Computational Insights into SARS-CoV-2 Main Protease Mutations and Nirmatrelvir Efficacy: The Effects of P132H and P132H-A173V.

Nirmatrelvir, a pivotal component of the oral antiviral Paxlovid for COVID-19, targets the SARS-CoV-2 main protease (Mpro) as a covalent inhibitor. Here, we employed combined computational methods to explore how the prevalent Omicron variant mutation P132H, alone and in combination with A173V (P132H-A173V), affects nirmatrelvir's efficacy. Our findings suggest that P132H enhances the noncovalent binding affinity of Mpro for nirmatrelvir, whereas P132H-A173V diminishes it. Although both mutants catalyze the rate-limiting step more efficiently than the wild-type (WT) Mpro, P132H slows the overall rate of covalent bond formation, whereas P132H-A173V accelerates it. Comprehensive analysis of noncovalent and covalent contributions to the overall binding free energy of the covalent complex suggests that P132H likely enhances Mpro sensitivity to nirmatrelvir, while P132H-A173V may confer resistance. Per-residue decompositions of the binding and activation free energies pinpoint key residues that significantly affect the binding affinity and reaction rates, revealing how the mutations modulate these effects. The mutation-induced conformational perturbations alter drug-protein local contact intensities and the electrostatic preorganization of the protein, affecting noncovalent binding affinity and the stability of key reaction states, respectively. Our findings inform the mechanisms of nirmatrelvir resistance and sensitivity, facilitating improved drug design and the detection of resistant strains.

Identification of and Mechanistic Insights into SARS-CoV-2 Main Protease Non-Covalent Inhibitors: An In-Silico Study.

The indispensable role of the SARS-CoV-2 main protease (Mpro) in the viral replication cycle and its dissimilarity to human proteases make Mpro a promising drug target. In order to identify the non-covalent Mpro inhibitors, we performed a comprehensive study using a combined computational strategy. We first screened the ZINC purchasable compound database using the pharmacophore model generated from the reference crystal structure of Mpro complexed with the inhibitor ML188. The hit compounds were then filtered by molecular docking and predicted parameters of drug-likeness and pharmacokinetics. The final molecular dynamics (MD) simulations identified three effective candidate inhibitors (ECIs) capable of maintaining binding within the substrate-binding cavity of Mpro. We further performed comparative analyses of the reference and effective complexes in terms of dynamics, thermodynamics, binding free energy (BFE), and interaction energies and modes. The results reveal that, when compared to the inter-molecular electrostatic forces/interactions, the inter-molecular van der Waals (vdW) forces/interactions are far more important in maintaining the association and determining the high affinity. Given the un-favorable effects of the inter-molecular electrostatic interactions-association destabilization by the competitive hydrogen bond (HB) interactions and the reduced binding affinity arising from the un-compensable increase in the electrostatic desolvation penalty-we suggest that enhancing the inter-molecular vdW interactions while avoiding introducing the deeply buried HBs may be a promising strategy in future inhibitor optimization.

Amitosis as a strategy of cell division-Insight from the proliferation of Tetrahymena thermophila macronuclei.

Cell division is a necessity of life which can be either mitotic or amitotic. While both are fundamental, amitosis is sometimes considered a relic of little importance in biology. Nevertheless, eukaryotes often have polyploid cells, including cancer cells, which may divide amitotically. To understand how amitosis ensures the completion of cell division, we turn to the macronuclei of ciliates. The grand scheme governing the proliferation of the macronuclei of ciliate cells, which involves chromosomal replication and amitosis, is currently unknown, which is crucial for developing population genetics model of ciliate populations. Using a novel model that encompasses a wide range of mechanisms together with experimental data of the composition of mating types at different stages derived from a single karyonide of Tetrahymena thermophila, we show that the chromosomal replication of the macronucleus has a strong head-start effect, with only about five copies of chromosomes replicated at a time and persistent reuse of the chromosomes involved in the early replication. Furthermore the fission of a fully grown macronucleus is non-random with regard to chromosome composition, with a strong tendency to push chromosomes and their replications to the same daughter cell.

RBD-Modified Bacterial Vesicles Elicited Potential Protective Immunity against SARS-CoV-2.

