HelixDiff, a Score-Based Diffusion Model for Generating All-Atom α-Helical Structures.

Here, we present HelixDiff, a score-based diffusion model for generating all-atom helical structures. We developed a hot spot-specific generation algorithm for the conditional design of α-helices targeting critical hotspot residues in bioactive peptides. HelixDiff generates α-helices with near-native geometries for most test scenarios with root-mean-square deviations (RMSDs) less than 1 Å. Significantly, HelixDiff outperformed our prior GAN-based model with regard to sequence recovery and Rosetta scores for unconditional and conditional generations. As a proof of principle, we employed HelixDiff to design an acetylated GLP-1 D-peptide agonist that activated the glucagon-like peptide-1 receptor (GLP-1R) cAMP accumulation without stimulating the glucagon-like peptide-2 receptor (GLP-2R). We predicted that this D-peptide agonist has a similar orientation to GLP-1 and is substantially more stable in MD simulations than our earlier D-GLP-1 retro-inverse design. This D-peptide analogue is highly resistant to protease degradation and induces similar levels of AKT phosphorylation in HEK293 cells expressing GLP-1R compared to the native GLP-1. We then discovered that matching crucial hotspots for the GLP-1 function is more important than the sequence orientation of the generated D-peptides when constructing D-GLP-1 agonists.

Engineering a Rigid Nucleic Acid Structure to Improve the Limit of Detection for Genetic Assays.

Detecting nucleic acids at ultralow concentrations is critical for research and clinical applications. Particle-based assays are commonly used to detect nucleic acids. However, DNA hybridization on particle surfaces is inefficient due to the instability of tethered sequences, which negatively influences the assay's detection sensitivity. Here, we report a method to stabilize sequences on particle surfaces using a double-stranded linker at the 5' end of the tethered sequence. We termed this method Rigid Double Stranded Genomic Linkers for Improved DNA Analysis (RIGID-DNA). Our method led to a 3- and 100-fold improvement of the assays' clinical and analytical sensitivity, respectively. Our approach can enhance the hybridization efficiency of particle-based assays without altering existing assay workflows. This approach can be adapted to other platforms and surfaces to enhance the detection sensitivity.

Three decades targeting falcipains to develop antiplasmodial agents: what have we learned and what can be done next?

Malaria is a devastating infectious disease that affects large swathes of human populations across the planet's tropical regions. It is caused by parasites of the genus Plasmodium, with Plasmodium falciparum being responsible for the most lethal form of the disease. During the intraerythrocytic stage in the human hosts, malaria parasites multiply and degrade hemoglobin (Hb) using a battery of proteases, which include two cysteine proteases, falcipains 2 and 3 (FP-2 and FP-3). Due to their role as major hemoglobinases, FP-2 and FP-3 have been targeted in studies aiming to discover new antimalarials and numerous inhibitors with activity against these enzymes, and parasites in culture have been identified. Nonetheless, cross-inhibition of human cysteine cathepsins remains a serious hurdle to overcome for these compounds to be used clinically. In this article, we have reviewed key functional and structural properties of FP-2/3 and described different compound series reported as inhibitors of these proteases during decades of active research in the field. Special attention is also paid to the wide range of computer-aided drug design (CADD) techniques successfully applied to discover new active compounds. Finally, we provide guidelines that, in our understanding, will help advance the rational discovery of new FP-2/3 inhibitors.

Computational Design of Potent and Selective d-Peptide Agonists of the Glucagon-like Peptide-2 Receptor.

Here, we designed three d-GLP-2 agonists that activated the glucagon-like peptide-2 receptor (GLP-2R) cyclic adenosine monophosphate (cAMP) accumulation without stimulating the glucagon-like peptide-1 receptor (GLP-1R). All the d-GLP-2 agonists increased the protein kinase B phosphorylated (p-AKT) expression levels in a time- and concentration-dependent manner in vitro. The most effective d-GLP-2 analogue boosted the AKT phosphorylation 2.28 times more effectively compared to the native l-GLP-2. The enhancement in the p-AKT levels induced by the d-GLP-2 analogues could be explained by GLP-2R's more prolonged activation, given that the d-GLP-2 analogues induce a lower ß-arrestin recruitment. The higher stability to protease degradation of our d-GLP-2 agonists helps us envision their potential applications in enhancing intestinal absorption and treating inflammatory bowel illness while lowering the high dosage required by the current treatments.

