In silico prediction of protein flexibility with local structure approach

Drug repositioning for rosacea disease: Biological TARGET identification, molecular docking, pharmacophore mapping, and molecular dynamics analysis

Rosacea is a chronic dermatological condition that currently lacks a clear treatment approach due to an uncomprehensive knowledge of its pathogenesis. The main obstacle lies in understanding its etiology and the mode of action of the different drugs used. This study aims to clarify these aspects by employing drug repositioning. Using an in silico approach, we performed a transcriptomic analysis comparing samples from individuals with diverse types of rosacea to those from healthy controls to identify genes deregulated in this disease. Subsequently, we realized molecular docking and molecular dynamics studies to assess the binding affinity of drugs currently used to treat rosacea and drugs that target proteins interacting with, and thus affecting, proteins deregulated in rosacea. Our findings revealed that the downregulation of SKAP2 and upregulation of S100A7A in rosacea, could be involved in the pathogenesis of the disease. Furthermore, considering the drugs currently used for rosacea management, we demonstrated stable interactions between isotretinoin and BFH772 with SKAP2, and permethrin and PAC-14028 with S100A7A. Similarly, considering drugs targeting SKAP2 and S100A7A interactome proteins, we found that pitavastatin and dasatinib exert stable interactions with SKAP2, and lovastatin and tirbanibulin with S100A7A. In addition, we determine that the types of bonds involved in the interactions were different in SKAP2 from S100A7A. The drug-SKAP2 interactions are hydrogen bonds, whereas the drug-S100A7A interactions are of the hydrophobic type. In conclusion, our study provides evidence for the possible contribution of SKAP2 and S100A7A to rosacea pathology. Furthermore, it provides significant information on the molecular interactions between drugs and these proteins, highlighting the importance of considering structural features and binding interactions in the design of targeted therapies for skin disorders such as rosacea.

Assessment of Four Theoretical Approaches to Predict Protein Flexibility in the Crystal Phase and Solution

In this paper, we evaluated the ability of four coarse-grained methods to predict protein flexible regions with potential biological importance, UNRES-flex, UNRES-DSSP-flex (based on the united residue model of polypeptide chains without and with secondary structure restraints, respectively), CABS-flex (based on the C-α, C-β, and side chain model), and nonlinear rigid block normal mode analysis (NOLB) with a set of 100 protein structures determined by NMR spectroscopy or X-ray crystallography, with all secondary structure types. End regions with high fluctuations were excluded from analysis. The Pearson and Spearman correlation coefficients were used to quantify the conformity between the calculated and experimental fluctuation profiles, the latter determined from NMR ensembles and X-ray B-factors, respectively. For X-ray structures (corresponding to proteins in a crowded environment), NOLB resulted in the best agreement between the predicted and experimental fluctuation profiles, while for NMR structures (corresponding to proteins in solution), the ranking of performance is CABS-flex > UNRES-DSSP-flex > UNRES-flex > NOLB; however, CABS-flex sometimes exaggerated the extent of small fluctuations, as opposed to UNRES-DSSP-flex.

Machine learning-based prediction of proteins' architecture using sequences of amino acids and structural alphabets

In addition to the growth of protein structures generated through wet laboratory experiments and deposited in the PDB repository, AlphaFold predictions have significantly contributed to the creation of a much larger database of protein structures. Annotating such a vast number of structures has become an increasingly challenging task. CATH is widely recognized as one the most common platforms for addressing this challenge, as it classifies proteins based on their structural and evolutionary relationships, offering the scientific community an invaluable resource for uncovering various properties, including functional annotations. While CATH annotation involves - to some extent - human intervention, keeping up with the classification of the rapidly expanding repositories of protein structures has become exceedingly difficult. Therefore, there is a pressing need for a fully automated approach. On the other hand, the abundance of protein sequences stemming from next generation sequencing technologies, lacking structural annotations, presents an additional challenge to the scientific community. Consequently, 'pre-annotating' protein sequences with structural features, ensuring a high level of precision, could prove highly advantageous. In this paper, after a thorough investigation, we introduce a novel machine-learning model capable of classifying any protein domain, whether it has a known structure or not, into one of the 40 main CATH Architectures. We achieve an F1 Score of 0.92 using only the amino acid sequence and a score of 0.94 using both the sequence of amino acids and the sequence of structural alphabets.Communicated by Ramaswamy H. Sarma.

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 (V_HH) per chain, composed of Frameworks (FRs) and Complementarity Determining regions (CDRs) like their VH and VL counterparts in IgG. Even when expressed independently, V_HH domains display excellent solubility and (thermo)stability, which helps them to retain their impressive interaction capabilities. Sequence and structural features of V_HH 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 V_HH 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 V_HHs 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 V_HH that may impact their in silico design.

