Protein Binding Sites Research Articles

PROTAC for agriculture: learning from human medicine to generate new biotechnological weed control solutions.

Weed control has relied on the use of organic and inorganic molecules that interfere with druggable targets, especially enzymes, for almost a century. This approach, although effective, has resulted in multiple cases of herbicide resistance. Furthermore, the rate of discovery of new druggable targets that are selective and with favorable environmental profiles has slowed down, highlighting the need for innovative control tools. The arrival of the biotechnology and genomics era gave hope to many that all sorts of new control tools would be developed. However, the reality is that most efforts have been limited to the development of transgenic crops with resistance to a few existing herbicides, which in fact is just another form of selectivity. Proteolysis-targeting chimera (PROTAC) is a new technology developed to treat human diseases but that has potential for multiple applications in agriculture. This technology uses a small bait molecule linked to an E3 ligand. The 3-dimensional structure of the bait favors physical interaction with a binding site in the target protein in a manner that allows E3 recruitment, ubiquitination and then proteasome-mediated degradation. This system makes it possible to circumvent the need to find druggable targets because it can degrade structural proteins, transporters, transcription factors, and enzymes without the need to interact with the active site. PROTAC can help control herbicide-resistant weeds as well as expand the number of biochemical targets that can be used for weed control. In the present article, we provide an overview of how PROTAC works and describe the possible applications for weed control as well as the challenges that this technology might face during development and implementation for field uses. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Multi-feature clustering of CTCF binding creates robustness for loop extrusion blocking and Topologically Associating Domain boundaries

Topologically Associating Domains (TADs) separate vertebrate genomes into insulated regulatory neighborhoods that focus genome-associated processes. TADs are formed by Cohesin-mediated loop extrusion, with many TAD boundaries consisting of clustered binding sites of the CTCF insulator protein. Here we determine how this clustering of CTCF binding contributes to the blocking of loop extrusion and the insulation between TADs. We identify enrichment of three features of CTCF binding at strong TAD boundaries, consisting of strongly bound and closely spaced CTCF binding peaks, with a further enrichment of DNA-binding motifs within these peaks. Using multi-contact Nano-C analysis in cells with normal and perturbed CTCF binding, we establish that individual CTCF binding sites contribute to the blocking of loop extrusion, but in an incomplete manner. When clustered, individual CTCF binding sites thus create a stepwise insulation between neighboring TADs. Based on these results, we propose a model whereby multiple instances of temporal loop extrusion blocking create strong insulation between TADs.

Effect of single nucleotide polymorphisms on the structure of long noncoding RNAs and their interaction with RNA binding proteins

Long non-coding RNAs (lncRNA) are emerging as a new class of regulatory RNAs with remarkable potential to be utilized as therapeutic targets against many human diseases. Several genome-wide association studies (GWAS) have catalogued Single Nucleotide Polymorphisms (SNPs) present in the noncoding regions of the genome from where lncRNAs originate. In this study, we have selected 67 lncRNAs with GWAS-tagged SNPs and have also investigated their role in affecting the local secondary structures. Majority of the SNPs lead to changes in the secondary structure of lncRNAs to a different extent by altering the base pairing patterns. These structural changes in lncRNA are also manifested in form of alteration in the binding site for RNA binding proteins (RBPs) along with affecting their binding efficacies. Ultimately, these structural modifications may influence the transcriptional and post-transcriptional pathways of these RNAs, leading to the causation of diseases. Hence, it is important to understand the possible underlying mechanism of RBPs in association with GWAS-tagged SNPs in human diseases.

Applications of Big Data and AI-Driven Technologies in CADD (Computer-Aided Drug Design).

In the field of computer-aided drug design (CADD), there has been dramatic progress in the development of big data and AI-driven methodologies. The expensive and time-consuming process of drug design is related to biomedical complexity. CADD can be used to apply effective and efficient strategies to overcome obstacles in the field of drug design in order to properly design and develop a new medicine. To prepare the raw data for consistent and repeatable applications of big data and AI methodologies, data pre-processing methods are introduced. Big data and AI technologies can be used to develop drugs in areas including predicting absorption, distribution, metabolism, excretion, and toxicity properties as well as finding binding sites in target proteins and conducting structure-based virtual screenings. The accurate and thorough analysis of large amounts of biomedical data as well as the design of prediction models in the area of drug design is made possible by data pre-processing and applications of big data and AI skills. In the biomedical big data era, knowledge on the biological, chemical, or pharmacological structures of biomedical entities relevant to drug design should be analyzed with significant big data and AI approaches.

