiometry, and conformational changes induced by ligand binding.

Characterizing Epitope Binding Regions of Entire Antibody Panels by Combining Experimental and Computational Analysis of Antibody: Antigen Binding Competition

Vaccines and immunotherapies depend on the ability of antibodies to sensitively and specifically recognize particular antigens and specific epitopes on those antigens. As such, detailed characterization of antibody-antigen binding provides important information to guide development. Due to the time and expense required, high-resolution structural characterization techniques are typically used sparingly and late in a development process. Here, we show that antibody-antigen binding can be characterized early in a process for whole panels of antibodies by combining experimental and computational analyses of competition between monoclonal antibodies for binding to an antigen. Experimental "epitope binning" of monoclonal antibodies uses high-throughput surface plasmon resonance to reveal which antibodies compete, while a new complementary computational analysis that we call "dock binning" evaluates antibody-antigen docking models to identify why and where they might compete, in terms of possible binding sites on the antigen. Experimental and computational characterization of the identified antigenic hotspots then enables the refinement of the competitors and their associated epitope binding regions on the antigen. While not performed at atomic resolution, this approach allows for the group-level identification of functionally related monoclonal antibodies (i.e., communities) and identification of their general binding regions on the antigen. By leveraging extensive epitope characterization data that can be readily generated both experimentally and computationally, researchers can gain broad insights into the basis for antibody-antigen recognition in wide-ranging vaccine and immunotherapy discovery and development programs.

In Situ Proteolysis Condition-Induced Crystallization of the XcpVWX Complex in Different Lattices

Although prevalent in the determination of protein structures; crystallography always has the bottleneck of obtaining high-quality protein crystals for characterizing a wide range of proteins; especially large protein complexes. Stable fragments or domains of proteins are more readily to crystallize; which prompts the use of in situ proteolysis to remove flexible or unstable structures for improving crystallization and crystal quality. In this work; we investigated the effects of in situ proteolysis by chymotrypsin on the crystallization of the XcpVWX complex from the Type II secretion system of Pseudomonas aeruginosa. Different proteolysis conditions were found to result in two distinct lattices in the same crystallization solution. With a shorter chymotrypsin digestion at a lower concentration; the crystals exhibited a P3 hexagonal lattice that accommodates three complex molecules in one asymmetric unit. By contrast; a longer digestion with chymotrypsin of a 10-fold higher concentration facilitated the formation of a compact P2₁2₁2₁ orthorhombic lattice with only one complex molecule in each asymmetric unit. The molecules in the hexagonal lattice have shown high atomic displacement parameter values compared with the ones in the orthorhombic lattice. Taken together; our results clearly demonstrate that different proteolysis conditions can result in the generation of distinct lattices in the same crystallization solution; which can be exploited in order to obtain different crystal forms of a better quality

Using cryo-electron microscopy maps for X-ray structure determination of homologues

The combination of cryo-electron microscopy (cryo-EM) and X-ray crystallography reflects an important trend in structural biology. In a previously published study, a hybrid method for the determination of X-ray structures using initial phases provided by the corresponding parts of cryo-EM maps was presented. However, if the target structure of X-ray crystallography is not identical but homologous to the corresponding molecular model of the cryo-EM map, then the decrease in the accuracy of the starting phases makes the whole process more difficult. Here, a modified hybrid method is presented to handle such cases. The whole process includes three steps: cryo-EM map replacement, phase extension by NCS averaging and dual-space iterative model building. When the resolution gap between the cryo-EM and X-ray crystallographic data is large and the sequence identity is low, an intermediate stage of model building is necessary. Six test cases have been studied with sequence identity between the corresponding molecules in the cryo-EM and X-ray structures ranging from 34 to 52% and with sequence similarity ranging from 86 to 91%. This hybrid method consistently produced models with reasonable R_work and R_free values which agree well with the previously determined X-ray structures for all test cases, thus indicating the general applicability of the method for X-ray structure determination of homologues using cryo-EM maps as a starting point.

Dynamic signature of ligand binding over a protein surface

We study the motion of Zn^{2+} in the presence of ubiquitin by all-atom molecular-dynamics simulations. We observe that unlike normal diffusive liquid, metal ions show an exponential tail in the self-van Hove function (self-vHf). Moreover, the metal ions are trapped strongly by acidic residues which form a binding pocket over the protein surface. The exponential tail disappears by mutation of trapping residues, suggesting that the tail appears due to trapped motion of the ions. The mean-squared displacements, however, in all the cases show linear dependence on time. Our model establishes that ligand binding generically results in an exponential tail of self-vHf. The self-vHf may give an approach to find binding pockets over a protein surface.