Predicting a Stable Dimeric Form of the PD1-PDL1 Complex: Implications for Understanding the PD1 Activation Mechanism.

The activation of T cells is typically accompanied by inhibitory mechanisms within which the programmed cell death (PD1) receptor stands out. Upon binding the ligands PDL1 and PDL2, PD1 drives T cells to an unresponsive state called exhaustion, characterized by a markedly decreased capacity to exert effector functions. For this reason, PD1 has become one of the most important targets in cancer immunotherapy. Despite the numerous studies about PD1 signaling modulation, how the PD1 signaling is activated upon the ligands' binding remains an open question. Several experimental facts suggest that the activation of the PD1-PLD1 pathway depends on the interaction with an unknown partner at the cellular membrane. In this work, we investigate the possibility that the target of PD1-PDL1 is the same PD1-PDL1 complex. We combined molecular docking with molecular dynamics and umbrella sampling simulations to explore different binding modes and assess the complexes' stability. We predicted a stable dimeric form of the extracellular domains of the PD1-PDL1 complex. This dimeric complex has an affinity comparable to the PD1-PDL1 interaction and resembles the form of a linear lattice. We proposed a new model for PD1 activation where the PD1-PDL1 dimeric form could facilitate the interaction of the intracellular domains of PD1 and the further binding and activation of the SHP2 phosphatase. This model might explain the inhibitory effect of anti-PD1/PDL1 antibodies through the prevention of the formation of the PD1-PDL1 dimers and, subsequently, the abrogation of the SHP2 phosphatase activation.

Assessment of Different Parameters on the Accuracy of Computational Alanine Scanning of Protein-Protein Complexes with the Molecular Mechanics/Generalized Born Surface Area Method.

Computational alanine scanning with the molecular mechanics generalized Born surface area (MM/GBSA) method constitutes a widely used approach for identifying critical residues at protein-protein interfaces. Despite its popularity, the MM/GBSA method still has certain drawbacks due to its dependence on many factors. Here, we performed a systematical study on the impact of four different parameters, namely, the internal dielectric constant, the generalized Born model, the entropic term, and the inclusion of structural waters on the accuracy of computational alanine scanning calculations with the MM/GBSA method. Our results show that the internal dielectric constant is the most critical parameter for getting accurate predictions. The introduction of entropy and interfacial water molecules decreased the quality of the predictions, while the generalized Born model had little to no effect. Considering the significance of the internal dielectric value, we proposed a methodology based on the energetic predominance of a particular set of amino acids at the protein-protein interface for selecting an appropriate value for this variable. We hope that these results serve as a guideline for future studies of protein-protein complexes using the MM/GBSA method.

HelixGAN a deep-learning methodology for conditional de novo design of α-helix structures.

MOTIVATION: Protein and peptide engineering has become an essential field in biomedicine with therapeutics, diagnostics and synthetic biology applications. Helices are both abundant structural feature in proteins and comprise a major portion of bioactive peptides. Precise design of helices for binding or biological activity is still a challenging problem. RESULTS: Here, we present HelixGAN, the first generative adversarial network method to generate de novo left-handed and right-handed alpha-helix structures from scratch at an atomic level. We developed a gradient-based search approach in latent space to optimize the generation of novel α-helical structures by matching the exact conformations of selected hotspot residues. The designed α-helical structures can bind specific targets or activate cellular receptors. There is a significant agreement between the helix structures generated with HelixGAN and PEP-FOLD, a well-known de novo approach for predicting peptide structures from amino acid sequences. HelixGAN outperformed RosettaDesign, and our previously developed structural similarity method to generate D-peptides matching a set of given hotspots in a known L-peptide. As proof of concept, we designed a novel D-GLP1_1 analog that matches the conformations of critical hotspots for the GLP1 function. MD simulations revealed a stable binding mode of the D-GLP1_1 analog coupled to the GLP1 receptor. This novel D-peptide analog is more stable than our previous D-GLP1 design along the MD simulations. We envision HelixGAN as a critical tool for designing novel bioactive peptides with specific properties in the early stages of drug discovery. AVAILABILITY AND IMPLEMENTATION: https://github.com/xxiexuezhi/helix_gan. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Targeting the Receptor-Binding Motif of SARS-CoV-2 with D-Peptides Mimicking the ACE2 Binding Helix: Lessons for Inhibiting Omicron and Future Variants of Concern.

