Highlighting the Major Role of Cyclin C in Cyclin-Dependent Kinase 8 Activity through Molecular Dynamics Simulations.

Dysregulation of cyclin-dependent kinase 8 (CDK8) activity has been associated with many diseases, including colorectal and breast cancer. As usual in the CDK family, the activity of CDK8 is controlled by a regulatory protein called cyclin C (CycC). But, while human CDK family members are generally activated in two steps, that is, the binding of the cyclin to CDK and the phosphorylation of a residue in the CDK activation loop, CDK8 does not require the phosphorylation step to be active. Another peculiarity of CDK8 is its ability to be associated with CycC while adopting an inactive form. These specificities raise the question of the role of CycC in the complex CDK8-CycC, which appears to be more complex than the other members of the CDK family. Through molecular dynamics (MD) simulations and binding free energy calculations, we investigated the effect of CycC on the structure and dynamics of CDK8. In a second step, we particularly focused our investigation on the structural and molecular basis of the protein-protein interaction between the two partners by finely analyzing the energetic contribution of residues and simulating the transition between the active and the inactive form. We found that CycC has a stabilizing effect on CDK8, and we identified specific interaction hotspots within its interaction surface compared to other human CDK/Cyc pairs. Targeting these specific interaction hotspots could be a promising approach in terms of specificity to effectively disrupt the interaction between CDK8. The simulation of the conformational transition from the inactive to the active form of CDK8 suggests that the residue Glu99 of CycC is involved in the orientation of three conserved arginines of CDK8. Thus, this residue may assume the role of the missing phosphorylation step in the activation mechanism of CDK8. In a more general view, these results point to the importance of keeping the CycC in computational studies when studying the human CDK8 protein in both the active and the inactive form.

The mutual and dynamic role of TSPO and ligands in their binding process: An example with PK-11195.

Translocator protein (TSPO) is an 18 kDa transmembrane protein, localized primarily on the outer mitochondrial membrane. It has been found to be involved in various physiological processes and pathophysiological conditions. Though studies on its structure have been performed only recently, there is little information on the nature of dynamics and doubts about some structures referenced in the literature, especially the NMR structure of mouse TSPO. In the present work, we thoroughly study the dynamics of mouse TSPO protein by means of atomistic molecular dynamics simulations, in presence as well as in absence of the diagnostic ligand PKA. We considered two starting structures: the NMR structure and a homology model (HM) generated on the basis of X-ray structures from bacterial TSPO. We examine the conformational landscape in both the modes for both starting points, in presence and absence of the ligand, in order to measure its impact for both structures. The analysis highlights high flexibility of the protein globally, but NMR simulations show a surprisingly flexibility even in the presence of the ligand. Interestingly, this is not the case for HM calculations, to the point that the ligand seems not so stable as in the NMR system and an unbinding event process is partially sampled. All those results tend to show that the NMR structure of mTSPO seems not deficient but is just in another portion of the global conformation space of TSPO.

Evaluation of the Potential Impact of In Silico Humanization on VHH Dynamics.

Camelids have the peculiarity of having classical antibodies composed of heavy and light chains as well as single-chain antibodies. They have lost their light chains and one heavy-chain domain. This evolutionary feature means that their terminal heavy-chain domain, VH, called VHH here, has no partner and forms an independent domain. The VHH is small and easy to express alone; it retains thermodynamic and interaction properties. Consequently, VHHs have garnered significant interest from both biotechnological and pharmaceutical perspectives. However, due to their origin in camelids, they cannot be used directly on humans. A humanization step is needed before a possible use. However, changes, even in the constant parts of the antibodies, can lead to a loss of quality. A dedicated tool, Llamanade, has recently been made available to the scientific community. In a previous paper, we already showed the different types of VHH dynamics. Here, we have selected a representative VHH and tested two humanization hypotheses to accurately assess the potential impact of these changes. This example shows that despite the non-negligible change (1/10th of residues) brought about by humanization, the effect is not drastic, and the humanized VHH retains conformational properties quite similar to those of the camelid VHH.

A perspective on the sharing of docking data.