The disease caused by SARS-CoV-2 infection threatens human health. In this study, we used high-pressure homogenization technology not only to efficiently drive the bacterial membrane to produce artificial vesicles but also to force the fusion protein ClyA-receptor binding domain (RBD) to pass through gaps in the bacterial membrane to increase the contact between ClyA-RBD and the membrane. Therefore, the load of ClyA-RBD on the membrane is substantially increased. Using this technology, we constructed a "ring-like" bacterial biomimetic vesicle (BBV) loaded with polymerized RBD (RBD-BBV). RBD-BBVs injected subcutaneously can accumulate in lymph nodes, promote antigen uptake and processing, and elicit SARS-CoV-2-specific humoral and cellular immune responses in mice. In conclusion, we evaluated the potential of this novel bacterial vesicle as a vaccine delivery system and provided a new idea for the development of SARS-CoV-2 vaccines.

Exploring the Cold-Adaptation Mechanism of Serine Hydroxymethyltransferase by Comparative Molecular Dynamics Simulations.

Cold-adapted enzymes feature a lower thermostability and higher catalytic activity compared to their warm-active homologues, which are considered as a consequence of increased flexibility of their molecular structures. The complexity of the (thermo)stability-flexibility-activity relationship makes it difficult to define the strategies and formulate a general theory for enzyme cold adaptation. Here, the psychrophilic serine hydroxymethyltransferase (pSHMT) from Psychromonas ingrahamii and its mesophilic counterpart, mSHMT from Escherichia coli, were subjected to µs-scale multiple-replica molecular dynamics (MD) simulations to explore the cold-adaptation mechanism of the dimeric SHMT. The comparative analyses of MD trajectories reveal that pSHMT exhibits larger structural fluctuations and inter-monomer positional movements, a higher global flexibility, and considerably enhanced local flexibility involving the surface loops and active sites. The largest-amplitude motion mode of pSHMT describes the trends of inter-monomer dissociation and enlargement of the active-site cavity, whereas that of mSHMT characterizes the opposite trends. Based on the comparison of the calculated structural parameters and constructed free energy landscapes (FELs) between the two enzymes, we discuss in-depth the physicochemical principles underlying the stability-flexibility-activity relationships and conclude that (i) pSHMT adopts the global-flexibility mechanism to adapt to the cold environment and, (ii) optimizing the protein-solvent interactions and loosening the inter-monomer association are the main strategies for pSHMT to enhance its flexibility.

Methylation-driven model for analysis of dinucleotide evolution in genomes.

BACKGROUND: CpGs, the major methylation sites in vertebrate genomes, exhibit a high mutation rate from the methylated form of CpG to TpG/CpA and, therefore, influence the evolution of genome composition. However, the quantitative effects of CpG to TpG/CpA mutations on the evolution of genome composition in terms of the dinucleotide frequencies/proportions remain poorly understood. RESULTS: Based on the neutral theory of molecular evolution, we propose a methylation-driven model (MDM) that allows predicting the changes in frequencies/proportions of the 16 dinucleotides and in the GC content of a genome given the known number of CpG to TpG/CpA mutations. The application of MDM to the 10 published vertebrate genomes shows that, for most of the 16 dinucleotides and the GC content, a good consistency is achieved between the predicted and observed trends of changes in the frequencies and content relative to the assumed initial values, and that the model performs better on the mammalian genomes than it does on the lower-vertebrate genomes. The model's performance depends on the genome composition characteristics, the assumed initial state of the genome, and the estimated parameters, one or more of which are responsible for the different application effects on the mammalian and lower-vertebrate genomes and for the large deviations of the predicted frequencies of a few dinucleotides from their observed frequencies. CONCLUSIONS: Despite certain limitations of the current model, the successful application to the higher-vertebrate (mammalian) genomes witnesses its potential for facilitating studies aimed at understanding the role of methylation in driving the evolution of genome dinucleotide composition.

Molecular dynamics simulations reveal distinct differences in conformational dynamics and thermodynamics between the unliganded and CD4-bound states of HIV-1 gp120.