Spectroscopic, molecular docking and dynamic simulation studies of binding between the new anticancer agent olmutinib and human serum albumin

In this study, the interaction between human serum albumin (HSA), which is the key bio-distributor of exogenous and endogenous compounds in the human bloodstream, and HM61713 (Olmutinib; OMB), which is used as an anticancer drug, is examined by multiple spectroscopic techniques (steady-state fluorescence, UV spectrophotometry, synchronous, and 3 D fluorescence) combined with molecular docking and molecular dynamic simulation investigations. The fluorescence results clearly demonstrated quenching in HSA fluorescence in the existence of OMB indicating the formation of complex and have also shown that the interaction is static. Fluorescence spectroscopy was used to obtain the binding constant values that revealed a strong interaction between the HSA and OMB at 298 K with a binding constant of 7.39x10⁴ M^-1 suggesting strong interaction. OMB binds to HSA at site I (IIA). Electrostatic forces and H-bonding were the main binding forces of main bonding between HSA and OMB as revealed by docking and thermodynamic results.Communicated by Ramaswamy H. Sarma.

Study of the dynamic behavior of the cruzain enzyme in free and complexed forms with competitive and noncovalent benzimidazole inhibitors

There are only two drugs for the treatment of Chagas disease, namely, nifurtimox and benznidazole, that can cause several adverse effects. Despite the effectiveness of these drugs in the disease's acute phase, they are not recognized as curative in the chronic phase, establishing the need for more effective treatment in all stages of the disease. Cruzain is an enzyme that plays a vital role in the life cycle of the etiologic agent, the protozoan Trypanosoma cruzi, being relevant as a therapeutic target in the planning of new drugs. Using molecular docking and dynamics simulations, we have investigated the structural and dynamic factors that can be involved in the enzyme inhibition process at the atomic-molecular level by benzimidazole compounds that are potent cruzain inhibitors with in vitro trypanocidal activity. The study suggests that these inhibitors bind cruzain through steric and hydrogen bonding interactions without altering its secondary structure content and protein compaction. Besides, we observed that these inhibitors decrease the correlation of movements between Cα-atoms of cruzain, increasing the number of atomic communities, mainly in the α-helix that presents the catalytic Cys25 residue. As expected, we also observed a correlation between the inhibitory activity of each inhibitor and their respective binding-free energies, reinforcing that the affinity of the complexes seems to be a relevant factor for enzymatic inhibition. Hence, the results presented in this work contribute to a better understanding of the cruzain enzyme inhibition mechanism through competitive and non-covalent inhibitors.Communicated by Ramaswamy H. Sarma.

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

Integrin α_IIbβ₃, a glycoprotein complex expressed at the platelet surface, is involved in platelet aggregation and contributes to primary haemostasis. Several integrin α_IIbβ₃ 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 α_IIbCalf-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.

Co-evolutionary distance predictions contain flexibility information

MOTIVATION

Co-evolution analysis can be used to accurately predict residue-residue contacts from multiple sequence alignments. The introduction of machine-learning techniques has enabled substantial improvements in precision and a shift from predicting binary contacts to predict distances between pairs of residues. These developments have significantly improved the accuracy of de novo prediction of static protein structures. With AlphaFold2 lifting the accuracy of some predicted protein models close to experimental levels, structure prediction research will move on to other challenges. One of those areas is the prediction of more than one conformation of a protein. Here, we examine the potential of residue-residue distance predictions to be informative of protein flexibility rather than simply static structure.

RESULTS

We used DMPfold to predict distance distributions for every residue pair in a set of proteins that showed both rigid and flexible behaviour. Residue pairs that were in contact in at least one reference structure were classified as rigid, flexible or neither. The predicted distance distribution of each residue pair was analysed for local maxima of probability indicating the most likely distance or distances between a pair of residues. We found that rigid residue pairs tended to have only a single local maximum in their predicted distance distributions while flexible residue pairs more often had multiple local maxima. These results suggest that the shape of predicted distance distributions contains information on the rigidity or flexibility of a protein and its constituent residues.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characterizing the potentially neuronal acetylcholinesterase reactivity toward chiral pyraclofos: Enantioselective insights from spectroscopy, in silico docking, molecular dynamics simulation and per-residue energy decomposition studies