Computational approaches are nowadays largely applied in drug discovery projects. Among these, molecular docking is the most used for hit identification against a drug target protein. However, many scientists in the field shed light on the lack of availability and reproducibility of the data obtained from such studies to the whole community. Consequently, sustaining and developing the efforts toward a large and fully transparent sharing of those data could be beneficial for all researchers in drug discovery. The purpose of this article is first to propose guidelines and recommendations on the appropriate way to conduct virtual screening experiments and second to depict the current state of sharing molecular docking data. In conclusion, we have explored and proposed several prospects to enhance data sharing from docking experiment that could be developed in the foreseeable future.

General Trends of the Camelidae Antibody VHHs Domain Dynamics.

Conformational flexibility plays an essential role in antibodies' functional and structural stability. They facilitate and determine the strength of antigen-antibody interactions. Camelidae express an interesting subtype of single-chain antibody, named Heavy Chain only Antibody. They have only one N-terminal Variable domain (VHH) per chain, composed of Frameworks (FRs) and Complementarity Determining regions (CDRs) like their VH and VL counterparts in IgG. Even when expressed independently, VHH domains display excellent solubility and (thermo)stability, which helps them to retain their impressive interaction capabilities. Sequence and structural features of VHH domains contributing to these abilities have already been studied compared to classical antibodies. To have the broadest view and understand the changes in dynamics of these macromolecules, large-scale molecular dynamics simulations for a large number of non-redundant VHH structures have been performed for the first time. This analysis reveals the most prevalent movements in these domains. It reveals the four main classes of VHHs dynamics. Diverse local changes were observed in CDRs with various intensities. Similarly, different types of constraints were observed in CDRs, while FRs close to CDRs were sometimes primarily impacted. This study sheds light on the changes in flexibility in different regions of VHH that may impact their in silico design.

Quality assessment of VHH models.

Heavy Chain Only Antibodies are specific to Camelid species. Despite the lack of the light chain variable domain, their heavy chain variable domain (VH) domain, named VHH or nanobody, has promising potential applications in research and therapeutic fields. The structural study of VHH is therefore of great interest. Unfortunately, considering the huge amount of sequences that might be produced, only about one thousand of VHH experimental structures are publicly available in the Protein Data Bank, implying that structural model prediction of VHH is a necessary alternative to obtaining 3D information besides its sequence. The present study aims to assess and compare the quality of predictions from different modelling methodologies. Established comparative & homology modelling approaches to recent Deep Learning-based modelling strategies were applied, i.e. Modeller using single or multiple structural templates, ModWeb, SwissModel (with two evaluation schema), RoseTTAfold, AlphaFold 2 and NanoNet. The prediction accuracy was evaluated using RMSD, TM-score, GDT-TS, GDT-HA and Protein Blocks distance metrics. Besides the global structure assessment, we performed specific analyses of Frameworks and CDRs structures. We observed that AlphaFold 2 and especially NanoNet performed better than the other evaluated softwares. Importantly, we performed molecular dynamics simulations of an experimental structure and a NanoNet predicted model of a VHH in order to compare the global structural flexibility and local conformations using Protein Blocks. Despite rather similar structures, substantial differences in dynamical properties were observed, which underlies the complexity of the task of model evaluation.Communicated by Ramaswamy H. Sarma.

Conformational and binding mode assessment of the human IL-3 recognition by its alpha receptor.

Protein-protein interactions (PPIs) are attractive targets as they are critical in a variety of biological processes and pathologies. As an illustration, the interleukin 3 (IL-3) and its α subunit receptor (IL-3Rα) are two proteins belonging to the cytokine or receptor ßc family and are involved in several disorders like inflammatory diseases or hematological malignancies. This PPI exhibits a low binding affinity and a complex formed by a mutant form of IL-3 (superkine) and IL-3Rα have emerged from the literature, with an increase of the affinity. Therefore, in this study, we performed molecular dynamics simulations and binding energy calculation in order to evaluate protein dynamics and to characterize the main interactions between IL-3 and IL-3Rα, considering both wild-type and mutant. First, in the case of IL-3Rα/IL-3 wild-type complex, IL-3Rα can adopt three different conformations essentially driven by NTD domain, including the open and closed conformations, previously observed in crystal structures. Additionally, our results reveal a third conformation that has a distinct interaction profile that the others. Interestingly, these conformational changes are attenuated in IL-3Rα/IL-3 mutant complex. Then, we highlighted the contribution of different residues which interact principally with IL-3 or IL-3Rα conserved region. As for the mutated residue at position 135 of IL-3, other residues such as IL-3 E138, IL-3 D40, IL-3Rα Y279, IL-3Rα K235, or IL-3Rα R277 seem important for a low or a high binding affinity. Altogether these findings yield new information that could be exploited in a drug discovery process.

