An analysis of the interactions between the Sem-5 SH3 domain and its ligands using molecular dynamics, free energy calculations, and sequence analysis

Through virtual saturation mutagenesis and rational design for superior substrate conversion in engineered d-amino acid oxidase

The d-amino acid oxidase (DAAO) is pivotal in obtaining optically pure l-glufosinate (l-PPT) by converting d-glufosinate (d-PPT) to its deamination product. We screened and designed a Rasamsonia emersonii DAAO (ReDAAO), making it more suitable for oxidizing d-PPT. Using Caver 3.0, we delineated three substrate binding pockets and, via alanine scanning, identified nearby key residues. Pinpointing key residues influencing activity, we applied virtual saturation mutagenesis (VSM), and experimentally validated mutants which reduced substrate binding energy. Analysis of positive mutants revealed elongated side-chain prevalence in substrate binding pocket periphery. Although computer-aided approaches can rapidly identify advantageous mutants and guide further design, the mutations obtained in the first round may not be suitable for combination with other advantageous mutations. Therefore, each round of combination requires reasonable iteration. Employing VSM-assisted screening multiple times and after four rounds of combining mutations, we ultimately obtained a mutant, N53V/F57Q/V94R/V242R, resulting in a mutant with a 5097% increase in enzyme activity compared to the wild type. It provides valuable insights into the structural determinants of enzyme activity and introduces a novel rational design procedure.

Hydrophobic substrate binding pocket remodeling of echinocandin B deacylase based on multi-dimensional rational design

Actinoplanes utahensis deacylase (AAC)-catalyzed deacylation of echinocandin B (ECB) is a promising method for the synthesis of anidulafungin, the newest of the echinocandin antifungal agents. However, the low activity of AAC significantly limits its practical application. In this work, we have devised a multi-dimensional rational design strategy for AAC, conducting separate analyses on the substrate-binding pocket's volume, curvature, and length. Furthermore, we quantitatively analyzed substrate properties, particularly on hydrophilic and hydrophobic. Accordingly, we tailored the linoleic acid-binding pocket of AAC to accommodate the extended long lipid chain of ECB. By fine-tuning the key residues, the resulting AAC mutants can accommodate the ECB lipid chain with a lower curvature binding pocket. The D53A/I55F/G57M/F154L/Q661L mutant (MT) displayed 331 % higher catalytic efficiency than the wild-type (WT) enzyme. The MT product conversion was 94.6 %, reaching the highest reported level. Utilizing a multi-dimensional rational design for a customized mutation strategy of the substrate-binding pocket is an effective approach to enhance the catalytic efficiency of enzymes in handling complicated substrates.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.

Vitamin D3 and its hydroxyderivatives as promising drugs against COVID-19: a computational study

The epidemiologic correlation between the poor prognosis of SARS-CoV-2 infection and vitamin D deficiency has been observed worldwide, however, their molecular mechanisms are not fully understood. In this study, we used combined molecular docking, molecular dynamics simulations and binding free energy analyses to investigate the potentials of vitamin D3 and its hydroxyderivatives as TMPRSS2 inhibitor and to inhibit the SARS-CoV-2 receptor binding domain (RBD) binding to angiotensin-converting enzyme 2 (ACE2), as well as to unveil molecular and structural basis of 1,25(OH)₂D3 capability to inhibit ACE2 and SARS-CoV-2 RBD interactions. The results show that vitamin D3 and its hydroxyderivatives are favorable to bind active site of TMPRSS2 and the binding site(s) between ACE2 and SARS-CoV2-RBD, which indicate that vitamin D3 and its biologically active hydroxyderivatives can serve as TMPRSS2 inhibitor and can inhibit ACE2 binding of SARS-CoV-2 RBD to prevent SARS-CoV-2 entry. Interaction of 1,25(OH)₂D3 with SARS-CoV-2 RBD and ACE2 resulted in the conformation and dynamical motion changes of the binding surfaces between SARS-CoV-2 RBD and ACE2 to interrupt the binding of SARS-CoV-2 RBD with ACE2. The interaction of 1,25(OH)₂D3 with TMPRSS2 also caused the conformational and dynamical motion changes of TMPRSS2, which could affect TMPRSS2 to prime SARS-CoV-2 spike proteins. Our results propose that vitamin D3 and its biologically active hydroxyderivatives are promising drugs or adjuvants in the treatment of COVID-19. Communicated by Ramaswamy H. Sarma.

The role of zinc finger linkers in zinc finger protein binding to DNA

Zinc finger proteins (ZFP) play important roles in cellular processes. The DNA binding region of ZFP consists of 3 zinc finger DNA binding domains connected by amino acid linkers, the sequence TGQKP connects ZF1 and ZF2, and TGEKP connects ZF2 with ZF3. Linkers act to tune the zinc finger protein in the right position to bind its DNA target, the type of amino acid residues and length of linkers reflect on ZF1-ZF2-ZF3 interactions and contribute to the search and recognition process of ZF protein to its DNA target. Linker mutations and the affinity of the resulting mutants to specific and nonspecific DNA targets were studied by MD simulations and MM_GB(PB)SA. The affinity of mutants to DNA varied with type and position of amino acid residue. Mutation of K in TGQKP resulted in loss in affinity due to the loss of positive K interaction with phosphates, mutation of G showed loss in affinity to DNA, WT protein and all linker mutants showed loss in affinity to a nonspecific DNA target, this finding confirms previous reports which interpreted this loss in affinity as due to ZF1 having an anchoring role, and ZF3 playing an explorer role in the binding mechanism. The change in ZFP-DNA affinity with linker mutations is discussed in view of protein structure and role of linker residues in binding.

