How to Distinguish Conformational Selection and Induced Fit Based on Chemical Relaxation Rates

Ligand-induced protein transition state stabilization switches the binding pathway from conformational selection to induced fit

Protein-ligand complex formation is fundamental to biological function. A central question is whether proteins spontaneously adopt binding-competent conformations to which ligands bind conformational selection (CS) or whether ligands induce the binding-competent conformation induced fit (IF). Here, we resolve the CS and IF binding pathways by characterizing protein conformational dynamics over a wide range of ligand concentrations using NMR relaxation dispersion. We determined the relative flux through the two pathways using a four-state binding model that includes both CS and IF. Experiments conducted without ligand show that galectin-3 exchanges between the ground-state conformation and a high-energy conformation similar to the ligand-bound conformation, demonstrating that CS is a plausible pathway. Near-identical crystal structures of the apo and ligand-bound states suggest that the high-energy conformation in solution corresponds to the apo crystal structure. Stepwise additions of the ligand lactose induce progressive changes in the relaxation dispersions that we fit collectively to the four-state model, yielding all microscopic rate constants and binding affinities. The ligand affinity is higher for the bound-like conformation than for the ground state, as expected for CS. Nonetheless, the IF pathway contributes greater than 70% of the total flux even at low ligand concentrations. The higher flux through the IF pathway is explained by considerably higher rates of exchange between the two protein conformations in the ligand-associated state. Thus, the ligand acts to decrease the activation barrier between protein conformations in a manner reciprocal to enzymatic transition-state stabilization of reactions involving ligand transformation.

A simple method to resolve rate constants when the binding mechanism obeys induced fit or conformational selection

Many interactions involving a ligand and its molecular target are studied by rapid kinetics using a stopped-flow apparatus. Information obtained from these studies is often limited to a single, saturable relaxation that is insufficient to resolve all independent rate constants even for a two-step mechanism of binding obeying induced fit (IF) or conformational selection (CS). We introduce a simple method of general applicability where this limitation is overcome. The method accurately reproduces the rate constants for ligand binding to the serine protease thrombin determined independently from the analysis of multiple relaxations. Application to the inactive zymogen precursor of thrombin, prethrombin-2, resolves all rate constants for a binding mechanism of IF or CS from a single, saturable relaxation. Comparison with thrombin shows that the prethrombin-2 to thrombin conversion enhances ligand binding to the active site not by improving accessibility through the value of kon but by reducing the rate of dissociation koff. The conclusion holds regardless of whether binding is interpreted in terms of IF or CS and has general relevance for the mechanism of zymogen activation of serine proteases. The method also provides a simple test of the validity of IF and CS and indicates when more complex mechanisms of binding should be considered.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Elucidating Dynamics of Adenylate Kinase from Enzyme Opening to Ligand Release

This study explores ligand-driven conformational changes in adenylate kinase (AK), which is known for its open-to-close conformational transitions upon ligand binding and release. By utilizing string free energy simulations, we determine the free energy profiles for both enzyme opening and ligand release and compare them with profiles from the apoenzyme. Results reveal a three-step ligand release process, which initiates with the opening of the adenosine triphosphate-binding subdomain (ATP lid), followed by ligand release and concomitant opening of the adenosine monophosphate-binding subdomain (AMP lid). The ligands then transition to nonspecific positions before complete dissociation. In these processes, the first step is energetically driven by ATP lid opening, whereas the second step is driven by ATP release. In contrast, the AMP lid opening and its ligand release make minor contributions to the total free energy for enzyme opening. Regarding the ligand binding mechanism, our results suggest that AMP lid closure occurs via an induced-fit mechanism triggered by AMP binding, whereas ATP lid closure follows conformational selection. This difference in the closure mechanisms provides an explanation with implications for the debate on ligand-driven conformational changes of AK. Additionally, we determine an X-ray structure of an AK variant that exhibits significant rearrangements in the stacking of catalytic arginines, explaining its reduced catalytic activity. In the context of apoenzyme opening, the sequence of events is different. Here, the AMP lid opens first while the ATP lid remains closed, and the free energy associated with ATP lid opening varies with orientation, aligning with the reported AK opening and closing rate heterogeneity. Finally, this study, in conjunction with our previous research, provides a comprehensive view of the intricate interplay between various structural elements, ligands, and catalytic residues that collectively contribute to the robust catalytic power of the enzyme.

Computer-Aided Drug Discovery and Design: Recent Advances and Future Prospects

Computer-aided drug discovery and design involve the use of information technologies to identify and develop, on a rational ground, chemical compounds that align a set of desired physicochemical and biological properties. In its most common form, it involves the identification and/or modification of an active scaffold (or the combination of known active scaffolds), although de novo drug design from scratch is also possible. Traditionally, the drug discovery and design processes have focused on the molecular determinants of the interactions between drug candidates and their known or intended pharmacological target(s). Nevertheless, in modern times, drug discovery and design are conceived as a particularly complex multiparameter optimization task, due to the complicated, often conflicting, property requirements.This chapter provides an updated overview of in silico approaches for identifying active scaffolds and guiding the subsequent optimization process. Recent groundbreaking advances in the field have also analyzed the integration of state-of-the-art machine learning approaches in every step of the drug discovery process (from prediction of target structure to customized molecular docking scoring functions), integration of multilevel omics data, and the use of a diversity of computational approaches to assist target validation and assess plausible binding pockets.

Unravelling the mechanism of neurotensin recognition by neurotensin receptor 1

The conformational ensembles of G protein-coupled receptors (GPCRs) include inactive and active states. Spectroscopy techniques, including NMR, show that agonists, antagonists and other ligands shift the ensemble toward specific states depending on the pharmacological efficacy of the ligand. How receptors recognize ligands and the kinetic mechanism underlying this population shift is poorly understood. Here, we investigate the kinetic mechanism of neurotensin recognition by neurotensin receptor 1 (NTS1) using 19F-NMR, hydrogen-deuterium exchange mass spectrometry and stopped-flow fluorescence spectroscopy. Our results indicate slow-exchanging conformational heterogeneity on the extracellular surface of ligand-bound NTS1. Numerical analysis of the kinetic data of neurotensin binding to NTS1 shows that ligand recognition follows an induced-fit mechanism, in which conformational changes occur after neurotensin binding. This approach is applicable to other GPCRs to provide insight into the kinetic regulation of ligand recognition by GPCRs.