Matching pH values for antibody stabilization and crystallization suggest rationale for accelerated development of biotherapeutic drugs

Monoclonal antibodies (mAbs) are currently leading products in the global biopharmaceutical market. Multiple mAbs are in clinical development and novel biotherapeutic protein scaffolds, based on the canonical immunoglobulin G (IgG) fold, are emerging as treatment options for various medical conditions. However, fast approvals for biotherapeutics are challenging to achieve, because of difficult scientific development procedures and complex regulatory processes. Selecting molecular entities with superior physicochemical properties that proceed into clinical trials and the identification of stable formulations are crucial developability aspects. It is widely accepted that the solution pH has critical influences on both the protein's colloidal stability and its crystallization behavior. Furthermore, proteins usually crystallize best at solution conditions that enable high protein solubility, purity, stability, and monodispersity. Therefore, we hypothesize that the solution pH value is a central parameter that is linking together protein formulation, protein crystallization, and thermal protein stability. In order to experimentally test this hypothesis, we have investigated the effect of the solution pH on the thermal stabilities and crystallizabilities for three different mAbs. Combining biophysical measurements with high throughput protein (HTP) crystallization trials we observed a correlation in the buffer pH values for eminent mAb stability and successful crystallization. Specifically, differential scanning fluorimetry (DSF) was used to determine pH values that exert highest thermal mAb stabilities and additionally led to the identification of unfolding temperatures of individual mAb domains. Independently performed crystallization trials with the same mAbs resulted in their successful crystallization at pH values that displayed highest thermal stabilities. In summary, the presented results suggest a strategy how protein crystallization could be used as a screening method for the development of biotherapeutic protein formulations with improved in vitro stabilities.

Molstack: A platform for interactive presentations of electron density and cryo-EM maps and their interpretations

In the Special Issue on Tools for Protein Science in 2018, we presented Molstack: a concept of a cloud-based platform for sharing electron density maps and their interpretations. Molstack is a web platform that allows the interactive visualization of density maps through the simultaneous presentation of multiple datasets and models in a way that allows for easy pairwise comparison. We anticipated that the users of this conceptually simple platform would find many different uses for their projects, and we were not mistaken. We have observed researchers use Molstack to present experimental evidence for their models in the form of electron density maps, omit maps, and anomalous difference density maps. Users also employed Molstack to present alternative interpretations of densities, including rerefinements and speculative interpretations. While we anticipated these types of projects to be the main use cases, we were pleased to see Molstack used to display superpositions of different models, as a tool for story-driven presentations, and for collaboration as well. Here, we present developments in the platform that were driven by user feedback, highlight several cases that used Molstack to enhance the publication, and discuss possible directions for the platform.

Crystal contact-free conformation of an intrinsically flexible loop in protein crystal: Tim21 as the case study

BACKGROUND

In protein crystals, flexible loops are frequently deformed by crystal contacts, whereas in solution, the large motions result in the poor convergence of such flexible loops in NMR structure determinations. We need an experimental technique to characterize the structural and dynamic properties of intrinsically flexible loops of protein molecules.

METHODS

We designed an intended crystal contact-free space (CCFS) in protein crystals, and arranged the flexible loop of interest in the CCFS. The yeast Tim 21 protein was chosen as the model protein, because one of the loops (loop 2) is distorted by crystal contacts in the conventional crystal.

RESULTS

Yeast Tim21 was fused to the MBP protein by a rigid α-helical linker. The space created between the two proteins was used as the CCFS. The linker length provides adjustable freedom to arrange loop 2 in the CCFS. We re-determined the NMR structure of yeast Tim21, and conducted MD simulations for comparison. Multidimensional scaling was used to visualize the conformational similarity of loop 2. We found that the crystal contact-free conformation of loop 2 is located close to the center of the ensembles of the loop 2 conformations in the NMR and MD structures.

CONCLUSIONS

Loop 2 of yeast Tim21 in the CCFS adopts a representative, dominant conformation in solution.