Vitamin D and lumisterol derivatives can act on liver X receptors (LXRs)

The interactions of derivatives of lumisterol (L3) and vitamin D3 (D3) with liver X receptors (LXRs) were investigated. Molecular docking using crystal structures of the ligand binding domains (LBDs) of LXRα and β revealed high docking scores for L3 and D3 hydroxymetabolites, similar to those of the natural ligands, predicting good binding to the receptor. RNA sequencing of murine dermal fibroblasts stimulated with D3-hydroxyderivatives revealed LXR as the second nuclear receptor pathway for several D3-hydroxyderivatives, including 1,25(OH)2D3. This was validated by their induction of genes downstream of LXR. L3 and D3-derivatives activated an LXR-response element (LXRE)-driven reporter in CHO cells and human keratinocytes, and by enhanced expression of LXR target genes. L3 and D3 derivatives showed high affinity binding to the LBD of the LXRα and β in LanthaScreen TR-FRET LXRα and β coactivator assays. The majority of metabolites functioned as LXRα/β agonists; however, 1,20,25(OH)3D3, 1,25(OH)2D3, 1,20(OH)2D3 and 25(OH)D3 acted as inverse agonists of LXRα, but as agonists of LXRβ. Molecular dynamics simulations for the selected compounds, including 1,25(OH)2D3, 1,20(OH)2D3, 25(OH)D3, 20(OH)D3, 20(OH)L3 and 20,22(OH)2L3, showed different but overlapping interactions with LXRs. Identification of D3 and L3 derivatives as ligands for LXRs suggests a new mechanism of action for these compounds.

Computational analysis of binding free energies, hotspots and the binding mechanism of Bcl-xL/Bcl-2 binding to Bad/Bax

Hierarchical clustering tree of residues providing contributions to system binding based on the binding free energy of specific residues for (A) Bcl-xL systems (B) Bcl-2 systems.

Plant-derived natural polyphenols as potential antiviral drugs against SARS-CoV-2 via RNA-dependent RNA polymerase (RdRp) inhibition: an in-silico analysis

The sudden outburst of Coronavirus disease (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) poses a massive threat to global public health. Currently, no therapeutic drug or vaccine exists to treat COVID-19. Due to the time taking process of new drug development, drug repurposing might be the only viable solution to tackle COVID-19. RNA-dependent RNA polymerase (RdRp) catalyzes SARS-CoV-2 RNA replication and hence, is an obvious target for antiviral drug design. Interestingly, several plant-derived polyphenols effectively inhibit the RdRp of other RNA viruses. More importantly, polyphenols have been used as dietary supplementations for a long time and played beneficial roles in immune homeostasis. We were curious to study the binding of polyphenols with SARS-CoV-2 RdRp and assess their potential to treat COVID-19. Herein, we made a library of polyphenols that have shown substantial therapeutic effects against various diseases. They were successfully docked in the catalytic pocket of RdRp. The investigation reveals that EGCG, theaflavin (TF1), theaflavin-3'-O-gallate (TF2a), theaflavin-3'-gallate (TF2b), theaflavin 3,3'-digallate (TF3), hesperidin, quercetagetin, and myricetin strongly bind to the active site of RdRp. Further, a 150-ns molecular dynamic simulation revealed that EGCG, TF2a, TF2b, TF3 result in highly stable bound conformations with RdRp. The binding free energy components calculated by the MM-PBSA also confirm the stability of the complexes. We also performed a detailed analysis of ADME prediction, toxicity prediction, and target analysis for their druggability. Overall, our results suggest that EGCG, TF2a, TF2b, TF3 can inhibit RdRp and represent an effective therapy for COVID-19.Communicated by Ramaswamy H. Sarma.

Sars-cov-2 host entry and replication inhibitors from Indian ginseng: an in-silico approach

COVID-19 has ravaged the world and is the greatest of pandemics in modern human history, in the absence of treatment or vaccine, the mortality and morbidity rates are very high. The present investigation identifies potential leads from the plant Withania somnifera (Indian ginseng), a well-known antiviral, immunomodulatory, anti-inflammatory and a potent antioxidant plant, using molecular docking and dynamics studies. Two different protein targets of SARS-CoV-2 namely NSP15 endoribonuclease and receptor binding domain of prefusion spike protein from SARS-CoV-2 were targeted. Molecular docking studies suggested Withanoside X and Quercetin glucoside from W. somnifera have favorable interactions at the binding site of selected proteins, that is, 6W01 and 6M0J. The top-ranked phytochemicals from docking studies, subjected to 100 ns molecular dynamics (MD) suggested Withanoside X with the highest binding free energy (ΔG_bind = -89.42 kcal/mol) as the most promising inhibitor. During MD studies, the molecule optimizes its conformation for better fitting with the receptor active site justifying the high binding affinity. Based on proven therapeutic, that is, immunomodulatory, antioxidant and anti-inflammatory roles and plausible potential against n-CoV-2 proteins, Indian ginseng could be one of the alternatives as an antiviral agent in the treatment of COVID 19. Communicated by Ramaswamy H. Sarma.

