Enhancing genome-wide populus trait prediction through deep convolutional neural networks.

As a promising model, genome-based plant breeding has greatly promoted the improvement of agronomic traits. Traditional methods typically adopt linear regression models with clear assumptions, neither obtaining the linkage between phenotype and genotype nor providing good ideas for modification. Nonlinear models are well characterized in capturing complex nonadditive effects, filling this gap under traditional methods. Taking populus as the research object, this paper constructs a deep learning method, DCNGP, which can effectively predict the traits including 65 phenotypes. The method was trained on three datasets, and compared with other four classic models-Bayesian ridge regression (BRR), Elastic Net, support vector regression, and dualCNN. The results show that DCNGP has five typical advantages in performance: strong prediction ability on multiple experimental datasets; the incorporation of batch normalization layers and Early-Stopping technology enhancing the generalization capabilities and prediction stability on test data; learning potent features from the data and thus circumventing the tedious steps of manual production; the introduction of a Gaussian Noise layer enhancing predictive capabilities in the case of inherent uncertainties or perturbations; fewer hyperparameters aiding to reduce tuning time across datasets and improve auto-search efficiency. In this way, DCNGP shows powerful predictive ability from genotype to phenotype, which provide an important theoretical reference for building more robust populus breeding programs.

Structural characterization of the Plasmodium falciparum lactate transporter PfFNT alone and in complex with antimalarial compound MMV007839 reveals its inhibition mechanism.

Plasmodium falciparum, the deadliest causal agent of malaria, caused more than half of the 229 million malaria cases worldwide in 2019. The emergence and spreading of frontline drug-resistant Plasmodium strains are challenging to overcome in the battle against malaria and raise urgent demands for novel antimalarial agents. The P. falciparum formate-nitrite transporter (PfFNT) is a potential drug target due to its housekeeping role in lactate efflux during the intraerythrocytic stage. Targeting PfFNT, MMV007839 was identified as a lead compound that kills parasites at submicromolar concentrations. Here, we present 2 cryogenic-electron microscopy (cryo-EM) structures of PfFNT, one with the protein in its apo form and one with it in complex with MMV007839, both at 2.3 Å resolution. Benefiting from the high-resolution structures, our study provides the molecular basis for both the lactate transport of PfFNT and the inhibition mechanism of MMV007839, which facilitates further antimalarial drug design.

Revealing Allosteric Mechanism of Amino Acid Binding Proteins from Open to Closed State.

Amino acid binding proteins (AABPs) undergo significant conformational closure in the periplasmic space of Gram-negative bacteria, tightly binding specific amino acid substrates and then initiating transmembrane transport of nutrients. Nevertheless, the possible closure mechanisms after substrate binding, especially long-range signaling, remain unknown. Taking three typical AABPs-glutamine binding protein (GlnBP), histidine binding protein (HisJ) and lysine/arginine/ornithine binding protein (LAOBP) in Escherichia coli (E. coli)-as research subjects, a series of theoretical studies including sequence alignment, Gaussian network model (GNM), anisotropic network model (ANM), conventional molecular dynamics (cMD) and neural relational inference molecular dynamics (NRI-MD) simulations were carried out. Sequence alignment showed that GlnBP, HisJ and LAOBP have high structural similarity. According to the results of the GNM and ANM, AABPs' Index Finger and Thumb domains exhibit closed motion tendencies that contribute to substrate capture and stable binding. Based on cMD trajectories, the Index Finger domain, especially the I-Loop region, exhibits high molecular flexibility, with residues 11 and 117 both being potentially key residues for receptor-ligand recognition and initiation of receptor allostery. Finally, the signaling pathway of AABPs' conformational closure was revealed by NRI-MD training and trajectory reconstruction. This work not only provides a complete picture of AABPs' recognition mechanism and possible conformational closure, but also aids subsequent structure-based design of small-molecule oncology drugs.

Molecular basis for substrate recognition by the bacterial nucleoside transporter NupG.