GENERAL SIGNIFICANCE

No single powerful technique is available for the characterization of flexible structures in protein molecules. NMR analyses and MD simulations provide useful, but incomplete information. CCFS crystallography offers a third route to this goal.

The role of small-angle scattering in structure-based screening applications

In many biomolecular interactions, changes in the assembly states and structural conformations of participants can act as a complementary reporter of binding to functional and thermodynamic assays. This structural information is captured by a number of structural biology and biophysical techniques that are viable either as primary screens in small-scale applications or as secondary screens to complement higher throughput methods. In particular, small-angle X-ray scattering (SAXS) reports the average distance distribution between all atoms after orientational averaging. Such information is important when for example investigating conformational changes involved in inhibitory and regulatory mechanisms where binding events do not necessarily cause functional changes. Thus, we summarise here the current and prospective capabilities of SAXS-based screening in the context of other methods that yield structural information. Broad guidelines are also provided to assist readers in preparing screening protocols that are tailored to available X-ray sources.

Biophysical, Biochemical, and Cell Based Approaches Used to Decipher the Role of Carbonic Anhydrases in Cancer and to Evaluate the Potency of Targeted Inhibitors

Carbonic anhydrases (CAs) are thought to be important for regulating pH in the tumor microenvironment. A few of the CA isoforms are upregulated in cancer cells, with only limited expression in normal cells. For these reasons, there is interest in developing inhibitors that target these tumor-associated CA isoforms, with increased efficacy but limited nonspecific cytotoxicity. Here we present some of the biophysical, biochemical, and cell based techniques and approaches that can be used to evaluate the potency of CA targeted inhibitors and decipher the role of CAs in tumorigenesis, cancer progression, and metastatic processes. These techniques include esterase activity assays, stop flow kinetics, and mass inlet mass spectroscopy (MIMS), all of which measure enzymatic activity of purified protein, in the presence or absence of inhibitors. Also discussed is the application of X-ray crystallography and Cryo-EM as well as other structure-based techniques and thermal shift assays to the studies of CA structure and function. Further, large-scale genomic and proteomic analytical methods, as well as cell based techniques like those that measure cell growth, apoptosis, clonogenicity, and cell migration and invasion, are discussed. We conclude by reviewing approaches that test the metastatic potential of CAs and how the aforementioned techniques have contributed to the field of CA cancer research.

Ligand Proton Pseudocontact Shifts Determined from Paramagnetic Relaxation Dispersion in the Limit of NMR Intermediate Exchange

Delineation of protein-ligand interaction modes is key for rational drug discovery. The availability of complex crystal structures is often limited by the aqueous solubility of the compounds, while lead-like compounds with micromolar affinities normally fall into the NMR intermediate exchange regime, in which severe line broadening to beyond the detection of interfacial resonances limits NMR applications. Here, we developed a new method to retrieve low-populated bound-state ¹H pseudocontact shifts (PCSs) using paramagnetic relaxation dispersion (RD). We evaluated using a ¹H PCS-RD approach in a BRM bromodomain lead-like inhibitor to filter molecular docking poses using multiple intermolecular structural restraints. Considering the universal presence of proton atoms in druglike compounds, our work will have wide application in structure-guided drug discovery even under an extreme condition of NMR intermediate exchange and low aqueous solubility of ligands.

Egress and invasion machinery of malaria: an in-depth look into the structural and functional features of the flap dynamics of plasmepsin IX and X

Plasmepsins, a family of aspartic proteases expressed by Plasmodium falciparum parasite, have been identified as key mediators in the onset of lethal malaria. Precedence has been placed on this family of enzymes due their essential role in the virulence of the parasite, thus highlighting their importance as novel drug targets. A previously published study by our group proposed a set of parameters used to define the flap motion of aspartic proteases. These parameters were used in the study of Plm I-V and focused on the flap flexibility as well as structural dynamics. Recent studies have highlighted the essential role played by Plm IX and X in egress and invasion of the malarial parasite. This study aims to close the gap on the latter family, investigating the flap dynamics of Plms IX and X. Molecular dynamics simulations demonstrated an "open and close" mechanism at the region of the catalytic site. Further computation of the dihedral angles at the catalytic region revealed tractability at both the flap tip and flexible loop. This structural versatility enhances the interaction of variant ligand sizes, in comparison to other Plm family members. The results obtained from this study signify the essential role of structural flap dynamics and its resultant effect on the binding landscapes of Plm IX and X. We believe that this unique structural mechanism may be integrated in the design and development of effective anti-malarial drugs.

