A computational investigation was employed to better understand the engagement mechanism for the formation of ternary complexes involving VHL-recruiting PROTACs designed for oncogenic KRasG12C. Rounds of protein-protein docking followed by conformational searches enabled the prediction of the most likely ternary complexes for each PROTAC, which were further validated through rounds of MD simulations. The methodology was applied to six PROTAC molecules (LC1-LC6) that were previously designed, synthesized, tested in cell assays, and reported in the literature. These control systems included five different linker sizes and were derived from the KRasG12C covalent ligand MRTX849 and the VHL ligand 3. Our results suggest that these compounds are capable of engaging KRasG12C and VHL, forming dynamically stable ternary complexes under a predominant binding mode. It was also observed that KRasG12C and VHL exhibit similar dynamic behaviors for binding the PROTAC versus the individual ligand warheads with no linker. Our findings reinforce the concept that this methodology can serve as a powerful tool for designing structures and prioritizing compounds for further synthesis and biological evaluation.

We develop a framework for the design of optimized alchemical transformation pathways in free energy simulations using nonlinear mixing and a new functional form for so-called "softcore" potentials. We describe the implementation and testing of this framework in the GPU-accelerated AMBER software suite. The new optimized alchemical transformation pathways integrate a number of important features, including (1) the use of smoothstep functions to stabilize behavior near the transformation end points, (2) consistent power scaling of Coulomb and Lennard-Jones (LJ) interactions with unitless control parameters to maintain balance of electrostatic attractions and exchange repulsions, (3) pairwise form based on the LJ contact radius for the effective interaction distance with separation-shifted scaling, and (4) rigorous smoothing of the potential at the nonbonded cutoff boundary. The new softcore potential form is combined with smoothly transforming nonlinear λ weights for mixing specific potential energy terms, along with flexible λ-scheduling features, to enable robust and stable alchemical transformation pathways. The resulting pathways are demonstrated and tested, and shown to be superior to the traditional methods in terms of numerical stability and minimal variance of the free energy estimates for all cases considered. The framework presented here can be used to design new alchemical enhanced sampling methods, and leveraged in robust free energy workflows for large ligand data sets.

The most common host entry point of human adapted coronaviruses (CoV) including SARS-CoV-2 is through the initial colonization in the nostril and mouth region which is responsible for spread of the infection. Most recent studies suggest that the commercially available oral and nasal rinse products are effective in inhibiting the viral replication. However, the anti-viral mechanism of the active ingredients present in the oral rinses have not been studied. In the present study, we have assessed in vitro enzymatic inhibitory activity of active ingredients in the oral mouth rinse products: aloin A and B, chlorhexidine, eucalyptol, hexetidine, menthol, triclosan, methyl salicylate, sodium fluoride and povidone, against two important proteases of SARS-CoV-2 PLpro and 3CLpro. Our results indicate only aloin A and B effectively inhibited proteolytic activity of PLpro with an IC 50 of 13.16 and 16.08 μM. Interestingly, neither of the aloin isoforms inhibited 3CLpro enzymatic activity. Computational structural modelling of aloin A and B interaction with PLpro revealed that, both aloin isoforms form hydrogen bond with Tyr 268 of PLpro, which is critical for their proteolytic activity. Furthermore, 100 ns molecular dynamics (MD) simulation studies predicted that both aloin isoforms have strong interaction with Glu 167 , which is required for PLpro deubiquitination activity. Our results from the in vitro deubiquitinase inhibition assay show that aloin A and B isomers exhibit deubiquitination inhibitory activity with an IC 50 value of 15.68 and 17.51 µM, respectively. In conclusion, the isoforms of aloin inhibit both proteolytic and the deubiquitinating activity of SARS-CoV-2 PLpro, suggesting potential in inhibiting the replication of SARS-CoV-2 virus.

ATP synthase's intrinsic molecular electrostatic potential (MESP) adds constructively to, and hence reinforces, the chemiosmotic voltage. This ATP synthase voltage represents a new free energy term that appears to have been overlooked. This term is at least roughly equal in order of magnitude and opposite in sign to the energy needed to be dissipated as a Maxwell's demon (Landauer principle).