The COVID-19 pandemic continues to spread around the world, with several new variants emerging, particularly those of concern (VOCs). Omicron (B.1.1.529), a recent VOC with many mutations in the spike protein's receptor-binding domain (RBD), has attracted a great deal of scientific and public interest. We previously developed two D-peptide inhibitors for the infection of the original SARS-CoV-2 and its VOCs, alpha and beta, in vitro. Here, we demonstrated that Covid3 and Covid_extended_1 maintained their high-affinity binding (29.4-31.3 nM) to the omicron RBD. Both D-peptides blocked the omicron variant in vitro infection with IC50s of 3.13 and 5.56 µM, respectively. We predicted that Covid3 shares a larger overlapping binding region with the ACE2 binding motif than different classes of neutralizing monoclonal antibodies. We envisioned the design of D-peptide inhibitors targeting the receptor-binding motif as the most promising approach for inhibiting current and future VOCs of SARS-CoV-2, given that the ACE2 binding interface is more limited to tolerate mutations than most of the RBD's surface.

Unraveling a Conserved Conformation of the FG Loop upon the Binding of Natural Ligands to the Human and Murine PD1.

The activation of T cells is normally accompanied by inhibitory mechanisms within which the PD1 receptor stands out. PD1 drives T cells to an unresponsive state called exhaustion, characterized by a markedly decreased capacity to exert effector functions upon binding the ligands PDL1 and PDL2. For this reason, PD1 has become one of the most important targets in cancer immunotherapy. Despite the numerous studies about PD1 signaling modulation, how the PD1 signaling pathway is activated upon the ligands' binding remains an open question. In this work, we used molecular dynamics simulations to assess the differences of the PD1 motion in the free state and in complex with the ligands. We found that, in both human and murine systems, the binding of PDL1 and PDL2 stabilizes the conformation of the FG loop similarly. This result, combined with the conservation of the FG loop residues across species, suggests that the conformation of the FG loop is somehow related to the signaling process. We also found a high similarity between the PD1-PDL1 structures with the variable region of an antibody structure, where the FG loop occupies a similar position to the CDR3 light chain.

Discovery of tight-binding competitive inhibitors of dipeptidyl peptidase IV.

Dipeptidyl peptidase IV (DPP-IV, EC 3.4.14.5) is an abundant serine aminopeptidase that preferentially cleaves N-terminal Xaa-Pro or Xaa-Ala dipeptides from oligopeptides. Inhibitors of DPP-IV activity are used for treating type 2 diabetes mellitus and other diseases. DPP-IV is also involved in tumor progression. We identified four new non-peptide tight-binding competitive inhibitors of porcine DPP-IV by virtual screening and enzymatic assays. Molecular docking simulations supported the competitive behavior, and the selectivity of one of the compounds in the DPP-IV family. Since three of these inhibitors are also aminopeptidase N (APN) inhibitors, we tested their impact on APN+/DPP-IV+ and DPP-IV+ human tumor cells' viability. Using kinetic assays, we determined that HL-60 tumor cells express both APN and DPP-IV activities and that MDA-MB-231 tumor cells express DPP-IV activity. The inhibitors had a slight inhibitory effect on human HEK-293 cell viability but reduced the viability of APN+/DPP-IV+ and DPP-IV+ human tumor cells more potently. Remarkably, the intraperitoneal injection of these compounds inhibited DPP-IV activity in rat brain, liver, and pancreas. In silico studies suggested inhibitors binding to serum albumin contribute to blood-brain barrier crossing. The spectrum of action of some of these compounds may be useful for niche applications.

Tailored Parameterization of the LIE Method for Calculating the Binding Free Energy of Vps34-Inhibitor Complexes.