Revealing the architecture of protein complexes by an orthogonal approach combining HDXMS, CXMS, and disulfide trapping

Many cellular functions necessitate structural assemblies of two or more associated proteins. The structural characterization of protein complexes using standard methods, such as X-ray crystallography, is challenging. Herein, we describe an orthogonal approach using hydrogen-deuterium-exchange mass spectrometry (HDXMS), cross-linking mass spectrometry (CXMS), and disulfide trapping to map interactions within protein complexes. HDXMS measures changes in solvent accessibility and hydrogen bonding upon complex formation; a decrease in HDX rate could account for newly formed intermolecular or intramolecular interactions. To distinguish between inter- and intramolecular interactions, we use a CXMS method to determine the position of direct interface regions by trapping intermolecular residues in close proximity to various cross-linkers (e.g., disuccinimidyl adipate (DSA)) of different lengths and reactive groups. Both MS-based experiments are performed on high-resolution mass spectrometers (e.g., an Orbitrap Elite hybrid mass spectrometer). The physiological relevance of the interactions identified through HDXMS and CXMS is investigated by transiently co-expressing cysteine mutant pairs, one mutant on each protein at the discovered interfaces, in an appropriate cell line, such as HEK293. Disulfide-trapped protein complexes are formed within cells spontaneously or are facilitated by addition of oxidation reagents such as H₂O₂ or diamide. Western blotting analysis, in the presence and absence of reducing reagents, is used to determine whether the disulfide bonds are formed in the proposed complex interface in physiologically relevant milieus. The procedure described here requires 1-2 months. We demonstrate this approach using the β2-adrenergic receptor-β-arrestin1 complex as the model system.

Combining X-Ray Crystallography with Small Angle X-Ray Scattering to Model Unstructured Regions of Nsa1 from S. Cerevisiae

Determination of the full-length structure of ribosome assembly factor Nsa1 from Saccharomyces cerevisiae (S. cerevisiae) is challenging because of the disordered and protease labile C-terminus of the protein. This manuscript describes the methods to purify recombinant Nsa1 from S. cerevisiae for structural analysis by both X-ray crystallography and SAXS. X-ray crystallography was utilized to solve the structure of the well-ordered N-terminal WD40 domain of Nsa1, and then SAXS was used to resolve the structure of the C-terminus of Nsa1 in solution. Solution scattering data was collected from full-length Nsa1 in solution. The theoretical scattering amplitudes were calculated from the high-resolution crystal structure of the WD40 domain, and then a combination of rigid body and ab initio modeling revealed the C-terminus of Nsa1. Through this hybrid approach the quaternary structure of the entire protein was reconstructed. The methods presented here should be generally applicable for the hybrid structural determination of other proteins composed of a mix of structured and unstructured domains.

Drugs and Targets in Fibrosis

Fibrosis contributes to the development of many diseases and many target molecules are involved in fibrosis. Currently, the majority of fibrosis treatment strategies are limited to specific diseases or organs. However, accumulating evidence demonstrates great similarities among fibroproliferative diseases, and more and more drugs are proved to be effective anti-fibrotic therapies across different diseases and organs. Here we comprehensively review the current knowledge on the pathological mechanisms of fibrosis, and divide factors mediating fibrosis progression into extracellular and intracellular groups. Furthermore, we systematically summarize both single and multiple component drugs that target fibrosis. Future directions of fibrosis drug discovery are also proposed.

PEM-fitter: A Coarse-Grained Method to Validate Protein Candidate Models

The volumetric images produced by Cryo-Electron Microscopy (cryo-EM) technique are used to model macromolecular assemblies and machines. De novo protein modeling uses these images to computationally model the structure of the molecules. Many candidate conformations are usually generated during the intermediate step. Conventionally, each of these candidates is evaluated by time-consuming approaches such as potential energy. We introduce an initial version of a geometrical screening method that uses the skeleton of the cryo-EM images to evaluate candidate structures. The aim of this method is to reduce the number of native-like candidate conformations and, therefore, reduce the time required for structural evaluation by energy calculations. A test of two datasets was performed. The first dataset contains 10 proteins and shows that our method can successfully detect the correct native structure for the given skeleton among a set of different protein structures. The second dataset contains 12 proteins and shows that our method can filter slightly modified decoy conformations of the same protein. The efficiency of the method is also reported.