Nucleoside homeostasis, which is mediated by transporters and channels, is essential for all life on Earth. In Escherichia coli, NupG mediates the transport of nucleosides and was deemed to be the prototype of the nucleoside proton symporter (NHS) family and the major facilitator superfamily. To date, the substrate recognition and transport mechanisms of NHS transporters are still elusive. Here, we report two crystal structures of NupG (WT and D323A NupG) resolved at 3.0 Å. Both structures reveal an identical inward-open conformation. Together with molecular docking and molecular dynamics simulations and in vitro uridine-binding assays, we found that the uridine binding site, which locates in the central cavity between N and C domains of NupG, is constituted by R136, T140, F143, Q225, N228, Q261, E264, Y318, and F322. Moreover, we found that D323 is very important for substrate binding via in vitro uridine-binding assays using D323 mutations, although it does not have a direct contact with uridine. Our structural and biochemical data therefore provide an important framework for the mechanistic understanding of nucleoside transporters of the NHS family.

Allosteric and transport modulation of human concentrative nucleoside transporter 3 at the atomic scale.

Nucleosides are important precursors of nucleotide synthesis in cells, and nucleoside transporters play an important role in many physiological processes by mediating transmembrane transport and absorption. During nucleoside transport, such proteins undergo a significant conformational transition between the outward- and inward-facing states, which leads to alternating access of the substrate-binding site to either side of the membrane. In this work, a variety of molecular simulation methods have been applied to comparatively investigate the motion modes of human concentrative nucleoside transporter 3 (hCNT3) in three states, as well as global and local cavity conformational changes; and finally, a possible elevator-like transport mechanism consistent with experimental data was proposed. The results of the Gaussian network model (GNM) and anisotropic network model (ANM) show that hCNT3 as a whole tends to contract inwards and shift towards a membrane inside, exhibiting an allosteric process that is more energetically favorable than the rigid conversion. To reveal the complete allosteric process of hCNT3 in detail, a series of intermediate conformations were obtained by an adaptive anisotropic network model (aANM). One of the simulated intermediate states is similar to that of a crystal structure, which indicates that the allosteric process is reliable; the state with lower energy is slightly inclined to the inward-facing structure rather than the expected intermediate crystal structure. The final HOLE analysis showed that except for the outward-facing state, the transport channels were gradually enlarged, which was conductive to the directional transport of nucleosides. Our work provides a theoretical basis for the multistep elevator-like transportation mechanism of nucleosides, which helps to further understand the dynamic recognition between nucleoside substrates and hCNT3 as well as the design of nucleoside anticancer drugs.

The global motion affecting electron transfer in Plasmodium falciparum type II NADH dehydrogenases: a novel non-competitive mechanism for quinoline ketone derivative inhibitors.

With the emergence of drug-resistant Plasmodium falciparum, the treatment of malaria has become a significant challenge; therefore, the development of antimalarial drugs acting on new targets is extremely urgent. In Plasmodium falciparum, type II nicotinamide adenine dinucleotide (NADH) dehydrogenase (NDH-2) is responsible for catalyzing the transfer of two electrons from NADH to flavin adenine dinucleotide (FAD), which in turn transfers the electrons to coenzyme Q (CoQ). As an entry enzyme for oxidative phosphorylation, NDH-2 has become one of the popular targets for the development of new antimalarial drugs. In this study, reliable motion trajectories of the NDH-2 complex with its co-factors (NADH and FAD) and inhibitor, RYL-552, were obtained by comparative molecular dynamics simulations. The influence of cofactor binding on the global motion of NDH-2 was explored through conformational clustering, principal component analysis and free energy landscape. The molecular interactions of NDH-2 before and after its binding with the inhibitor RYL-552 were analyzed, and the key residues and important hydrogen bonds were also determined. The results show that the association of RYL-552 results in the weakening of intramolecular hydrogen bonds and large allosterism of NDH-2. There was a significant positive correlation between the angular change of the key pocket residues in the NADH-FAD-pockets that represents the global functional motion and the change in distance between NADH-C4 and FAD-N5 that represents the electron transfer efficiency. Finally, the possible non-competitive inhibitory mechanism of RYL-552 was proposed. Specifically, the association of inhibitors with NDH-2 significantly affects the global motion mode of NDH-2, leading to widening of the distance between NADH and FAD through cooperative motion induction; this reduces the electron transfer efficiency of the mitochondrial respiratory chain. The simulation results provide useful theoretical guidance for subsequent antimalarial drug design based on the NDH-2 structure and the respiratory chain electron transfer mechanism.