Electrostatic complementarity at the interface drives transient protein-protein interactions

Understanding the mechanisms driving bio-molecules binding and determining the resulting complexes' stability is fundamental for the prediction of binding regions, which is the starting point for drug-ability and design. Characteristics like the preferentially hydrophobic composition of the binding interfaces, the role of van der Waals interactions, and the consequent shape complementarity between the interacting molecular surfaces are well established. However, no consensus has yet been reached on the role of electrostatic. Here, we perform extensive analyses on a large dataset of protein complexes for which both experimental binding affinity and pH data were available. Probing the amino acid composition, the disposition of the charges, and the electrostatic potential they generated on the protein molecular surfaces, we found that (i) although different classes of dimers do not present marked differences in the amino acid composition and charges disposition in the binding region, (ii) homodimers with identical binding region show higher electrostatic compatibility with respect to both homodimers with non-identical binding region and heterodimers. Interestingly, (iii) shape and electrostatic complementarity, for patches defined on short-range interactions, behave oppositely when one stratifies the complexes by their binding affinity: complexes with higher binding affinity present high values of shape complementarity (the role of the Lennard-Jones potential predominates) while electrostatic tends to be randomly distributed. Conversely, complexes with low values of binding affinity exploit Coulombic complementarity to acquire specificity, suggesting that electrostatic complementarity may play a greater role in transient (or less stable) complexes. In light of these results, (iv) we provide a novel, fast, and efficient method, based on the 2D Zernike polynomial formalism, to measure electrostatic complementarity without the need of knowing the complex structure. Expanding the electrostatic potential on a basis of 2D orthogonal polynomials, we can discriminate between transient and permanent protein complexes with an AUC of the ROC of [Formula: see text] 0.8. Ultimately, our work helps shedding light on the non-trivial relationship between the hydrophobic and electrostatic contributions in the binding interfaces, thus favoring the development of new predictive methods for binding affinity characterization.

Hexahexyloxycalix[6]arene, a Conformationally Adaptive Host for the Complexation of Linear and Branched Alkylammonium Guests

Hexahexyloxycalix[6]arene 2b leads to the endo-cavity complexation of linear and branched alkylammonium guests showing a conformational adaptive behavior in CDCl₃ solution. Linear n-pentylammonium guest 6a⁺ induces the cone conformation of 2b at the expense of the 1,2,3-alternate, which is the most abundant conformer of 2b in the absence of a guest. In a different way, branched alkylammonium guests, such as tert-butylammonium 6b⁺ and isopropylammonium 6c⁺, select the 1,2,3-alternate as the favored 2b conformation (6b⁺/6c⁺⊂2b^1,2,3-alt), but other complexes in which 2b adopts different conformations, namely, 6b⁺/6c⁺⊂2b^cone, 6b⁺/6c⁺⊂2b^paco, and 6b⁺/6c⁺⊂2b^1,2-alt, have also been revealed. Binding constant values determined via NMR experiments indicated that the 1,2,3-alternate was the best-fitting 2b conformation for the complexation of branched alkylammonium guests, followed by cone > paco > 1,2-alt. Our NCI and NBO calculations suggest that the H-bonding interactions (⁺N-H···O) between the ammonium group of the guest and the oxygen atoms of calixarene 2b are the main determinants of the stability order of the four complexes. These interactions are weakened by increasing the guest steric encumbrance, thus leading to a lower binding affinity. Two stabilizing H-bonds are possible with the 1,2,3-alt- and cone-2b conformations, whereas only one H-bond is possible with the other paco- and 1,2-alt-2b stereoisomers.

Distinct activation mechanisms regulate subtype selectivity of Cannabinoid receptors

Design of cannabinergic subtype selective ligands is challenging because of high sequence and structural similarities of cannabinoid receptors (CB₁ and CB₂). We hypothesize that the subtype selectivity of designed selective ligands can be explained by the ligand binding to the conformationally distinct states between cannabinoid receptors. Analysis of ~ 700 μs of unbiased simulations using Markov state models and VAMPnets identifies the similarities and distinctions between the activation mechanism of both receptors. Structural and dynamic comparisons of metastable intermediate states allow us to observe the distinction in the binding pocket volume change during CB₁ and CB₂ activation. Docking analysis reveals that only a few of the intermediate metastable states of CB₁ show high affinity towards CB₂ selective agonists. In contrast, all the CB₂ metastable states show a similar affinity for these agonists. These results mechanistically explain the subtype selectivity of these agonists by deciphering the activation mechanism of cannabinoid receptors.

Biological Calorimetry: Old Friend, New Insights

Calorimetry is an old experimental technique (first instrument developed in S. XVIII), but it is broadly used and still provides key information for understanding biological processes at the molecular level, particularly, cooperative phenomena in protein interactions. Here, we review and highlight some key aspects of biological calorimetry. Several biological systems will be described in which calorimetry was instrumental for modeling the behavior of the protein and obtaining further biological insight.

The binding model of adenosine-specific DNA aptamer: Umbrella sampling study

We report a novel model of the selective binding mechanism of adenosine-specific DNA aptamer. Our theoretical investigations of AMP (Adenosine monophosphate) dissociation from aptamer-AMP complexes reveals new details of aptamer molecular specificity and stabilisation factors. Umbrella sampling MD calculations using parmbsc1 force field shows that the disordered structure of the internal loop of the unbound aptamer hairpin has a characteristic packing of guanines, which prevents barrier-free penetration of ligands into the site cavity. Also, this disordered structure of the unbound aptamer has a network of hydrogen bonds stabilising the cavity near the target guanines within the binding sites during the whole binding process. We suggested that the first AMP molecule binds to the disordered structure of the site closest to the aptamer hairpin stem and spends some free energy on ordering of the internal loop. Then the second AMP molecule binds to the ordered site closest to the aptamer hairpin loop with a lower energy gain. As a result, the induced-fit binding model is the most applicable for this aptamer and does not contradict the modern experimental NMR and calorimetry data.

Multiplexed rapid antigen tests developed using multicolored nanoparticles and cross-reactive antibody pairs: Implications for pandemic preparedness

Global public health infrastructure is unprepared for emerging pathogen epidemics, in part because diagnostic tests are not developed in advance. The recent Zika, Ebola, and SARS-CoV-2 virus epidemics are cases in point. We demonstrate here that multicolored gold nanoparticles, when coupled to cross-reactive monoclonal antibody pairs generated from a single immunization regimen, can be used to create multiple diagnostics that specifically detect and distinguish related viruses. The multiplex approach for specific detection centers on immunochromatography with pairs of antibody-conjugated red and blue gold nanoparticles, coupled with clustering algorithms to detect and distinguish related pathogens. Cross-reactive antibodies were used to develop rapid tests for i) Dengue virus serotypes 1-4, ii) Zika virus, iii) Ebola and Marburg viruses, and iv) SARS-CoV and SARS-CoV-2 viruses. Multiplexed rapid antigen tests based on multicolored nanoparticles and cross-reactive antibodies and can be developed prospectively at low cost to improve preparedness for epidemic outbreaks.