A selective knockout method for discovery of minor active components from plant extracts: Feasibility and challenges as illustrated by an application to Salvia miltiorrhiza

Natural products have been recognized to play an invaluable role in drug discovery. However, efficient discovery of minor active constituents from natural sources is challenging due to the low abundance and complex matrices. In this study, we developed a selective knockout method to discover minor bioactive components from complex phytochemical mixtures, using a Chinese medicine as an example. Based on the chromatographic fingerprint, six major components in the ethyl acetate extract of the root of Salvia miltiorrhiza (EASM) were selectively knocked out via high-resolution peak fraction (HRPF) approach. The remaining extract was automatically enriched and fractionated to generate a chemical library consisting of 62 minor components with contents less than 3‰. Simultaneously, a parallel mass-spectrometry (MS) analysis was performed to ensure purity and to characterize the structure of the compound in each fraction. Via an antioxidant response element (ARE)-driven luciferase reporter system, 33 minor components were screened out as nuclear factor erythroid 2-related factor 2 (Nrf2) activators and 30 components were identified. Here, the Nrf2 activation activities of 21 components have been reported for the first time. Different from the existing methods for discovery of active compounds from natural products, in the developed method of this manuscript, the major components are selectively removed, and the fractions of the minor components are prepared after several times of preparative HPLC enrichment by high-resolution peak fraction approach. It improves the prospective discovery of minor active components from complex medicinal herbs.

The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening

Structure-based virtual screening (SBVS) has become an indispensable technique for hit identification at the early stage of drug discovery. However, the accuracy of current scoring functions is not high enough to confer success to every target and thus remains to be improved. Previously, we had developed binary pose filters (PFs) using knowledge derived from the protein-ligand interface of a single X-ray structure of a specific target. This novel approach had been validated as an effective way to improve ligand enrichment. Continuing from it, in the present work we attempted to incorporate knowledge collected from diverse protein-ligand interfaces of multiple crystal structures of the same target to build PF ensembles (PFEs). Toward this end, we first constructed a comprehensive data set to meet the requirements of ensemble modeling and validation. This set contains 10 diverse targets, 118 well-prepared X-ray structures of protein-ligand complexes, and large benchmarking actives/decoys sets. Notably, we designed a unique workflow of two-layer classifiers based on the concept of ensemble learning and applied it to the construction of PFEs for all of the targets. Through extensive benchmarking studies, we demonstrated that (1) coupling PFE with Chemgauss4 significantly improves the early enrichment of Chemgauss4 itself and (2) PFEs show greater consistency in boosting early enrichment and larger overall enrichment than our prior PFs. In addition, we analyzed the pairwise topological similarities among cognate ligands used to construct PFEs and found that it is the higher chemical diversity of the cognate ligands that leads to the improved performance of PFEs. Taken together, the results so far prove that the incorporation of knowledge from diverse protein-ligand interfaces by ensemble modeling is able to enhance the screening competence of SBVS scoring functions.

Production, Crystallization and Structure Determination of C. difficile PPEP-1 via Microseeding and Zinc-SAD

New therapies are needed to treat Clostridium difficile infections that are a major threat to human health. The C. difficile metalloprotease PPEP-1 is a target for future development of inhibitors to decrease the virulence of the pathogen. To perform biophysical and structural characterization as well as inhibitor screening, large amounts of pure and active protein will be needed. We have developed a protocol for efficient production and purification of PPEP-1 by the use of E. coli as the expression host yielding sufficient amounts and purity of protein for crystallization and structure determination. Additionally, using microseeding, highly intergrown crystals of PPEP-1 can be grown to well-ordered crystals suitable for X-ray diffraction analysis. The methods could also be used to produce other recombinant proteins and to study the structures of other proteins producing intergrown crystals.

The Intersection of Structural and Chemical Biology - An Essential Synergy

The continual improvement in our ability to generate high resolution structural models of biological molecules has stimulated and supported innovative chemical biology projects that target increasingly challenging ligand interaction sites. In this review we outline some of the recent developments in chemical biology and rational ligand design and show selected examples that illustrate the synergy between these research areas.