Detailed description of the mechanism of action of the therapeutic antibodies is essential for the functional characterization and future optimization of potential clinical agents. We recently developed KD035, a fully human antibody targeting vascular endothelial growth factor receptor 2 (VEGFR2). KD035 blocked VEGF-A, and VEGF-C-mediated VEGFR2 activation, as demonstrated by the in vitro binding and competition assays and functional cellular assays. Here, we report a computational model of the complex between the variable fragment of KD035 (KD035(Fv)) and the domains 2 and 3 of the extracellular portion of VEGFR2 (VEGFR2(D2-3)). Our modeling was guided by a priori experimental information including the X-ray structures of KD035 and related antibodies, binding assays, target domain mapping and comparison of KD035 affinity for VEGFR2 from different species. The accuracy of the model was assessed by molecular dynamics simulations, and subsequently validated by mutagenesis and binding analysis. Importantly, the steps followed during the generation of this model can set a precedent for future in silico efforts aimed at the accurate description of the antibody-antigen and more broadly protein-protein complexes.

Understanding the relationship between protein structural dynamics and function is crucial for both basic research and biotechnology. However, methods for studying the fast dynamics of structural changes are limited. Here, we introduce fluorescent nanoantennas as a spectroscopic technique to sense and report protein conformational changes through noncovalent dye-protein interactions. Using experiments and molecular simulations, we detect and characterize five distinct conformational states of intestinal alkaline phosphatase, including the transient enzyme-substrate complex. We also explored the universality of the nanoantenna strategy with another model protein, Protein G and its interaction with antibodies, and demonstrated a rapid screening strategy to identify efficient nanoantennas. These versatile nanoantennas can be used with diverse dyes to monitor small and large conformational changes, suggesting that they could be used to characterize diverse protein movements or in high-throughput screening applications.

This talk will underscore the importance of developing fast Quantum Crystallographic (QCr) [1] approaches to accurately calculate the electric fields and their associated electrostatic potentials of large molecules such as proteins. Crystallographic structures of ATP synthase from five species have been used to calculate (approximately) and compare their intrinsic electrostatic potentials and fields [2-4]. Striking consistent patterns (and differences) in the topographies of these scalar and vector fields are uncovered across the five studied ATP synthases [2]. The role of these fields in the biological function of ATP synthase will be discussed within the context of Mitchell’s chemisomotic theory. Our calculations suggest that, due to the intrinsic field of ATP synthase itself, the standard equation of chemiosmotic must be augmented by including a term that accounts for the contributi on to Δ G of the difference in ATP synthase’s electrostatic potential,  , between the points of entry and exit of the protons in the mitochondrion. With this inclusion, our proposed amended equation for the chemisomotic Δ G , in standard notation, becomes [2-4]: Our results can be summed-up into assigning two separate but complementary roles to ATP synthase [2]: reaction:

Free energy calculations using Thermodynamic Integration or Free Energy Perturbation techniques rely on statistics sampled from Monte Carlo or Molecular Dynamics simulations. In the present work, we characterize the expected variances from such simulations in the general case of estimating relative free energies of a collection of small molecules against a common receptor. Variance minimizing parameters for: (i) soft-core potentials, (ii) numerical integration, and (iii) pairwise transformation topologies (simulation plans) are presented. The results of computational experiments are discussed, including an application to p38 MAP kinase inhibitors.

Emerging outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is a major threat to public health. The morbidity is increasing due to lack of SARS-CoV-2 specific drugs. Herein, we have identified potential drugs that target the 3-chymotrypsin like protease (3CLpro), the main protease that is pivotal for the replication of SARS-CoV-2. Computational molecular modeling was used to screen 3987 FDA approved drugs, and 47 drugs were selected to study their inhibitory effects on SARS-CoV-2 specific 3CLpro enzyme in vitro. Our results indicate that boceprevir, ombitasvir, paritaprevir, tipranavir, ivermectin, and micafungin exhibited inhibitory effect towards 3CLpro enzymatic activity. The 100 ns molecular dynamics simulation studies showed that ivermectin may require homodimeric form of 3CLpro enzyme for its inhibitory activity. In summary, these molecules could be useful to develop highly specific therapeutically viable drugs to inhibit the SARS-CoV-2 replication either alone or in combination with drugs specific for other SARS-CoV-2 viral targets.