AI-driven Discovery of Celecoxib and Dexamethasone for Exploring their Mode of Action as Human Interleukin (IL-6) Inhibitors to Treat COVID-19-induced Cytokine Storm in Humans.

In the case of COVID-19 patients, it has been observed that the immune system of the infected person exhibits an extreme inflammatory response known as cytokine release syndrome (CRS) where the inflammatory cytokines are swiftly produced in quite large amounts in response to infective stimuli. Numerous case studies of COVID-19 patients with severe symptoms have documented the presence of higher plasma concentrations of human interleukin-6 (IL-6), which suggests that IL-6 is a crucial factor in the pathophysiology of the disease. In order to prevent CRS in COVID-19 patients, the drugs that can exhibit binding interactions with IL-6 and block the signaling pathways to decrease the IL-6 activity may be repurposed. This research work focused on molecular docking-based screening of the drugs celecoxib (CXB) and dexamethasone (DME) to explore their potential to interact with the binding sites of IL-6 protein and reduce the hyper-activation of IL-6 in the infected personnel. Both of the drugs were observed to bind with the IL-6 (IL-6 receptor alpha chain) and IL-6Rα receptor with the respective affinities of -7.3 kcal/mol and -6.3 kcal/mol, respectively, for CXB and DME. Moreover, various types of binding interactions of the drugs with the target proteins were also observed in the docking studies. The dynamic behaviors of IL-6/IL-6Rα in complex with the drugs were also explored through molecular dynamics simulation analysis. The results indicated significant stabilities of the acquired drug-protein complexes up to 100 ns. The findings of this study have suggested the potential of the drugs studied to be utilized as antagonists for countering CRS in COVID-19 ailment. This study presents the studied drugs as promising candidates both for the clinical and pre-clinical treatment of COVID-19.

Synthesis, Cytotoxic Potential, and Molecular Docking Studies of Ortho-carboxamidostilbene Analogs

Abstract: A total of eleven ortho-carboxamidostilbene derivatives were synthesized through Heck coupling with a different type of amide derivatives. These compounds were characterized by FTIR, 1D- and 2D-NMR as well as mass spectroscopy analysis (HRESIMS). The synthesized compounds were tested for their cytotoxic potential against four human cancer cell lines (MCF-7, MDA-MB-231, MCF-7/TAMR-1, and A549), as well as two human normal cell lines (MCF-10A and BEAS-2B) using tamoxifen and cisplatin as a positive control. The active compound has proceeded with molecular docking on the colchicine binding site of tubulin protein using AutoDock Vina and Biovia Discovery Studio. Compounds 6a, 6d-6k exhibited selective cytotoxic activity against A549 cells rather than breast cancer cell lines. Compounds 6d, 6f, and 6g showed moderate cytotoxicity to A549 cells after 72 hours, with IC50 values of 10.4 μM, 6.47 μM, and 8.99 μM, respectively. Interestingly, these compounds had a high selective index (SI) value against A549 lung cancer cells, ranging from 8.87 to 15.4 μM. Molecular docking studies for compounds 6d, 6f, and 6g on the colchicine binding site of tubulin protein, α- and β-subunits were done to comprehend and research ligand-receptor interactions.

In silico Study of Alkaloid Compounds with Computational Approach for Selection of Drug Leads for COVID-19

Background: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virulent source of COVID-19 disease. As a result of the rapid transmission of the viral agent and deficiency of specific drugs against the virus, a worldwide pandemic ensued with a terrifying death toll. Thus there is tremendous urgency to discover substances for the development of specific COVID-19 drugs. With increasing public interest in natural products, this study aims to discover alkaloid compounds capable of inhibiting SARS-CoV-2 with the assistance of bioinformatics. Methods: In this work, 298 alkaloids with reported antiviral properties were identified, and their biological activities were validated with QSAR analysis using the Pass Online server until only 7 alkaloids remained. Molecular docking studies for these 7 alkaloids onto SARS-CoV-2 3CLpro, a protein involved in viral replication, were carried out with AutoDock Vina, followed by in silico visualization of the protein-alkaloid interaction with Ligplot+ program and prediction of ADME-Tox properties of the alkaloids using Toxtree program and SwissADME online server. Results: Fangchinoline, phenanthroindolizidine, and polyalthenol are predicted to have strong binding affinity with SARS-CoV-2 3CLpro. Visualization of the molecular interactions between the ligand and protein target, however, showed that homonojirimycin formed the most hydrogen bonds with the protein binding site. Most of the alkaloids have little to no violation of Lipinski’s Rule of 5, easy to moderate synthetic accessibility, and good pharmacokinetic properties. Conclusion: Fangchinoline, phenanthroindolizidine, and polyalthenol exhibited high binding affinity values to SARS-CoV-2 3CLpro, with polyalthenol predicted to possess the strongest binding interactions to the active site of the protein. Polyalthenol and phenanthroindolizidine confer the most versatility in terms of bioavailability, however, supplementary observation of phenanthroindolizidine for the prospect of mutagenicity is required before it can be recommended for further drug development