In Search of a Dynamical Vocabulary: A Pipeline to Construct a Basis of Shared Traits in Large-Scale Motions of Proteins

The paradigmatic sequence–structure–dynamics–function relation in proteins is currently well established in the scientific community; in particular, a large effort has been made to probe the first connection, indeed providing convincing evidence of its strength and rationalizing it in a quantitative and general framework. In contrast, however, the role of dynamics as a link between structure and function has eluded a similarly clear-cut verification and description. In this work, we propose a pipeline aimed at building a basis for the quantitative characterization of the large-scale dynamics of a set of proteins, starting from the sole knowledge of their native structures. The method hinges on a dynamics-based clusterization, which allows a straightforward comparison with structural and functional protein classifications. The resulting basis set, obtained through the application to a group of related proteins, is shown to reproduce the salient large-scale dynamical features of the dataset. Most interestingly, the basis set is shown to encode the fluctuation patterns of homologous proteins not belonging to the initial dataset, thus highlighting the general applicability of the pipeline used to build it.

A litmus test for classifying recognition mechanisms of transiently binding proteins

Partner recognition in protein binding is critical for all biological functions, and yet, delineating its mechanism is challenging, especially when recognition happens within microseconds. We present a theoretical and experimental framework based on straight-forward nuclear magnetic resonance relaxation dispersion measurements to investigate protein binding mechanisms on sub-millisecond timescales, which are beyond the reach of standard rapid-mixing experiments. This framework predicts that conformational selection prevails on ubiquitin’s paradigmatic interaction with an SH3 (Src-homology 3) domain. By contrast, the SH3 domain recognizes ubiquitin in a two-state binding process. Subsequent molecular dynamics simulations and Markov state modeling reveal that the ubiquitin conformation selected for binding exhibits a characteristically extended C-terminus. Our framework is robust and expandable for implementation in other binding scenarios with the potential to show that conformational selection might be the design principle of the hubs in protein interaction networks.

The authors provide a litmus test for the recognition mechanism of transiently binding proteins based on nuclear magnetic resonance and find a conformational selection binding mechanism through concentration-dependent kinetics of ubiquitin and SH3.

Unravelling the binding mode of a methamphetamine aptamer: a spectroscopic and calorimetric investigation

Nucleic acid aptamers are bio-molecular recognition agents that bind to their targets with high specificity and affinity, and hold promise in a range of biosensor and therapeutic applications. In the case of small molecule targets, their small size and limited number of functional groups constitute challenges for their detection by aptamer-based biosensors because bio-recognition events may both be weak and produce poorly transduced signals. The binding affinity is principally used to characterize aptamer-ligand interactions; however a structural understanding of bio-recognition is arguably more valuable in order to design a strong response in biosensor applications. Using a combination of nuclear magnetic resonance, circular dichroism, and isothermal titration calorimetry, we propose a binding model for a new methamphetamine aptamer and determine the main interactions driving complex formation. These measurements reveal only modest structural changes to the aptamer upon binding and are consistent with a conformational selection binding model. The aptamer-methamphetamine complex formation was observed to be entropically driven, apparently involving hydrophobic and electrostatic interactions. Taken together, our results exemplify a means of elucidating small molecule-aptamer binding interactions, which may be decisive in the development of aptasensors and therapeutics, and may contribute to a deeper understanding of interactions driving aptamer selection.

Factors That Contribute to hIAPP Amyloidosis in Type 2 Diabetes Mellitus

Cases of Type 2 Diabetes Mellitus (T2DM) are increasing at an alarming rate due to the rise in obesity, sedentary lifestyles, glucose-rich diets and other factors. Numerous studies have increasingly illustrated the pivotal role that human islet amyloid polypeptide (hIAPP) plays in the pathology of T2DM through damage and subsequent loss of pancreatic β-cell mass. HIAPP can misfold and form amyloid fibrils which are preceded by pre-fibrillar oligomers and monomers, all of which have been linked, to a certain extent, to β-cell cytotoxicity through a range of proposed mechanisms. This review provides an up-to-date summary of recent progress in the field, highlighting factors that contribute to hIAPP misfolding and aggregation such as hIAPP protein concentration, cell stress, molecular chaperones, the immune system response and cross-seeding with other amyloidogenic proteins. Understanding the structure of hIAPP and how these factors affect amyloid formation will help us better understand how hIAPP misfolds and aggregates and, importantly, help identify potential therapeutic targets for inhibiting amyloidosis so alternate and more effective treatments for T2DM can be developed.

Assembly of π-Stacking Helical Peptides into a Porous and Multivariable Proteomimetic Framework

The evolution of proteins from simpler, self-assembled peptides provides a powerful blueprint for the design of complex synthetic materials. Previously, peptide-metal frameworks using short sequences (≤3 residues) have shown great promise as proteomimetic materials that exhibit sophisticated capabilities. However, their development has been hindered due to few variable residues and restricted choice of side-chains that are compatible with metal ions. Herein, we developed a noncovalent strategy featuring π-stacking bipyridyl residues to assemble much longer peptides into crystalline frameworks that tolerate even previously incompatible acidic and basic functionalities and allow an unprecedented level of pore variations. Single-crystal X-ray structures are provided for all variants to guide and validate rational design. These materials exhibit hallmark proteomimetic behaviors such as guest-selective induced fit and assembly of multimetallic units. Significantly, we demonstrate facile optimization of the framework design to substantially increase affinity toward a complex organic molecule.

CDH1 Germline Variants in a Tunisian Cohort with Hereditary Diffuse Gastric Carcinoma

Mutational screening of the CDH1 gene is a standard treatment for patients who fulfill Hereditary Diffuse Gastric Cancer (HDGC) testing criteria. In this framework, the classification of variants found in this gene is a crucial step for the clinical management of patients at high risk for HDGC. The aim of our study was to identify CDH1 as well as CTNNA1 mutational profiles predisposing to HDGC in Tunisia. Thirty-four cases were included for this purpose. We performed Sanger sequencing for the entire coding region of both genes and MLPA (Multiplex Ligation Probe Amplification) assays to investigate large rearrangements of the CDH1 gene. As a result, three cases, all with the HDGC inclusion criteria (8.82% of the entire cohort), carried pathogenic and likely pathogenic variants of the CDH1 gene. These variants involve a novel splicing alteration, a missense c.2281G > A detected by Sanger sequencing, and a large rearrangement detected by MLPA. No pathogenic CTNNA1 variants were found. The large rearrangement is clearly pathogenic, implicating a large deletion of two exons. The novel splicing variant creates a cryptic site. The missense variant is a VUS (Variant with Uncertain Significance). With ACMG (American College of Medical Genetics and Genomics) classification and the evidence available, we thus suggest a revision of its status to likely pathogenic. Further functional studies or cosegregation analysis should be performed to confirm its pathogenicity. In addition, molecular exploration will be needed to understand the etiology of the other CDH1- and CTNNA1-negative cases fulfilling the HDGC inclusion criteria.

