Computational Design of BH3-Mimetic Peptide Inhibitors That Can Bind Specifically to Mcl-1 or Bcl-XL: Role of Non-Hot Spot Residues

Discovery of Highly Bioactive Peptides through Hierarchical Structural Information and Molecular Dynamics Simulations

Peptide drugs play an essential role in modern therapeutics, but the computational design of these molecules is hindered by several challenges. Traditional methods like molecular docking and molecular dynamics (MD) simulation, as well as recent deep learning approaches, often face limitations related to computational resource demands, complex binding affinity assessments, extensive data requirements, and poor model interpretability. Here, we introduce PepHiRe, an innovative methodology that utilizes the hierarchical structural information in peptide sequences and employs a novel strategy called Ladderpath, rooted in algorithmic information theory, to rapidly generate and enhance the efficiency and clarity of novel peptide design. We applied PepHiRe to develop BH3-like peptide inhibitors targeting myeloid cell leukemia-1, a protein associated with various cancers. By analyzing just eight known bioactive BH3 peptide sequences, PepHiRe effectively derived a hierarchy of subsequences used to create new BH3-like peptides. These peptides underwent screening through MD simulations, leading to the selection of five candidates for synthesis and subsequent in vitro testing. Experimental results demonstrated that these five peptides possess high inhibitory activity, with IC50 values ranging from 28.13 ± 7.93 to 167.42 ± 22.15 nM. Our study explores a white-box model driven technique and a structured screening pipeline for identifying and generating novel peptides with potential bioactivity.

In silico design of potential Mcl-1 peptide-based inhibitors

CONTEXT

BIM (Bcl-2 interacting mediator of apoptosis)-derived peptides that specifically target over-expressed Mcl-1 (myeloid cell leukemia-1) protein and induce apoptosis are potentially anti-cancer agents. Since the helicity of BIM-derived peptides has a crucial role in their functionality, a range of strategies have been used to increase the helicity including the introduction of unnatural residues and stapling methods that have some drawbacks such as the accumulation in the liver. To avoid these drawbacks, this study aimed to design a more helical peptide by utilizing bioinformatics algorithms and molecular dynamics simulations without exploiting unnatural residues and stapling methods. MM-PBSA results showed that the mutations of A4fE and A2eE in analogue 5 demonstrate a preference towards binding with Mcl-1. As evidenced by Circular dichroism results, the helicity increases from 18 to 34%, these findings could enhance the potential of analogue 5 as an anti-cancer agent targeting Mcl-1. The applied strategies in this research could shed light on the in silico peptide design. Moreover, analogue 5 as a drug candidate can be evaluated in vitro and in vivo studies.

METHODS

The sequence of the lead peptide was determined using the ApInAPDB database and PRALINE program. Contact finder and PDBsum web server softwares were used to determine the contact involved amino acids in complex with Mcl-1. All identified salt bridge contributing residues were unaltered to preserve the binding affinity. After proposing novel analogues, their secondary structures were predicted by Cham finder web server software and GOR, Neural Network, and Chou-Fasman algorithms. Finally, molecular dynamics simulations run for 100 ns were done using the GROMACS, version 5.0.7, with the CHARMM36 force field. MM-PBSA was used to assess binding affinity specificity in targeting Mcl-1 and Bcl-xL (B-cell lymphoma extra-large).

Molecular dynamics studies of CED-4/CED-9/EGL-1 ternary complex reveal CED-4 release mechanism in the linear apoptotic pathway of Caenorhabditis elegans

Many steps in programmed cell death are evolutionarily conserved across different species. The Caenorhabditis elegans proteins CED-9, CED-4 and EGL-1 involved in apoptosis are respectively homologous to anti-apoptotic Bcl-2 proteins, Apaf-1 and the "BH3-only" pro-apototic proteins in mammals. In the linear apoptotic pathway of C. elegans, EGL-1 binding to CED-9 leads to the release of CED-4 from CED-9/CED-4 complex. The molecular events leading to this process are not clearly elucidated. While the structures of CED-9 apo, CED-9/EGL-1 and CED-9/CED-4 complexes are known, the CED-9/CED-4/EGL-1 ternary complex structure is not yet determined. In this work, we modeled this ternary complex and performed molecular dynamics simulations of six different systems involving CED-9. CED-9 displays differential dynamics depending upon whether it is bound to CED-4 and/or EGL-1. CED-4 exists as an asymmetric dimer (CED4a and CED4b) in CED-9/CED-4 complex. CED-4a exhibits higher conformational flexibility when simulated without CED-4b. Principal Component Analysis revealed that the direction of CED-4a's winged-helix domain motion differs in the ternary complex. Upon EGL-1 binding, majority of non-covalent interactions involving CARD domain in the CED-4a-CED-9 interface have weakened and only half of the contacts found in the crystal structure between α/β domain of CED4a and CED-9 are found to be stable. Additional stable contacts in the ternary complex and differential dynamics indicate that winged-helix domain may play a key role in CED-4a's dissociation from CED-9. This study has provided a molecular level understanding of potential intermediate states that are likely to occur when CED-4a is released from CED-9.