The binding profile of SARS-CoV-2 with human leukocyte antigen polymorphisms reveals critical alleles involved in immune evasion.

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), astonished the world and led to millions of deaths. Due to viral new mutations and immune evasion, SARS-CoV-2 ranked first in transmission and influence. The binding affinity of human leukocyte antigen (HLA) polymorphisms to SARS-CoV-2 might be related to immune escape, but the mechanisms remained unclear. In this study, we obtained the binding affinity of SARS-CoV-2 strains with different HLA proteins and identified 31 risk alleles. Subsequent structural predictions identified 10 active binding sites in these HLA proteins that may promote immune evasion. Particularly, we also found that the weak binding ability with HLA class I polymorphisms could contribute to the immune evasion of Omicron. These findings suggest important implications for preventing the immune evasion of SARS-CoV-2 and providing new insights for the vaccine design.

RefinePocket: An Attention-Enhanced and Mask-Guided Deep Learning Approach for Protein Binding Site Prediction.

Protein binding site prediction is an important prerequisite task of drug discovery and design. While binding sites are very small, irregular and varied in shape, making the prediction very challenging. Standard 3D U-Net has been adopted to predict binding sites but got stuck with unsatisfactory prediction results, incomplete, out-of-bounds, or even failed. The reason is that this scheme is less capable of extracting the chemical interactions of the entire region and hardly takes into account the difficulty of segmenting complex shapes. In this paper, we propose a refined U-Net architecture, called RefinePocket, consisting of an attention-enhanced encoder and a mask-guided decoder. During encoding, taking binding site proposal as input, we employ Dual Attention Block (DAB) hierarchically to capture rich global information, exploring residue relationship and chemical correlations in spatial and channel dimensions respectively. Then, based on the enhanced representation extracted by the encoder, we devise Refine Block (RB) in the decoder to enable self-guided refinement of uncertain regions gradually, resulting in more precise segmentation. Experiments show that DAB and RB complement and promote each other, making RefinePocket has an average improvement of 10.02% on DCC and 4.26% on DVO compared with the state-of-the-art method on four test sets.

Molecular Docking Study on Phytochemical Profiling of Trichosanthes Dioica (Pointed gourd) against Antitumor Evaluation as Cyclin Dependent Kinase -2(CDK2) inhibitors

Natural products in drug discovery have been extensively documented, including their subscription to the evolution of present drugs. Trichosanthes dioca, a group of family Cucurbitaceae, is an annual or perennial herb distributed in tropical Asia and Australia. Pointed gourd (Trichosanthes dioica Roxb.) is investigated by a common name of parwal and is cultivated predominantly as a vegetable. The remarkable medicinal properties are antihyperglycemic, antihyperlipidemic, antitumor, cytotoxic, arsenic poisoning, ameliorative, anti-inflammatory, antidiarrheal, and varieties of pharmacological activities of T. dioica. D.T. dioica root demonstrates remarkable cytotoxic and genotoxic properties thus suggesting the feasibility of its possible use as a natural antitumor agent. The 3D crystal structure of the protein 1KE9 (CYCLIN-DEPENDENT KINASE 2 (CDK2) was retrieved from Protein Data Bank (PDB) and protein binding sites of the compounds were identified. The 2D structure of Indian compounds of derivatives of glycosides and triterpenes was derived from the PubChem database. The present study analyzed the molecular docking studies on the protein which is responsible for anticancer with the compounds evolved from Trichosanthes dioca. The Docking was done by Schrodinger Maestro 12.4 software tool, compounds of colocynthin' derivatives of glycosides having better docking scores than the other compounds. So it has been concluded that derivatives of glycosides can be used as an anticancer drug.