Vps34 is the only isoform of the PI3K family in fungi, making this protein an attractive target to develop new treatments against pathogenic fungi. The high structural similarity between the active sites of the human and fungal Vps34 makes repurposing of human Vps34 inhibitors an appealing strategy. Nonetheless, while some of the cross-reactive inhibitors might have the potential to treat fungal infections, a safer approach to prevent undesired side effects would be to identify molecules that specifically inhibit the fungal Vps34. This study presents the parameterization of four LIE models for estimating the binding free energy of Vps34-inhibitor complexes. Two models are parameterized using a multiparametric linear regression leaving one or more free parameters, while the other two are based on the LIE-D model. All of the models show good predictive capacity (R 2 > 0.7, r > 0.85) and a low mean absolute error (MAE < 0.71 kcal/mol). The current study highlights the advantages of LIE-D-derived models when predicting the weight of the different contributions to the binding free energy. It is expected that this study will provide researchers with a valuable tool to identify new Vps34 inhibitors for relevant applications such as cancer treatment and the development of new antimicrobial agents.

Computational Design of Potent D-Peptide Inhibitors of SARS-CoV-2.

Blocking the association between the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein receptor-binding domain (RBD) and the human angiotensin-converting enzyme 2 (ACE2) is an attractive therapeutic approach to prevent the virus from entering human cells. While antibodies and other modalities have been developed to this end, d-amino acid peptides offer unique advantages, including serum stability, low immunogenicity, and low cost of production. Here, we designed potent novel D-peptide inhibitors that mimic the ACE2 α1-binding helix by searching a mirror-image version of the PDB. The two best designs bound the RBD with affinities of 29 and 31 nM and blocked the infection of Vero cells by SARS-CoV-2 with IC50 values of 5.76 and 6.56 µM, respectively. Notably, both D-peptides neutralized with a similar potency the infection of two variants of concern: B.1.1.7 and B.1.351 in vitro. These potent D-peptide inhibitors are promising lead candidates for developing SARS-CoV-2 prophylactic or therapeutic treatments.

gmx_MMPBSA: A New Tool to Perform End-State Free Energy Calculations with GROMACS.

Molecular mechanics/Poisson-Boltzmann (Generalized-Born) surface area is one of the most popular methods to estimate binding free energies. This method has been proven to balance accuracy and computational efficiency, especially when dealing with large systems. As a result of its popularity, several programs have been developed for performing MM/PB(GB)SA calculations within the GROMACS community. These programs, however, present several limitations. Here we present gmx_MMPBSA, a new tool to perform end-state free energy calculations from GROMACS molecular dynamics trajectories. gmx_MMPBSA provides the user with several options, including binding free energy calculations with different solvation models (PB, GB, or 3D-RISM), stability calculations, computational alanine scanning, entropy corrections, and binding free energy decomposition. Noteworthy, several promising methodologies to calculate relative binding free energies such as alanine scanning with variable dielectric constant and interaction entropy have also been implemented in gmx_MMPBSA. Two additional tools-gmx_MMPBSA_test and gmx_MMPBSA_ana-have been integrated within gmx_MMPBSA to improve its usability. Multiple illustrating examples can be accessed through gmx_MMPBSA_test, while gmx_MMPBSA_ana provides fast, easy, and efficient access to different graphics plotted from gmx_MMPBSA output files. The latest version (v1.4.3, 26/05/2021) is available free of charge (documentation, test files, and tutorials included) at https://github.com/Valdes-Tresanco-MS/gmx_MMPBSA.

Differential Effects of IL2Rα and IL15Rα over the Stability of the Common Beta-Gamma Signaling Subunits of the IL2 and IL15 Receptors.