In silico SELEX screening and statistical analysis of newly designed 5mer peptide-aptamers as Bcl-xl inhibitors using the Taguchi method

Drug development for cancer treatment is a complex process that requires special efforts. Targeting crucial proteins is the most essential purpose of drug design in cancers. Bcl-xl is an anti-apoptotic protein that binds to pro-apoptotic proteins and interrupts their signals. Pro-apoptotic Bcl-xl effectors are short BH3 sequences that form an alpha helix and bind to anti-apoptotic proteins to inhibit their activity. Computational systematic evolution of ligands by exponential enrichment (SELEX) is an exclusive approach for developing peptide aptamers as potential effectors. Here, the amino acids with a high tendency for constructing an alpha-helical structure were selected. Due to the enormous number of pentapeptides, Taguchi method was used to study a selected number of peptides. The binding affinity of the peptides to Bcl-xl was assessed using molecular docking, and after analysis of the obtained results, a final set of optimized peptides was arranged and constructed. For a better comparison, three chemical compounds with approved anti-Bcl-xl activity were selected for comparison with the top-ranked 5mer peptides. The optimized peptides showed considerable binding affinity to Bcl-xl. The molecular dynamics (MD) simulation indicated that the designed peptide (PO5) could create considerable interactions with the BH3 domain of Bcl-xl. The MM/GBSA calculations revealed that these interactions were even stronger than those created by chemical compounds. In silico SELEX is a novel approach to design and evaluate peptide-aptamers. The experimental design improves the SELEX process considerably. Finally, PO5 could be considered a potential inhibitor of Bcl-xl and a potential candidate for cancer treatment.

Designing BH3-Mimetic Peptide Inhibitors for the Viral Bcl-2 Homologues A179L and BHRF1: Importance of Long-Range Electrostatic Interactions

Viruses have evolved strategies to prevent apoptosis of infected cells at early stages of infection. The viral proteins (vBcl-2s) from specific viral genes adopt a helical fold that is structurally similar to that of mammalian antiapoptotic Bcl-2 proteins and exhibit little sequence similarity. Hence, vBcl-2 homologues are attractive targets to prevent viral infection. However, very few studies have focused on developing inhibitors for vBcl-2 homologues. In this study, we have considered two vBcl-2 homologues, A179L from African swine fever virus and BHRF1 from Epstein-Barr virus. We generated two sets of 8000 randomized BH3-like sequences from eight wild-type proapoptotic BH3 peptides. During this process, the four conserved hydrophobic residues and an Asp residue were retained at their respective positions, and all other positions were substituted randomly without any bias. We constructed 8000 structures each for A179L and BHRF1 in complex with BH3-like sequences. Histograms of interaction energies calculated between the peptide and the protein resulted in negatively skewed distributions. The BH3-like peptides with high helical propensities selected from the negative tail of the respective interaction energy distributions exhibited more favorable interactions with A179L and BHRF1, and they are rich in basic residues. Molecular dynamics studies and electrostatic potential maps further revealed that both acidic and basic residues favorably interact with A179L, while only basic residues have the most favorable interactions with BHRF1. As in mammalian homologues, the role of long-range interactions and nonhotspot residues has to be taken into account while designing specific BH3-mimetic inhibitors for vBcl-2 homologues.

Towards optimizing peptide-based inhibitors of protein-protein interactions: predictive saturation variation scanning (PreSaVS)

A simple-to-implement and experimentally validated computational workflow for sequence modification of peptide inhibitors of protein–protein interactions (PPIs) is described.

An experimentally validated approach for in silico modification of peptide based protein–protein interaction inhibitors is described.

Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

Protein-protein interactions (PPIs) mediate a large number of important regulatory pathways. Their modulation represents an important strategy for discovering novel therapeutic agents. However, the features of PPI binding surfaces make the use of structure-based drug discovery methods very challenging. Among the diverse approaches used in the literature to tackle the problem, linear peptides have demonstrated to be a suitable methodology to discover PPI disruptors. Unfortunately, the poor pharmacokinetic properties of linear peptides prevent their direct use as drugs. However, they can be used as models to design enzyme resistant analogs including, cyclic peptides, peptide surrogates or peptidomimetics. Small molecules have a narrower set of targets they can bind to, but the screening technology based on virtual docking is robust and well tested, adding to the computational tools used to disrupt PPI. We review computational approaches used to understand and modulate PPI and highlight applications in a few case studies involved in physiological processes such as cell growth, apoptosis and intercellular communication.