Antibodies play a crucial role in defending the human body against diseases, including life-threatening conditions like cancer. They mediate immune responses against foreign antigens and, in some cases, self-antigens. Over time, antibody-based technologies have evolved from monoclonal antibodies (mAbs) to chimeric antigen receptor T cells (CAR-T cells), significantly impacting biotechnology, diagnostics, and therapeutics. Although these advancements have enhanced therapeutic interventions, the integration of artificial intelligence (AI) is revolutionizing antibody design and optimization. This review explores recent AI advancements, including large language models (LLMs), diffusion models, and generative AI-based applications, which have transformed antibody discovery by accelerating de novo generation, enhancing immune response precision, and optimizing therapeutic efficacy. Through advanced data analysis, AI enables the prediction and design of antibody sequences, 3D structures, complementarity-determining regions (CDRs), paratopes, epitopes, and antigen–antibody interactions. These AI-powered innovations address longstanding challenges in antibody development, significantly improving speed, specificity, and accuracy in therapeutic design. By integrating computational advancements with biomedical applications, AI is driving next-generation cancer therapies, transforming precision medicine, and enhancing patient outcomes. Graphical Abstract

Lymphatic filariasis (LF) caused by the vector borne parasitic nematode Wuchereria bancrofti is of major concern of the World Health Organization (WHO). Lack of potential drug candidates worsens the situation. Presently available drugs are promising in killing the microfilaria (mf) but are not effective as adulticidal therapeutics. Previous studies have revealed that routine administration of the available drugs (albendazole, ivermectin and albendazole) sometime is associated with severe adverse effects (SAEs) in co-infection state. Therefore, potential and safe therapeutics are still required. Earlier studies on filarial thioredoxin reductase (TrxR) have shown that successful inhibition of it can lead to apoptotic death of the parasites. TrxR in filarial parasites plays a significant role in disease progression and pathogenesis, hence efficient non-reversible inhibition of TrxR can be a good strategy to treat LF. In this research, inhibitory potential of Scytonemin, a cyanobacterial metabolite on filarial TrxR was evaluated via different in silico methods and validated through in vitro experiments. Parasite death upon exposure to Scytonemin can be correlated with the TrxR inhibiting capacity of the compound. Therefore, this cyanobacterial-derived compound may possibly be used further as novel and safe therapeutic candidate against filarial infection.

The infection caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) resulted in a pandemic with huge death toll and economic consequences. The virus attaches itself to the human epithelial cells through noncovalent bonding of its spike protein with the angiotensin-converting enzyme-2 (ACE2) receptor on the host cell. Based on in silico studies we hypothesized that perturbing the functionally active conformation of spike protein through the reduction of its solvent accessible disulfide bonds, thereby disintegrating its structural architecture, may be a feasible strategy to prevent infection by reducing the binding affinity towards ACE2 enzyme. Proteomics data showed that N-acetyl cysteine (NAC), an antioxidant and mucolytic agent been widely in use in clinical medicine, forms covalent conjugates with solvent accessible cysteine residues of spike protein that were disulfide bonded in the native state. Further, in silico analysis indicated that the presence of the selective covalent conjugation of NAC with Cys525 perturbed the stereo specific orientations of the interacting key residues of spike protein that resulted in threefold weakening in the binding affinity of spike protein with ACE2 receptor. Interestingly, almost all SARS-CoV-2 variants conserved cystine residues in the spike protein. Our finding results possibly provides a molecular basis for identifying NAC and/or its analogues for targeting Cys-525 of the viral spike protein as fusion inhibitor and exploring in vivo pharmaco-preventive and its therapeutic potential activity for COVID-19 disease. However, in-vitro assay and animal model-based experiment are required to validate the probable mechanism of action.Communicated by Ramaswamy H. Sarma.

The X-ray crystal structures of HDAC8 complexed with Largazole thiol (LAR, PubChem CID: 56663191) and its synthetic variants (Ligand ID in PDB, PubChem CID: L6G, 91667418; L7G, 91667421; L8G, 91667420) (PDB Codes: 3RQD, 4RN0, 4RN2 and 4RN1) were analysed using molecular dynamics simulations to comprehend protein-ligand non-bonding energies (NBEs). The NBEs of ligands’ substructures vis-à-vis active site indicated that pyridyl fragment (F2B4) in L7G and L8G, and amide fragment (F2B5) in LAR and L6G are in high energy states. Based on ligands’ substructures and active site residues properties new compounds were designed by introducing phenolic and amidine moieties, respectively, for F2B4 and F2B5. This improved NBEs of new compounds (NC2, -60.93 kcal/mol; NC3, -42.42 kcal/mol). Also, Zn²⁺ group (substructure F1) of largazoles was modified with that of SAHA and Trapoxin A. Here, the results indicated in favor of Zn²⁺ group of Trapoxin A. New compound NC6 incorporating aforesaid modifications i.e., phenolic moiety for F2B4, amidine moiety for F2B5 and Zn²⁺ group of Trapoxin A in F1, offered best interactions with HDAC8 (-89.75 kcal/mol). Thus, the study revealed new depsipeptides as potential HDAC8 inhibitors.

Designing an inhibitor having strong affinity in the active site pocket is the cherished goal of structure based drug designing. To achieve this, it is considerably important to predict which structural scaffold is better suited for change to increase affinity. We have explored five HDAC2 co-crystals having PDB ligand code—SHH (vorinostat), LLX, 20Y, IWX (BRD4884) and 6EZ (BRD7232). For analyzing protein-ligand interaction at an atomistic level, we have employed the NAMD molecular dynamics (MD) package. The obtained 100 ns long MD trajectories were subjected to quantitative estimations of non-bonding energies (NBEs) for inferring their interactions with the whole protein or its composite active site (CAS). In addition, relative ΔG_bind was calculated to rank the inhibitors. These inhibitors’ NBEs reveal that the phenyl moieties are the major structural scaffold where modifications should be attempted. We designed new compounds (NCs) via introducing hydroxyl groups at 4,5 position of the phenyl moiety of 6EZ, called NC1. Improvement in NC1 further encouraged us for CAP modification by isochromane and isoindoline moieties in place of oxabicyclooctane in NC1, resulting in NC2 and NC3. We also explored trifluoromethyl oxadiazole in 6EZ (NC4 and NC5) and SHH (NC6 and NC7). This moiety acts as a ZBG in NC4 while acting as a part of the foot-pocket in the rest. NC2 and NC6 have highest favorable NBEs among all studied ligands due increased favorable electrostatic contribution. We expect these NBEs data will provide atomistic level insights and benefit in designing new and improved HDAC2 inhibitors. Communicated by Ramaswamy H. Sarma