Discovery of a Potent, Orally Active, and Long-Lasting P2X7 Receptor Antagonist as a Preclinical Candidate for Delaying the Progression of Chronic Kidney Disease.

Chronic kidney disease (CKD) is a condition characterized by functional deterioration with sustained inflammation and progressive fibrosis of the kidneys affecting over 800 million people worldwide. The P2X7 receptor (P2X7R) plays a key role in CKD progression. Our previous P2X7R antagonists demonstrated good efficacy for treating kidney injury but were limited by low oral exposure and short half-life, restricting their application. This study reports the optimization of P2X7R antagonists for better oral pharmacokinetics. The candidate compound 13a with the respective IC50 of 34.86 and 25.28 nM against human and murine P2X7R, administered orally at 10 mg/kg in mice, exhibits a remarkably long half-life of 161.64 h, with a high exposure of 1,163,980.55 µg·h/L. Oral administration of 13a (0.3 or 1.0 mg/kg, twice weekly) significantly reduced renal injury and fibrosis in unilateral ureteral obstruction and adenine diet-induced mice models, highlighting its potential for delaying the progression of CKD.

Omicron-included mutation-induced changes in epitopes of SARS-CoV-2 spike protein and effectiveness assessments of current antibodies.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading globally and continues to rage, posing a serious threat to human health and life quality. Antibody therapy and vaccines both have shown great efficacy in the prevention and treatment of COVID-19, whose development progress and adaptation range have attracted wide attention. However, with the emergence of variant strains of SARS-CoV-2, the neutralization activity of therapeutic or vaccine-induced antibodies may be reduced, requiring long-term virus monitoring and drug upgrade in response to its evolution. In this paper, conformational changes including continuous epitopes (CPs), discontinuous epitopes (DPs) and recognition interfaces of the three representative SARS-CoV-2 spike protein (SP) mutants (i.e., the Delta (B.1.617.2), Mu (B.1.621) and Omicron (B.1.1.529) strains), were analyzed to evaluate the effectiveness of current mainstream antibodies. The results showed that the conformation of SP wild type (WT) and mutants both remained stable, while the local antigenic epitopes underwent significant changes. Sufficient flexibility of SP CPs is critical for effective antibody recognition. The DPs of Delta, Mu and Omicron variants have showed stronger binding to human angiotensin converting enzyme-2 (hACE2) than WT; the possible drug resistance mechanisms of antibodies against three different epitopes (i.e., NTD_DP, RBD1_DP and RBD2_DP) were also proposed, respectively; the RBD2 of Delta, NTD of Mu, NTD and RBD2 of Omicron are deserve more attention in the subsequent design of next-generation vaccines. The simulation results not only revealed structural characteristics of SP antigenic epitopes, but also provided guidance for antibody modification, vaccine design and effectiveness evaluation.

Recognition and release of uridine and hCNT3: From multivariate interactions to molecular design.