Entropy Hotspots for the Binding of Intrinsically Disordered Ligands to a Receptor Domain

Proline-rich motifs (PRMs) are widely used for mediating protein-protein interactions with weak binding affinities. Because they are intrinsically disordered when unbound, conformational entropy plays a significant role for the binding. However, residue-level differences of the entropic contribution in the binding of different ligands remain not well understood. We use all-atom molecular dynamics simulation and the maximal information spanning tree formalism to analyze conformational entropy associated with the binding of two PRMs, one from the Abl kinase and the other from the nonstructural protein 1 of the 1918 Spanish influenza A virus, to the N-terminal SH3 (nSH3) domain of the CrkII protein. Side chains of the stably folded nSH3 experience more entropy change upon ligand binding than the backbone, whereas PRMs involve comparable but heterogeneous entropy changes among the backbone and side chains. In nSH3, two conserved nonpolar residues forming contacts with the PRM experience the largest side-chain entropy loss. In contrast, the C-terminal charged residues of PRMs that form polar contacts with nSH3 experience the greatest side-chain entropy loss, although their "fuzzy" nature is attributable to the backbone that remains relatively flexible. Thus, residues that form high-occupancy contacts between nSH3 and PRM do not reciprocally contribute to entropy loss. Furthermore, certain surface residues of nSH3 distal to the interface with PRMs gain entropy, indicating a nonlocal effect of ligand binding. Comparing between the PRMs from cAbl and nonstructural protein 1, the latter involves a larger side-chain entropy loss and forms more contacts with nSH3. Consistent with experiments, this indicates stronger binding of the viral ligand at the expense of losing the flexibility of side chains, whereas the backbone experiences less entropy loss. The entropy "hotspots" as identified in this study will be important for tuning the binding affinity of various ligands to a receptor.

Improving the performance of the MM/PBSA and MM/GBSA methods in recognizing the native structure of the Bcl-2 family using the interaction entropy method

Correct discrimination of native structure plays an important role in drug design. IE method significantly improves the performance of MM/PB(GB)SA method in discriminating native and decoy structures in protein–ligand/protein systems of Bcl-2 family.

Revealing binding selectivity of ligands toward murine double minute 2 and murine double minute X based on molecular dynamics simulations and binding free energy calculations

It is well known that the interactions of p53 with murine double minute 2 and murine double minute X, namely MDM2 and MDMX, have been significant targets of efficient anti-cancer drug design. In this study, molecular dynamics (MD) simulations, principal component (PC) analysis and binding free energy calculations are combined to recognize binding selectivity of three ligands to MDM2 and MDMX. The binding free energies were estimated by using molecular mechanics generalized Born surface area (MM-GBSA) method and the obtained results display that the increase in the binding enthalpy of three ligands to MDM2 relative to MDMX mainly drives the binding selectivity of them toward MDM2 and MDMX. The information obtained from PC analysis shows that the associations of ligands exert important impacts on internal dynamics of MDM2 and MDMX. Meanwhile, the calculations of residue-based free energy decomposition not only identify the hot interaction spots of ligands with MDM2 and MDMX, but also show the residues (L54, M53), (Y67, Y66), (V93, V92), (H96, P95), (I99, I98) and (Y100, Y99) in (MDM2, MDMX) are responsible for most contributions to the binding selectivity of three ligands toward MDM2 and MDMX. It is believed that this work can provide useful information for design of highly selective and dual inhibitors targeting MDM2 and MDMX.Communicated by Ramaswamy H. Sarma.

Evaluating the performance of MM/PBSA for binding affinity prediction using class A GPCR crystal structures

The recent expansion of GPCR crystal structures provides the opportunity to assess the performance of structure-based drug design methods for the GPCR superfamily. Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA)-based methods are commonly used for binding affinity prediction, as they provide an intermediate compromise of speed and accuracy between the empirical scoring functions used in docking and more robust free energy perturbation methods. In this study, we systematically assessed the performance of MM/PBSA in predicting experimental binding free energies using twenty Class A GPCR crystal structures and 934 known ligands. Correlations between predicted and experimental binding free energies varied significantly between individual targets, ranging from r = - 0.334 in the inactive-state CB₁ cannabinoid receptor to r = 0.781 in the active-state CB₁ cannabinoid receptor, while average correlation across all twenty targets was relatively poor (r = 0.183). MM/PBSA provided better predictions of binding free energies compared to docking scores in eight out of the twenty GPCR targets while performing worse for four targets. MM/PBSA binding affinity predictions calculated using a single, energy minimized structure provided comparable predictions to sampling from molecular dynamics simulations and may be more efficient when computational cost becomes restrictive. Additionally, we observed that restricting MM/PBSA calculations to ligands with a high degree of structural similarity to the crystal structure ligands improved performance in several cases. In conclusion, while MM/PBSA remains a valuable tool for GPCR structure-based drug design, its performance in predicting the binding free energies of GPCR ligands remains highly system-specific as demonstrated in a subset of twenty Class A GPCRs, and validation of MM/PBSA-based methods for each individual case is recommended before prospective use.