Interleukin (IL) 2 and IL15 are two members of the common gamma chain cytokine family, involved in the regulation of the T cell differentiation process. Both molecules use a specific alpha subunit, IL2Rα and IL15Rα, and share the same beta and gamma chains signaling receptors. The presence of the specific alpha subunit modulates the T cell ability to compete for both soluble cytokines while the beta and gamma subunits are responsible for the signal transduction. Recent experimental results point out that the specific alpha subunits modulate the capacity of IL2 and IL15 to induce the differentiation of stimulated T cells. In other membrane receptors, the outcome of the signal transduction has been associated with the strength of the interaction of the signaling subunits. Here, we investigate how IL2Rα and IL15Rα modulate the stability of their signaling complexes by combining molecular dynamics simulations and free energy calculations. Our simulations predict that IL2Rα binding destabilizes the ß-γc interaction mediated by IL2, while IL15Rα has the opposite effect. These results explain the ability of IL2Rα and IL15Rα to modulate the signaling outcome and suggest new strategies for the development of better CD8+ T cell differentiation protocols for adoptive cell transfer (ACT).

Exploring the conformational dynamics of PD1 in complex with different ligands: What we can learn for designing novel PD1 signaling blockers?

Activation of T cells triggers the expression of regulatory molecules like the programmed cell death 1 (PD1) protein. The association of PD1 with the natural ligands PDL1 and PDL2 induces an inhibitory signal that prevents T cells from proliferating and exerting effector functions. However, little is known about how the binding of the ligands induce the PD1 inhibitory signal over T cells effector functions. Here, we explore the dynamics of PD1 free, and in complex with different PDL1 variants as well as the therapeutic antibodies nivolumab and pembrolizumab in order to assess the conformational changes in PD1 related to the signaling process. Our simulations suggest a pre-conformational selection mechanism for the binding of the different PDL1 variants, while an induced-fit model fits better for the molecular recognition process of the therapeutic antibodies. A deep analysis of the changes on PD1 movement upon the binding to different ligands revealed that as larger is the difference in the conformation adopted by loop C'D with respect to the complex with PDL1 is higher the ligand ability to reduce the PD1 inhibitory signaling. This behavior suggests that targeting specific conformations of this loop can be useful for designing therapies able to recover T cells effector functions.

AMDock: a versatile graphical tool for assisting molecular docking with Autodock Vina and Autodock4.

AMDock (Assisted Molecular Docking) is a user-friendly graphical tool to assist in the docking of protein-ligand complexes using Autodock Vina and AutoDock4, including the option of using the Autodock4Zn force field for metalloproteins. AMDock integrates several external programs (Open Babel, PDB2PQR, AutoLigand, ADT scripts) to accurately prepare the input structure files and to optimally define the search space, offering several alternatives and different degrees of user supervision. For visualization of molecular structures, AMDock uses PyMOL, starting it automatically with several predefined visualization schemes to aid in setting up the box defining the search space and to visualize and analyze the docking results. One particularly useful feature implemented in AMDock is the off-target docking procedure that allows to conduct ligand selectivity studies easily. In summary, AMDock's functional versatility makes it a very useful tool to conduct different docking studies, especially for beginners. The program is available, either for Windows or Linux, at https://github.com/Valdes-Tresanco-MS . REVIEWERS: This article was reviewed by Alexander Krah and Thomas Gaillard.

Understanding the disrupting mechanism of the Tau aggregation motif "306 VQIVYK311 " by phenylthiazolyl-hydrazides inhibitors.

Alzheimer's disease is a progressive neurodegenerative disorder characterized by the abnormal processing of the Tau and the amyloid precursor proteins. The unusual aggregation of Tau is based on the formation of intermolecular ß-sheets through two motifs: 275 VQIINK280 and 306 VQIVYK311 . Phenylthiazolyl-hydrazides (PTHs) are capable of inhibiting/disassembling Tau aggregates. However, the disaggregation mechanism of Tau oligomers by PTHs is still unknown. In this work, we studied the disruption of the oligomeric form of the Tau motif 306 VQIVYK311 by PTHs through molecular docking, molecular dynamics, and free energy calculations. We predicted hydrophobic interactions as the major driving forces for the stabilization of Tau oligomer, with V306 and I308 being the major contributors. Nonpolar component of the binding free energy is essential to stabilize Tau-PTH complexes. PTHs disrupted mainly the van der Waals interactions between the monomers, leading to oligomer destabilization. Destabilization of full Tau filament by PTHs and emodin was not observed in the sampled 20 ns; however, in all cases, the nonpolar component of the binding free energy is essential for the formation of Tau filament-PTH and Tau filament-emodin. These results provide useful clues for the design of more effective Tau-aggregation inhibitors.