As a vital target for the development of novel anti-cancer drugs, human concentrative nucleoside transporter 3 (hCNT3) has been widely concerned. Nevertheless, the lack of a comprehensive understanding of molecular interactions and motion mechanism has greatly hindered the development of novel inhibitors against hCNT3. In this paper, molecular recognition of hCNT3 with uridine was investigated with molecular docking, conventional molecular dynamics (CMD) simulations and adaptive steered molecular dynamics (ASMD) simulations; and then, the uridine derivatives with possibly highly inhibitory activity were designed. The result of CMD showed that more water-mediated H-bonds and lower binding free energy both explained higher recognition ability and transported efficiency of hCNT3. While during the ASMD simulation, nucleoside transport process involved the significant side-chain flip of residues F321 and Q142, a typical substrate-induced conformational change. By considering electronegativity, atomic radius, functional group and key H-bonds factors, 25 novel uridine derivatives were constructed. Subsequently, the receptor-ligand binding free energy was predicted by solvated interaction energy (SIE) method to determine the inhibitor c8 with the best potential performance. This work not only revealed molecular recognition and release mechanism of uridine with hCNT3, but also designed a series of uridine derivatives to obtain lead compounds with potential high activity.

Specifically Targeting Mtb Cell-Wall and TMM Transporter: The Development of MmpL3 Inhibitors.

Tuberculosis (TB) remains a serious threat to whole human health. In particular, the drug resistance of Mycobacterium tuberculosis (Mtb) has become a huge challenge in clinical medicine, and it is extremely urgent to develop effective inhibitors with novel structures and mechanisms. Belonging to the Resistance, Nodulation and Division (RND) superfamily, Mycobacterial membrane proteins Large 3 (MmpL3) is mainly responsible for transporting mycolic acid outside cell membrane to form cell wall, and plays critical roles in iron acquisition which is vital to the survival of Mtb. As a potential Mtb target in recent years, its inhibitor research has attracted wide attention. A series of inhibitors (such as SQ109, AU1235, BM212, etc.) through experimental screening have been reported in succession, especially SQ109 has entered the clinical stage. In this paper, the structural biology information of target MmpL3 was summarized, and the structure-activity relationship (SAR) of inhibitors reported in recent years and their inhibitory mechanism both were reviewed, aiming to provide help for the rational design of MmpL3 inhibitors in the future.

Classification and Design of HIV-1 Integrase Inhibitors Based on Machine Learning.

A key enzyme in human immunodeficiency virus type 1 (HIV-1) life cycle, integrase (IN) aids the integration of viral DNA into the host DNA, which has become an ideal target for the development of anti-HIV drugs. A total of 1785 potential HIV-1 IN inhibitors were collected from the databases of ChEMBL, Binding Database, DrugBank, and PubMed, as well as from 40 references. The database was divided into the training set and test set by random sampling. By exploring the correlation between molecular descriptors and inhibitory activity, it is found that the classification and specific activity data of inhibitors can be more accurately predicted by the combination of molecular descriptors and molecular fingerprints. The calculation of molecular fingerprint descriptor provides the additional substructure information to improve the prediction ability. Based on the training set, two machine learning methods, the recursive partition (RP) and naive Bayes (NB) models, were used to build the classifiers of HIV-1 IN inhibitors. Through the test set verification, the RP technique accurately predicted 82.5% inhibitors and 86.3% noninhibitors. The NB model predicted 88.3% inhibitors and 87.2% noninhibitors with correlation coefficient of 85.2%. The results show that the prediction performance of NB model is slightly better than that of RP, and the key molecular segments are also obtained. Additionally, CoMFA and CoMSIA models with good activity prediction ability both were constructed by exploring the structure-activity relationship, which is helpful for the design and optimization of HIV-1 IN inhibitors.

Concepts and Application of DNA Origami and DNA Self-Assembly: A Systematic Review.

With the arrival of the post-Moore Era, the development of traditional silicon-based computers has reached the limit, and it is urgent to develop new computing technology to meet the needs of science and life. DNA computing has become an essential branch and research hotspot of new computer technology because of its powerful parallel computing capability and excellent data storage capability. Due to good biocompatibility and programmability properties, DNA molecules have been widely used to construct novel self-assembled structures. In this review, DNA origami is briefly introduced firstly. Then, the applications of DNA self-assembly in material physics, biogenetics, medicine, and other fields are described in detail, which will aid the development of DNA computational model in the future.