Estimation of Drug-Target Residence Time by Targeted Molecular Dynamics Simulations.

Drug-target residence time has emerged as a key selection factor in drug discovery since the binding duration of a drug molecule to its protein target can significantly impact its in vivo efficacy. The challenge in studying the residence time, in early drug discovery stages, lies in how to cost-effectively determine the residence time for the systematic assessment of compounds. Currently, there is still a lack of computational protocols to quickly estimate such a measure, particularly for large and flexible protein targets and drugs. Here, we report an efficient computational protocol, based on targeted molecular dynamics, to rank drug candidates by their residence time and to obtain insights into ligand-target dissociation mechanisms. The method was assessed on a dataset of 10 arylpyrazole inhibitors of CDK8, a large, flexible, and clinically important target, for which the experimental residence time of the inhibitors ranges from minutes to hours. The compounds were correctly ranked according to their estimated residence time scores compared to their experimental values. The analysis of protein-ligand interactions along the dissociation trajectories highlighted the favorable contribution of hydrophobic contacts to residence time and revealed key residues that strongly affect compound residence time.

VHH Structural Modelling Approaches: A Critical Review.

VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of VHHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved VHH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.

Analysis of Integrin αIIb Subunit Dynamics Reveals Long-Range Effects of Missense Mutations on Calf Domains.

Integrin αIIbß3, a glycoprotein complex expressed at the platelet surface, is involved in platelet aggregation and contributes to primary haemostasis. Several integrin αIIbß3 polymorphisms prevent the aggregation that causes haemorrhagic syndromes, such as Glanzmann thrombasthenia (GT). Access to 3D structure allows understanding the structural effects of polymorphisms related to GT. In a previous analysis using Molecular Dynamics (MD) simulations of αIIbCalf-1 domain structure, it was observed that GT associated with single amino acid variation affects distant loops, but not the mutated position. In this study, experiments are extended to Calf-1, Thigh, and Calf-2 domains. Two loops in Calf-2 are unstructured and therefore are modelled expertly using biophysical restraints. Surprisingly, MD revealed the presence of rigid zones in these loops. Detailed analysis with structural alphabet, the Proteins Blocks (PBs), allowed observing local changes in highly flexible regions. The variant P741R located at C-terminal of Calf-1 revealed that the Calf-2 presence did not affect the results obtained with isolated Calf-1 domain. Simulations for Calf-1 + Calf-2, and Thigh + Calf-1 variant systems are designed to comprehend the impact of five single amino acid variations in these domains. Distant conformational changes are observed, thus highlighting the potential role of allostery in the structural basis of GT.

Exploring Dihydroflavonol-4-Reductase Reactivity and Selectivity by QM/MM-MD Simulations.

Flavonoids are secondary metabolites ubiquitously found in plants. Their antioxidant properties make them highly interesting natural compounds for use in pharmacology. Therefore, unravelling the mechanisms of flavonoid biosynthesis is an important challenge. Among all the enzymes involved in this biosynthetic pathway, dihydroflavonol-4-reductase (DFR) plays a key role in the production of anthocyanins and proanthocyanidins. Here, we provide new information on the mechanism of action of this enzyme by using QM/MM-MD simulations applied to both dihydroquercetin (DHQ) and dihydrokaempferol (DHK) substrates. The consideration of these very similar compounds shed light on the major role played by the enzyme on the stabilization of the transition state but also on the activation of the substrate before the reaction through near-attack conformer effects.

Structural and evolutionary exploration of the IL-3 family and its alpha subunit receptors.