The entry of human immunodeficiency virus type I (HIV-1) into host cells is initiated by binding to the cell-surface receptor CD4, which induces a conformational transition of the envelope (Env) glycoprotein gp120 from the closed, unliganded state to the open, CD4-bound state. Despite many available structures in these two states, detailed aspects on the dynamics and thermodynamics of gp120 remain elusive. Here, we performed microsecond-scale (µs-scale) multiple-replica molecular dynamics (MD) simulations to explore the differences in the conformational dynamics, protein motions, and thermodynamics between the unliganded and CD4-bound/complexed forms of gp120. Comparative analyses of MD trajectories reveal that CD4 binding promotes the structural deviations/changes and conformational flexibility, loosens the structural packing, and complicates the molecular motions of gp120. Comparison of the constructed free energy landscapes (FELs) reveals that the CD4-complexed gp120 has more conformational substates, larger conformational entropy, and lower thermostability than the unliganded form. Therefore, the unliganded conformation represents a structurally and energetically stable "ground state" for the full-length gp120. The observed great increase in the mobility of V1/V2 and V3 along with their more versatile movement directions in the CD4-bound gp120 compared to the unliganded form suggests that their orientations with respect to each other and to the structural core determine the differences in the conformational dynamics and thermodynamics between the two gp120 forms. The results presented here provide a basis by which to better understand the functional and immunological properties of gp120 and, furthermore, to deploy appropriate strategies for the development of anti-HIV-1 drugs or vaccines.

New Insight into Mechanisms of Protein Adaptation to High Temperatures: A Comparative Molecular Dynamics Simulation Study of Thermophilic and Mesophilic Subtilisin-Like Serine Proteases.

In high-temperature environments, thermophilic proteins must possess enhanced thermal stability in order to maintain their normal biological functions. However, the physicochemical basis of the structural stability of thermophilic proteins at high temperatures remains elusive. In this study, we performed comparative molecular dynamics simulations on thermophilic serine protease (THM) and its homologous mesophilic counterpart (PRK). The comparative analyses of dynamic structural and geometrical properties suggested that THM adopted a more compact conformation and exhibited more intramolecular interactions and lower global flexibility than PRK, which could be in favor of its thermal stability in high-temperature environments. Comparison between protein solvent interactions and the hydrophobicity of these two forms of serine proteases showed that THM had more burial of nonpolar areas, and less protein solvent hydrogen bonds (HBs), indicating that solvent entropy maximization and mobility may play a significant role in THM's adaption to high temperature environments. The constructed funnel-like free energy landscape (FEL) revealed that, in comparison to PRK, THM had a relatively flat and narrow free energy surface, and a lower minimum free energy level, suggesting that the thermophilic form had lower conformational diversity and flexibility. Combining the FEL theory and our simulation results, we conclude that the solvent (entropy force) plays a significant role in protein adaption at high temperatures.

Effects of CD4 Binding on Conformational Dynamics, Molecular Motions, and Thermodynamics of HIV-1 gp120.

Human immunodeficiency virus type-1 (HIV-1) infection is triggered by its envelope (Env) glycoprotein gp120 binding to the host-cell receptor CD4. Although structures of Env/gp120 in the liganded state are known, detailed information about dynamics of the liganded gp120 has remained elusive. Two structural models, the CD4-free gp120 and the gp120-CD4 complex, were subjected to µs-scale multiple-replica molecular dynamics (MD) simulations to probe the effects of CD4 binding on the conformational dynamics, molecular motions, and thermodynamics of gp120. Comparative analyses of MD trajectories in terms of structural deviation and conformational flexibility reveal that CD4 binding effectively suppresses the overall conformational fluctuations of gp120. Despite the largest fluctuation amplitude of the V1/V2 region in both forms of gp120, the presence of CD4 prevents it from approaching the gp120 core. Comparison of the constructed free energy landscapes (FELs) shows that CD4 binding reduces the conformational entropy and conformational diversity while enhancing the stability of gp120. Further comparison of the representative structures extracted from free energy basins/minima of FELs reveals that CD4 binding weakens the reorientation ability of V1/V2 and hence hinders gp120 from transitioning out of the liganded state to the unliganded state. Therefore, locking gp120 conformation via restraining V1/V2 reorientation with small molecules seems to be a promising strategy to control HIV-1 infection. Our computer simulation results support the conformational selection mechanism for CD4 binding to gp120 and facilitate the understanding of HIV-1 immune evasion mechanisms.

Suppression of MIF-induced neuronal apoptosis may underlie the therapeutic effects of effective components of Fufang Danshen in the treatment of Alzheimer's disease.