Efficient whole-cell catalysis for 5-aminovalerate production from L-lysine by using engineered Escherichia coli with ethanol pretreatment.

Microorganisms can utilize biomass to produce valuable chemicals, showing sustainable, renewable and economic advantages compared with traditional chemical synthesis. As a potential five-carbon platform polymer monomer, 5-aminovalerate has been widely used in industrial fields such as clothes and disposable goods. Here we establish an efficient whole-cell catalysis for 5-aminovalerate production with ethanol pretreatment. In this study, the metabolic pathway from L-lysine to 5-aminovalerate was constructed at the cellular level by introducing L-lysine α-oxidase. The newly produced H2O2 and added ethanol both are toxic to the cells, obviously inhibiting their growth. Here, a promising strategy of whole-cell catalysis with ethanol pretreatment is proposed, which greatly improves the yield of 5-aminovalerate. Subsequently, the effects of ethanol pretreatment, substrate concentration, reaction temperature, pH value, metal ion additions and hydrogen peroxide addition on the whole-cell biocatalytic efficiency were investigated. Using 100 g/L of L-lysine hydrochloride as raw material, 50.62 g/L of 5-aminovalerate could be excellently produced via fed-batch bioconversion with the yield of 0.84 mol/mol. The results show that a fast, environmentally friendly and efficient production of 5-aminovalerate was established after introducing the engineered whole-cell biocatalysts. This strategy, combined with ethanol pretreatment, can not only greatly enhance the yield of 5-aminovalerate but also be applied to the biosynthesis of other valuable chemicals.

The Advances of the Structure and Function of Indoleamine 2, 3- dioxygenase 1 and Its Inhibitors.

Indoleamine 2, 3-dioxygenase 1 (IDO1) is the only rate-limiting enzyme outside the liver that catalyzes the oxidation and cracking of indole rings in the tryptophan along the kynurenine pathway (KP). The overactivation of IDO1 is closely related to the pathogenesis of various human immune and neurological diseases. As an important target for the treatment of many human serious diseases, including malignant tumors, the development of IDO1 inhibitors is of great practical significance. In this work, the structure and function of IDO1 both are summarized from the aspects of the signal pathway, catalytic mechanism, structural biology, and so on. Moreover, the current development status of IDO1 inhibitors is also systematically reviewed, which provides assistance for anti-cancer drug design based on the structure of receptors.

Inhibition Mechanism of Indoleamine 2, 3-Dioxygenase 1 (IDO1) by Amidoxime Derivatives and Its Revelation in Drug Design: Comparative Molecular Dynamics Simulations.

For cancer treatment, in addition to the three standard therapies of surgery, chemotherapy, and radiotherapy, immunotherapy has become the fourth internationally-recognized alternative treatment. Indoleamine 2, 3-dioxygenase 1 (IDO1) catalyzes the conversion of tryptophan to kynurenine causing lysine depletion, which is an important target in the research and development of anticancer drugs. Epacadostat (INCB024360) is currently one of the most potent IDO1 inhibitors, nevertheless its inhibition mechanism still remains elusive. In this work, comparative molecular dynamics simulations were performed to reveal that the high inhibitory activity of INCB024360 mainly comes from two aspects: disturbing the ligand delivery tunnel and then preventing small molecules such as oxygen and water molecules from accessing the active site, as well as hindering the shuttle of substrate tryptophan with product kynurenine through the heme binding pocket. The scanning of key residues showed that L234 and R231 residues both were crucial to the catalytic activity of IDO1. With the association with INCB024360, L234 forms a stable hydrogen bond with G262, which significantly affects the spatial position of G262-A264 loop and then greatly disturbs the orderliness of ligand delivery tunnel. In addition, the cleavage of hydrogen bond between G380 and R231 increases the mobility of the GTGG conserved region, leading to the closure of the substrate tryptophan channel. This work provides new ideas for understanding action mechanism of amidoxime derivatives, improving its inhibitor activity and developing novel inhibitors of IDO1.