Interleukin-3 (IL-3) is a cytokine belonging to the family of common ß (ßc) and is involved in various biological systems. Its activity is mediated by the interaction with its receptor (IL-3R), a heterodimer composed of two distinct subunits: IL-3Rα and ßc. IL-3 and its receptor, especially IL-3Rα, play a crucial role in pathologies like inflammatory diseases and therefore are interesting therapeutic targets. Here, we have performed an analysis of these proteins and their interaction based on structural and evolutionary information. We highlighted that IL-3 and IL-3Rα structural architectures are conserved across evolution and shared with other proteins belonging to the same ßc family interleukin-5 (IL-5) and granulocyte-macrophage colony-stimulating factor (GM-CSF). The IL-3Rα/IL-3 interaction is mediated by a large interface in which most residues are surprisingly not conserved during evolution and across family members. In spite of this high variability, we suggested small regions constituted by few residues conserved during the evolution in both proteins that could be important for the binding affinity.

Equipping Coiled-Coil Peptide Dimers With Furan Warheads Reveals Novel Cross-Link Partners.

Using a coiled-coil peptide dimer as a model system to explore furan reactivity, we describe novel cross-link partners of furan warheads for site-specific cross-linking. We demonstrate that replacement of weak interhelical ionic contacts with a furan moiety and its potential cross-link partner affords covalently connected coiled-coil motifs upon furan activation. We describe for the first time the reaction of the activated furan warhead with cysteine and tyrosine, besides the previously reported lysine, thus enhancing the versatility of the furan cross-link methodology by the possibility to target different amino acids. The present in vitro validation of "furan-armed" α-helices provides further grounds for exploiting furan technology in the development of furan-modified ligands/proteins to target proteins in a covalent way through various amino acid side chains.

Versatile Dimerisation Process of Translocator Protein (TSPO) Revealed by an Extensive Sampling Based on a Coarse-Grained Dynamics Study.

Translocator protein (TSPO), a mitochondrial membrane protein, has been extensively studied, and its role is still debated and continues to be enigmatic. From a structural perspective, despite availability of atomic structures from different species, the possible oligomeric state and its 3D structure remains elusive. In the present study, we attempted to study dynamics of TSPO from the perspective of oligomerization. In this aim, we examined if and how TSPO monomers could assemble to form a dimer. Accordingly, we performed several coarse-grained molecular dynamics simulations considering two different initial configurations, one with a pair of TSPO monomers distantly placed in a model of a bilayer composed of DMPC/cholesterol mixture and the other with preformed dimer models with different starting interactions. We identify stable TSPO dimers with diverse interfaces, some of which were consistent with earlier experimental observations on putative TSPO oligomer interfaces. For most of the stable ones, interactions between aromatic residues were significantly overrepresented in diverse oligomeric organizations. Interestingly, we identified different communication pathways that involve dimer interfaces. Additionally, we observed that cholesterol molecules in close interaction with the TSPO dimer were able to translocate through the bilayer. This phenomenon might be related to the putative mechanism of cholesterol transport and could be increased and favored by the dimer formation. Overall, our observations shed new light on TSPO oligomerization and bring new perspectives on its dynamics, as well its interactions with protein and ligand partners.

Computational Analysis of Crystallization Additives for the Identification of New Allosteric Sites.

Allosteric effect can modulate the biological activity of a protein. Thus, the discovery of new allosteric sites is very attractive for designing new modulators or inhibitors. Here, we propose an innovative way to identify allosteric sites, based on crystallization additives (CA), used to stabilize proteins during the crystallization process. Density and clustering analyses of CA, applied on protein kinase and nuclear receptor families, revealed that CA are not randomly distributed around protein structures, but they tend to aggregate near common sites. All orthosteric and allosteric cavities described in the literature are retrieved from the analysis of CA distribution. In addition, new sites were identified, which could be associated to putative allosteric sites. We proposed an efficient and easy way to use the structural information of CA to identify allosteric sites. This method could assist medicinal chemists for the design of new allosteric compounds targeting cavities of new drug targets.

An original class of small sized molecules as versatile fluorescent probes for cellular imaging.