Advances in the Computational Identification of Allosteric Sites and Pathways in Proteins

With the increasing difficulty to develop new drugs and the emergence of resistance to traditional orthosteric-site inhibitors, the search for alternatives is finally approaching the focus on allosteric sites. Allosteric sites offer opportunities to regulate many pharmacologically targeted pathways by inhibition or activation. In addition, allosteric sites tend to be less conserved than the functional site, which may facilitate the design of specific effectors in the protein families for which specific orthosteric inhibitors have proved difficult to design. Furthermore, recent evidence suggests that all proteins might be susceptible of allosteric regulation, increasing the space of druggable targets. Computational identification of allosteric sites has therefore become an active field of research. The problem can be approached from two sides: (1) the identification of allosteric-communication pathways between the functional site and potential allosteric sites and (2) the functional-site-independent identification of allosteric sites. While the first approach tends to be more laborious and thus restricted to a single protein, the second tends to be more amenable to larger-scale analysis, thus providing tools for the two drug discovery scenarios: the analysis of known targets and the screening for new potential targets. Here, I show some basic concepts and methods useful to the identification of allosteric sites and pathways, in line with these two approaches. I describe them in some detail to build a clear framework, at the risk of losing the interest of experts. Examples of recent studies involving these methods are also illustrated, focusing on the techniques rather than on their findings on allosterism.

The impact of interior dielectric constant and entropic change on HIV-1 complex binding free energy prediction

At present, the calculated binding free energy obtained using the molecular mechanics/Poisson-Boltzmann (Generalized-Born) surface area (MM/PB(GB)SA) method is overestimated due to the lack of knowledge of suitable interior dielectric constants in the simulation on the interaction of Human Immunodeficiency Virus (HIV-1) protease systems with inhibitors. Therefore, the impact of different values of the interior dielectric constant and the entropic contribution when using the MM/PB(GB)SA method to calculate the binding free energy was systemically evaluated. Our results show that the use of higher interior dielectric constants (1.4-2.0) can clearly improve the predictive accuracy of the MM/PBSA and MM/GBSA methods, and computational errors are significantly reduced by including the effects of electronic polarization and using a new highly efficient interaction entropy (IE) method to calculate the entropic contribution. The suitable range for the interior dielectric constant is 1.4-1.6 for the MM/PBSA method; within this range, the correlation coefficient fluctuates around 0.84, and the mean absolute error fluctuates around 2 kcal/mol. Similarly, an interior dielectric constant of 1.8-2.0 produces a correlation coefficient of approximately 0.76 when using the MM/GBSA method. In addition, the entropic contribution of each individual residue was further calculated using the IE method to predict hot-spot residues, and the detailed binding mechanisms underlying the interactions of the HIV-1 protease, its inhibitors, and bridging water molecules were investigated. In this study, the use of a higher interior dielectric constant and the IE method can improve the calculation accuracy of the HIV-1 system.

Insight into selective mechanism of class of I-BRD9 inhibitors toward BRD9 based on molecular dynamics simulations

Recently, bromodomain-containing protein 9 (BRD9), 7 (BRD7), and 4 (BRD4) have been potential targets of anticancer drug design. Molecular dynamic simulations followed by molecular mechanics Poisson-Boltzmann surface area calculation were performed to study the selective mechanism of I-BRD9 inhibitor H1B and its derivatives N1D, TVU, and 5V2 toward BRD9 and BRD4. The rank of our calculated binding free energies agrees with that of the experimental data. The results show that binding free energy of H1B to BRD7 is slightly lower than that of H1B to BRD9, and all four inhibitors bind more tightly to BRD9 than to BRD4. Decomposition of binding free energies into individual residues implies that Ile164 and Asn211 in BRD7 and Ile53 and Asn100 in BRD9 play a significant role in the selectivity of H1B toward BRD7 and BRD9. Besides, several key residues Phe44, Ile53, Asn100, Thr104 in BRD9 and Pro82, Lys91, Asn140, Asp144 in BRD4 that are located in the ZA-loop and BC-loop provide significant contributions to binding selectivity of inhibitors to BRD9 and BRD4. This study is expected to provide important theoretical guidance for rational designs of highly selective inhibitors targeting BRD9 and BRD4.

Exploring the Reasons for Decrease in Binding Affinity of HIV-2 Against HIV-1 Protease Complex Using Interaction Entropy Under Polarized Force Field

In this study, the differences of binding patterns between two type HIV (HIV-1 and HIV-2) protease and two inhibitors (darunavir and amprenavir) are analyzed and compared using the newly developed interaction entropy (IE) method for the entropy change calculation combined with the polarized force field. The functional role of protonation states in the two HIV-2 complexes is investigated and our study finds that the protonated OD1 atom of Asp25' in B chain is the optimal choice. Those calculated binding free energies obtained from the polarized force field combined with IE method are significantly consistent with the experimental observed. The bridging water W301 is favorable to the binding of HIV-1 complexes; however, it is unfavorable to the HIV-2 complexes in current study. The volume of pocket, B-factor of Cα atoms and the distance of flap tip in HIV-2 complexes are smaller than that of HIV-1 consistently. These changes may cause localized rearrangement of residues lining their surface and finally result in the different binding mode for the two types HIV. Predicated hot-spot residues (Ala28/Ala28', Ile50/Ile50', and Ile84/Ile84') are nearly same in the four systems. However, the contribution to the free energy of Asp30 residue is more favorable in HIV-1 system than in HIV-2 system. Current study, to some extent, reveals the origin for the decrease in binding affinity of inhibitors against HIV-2 compared with HIV-1 and will provides theoretical guidance for future design of potent dual inhibitors targeting two type HIV protease.