Synthesis, in vitro Cytotoxicity Evaluation, and Docking Studies of Gloriosine Derivatives as Potential Anticancer Agents

AbstractIn the present work, series of C10‐amine and amide derivatives of gloriosine were synthesized and evaluated for in vitro cytotoxic activity against a panel of six human cancer cell lines (MDA‐MB‐231, U87, FaDu, SiHa, A549, and MCF‐7) of multiple tissue origin. The synthesized compounds were characterized by 1H and 13C NMR and MS experiments. In vitro cytotoxicity study showed that most of the C10‐amine derivatives demonstrated superior activity in two of the tested cell lines, namely U87 and FaDu cell lines, while C10‐amide derivatives showed poor activity in all the cell lines. The C10‐amine derivatives were subjected to molecular docking studies to explore their possible binding interactions with colchicine binding site of tubulin protein, and in‐silico ADME profiling to study the drug‐likeness. The C10‐amine derivatives may be less toxic than gloriosine towards normal cells and may provide the lead for anticancer drug development.

Utilizing hydrogen exchange measurements to drive small molecules into cryptic protein binding sites

Utilizing hydrogen exchange measurements to drive small molecules into cryptic protein binding sites

First identification of canine adenovirus 1 in mink and bioinformatics analysis of its 100 K protein.

Animal trade favors the spreading of emerging canine adenovirus 1 (CAdV-1) in mink. Because the 100K protein is not exposed to the viral surface at any stage, it can be used to differentiate the vaccine from wild virus infection. However, no related research has been conducted. This study aimed to find evidence of CAdV-1 in mink and predict the character of the 100K protein in the current circulating CAdV-1 strain of mink. In this experiment, the identification of CAdV-1, the phylogenetic tree, homology, and bioinformatics analysis of 100K were conducted. The results showed that the CAdV-1 was identified in the mink and that its Fiber was located in a separate branch. It was closely related to strains isolated from Norwegian Arctic fox and Red fox. 100K was located in a separate branch, which had the closest genetic relationship with skunks, porcupines, raccoons, and hedgehogs and a far genetic relationship with the strains in dogs. 100K protein is an unstable and hydrophobic protein. It had evidence of selective pressure and recombination, 1 glycosylation site, 48 phosphorylation sites, 60 dominant B cell epitopes, and 9 peptides of MHC-I and MHC-II. Its subcellular localization was mainly in the endoplasmic reticulum and mitochondria. The binding sites of 100K proteins were DBP proteins and 33K proteins. The stains in the mink were different from fox. The exploration of its genomic characteristics will provide us with a deeper understanding of the prevention of canine adenovirus.

Lipid composition modulates interactions of p7 viroporin during membrane insertion

Viral proteins interact with lipid membranes during various stages in the viral life cycle to propagate infection. p7 is an ion channel forming protein of Hepatitis C virus (HCV) that participates in viral assembly. Studies show that it has close ties to lipid metabolism in the cell and anionic phosphatidylserine (PS) lipids are suggested to be key for its permeabilizing function, but the mechanism of its interaction with the lipid environment is largely unknown. To begin unraveling the molecular processes of the protein, we evaluated the impact of lipid environment on the binding and insertion mechanism of p7 prior to channel formation and viral assembly using molecular dynamics simulations. It is seen that p7 is sensitive to its lipid environment and results in different remodeling patterns in membranes. Helix 1 (H1) is especially important for peptide insertion, with deeper entry taking place when the membrane contains phosphatidylserine (PS). Helix 2 (H2) and the adjacent loop connecting to Helix 3 (H3) prompts recruitment of phosphatidylethanolamine (PE) lipids to the protein binding site in membrane models with lower surface charge. This work provides perspectives on the interplay between protein-lipid dynamics and membrane composition, and insights on membrane reorganization in mechanisms of disease.

Identification of the Seaweed Metabolites as Potential Anti-tubercular Agents Against Human Pantothenate synthetase: An In Silico Approach.