Fufang Danshen (FFDS or Compound Danshen) consists of three Chinese herbs Danshen (Salviae miltiorrhizae radix et rhizome), Sanqi (Notoginseng radix et rhizome) and Tianranbingpian (Borneolum, or D-borneol), which has been show to significantly improve the function of the nervous system and brain metabolism. In this study we explored the possible mechanisms underlying the therapeutic effects of the combination of the effective components of FFDS (Tan IIA, NG-R1 and Borneol) in the treatment of Alzheimer's disease (AD) based on network pharmacology. We firstly constructed AD-related FFDS component protein interaction networks, and revealed that macrophage migration inhibitory factor (MIF) might regulate neuronal apoptosis through Bad in the progression of AD. Then we investigated the apoptosis-inducing effects of MIF and the impact of the effective components of FFDS in human neuroblastoma SH-SY5Y cells. We observed the characteristics of a "Pendular state" of MIF, where MIF (8 ng/mL) increased the ratio of p-Bad/Bad by activating Akt and the IKKα/ß signaling pathway to assure cell survival, whereas MIF (50 ng/mL) up-regulated the expression of Bad to trigger apoptosis of SH-SY5Y cells. MIF displayed neurotoxicity similar to Aß1-42, which was associated with the MIF-induced increased expression of Bad. Application of the FFDS composite solution significantly decreased the expression levels of Bad, suppressed MIF-induced apoptosis in SH-SY5Y cells. In a D-galactose- and AlCl3-induced AD mouse model, administration of the FFDS composite solution significantly improved the learning and memory, as well as neuronal morphology, and decreased the serum levels of INF-γ. Therefore, the FFDS composite solution exerts neuroprotective effects through down-regulating the level of Bad stimulated by MIF.

Effect of the Solvent Temperatures on Dynamics of Serine Protease Proteinase K.

To obtain detailed information about the effect of the solvent temperatures on protein dynamics, multiple long molecular dynamics (MD) simulations of serine protease proteinase K with the solute and solvent coupled to different temperatures (either 300 or 180 K) have been performed. Comparative analyses demonstrate that the internal flexibility and mobility of proteinase K are strongly dependent on the solvent temperatures but weakly on the protein temperatures. The constructed free energy landscapes (FELs) at the high solvent temperatures exhibit a more rugged surface, broader spanning range, and higher minimum free energy level than do those at the low solvent temperatures. Comparison between the dynamic hydrogen bond (HB) numbers reveals that the high solvent temperatures intensify the competitive HB interactions between water molecules and protein surface atoms, and this in turn exacerbates the competitive HB interactions between protein internal atoms, thus enhancing the conformational flexibility and facilitating the collective motions of the protein. A refined FEL model was proposed to explain the role of the solvent mobility in facilitating the cascade amplification of microscopic motions of atoms and atomic groups into the global collective motions of the protein.

Insights into Protein-Ligand Interactions: Mechanisms, Models, and Methods.

Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein-ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein-ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models--the "lock-and-key", "induced fit", and "conformational selection"--are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein-ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed.

Mechanistic Origin of Different Binding Affinities of SARS-CoV and SARS-CoV-2 Spike RBDs to Human ACE2.

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (RBDCoV2) has a higher binding affinity to the human receptor angiotensin-converting enzyme 2 (ACE2) than the SARS-CoV RBD (RBDCoV). Here, we performed molecular dynamics (MD) simulations, binding free energy (BFE) calculations, and interface residue contact network (IRCN) analysis to explore the mechanistic origin of different ACE2-binding affinities of the two RBDs. The results demonstrate that, when compared to the RBDCoV2-ACE2 complex, RBDCoV-ACE2 features enhanced dynamicsand inter-protein positional movements and increased conformational entropy and conformational diversity. Although the inter-protein electrostatic attractive interactions are the primary determinant for the high ACE2-binding affinities of both RBDs, the significantly enhanced electrostatic attractive interactions between ACE2 and RBDCoV2 determine the higher ACE2-binding affinity of RBDCoV2 than of RBDCoV. Comprehensive comparative analyses of the residue BFE components and IRCNs between the two complexes reveal that it is the residue changes at the RBD interface that lead to the overall stronger inter-protein electrostatic attractive force in RBDCoV2-ACE2, which not only tightens the interface packing and suppresses the dynamics of RBDCoV2-ACE2, but also enhances the ACE2-binding affinity of RBDCoV2. Since the RBD residue changes involving gain/loss of the positively/negatively charged residues can greatly enhance the binding affinity, special attention should be paid to the SARS-CoV-2 variants carrying such mutations, particularly those near or at the binding interfaces with the potential to form hydrogen bonds and/or salt bridges with ACE2.