A Method to Calculate the Relative Binding Free Energy Differences of α-Helical Stapled Peptides.

Hydrocarbon-stapled peptides are a class of bioactive α-helical ligands developed to target protein-protein interactions. Peptide stapling has benefited from the development of several chemical reactions to modulate their membrane permeability and binding affinity. However, in most current programs, choosing the best stapling positions is usually a trial-and-error process. Here, we develop a protocol to obtain optimal stapling positions computationally. Our method is based on molecular dynamics simulations and free energy calculations with nonequilibrium approaches; here, we predict the binding poses, hot-spot residues, and binding affinity differences of a set of perfluoroarene stapled α-helical peptides of the BIM BH3 peptide to the BCLXL receptor. The prediction of the hot-spot residues within the target peptide through computational alanine scanning anticipates not only the key residues for the receptor-peptide complex formation but also which positions should be avoided when applying the stapling groups. The staple moieties introduce local conformational changes not only in the replaced positions but also on their neighbor residues of the template peptide further affecting their binding behavior. Our approach is successful at rank-ordering the binding affinities of these stapled peptides with respect to the BIM BH3 peptide.

Membrane Remodeling by the Lytic Fragment of SticholysinII: Implications for the Toroidal Pore Model.

Sticholysins are pore-forming toxins of biomedical interest and represent a prototype of proteins acting through the formation of protein-lipid or toroidal pores. Peptides spanning the N-terminus of sticholysins can mimic their permeabilizing activity and, together with the full-length toxins, have been used as a tool to understand the mechanism of pore formation in membranes. However, the lytic mechanism of these peptides and the lipid shape modulating their activity are not completely clear. In this article, we combine molecular dynamics simulations and experimental biophysical tools to dissect different aspects of the pore-forming mechanism of StII1-30, a peptide derived from the N-terminus of sticholysin II (StII). With this combined approach, membrane curvature induction and flip-flop movement of the lipids were identified as two important membrane remodeling steps mediated by StII1-30. Pore formation by this peptide was enhanced by the presence of the negatively curved lipid phosphatidylethanolamine in membranes. This lipid emerged not only as a facilitator of membrane interactions but also as a structural element of the StII1-30 pore that is recruited to the ring upon its assembly. Collectively, these, to our knowledge, new findings support a toroidal model for the architecture of the pore formed by StII1-30 and provide new molecular insight into the role of phosphatidylethanolamine as a membrane component that can easily integrate into the ring of toroidal pores, thus probably aiding in their stabilization. This study contributes to a better understanding of the molecular mechanism underlying the permeabilizing activity of StII1-30 and peptides or proteins acting via a toroidal pore mechanism and offers an informative framework for the optimization of the biomedical application of this and similar molecules.

Hexahydropyrrolo[2,3-b]indole Compounds as Potential Therapeutics for Alzheimer's Disease.

Alzheimer's disease (AD) is the most common form of dementia among the elderly and has become a leading public health concern worldwide. It represents a huge economic and psychological burden to caregivers and families. The presence of extracellular amyloid beta (Aß) plaques is one of the hallmarks of this neurodegenerative disorder. Amyloid plaques are comprised of aggregates of Aß peptides, mainly Aß42, originated by the cleavage of the amyloid precursor protein (APP). Aß is a crucial target for the treatment of AD, but to date, no effective treatment for the clearance of Aß has been found. We have identified four new hexahydropyrroloindoles (HPI) synthetic compounds that are able to inhibit the aggregation of Aß42 and/or disaggregate the fibril. Docking experiments suggest that the nonpolar component of the interaction of compounds with Aß42 contributes favorably to the binding free energy of each complex. Molecular dynamics simulations suggested fibril disaggregating activity of compounds 1 via interaction with hydrophobic moieties of the fibril. Consistently, compounds 1 and 2 were able to mitigate Aß42 fibrils induced death in rat pheochromocytoma cells (PC 12). One of the compounds reduces the formation of Aß aggregates in vivo and the paralysis associated with Aß toxicity in Caenorhabditis elegans. Our study thus augments efforts for the identification and characterization of new agents that may help stop or delay the progression of AD.