Tuberculosis is the disease which is caused due to the contagion of Mycobacterium tuberculosis. The multidrug resistance Mycobacterium tuberculosis is the main hassle in the treatment of this worldwide health threats. Pantothenate synthase is a legitimate goal for rational drug designing against Mycobacterium tuberculosis. The enzyme is most active in the presence of magnesium or manganese. Marine algal cell wall is rich in sulfated polysaccharides such as fucoidans (brown algae), κ-carrageenans (red algae), and ulvan (green algae) with various favorable biological activities such as anticoagulant, antiviral, antioxidative, anticancer, and immunomodulating activities. In this study, we have modeled binding modes of selected known anti-tubercular compounds and different solvent extract against pantothenate synthase using advanced docking program AutoDock 4.2 tool. In our current study, in silico experiments were carried out to determine if fucoidan, κ-carrageenan, and ulvan sulfated polysaccharides could be a potential target against PANc (pantothenate synthetase), with the goal of identifying potential inhibitors as anti-TB leads targeting PANc for further wet lab validation. Two bioactive compounds were docked to the Mtb pantothenate synthetase protein binding site, with docking scores ranging from -5.57 to -2.73. κ-carrageenan had the best pose and docking score, with a Ligand fit score of -5.815. Ulvan did not dock with the protein. The molecular dynamics simulations were conducted with substrate and ligand bounded fucoidan and κ-carrageenan for 150ns and the protein Mtb pantothenate synthetase showed a stable conformation in the simulation, with tight amino acid contributions binding to the ligand molecule. RMSD characterizes the conformation and stability of protein ligand complexes, with higher fluctuations indicating low stability and minimal low-level fluctuations indicating equilibration and stability. The graph for RMSF shows significant peaks due to fluctuations in active site regions and other peaks indicating the adaptation of the ligand molecule to the protein binding pocket. From the molecular dynamics study, it is clear that the compounds are having good binding affinity in the active site. The root mean square deviation, root mean square fluctuations, and radius of gyration are supportive evidences which helped us to conclude that the compounds κ-carrageenan and fucoidan are suitable lead molecules for inhibiting pantothenate synthetase. Based on these evidences, the natural compounds from seaweeds can be tested clinically either alone or in combinations against the protein, which could facilitate the designing or the synthesis of new lead molecules as drugs against the tuberculosis.

Structural Modifications and Novel Protein-Binding Sites in Pre-miR-675-Explaining Its Regulatory Mechanism in Carcinogenesis.

Pre-miR-675 is a microRNA expressed from the exon 1 of H19 long noncoding RNA, and the atypical expression of pre-miR-675 has been linked with several diseases and disorders including cancer. To execute its function inside the cell, pre-miR-675 is folded into a particular conformation, which aids in its interaction with several other biological molecules. However, the exact folding dynamics of pre-miR-675 and its protein-binding motifs are currently unknown. Moreover, how H19 lncRNA and pre-miR-675 crosstalk and modulate each other's activities is also unclear. The detailed structural analysis of pre-miR-675 in this study determines its earlier unknown conformation and identifies novel protein-binding sites on pre-miR-675, thus making it an excellent therapeutic target against cancer. Co-folding analysis between H19 lncRNA and pre-miR-675 determine structural transformations in pre-miR-675, thus describing the earlier unknown mechanism of interaction between these two molecules. Comprehensively, this study details the conformation of pre-miR-675 and its protein-binding sites and explains its relationship with H19 lncRNA, which can be interpreted to understand the role of pre-miR-675 in the development and progression of tumorigenesis and designing new therapeutics against cancers.

Molecular investigation of TSHR gene in Bangladeshi congenital hypothyroid patients.

The disorder of thyroid gland development or thyroid dysgenesis accounts for 80-85% of congenital hypothyroidism (CH) cases. Mutations in the TSHR gene are mostly associated with thyroid dysgenesis, and prevent or disrupt normal development of the gland. There is limited data available on the genetic spectrum of congenital hypothyroid children in Bangladesh. Thus, an understanding of the molecular aetiology of thyroid dysgenesis is a prerequisite. The aim of the study was to investigate the effect of mutations in the TSHR gene on the small molecule thyrogenic drug-binding site of the protein. We identified two nonsynonymous mutations (p.Ser508Leu, p.Glu727Asp) in the exon 10 of the TSHR gene in 21 patients with dysgenesis by sequencing-based analysis. Later, the TSHR368-764 protein was modeled by the I-TASSER server for wild-type and mutant structures. The model proteins were targeted by thyrogenic drugs, MS437 and MS438 to perceive the effect of mutations. The damaging effect in drug-protein complexes of mutants was explored by molecular docking and molecular dynamics simulations. The binding affinity of wild-type protein was much higher than the mutant cases for both of the drug ligands (MS437 and MS438). Molecular dynamics simulates the dynamic behavior of wild-type and mutant complexes. MS437-TSHR368-764MT2 and MS438-TSHR368-764MT1 showed stable conformations in biological environments. Finally, Principle Component Analysis revealed structural and energy profile discrepancies. TSHR368-764MT1 exhibited much more variations than TSHR368-764WT and TSHR368-764MT2, emphasizing a more damaging pattern in TSHR368-764MT1. This genetic study might be helpful to explore the mutational impact on drug binding sites of TSHR protein which is important for future drug design and selection for the treatment of congenital hypothyroid children with dysgenesis.