A Computational Approach to Investigate TDP-43 RNA-Recognition Motif 2 C-Terminal Fragments Aggregation in Amyotrophic Lateral Sclerosis

Many of the molecular mechanisms underlying the pathological aggregation of proteins observed in neurodegenerative diseases are still not fully understood. Among the aggregate-associated diseases, Amyotrophic Lateral Sclerosis (ALS) is of relevant importance. In fact, although understanding the processes that cause the disease is still an open challenge, its relationship with protein aggregation is widely known. In particular, human TDP-43, an RNA/DNA binding protein, is a major component of the pathological cytoplasmic inclusions observed in ALS patients. Indeed, the deposition of the phosphorylated full-length TDP-43 in spinal cord cells has been widely studied. Moreover, it has also been shown that the brain cortex presents an accumulation of phosphorylated C-terminal fragments (CTFs). Even if it is debated whether the aggregation of CTFs represents a primary cause of ALS, it is a hallmark of TDP-43 related neurodegeneration in the brain. Here, we investigate the CTFs aggregation process, providing a computational model of interaction based on the evaluation of shape complementarity at the molecular interfaces. To this end, extensive Molecular Dynamics (MD) simulations were conducted for different types of protein fragments, with the aim of exploring the equilibrium conformations. Adopting a newly developed approach based on Zernike polynomials, able to find complementary regions in the molecular surface, we sampled a large set of solvent-exposed portions of CTFs structures as obtained from MD simulations. Our analysis proposes and assesses a set of possible association mechanisms between the CTFs, which could drive the aggregation process of the CTFs. To further evaluate the structural details of such associations, we perform molecular docking and additional MD simulations to propose possible complexes and assess their stability, focusing on complexes whose interacting regions are both characterized by a high shape complementarity and involve β3 and β5 strands at their interfaces.

Analytical and functional aspects of protein-ligand interactions: Beyond induced fit and conformational selection

Ligand-dependent changes in protein conformation are foundational to biology. Historical mechanistic models for substrate-specific proteins are induced fit (IF) and conformational selection (CS), which invoke a change in protein conformation after ligand binds or before ligand binds, respectively. These mechanisms have important, but rarely discussed, functional relevance because IF vs. CS can differentially affect a protein's substrate specificity or promiscuity, and its regulatory properties. The modern view of proteins as conformational ensembles in both ligand free and bound states, together with the realization that most proteins exhibit some substrate promiscuity, demands a deeper interpretation of the historical models and provides an opportunity to improve mechanistic analyses. Here we describe alternative analytical strategies for distinguishing the historical models, including the more complex expanded versions of IF and CS. Functional implications of the different models are described. We provide an alternative perspective based on protein ensembles interacting with ligand ensembles that clarifies how a single protein can 'apparently' exploit different mechanisms for different ligands. Mechanistic information about protein ensembles can be optimized when they are probed with multiple ligands.

Induced fit versus conformational selection: From rate constants to fluxes… and back to rate constants

Induced fit- (IF) and conformational selection (CS) binding mechanisms have long been regarded to be mutually exclusive. Yet, they are now increasingly considered to produce the final ligand-target complex alongside within a thermodynamic cycle. This viewpoint benefited from the introduction of binding fluxes as a tool for analyzing the overall behavior of such cycle. This study aims to provide more vivid and applicable insights into this emerging field. In this respect, combining differential equation- based simulations and hitherto little explored alternative modes of calculation provide concordant information about the intricate workings of such cycle. In line with previous reports, we observe that the relative contribution of IF increases with the ligand concentration at equilibrium. Yet the baseline contribution may vary from one case to another and simulations as well as calculations show that this parameter is essentially regulated by the dissociation rate of both pathways. Closer attention should be paid to how the contributions of IF and CS compare at physiologically relevant drug/ligand concentrations. To this end, a simple equation discloses how changing a limited set of "microscopic" rate constants can extend the concentration range at which CS contributes most effectively. Finally, it could also be beneficial to extend the utilization of flux- based approaches to more physiologically relevant time scales and alternative binding models.

Improved epitope resolution of the prefusion trimer-specific antibody AM14 bound to the RSV F glycoprotein

Respiratory syncytial virus (RSV) is the most common cause of acute lower respiratory tract infections resulting in medical intervention and hospitalizations during infancy and early childhood, and vaccination against RSV remains a public health priority. The RSV F glycoprotein is a major target of neutralizing antibodies, and the prefusion stabilized form of F (DS-Cav1) is under investigation as a vaccine antigen. AM14 is a human monoclonal antibody with the exclusive capacity of binding an epitope on prefusion F (PreF), which spans two F protomers. The quality of recognizing a trimer-specific epitope makes AM14 valuable for probing PreF-based immunogen conformation and functionality during vaccine production. Currently, only a low-resolution (5.5 Å) X-ray structure is available of the PreF-AM14 complex, revealing few reliable details of the interface. Here, we perform complementary structural studies using X-ray crystallography and cryo-electron microscopy (cryo-EM) to provide improved resolution structures at 3.6 Å and 3.4 Å resolutions, respectively. Both X-ray and cryo-EM structures provide clear side-chain densities, which allow for accurate mapping of the AM14 epitope on DS-Cav1. The structures help rationalize the molecular basis for AM14 loss of binding to RSV F monoclonal antibody-resistant mutants and reveal flexibility for the side chain of a key antigenic residue on PreF. This work provides the basis for a comprehensive understanding of RSV F trimer specificity with implications in vaccine design and quality assessment of PreF-based immunogens.