Trimethoprim (TMP) is widely used to treat infections in humans and in livestock, accelerating the incidence of TMP resistance. The emergent and largely untracked type II dihydrofolate reductases (DfrBs) are intrinsically TMP-resistant plasmid-borne Dfrs that are structurally and evolutionarily unrelated to chromosomal Dfrs. We report kinetic characterization of the known DfrB family members. Their kinetic constants are conserved and all are poorly inhibited by TMP, consistent with TMP resistance. We investigate their inhibition with known and novel bisubstrate inhibitors of 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK). Importantly, all are inhibited by the HPPK inhibitors, making these molecules dual-target inhibitors of two folate pathway enzymes that are strictly microbial.

Hypoxia sensors are essential for regulating local oxygen (O2) homeostasis within the body. This is especially pertinent within the CNS, which is particularly vulnerable to O2 deprivation due to high energetic demand. Here, we reveal hypoxia-monitoring function exerted by astrocytes through an O2-regulated protein trafficking mechanism within the CNS. Strikingly, cultured mouse astrocytes isolated from the parafacial respiratory group (pFRG) and retrotrapezoid nucleus (RTN) region are capable of rapidly responding to moderate hypoxia via the sensor cation channel transient receptor potential (TRP) A1 but, unlike multimodal sensory neurons, are inert to hyperoxia and other TRPA1 activators (carbon dioxide, electrophiles, and oxidants) in normoxia. Mechanistically, O2 suppresses TRPA1 channel activity by protein internalization via O2-dependent proline hydroxylation and subsequent ubiquitination by an E3 ubiquitin ligase, NEDD4-1 (neural precursor cell-expressed developmentally down-regulated protein 4). Hypoxia inhibits this process and instantly accumulates TRPA1 proteins at the plasma membrane, inducing TRPA1-mediated Ca2+ influx that triggers ATP release from pFRG/RTN astrocytes, potentiating respiratory center activity. Furthermore, astrocyte-specific Trpa1 disruption in a mouse brainstem-spinal cord preparation impedes the amplitude augmentation of the central autonomic respiratory output during hypoxia. Thus, reversible coupling of the TRPA1 channels with O2-dependent protein translocation allows astrocytes to act as acute hypoxia sensors in the medullary respiratory center.

Natural raspberry ketone has a high value in the flavor, fragrance and pharmaceutical industries. Its extraction is costly, justifying the search for biosynthetic routes. We hypothesized that cytochrome P450 BM3 (P450 BM3) could be engineered to catalyze the hydroxylation of 4‐phenyl‐2‐butanone, a naturally sourceable precursor, to raspberry ketone. The synthesis of indigo by variants of P450 BM3 has previously served as a predictor of promiscuous oxidation reactions. To this end, we screened 53 active‐site variants of P450 BM3 using orthogonal high‐throughput workflows to identify the most streamlined route to all indigo‐forming variants. Among the three known and 13 new indigo‐forming variants, eight hydroxylated 4‐phenyl‐2‐butanone to raspberry ketone. Previously unreported variant A82Q displayed the highest initial rates and coupling efficiencies in synthesis of indigo and of raspberry ketone. It produced the highest total concentration of raspberry ketone despite producing less total indigo than previously reported variants. Its productivity, although modest, clearly demonstrates the potential for development of a biocatalytic route to raspberry ketone. In addition to validating indigo as a robust predictor of this promiscuous activity, we demonstrate that monitoring rapid NADPH consumption serves as an alternative predictor of a promiscuous reactivity in P450 BM3.

Understanding the principles of protein dynamics will help guide engineering of protein function: altering protein motions may be a barrier to success or may be an enabling tool for protein engineering. The impact of dynamics on protein function is typically reported over a fraction of the full scope of motional timescales. If motional patterns vary significantly at different timescales, then only by monitoring motions broadly will we understand the impact of protein dynamics on engineering functional proteins. Using an integrative approach combining experimental and in silico methodologies, we elucidate protein dynamics over the entire span of fast to slow timescales (ps to ms) for a laboratory-engineered system composed of five interrelated β-lactamases: two natural homologs and three laboratory-recombined variants. Fast (ps-ns) and intermediate (ns-µs) dynamics were mostly conserved. However, slow motions (µs-ms) were few and conserved in the natural homologs yet were numerous and widely dispersed in their recombinants. Nonetheless, modified slow dynamics were functionally tolerated. Crystallographic B-factors from high-resolution X-ray structures were partly predictive of the conserved motions but not of the new slow motions captured in our solution studies. Our inspection of protein dynamics over a continuous range of timescales vividly illustrates the complexity of dynamic impacts of protein engineering as well as the functional tolerance of an engineered enzyme system to new slow motions.