An unusual class, compact in size, of fluorescent probes based on pyridazino-1,3a,6a-triazapentalene scaffolds exhibits promising fluorescent properties (quantum yield values up to 73%, large Stokes shifts, emission wavelengths located in the green-yellow range, excellent solubility) with good photostability suitable for optical imaging applications.

In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide Interactions.

Peptide⁻protein interactions are corner-stones of living functions involved in essential mechanisms, such as cell signaling. Given the difficulty of obtaining direct experimental structural biology data, prediction of those interactions is of crucial interest for the rational development of new drugs, notably to fight diseases, such as cancer or Alzheimer's disease. Because of the high flexibility of natural unconstrained linear peptides, prediction of their binding mode in a protein cavity remains challenging. Several theoretical approaches have been developed in the last decade to address this issue. Nevertheless, improvements are needed, such as the conformation prediction of peptide side-chains, which are dependent on peptide length and flexibility. Here, we present a novel in silico method, Iterative Residue Docking and Linking (IRDL), to efficiently predict peptide⁻protein interactions. In order to reduce the conformational space, this innovative method splits peptides into several short segments. Then, it uses the performance of intramolecular covalent docking to rebuild, sequentially, the complete peptide in the active site of its protein target. Once the peptide is constructed, a rescoring step is applied in order to correctly rank all IRDL solutions. Applied on a set of 11 crystallized peptide⁻protein complexes, the IRDL method shows promising results, since it is able to retrieve experimental binding conformations with a Root Mean Square Deviation (RMSD) below 2 Šin the top five ranked solutions. For some complexes, IRDL method outperforms two other docking protocols evaluated in this study. Hence, IRDL is a new tool that could be used in drug design projects to predict peptide⁻protein interactions.

Development of Kinase Inhibitors via Metal-Catalyzed C⁻H Arylation of 8-Alkyl-thiazolo[5,4-f]-quinazolin-9-ones Designed by Fragment-Growing Studies.

Efficient metal catalyzed C⁻H arylation of 8-alkyl-thiazolo[5,4-f]-quinazolin-9-ones was explored for SAR studies. Application of this powerful chemical tool at the last stage of the synthesis of kinase inhibitors allowed the synthesis of arrays of molecules inspired by fragment-growing studies generated by molecular modeling calculations. Among the potentially active compounds designed through this strategy, FC162 (4c) exhibits nanomolar IC50 values against some kinases, and is the best candidate for the development as a DYRK kinase inhibitor.

Enhanced Molecular Dynamics Methods Applied to Drug Design Projects.

Nobel Laureate Richard P. Feynman stated: "[…] everything that living things do can be understood in terms of jiggling and wiggling of atoms […]." The importance of computer simulations of macromolecules, which use classical mechanics principles to describe atom behavior, is widely acknowledged and nowadays, they are applied in many fields such as material sciences and drug discovery. With the increase of computing power, molecular dynamics simulations can be applied to understand biological mechanisms at realistic timescales. In this chapter, we share our computational experience providing a global view of two of the widely used enhanced molecular dynamics methods to study protein structure and dynamics through the description of their characteristics, limits and we provide some examples of their applications in drug design. We also discuss the appropriate choice of software and hardware. In a detailed practical procedure, we describe how to set up, run, and analyze two main molecular dynamics methods, the umbrella sampling (US) and the accelerated molecular dynamics (aMD) methods.

An Unusual Binding Model of the Methyl 9-Anilinothiazolo[5,4-f] quinazoline-2-carbimidates (EHT 1610 and EHT 5372) Confers High Selectivity for Dual-Specificity Tyrosine Phosphorylation-Regulated Kinases.

Methyl 9-anilinothiazolo[5,4-f]quinazoline-2-carbimidates 1 (EHT 5372) and 2 (EHT 1610) are strong inhibitors of DYRK's family kinases. The crystal structures of the complex revealed a noncanonical binding mode of compounds 1 and 2 in DYRK2, explaining the remarkable selectivity and potency of these inhibitors. The structural data and comparison presented here provide therefore a template for further improvement of this inhibitor class and for the development of novel inhibitors selectively targeting DYRK kinases.