Determination of sitagliptin in human plasma using a smart electrochemical sensor based on electroactive molecularly imprinted nanoparticles

Sitagliptin is a hypoglycaemic agent used to reduce blood sugar levels in patients with type 2 diabetes mellitus (T2DM). Real time monitoring of sitagliptin levels is crucial to prevent overdose, which might cause liver, kidney and pancreatic diseases. As an alternative solution, a sitagliptin voltammetric sensor was fabricated using artificial receptors called electroactive molecularly imprinted polymer nanoparticles (nanoMIPs). The nanoMIP tagged with a redox probe (ferrocene) combines both the recognition and reporting functions. Traditional electrochemical sensors determine the redox activity of an analyte. Thus, they are influenced by interfering molecules and the nature of the sample. These innovative nanoMIPs allow us to easily design and customise sensors, increase their sensitivity and minimise the cross reactivity in biological samples. The present technology replaces the traditional enzyme-mediator pairs used in traditional biosensors. The polymer composition was optimized "in silico" using docking and screening methods. Nanoparticles were synthesized via free radical polymerization and a solid phase method and then characterized by infrared spectroscopy (FTIR), transmission electron microscopy (TEM) and dynamic light scattering (DLS). The specific sitagliptin nanoparticles were covalently immobilized on platinum electrodes via silane and carbodiimide chemistry. The determination of sitagliptin in human plasma by a nanoMIP sensor was assessed by differential pulse voltammetry (DPV). The sensor current response was directly related to the change in nanoMIP conformation triggered by the analyte. The optimisation of the sensor response was made by adjusting (i) the silane concentration, (ii) nanoMIP concentration, and (iii) immobilization time. The sensor measurements in plasma revealed high selectivity and a sensitivity of 32.5 ± 0.6 nA pM^-1 towards sitagliptin, and the limit of detection of the fabricated sensor was found to be 0.06 pM. The sensor displayed a satisfactory performance for the determination of sitagliptin in spiked human plasma, demonstrating the potential of this technology for drug monitoring and clinical diagnosis.

Kinetic Constraints in the Specific Interaction between Phosphorylated Ubiquitin and Proteasomal Shuttle Factors

Ubiquitin (Ub) specifically interacts with the Ub-associating domain (UBA) in a proteasomal shuttle factor, while the latter is involved in either proteasomal targeting or self-assembly coacervation. PINK1 phosphorylates Ub at S65 and makes Ub alternate between C-terminally relaxed (pUb_RL) and retracted conformations (pUb_RT). Using NMR spectroscopy, we show that pUb_RL but not pUb_RT preferentially interacts with the UBA from two proteasomal shuttle factors Ubqln2 and Rad23A. Yet discriminatorily, Ubqln2-UBA binds to pUb more tightly than Rad23A does and selectively enriches pUb_RL upon complex formation. Further, we determine the solution structure of the complex between Ubqln2-UBA and pUb_RL and uncover the thermodynamic basis for the stronger interaction. NMR kinetics analysis at different timescales further suggests an indued-fit binding mechanism for pUb-UBA interaction. Notably, at a relatively low saturation level, the dissociation rate of the UBA-pUb_RL complex is comparable with the exchange rate between pUb_RL and pUb_RT. Thus, a kinetic constraint would dictate the interaction between Ub and UBA, thus fine-tuning the functional state of the proteasomal shuttle factors.

Understanding the Binding Transition State After the Conformational Selection Step: The Second Half of the Molecular Recognition Process Between NS1 of the 1918 Influenza Virus and Host p85β

Biomolecular recognition often involves conformational changes as a prerequisite for binding (i.e., conformational selection) or concurrently with binding (i.e., induced-fit). Recent advances in structural and kinetic approaches have enabled the detailed characterization of protein motions at atomic resolution. However, to fully understand the role of the conformational dynamics in molecular recognition, studies on the binding transition state are needed. Here, we investigate the binding transition state between nonstructural protein 1 (NS1) of the pandemic 1918 influenza A virus and the human p85β subunit of PI3K. 1918 NS1 binds to p85β via conformational selection. We present the free-energy mapping of the transition and bound states of the 1918 NS1:p85β interaction using linear free energy relationship and ϕ-value analyses. We find that the binding transition state of 1918 NS1 and p85β is structurally similar to the bound state with well-defined binding orientation and hydrophobic interactions. Our finding provides a detailed view of how protein motion contributes to the development of intermolecular interactions along the binding reaction coordinate.

Conformational Dynamics of the Dengue Virus Protease Revealed by Fluorescence Correlation and Single-Molecule FRET Studies

The dengue virus protease (DENV-PR) represents an attractive target for counteracting DENV infections. It is generally assumed that DENV-PR can exist in an open and a closed conformation and that active site directed ligands stabilize the closed state. While crystal structures of both the open and the closed conformation were successfully resolved, information about the prevalence of these conformations in solution remains elusive. Herein, we address the question of whether there is an equilibrium between different conformations in solution which can be influenced by addition of a competitive inhibitor. To this end, DENV-PR was statistically labeled by two dye molecules constituting a FRET (fluorescence resonance energy transfer) couple. Fluorescence correlation spectroscopy and photon-burst detection were employed to examine FRET pair labeled DENV-PRs freely diffusing in solution. The measurements were performed with two double mutants and with two dye couples. The data provide strong evidence that an equilibrium of at least two conformations of DENV-PR exists in solution. The competitive inhibitor stabilizes the closed state. Because the open and closed conformations appear to coexist in solution, our results support the picture of a conformational selection rather than that of an induced fit mechanism with respect to the inhibitor-induced formation of the closed state.

Structural Basis of Selective Human Indoleamine-2,3-dioxygenase 1 (hIDO1) Inhibition

hIDO1 is a heme-dioxygenase overexpressed in the tumor microenvironment and is implicated in the survival of cancer cells. Metabolism of tryptophan to N-formyl-kynurenine by hIDO1 leads to immune suppression to result in cancer cell immune escape. In this article, we discuss the discovery of selective hIDO1 inhibitors for therapeutic intervention that have been promoted to clinical trials and for which crystallographic structural information is available for the respective inhibitor-enzyme complex. The structural insights are based on the complex crystal structures and the relative biological data profiles. The structural basis of selective hIDO1 inhibition, as discussed herein, opens new avenues to the discovery of novel inhibitors with improved activity profiles, selectivity, and distinct structure frameworks.

Viewing SARS-CoV-2 Nucleocapsid Protein in Terms of Molecular Flexibility

The latest coronavirus SARS-CoV-2, which causes coronavirus disease 2019 (COVID-19) pneumonia leading to the pandemic, contains 29 proteins. Among them, nucleocapsid protein (NCoV2) is one of the abundant proteins and shows multiple functions including packaging the RNA genome during the infection cycle. It has also emerged as a potential drug target. In this review, the current status of the research of NCoV2 is described in terms of molecular structure and dynamics. NCoV2 consists of two domains, i.e., the N-terminal domain (NTD) and the C-terminal domain (CTD) with a disordered region between them. Recent simulation studies have identified several potential drugs that can bind to NTD or CTD with high affinity. Moreover, it was shown that the degree of flexibility in the disordered region has a large effect on drug binding rate, suggesting the importance of molecular flexibility for the NCoV2 function. Molecular flexibility has also been shown to be integral to the formation of droplets, where NCoV2, RNA and/or other viral proteins gather through liquid-liquid phase separation and considered important for viral replication. Finally, as one of the future research directions, a strategy for obtaining the structural and dynamical information on the proteins contained in droplets is presented.