Chiral organophosphorus agents are distributed ubiquitously in the environment, but the neuroactivity of these asymmetric chemicals to humans remains uncertain. This scenario was to explore the stereoselective neurobiological response of human acetylcholinesterase (AChE) to chiral pyraclofos at the enantiomeric scale, and then decipher the microscopic basis of enantioselective neurotoxicity of pyraclofos enantiomers. The results indicated that (R)-/(S)-pyraclofos can form the bioconjugates with AChE with a stoichiometric ratio of 1:1, but the neuronal affinity of (R)-pyraclofos (K = 6.31 × 10⁴ M^-1) with AChE was larger than that of (S)-pyraclofos (K = 1.86 × 10⁴ M^-1), and significant enantioselectivity was existed in the biochemical reaction. The modes of neurobiological action revealed that pyraclofos enantiomers were situated at the substrate binding domain, and the strength of the overall noncovalent bonds between (S)-pyraclofos and the residues was weaker than that of (R)-pyraclofos, resulting in the high inhibitory effect of (R)-pyraclofos toward the activity of AChE. Dynamic enantioselective biointeractions illustrated that the intervention of inherent conformational flexibility in the AChE-(R)-pyraclofos was greater than that of the AChE-(S)-pyraclofos, which arises from the big spatial displacement and the conformational flip of the binding domain composed of the residues Thr-64～Asn-89, Gly-122～Asp-134, and Thr-436～Tyr-449. Energy decomposition exhibited that the Gibbs free energies of the AChE-(R)-/(S)-pyraclofos were ΔG° = －37.4/－30.2 kJ mol^-1, respectively, and the disparity comes from the electrostatic energy during the stereoselective neurochemical reactions. Quantitative conformational analysis further confirmed the atomic-scale computational chemistry conclusions, and the perturbation of (S)-pyraclofos on the AChE's ordered conformation was lower than that of (R)-pyraclofos, which is germane to the interaction energies of the crucial residues, e.g. Tyr-124, Tyr-337, Asp-74, Trp-86, and Tyr-119. Evidently, this attempt will contribute mechanistic information to uncovering the neurobiological effects of chiral organophosphates on the body.

CALR-ETdb, the database of calreticulin variants diversity in essential thrombocythemia

Essential thrombocythemia (ET) is a blood cancer defined by a strong increase of platelet numbers. A quarter of patients suffering from ET show mutations in the last exon of calreticulin (CALR) gene. Two variants named type 1 and type 2 represent 85% of these patients. However, a large number of other variants have been determined. In this study, we have compiled variants taken from COSMIC database and literature leading to 155 different variants. This large number of variants allowed redefining 5 new classes extending the classification of type 1-like and type 2-like to a finer description. These analyses showed that last class, named E, corresponding to more than 10% of CALR variants seemed not attached to ET. Structural properties analyzed showed that CALR variants associated to ET have common features. All the compiled and refined information had been included into a freely dedicated database CALR-ETdb (https://www.dsimb.inserm.fr/CALR-ET).

Impact of protein dynamics on secondary structure prediction

Protein 3D structures support their biological functions. As the number of protein structures is negligible in regards to the number of available protein sequences, prediction methodologies relying only on protein sequences are essential tools. In this field, protein secondary structure prediction (PSSPs) is a mature area, and is considered to have reached a plateau. Nonetheless, proteins are highly dynamical macromolecules, a property that could impact the PSSP methods. Indeed, in a previous study, the stability of local protein conformations was evaluated demonstrating that some regions easily changed to another type of secondary structure. The protein sequences of this dataset were used by PSSPs and their results compared to molecular dynamics to investigate their potential impact on the quality of the secondary structure prediction. Interestingly, a direct link is observed between the quality of the prediction and the stability of the assignment to the secondary structure state. The more stable a local protein conformation is, the better the prediction will be. The secondary structure assignment not taken from the crystallized structures but from the conformations observed during the dynamics slightly increase the quality of the secondary structure prediction. These results show that evaluation of PSSPs can be done differently, but also that the notion of dynamics can be included in development of PSSPs and other approaches such as de novo approaches.

Analysis of Protein Disorder Predictions in the Light of a Protein Structural Alphabet

Intrinsically-disordered protein (IDP) characterization was an amazing change of paradigm in our classical sequence-structure-function theory. Moreover, IDPs are over-represented in major disease pathways and are now often targeted using small molecules for therapeutic purposes. This has had created a complex continuum from order-that encompasses rigid and flexible regions-to disorder regions; the latter being not accessible through classical crystallographic methodologies. In X-ray structures, the notion of order is dictated by access to resolved atom positions, providing rigidity and flexibility information with low and high experimental B-factors, while disorder is associated with the missing (non-resolved) residues. Nonetheless, some rigid regions can be found in disorder regions. Using ensembles of IDPs, their local conformations were analyzed in the light of a structural alphabet. An entropy index derived from this structural alphabet allowed us to propose a continuum of states from rigidity to flexibility and finally disorder. In this study, the analysis was extended to comparing these results to disorder predictions, underlying a limited correlation, and so opening new ideas to characterize and predict disorder.