Base Dynamics in the HhaI Protein Binding Site.

Protein-DNA interactions play an important role in numerous biological functions within the living cell. In many of these interactions, the DNA helix is significantly distorted upon protein-DNA complex formation. The HhaI restriction-modification system is one such system, where the methylation target is flipped out of the helix when bound to the methyltransferase. However, the base flipping mechanism is not well understood. The dynamics of the binding site of the HhaI methyltransferase and endonuclease (underlined) within the DNA oligomer [d(G1A2T3A4G5C6G7C8T9A10T11C12)]2 are studied using deuterium solid-state NMR (SSNMR). SSNMR spectra obtained from DNAs deuterated on the base of nucleotides within and flanking the [5'-GCGC-3']2 sequence indicate that all of these positions are structurally flexible. Previously, conformational flexibility within the phosphodiester backbone and furanose ring within the target sequence has been observed and hypothesized to play a role in the distortion mechanism. However, whether that distortion was occurring through an active or passive mechanism remained unclear. These NMR data demonstrate that although the [5'-GCGC-3']2 sequence is dynamic, the target cytosine is not passively flipping out of the double-helix on the millisecond-picosecond time scale. Additionally, although previous studies have shown that both the furanose ring and phosphodiester backbone experience a change in dynamics upon methylation, which may play a role in recognition and cleavage by the endonuclease, our observations here indicate that methylation has no effect on the dynamics of the base itself.

Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach.

In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS H2O (MD) methodology, for the identification of conserved water molecules. Our method uses experimental structures of proteins homologous to a query, which are subsequently superimposed upon it. Areas with a particular species present in a similar location among many homologous protein structures are identified using a clustering algorithm. Dense clusters likely represent positions containing species important to the query protein structure or function. We analyze well-characterized apo protein structures and show that the MADE approach can identify clusters corresponding to the expected positions of metal ions in their binding sites. The greatest advantage of our method lies in its generality. It can in principle be applied to any species found in protein records; it is not only limited to metal ions. We additionally demonstrate that the MADE approach can be successfully applied to predict the location of cofactors in computer-modeled structures, e.g., via AlphaFold. We also conduct a careful protein superposition method comparison and find our methodology robust and the results largely independent of the selected protein superposition algorithm. We postulate that with increasing structural data availability, additional applications of the MADE approach will be possible such as non-protein systems, water network identification, protein binding site elaboration, and analysis of binding events, all in a dynamic manner. We have implemented the MADE approach as a plugin for the PyMOL molecular visualization tool. The MADE plugin is available free of charge at https://gitlab.com/Jukic/made_software.

DOX_BDW: Incorporating Solvation and Desolvation Effects of Cavity Water into Nonfitting Protein-Ligand Binding Affinity Prediction.

Accurate prediction of the protein-ligand binding affinity (PLBA) with an affordable cost is one of the ultimate goals in the field of structure-based drug design (SBDD), as well as a great challenge in the computational and theoretical chemistry. Herein, we have systematically addressed the complicated solvation and desolvation effects on the PLBA brought by the difference of the explicit water in the protein cavity before and after ligands bind to the protein-binding site. Based on the new solvation model, a nonfitting method at the first-principles level for the PLBA prediction was developed by taking the bridging and displaced water (BDW) molecules into account simultaneously. The newly developed method, DOX_BDW, was validated against a total of 765 noncovalent and covalent protein-ligand binding pairs, including the CASF2016 core set, Cov_2022 covalent binding testing set, and six testing sets for the hit and lead compound optimization (HLO) simulation. In all of the testing sets, the DOX_BDW method was able to produce PLBA predictions that were strongly correlated with the corresponding experimental data (R = 0.66-0.85). The overall performance of DOX_BDW is better than the current empirical scoring functions that are heavily parameterized. DOX_BDW is particularly outstanding for the covalent binding situation, implying the need for considering an electronic structure in covalent drug design. Furthermore, the method is especially recommended to be used in the HLO scenario of SBDD, where hundreds of similar derivatives need to be screened and refined. The computational cost of DOX_BDW is affordable, and its accuracy is remarkable.