A multistep docking and scoring protocol for congeneric series: Implementation on kinase DFG-out type II inhibitors

AIM

Rescoring of docking-binding poses can significantly improve molecular docking results. Our aim was to evaluate postprocessing docking protocols in order to determine the most suitable methodology for the study of the binding of congeneric compounds to protein kinases.

MATERIALS & METHODS

Diverse ligand-receptor poses generated after docking were submitted to different relaxation protocols. The Molecular Mechanics Poisson-Boltzmann (Generalized Born) Surface Area approach was applied for the evaluation of the binding affinity of complexes obtained. The performance of various Molecular Mechanics Poisson-Boltzmann (Generalized Born) Surface Area methodologies was compared.

RESULTS

The inclusion of a postprocessing protocol after docking enhances the quality of the results, although the best methodology is system dependent.

CONCLUSION

An examination of the interactions established has allowed us to suggest useful modifications for the design of new type II inhibitors.

The R81T mutation in the nicotinic acetylcholine receptor of Aphis gossypii is associated with neonicotinoid insecticide resistance with differential effects for cyano- and nitro-substituted neonicotinoids

The cotton aphid, Aphis gossypii Glover, is one of the most agriculturally important insect pests. Neonicotinoid insecticides and sulfoxaflor have generally shown excellent control of A. gossypii, but these aphids have recently developed resistance against neonicotinoid insecticides. We previously characterized a field-collected A. gossypii Kushima clone that showed higher resistance to nitro-substituted neonicotinoids, such as imidacloprid, than to cyano-substituted neonicotinoids, such as acetamiprid. This Kushima clone harbors the R81T mutation in the nicotinic acetylcholine receptor (nAChR) β1 subunit; this mutation is the source of neonicotinoid insecticide resistance. In the present study, electrophysiological analyses and molecular modeling were employed to investigate the differential effects of the R81T mutation on cyano- and nitro-substituted neonicotinoids and sulfoxaflor. We isolated full-length coding sequences of A. gossypii nAChR α1, α2, and β1 subunits. When co-expressed in Xenopus laevis oocytes with chicken β2 nAChR, A. gossypii α1 evoked inward currents in a concentration-dependent manner in response to acetylcholine (ACh) and showed sensitivity to neonicotinoid and sulfoxaflor. Additionally, the chicken β2 T77R+E79V (equivalent double mutant of R81T) mutation resulted in a lower effect to cyano-substituted neonicotinoids and sulfoxaflor than to nitro-substituted neonicotinoids. Electrophysiological data and nAChR homology modeling analysis suggested that the Kushima clone exhibited different levels of resistance to cyano- and nitro-substituted neonicotinoid insecticides.

Effect of electrostatic polarization and bridging water on CDK2–ligand binding affinities calculated using a highly efficient interaction entropy method

A new highly efficient interaction entropy (IE) method combined with the polarized protein-specific charge (PPC) force field is employed to investigate the interaction mechanism of CDK2–ligand binding and the effect of the bridging water.

Molecular basis of the recognition of FMN by a HAD phosphatase TON_0338

The haloalkaloic acid dehalogenase (HAD) phosphatase from Thermococcus onnurineus NA1 (TON_0338), has phosphatase activity the flavin mono-nucleotide (FMN). The molecular origin and structural motifs for the activity deficiency of double-tryptophan mutant have not been rationalized at atomic resolution. Molecular dynamics (MD) simulations and the molecular mechanics/Generalized-Born surface area (MM/GBSA) free energy calculations were used to explore the effects of mutations on the changes in both structural flexibility and conformational dynamics. The non-polar solvation energy plays an indispensable role in the binding process of TON_0338 and FMN. The tryptophan sandwich structure provides a primary function to anchor FMN and keeps FMN well bound to TON_0338. The double-tryptophan mutation has influences on the secondary structures of TON_0338 and changes the conformation, which would lead to reduced activity of W58A/W61A-FMN binding. The present study provides important insights into the structure-function relationships of TON_0338 protein, which could contribute to further understanding about the HAD phosphatases.

From Binding-Induced Dynamic Effects in SH3 Structures to Evolutionary Conserved Sectors

Src Homology 3 domains are ubiquitous small interaction modules known to act as docking sites and regulatory elements in a wide range of proteins. Prior experimental NMR work on the SH3 domain of Src showed that ligand binding induces long-range dynamic changes consistent with an induced fit mechanism. The identification of the residues that participate in this mechanism produces a chart that allows for the exploration of the regulatory role of such domains in the activity of the encompassing protein. Here we show that a computational approach focusing on the changes in side chain dynamics through ligand binding identifies equivalent long-range effects in the Src SH3 domain. Mutation of a subset of the predicted residues elicits long-range effects on the binding energetics, emphasizing the relevance of these positions in the definition of intramolecular cooperative networks of signal transduction in this domain. We find further support for this mechanism through the analysis of seven other publically available SH3 domain structures of which the sequences represent diverse SH3 classes. By comparing the eight predictions, we find that, in addition to a dynamic pathway that is relatively conserved throughout all SH3 domains, there are dynamic aspects specific to each domain and homologous subgroups. Our work shows for the first time from a structural perspective, which transduction mechanisms are common between a subset of closely related and distal SH3 domains, while at the same time highlighting the differences in signal transduction that make each family member unique. These results resolve the missing link between structural predictions of dynamic changes and the domain sectors recently identified for SH3 domains through sequence analysis.