Intrinsic Dynamics of Protein-Peptide Unbinding

The dynamics of peptide-protein binding and unbinding of a variant of the RNase S system has been investigated. To initiate the process, a photoswitchable azobenzene moiety has been covalently linked to the S-peptide, thereby switching its binding affinity to the S-protein. Transient fluorescence quenching was measured with the help of a time-resolved fluorometer, which has been specifically designed for these experiments and is based on inexpensive light-emitting diodes and laser diodes only. One mutant shows on-off behavior with no specific binding detectable in one of the states of the photoswitch. Unbinding is faster by at least 2 orders of magnitude, compared to that of other variants of the RNase S system. We conclude that unbinding is essentially barrier-less in that case, revealing the intrinsic dynamics of the unbinding event, which occurs on a time scale of a few hundred microseconds in a strongly stretched-exponential manner.

What defines a synthetic riboswitch? - Conformational dynamics of ciprofloxacin aptamers with similar binding affinities but varying regulatory potentials

Among the many in vitro-selected aptamers derived from SELEX protocols, only a small fraction has the potential to be applied for synthetic riboswitch engineering. Here, we present a comparative study of the binding properties of three different aptamers that bind to ciprofloxacin with similar K_D values, yet only two of them can be applied as riboswitches. We used the inherent ligand fluorescence that is quenched upon binding as the reporter signal in fluorescence titration and in time-resolved stopped-flow experiments. Thus, we were able to demonstrate differences in the binding kinetics of regulating and non-regulating aptamers. All aptamers studied underwent a two-step binding mechanism that suggests an initial association step followed by a reorganization of the aptamer to accommodate the ligand. We show that increasing regulatory potential is correlated with a decreasing back-reaction rate of the second binding step, thus resulting in a virtually irreversible last binding step of regulating aptamers. We suggest that a highly favoured structural adaption of the RNA to the ligand during the final binding step is essential for turning an aptamer into a riboswitch. In addition, our results provide an explanation for the fact that so few aptamers with regulating capacity have been found to date. Based on our data, we propose an adjustment of the selection protocol for efficient riboswitch detection.

Into the Fray! A Beginner's Guide to Medicinal Chemistry

Modern medicinal chemistry is a complex, multidimensional discipline that operates at the interface of the chemical and biological sciences. The medicinal chemistry contribution to drug discovery is typically described in the context of the well-recited linear progression of the drug discovery pipeline. However, compound optimization is idiosyncratic to each project, and clear definitions of hit and lead molecules and the subsequent progress along the pipeline becomes easily blurred. In addition, this description lacks insight into the entangled relationship between chemical and pharmacological properties, and thus provides limited guidance on how innovative medicinal chemistry strategies can be applied to solve optimization problems, regardless of the stage in the pipeline. Through discussion and illustrative examples, this article seeks to provide insights into the finesse of medicinal chemistry and the subtlety of balancing chemical properties pharmacology. In so doing, it aims to serve as an accessible and simple-to-digest guide for anyone who wishes to learn about the underlying principles of medicinal chemistry, in a context that has been decoupled from the pipeline description.

The Perturbed Free-Energy Landscape: Linking Ligand Binding to Biomolecular Folding

The effects of ligand binding on biomolecular conformation are crucial in drug design, enzyme mechanisms, the regulation of gene expression, and other biological processes. Descriptive models such as "lock and key", "induced fit", and "conformation selection" are common ways to interpret such interactions. Another historical model, linked equilibria, proposes that the free-energy landscape (FEL) is perturbed by the addition of ligand binding energy for the bound population of biomolecules. This principle leads to a unified, quantitative theory of ligand-induced conformation change, building upon the FEL concept. We call the map of binding free energy over biomolecular conformational space the "binding affinity landscape" (BAL). The perturbed FEL predicts/explains ligand-induced conformational changes conforming to all common descriptive models. We review recent experimental and computational studies that exemplify the perturbed FEL, with emphasis on RNA. This way of understanding ligand-induced conformation dynamics motivates new experimental and theoretical approaches to ligand design, structural biology and systems biology.

TriTOX: A novel Trichomonas vaginalis assay platform for high-throughput screening of compound libraries

Trichomonas vaginalis is a neglected urogenital parasitic protist that causes 170 million cases of trichomoniasis annually, making it the most prevalent non-viral, sexually transmitted disease. Trichomoniasis treatment relies on nitroheterocyclics, such as metronidazole. However, with increasing drug-resistance, there is an urgent need for novel anti-trichomonals. Little progress has been made to translate anti-trichomonal research into commercialised therapeutics, and the absence of a standardised compound-screening platform is the immediate stumbling block for drug-discovery. Herein, we describe a simple, cost-effective growth assay for T. vaginalis and the related Tritrichomonas foetus. Tracking changes in pH were a valid indicator of trichomonad growth (T. vaginalis and T. foetus), allowing development of a miniaturised, chromogenic growth assay based on the phenol red indicator in 96- and 384-well microtiter plate formats. The outputs of this assay can be quantitatively and qualitatively assessed, with consistent dynamic ranges based on Z' values of 0.741 and 0.870 across medium- and high-throughput formats, respectively. We applied this high-throughput format within the largest pure-compound microbial metabolite screen (812 compounds) for T. vaginalis and identified 43 hit compounds. We compared these identified compounds to mammalian cell lines, and highlighted extensive overlaps between anti-trichomonal and anti-tumour activity. Lastly, observing nanomolar inhibition of T. vaginalis by fumagillin, and noting this compound has reported activity in other protists, we performed in silico analyses of the interaction of fumagillin with its molecular target methionine aminopeptidase 2 for T. vaginalis, Giardia lamblia and Entamoeba histolytica, highlighting potential for fumagillin as a broad-spectrum anti-protistal against microaerophilic protists. Together, this new platform will accelerate drug-discovery efforts, underpin drug-resistance screening in trichomonads, and contributing to a growing body of evidence highlighting the potential of microbial natural products as novel anti-protistals.

Bringing the Ca2+ sensitivity of myristoylated recoverin into the physiological range

The prototypical Ca²⁺-sensor protein recoverin (Rec) is thought to regulate the activity of rhodopsin kinase (GRK1) in photoreceptors by switching from a relaxed (R) disc membrane-bound conformation in the dark to a more compact, cytosol-diffusing tense (T) conformation upon cell illumination. However, the apparent affinity for Ca²⁺ of its physiologically relevant form (myristoylated recoverin) is almost two orders of magnitude too low to support this mechanism in vivo. In this work, we compared the individual and synergistic roles of the myristic moiety, the GRK1 target and the disc membrane in modulating the calcium sensitivity of Rec. We show that the sole presence of the target or the disc membrane alone are not sufficient to achieve a physiological response to changes in intracellular [Ca²⁺]. Instead, the simultaneous presence of GRK1 and membrane allows the T to R transition to occur in a physiological range of [Ca²⁺] with high cooperativity via a conformational selection mechanism that drives the structural transitions of Rec in the presence of multiple ligands. Our conclusions may apply to other sensory transduction systems involving protein complexes and biological membranes.