Fast cross-linking by DOPA2 promotes the capturing of a stereospecific protein complex over nonspecific encounter complexes.

Transient and weak protein-protein interactions are essential to many biochemical reactions, yet are technically challenging to study. Chemical cross-linking of proteins coupled with mass spectrometry analysis (CXMS) provides a powerful tool in the analysis of such interactions. Central to this technology are chemical cross-linkers. Here, using two transient heterodimeric complexes EIN/HPr and EIIAGlc/EIIBGlc as our model systems, we evaluated the effects of two amine-specific homo-bifunctional cross-linkers with different reactivities. We showed previously that DOPA2 (di-ortho-phthalaldehyde with a di-ethylene glycol spacer arm) cross-links proteins 60-120 times faster than DSS (disuccinimidyl suberate). We found that though most of the intermolecular cross-links of either cross-linker are consistent with the encounter complexes (ECs), an ensemble of short-lived binding intermediates, more DOPA2 intermolecular cross-links could be assigned to the stereospecific complex (SC), the final lowest-energy conformational state for the two interacting proteins. Our finding suggests that faster cross-linking captures the SC more effectively and cross-linkers of different reactivities potentially probe protein-protein interaction dynamics across multiple timescales.

Characterization of protein unfolding by fast cross-linking mass spectrometry using di-ortho-phthalaldehyde cross-linkers.

Chemical cross-linking of proteins coupled with mass spectrometry is widely used in protein structural analysis. In this study we develop a class of non-hydrolyzable amine-selective di-ortho-phthalaldehyde (DOPA) cross-linkers, one of which is called DOPA2. Cross-linking of proteins with DOPA2 is 60-120 times faster than that with the N-hydroxysuccinimide ester cross-linker DSS. Compared with DSS cross-links, DOPA2 cross-links show better agreement with the crystal structures of tested proteins. More importantly, DOPA2 has unique advantages when working at low pH, low temperature, or in the presence of denaturants. Using staphylococcal nuclease, bovine serum albumin, and bovine pancreatic ribonuclease A, we demonstrate that DOPA2 cross-linking provides abundant spatial information about the conformations of progressively denatured forms of these proteins. Furthermore, DOPA2 cross-linking allows time-course analysis of protein conformational changes during denaturant-induced unfolding.

A Deep Learning Approach for Predicting Antigenic Variation of Influenza A H3N2.

Modeling antigenic variation in influenza (flu) virus A H3N2 using amino acid sequences is a promising approach for improving the prediction accuracy of immune efficacy of vaccines and increasing the efficiency of vaccine screening. Antigenic drift and antigenic jump/shift, which arise from the accumulation of mutations with small or moderate effects and from a major, abrupt change with large effects on the surface antigen hemagglutinin (HA), respectively, are two types of antigenic variation that facilitate immune evasion of flu virus A and make it challenging to predict the antigenic properties of new viral strains. Despite considerable progress in modeling antigenic variation based on the amino acid sequences, few studies focus on the deep learning framework which could be most suitable to be applied to this task. Here, we propose a novel deep learning approach that incorporates a convolutional neural network (CNN) and bidirectional long-short-term memory (BLSTM) neural network to predict antigenic variation. In this approach, CNN extracts the complex local contexts of amino acids while the BLSTM neural network captures the long-distance sequence information. When compared to the existing methods, our deep learning approach achieves the overall highest prediction performance on the validation dataset, and more encouragingly, it achieves prediction agreements of 99.20% and 96.46% for the strains in the forthcoming year and in the next two years included in an existing set of chronological amino acid sequences, respectively. These results indicate that our deep learning approach is promising to be applied to antigenic variation prediction of flu virus A H3N2.

New exon and accelerated evolution of placental gene Nrk occurred in the ancestral lineage of placental mammals.

INTRODUCTION: The chorioallantoic placenta is a specific organ for placental mammals. However, the adaptive events during its emergence are still poorly investigated. METHODS: We scanned the chromosome X to detect the accelerated evolution in the ancestral lineage of placental mammals, and constructed 3D protein structure models of a candidate by homology modeling. RESULTS: Eight branch-specific accelerated regions were identified. Five of these regions (P=5.61×10-11 ~ 9.03×10-8) are located in the five exons of Nik-related kinase (Nrk), which is essential in placenta development and fetoplacental induction of labor. Nrk belongs to the germinal center kinase-IV subfamily with the overall similar protein structure; however, a new exon emerged in ancestors of placental mammals and its sequence has been conserved since then. Structure modelling of NRK suggests that the accelerated exons and the placental-mammal-specific exon (as a new loop) could change the enzymatic activity and the structure of placental mammal NRK. DISCUSSION: Since the new loop is surrounded by the accelerated protein regions, it is likely that the new loop occurred and shifted the function of NRK, and then the accelerated evolution of Nrk occurred to adapt the structure change caused by the new loop in the ancestral lineage of placental mammals. Overall, this work suggests that the fundamental process of placental development and fetoplacental induction of labor has been targeted by positive Darwinian selection.