Small protein domains as Src Homology 3 often act as docking sites and serve as regulatory elements. To understand their role in the regulation of a protein’s activity, one needs to understand how their backbone and sidechain dynamics are affected when binding to peptides. We have therefore computationally analyzed eight different SH3 domain structures, predicting dynamical effects induced by binding through our MCIT approach that has been shown to correlate well with experimental data. We show first that binding the Src SH3 domain triggers a particular cascade of dynamic effects, which are compatible with an induced fit mechanism reported before. We then combined the predictions for the eight SH3 domains into different consensus models, with the aim of analyzing, for the first time from a structural perspective, commonalities and differences in the transduction mechanisms among these SH3 domains. These consensus results are, on one hand, in agreement with the domain sectors recently identified for the entire family of SH3 domains. On the other hand, they reveal also that differences exist between the different subgroups that were studied here, requiring extensive experimental investigations of the importance of these differences for the proteins wherein these SH3 domains can be found.

Zinc finger protein binding to DNA: an energy perspective using molecular dynamics simulation and free energy calculations on mutants of both zinc finger domains and their specific DNA bases

Energy calculations based on MM-GBSA were employed to study various zinc finger protein (ZF) motifs binding to DNA. Mutants of both the DNA bound to their specific amino acids were studied. Calculated energies gave evidence for a relationship between binding energy and affinity of ZF motifs to their sites on DNA. ΔG values were -15.82(12), -3.66(12), and -12.14(11.6) kcal/mol for finger one, finger two, and finger three, respectively. The mutations in the DNA bases reduced the value of the negative energies of binding (maximum value for ΔΔG = 42Kcal/mol for F1 when GCG mutated to GGG, and ΔΔG = 22 kcal/mol for F2, the loss in total energy of binding originated in the loss in electrostatic energies upon mutation (r = .98). The mutations in key amino acids in the ZF motif in positions-1, 2, 3, and 6 showed reduced binding energies to DNA with correlation coefficients between total free energy and electrostatic was .99 and with Van der Waal was .93. Results agree with experimentally found selectivity which showed that Arginine in position-1 is specific to G, while Aspartic acid (D) in position 2 plays a complicated role in binding. There is a correlation between the MD calculated free energies of binding and those obtained experimentally for prepared ZF motifs bound to triplet bases in other reports (), our results may help in the design of ZF motifs based on the established recognition codes based on energies and contributing energies to the total energy.

Probing Difference in Binding Modes of Inhibitors to MDMX by Molecular Dynamics Simulations and Different Free Energy Methods

The p53-MDMX interaction has attracted extensive attention of anti-cancer drug development in recent years. This current work adopted molecular dynamics (MD) simulations and cross-correlation analysis to investigate conformation changes of MDMX caused by inhibitor bindings. The obtained information indicates that the binding cleft of MDMX undergoes a large conformational change and the dynamic behavior of residues obviously change by the presence of different structural inhibitors. Two different methods of binding free energy predictions were employed to carry out a comparable insight into binding mechanisms of four inhibitors PMI, pDI, WK23 and WW8 to MDMX. The data show that the main factor controlling the inhibitor bindings to MDMX arises from van der Waals interactions. The binding free energies were further divided into contribution of each residue and the derived information gives a conclusion that the hydrophobic interactions, such as CH-CH, CH-π and π-π interactions, are responsible for the inhibitor associations with MDMX.

Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set

By using different evaluation strategies, we systemically evaluated the performance of Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodologies based on more than 1800 protein-ligand crystal structures in the PDBbind database. The results can be summarized as follows: (1) for the one-protein-family/one-binding-ligand case which represents the unbiased protein-ligand complex sampling, both MM/GBSA and MM/PBSA methodologies achieve approximately equal accuracies at the interior dielectric constant of 4 (with rp = 0.408 ± 0.006 of MM/GBSA and rp = 0.388 ± 0.006 of MM/PBSA based on the minimized structures); while for the total dataset (1864 crystal structures), the overall best Pearson correlation coefficient (rp = 0.579 ± 0.002) based on MM/GBSA is better than that of MM/PBSA (rp = 0.491 ± 0.003), indicating that biased sampling may significantly affect the accuracy of the predicted result (some protein families contain too many instances and can bias the overall predicted accuracy). Therefore, family based classification is needed to evaluate the two methodologies; (2) the prediction accuracies of MM/GBSA and MM/PBSA for different protein families are quite different with rp ranging from 0 to 0.9, whereas the correlation and ranking scores (an averaged rp/rs over a list of protein folds and also representing the unbiased sampling) given by MM/PBSA (rp-score = 0.506 ± 0.050 and rs-score = 0.481 ± 0.052) are comparable to those given by MM/GBSA (rp-score = 0.516 ± 0.047 and rs-score = 0.463 ± 0.047) at the fold family level; (3) for the overall prediction accuracies, molecular dynamics (MD) simulation may not be quite necessary for MM/GBSA (rp-minimized = 0.579 ± 0.002 and rp-1ns = 0.564 ± 0.002), but is needed for MM/PBSA (rp-minimized = 0.412 ± 0.003 and rp-1ns = 0.491 ± 0.003). However, for the individual systems, whether to use MD simulation is depended. (4) both MM/GBSA and MM/PBSA may be unable to give successful predictions for the ligands with high formal charges, with the Pearson correlation coefficient ranging from 0.621 ± 0.003 (neutral ligands) to 0.125 ± 0.142 (ligands with a formal charge of 5). Therefore, it can be summarized that, although MM/GBSA and MM/PBSA perform similarly in the unbiased dataset, for the currently available crystal structures in the PDBbind database, compared with MM/GBSA, which may be used in multi-target comparisons, MM/PBSA is more sensitive to the investigated systems, and may be more suitable for individual-target-level binding free energy ranking. This study may provide useful guidance for the post-processing of docking based studies.