Markov State Models to Elucidate Ligand Binding Mechanism

Molecular dynamics simulations can now routinely access the microsecond timescale, making feasible direct sampling of ligand association events. While Markov State Model (MSM) approaches offer a useful framework for analyzing such trajectory data to gain insight into binding mechanisms, accurate modeling of ligand association pathways and kinetics must be done carefully. We describe methods and good practices for constructing MSMs of ligand binding from unbiased trajectory data and discuss how to use time-lagged independent component analysis (tICA) to build informative models, using as an example recent simulation work to model the binding of phenylalanine to the regulatory ACT domain dimer of phenylalanine hydroxylase. We describe a variety of methods for estimating association rates from MSMs and discuss how to distinguish between conformational selection and induced-fit mechanisms using MSMs. In addition, we review some examples of MSMs constructed to elucidate the mechanisms by which p53 transactivation domain (TAD) and related peptides bind the oncoprotein MDM2.

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

Mechanisms of ligand binding

Many processes in chemistry and biology involve interactions of a ligand with its molecular target. Interest in the mechanism governing such interactions has dominated theoretical and experimental analysis for over a century. The interpretation of molecular recognition has evolved from a simple rigid body association of the ligand with its target to appreciation of the key role played by conformational transitions. Two conceptually distinct descriptions have had a profound impact on our understanding of mechanisms of ligand binding. The first description, referred to as induced fit, assumes that conformational changes follow the initial binding step to optimize the complex between the ligand and its target. The second description, referred to as conformational selection, assumes that the free target exists in multiple conformations in equilibrium and that the ligand selects the optimal one for binding. Both descriptions can be merged into more complex reaction schemes that better describe the functional repertoire of macromolecular systems. This review deals with basic mechanisms of ligand binding, with special emphasis on induced fit, conformational selection, and their mathematical foundations to provide rigorous context for the analysis and interpretation of experimental data. We show that conformational selection is a surprisingly versatile mechanism that includes induced fit as a mathematical special case and even captures kinetic properties of more complex reaction schemes. These features make conformational selection a dominant mechanism of molecular recognition in biology, consistent with the rich conformational landscape accessible to biological macromolecules being unraveled by structural biology.

A Global Minimization Toolkit for Batch-Fitting and χ2 Cluster Analysis of CW-EPR Spectra

Electron paramagnetic resonance spectroscopy (EPR) is a uniquely powerful technique for characterizing conformational dynamics at specific sites within a broad range of molecular species in water. Computational tools for fitting EPR spectra have enabled dynamics parameters to be determined quantitatively. These tools have dramatically broadened the capabilities of EPR dynamics analysis, however, their implementation can easily lead to overfitting or problems with self-consistency. As a result, dynamics parameters and associated properties become difficult to reliably determine, particularly in the slow-motion regime. Here, we present an EPR analysis strategy and the corresponding computational tool for batch-fitting EPR spectra and cluster analysis of the χ2 landscape in Linux. We call this tool CSCA (Chi-Squared Cluster Analysis). The CSCA tool allows us to determine self-consistent rotational diffusion rates and enables calculations of activation energies of diffusion from Arrhenius plots. We demonstrate CSCA using a model system designed for EPR analysis: a self-assembled nanoribbon with radical electron spin labels positioned at known distances off the surface. We anticipate that the CSCA tool will increase the reproducibility of EPR fitting for the characterization of dynamics in biomolecules and soft matter.

Energetics and kinetics of substrate analog-coupled staphylococcal nuclease folding revealed by a statistical mechanical approach

Protein conformational changes associated with ligand binding, especially those involving intrinsically disordered proteins, are mediated by tightly coupled intra- and intermolecular events. Such reactions are often discussed in terms of two limiting kinetic mechanisms, conformational selection (CS), where folding precedes binding, and induced fit (IF), where binding precedes folding. It has been shown that coupled folding/binding reactions can proceed along both CS and IF pathways with the flux ratio depending on conditions such as ligand concentration. However, the structural and energetic basis of such complex reactions remains poorly understood. Therefore, we used experimental, theoretical, and computational approaches to explore structural and energetic aspects of the coupled-folding/binding reaction of staphylococcal nuclease in the presence of the substrate analog adenosine-3',5'-diphosphate. Optically monitored equilibrium and kinetic data, combined with a statistical mechanical model, gave deeper insight into the relative importance of specific and Coulombic protein-ligand interactions in governing the reaction mechanism. We also investigated structural aspects of the reaction at the residue level using NMR and all-atom replica-permutation molecular dynamics simulations. Both approaches yielded clear evidence for accumulation of a transient protein-ligand encounter complex early in the reaction under IF-dominant conditions. Quantitative analysis of the equilibrium/kinetic folding revealed that the ligand-dependent CS-to-IF shift resulted from stabilization of the compact transition state primarily by weakly ligand-dependent Coulombic interactions with smaller contributions from specific binding energies. At a more macroscopic level, the CS-to-IF shift was represented as a displacement of the reaction "route" on the free energy surface, which was consistent with a flux analysis.

Structure dictates the mechanism of ligand recognition in the histidine and maltose binding proteins

Two mechanisms, induced fit (IF) and conformational selection (CS), have been proposed to explain ligand recognition coupled conformational changes. The histidine binding protein (HisJ) adopts the CS mechanism, in which a pre-equilibrium is established between the open and the closed states with the ligand binding to the closed state. Despite being structurally similar to HisJ, the maltose binding protein (MBP) adopts the IF mechanism, in which the ligand binds the open state and induces a transition to the closed state. To understand the molecular determinants of this difference, we performed molecular dynamics (MD) simulations of coarse-grained dual structure based models. We find that intra-protein contacts unique to the closed state are sufficient to promote the conformational transition in HisJ, indicating a CS-like mechanism. In contrast, additional ligand-mimicking contacts are required to “induce” the conformational transition in MBP suggesting an IF-like mechanism. In agreement with experiments, destabilizing modifications to two structural features, the spine helix (SH) and the balancing interface (BI), present in MBP but absent in HisJ, reduce the need for ligand-mimicking contacts indicating that SH and BI act as structural restraints that keep MBP in the open state. We introduce an SH like element into HisJ and observe that this can impede the conformational transition increasing the importance of ligand-mimicking contacts. Similarly, simultaneous mutations to BI and SH in MBP reduce the barrier to conformational transitions significantly and promote a CS-like mechanism. Together, our results show that structural restraints present in the protein structure can determine the mechanism of conformational transitions and even simple models that correctly capture such structural features can predict their positions. MD simulations of such models can thus be used, in conjunction with mutational experiments, to regulate protein ligand interactions, and modulate ligand binding affinities.