Recombination facilitates neofunctionalization of duplicate genes via originalization.

BACKGROUND: Recently originalization was proposed to be an effective way of duplicate-gene preservation, in which recombination provokes the high frequency of original (or wild-type) allele on both duplicated loci. Because the high frequency of wild-type allele might drive the arising and accumulating of advantageous mutation, it is hypothesized that recombination might enlarge the probability of neofunctionalization (Pneo) of duplicate genes. In this article this hypothesis has been tested theoretically. RESULTS: Results show that through originalization recombination might not only shorten mean time to neofunctionalizaiton, but also enlarge Pneo. CONCLUSIONS: Therefore, recombination might facilitate neofunctionalization via originalization. Several extensive applications of these results on genomic evolution have been discussed: 1. Time to nonfunctionalization can be much longer than a few million generations expected before; 2. Homogenization on duplicated loci results from not only gene conversion, but also originalization; 3. Although the rate of advantageous mutation is much small compared with that of degenerative mutation, Pneo cannot be expected to be small.

The Energetic Origin of Different Catalytic Activities in Temperature-Adapted Trypsins.

Psychrophilic enzymes were always observed to have higher catalytic activity (k cat) than their mesophilic homologs at room temperature, while the origin of this phenomenon remains obscure. Here, we used two different temperature-adapted trypsins, the psychrophilic Atlantic cod trypsin (ACT) and the mesophilic bovine trypsin (BT), as a model system to explore the energetic origin of their different catalytic activities using computational methods. The results reproduce the characteristic changing trends in the activation free energy, activation enthalpy, and activation entropy between the psychrophilic and mesophilic enzymes, where, in particular, the slightly decreased activation free energy of ACT is determined by its considerably reduced activation enthalpy rather than by its more negative activation entropy compared to BT. The calculated electrostatic contributions to the solvation free energies in the reactant state/ground sate (RS/GS) and transition state (TS) show that, going from BT to ACT, the TS stabilization has a predominant effect over the RS stabilization on lowering the activation enthalpy of ACT. Comparison between the solvation energy components reveals a more optimized electrostatic preorganization to the TS in ACT, which provides a larger stabilization to the TS through reducing the reorganization energy, thus resulting in the lower activation enthalpy and hence lower activation free energy of ACT. Thus, it can be concluded that it is the difference in the protein electrostatic environment, and hence its different stabilizing effects on the TS, that brings about the different catalytic activities of different temperature-adapted trypsins.

CD4-binding obstacles in conformational transitions and allosteric communications of HIV gp120.

As the only exposed viral protein at the membrane surface of HIV, envelope glycoprotein gp120 is responsible for recognizing host cells and mediating virus-cell membrane fusion. Available structures of gp120 indicate that it exhibits two distinct conformational states, called closed and open states. Although experimental data demonstrates that CD4 binding stabilizes open state of gp120, detailed structural dynamics and kinetics of gp120 during this process remain elusive. Here, two open-state gp120 simulation systems, one without any ligands (ligand-free) and the other complexed with CD4 (CD4-bound), were subjected to microsecond-scale molecular dynamics simulations following the conformational transitions and allosteric pathways of gp120 evaluated by using the Markov state model and a network-based method, respectively. Our results provide an atomic-resolution description of gp120 conformational transitions, suggesting that gp120 is intrinsically dynamic from the open state to closed state, whereas CD4 binding blocks these transitions. Consistent with experimental structures, five metastable conformations with different orientations of the V1/V2 region and V3 loop have been extracted. The binding of CD4 significantly enhances allosteric communications from the CD4-binding site to V3 loop and ß20-21 hairpin, resulting in high-affinity interactions with coreceptors and activation of the conformational transitions switcher, respectively. This study will facilitate the structural understanding of the CD4-binding effects on conformational transitions and allosteric pathways of gp120.