Computer-aided research on the relationship between molecular structures of natural compounds (NC) and their biological activities have been carried out extensively because the molecular structures of new drug candidates are usually analogous to or derived from the molecular structures of NC. In order to express the relationship physically realistically using a computer, it is essential to have a molecular descriptor set that can adequately represent the characteristics of the molecular structures belonging to the NC’s chemical space. Although several topological descriptors have been developed to describe the physical, chemical, and biological properties of organic molecules, especially synthetic compounds, and have been widely used for drug discovery researches, these descriptors have limitations in expressing NC-specific molecular structures. To overcome this, we developed a novel molecular fingerprint, called Natural Compound Molecular Fingerprints (NC-MFP), for explaining NC structures related to biological activities and for applying the same for the natural product (NP)-based drug development. NC-MFP was developed to reflect the structural characteristics of NCs and the commonly used NP classification system. NC-MFP is a scaffold-based molecular fingerprint method comprising scaffolds, scaffold-fragment connection points (SFCP), and fragments. The scaffolds of the NC-MFP have a hierarchical structure. In this study, we introduce 16 structural classes of NPs in the Dictionary of Natural Product database (DNP), and the hierarchical scaffolds of each class were calculated using the Bemis and Murko (BM) method. The scaffold library in NC-MFP comprises 676 scaffolds. To compare how well the NC-MFP represents the structural features of NCs compared to the molecular fingerprints that have been widely used for organic molecular representation, two kinds of binary classification tasks were performed. Task I is a binary classification of the NCs in commercially available library DB into a NC or synthetic compound. Task II is classifying whether NCs with inhibitory activity in seven biological target proteins are active or inactive. Two tasks were developed with some molecular fingerprints, including NC-MFP, using the 1-nearest neighbor (1-NN) method. The performance of task I showed that NC-MFP is a practical molecular fingerprint to classify NC structures from the data set compared with other molecular fingerprints. Performance of task II with NC-MFP outperformed compared with other molecular fingerprints, suggesting that the NC-MFP is useful to explain NC structures related to biological activities. In conclusion, NC-MFP is a robust molecular fingerprint in classifying NC structures and explaining the biological activities of NC structures. Therefore, we suggest NC-MFP as a potent molecular descriptor of the virtual screening of NC for natural product-based drug development.

Six kuwanon derivatives (A/B/C/E/H/J) extracted from the roots of Morus alba L. were evaluated to determine their cyclooxygenase (COX)-1 and 2 inhibitory effects. Cyclooxygenase (COX) is known as the target enzyme of nonsteroidal anti-inflammatory drugs (NSAIDs), which are the most widely used therapeutic agents for pain and inflammation. Among six kuwanon derivatives, kuwanon A showed selective COX-2 inhibitory activity, almost equivalent to that of celecoxib, a known COX inhibitor. Kuwanon A showed high COX-2 inhibitory activity (IC₅₀ = 14 μM) and a selectivity index (SI) range of >7.1, comparable to celecoxib (SI > 6.3). To understand the mechanisms underlying this effect, we performed docking simulations, fragment molecular orbital (FMO) calculations, and pair interaction energy decomposition analysis (PIEDA) at the quantum-mechanical level. As a result, kuwanon A had the strongest interaction with Arg120 and Tyr355 at the gate of the COX active site (−7.044 kcal/mol) and with Val89 in the membrane-binding domain (−6.599 kcal/mol). In addition, kuwanon A closely bound to Val89, His90, and Ser119, which are residues at the entrance and exit routes of the COX active site (4.329 Å). FMO calculations and PIEDA well supported the COX-2 selective inhibitory action of kuwanon A. It showed that the simulation and modeling results and experimental evidence were consistent.

In the past 2 years, since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple SARS-CoV-2 variants have emerged. Whenever a new variant emerges, considerable time is required to analyze the binding affinity of the viral surface proteins to human angiotensin-converting enzyme 2 (hACE2) and monoclonal antibodies. To efficiently predict the binding affinities associated with hACE2 and monoclonal antibodies in a short time, herein, we propose a method applying statistical analysis to simulations performed using molecular and quantum mechanics. This method efficiently predicted the trend of binding affinity for the binding of the spike protein of each variant of SARS-CoV-2 to hACE2 and individually to eight commercial monoclonal antibodies. Additionally, this method accurately predicted interaction energy changes in the crystal structure for 10 of 13 mutated residues in the Omicron variant, showing a significant change in the interaction energy of hACE2. S375F was found to be a mutation that majorly changed the binding affinity of the spike protein to hACE2 and the eight monoclonal antibodies. Our proposed analysis method enables the prediction of the binding affinity of new variants to hACE2 or to monoclonal antibodies in a shorter time compared to that utilized by the experimental method.

Modulating protein-protein interactions (PPIs) is an attractive strategy in drug discovery. Molecular glues, bifunctional small-molecule drugs that promote PPIs, offer an approach to targeting traditionally undruggable targets. However, the efficient discovery of molecular glues has been hampered by the current limitations of conventional ensemble-averaging-based methods. In this study, we present a YaxAB nanopore for probing the efficacy of molecular glues in inducing PPIs. Using YaxAB nanopores, we demonstrate single-molecule-based, label-free monitoring of protein complex formation between mammalian target of rapamycin (mTOR) and FK506-binding proteins (FKBPs) triggered by the molecular glue, rapamycin. Owing to its wide entrance and adjustable pore size, in combination with potent electro-osmotic flow (EOF), a single funnel-shaped YaxAB nanopore enables the simultaneous detection and single-molecule-level quantification of multiprotein states, including single proteins, binary complexes, and ternary complexes induced by rapamycin. Notably, YaxAB nanopores could sensitively discriminate between the binary complexes or ternary complexes induced by rapamycin and its analogues, despite the subtle size differences of ∼122 or ∼116 Da, respectively. Taken together, our results provide proof-of-concept for single-molecule-based, label-free, and ultrasensitive screening and structure-activity relationship (SAR) analysis of molecular glues, which will contribute to low-cost, highly efficient discovery, and rational design of bifunctional modality of drugs, such as molecular glues.

X-linked inhibitor of apoptosis protein (XIAP) is an important regulator of cancer cell survival whose BIR3 domain (XIAP-BIR3) recognizes the Smac N-terminal tetrapeptide sequence (AVPI), making it an attractive protein-protein interaction (PPI) target for cancer therapies. We used the fragment molecular orbital (FMO) method to study the binding modes and affinities between XIAP-BIR3 and a series of its inhibitors (1-8) that mimic the AVPI binding motif; the inhibitors had common interactions with key residues in a hot spot region of XIAP-BIR3 (P1-P4 subpockets) with increased binding affinity mainly attributed to specific interactions with the P1 and P4 subpockets. Based on the structural information from FMO results, we proposed a novel XIAP natural product inhibitor, neoeriocitrin 10, which was derived from our preciously reported XIAP-BIR3 inhibitor 9, can be used as a highly potent candidate for XIAP-BIR3 inhibition. We also performed pair interaction energy decomposition analysis to investigate the binding energies between specific binding residues and individual ligands, showing that the novel natural product neoeriocitrin 10 had a higher binding affinity than epicatechin gallate 9. Molecular docking and dynamics simulations were performed to explore the mode of binding between 10 and XIAP-BIR3, demonstrating that 10 binds more strongly to the P1 and P4 pockets than 9. Overall, we present a novel natural product, neoeriocitrin 10, and demonstrate that the FMO method can be used to identify hot spots in PPIs and design new compounds for XIAP inhibition.