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MBP operates by induced fit, HisJ by the conformational selection mechanism.

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Dual structure based models (dSBMs) encode two structures of a protein.

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MD simulations of dSBMs can identify the mechanism of conformational transitions.

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Locks, absent in HisJ, hold MBP open with ligand contacts required for closing.

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Binding mechanisms can be modified by altering such structural locks.

Prospecting for new catechol-O-methyltransferase (COMT) inhibitors as a potential treatment for Parkinson's disease: a study by molecular dynamics and structure-based virtual screening

Parkinson's disease (PD) is a neurodegenerative, chronic, and progressive disease, common in the elderly. The catechol-O-methyltransferase (COMT) is a monomeric enzyme involved in dopamine (DA) degradation, the neurotransmitter in deficit in patients with PD. The reference treatment of PD consists of levodopa (L-dopa) administration, which is the precursor of DA. The inhibition of COMT is an adjuvant treatment in PD since it keeps DA levels constant. The goal of this study was to identify drug candidates capable of inhibiting COMT for the treatment of PD and identify important fragments of these molecules. Initially, we analyzed the flexibility of COMT and defined its main conformations in solution regarding the absence (system I) and presence of the S-adenosyl-L-methionine (SAM) cofactor (system II) through molecular dynamics (MD) simulations. Two regions in these structures were selected for molecular docking, firstly the entire cavity where the cofactor and substrates are bound and secondly the specific biding region of the enzyme substrates. Based on the conformations of the MD, the virtual screening (VS) was performed against FDA Approved and Zinc Natural Products databases aiming at the selection of the best compounds. Subsequently, the absorption, distribution, metabolization, excretion, and toxicity (ADMET) properties, as well as drug-score and drug-likeness indexes of the most promising compounds were analyzed. After a detailed analysis of the compounds selected by structure-based VS, it was possible to highlight the fragments most frequently involved in their stability: 2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indole, 9H-Benz(c)indole(3,2,1-ij)(1,5)naphthyridin-9-one and (10R,13S)-10,13-dimethyl-1,2,6,7,8,9,11,12,14,15,16,17dodecahydrocyclopenta[a]phenanthren-3-one. The identification of these potential fragments is essential for the prospection of more specific inhibitors against COMT using the technique of Fragment-based lead discovery (FBLD). Besides, this study allowed us to identify the potential COMT inhibitors through a complete understanding of molecular-level interactions based on the flexibility of this protein.Communicated by Ramaswamy H. Sarma.

Antibody Structure and Function: The Basis for Engineering Therapeutics

Antibodies and antibody-derived macromolecules have established themselves as the mainstay in protein-based therapeutic molecules (biologics). Our knowledge of the structure–function relationships of antibodies provides a platform for protein engineering that has been exploited to generate a wide range of biologics for a host of therapeutic indications. In this review, our basic understanding of the antibody structure is described along with how that knowledge has leveraged the engineering of antibody and antibody-related therapeutics having the appropriate antigen affinity, effector function, and biophysical properties. The platforms examined include the development of antibodies, antibody fragments, bispecific antibody, and antibody fusion products, whose efficacy and manufacturability can be improved via humanization, affinity modulation, and stability enhancement. We also review the design and selection of binding arms, and avidity modulation. Different strategies of preparing bispecific and multispecific molecules for an array of therapeutic applications are included.

Spontaneous Ligand Access Events to Membrane-Bound Cytochrome P450 2D6 Sampled at Atomic Resolution

The membrane-anchored enzyme Cytochrome P450 2D6 (CYP2D6) is involved in the metabolism of around 25% of marketed drugs and its metabolic performance shows a high interindividual variation. While it was suggested that ligands access the buried active site of the enzyme from the membrane, no proof from unbiased simulations has been provided to support this hypothesis. Laboratory experiments fail to capture the access process which is suspected to influence binding kinetics. Here, we applied unbiased molecular dynamics (MD) simulations to investigate the access of ligands to wild-type CYP2D6, as well as the allelic variant CYP2D6*53. In multiple simulations, substrates accessed the active site of the enzyme from the protein-membrane interface to ultimately adopt a conformation that would allow a metabolic reaction. We propose the necessary steps for ligand access and the results suggest that the increased metabolic activity of CYP2D6*53 might be caused by a facilitated ligand uptake.

Binding-induced folding under unfolding conditions: Switching between induced fit and conformational selection mechanisms

The chemistry of protein-ligand binding is the basis of virtually every biological process. Ligand binding can be essential for a protein to function in the cell by stabilizing or altering the conformation of a protein, particularly for partially or completely unstructured proteins. However, the mechanisms by which ligand binding impacts disordered proteins or influences the role of disorder in protein folding is not clear. To gain insight into this question, the mechanism of folding induced by the binding of a Pro-rich peptide ligand to the SH3 domain of phosphatidylinositol 3-kinase unfolded in the presence of urea has been studied using kinetic methods. Under strongly denaturing conditions, folding was found to follow a conformational selection (CS) mechanism. However, under mildly denaturing conditions, a ligand concentration-dependent switch in the mechanism was observed. The folding mechanism switched from being predominantly a CS mechanism at low ligand concentrations to being predominantly an induced fit (IF) mechanism at high ligand concentrations. The switch in the mechanism manifests itself as an increase in the reaction flux along the IF pathway at high ligand concentrations. The results indicate that, in the case of intrinsically disordered proteins too, the folding mechanism is determined by the concentration of the ligand that induces structure formation.

Features of molecular recognition of intrinsically disordered proteins via coupled folding and binding

The sequence-structure-function paradigm of proteins has been revolutionized by the discovery of intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). In contrast to traditional ordered proteins, IDPs/IDRs are unstructured under physiological conditions. The absence of well-defined three-dimensional structures in the free state of IDPs/IDRs is fundamental to their function. Folding upon binding is an important mode of molecular recognition for IDPs/IDRs. While great efforts have been devoted to investigating the complex structures and binding kinetics and affinities, our knowledge on the binding mechanisms of IDPs/IDRs remains very limited. Here, we review recent advances on the binding mechanisms of IDPs/IDRs. The structures and kinetic parameters of IDPs/IDRs can vary greatly, and the binding mechanisms can be highly dependent on the structural properties of IDPs/IDRs. IDPs/IDRs can employ various combinations of conformational selection and induced fit in a binding process, which can be templated by the target and/or encoded by the IDP/IDR. Further studies should provide deeper insights into the molecular recognition of IDPs/IDRs and enable the rational design of IDP/IDR binding mechanisms in the future.