Revealing origin of decrease in potency of darunavir and amprenavir against HIV-2 relative to HIV-1 protease by molecular dynamics simulations

Clinical inhibitors Darunavir (DRV) and Amprenavir (APV) are less effective on HIV-2 protease (PR2) than on HIV-1 protease (PR1). To identify molecular basis associated with the lower inhibition, molecular dynamics (MD) simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations were performed to investigate the effectiveness of the PR1 inhibitors DRV and APV against PR1/PR2. The rank of predicted binding free energies agrees with the experimental determined one. Moreover, our results show that two inhibitors bind less strongly to PR2 than to PR1, again in agreement with the experimental findings. The decrease in binding free energies for PR2 relative to PR1 is found to arise from the reduction of the van der Waals interactions induced by the structural adjustment of the triple mutant V32I, I47V and V82I. This result is further supported by the difference between the van der Waals interactions of inhibitors with each residue in PR2 and in PR1. The results from the principle component analysis suggest that inhibitor binding tends to make the flaps of PR2 close and the one of PR1 open. We expect that this study can theoretically provide significant guidance and dynamics information for the design of potent dual inhibitors targeting PR1/PR2.

Molecular recognition in a diverse set of protein-ligand interactions studied with molecular dynamics simulations and end-point free energy calculations

End-point free energy calculations using MM-GBSA and MM-PBSA provide a detailed understanding of molecular recognition in protein-ligand interactions. The binding free energy can be used to rank-order protein-ligand structures in virtual screening for compound or target identification. Here, we carry out free energy calculations for a diverse set of 11 proteins bound to 14 small molecules using extensive explicit-solvent MD simulations. The structure of these complexes was previously solved by crystallography and their binding studied with isothermal titration calorimetry (ITC) data enabling direct comparison to the MM-GBSA and MM-PBSA calculations. Four MM-GBSA and three MM-PBSA calculations reproduced the ITC free energy within 1 kcal·mol(-1) highlighting the challenges in reproducing the absolute free energy from end-point free energy calculations. MM-GBSA exhibited better rank-ordering with a Spearman ρ of 0.68 compared to 0.40 for MM-PBSA with dielectric constant (ε = 1). An increase in ε resulted in significantly better rank-ordering for MM-PBSA (ρ = 0.91 for ε = 10), but larger ε significantly reduced the contributions of electrostatics, suggesting that the improvement is due to the nonpolar and entropy components, rather than a better representation of the electrostatics. The SVRKB scoring function applied to MD snapshots resulted in excellent rank-ordering (ρ = 0.81). Calculations of the configurational entropy using normal-mode analysis led to free energies that correlated significantly better to the ITC free energy than the MD-based quasi-harmonic approach, but the computed entropies showed no correlation with the ITC entropy. When the adaptation energy is taken into consideration by running separate simulations for complex, apo, and ligand (MM-PBSAADAPT), there is less agreement with the ITC data for the individual free energies, but remarkably good rank-ordering is observed (ρ = 0.89). Interestingly, filtering MD snapshots by prescoring protein-ligand complexes with a machine learning-based approach (SVMSP) resulted in a significant improvement in the MM-PBSA results (ε = 1) from ρ = 0.40 to ρ = 0.81. Finally, the nonpolar components of MM-GBSA and MM-PBSA, but not the electrostatic components, showed strong correlation to the ITC free energy; the computed entropies did not correlate with the ITC entropy.

Investigating allostery in molecular recognition: insights from a computational study of multiple antibody-antigen complexes

Antibody-antigen recognition plays a key role in the immune response against pathogens. Here, we have investigated various aspects of this problem by analyzing a large and diverse set of antibodies and their respective complexes with protein antigens through atomistic simulations. Common features of antibody response to the presence of antigens are elucidated by the analysis of the proteins' internal dynamics and coordination in different ligand states, combined with the analysis of the interaction networks implicated in the stabilization of functional structures. The use of a common structural reference reveals preferential changes in the dynamic coordination and intramolecular interaction networks induced by antigen binding and shared by all antibodies. Such changes propagate from the binding region through the whole immunoglobulin domains. Overall, complexed antibodies show more diffuse networks of nonbonded interactions and a general higher internal dynamic coordination, which preferentially involve the immunoglobulin (Ig) domains of the heavy chain. The combined results provide atomistic insights into the correlations between the modulation of conformational dynamics, structural stability, and allosteric signal transduction. In particular, the results suggest that specific networks of residues, shared among all the analyzed proteins, define the molecular pathways by which antibody structures respond to antigen binding. Our studies may have implications in practical use, such as the rational design of antibodies with specifically modulated antigen-binding affinities.