Flexible transmembrane helices frequently support the conformational transitions between different functional states of membrane proteins. While proline is well known to distort and destabilize transmembrane helices, the role of glycine is still debated. Here, we systematically investigated the effect of glycine on transmembrane helix flexibility by placing it at different sites within the otherwise uniform leucine/valine repeat sequence of the LV16 model helix. We show that amide deuterium/hydrogen exchange kinetics are increased near glycine. Molecular dynamics simulations reproduce the measured exchange kinetics and reveal, at atomic resolution, a severe packing defect at glycine that enhances local hydration. Furthermore, glycine alters H-bond occupancies and triggers a redistribution of α-helical and 310-helical H-bonds. These effects facilitate local helix bending at the glycine site and change the collective dynamics of the helix.

This review presents computational methods that experimentalists can readily use to create smart libraries for enzyme engineering and to obtain insights into protein-substrate complexes. Computational tools have the reputation of being hard to use and inaccurate compared to experimental methods in enzyme engineering, yet they are essential to probe datasets of ever-increasing size and complexity. In recent years, bioinformatics groups have made a huge leap forward in providing user-friendly interfaces and accurate algorithms for experimentalists. These methods guide efficient experimental planning and allow the enzyme engineer to rationalize time and resources. Computational tools nevertheless face challenges in the realm of transient modern technology.

Prediction of substrate-specific mutational hotspots for enzyme engineering is a complex and computationally intensive task. This becomes particularly challenging when the available crystal structures have no ligand, bind a distant homologue of the desired substrate, or hold the ligand in a nonproductive conformation. To address that shortcoming, we present a combined molecular dynamics simulation and molecular docking protocol to predict the conformation of catalytically relevant enzyme ligand complexes even in the absence of a ligand-bound structure. We applied the adaptive biasing force method to predict the ligand-specific path of diffusion of a fatty acid substrate from the bulk media into the active site of cytochrome P450 CYP102A1 (BM3). Starting with a ligand-free crystal structure, we successfully identified all residues known to be involved in palmitic acid binding to BM3. The binding trajectory also revealed a yet unknown binding residue, Q73, which we confirmed experimentally. Building the free-energy landscape illustrates that, similar to human cytochrome P450s, binding is multistep and does not follow simple Michaelis-Menten kinetics. We confirmed the robustness of the method using a structurally distinct substrate, the small aromatic indole. We then applied the predicted BM3:palmitate complex to molecular docking of a library of 29 palmitate analogues. This produced catalytically relevant binding poses for the entire library, while docking directly into ligand-free and ligand-bound crystal structures gave poor results. This fast and simple computational method is broadly applicable for predicting binding hotspots in a substrate-specific manner and has the potential to drastically reduce the experimental screening effort to tailor an enzyme to substrates of interest.

The Golden Gate strategy entails the use of type IIS restriction enzymes, which cut outside of their recognition sequence. It enables unrestricted design of unique DNA fragments that can be readily and seamlessly recombined. Successfully employed in other synthetic biology applications, we demonstrate its advantageous use to engineer a biocatalyst. Hot-spots for mutations were individuated in three distinct regions of Candida antarctica lipase A (Cal-A), the biocatalyst chosen as a target to demonstrate the versatility of this recombination method. The three corresponding gene segments were subjected to the most appropriate method of mutagenesis (targeted or random). Their straightforward reassembly allowed combining products of different mutagenesis methods in a single round for rapid production of a series of diverse libraries, thus facilitating directed evolution. Screening to improve discrimination of short-chain versus long-chain fatty acid substrates was aided by development of a general, automated method for visual discrimination of the hydrolysis of varied substrates by whole cells.