Develop and test a solvent accessible surface area-based model in conformational entropy calculations

It is of great interest in modern drug design to accurately calculate the free energies of protein-ligand or nucleic acid-ligand binding. MM-PBSA (molecular mechanics Poisson-Boltzmann surface area) and MM-GBSA (molecular mechanics generalized Born surface area) have gained popularity in this field. For both methods, the conformational entropy, which is usually calculated through normal-mode analysis (NMA), is needed to calculate the absolute binding free energies. Unfortunately, NMA is computationally demanding and becomes a bottleneck of the MM-PB/GBSA-NMA methods. In this work, we have developed a fast approach to estimate the conformational entropy based upon solvent accessible surface area calculations. In our approach, the conformational entropy of a molecule, S, can be obtained by summing up the contributions of all atoms, no matter they are buried or exposed. Each atom has two types of surface areas, solvent accessible surface area (SAS) and buried SAS (BSAS). The two types of surface areas are weighted to estimate the contribution of an atom to S. Atoms having the same atom type share the same weight and a general parameter k is applied to balance the contributions of the two types of surface areas. This entropy model was parametrized using a large set of small molecules for which their conformational entropies were calculated at the B3LYP/6-31G* level taking the solvent effect into account. The weighted solvent accessible surface area (WSAS) model was extensively evaluated in three tests. For convenience, TS values, the product of temperature T and conformational entropy S, were calculated in those tests. T was always set to 298.15 K through the text. First of all, good correlations were achieved between WSAS TS and NMA TS for 44 protein or nucleic acid systems sampled with molecular dynamics simulations (10 snapshots were collected for postentropy calculations): the mean correlation coefficient squares (R²) was 0.56. As to the 20 complexes, the TS changes upon binding; TΔS values were also calculated, and the mean R² was 0.67 between NMA and WSAS. In the second test, TS values were calculated for 12 proteins decoy sets (each set has 31 conformations) generated by the Rosetta software package. Again, good correlations were achieved for all decoy sets: the mean, maximum, and minimum of R² were 0.73, 0.89, and 0.55, respectively. Finally, binding free energies were calculated for 6 protein systems (the numbers of inhibitors range from 4 to 18) using four scoring functions. Compared to the measured binding free energies, the mean R² of the six protein systems were 0.51, 0.47, 0.40, and 0.43 for MM-GBSA-WSAS, MM-GBSA-NMA, MM-PBSA-WSAS, and MM-PBSA-NMA, respectively. The mean rms errors of prediction were 1.19, 1.24, 1.41, 1.29 kcal/mol for the four scoring functions, correspondingly. Therefore, the two scoring functions employing WSAS achieved a comparable prediction performance to that of the scoring functions using NMA. It should be emphasized that no minimization was performed prior to the WSAS calculation in the last test. Although WSAS is not as rigorous as physical models such as quasi-harmonic analysis and thermodynamic integration (TI), it is computationally very efficient as only surface area calculation is involved and no structural minimization is required. Moreover, WSAS has achieved a comparable performance to normal-mode analysis. We expect that this model could find its applications in the fields like high throughput screening (HTS), molecular docking, and rational protein design. In those fields, efficiency is crucial since there are a large number of compounds, docking poses, or protein models to be evaluated. A list of acronyms and abbreviations used in this work is provided for quick reference.

Computational studies of difference in binding modes of peptide and non-peptide inhibitors to MDM2/MDMX based on molecular dynamics simulations

Inhibition of p53-MDM2/MDMX interaction is considered to be a promising strategy for anticancer drug design to activate wild-type p53 in tumors. We carry out molecular dynamics (MD) simulations to study the binding mechanisms of peptide and non-peptide inhibitors to MDM2/MDMX. The rank of binding free energies calculated by molecular mechanics generalized Born surface area (MM-GBSA) method agrees with one of the experimental values. The results suggest that van der Waals energy drives two kinds of inhibitors to MDM2/MDMX. We also find that the peptide inhibitors can produce more interaction contacts with MDM2/MDMX than the non-peptide inhibitors. Binding mode predictions based on the inhibitor-residue interactions show that the π–π, CH–π and CH–CH interactions dominated by shape complimentarity, govern the binding of the inhibitors in the hydrophobic cleft of MDM2/MDMX. Our studies confirm the residue Tyr99 in MDMX can generate a steric clash with the inhibitors due to energy and structure. This finding may theoretically provide help to develop potent dual-specific or MDMX inhibitors.

Acentric 2-D ensembles of D-br-A electron-transfer chromophores via vectorial orientation within amphiphilic n-helix bundle peptides for photovoltaic device applications

We show that simply designed amphiphilic 4-helix bundle peptides can be utilized to vectorially orient a linearly extended donor-bridge-acceptor (D-br-A) electron transfer (ET) chromophore within its core. The bundle's interior is shown to provide a unique solvation environment for the D-br-A assembly not accessible in conventional solvents and thereby control the magnitudes of both light-induced ET and thermal charge recombination rate constants. The amphiphilicity of the bundle's exterior was employed to vectorially orient the peptide-chromophore complex at a liquid-gas interface, and its ends were tailored for subsequent covalent attachment to an inorganic surface, via a "directed assembly" approach. Structural data, combined with evaluation of the excited state dynamics exhibited by these peptide-chromophore complexes, demonstrate that densely packed, acentrically ordered 2-D monolayer ensembles of such complexes at high in-plane chromophore densities approaching 1/200 Å(2) offer unique potential as active layers in binary heterojunction photovoltaic devices.